Document ID: EPA-HQ-OAR-2002-0060-0636
Agency: epa
Document Type: Supporting & Related Material
Title: 
Posted Date: 2003-08-29T04:00Z

Economic
Impact
Analysis
of
the
Final
Stationary
Combustion
Turbines
NESHAP:
Final
Report
EPA­
452/
R­
03­
014
August
2003
Economic
Impact
Analysis
of
the
Final
Stationary
Combustion
Turbines
NESHAP
By:

RTI
International*
Health,
Social,
and
Economics
Research
Research
Triangle
Park,
North
Carolina
27709
Prepared
for:

U.
S.
Environmental
Protection
Agency
Office
of
Air
Quality
Planning
and
Standards
Innovative
Strategies
and
Economics
Group,
C339­
01
Research
Triangle
Park,
NC
27711
*
RTI
International
is
a
trade
name
of
Research
Triangle
Institute.
This
report
has
been
reviewed
by
the
Emission
Standards
Division
of
the
Office
of
Air
Quality
Planning
and
Standards
of
the
United
States
Environmental
Protection
Agency
and
approved
for
publication.
Mention
of
trade
names
or
commercial
products
is
not
intended
to
constitute
endorsement
or
recommendation
for
use.
Copies
of
this
report
are
available
through
the
Library
Services
(
MD­
35),
U.
S.
Environmental
Protection
Agency,
Research
Triangle
Park,
NC
27711,
or
from
the
National
Technical
Information
Services
5285
Port
Royal
Road,
Springfield,
VA
22161.
iii
TABLE
OF
CONTENTS
Section
Page
1
Introduction
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1­
1
1.1
Agency
Requirements
for
an
EIA
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1­
1
1.2
Scope
and
Purpose
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1­
2
1.3
Organization
of
the
Report
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1­
2
2
Combustion
Turbine
Technologies
and
Costs
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2­
1
2.1
Simple­
Cycle
Combustion
Turbine
Technologies
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2­
1
2.2
Combined­
Cycle
Combustion
Turbine
Technologies
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2­
2
2.3
Capital
and
Installation
Costs
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2­
4
2.4
O&
M
Costs
Including
Fuel
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2­
5
3
Background
on
Health
Affects
and
Regulatory
Alternatives
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3­
1
3.1.
Background
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3­
1
3.1.1
Criteria
Used
in
NESHAP
Development
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3­
1
3.2
Health
Effects
Associated
with
HAPs
from
Stationary
Combustion
Turbines
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3­
2
3.3
Summary
of
the
Rule
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3­
3
3.3.1
Source
Categories
and
Subcategories
Affected
by
the
Rule
.
.
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3­
4
3.3.2
Emission
Limitations
and
Operating
Limitations
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3­
6
3.3.3
Initial
Compliance
Requirements
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3­
7
3.3.4
Continuous
Compliance
Provisions
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3­
8
3.3.5
Notification,
Record­
keeping,
and
Reporting
Requirements
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3­
9
3.4
Rationale
for
Selecting
Standards
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3­
10
3.4.1
Selection
of
Source
Categories
and
Subcategories
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3­
10
iv
3.4.2
Determination
of
Basis
and
Level
of
Emission
Limitations
for
Existing
Sources
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3­
13
3.4.2.1
MACT
Floor
for
Existing
Lean
Premix
Combustion
Turbines
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3­
13
3.4.2.2
MACT
for
Existing
Lean
Premix
Combustion
Turbines
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3­
15
3.4.2.3
MACT
Floor
for
Existing
Diffusion
Flame
Combustion
Turbines
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3­
15
3.4.2.4
MACT
for
Existing
Diffusion
Flame
Combustion
Turbines
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3­
17
3.4.3
New
Sources
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3­
17
3.4.3.1
New
Lean
Premix
Gas­
Fired
Combustion
Turbines
.
3­
18
3.4.3.2
New
Lean
Premix
Oil­
Fired
Combustion
Turbines
.
3­
19
3.4.3.3
New
Diffusion
Flame
Gas­
Fired
Combustion
Turbines
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3­
20
3.4.3.4
New
Diffusion
Flame
Oil­
Fired
Combustion
Turbines
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3­
21
3.4.4
MACT
for
Other
Subcategories
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3­
22
3.4.5
Selection
of
Initial
Compliance
Requirements
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3­
24
3.4.5.1
How
Did
We
Select
the
Continuous
Compliance
Requirements?
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3­
24
3.4.5.2
How
Did
We
Select
the
Testing
Methods
to
Measure
these
Low
Concentrations
of
Formaldehyde?
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3­
25
4
Projection
of
Units
and
Facilities
in
Affected
Sectors
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4­
1
4.1
Profile
of
Existing
Combustion
Turbine
Units
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4­
1
4.1.1
Distribution
of
Units
and
Facilities
by
Industry
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4­
2
4.1.2
Technical
Characteristics
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4­
2
4.2
Projected
Growth
of
Combustion
Turbines
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4­
5
4.2.1
Comparison
of
Alternative
Growth
Estimates
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4­
5
4.3
Number
of
Affected
Stationary
Combustion
Turbines
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4­
7
4.4
HAP
and
Other
Emission
Reductions
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4­
8
4.5
Energy
and
Other
Impacts
from
Direct
Application
of
Control
Measures
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4­
9
4.5.1
Water
Impacts
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4­
9
4.5.2
Solid
Waste
Impacts
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4­
10
v
4.6
Trends
in
the
Electric
Utility
Industry
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4­
10
5
Profiles
of
Affected
Industries
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5­
1
5.1
Electric
Utility
Industry
(
NAICS
22111)
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5­
1
5.1.1
Market
Structure
of
the
Electric
Power
Industry
.
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5­
1
5.1.1.1
The
Evolution
of
the
Electric
Power
Industry
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5­
2
5.1.1.2
Structure
of
the
Traditional
Regulated
Utility
.
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5­
3
5.1.1.3
Current
Electric
Power
Supply
Chain
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5­
6
5.1.1.4
Overview
of
Deregulation
and
the
Potential
Future
Structure
of
the
Electricity
Market
.
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5­
14
5.1.2
Electricity
Generation
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5­
16
5.1.2.1
Growth
in
Generation
Capacity
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5­
19
5.1.3
Electricity
Consumption
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5­
22
5.2
Oil
and
Gas
Extraction
(
NAICS
211)
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5­
23
5.2.1
Introduction
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5­
24
5.2.2
Supply
Side
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5­
27
5.2.2.1
Production
Processes
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5­
27
5.2.2.2
Types
of
Output
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5­
28
5.2.2.3
Major
By­
products
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5­
30
5.2.2.4
Costs
of
Production
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5­
30
5.2.2.5
Capacity
Utilization
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5­
31
5.2.3
Demand
Side
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5­
32
5.2.4
Organization
of
the
Industry
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5­
33
5.2.5
Markets
and
Trends
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5­
36
5.3
Natural
Gas
Pipelines
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5­
37
5.3.1
Introduction
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5­
37
5.3.2
Supply
Side
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.
5­
39
5.3.2.1
Service
Description
.
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.
5­
39
5.3.2.2
By­
products
.
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.
5­
40
5.3.2.3
Costs
of
Production
.
.
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.
5­
40
5.3.2.4
Capacity
Utilization
.
.
.
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.
5­
40
5.3.3
Demand
Side
.
.
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.
5­
42
5.3.4
Organization
of
the
Industry
.
.
.
.
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.
.
5­
43
5.3.5
Markets
and
Trends
.
.
.
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.
5­
43
vi
6
Economic
Analysis
Methods
.
.
.
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.
.
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
.
.
.
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.
.
6­
2
6.2.2
Modeling
Dimension
2:
Interaction
Between
Economic
Sectors
.
.
.
.
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.
.
.
6­
3
6.3
Selected
Modeling
Approach
Used
for
Combustion
Turbine
Analysis
.
.
.
.
.
.
.
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.
.
6­
4
6.3.1
Electricity
Markets
.
.
.
.
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.
.
6­
7
6.3.2
Other
Energy
Markets
.
.
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.
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.
.
.
.
6­
7
6.3.3
Supply
and
Demand
Elasticities
for
Energy
Markets
.
.
.
.
.
.
.
.
6­
8
6.3.4
Final
Product
and
Service
Markets
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
10
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
7
Economic
Impact
Analysis
.
.
.
.
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.
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.
.
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.
.
.
.
7­
1
7.1
Engineering
Control
Cost
Inputs
.
.
.
.
.
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.
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.
.
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.
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.
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.
.
.
.
.
.
.
.
7­
1
7.1.1
Computing
Supply
Shifts
in
the
Electricity
Market
.
.
.
.
.
.
.
.
.
.
7­
2
7.2
Market­
Level
Results
.
.
.
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.
.
7­
3
7.3
Social
Cost
Estimates
.
.
.
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.
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.
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.
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.
.
.
7­
6
7.4
Executive
Order
13211
(
Energy
Effects)
.
.
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.
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.
.
.
.
7­
7
8
Small
Entity
Impacts
.
.
.
.
.
.
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.
.
.
.
8­
1
8.1
Identifying
Small
Businesses
.
.
.
.
.
.
.
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.
.
8­
2
8.2
Screening­
Level
Analysis
.
.
.
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.
.
8­
2
8.3
Assessment
.
.
.
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.
8­
3
vii
References
.
.
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.
.
.
R­
1
Appendix
A
Overview
of
the
Market
Model
.
.
.
.
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.
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.
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.
.
.
A­
1
Appendix
B
Assumptions
and
Sensitivity
Analysis
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
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.
.
.
.
.
.
.
.
B­
1
viii
LIST
OF
FIGURES
Number
Page
2­
1
Simple­
Cycle
Gas
Turbine
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
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.
.
.
2­
2
2­
2
Combined­
Cycle
Gas
Turbine
.
.
.
.
.
.
.
.
.
.
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.
.
.
.
.
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.
.
.
.
.
.
.
2­
3
4­
1
Number
of
Units
by
MW
Capacity
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
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.
.
.
.
.
.
.
.
.
.
4­
4
4­
2
Number
of
Units
by
Annual
MWh
Output
Equivalent
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
4­
6
4­
3
Number
of
Units
by
Annual
Hours
of
Operation
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
4­
6
5­
1
Traditional
Electric
Power
Industry
Structure
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
4
5­
2
Electric
Utility
Industry
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
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.
.
.
.
.
.
.
.
.
.
5­
8
5­
3
Utility
and
Nonutility
Generation
and
Shares
by
Class,
1988
and
1998
.
.
.
.
.
5­
10
5­
4
Annual
Electricity
Sales
by
Sector
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
19
6­
1
Links
Between
Energy
and
Final
Product
Markets
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
6
6­
2
Electricity
Market
.
.
.
.
.
.
.
.
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.
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.
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.
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.
.
.
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.
.
.
.
.
.
.
6­
8
6­
3
Potential
Market
Effects
of
the
Proposed
MACT
on
Petroleum,
Natural
Gas,
or
Coal
.
.
.
.
.
.
.
.
.
.
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.
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.
.
.
.
.
.
6­
9
6­
4
Fuel
Market
Interactions
with
Facility­
Level
Production
Decisions
.
.
.
.
.
.
.
.
6­
11
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
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
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.
.
.
.
.
.
.
.
.
.
7­
4
ix
LIST
OF
TABLES
Number
Page
2­
1
Comparison
of
Emissions
from
Coal­
Fired
and
Simple­
Cycle
Turbines
and
Combined­
Cycle
Turbines
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
2­
4
2­
2
Overall
Installation
Costs
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
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.
.
.
.
.
.
.
.
.
.
.
.
.
2­
5
2­
3
Comparison
of
Percentage
of
Costs
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
2­
6
4­
1
Facilities
With
Units
Having
Capacities
Above
1
MW
by
Industry
Grouping
and
Government
Sector
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
4­
3
4­
2
Stationary
Combustion
Turbine
Projections
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
4­
4
4­
3
Planned
Capacity
Additions
at
U.
S.
Public
Utilities,
1998
through
2007,
as
of
January
1,
1998
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
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.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
4­
7
5­
1
Total
Expenditures
in
1996
($
103)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
7
5­
2
Number
of
Electricity
Suppliers
in
1999
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
9
5­
3
Top
Power
Marketing
Companies,
First
Quarter
1999
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
13
5­
4
Industry
Capability
by
Energy
Source,
2000
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
17
5­
5
Installed
Capacity
at
U.
S.
Nonutility
Attributed
to
Major
Industry
Groups
and
Census
Division,
1995
through
1999
(
MW)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
17
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
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
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.
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.
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.
.
.
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.
.
.
.
.
.
.
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
.
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.
5­
22
5­
10
U.
S.
Electric
Utility
Retail
Sales
of
Electricity
by
Sector,
1989
Through
July
1999
(
Million
kWh)
.
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.
5­
23
5­
11
Crude
Petroleum
and
Natural
Gas
Industries
Likely
to
Be
Affected
by
the
Regulation
.
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.
5­
25
5­
12
Summary
Statistics,
Crude
Oil
and
Natural
Gas
Extraction
and
Related
Industries
.
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.
5­
26
5­
13
U.
S.
Supply
of
Crude
Oil
and
Petroleum
Products
(
103
barrels),
1998
.
.
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.
5­
29
5­
14
U.
S.
Natural
Gas
Production,
1998
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.
5­
30
x
5­
15
Costs
of
Production,
Crude
Oil
and
Natural
Gas
Extraction
and
Related
Industries
.
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.
5­
31
5­
16
Estimated
U.
S.
Oil
and
Gas
Reserves,
Annual
Production,
and
Imports,
1998
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.
5­
32
5­
17
Size
of
Establishments
and
Value
of
Shipments,
Crude
Oil
and
Natural
Gas
Extraction
Industry
(
NAICS
211111),
1997
and
1992
.
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.
5­
34
5­
18
Size
of
Establishments
and
Value
of
Shipments,
Natural
Gas
Liquids
Industry
(
NAICS
211112),
1997
and
1992
.
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.
5­
35
5­
19
Size
of
Establishments
and
Value
of
Shipments,
Drilling
Oil
and
Gas
Wells
Industry
(
NAICS
213111),
1997
and
1992
.
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.
.
5­
36
5­
20
Size
of
Establishments
and
Value
of
Shipments,
Oil
and
Gas
Field
Services
(
NAICS
213112),
1997
and
1992
.
.
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.
.
5­
37
5­
21
Summary
Statistics
for
the
Natural
Gas
Pipeline
Industry
(
NAICS
4862),
1997
.
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.
5­
38
5­
22
Summary
Profile
of
Completed
and
Proposed
Natural
Gas
Pipeline
Projects,
1996
to
2000
.
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.
5­
41
5­
23
Energy
Usage
and
Cost
of
Fuel,
1994­
1998
.
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.
.
5­
42
5­
24
Transmission
Pipeline
Capacity,
Average
Daily
Flows,
and
Usage
Rates,
1990
and
1997
.
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.
.
5­
42
5­
25
Five
Largest
Natural
Gas
Pipeline
Companies
by
System
Mileage,
2000
.
.
.
.
5­
44
6­
1
Comparison
of
Modeling
Approaches
.
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6­
3
6­
2
Supply
and
Demand
Elasticities
.
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.
6­
10
6­
3
Fuel
Price
Elasticities
.
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.
6­
12
6­
4
Supply
and
Demand
Elasticities
for
Industrial
and
Commercial
Sectors
.
.
.
.
.
6­
14
7­
1
Engineering
Cost
Analysis
for
the
Stationary
Combustion
Turbine
MACT
Standard
.
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.
7­
2
7­
2
Summary
of
Turbine
Cost
Information
and
Supply
Shifts
.
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.
.
7­
3
7­
3
Market­
Level
Impacts
of
Stationary
Combustion
Turbines
MACT
Standard:
2005
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.
7­
5
7­
4
Changes
in
Market
Share
for
Electricity
Suppliers
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.
7­
6
7­
5
Distribution
of
Social
Costs
of
Stationary
Combustion
Turbines
MACT
Standard:
2005
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.
7­
8
8­
1
Number
of
Units
Greater
than
1
MW
at
Small
Parents
by
Industry
.
.
.
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.
.
.
.
8­
4
8­
2
Summary
Statistics
for
SBREFA
Screening
Analysis:
Recommended
Alternative
.
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8­
5
xi
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
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
xii
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
112
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
hazardous
air
pollutants
(
HAPs)
generated
by
the
combustion
of
fossil
fuels
in
combustion
turbines.
The
primary
HAPs
emitted
by
turbines
include
formaldehyde,
acetaldehyde,
toluene,
and
benzene.
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
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
112
of
the
CAA
Amendments
of
1990
establishes
the
authority
to
set
national
emissions
standards
for
HAPs.
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
HAPs
into
the
atmosphere.

To
reduce
emissions
of
HAPs,
the
Agency
establishes
maximum
achievable
control
technology
(
MACT)
standards.
The
term
"
MACT
floor"
refers
to
the
minimum
control
technology
on
which
MACT
standards
can
be
based.
For
existing
major
sources,
the
MACT
floor
is
the
average
emissions
limitation
achieved
by
the
best
performing
12
percent
of
sources
(
if
there
are
30
or
more
sources
in
the
category
or
subcategory).
For
new
sources,
the
MACT
floor
must
be
no
less
stringent
than
the
emissions
control
achieved
in
practice
by
the
best
controlled
similar
source.
The
MACT
can
also
be
chosen
to
be
more
stringent
than
the
floor,
considering
the
costs
and
the
health
and
environmental
impacts.
Emissions
reductions
and
the
costs
associated
with
the
regulation
are
based
primarily
on
the
installation
of
an
oxidation
catalyst
emission
control
device,
such
as
a
carbon
monoxide
(
CO)
oxidation
catalyst.
These
control
devices
are
used
to
reduce
CO
emissions
and
are
currently
installed
on
several
stationary
combustion
turbines.
In
addition,
performance
testing
is
required
of
all
affected
stationary
combustion
turbines.

The
regulation
affects
new
stationary
combustion
turbines
over
1
megawatt
(
MW).
This
analysis
uses
data
from
EPA's
Inventory
Database
V.
4
 
Turbines
(
referred
to
as
the
Inventory
Database).
To
estimate
the
economic
impacts
associated
with
the
regulation,
new
stationary
combustion
turbines
are
projected
through
the
year
2005.

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:


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).


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
HAPs
emitted
by
combustion
turbines.
1­
3

Section
4
provides
projections
of
new
stationary
combustion
turbines
through
the
year
2005.
This
section
also
profiles
the
population
of
existing
turbines.


Section
5
profiles
the
electric
service
industry
(
NAICS
221),
oil
and
gas
extraction
industry
(
NAICS
211),
and
the
natural
gas
pipeline
industry
(
NAICS
486).


Section
6
presents
the
methodology
for
assessing
the
economic
impacts
of
the
NESHAP
and
describes
the
computerized
market
model
used
to
estimate
the
social
cost
impacts
and
to
dissagregate
impacts
into
changes
in
producer
and
consumer
surplus.


Section
7
presents
the
economic
impact
estimates
for
the
NESHAP
and
describes
the
control
alternatives
used
to
estimate
the
impacts.
This
section
also
discusses
the
regulation's
impact
on
energy
supply,
distribution,
and
use.


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
NESHAP.
Appendix
B
describes
the
limitations
of
the
data
and
market
model
and
presents
sensitivity
analyses
associated
with
key
assumptions.
1Combustion
turbine
technology
used
for
aircraft
engines
is
virtually
the
same
except
the
energy
is
used
to
generate
thrust.

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.
1
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
2Spinning
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
2
as
spinning
reserves
or
black­
start
back­
up
capacity.
2
The
disadvantage
of
simple­
cycle
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
Compressor
Turbine
Combustion
Chamber
Fuel
Air
Fuel
Compressor
Turbine
Shaft
Work
Output
Exhaust
Gas
Turbines
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
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.

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
Combustion
Gases
300­
400
°
F
Emissions
Steam
Generator
Steam
Turbine
Steam
Electric
Generator
Shaft
Combined
Cycle
Gas
Turbine
Fuel
Air
Electric
Generator
Shaft
Combustion
Gases
900­
1000
°
F
Figure
2­
2.
Combined­
Cycle
Gas
Turbine
Source:
Siemens
Westinghouse.
August
31,
1999.
Presentation.
2­
4
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
NO
x
emissions
by
14
percent
over
simple­
cycle
combustion
turbines
and
89
percent
over
existing
coal
electricity
generation
plants.
In
addition,
CO
2
emissions
will
be
5
percent
lower
than
emissions
from
SCCTs
and
64
percent
lower
than
existing
coal
plants.

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
Table
2­
1.
Comparison
of
Emissions
from
Coal­
Fired
and
Simple­
Cycle
Turbines
and
Combined­
Cycle
Turbines
NO
x
(
lb/
MW­
hr)
CO
2
(
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
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
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
turbines.
Table
2­
3
compares
the
percentage
of
costs
spent
on
annualized
capital,
operation
and
maintenance,
and
fuel
for
both
simple
turbines
and
CCCTs.

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
(
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).
Table
2­
3.
Comparison
of
Percentage
of
Costsa
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.
3­
1
SECTION
3
BACKGROUND
ON
HEALTH
AFFECTS
AND
REGULATORY
ALTERNATIVES
3.1
Background
Section
112
of
the
CAA
requires
EPA
to
list
categories
and
subcategories
of
major
sources
and
area
sources
of
HAPs
and
to
establish
NESHAPs
for
the
listed
source
categories
and
subcategories.
The
stationary
turbine
source
category
was
listed
on
July
16,
1992
(
57
FR
31576).
Major
sources
of
HAPs
are
those
that
have
the
potential
to
emit
greater
than
10
ton/
yr
of
any
one
HAP
or
25
ton/
yr
of
any
combination
of
HAPs.

3.1.1
Criteria
Used
in
NESHAP
Development
Section
112
of
the
CAA
requires
that
we
establish
NESHAPs
for
controlling
HAPs
from
both
new
and
existing
major
sources.
The
CAA
requires
the
NESHAP
to
reflect
the
maximum
degree
of
reduction
in
emissions
of
HAPs
that
is
achievable.
This
level
of
control
is
commonly
referred
to
as
the
MACT.

The
MACT
floor
is
the
minimum
control
level
allowed
for
a
NESHAP
and
is
defined
under
section
112(
d)(
3)
of
the
CAA.
In
essence,
the
MACT
floor
ensures
that
the
standard
is
set
at
a
level
that
assures
that
all
major
sources
achieve
the
level
of
control
at
least
as
stringent
as
that
already
achieved
by
the
better
controlled
and
lower
emitting
sources
in
each
source
category
or
subcategory.
For
new
sources,
the
MACT
standards
cannot
be
less
stringent
than
the
emission
control
that
is
achieved
in
practice
by
the
best
controlled
similar
source.
The
MACT
standards
for
existing
sources
can
be
less
stringent
than
standards
for
new
sources,
but
they
cannot
be
less
stringent
than
the
average
emission
limitation
achieved
by
the
best
performing
12
percent
of
existing
sources
in
the
category
or
subcategory
(
or
the
best
performing
five
sources
for
categories
or
subcategories
with
fewer
than
30
sources).

In
developing
MACT,
we
also
consider
control
options
that
are
more
stringent
than
the
floor.
We
may
establish
standards
more
stringent
than
the
floor
based
on
the
consideration
of
cost
of
achieving
the
emissions
reductions,
any
nonair
quality
health
and
environmental
impacts,
and
energy
requirements.

Discussion
of
the
costs
and
other
impacts
associated
with
the
MACT
floor
and
other
alternatives
can
be
found
in
Section
4.
3­
2
3.2
Health
Effects
Associated
with
HAPs
from
Stationary
Combustion
Turbines
Several
HAPs
are
emitted
from
stationary
combustion
turbines.
These
HAP
emissions
are
formed
during
combustion
or
result
from
HAP
compounds
contained
in
the
fuel
burned.

Among
the
HAPs
that
have
been
measured
in
emission
tests
that
were
conducted
at
natural
gas­
fired
and
distillate
oil­
fired
combustion
turbines
are
1,3
butadiene,
acetaldehyde,
acrolein,
benzene,
ethylbenzene,
formaldehyde,
naphthalene,
poly
aromatic
hydrocarbons
(
PAH),
propylene
oxide,
toluene,
and
xylenes.
Metallic
HAPs
from
distillate
oil­
fired
stationary
combustion
turbines
that
have
been
measured
are
arsenic,
beryllium,
cadmium,
chromium,
lead,
manganese,
mercury,
nickel,
and
selenium.
Natural
gas­
fired
stationary
combustion
turbines
do
not
emit
metallic
HAPs.

Although
numerous
HAPs
may
be
emitted
from
combustion
turbines,
only
a
few
account
for
essentially
all
the
mass
(
about
97
percent)
of
HAP
emissions
from
natural
gasfired
stationary
combustion
turbines.
These
HAPs
are
formaldehyde,
toluene,
benzene,
and
acetaldehyde.

The
HAPs
emitted
in
the
largest
quantity
is
formaldehyde.
Formaldehyde
is
a
probable
human
carcinogen
and
can
cause
irritation
of
the
eyes
and
respiratory
tract,
coughing,
dry
throat,
tightening
of
the
chest,
headache,
and
heart
palpitations.
Acute
inhalation
has
caused
bronchitis,
pulmonary
edema,
pneumonitis,
pneumonia,
and
death
due
to
respiratory
failure.
Long­
term
exposure
can
cause
dermatitis
and
sensitization
of
the
skin
and
respiratory
tract.

Other
HAPs
emitted
in
significant
quantities
from
stationary
combustion
turbines
include
toluene,
benzene,
and
acetaldehyde.
The
health
effect
of
primary
concern
for
toluene
is
dysfunction
of
the
central
nervous
system
(
CNS).
Toluene
vapor
also
causes
narcosis.
Controlled
exposure
of
human
subjects
produced
mild
fatigue,
weakness,
confusion,
lacrimation,
and
paresthesia;
at
higher
exposure
levels
there
were
also
euphoria,
headache,
dizziness,
dilated
pupils,
and
nausea.
After
effects
included
nervousness,
muscular
fatigue,
and
insomnia
persisting
for
several
days.
Acute
exposure
may
cause
irritation
of
the
eyes,
respiratory
tract,
and
skin.
It
may
also
cause
fatigue,
weakness,
confusion,
headache,
and
drowsiness.
Very
high
concentrations
may
cause
unconsciousness
and
death.

Benzene
is
a
known
human
carcinogen.
The
health
effects
of
benzene
include
nerve
inflammation,
CNS
depression,
and
cardiac
sensitization.
Chronic
exposure
to
benzene
can
cause
fatigue,
nervousness,
irritability,
blurred
vision,
and
labored
breathing
and
has
produced
anorexia
and
irreversible
injury
to
the
blood­
forming
organs;
effects
include
3­
3
aplastic
anemia
and
leukemia.
Acute
exposure
can
cause
dizziness,
euphoria,
giddiness,
headache,
nausea,
staggering
gait,
weakness,
drowsiness,
respiratory
irritation,
pulmonary
edema,
pneumonia,
gastrointestinal
irritation,
convulsions,
and
paralysis.
Benzene
can
also
cause
irritation
to
the
skin,
eyes,
and
mucous
membranes.

Acetaldehyde
is
a
probable
human
carcinogen.
The
health
effects
for
acetaldehyde
are
irritation
of
the
eyes,
mucous
membranes,
skin,
and
upper
respiratory
tract,
and
it
is
a
CNS
depressant
in
humans.
Chronic
exposure
can
cause
conjunctivitis,
coughing,
difficult
breathing,
and
dermatitis.
Chronic
exposure
may
cause
heart
and
kidney
damage,
embryotoxicity,
and
teratogenic
effects.

3.3
Summary
of
the
Rule
The
rule
applies
to
you
if
you
own
or
operate
a
stationary
combustion
turbine
that
is
located
at
a
major
source
of
HAP
emissions,
the
definition
of
which
is
mentioned
above.

It
should
be
noted
that
the
rule
does
not
apply
to
stationary
combustion
turbines
located
at
an
area
source
of
HAP
emissions.
An
area
source
of
HAP
emissions
is
a
contiguous
site
under
common
control
that
is
not
a
major
source.

The
rule
does
not
cover
duct
burners.
They
are
part
of
the
waste
heat
recovery
unit
in
a
combined
cycle
system.
Waste
heat
recovery
units,
whether
part
of
a
cogeneration
system
or
a
combined
cycle
system,
are
steam­
generating
units
and
are
not
covered
by
the
rule.

Stationary
combustion
turbines
located
at
research
or
laboratory
facilities
are
not
subject
to
the
final
rule
if
research
is
conducted
on
the
turbine
itself
and
the
turbine
is
not
being
used
to
power
other
applications
at
the
research
or
laboratory
facility.

Finally,
the
rule
does
not
apply
to
stationary
combustion
engine
test
cells/
stands
because
these
facilities
will
be
covered
by
another
NESHAP,
40
CFR
part
63,
subpart
PPPPP.

For
those
sources
that
are
covered,
eight
subcategories
have
been
defined
within
the
stationary
combustion
turbine
source
category.
Although
all
stationary
combustion
turbines
are
subject
to
the
rule,
each
subcategory
has
distinct
requirements.
For
example,
existing
combustion
turbines
and
stationary
combustion
turbines
with
a
rated
peak
power
output
of
less
than
1.0
megawatt
(
MW)
(
at
International
Organization
for
Standardization
(
ISO)
standard
day
conditions)
are
not
required
to
comply
with
emission
limitations,
recordkeeping
or
reporting
requirements
in
the
rule.
New
or
reconstructed
stationary
combustion
turbines
with
a
rated
peak
power
output
of
1.0
MW
or
more
that
either
operate
exclusively
as
an
emergency
stationary
combustion
turbine,
on
the
North
Slope
of
Alaska,
or
as
a
stationary
3­
4
combustion
turbine
that
burns
landfill
gas
or
digester
gas
equivalent
to
10
percent
or
more
of
the
gross
heat
input
on
an
annual
basis
or
where
gasified
municipal
solid
waste
(
MSW)
is
used
to
generate
10
percent
or
more
of
the
gross
heat
input
to
the
turbine
on
an
annual
basis
do
not
have
to
comply
with
an
emission
limitation
but
have
initial
notification
requirements.
New
or
reconstructed
combustion
turbines
must
comply
with
emission
limitations,
recordkeeping
and
reporting
requirements
in
the
rule.
You
must
determine
your
source's
subcategory
to
determine
which
requirements
apply
to
your
source.

3.3.1
Source
Categories
and
Subcategories
Affected
by
the
Rule
A
stationary
combustion
turbine
includes

all
equipment,
including,
but
not
limited
to,
the
turbine,
the
fuel,
air,
lubrication
and
exhaust
gas
systems,
control
systems
(
except
emissions
control
equipment);


any
ancillary
components
and
subcomponents
comprising
any
simple
cycle
stationary
combustion
turbine;
and

any
regenerative/
recuperative
cycle
stationary
combustion
turbine,
or
the
combustion
turbine
portion
of
any
stationary
combined
cycle
steam/
electric
generating
system.

Stationary
means
that
the
combustion
turbine
is
not
self­
propelled
or
intended
to
be
propelled
while
performing
its
function.
A
stationary
combustion
turbine
may,
however,
be
mounted
on
a
vehicle
for
portability
or
transportability.

Stationary
combustion
turbines
have
been
divided
into
the
following
eight
subcategories:

1.
emergency
stationary
combustion
turbines,

2.
stationary
combustion
turbines
that
burn
landfill
or
digester
gas
equivalent
to
10
percent
or
more
of
the
gross
heat
input
on
an
annual
basis
or
where
gasified
MSW
is
used
to
generate
10
percent
or
more
of
the
gross
heat
input
to
the
stationary
combustion
turbine
on
an
annual
basis,

3.
stationary
combustion
turbines
of
less
than
1
MW
rated
peak
power
output,

4.
stationary
lean
premix
combustion
turbines
when
firing
gas
and
when
firing
oil
at
sites
where
all
turbines
fire
oil
no
more
than
1000
hours
annually
(
also
referred
to
herein
as
"
lean
premix
gas­
fired
turbines"),
3­
5
5.
stationary
lean
premix
combustion
turbines
when
firing
oil
at
sites
where
all
turbines
fire
oil
more
than
1000
hours
annually
(
also
referred
to
herein
as
"
lean
premix
oil­
fired
turbines"),

6.
stationary
diffusion
flame
combustion
turbines
when
firing
gas
and
when
firing
oil
at
sites
where
all
turbines
fire
oil
no
more
than
1000
hours
annually
(
also
referred
to
herein
as
"
diffusion
flame
gas­
fired
turbines"),

7.
stationary
diffusion
flame
combustion
turbines
when
firing
oil
at
sites
where
all
turbines
fire
oil
more
than
1000
hours
annually
(
also
referred
to
herein
as
"
diffusion
flame
oil­
fired
turbines"),
and
8.
stationary
combustion
turbines
operated
on
the
North
Slope
of
Alaska
(
defined
as
the
area
north
of
the
Arctic
Circle
[
latitude
66.5
°
North]).

An
emergency
stationary
combustion
turbine
means
any
stationary
combustion
turbine
that
operates
in
an
emergency
situation.
Examples
include
stationary
combustion
turbines
used
to
produce
power
for
critical
networks
or
equipment
(
including
power
supplied
to
portions
of
a
facility)
when
electric
power
from
the
local
utility
is
interrupted,
or
stationary
combustion
turbines
used
to
pump
water
in
the
case
of
fire
or
flood,
etc.
Emergency
stationary
combustion
turbines
do
not
include
stationary
combustion
turbines
used
as
peaking
units
at
electric
utilities
or
stationary
combustion
turbines
at
industrial
facilities
that
typically
operate
at
low
capacity
factors.
Emergency
stationary
combustion
turbines
may
be
operated
for
the
purpose
of
maintenance
checks
and
readiness
testing,
provided
that
the
tests
are
required
by
the
manufacturer,
the
vendor,
or
the
insurance
company
associated
with
the
turbine.
Required
testing
of
such
units
should
be
minimized,
but
there
is
no
time
limit
on
the
use
of
emergency
stationary
sources.

Stationary
combustion
turbines
that
burn
landfill
or
digester
gas
equivalent
to
10
percent
or
more
of
the
gross
heat
input
on
an
annual
basis
or
stationary
combustion
turbines
where
gasified
MSW
is
used
to
generate
10
percent
or
more
of
the
gross
heat
input
to
the
stationary
combustion
turbine
on
an
annual
basis
qualify
as
a
separate
subcategory
because
the
types
of
control
available
for
these
turbines
are
limited.

Stationary
combustion
turbines
of
less
than
1
MW
rated
peak
power
output
were
also
identified
as
a
subcategory.
These
small
stationary
combustion
turbines
are
few
in
number,
and,
to
our
knowledge,
none
use
emission
control
technology
to
reduce
HAPs.
Therefore,
it
would
be
inappropriate
to
require
HAP
emission
controls
to
be
applied
to
them
without
further
information
on
control
technology
performance.

Two
subcategories
of
stationary
lean
premix
combustion
turbines
were
established:
stationary
lean
premix
combustion
turbines
when
firing
gas
and
when
firing
oil
at
sites
where
3­
6
all
turbines
fire
oil
no
more
than
1000
hours
annually
(
also
referred
to
as
"
lean
premix
gasfired
turbines"),
and
stationary
lean
premix
combustion
turbines
when
firing
oil
at
sites
where
all
turbines
fire
oil
more
than
1000
hours
annually
(
also
referred
to
as
"
lean
premix
oil­
fired
turbines").
Lean
premix
technology,
introduced
in
the
1990s,
was
developed
to
reduce
nitrogen
oxide
(
NO
x)
emissions
without
the
use
of
add­
on
controls.
In
a
lean
premix
combustor,
the
air
and
fuel
are
thoroughly
mixed
to
form
a
lean
mixture
for
combustion.
Mixing
may
occur
before
or
in
the
combustion
chamber.
Lean
premix
combustors
emit
lower
levels
of
NO
x,
carbon
monoxide
(
CO),
formaldehyde
and
other
HAPs
than
diffusion
flame
combustion
turbines.

Two
subcategories
of
stationary
diffusion
flame
combustion
turbines
were
established:
stationary
diffusion
flame
combustion
turbines
when
firing
gas
and
when
firing
oil
at
sites
where
all
turbines
fire
oil
no
more
than
1000
hours
annually
(
also
referred
to
as
"
diffusion
flame
gas­
fired
turbines"),
and
stationary
diffusion
flame
combustion
turbines
when
firing
oil
at
sites
where
all
turbines
fire
oil
more
than
1000
hours
annually
(
also
referred
to
as
"
diffusion
flame
oil­
fired
turbines").
In
a
diffusion
flame
combustor,
the
fuel
and
air
are
injected
at
the
combustor
and
are
mixed
only
by
diffusion
prior
to
ignition.
Hazardous
air
pollutant
emissions
from
these
turbines
can
be
significantly
decreased
with
the
addition
of
air
pollution
control
equipment.

Stationary
combustion
turbines
located
on
the
North
Slope
of
Alaska
have
been
identified
as
a
subcategory
because
of
operating
limitations
and
uncertainties
regarding
the
application
of
controls
to
these
units.
There
are
very
few
of
these
units,
and
none
have
installed
emission
controls
for
reducing
HAPs.

3.3.2
Emission
Limitations
and
Operating
Limitations
As
the
owner
or
operator
of
a
new
or
reconstructed
lean
premix
gas­
fired
turbine,
a
new
or
reconstructed
lean
premix
oil­
fired
turbine,
a
new
or
reconstructed
diffusion
flame
gas­
fired
turbine,
or
a
new
or
reconstructed
diffusion
flame
oil­
fired
turbine,
you
must
comply
with
the
emission
limitation
to
reduce
the
concentration
of
formaldehyde
in
the
exhaust
from
the
new
or
reconstructed
stationary
combustion
turbine
to
91
parts
per
billion
by
volume
(
ppbv)
or
less,
dry
basis
(
ppbvd),
at
15
percent
oxygen
by
the
effective
date
of
the
standards
(
or
upon
startup
if
you
start
up
your
stationary
combustion
turbine
after
the
effective
date
of
the
standards).

If
you
comply
with
the
emission
limitation
for
formaldehyde
emissions
and
you
use
an
oxidation
catalyst
emission
control
device,
you
must
continuously
monitor
the
oxidation
3­
7
catalyst
inlet
temperature
and
maintain
the
inlet
temperature
to
the
oxidation
catalyst
within
the
range
recommended
by
the
catalyst
manufacturer.

If
you
comply
with
the
emission
limitation
for
formaldehyde
emissions
and
you
do
not
use
an
oxidation
catalyst
emission
control
device,
you
must
petition
the
Administrator
for
approval
of
operating
limitations
or
approval
of
no
operating
limitations.

3.3.3
Initial
Compliance
Requirements
If
you
operate
a
new
or
reconstructed
lean
premix
gas­
fired
turbine,
a
new
or
reconstructed
lean
premix
oil­
fired
turbine,
a
new
or
reconstructed
diffusion
flame
gas­
fired
turbine,
or
a
new
or
reconstructed
diffusion
flame
oil­
fired
turbine,
you
must
conduct
an
initial
performance
test
using
Test
Method
320
of
40
CFR
part
63,
appendix
A,
to
demonstrate
that
the
outlet
concentration
of
formaldehyde
is
91
ppbvd
or
less
(
corrected
to
15
percent
oxygen).
To
correct
to
15
percent
oxygen,
dry
basis,
you
must
measure
oxygen
using
Method
3A
or
3B
of
40
CFR
part
60,
appendix
A,
and
moisture
using
either
Method
4
of
40
CFR
part
60,
appendix
A,
or
Test
Method
320
of
40
CFR
part
63,
appendix
A.
The
initial
performance
test
must
be
conducted
at
high
load
conditions,
defined
as
100
percent
±
10
percent.

If
you
operate
a
new
or
reconstructed
stationary
combustion
turbine
in
one
of
the
subcategories
required
to
comply
with
an
emission
limitation
and
use
an
oxidation
catalyst
emission
control
device,
you
must
also
install
a
continuous
parameter
monitoring
system
(
CPMS)
to
continuously
monitor
the
oxidation
catalyst
inlet
temperature.

If
you
operate
a
new
or
reconstructed
stationary
combustion
turbine
in
one
of
the
subcategories
required
to
comply
with
an
emission
limitation
and
you
do
not
use
an
oxidation
catalyst
emission
control
device,
you
must
petition
the
Administrator
for
approval
of
operating
limitations
or
approval
of
no
operating
limitations.

If
you
petition
the
Administrator
for
approval
of
operating
limitations,
your
petition
must
include
the
following:
(
1)
identification
of
the
specific
parameters
you
propose
to
use
as
operating
limitations;
(
2)
a
discussion
of
the
relationship
between
these
parameters
and
HAP
emissions,
identifying
how
HAP
emissions
change
with
changes
in
these
parameters,
and
how
limitations
on
these
parameters
will
serve
to
limit
HAP
emissions;
(
3)
a
discussion
of
how
you
will
establish
the
upper
and/
or
lower
values
for
these
parameters
that
will
establish
the
limits
on
these
parameters
in
the
operating
limitations;
(
4)
a
discussion
identifying
the
methods
you
will
use
to
measure
and
the
instruments
you
will
use
to
monitor
these
parameters,
as
well
as
the
relative
accuracy
and
precision
of
these
methods
and
3­
8
instruments;
and
(
5)
a
discussion
identifying
the
frequency
and
methods
for
recalibrating
the
instruments
you
will
use
for
monitoring
these
parameters.

If
you
petition
the
Administrator
for
approval
of
no
operating
limitations,
your
petition
must
include
the
following:
(
1)
identification
of
the
parameters
associated
with
operation
of
the
stationary
combustion
turbine
and
any
emission
control
device
that
could
change
intentionally
(
e.
g.,
operator
adjustment,
automatic
controller
adjustment)
or
unintentionally
(
e.
g.,
wear
and
tear,
error)
on
a
routine
basis
or
over
time;
(
2)
a
discussion
of
the
relationship,
if
any,
between
changes
in
these
parameters
and
changes
in
HAP
emissions;
(
3)
for
those
parameters
with
a
relationship
to
HAP
emissions,
a
discussion
of
whether
establishing
limitations
on
these
parameters
would
serve
to
limit
HAP
emissions;
(
4)
for
those
parameters
with
a
relationship
to
HAP
emissions,
a
discussion
of
how
you
could
establish
upper
and/
or
lower
values
for
these
parameters
which
would
establish
limits
on
these
parameters
in
operating
limitations;
(
5)
for
those
parameters
with
a
relationship
to
HAP
emissions,
a
discussion
identifying
the
methods
you
could
use
to
measure
these
parameters
and
the
instruments
you
could
use
to
monitor
them,
as
well
as
the
relative
accuracy
and
precision
of
these
methods
and
instruments;
(
6)
for
these
parameters,
a
discussion
identifying
the
frequency
and
methods
for
recalibrating
the
instruments
you
could
use
to
monitor
them;
and
(
7)
a
discussion
of
why,
from
your
point
of
view,
it
is
infeasible,
unreasonable,
or
unnecessary
to
adopt
these
parameters
as
operating
limitations.

3.3.4
Continuous
Compliance
Provisions
Several
general
continuous
compliance
requirements
apply
to
stationary
combustion
turbines
required
to
comply
with
the
emission
limitations.
You
are
required
to
comply
with
the
emission
limitations
and
the
operating
limitations
(
if
applicable)
at
all
times,
except
during
startup,
shutdown,
and
malfunction
of
your
stationary
combustion
turbine.
You
must
also
operate
and
maintain
your
stationary
combustion
turbine,
air
pollution
control
equipment,
and
monitoring
equipment
according
to
good
air
pollution
control
practices
at
all
times,
including
startup,
shutdown,
and
malfunction.
You
must
conduct
monitoring
at
all
times
that
the
stationary
combustion
turbine
is
operating,
except
during
periods
of
malfunction
of
the
monitoring
equipment
or
necessary
repairs
and
quality
assurance
or
control
activities,
such
as
calibration
checks.

To
demonstrate
continuous
compliance
with
the
emission
limitations,
you
must
conduct
annual
performance
tests
for
formaldehyde.
You
must
conduct
the
annual
performance
tests
using
Test
Method
320
of
40
CFR
part
63,
appendix
A,
to
demonstrate
that
the
outlet
concentration
of
formaldehyde
is
at
or
below
91
ppbvd
of
formaldehyde
(
corrected
3­
9
to
15
percent
oxygen).
The
annual
performance
test
must
be
conducted
at
high
load
conditions,
defined
as
100
percent
±
10
percent.

If
you
operate
a
new
or
reconstructed
stationary
combustion
turbine
in
one
of
the
subcategories
required
to
comply
with
an
emission
limitation
and
you
use
an
oxidation
catalyst
emission
control
device,
you
must
demonstrate
continuous
compliance
with
the
operating
limitations
by
continuously
monitoring
the
oxidation
catalyst
inlet
temperature.
The
4­
hour
rolling
average
of
the
valid
data
must
be
within
the
range
recommended
by
the
catalyst
manufacturer.

If
you
operate
a
new
or
reconstructed
stationary
combustion
turbine
in
one
of
the
subcategories
required
to
comply
with
an
emission
limitation
and
you
do
not
use
an
oxidation
catalyst
emission
control
device,
you
must
demonstrate
continuous
compliance
with
the
operating
limitations
by
continuously
monitoring
parameters
which
have
been
approved
by
the
Administrator
(
if
any).

3.3.5
Notification,
Record­
keeping,
and
Reporting
Requirements
You
must
submit
all
of
the
applicable
notifications
as
listed
in
the
NESHAP
General
Provisions
(
40
CFR
part
63,
subpart
A),
including
an
initial
notification,
notification
of
performance
test
or
evaluation,
and
a
notification
of
compliance,
for
each
stationary
combustion
turbine
that
must
comply
with
the
emission
limitation.
If
your
new
or
reconstructed
source
is
located
at
a
major
source,
has
greater
than
1
MW
rated
peak
power
output,
and
is
an
emergency
stationary
combustion
turbine,
or
a
stationary
combustion
turbine
located
on
the
North
Slope
of
Alaska,
you
must
submit
only
an
initial
notification.
For
each
combustion
turbine
that
burns
landfill
or
digester
gas
equivalent
to
10
percent
or
more
of
the
gross
heat
input
on
an
annual
basis
or
where
gasified
MSW
is
used
to
generate
10
percent
or
more
of
the
gross
heat
input
to
the
stationary
combustion
turbine
on
an
annual
basis,
you
must
submit
an
initial
notification
and
report
the
necessary
information
to
document
the
fuel
usage
of
the
turbine
but
you
do
not
have
to
comply
with
the
emission
limitation.

For
each
combustion
turbine
in
one
of
the
subcategories
that
is
subject
to
an
emission
limitation,
you
must
record
all
of
the
data
necessary
to
determine
if
you
are
in
compliance
with
the
emission
limitation.
Your
records
must
be
in
a
form
suitable
and
readily
available
for
review.
You
must
also
keep
each
record
for
5
years
following
the
date
of
each
occurrence,
measurement,
maintenance,
report,
or
record.
Records
must
remain
on
site
for
at
least
2
years
and
then
can
be
maintained
off
site
for
the
remaining
3
years.
3­
10
3.4
Rationale
for
Selecting
Standards
3.4.1
Selection
of
Source
Categories
and
Subcategories
Stationary
combustion
turbines
can
be
major
sources
of
HAP
emissions
and,
as
a
result,
we
listed
them
as
a
major
source
category
for
regulatory
development
under
section
112
of
the
CAA,
which
allows
us
to
establish
subcategories
within
a
source
category
for
the
purpose
of
regulation.
Consequently,
we
evaluated
several
criteria
associated
with
stationary
combustion
turbines
that
might
serve
as
potential
subcategories.

We
identified
emergency
stationary
combustion
turbines
as
a
subcategory.
Emergency
stationary
combustion
turbines
operate
only
in
emergencies,
such
as
a
loss
of
power
provided
by
another
source.
These
types
of
stationary
combustion
turbines
operate
infrequently
and,
when
called
on
to
operate,
must
respond
without
failure
and
without
lengthy
periods
of
startup.
These
conditions
limit
the
applicability
of
HAP
emission
control
technology
to
emergency
stationary
combustion
turbines.

Similarly,
stationary
combustion
turbines
that
burn
landfill
or
digester
gas
equivalent
to
10
percent
or
more
of
the
gross
heat
input
on
an
annual
basis
or
where
gasified
MSW
is
used
to
generate
10
percent
or
more
of
the
gross
heat
input
to
the
stationary
combustion
turbine
on
an
annual
basis
were
identified
as
a
subcategory.
Landfill
gas,
digester
gas,
and
gasified
MSW
contain
a
family
of
chemicals
referred
to
as
siloxanes,
which
limit
the
application
of
HAP
emission
control
technology.

Stationary
combustion
turbines
of
less
than
1
MW
rated
peak
power
output
were
also
identified
as
a
subcategory.
We
believe
these
small
stationary
combustion
turbines
are
few
in
number.
These
small
stationary
combustion
turbines
are
sufficiently
dissimilar
from
larger
combustion
turbines
that
we
cannot
evaluate
the
feasibility
of
emission
control
technology
based
on
information
concerning
the
larger
turbines.
To
our
knowledge,
none
of
the
smaller
turbines
use
emission
control
technology
to
reduce
HAP.
Therefore,
we
believe
it
would
be
inappropriate
to
require
HAP
emission
controls
to
be
applied
to
them
without
further
information
on
control
technology
performance.

Stationary
combustion
turbines
can
be
classified
as
either
diffusion
flame
or
lean
premix.
We
examined
formaldehyde
test
data
for
both
diffusion
flame
and
lean
premix
stationary
combustion
turbines
and
observed
that
uncontrolled
formaldehyde
emissions
for
stationary
lean
premix
combustion
turbines
are
significantly
lower
than
those
of
stationary
diffusion
flame
combustion
turbines.
Because
of
the
difference
in
the
two
technologies,
we
decided
to
establish
subcategories
for
diffusion
flame
and
lean
premix
stationary
combustion
turbines.
3­
11
We
further
investigated
subcategorizing
lean
premix
turbines
based
on
fuel.
At
the
time
of
proposal,
EPA
was
not
aware
of
the
availability
of
distillate
oil­
fired
stationary
combustion
turbines
that
operated
in
the
lean
premix
mode.
We
received
comments
indicating
otherwise
during
the
public
comment
period
from
combustion
turbine
manufacturers.
We
believe
there
is
a
difference
in
uncontrolled
HAP
emissions
between
natural
gas
and
distillate
oil
for
stationary
lean
premix
combustion
turbines.
This
is
based
on
test
data
for
stationary
diffusion
flame
combustion
turbines
which
clearly
show
there
is
a
difference
in
the
composition
of
uncontrolled
HAP
emissions
between
natural
gas
and
distillate
oil.
We
believe
this
also
would
apply
to
stationary
lean
premix
combustion
turbines.
For
stationary
lean
premix
combustion
turbines,
NO
x
emissions
also
vary
depending
on
which
fuel
is
burned
in
the
combustion
process.
Information
from
combustion
turbine
vendors
indicate
that
NO
x
emission
guarantees
for
distillate
oil
can
be
up
to
five
times
higher
than
the
NO
x
emission
guarantees
for
natural
gas
for
stationary
lean
premix
combustion
turbines.
Finally,
the
mass
of
total
emissions
may
be
similar
for
natural
gas
and
distillate
oil,
but
some
pollutants
such
as
formaldehyde
are
lower
for
distillate
oil
and
other
pollutants
such
as
PAH
and
metals
are
higher
for
oil.
For
all
practical
purposes,
uncontrolled
natural
gas
metal
emissions
are
nonexistent,
while
they
are
emitted
in
small
quantities
when
burning
distillate
oil.

We
expect
that
the
majority
of
distillate
oil
burned
in
stationary
combustion
turbines
will
be
fuel
oil
number
2.
We
recognize
that
stationary
combustion
turbine
owners
and
operators
may
burn
different
varieties
of
distillate
oil;
however,
we
believe
that
any
other
distillate
oil
combusted
will
be
of
similar
quality
and
composition
to
fuel
oil
number
2.
We
do
not
anticipate
that
owners
and
operators
will
burn
any
other
liquid­
based
fuel
that
is
more
contaminated
with
metals
than
fuel
oil
and
expect
that
most
available
liquid
fuels
that
may
be
used
in
stationary
combustion
turbines
will
be
similar
and
fairly
consistent.

In
recognition
of
the
clear
differences
we
found
in
the
composition
of
HAP
emissions
depending
on
the
fuel
that
is
used,
we
have
determined
that
it
is
appropriate
to
subcategorize
further
within
stationary
lean
premix
combustion
turbines
based
on
fuel
use.
In
devising
appropriate
subcategories
based
on
fuel
use,
we
needed
to
consider
that
many
combustion
turbines
are
configured
both
to
use
natural
gas
and
distillate
oil.
These
dual
fuel
units
typically
burn
natural
gas
as
their
primary
fuel,
and
only
utilize
distillate
oil
as
a
backup.
Without
some
allowance
for
this
limited
backup
use
of
distillate
oil,
these
turbines
might
switch
subcategories
frequently,
causing
confusion
for
sources
and
complicating
compliance
demonstrations.
To
limit
the
frequency
of
switching
between
subcategories
which
would
result
from
limited
usage
of
distillate
oil
as
a
backup
fuel,
we
have
defined
the
lean
premix
gas­
fired
subcategory
in
a
manner
which
permits
turbines
that
fire
gas
using
lean
premix
3­
12
technology
to
remain
in
the
subcategory
if
all
turbines
at
the
site
in
question
fire
oil
no
more
than
a
total
of
1000
hours
during
the
calendar
year.
We
believe
this
1000
hour
allowance
will
be
sufficient
to
accommodate
those
situations
where
distillate
oil
is
used
only
as
a
backup.
The
lean
premix
gas­
fired
turbines
subcategory
will
be
defined
to
include:
(
a)
each
stationary
combustion
turbine
which
is
equipped
only
to
fire
gas
using
lean
premix
technology,
(
b)
each
stationary
combustion
turbine
which
is
equipped
both
to
fire
gas
using
lean
premix
technology
and
to
fire
oil,
during
any
period
when
it
is
firing
gas,
and
(
c)
each
stationary
combustion
turbine
which
is
equipped
both
to
fire
gas
using
lean
premix
technology
and
to
fire
oil,
and
is
located
at
a
major
source
where
all
stationary
combustion
turbines
fire
oil
no
more
than
an
aggregate
total
of
1000
hours
during
the
calendar
year.

The
lean
premix
oil­
fired
turbines
subcategory
will
be
defined
to
include:
(
a)
each
stationary
combustion
turbine
which
is
equipped
only
to
fire
oil
using
lean
premix
technology,
and
(
b)
each
stationary
combustion
turbine
which
is
equipped
both
to
fire
oil
using
lean
premix
technology
and
to
fire
gas,
and
is
located
at
a
major
source
where
all
stationary
combustion
turbines
fire
oil
more
than
an
aggregate
total
of
1000
hours
during
the
calendar
year,
during
any
period
when
it
is
firing
oil.
We
do
not
know
of
any
actual
combustion
turbines
which
would
be
in
this
subcategory,
but
this
is
possible
because
we
have
been
advised
that
combustion
turbines
can
be
configured
to
burn
oil
using
lean
premix
technology.

We
further
investigated
subcategorizing
diffusion
flame
turbines
based
on
fuel.
For
diffusion
flame
turbines,
test
data
show
that
HAP
emissions
vary
depending
on
which
fuel
is
burned.
Formaldehyde
emissions
are
in
general
lower
for
diffusion
flame
units
firing
distillate
oil
versus
diffusion
flame
units
firing
natural
gas.
Emissions
data
also
show
that
NO
x
levels
are
higher
for
diffusion
flame
units
firing
distillate
oil
than
diffusion
flame
units
firing
natural
gas.
Finally,
other
fuel
differences
between
natural
gas
and
distillate
oil
include
higher
levels
of
pollutants
such
as
PAH
and
metals
in
the
emissions
of
stationary
diffusion
flame
combustion
turbines
burning
distillate
oil.
Quantities
of
these
pollutants
are
small
for
distillate
oil;
metal
emissions
from
natural
gas
are
at
non­
detectable
levels.
As
previously
indicated,
we
expect
that
most
owners
and
operators
of
stationary
combustion
turbines
will
burn
distillate
oil
of
the
form
fuel
oil
number
2.
However,
we
recognize
that
other
liquid
based
fuels
may
be
also
be
fired,
but
these
fuels
will
be
similar
to
fuel
oil
number
2,
and
do
not
expect
owners
and
operators
to
burn
any
other
fuel
that
is
more
contaminated
with
metals.

As
in
the
case
of
the
lean
premix
turbines,
we
concluded
based
on
the
clear
differences
in
the
composition
of
HAP
emissions
depending
on
the
fuel
that
is
used
that
it
is
3­
13
appropriate
to
subcategorize
further
within
stationary
diffusion
flame
combustion
turbines
based
on
fuel
use.
As
in
the
case
of
the
lean
premix
turbines,
we
have
included
a
1000
hour
per
site
allowance
for
limited
backup
use
of
distillate
oil
in
order
to
limit
the
frequency
that
dual
fuel
turbines
will
switch
subcategories.
We
believe
this
1000
hour
allowance
will
be
sufficient
to
accommodate
those
situations
where
distillate
oil
is
used
only
as
a
backup.

The
diffusion
flame
gas­
fired
turbines
subcategory
will
be
defined
to
include:
(
a)
each
stationary
combustion
turbine
which
is
equipped
only
to
fire
gas
using
diffusion
flame
technology,
(
b)
each
stationary
combustion
turbine
which
is
equipped
both
to
fire
gas
using
diffusion
flame
technology
and
to
fire
oil,
during
any
period
when
it
is
firing
gas,
and
(
c)
each
stationary
combustion
turbine
which
is
equipped
both
to
fire
gas
using
diffusion
flame
technology
and
to
fire
oil,
and
is
located
at
a
major
source
where
all
stationary
combustion
turbines
fire
oil
no
more
than
an
aggregate
total
of
1000
hours
during
the
calendar
year.

The
diffusion
flame
oil­
fired
turbines
subcategory
will
be
defined
to
include:
(
a)
each
stationary
combustion
turbine
which
is
equipped
only
to
fire
oil
using
diffusion
flame
technology,
and
(
b)
each
stationary
combustion
turbine
which
is
equipped
both
to
fire
oil
using
diffusion
flame
technology
and
to
fire
gas,
and
is
located
at
a
major
source
where
all
stationary
combustion
turbines
fire
oil
more
than
an
aggregate
total
of
1000
hours
during
the
calendar
year,
during
any
period
when
it
is
firing
oil.
We
expect
that
the
vast
majority
of
all
stationary
combustion
turbines
which
are
primarily
oil­
fired
will
be
included
in
this
subcategory.

Stationary
combustion
turbines
located
on
the
North
Slope
of
Alaska
have
been
identified
as
a
subcategory
because
of
operation
limitations
and
uncertainties
regarding
the
application
of
controls
to
these
units.
There
are
very
few
of
these
units,
and
none
have
installed
emission
controls
for
reducing
HAPs.

3.4.2
Determination
of
Basis
and
Level
of
Emission
Limitations
for
Existing
Sources
As
established
in
section
112
of
the
CAA,
the
MACT
standards
must
be
no
less
stringent
than
the
MACT
floor.
The
MACT
floor
for
existing
sources
is
the
average
emission
limitation
achieved
by
the
best
performing
12
percent
of
existing
sources.

3.4.2.1
MACT
Floor
for
Existing
Lean
Premix
Combustion
Turbines
We
have
established
two
subcategories
of
stationary
lean
premix
combustion
turbines,
lean
premix
gas­
fired
turbines
and
lean
premix
oil­
fired
turbines.
Emissions
of
each
HAP
are
relatively
homogeneous
within
each
of
these
two
subcategories,
and
any
variation
in
HAP
emissions
cannot
be
readily
controlled
except
by
add­
on
control.
To
3­
14
determine
the
MACT
floor
for
both
subcategories
of
existing
stationary
lean
premix
combustion
turbines,
the
EPA's
combustion
turbine
inventory
database
was
consulted.

The
inventory
database
provides
population
information
on
stationary
combustion
turbines
in
the
United
States
(
U.
S.)
and
was
constructed
in
order
to
support
the
development
of
the
rule.
Data
in
the
inventory
database
are
based
on
information
from
available
databases,
such
as
the
Aerometric
Information
Retrieval
System
(
AIRS),
the
Ozone
Transport
and
Assessment
Group
(
OTAG),
and
State
and
local
agencies'
databases.
The
first
version
of
the
database
was
released
in
1997.
Subsequent
versions
have
been
released
reflecting
additional
or
updated
data.
The
most
recent
release
of
the
database
is
version
4,
released
in
November
1998.

The
inventory
database
contains
information
on
approximately
4,800
stationary
combustion
turbines.
The
current
stationary
combustion
turbine
population
is
estimated
to
be
about
8,000
turbines.
Therefore,
the
inventory
database
represents
about
60
percent
of
the
stationary
combustion
turbines
in
the
U.
S.
At
least
20
percent
of
those
turbines
are
estimated
to
be
lean
premix
combustion
turbines,
based
on
conversations
with
turbine
manufacturers.

The
information
contained
in
the
inventory
database
is
believed
to
be
representative
of
stationary
combustion
turbines
primarily
because
of
its
comprehensiveness.
The
database
includes
both
small
and
large
stationary
combustion
turbines
in
different
user
segments.
Forty­
eight
percent
are
"
industrial,"
39
percent
are
"
utility,"
and
13
percent
are
"
pipeline."
Note
that
independent
power
producers
(
IPP)
are
included
in
the
utility
and
industrial
segments.

We
examined
all
of
the
information
available
to
us
including
the
inventory
database
to
identify
any
operational
modifications
such
as
equipment
adjustments
or
work
practice
revisions
which
might
be
associated
with
lower
HAP
emissions.
We
were
unsuccessful
in
identifying
any
such
operational
modifications.
Therefore,
we
were
unable
to
utilize
any
factors
other
than
add­
on
controls
in
deriving
the
MACT
floor.

Another
approach
we
investigated
to
identify
a
MACT
floor
was
to
review
the
requirements
in
existing
State
regulations
and
permits.
No
State
regulations
exist
for
HAP
emission
limits
for
stationary
combustion
turbines.
Only
one
State
permit
limitation
for
a
single
HAP
(
benzene)
was
identified.
Therefore,
we
were
unable
to
use
State
regulations
or
permits
in
deriving
a
MACT
floor.

The
only
add­
on
control
technology
currently
proven
to
reduce
HAP
emissions
from
stationary
lean
premix
combustion
turbines
is
an
oxidation
catalyst
emission
control
device.
At
proposal,
the
inventory
database
indicated
that
no
existing
stationary
lean
premix
3­
15
combustion
turbines
were
controlled
with
oxidation
catalyst
systems.
During
the
public
comment
period,
we
received
a
test
report
where
a
lean
premix
combustion
turbine
burning
natural
gas
was
tested
twice
about
2
years
apart
with
an
oxidation
catalyst
in
operation.

We
estimate
that
about
1
percent
of
existing
lean
premix
gas­
fired
turbines
may
have
oxidation
catalyst
systems
installed.
Accordingly,
the
average
of
the
best
performing
12
percent
is
no
emission
reduction.
Therefore,
the
MACT
floor
for
existing
lean
premix
gasfired
turbines
for
each
individual
HAP
is
no
emission
reduction.

For
lean
premix
oil­
fired
turbines,
we
do
not
have
any
data
indicating
that
turbines
in
this
subcategory
are
in
actual
use,
nor
do
we
have
data
indicating
that
oxidation
catalysts
have
been
installed.
Accordingly,
the
average
emission
limitation
achieved
by
the
best
performing
existing
units
in
this
subcategory
for
each
individual
HAP
would
also
be
no
emission
reduction.

3.4.2.2
MACT
for
Existing
Lean
Premix
Combustion
Turbines
To
determine
MACT
for
both
subcategories
of
existing
stationary
lean
premix
combustion
turbines,
we
evaluated
regulatory
alternatives
more
stringent
than
the
MACT
floor.
We
considered
requiring
the
use
of
an
oxidation
catalyst
emission
control
device.
According
to
catalyst
vendors,
oxidation
catalysts
are
currently
being
used
on
some
existing
lean
premix
stationary
combustion
turbines.
In
addition,
we
recently
received
a
test
report
where
testing
was
conducted
on
a
lean
premix
unit
with
an
oxidation
catalyst.
However,
an
analysis
of
the
application
of
oxidation
catalyst
control
to
existing
lean
premix
stationary
combustion
turbines
showed
that
the
incremental
cost
per
ton
of
HAP
removed
was
excessive.
We
have
not
identified
any
operational
modifications
which
are
not
currently
in
use
for
these
turbines
but
might
result
in
HAP
reductions.
Nor
have
we
identified
any
technologies
to
control
those
metallic
HAPs
which
may
be
emitted
during
burning
of
distillate
oil
which
are
technologically
feasible
and
cost­
effective.
For
these
reasons,
we
concluded
that
MACT
for
each
individual
HAP
for
existing
sources
in
both
subcategories
of
existing
stationary
lean
premix
combustion
turbines
is
the
same
as
the
MACT
floor,
i.
e.,
no
emission
reduction.

3.4.2.3
MACT
Floor
for
Existing
Diffusion
Flame
Combustion
Turbines
We
have
established
two
subcategories
of
stationary
diffusion
flame
combustion
turbines,
diffusion
flame
gas­
fired
turbines
and
diffusion
flame
oil­
fired
turbines.
We
believe
emissions
of
each
HAP
are
relatively
homogeneous
within
each
of
these
two
subcategories
and
any
variation
in
HAP
emissions
cannot
be
readily
controlled
except
by
add­
on
control.
To
determine
the
MACT
floor
for
both
subcategories
of
existing
stationary
3­
16
diffusion
flame
combustion
turbines,
we
consulted
the
inventory
database
previously
discussed
in
this
section.
At
least
80
percent
of
those
turbines
are
assumed
to
be
diffusion
flame
combustion
turbines,
based
on
conversations
with
turbine
manufacturers.

We
investigated
the
use
of
operational
modifications
such
as
equipment
adjustments
and
work
practice
revisions
for
stationary
diffusion
flame
combustion
turbines
to
determine
if
HAP
reductions
associated
with
such
operational
modifications
might
be
relevant
in
deriving
the
MACT
floor.
We
found
no
relevant
references
in
the
inventory
database.
Most
stationary
diffusion
flame
combustion
turbines
will
not
operate
unless
preset
conditions
established
by
the
manufacturer
are
met.
Stationary
diffusion
flame
combustion
turbines,
by
manufacturer
design,
permit
little
operator
involvement
and
there
are
no
operating
parameters,
such
as
air/
fuel
ratio,
for
the
operator
to
adjust.
We
concluded,
therefore,
that
there
are
no
specific
operational
modifications
which
could
reduce
HAP
emissions
or
which
could
serve
to
identify
a
MACT
floor.

Another
approach
we
investigated
to
identify
a
MACT
floor
was
to
review
the
requirements
in
existing
State
regulations
and
permits.
No
State
regulations
exist
for
HAP
emission
limits
for
stationary
combustion
turbines.
Only
one
State
permit
limitation
for
a
single
HAP
(
benzene)
was
identified.
Therefore,
we
were
unable
to
use
State
regulations
or
permits
in
deriving
a
MACT
floor.

We
examined
the
inventory
database
for
information
on
HAP
emission
control
technology.
There
were
no
turbines
controlled
with
oxidation
catalyst
systems
in
the
inventory
database
so
we
used
information
supplied
by
catalyst
vendors.
There
are
about
200
oxidation
catalyst
systems
installed
in
the
U.
S.
The
only
control
technology
currently
proven
to
reduce
HAP
emissions
from
stationary
diffusion
flame
combustion
turbines
is
an
oxidation
catalyst
emission
control
device,
such
as
a
CO
oxidation
catalyst.
These
control
devices
are
used
to
reduce
CO
emissions
and
are
currently
installed
on
several
stationary
combustion
turbines.

Less
than
3
percent
of
existing
stationary
diffusion
flame
gas­
fired
turbines
in
the
U.
S.,
based
on
information
in
our
inventory
database
and
information
from
catalyst
vendors,
are
equipped
with
oxidation
catalyst
emission
control
devices.
Therefore,
the
average
emission
limitation
for
the
best
performing
12
percent
of
existing
diffusion
flame
gas­
fired
turbines
is
no
emission
reduction
and
the
MACT
floor
for
each
individual
HAP
for
existing
turbines
in
this
subcategory
is
also
no
emission
reduction.

We
estimate
that
less
than
1
percent
of
existing
stationary
diffusion
flame
oil­
fired
turbines
have
oxidation
catalyst
systems
installed.
Thus,
the
average
of
the
best
performing
3­
17
12
percent
of
existing
diffusion
flame
oil­
fired
turbines
is
no
emission
reduction
for
organic
HAP.
No
technologies
to
control
metallic
HAP
have
been
installed
on
the
existing
turbines
in
this
subcategory.
Therefore,
the
MACT
floor
for
each
individual
HAP
for
existing
turbines
in
the
diffusion
flame
oil­
fired
subcategory
is
no
emission
reduction.

3.4.2.4
MACT
for
Existing
Diffusion
Flame
Combustion
Turbines
To
determine
MACT
for
both
subcategories
of
existing
diffusion
flame
combustion
turbines,
regulatory
alternatives
more
stringent
than
the
MACT
floor
were
evaluated.
One
beyond­
the­
floor
regulatory
option
is
requiring
an
oxidation
catalyst.
However,
cost
per
ton
estimates
of
oxidation
catalyst
emission
control
devices
for
control
of
total
HAP
from
stationary
diffusion
flame
combustion
turbines
were
deemed
excessive.
In
addition,
we
did
not
identify
any
operational
modifications
which
are
not
currently
in
use
for
these
turbines
but
might
result
in
HAP
reductions.
Moreover,
we
did
not
identify
any
technologies
to
control
those
metallic
HAP
which
may
be
emitted
during
burning
of
distillate
oil
which
are
technologically
feasible
and
cost­
effective.
For
these
reasons,
MACT
for
each
individual
HAP
for
turbines
in
both
subcategories
of
existing
stationary
diffusion
flame
combustion
turbines
is
the
same
as
the
MACT
floor,
i.
e.,
no
emission
reduction.

3.4.3
New
Sources
For
new
sources,
the
MACT
floor
is
defined
as
the
emission
control
that
is
achieved
in
practice
by
the
best
controlled
similar
source.
To
be
a
similar
source,
a
source
should
not
have
any
characteristics
that
differ
sufficiently
to
have
a
material
effect
on
the
feasibility
of
emission
controls,
but
the
source
need
not
be
in
the
same
source
category
or
subcategory.

We
considered
using
a
surrogate
in
order
to
reduce
the
costs
associated
with
monitoring
while
at
the
same
time
being
relatively
sure
that
the
pollutants
the
surrogate
is
supposed
to
represent
are
also
controlled.
We
investigated
the
use
of
formaldehyde
concentration
as
a
surrogate
for
all
organic
HAP
emissions.
Formaldehyde
is
the
HAP
emitted
in
the
highest
concentrations
from
stationary
combustion
turbines.
Formaldehyde,
toluene,
benzene,
and
acetaldehyde
account
for
essentially
all
the
mass
of
HAP
emissions
from
the
stationary
combustion
turbine
exhaust,
and
emissions
data
show
that
these
pollutants
are
equally
controlled
by
an
oxidation
catalyst.

Information
from
testing
conducted
on
a
diffusion
flame
combustion
turbine
equipped
with
an
oxidation
catalyst
control
system
indicated
that
the
formaldehyde
and
acetaldehyde
emission
reduction
efficiency
achieved
was
97
and
94
percent,
respectively.
Later,
after
review
of
an
expert
task
group,
the
conclusion
reached
was
that
both
formaldehyde
and
acetaldehyde
were
controlled
at
least
90
percent.
In
addition,
emissions
3­
18
tests
conducted
on
reciprocating
internal
combustion
engines
(
RICE)
at
Colorado
State
University
(
CSU)
in
1998
showed
that
the
benzene
emission
reduction
efficiency
across
an
oxidation
catalyst
averaged
73
percent,
and
the
toluene
emission
reduction
averaged
77
percent
for
16
runs
at
various
engine
conditions
on
a
two­
stroke
lean
burn
engine.
The
toluene
emission
reduction
efficiency
across
the
oxidation
catalyst
averaged
85
percent
for
ten
runs
at
various
engine
conditions
on
a
compression
ignition
RICE.
We
would
expect
the
emissions
reductions
efficiencies
for
benzene
and
toluene
from
combustion
turbines
to
be
as
high
or
higher
than
those
reported
for
the
CSU
RICE
tests
since
combustion
turbines
catalyst
temperatures
are
generally
higher.
Finally,
catalyst
performance
information
obtained
from
a
catalyst
vendor
indicated
that
the
percent
conversion
for
an
oxidation
catalyst
system
installed
on
combustion
turbines
did
not
vary
significantly
between
formaldehyde,
benzene,
and
toluene.
The
percent
conversion
was
measured
at
77,
72,
and
71
for
formaldehyde,
benzene,
and
toluene,
respectively.
Although
emissions
reductions
for
large
molecules
may
in
theory
be
less
than
for
formaldehyde,
the
above
information
shows
that
formaldehyde
is
a
good
surrogate
for
the
most
significant
HAP
pollutants
emitted
from
combustion
turbines
as
demonstrated
by
evaluating
the
reduction
efficiency
of
larger,
heavier
molecules,
hence
taking
differences
in
molecular
density
into
account.
In
addition,
emission
data
show
that
HAP
emission
levels
and
formaldehyde
emission
levels
are
related,
in
the
sense
that
when
emissions
of
one
are
low,
emissions
of
the
other
are
low
and
vice
versa.
This
leads
us
to
conclude
that
emission
control
technologies
which
lead
to
reductions
in
formaldehyde
emissions
will
lead
to
reductions
in
organic
HAP
emissions.
For
the
reasons
provided
above,
it
is
appropriate
to
use
formaldehyde
as
a
surrogate
for
all
organic
HAP
emissions.

3.4.3.1
New
Lean
Premix
Gas­
Fired
Combustion
Turbines
To
determine
the
MACT
floor
for
new
stationary
lean
premix
gas­
fired
turbines,
we
reviewed
the
emissions
data
we
had
available
at
proposal
and
additional
test
reports
received
during
the
comment
period.
In
order
to
set
the
MACT
floor
for
new
sources
in
this
subcategory,
we
chose
the
best
performing
turbine.
Emissions
of
each
HAP
are
relatively
homogeneous
within
the
subcategory
of
stationary
lean
premix
gas­
fired
turbines
and
any
variation
in
HAP
emissions
cannot
be
readily
controlled
except
by
add­
on
control.
The
best
performing
turbine
is
equipped
with
an
oxidation
catalyst.

The
formaldehyde
concentration
from
the
best
performing
turbine
was
measured
at
the
outlet
of
the
control
device
using
CARB
430.
Concerns
were
raised
during
the
public
comment
period
that
CARB
430
formaldehyde
results
can
be
biased
low
as
compared
to
formaldehyde
results
obtained
by
FTIR.
For
a
comprehensive
discussion
of
test
methods
and
the
development
of
the
correlation
between
CARB
430
and
FTIR
formaldehyde
levels,
3­
19
please
refer
to
the
memorandum
entitled
"
Review
of
Test
Methods
and
Data
used
to
Quantify
Formaldehyde
Concentrations
from
Combustion
Turbines"
in
the
docket.
A
bias
factor
of
1.7
was,
therefore,
applied
to
the
formaldehyde
concentration
of
the
best
performing
turbine.
The
best
performing
turbine
was
tested
twice
under
the
same
conditions
about
2
years
apart
where
one
test
measured
19
ppbvd
and
the
other
test
measured
91
ppbvd
formaldehyde
(
numbers
have
been
bias
corrected).
We
determined
that
since
both
of
these
tests
were
performed
under
similar
conditions
but
at
different
times,
this
represented
the
variability
of
the
best
performing
unit
and
used
the
higher
value
as
the
MACT
floor.
The
MACT
floor
for
organic
HAP
for
new
stationary
lean
premix
gas­
fired
turbines
is,
therefore,
an
emission
limit
of
91
ppbvd
formaldehyde
at
15
percent
oxygen.

We
recognize
that
our
selection
of
an
emission
limit
of
91
ppbvd
formaldehyde
is
based
on
quite
limited
data.
We
think
that
each
new
combustion
turbine
in
this
subcategory
should
be
able
to
achieve
compliance
with
this
limit
if
an
oxidation
catalyst
is
properly
installed
and
operated.
If
actual
emission
data
demonstrate
that
we
are
incorrect,
and
that
sources
which
properly
install
and
operate
an
oxidation
catalyst
cannot
consistently
achieve
compliance,
we
will
revise
the
standard
accordingly.

No
beyond­
the­
floor
regulatory
alternatives
were
identified
for
new
lean
premix
gasfired
turbines.
We
are
not
aware
of
any
add­
on
control
devices
which
can
reduce
organic
HAP
emissions
to
levels
lower
than
those
resulting
from
the
application
of
oxidation
catalyst
systems.
We,
therefore,
determined
that
MACT
for
organic
HAP
emissions
from
new
stationary
lean
premix
gas­
fired
turbines
is
the
same
as
the
MACT
floor,
i.
e.,
an
emission
limit
of
91
ppbvd
formaldehyde
at
15
percent
oxygen.

3.4.3.2
New
Lean
Premix
Oil­
Fired
Combustion
Turbines
We
do
not
have
any
tests
for
lean
premix
combustion
turbines
firing
any
other
fuels
besides
natural
gas.
However,
we
expect
that
emissions
of
organic
HAP
will
be
controlled
by
installation
of
an
oxidation
catalyst
on
any
units
in
this
subcategory
to
a
degree
similar
to
lean
premix
gas­
fired
turbines
and
diffusion
flame
oil­
fired
turbines.
We
also
expect
that
organic
HAP
emissions
from
lean
premix
oil­
fired
turbines
would
be
equal
to
or
less
than
organic
HAP
emissions
from
lean
premix
gas­
fired
turbines.
We
have
these
expectations
based
on
the
fact
that
dual­
fuel
units
using
oxidation
catalyst
systems
operate
on
distillate
oil
and
the
fact
that
catalyst
vendors
indicate
that
oxidation
catalyst
systems
operate
equally
well
on
either
fuel.
Therefore,
we
used
the
best
performing
turbine
from
the
lean
premix
gas­
fired
turbine
subcategory
to
set
the
MACT
floor
for
lean
premix
oil­
fired
turbines.
As
a
result,
the
MACT
floor
for
organic
HAP
for
new
stationary
lean
premix
oil­
fired
turbines
is
an
emission
limit
of
91
ppbvd
formaldehyde
at
15
percent
oxygen.
3­
20
We
are
not
aware
of
any
similar
sources
which
are
equipped
with
emission
control
devices
that
could
also
reduce
emissions
of
metallic
HAP.
We
also
examined
the
inventory
database
in
an
attempt
to
identify
any
operating
modifications
which
might
reduce
metal
emissions,
but
could
not
identify
any
such
practices.
We
also
referred
to
the
inventory
database
to
determine
if
any
similar
sources
are
equipped
with
emission
controls
for
the
reduction
of
particulate
matter
(
PM)
which
would
also
reduce
metal
emissions.
No
such
units
were
found
in
the
inventory
database
and
none
were
identified
by
commenters
during
the
public
comment
period.
For
this
reason,
the
MACT
floor
for
new
stationary
lean
premix
oil­
fired
turbines
is
no
emission
control
for
metallic
HAP
emissions.

We
were
unable
to
identify
any
beyond­
the­
floor
regulatory
alternatives
for
new
stationary
lean
premix
oil­
fired
turbines.
We
know
of
no
emission
control
technology
currently
available
which
can
reduce
HAP
emissions
to
levels
lower
than
those
achieved
through
use
of
an
oxidation
catalyst.
We
also
have
not
identified
any
add­
on
controls
for
metallic
HAP.
We
conclude,
therefore,
that
MACT
for
new
lean
premix
oil­
fired
turbines
would
be
equivalent
to
the
MACT
floor,
i.
e.,
an
emission
limit
of
91
ppbvd
formaldehyde
at
15
percent
oxygen
for
organic
HAP,
and
no
emission
reduction
for
metallic
HAP.

3.4.3.3
New
Diffusion
Flame
Gas­
Fired
Combustion
Turbines
In
the
proposed
rule,
we
requested
sources
to
submit
any
HAP
emissions
test
data
available
from
stationary
combustion
turbines.
After
the
proposal,
we
also
contacted
several
State
agencies
to
request
emissions
test
data
from
diffusion
flame
combustion
turbines.
Due
to
the
CARB
advisory
issued
on
April
28,
2000,
which
stated
that
formaldehyde
emissions
data
where
the
NO
x
levels
were
greater
than
50
ppmvd
were
suspect
and
should
be
flagged
as
non­
quantitative,
we
conducted
an
analysis
of
existing
diffusion
flame
emissions
test
data.
Tests
where
the
NO
x
emissions
were
greater
than
50
ppm
or
tests
where
the
NO
x
levels
were
unknown
were
excluded
from
our
analysis.
Most
of
the
diffusion
flame
tests
in
the
emissions
database
were
unable
to
pass
the
screening.
Therefore,
we
specifically
requested
States
to
provide
test
reports
for
diffusion
flame
combustion
turbines
where
Method
320
was
used,
or
CARB
430
was
used
and
the
NO
x
emissions
were
below
50
ppmvd.
During
the
comment
period
we
received
three
additional
test
reports
for
testing
conducted
on
a
total
of
five
stationary
diffusion
flame
combustion
turbines.

To
identify
the
MACT
floor
for
new
stationary
diffusion
flame
gas­
fired
turbines,
we
based
our
analysis
on
the
performance
of
the
best
turbine.
Individual
HAP
emissions
are
relatively
homogeneous
within
the
subcategory
of
stationary
diffusion
flame
gas­
fired
turbines
and
any
variation
in
HAP
emissions
cannot
be
readily
controlled
except
by
add­
on
3­
21
control.
The
best
performing
turbine
in
this
subcategory
is
equipped
with
an
oxidation
catalyst.

As
previously
indicated,
formaldehyde
is
the
HAP
emitted
in
the
highest
concentrations
from
stationary
combustion
turbines
and
data
show
control
of
organic
HAP
emissions
and
formaldehyde
emissions
are
related.
We
have,
therefore,
concluded
that
formaldehyde
is
an
appropriate
surrogate
for
all
organic
HAP
emissions.

Formaldehyde
was
measured
by
CARB
430
at
the
outlet
of
the
oxidation
catalyst.
We
applied
a
bias
factor
of
1.7
to
the
formaldehyde
concentration
obtained
by
CARB
430
for
the
best
performing
turbine.
The
corrected
outlet
concentration
of
formaldehyde
from
the
best
performing
turbine
was
15
ppbvd.
We
only
have
one
controlled
test
for
this
turbine,
but
we
expect
that
similar
variability
would
be
associated
with
this
turbine
as
was
associated
with
the
best
performing
lean
premix
turbine.
Therefore,
applying
a
factor
of
5
to
the
formaldehyde
concentration
measured
at
the
outlet
of
the
best
performing
diffusion
flame
turbine
is
appropriate
to
account
for
variability.
Therefore,
we
would
establish
a
formaldehyde
emission
limitation
of
75
ppbvd
based
on
the
outlet
of
the
control
device.
However,
with
a
similar
control
system,
we
would
expect
that
the
emission
limit
should
be
no
lower
than
the
emission
limit
for
lean
premix
turbines
since
diffusion
flame
turbines
on
average
emit
more
HAP.
The
MACT
floor
for
new
stationary
diffusion
flame
combustion
gas­
fired
turbines
is,
therefore,
an
emission
limit
of
91
ppbvd
formaldehyde
at
15
percent
oxygen.

We
were
unable
to
identify
any
beyond­
the­
floor
regulatory
alternatives
for
new
stationary
diffusion
flame
gas­
fired
turbines.
We
know
of
no
emission
control
technology
currently
available
which
can
reduce
organic
HAP
emissions
to
levels
lower
than
that
achieved
through
the
use
of
an
oxidation
catalyst.
We
concluded,
therefore,
that
MACT
for
organic
HAP
emissions
from
new
diffusion
flame
stationary
gas­
fired
turbines
is
equivalent
to
the
MACT
floor,
i.
e.,
an
emission
limit
of
91
ppbvd
formaldehyde
at
15
percent
oxygen.

3.4.3.4
New
Diffusion
Flame
Oil­
Fired
Combustion
Turbines
To
determine
the
MACT
floor
for
new
diffusion
flame
oil­
fired
turbines,
we
again
based
our
analysis
on
the
best
performing
turbine.
Emissions
of
each
individual
HAP
are
relatively
homogeneous
within
stationary
diffusion
flame
oil­
fired
turbines
and
any
variation
in
HAP
emissions
cannot
be
readily
controlled
except
by
add­
on
control.
The
best
performing
turbine
in
this
subcategory
is
equipped
with
an
oxidation
catalyst.

As
previously
described
in
more
detail,
we
are
using
formaldehyde
as
a
surrogate
for
all
organic
HAP
emissions.
The
formaldehyde
was
measured
with
EPA
Method
0011
at
the
3­
22
outlet
of
the
control
device.
The
EPA
Method
0011
is
similar
to
CARB
430
and
the
problems
associated
with
CARB
430
are
expected
to
be
associated
with
EPA
Method
0011.
So
again
we
applied
a
bias
factor
of
1.7
to
the
formaldehyde
outlet
concentration
of
the
best
performing
diffusion
flame
oil­
fired
turbine.
The
corrected
formaldehyde
concentration
from
this
turbine
is
44
ppbvd.
We
only
had
one
controlled
test
for
this
turbine,
but
would
expect
some
variability
as
has
been
shown
with
other
turbines.
However,
since
formaldehyde
emissions
from
distillate
oil
fired
turbines
are
lower
on
average
by
a
factor
of
1.4,
we
do
not
believe
that
the
MACT
emission
limit
should
be
set
higher
than
the
emission
limit
for
new
stationary
diffusion
flame
gas­
fired
turbines.
Therefore,
the
MACT
floor
for
organic
HAP
for
new
stationary
diffusion
flame
oil­
fired
turbines
is
an
emission
limit
of
91
ppbvd
formaldehyde
at
15
percent
oxygen.

We
examined
the
inventory
database
to
identify
any
operating
practices
which
could
affect
metal
emissions.
We
were
unable
to
identify
any
such
practices.
We
also
determined
that
no
similar
sources
are
equipped
with
emission
control
devices
for
the
reduction
of
PM
which
could
also
reduce
metal
emissions.
Therefore,
the
MACT
floor
for
metallic
HAP
for
new
diffusion
flame
oil­
fired
turbines
is
no
emission
reduction.

To
determine
MACT
for
new
stationary
diffusion
oil­
fired
turbines,
we
tried
to
identify
beyond­
the­
floor
options.
There
are
currently
no
beyond­
the­
floor
regulatory
alternatives
for
this
subcategory
as
we
know
of
no
emission
control
technology
current
available
that
can
reduce
organic
HAP
emissions
to
levels
lower
than
that
obtained
with
the
use
of
an
oxidation
catalyst.
We
also
have
not
identified
any
add­
on
controls
for
metallic
HAP.
We
conclude,
therefore,
that
MACT
for
new
diffusion
flame
oil­
fired
turbines
would
be
equivalent
to
the
MACT
floor,
i.
e.,
an
emission
limit
of
91
ppbvd
formaldehyde
at
15
percent
oxygen
organic
HAP,
and
no
emission
reduction
for
metallic
HAP.

3.4.4
MACT
for
Other
Subcategories
Although
the
final
rule
will
apply
to
all
stationary
combustion
turbines
located
at
major
sources
of
HAP
emissions,
emergency
stationary
combustion
turbines,
stationary
combustion
turbines
that
burn
landfill
or
digester
gas
equivalent
to
10
percent
or
more
of
the
gross
heat
input
on
an
annual
basis
or
where
gasified
MSW
is
used
to
generate
10
percent
or
more
of
the
gross
heat
input
to
the
stationary
combustion
turbine
on
an
annual
basis,
stationary
combustion
turbines
of
less
than
1
MW
rated
peak
power
output,
and
stationary
combustion
turbines
located
on
the
North
Slope
of
Alaska
are
not
required
to
meet
the
emission
limitations
or
operating
limitations.
3­
23
For
each
of
the
other
subcategories
of
stationary
combustion
turbines,
we
have
concerns
about
the
applicability
of
emission
control
technology.
For
example,
emergency
stationary
combustion
turbines
operate
infrequently.
In
addition,
when
called
upon
to
operate
they
must
respond
immediately
without
failure
and
without
lengthy
startup
periods.
This
infrequent
operation
limits
the
applicability
of
HAP
emission
control
technology.

Landfill
and
digester
gases
contain
a
family
of
silicon­
based
gases
called
siloxanes.
Siloxanes
are
also
a
component
of
municipal
waste.
Combustion
of
siloxanes
forms
compounds
that
can
foul
post­
combustion
catalysts,
rendering
catalysts
inoperable
within
a
very
short
period
of
time.
It
is
our
judgment
based
on
public
comments
and
information
obtained
from
catalyst
vendors
and
sanitation
districts
that
firing
even
10
percent
landfill
or
digester
gas
will
cause
fouling
that
will
render
the
oxidation
catalyst
inoperable
within
a
short
period
of
time.
Pretreatment
of
exhaust
gases
to
remove
siloxanes
was
investigated.
However,
no
pretreatment
systems
are
in
use
and
their
long­
term
effectiveness
is
unknown.
We
also
considered
fuel
switching
for
this
subcategory
of
turbines.
Switching
to
a
different
fuel
such
as
natural
gas
or
diesel
would
potentially
allow
the
turbine
to
apply
an
oxidation
catalyst
emission
control
device.
However,
fuel
switching
would
defeat
the
purpose
of
using
this
type
of
fuel
which
would
then
either
be
allowed
to
escape
uncontrolled
or
would
be
burned
in
a
flare
with
no
energy
recovery.
We
believe
that
switching
landfill
or
digester
gas
or
gasified
MSW
to
another
fuel
is
inappropriate
and
is
an
environmentally
inferior
option.

For
stationary
combustion
turbines
of
less
than
1
MW
rated
peak
power
output,
we
have
concerns
about
the
effectiveness
of
scaling
down
the
oxidation
catalyst
emission
control
technology.
Just
as
there
are
often
unforeseen
problems
associated
with
scaling
up
a
technology,
there
can
be
problems
associated
with
scaling
down
a
technology.

Stationary
combustion
turbines
located
on
the
North
Slope
of
Alaska
have
been
identified
as
a
subcategory
due
to
operation
limitations
and
uncertainties
regarding
the
application
of
controls
to
these
units.
There
are
very
few
of
these
units;
in
addition,
none
have
installed
emission
controls
for
the
reduction
of
HAP.

As
a
result,
we
identified
subcategories
for
each
of
these
types
of
stationary
combustion
turbines
and
investigated
MACT
floors
and
MACT
for
each
subcategory.
As
expected,
since
we
identified
these
types
of
stationary
combustion
turbines
as
separate
subcategories
based
on
concerns
about
the
applicability
of
emission
control
technology,
we
found
no
stationary
combustion
turbines
in
these
subcategories
using
any
emission
control
technology
to
reduce
HAP
emissions.
As
discussed
above,
we
are
not
aware
of
any
work
practices
that
might
constitute
a
MACT
floor,
nor
did
we
find
that
the
use
of
a
particular
fuel
3­
24
results
in
HAP
emission
reductions.
The
MACT
floor,
therefore,
for
each
of
these
subcategories
is
no
emission
reduction.

Despite
our
concerns
with
the
applicability
of
emission
control
technology,
we
examined
the
cost
per
ton
of
HAP
removed
for
these
subcategories.
This
analysis
can
be
found
in
the
docket
(
Docket
ID
No.
OAR­
2002­
0060
(
A­
95­
51))
for
the
final
rule.
Whether
our
concerns
are
warranted
or
not,
we
consider
the
incremental
cost
per
ton
of
HAP
removed
excessive
 
primarily
because
of
the
very
small
reduction
in
HAP
emissions
that
would
result.

We
also
considered
the
non­
air
health,
environmental,
and
energy
impacts
of
an
oxidation
catalyst
system,
as
discussed
previously,
and
concluded
that
there
would
be
only
a
small
energy
impact
and
no
non­
air
health
or
environmental
impacts.
However,
as
stated
above,
we
did
not
adopt
this
regulatory
option
due
to
cost
considerations
and
concerns
about
the
applicability
of
this
technology
to
these
subcategories.
We
were
not
able
to
identify
any
other
means
of
achieving
HAP
emission
reduction
for
these
subcategories.

As
a
result,
for
all
of
these
reasons,
we
conclude
that
MACT
for
these
subcategories
is
the
MACT
floor
(
i.
e.,
no
emission
reduction).

3.4.5
Selection
of
Initial
Compliance
Requirements
New
and
reconstructed
sources
complying
with
the
emission
limitation
for
formaldehyde
emissions
are
required
to
conduct
an
initial
performance
test.
The
purpose
of
the
initial
test
is
to
demonstrate
initial
compliance
with
the
formaldehyde
emission
limitation.

3.4.5.1
How
Did
We
Select
the
Continuous
Compliance
Requirements?

If
you
must
comply
with
the
emission
limitations,
continuous
compliance
with
these
requirements
is
required
at
all
times
except
during
startup,
shutdown,
and
malfunction
of
your
stationary
combustion
turbine.
You
are
required
to
develop
a
startup,
shutdown,
and
malfunction
plan.

We
considered
requiring
FTIR
CEMS;
however,
we
concluded
that
the
costs
of
FTIR
CEMS
were
excessive
and
were
not
yet
demonstrated
at
the
low
formaldehyde
levels
of
the
standards.
We
considered
requiring
those
sources
to
continuously
monitor
operating
load
to
demonstrate
continuous
compliance
because
the
data
establishing
the
formaldehyde
outlet
concentration
level
are
based
on
tests
that
were
done
at
high
loads.
However,
we
believe
that
the
performance
of
a
stationary
combustion
turbine
at
high
load
is
also
indicative
of
its
3­
25
operation
at
lower
loads.
In
fact,
the
operator
can
make
no
parameter
adjustments
that
would
lead
to
lower
emissions.

For
these
reasons,
EPA
determined
that
it
would
be
appropriate
to
require
sources
that
comply
with
the
emission
limitation
for
formaldehyde
emissions
and
that
use
an
oxidation
catalyst
emission
control
device
to
continuously
monitor
the
oxidation
catalyst
inlet
temperature.
Continuously
monitoring
the
oxidation
catalyst
inlet
temperature
and
maintaining
this
temperature
within
the
range
recommended
by
the
catalyst
manufacturer
will
ensure
proper
operation
of
the
oxidation
catalyst
emission
control
device
and
continuous
compliance
with
the
emission
limitation
for
formaldehyde.

Sources
that
do
not
use
an
oxidation
catalyst
emission
control
device
are
required
to
petition
the
Administrator
for
approval
of
operating
limitations
or
approval
of
no
operating
limitations.

3.4.5.2
How
Did
We
Select
the
Testing
Methods
to
Measure
these
Low
Concentrations
of
Formaldehyde?

The
final
rule
requires
the
use
of
Method
320
to
determine
compliance
with
the
emission
limitation
for
formaldehyde.
With
regard
to
formaldehyde,
we
believe
systems
meeting
the
requirements
of
Method
320,
a
self­
validating
FTIR
method,
can
be
used
to
attain
detection
limits
for
formaldehyde
concentrations
well
below
the
current
emission
limitations
with
a
path
length
of
10
meters
or
less.
Some
of
the
older
technology
may
require
100
or
even
200
meter
path
lengths.
We
expect
state­
of­
the­
art
digital
signal
processing
(
to
reduce
signal
to
noise
ratio)
would
be
needed.
Method
320
also
includes
formaldehyde
spike
recovery
criteria,
which
require
spike
recoveries
of
70
to
130
percent.

While
we
believe
FTIR
systems
can
meet
the
requirements
of
Method
320
and
measure
formaldehyde
concentrations
at
these
low
levels,
we
have
limited
experience
with
their
use.
As
a
result,
we
solicited
comments
on
the
ability
and
use
of
FTIR
systems
to
meet
the
validation
and
quality
assurance
requirements
of
Method
320
for
the
purpose
of
determining
compliance
with
the
emission
limitation
for
formaldehyde.
Commenters
were
generally
in
agreement
that
Method
320
is
the
most
accurate
and
reliable
test
method
currently
available
to
test
for
formaldehyde
emissions
from
the
stationary
combustion
turbine
exhaust.

As
an
alternative
to
Method
320,
we
proposed
Method
323
for
natural
gas­
fired
sources.
Method
323
uses
the
acetyl
acetone
colorimetric
method
to
measure
formaldehyde
emissions
in
the
exhaust
of
natural
gas­
fired,
stationary
combustion
sources.
Commenters
did
not
support
Method
323
and
were
concerned
whether
this
method
could
provide
reliable
3­
26
results.
In
addition,
Method
323
has
not
been
validated
or
demonstrated
for
use
on
stationary
combustion
turbines
emitting
low
formaldehyde
emissions.
Therefore,
Method
323
has
not
been
included
as
a
compliance
method
for
formaldehyde
in
the
final
rule.

At
proposal
we
believed
CARB
Method
430
and
EPA
SW­
846
Method
0011
were
capable
of
measuring
formaldehyde
concentrations
at
these
low
levels.
Commenters
were
not
supportive
of
these
methods.
In
addition,
CARB
430
is
susceptible
to
interferences
and
sample
loss
contributes
to
large
measurement
variability.
Method
0011
uses
a
similar
analytical
approach
to
CARB
430
and
has
many
shortcomings
and
limited
application
opportunities.
Accordingly,
we
are
not
including
CARB
430
and
Method
0011
in
the
final
rule.

For
these
reasons,
EPA
has
specified
that
Method
320
should
be
used
to
determine
compliance
with
the
formaldehyde
emission
limitation
in
the
final
rule.
4­
1
SECTION
4
PROJECTION
OF
UNITS
AND
FACILITIES
IN
AFFECTED
SECTORS
The
regulation
will
affect
turbine
units
with
capacity
over
1
MW.
As
a
result,
the
economic
impact
estimates
presented
in
Section
6
and
the
small
business
screening
analysis
presented
in
Section
7
are
based
on
the
population
of
existing
units
and
the
projection
of
new
combustion
turbine
units
through
the
year
2007.
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
existing
and
new
combustion
turbines
that
will
be
affected
by
this
rule.

4.1
Profile
of
Existing
Combustion
Turbine
Units
This
section
profiles
existing
combustion
turbine
units
(
greater
than
1
MW)
with
respect
to
business
applications,
industry
of
parent
company,
and
fuel
use.
For
nonutility
combustion
turbines,
the
population
of
existing
sources
will
be
used
to
provide
the
characteristics
of
new
combustion
turbines
constructed
through
the
year
2007.

The
population
of
existing
combustion
turbine
units
used
in
the
analysis
was
developed
from
the
EPA
Inventory
Database
V.
4
 
Turbines
(
referred
to
as
the
Inventory
Database).
The
combustion
turbines
contained
in
the
Inventory
Database
are
based
on
information
from
the
Aerometric
Information
Retrieval
System
(
AIRS)
and
Ozone
Transport
Assessment
Group
(
OTAG)
databases,
state
and
local
permit
records,
and
the
combustion
source
Information
Collection
Request
(
ICR)
conducted
by
the
Agency
in
1997.
The
list
of
combustion
turbine
units
contained
in
the
Inventory
Database
was
reviewed
and
updated
by
industry
and
environmental
stakeholders
as
part
of
the
Industrial
Combustion
Coordinated
Rulemaking
(
ICCR),
chartered
under
the
Federal
Advisory
Committee
Act
(
FACA).

From
the
Inventory
Database,
EPA
identified
2,072
combustion
turbines
with
greater
than
1
MW
capacity.
More
than
2,800
additional
turbines
were
listed
in
the
database,
but
their
records
lacked
capacity
information
and/
or
industry
information,
so
these
units
are
excluded
from
this
analysis.
The
total
estimated
population
of
existing
combustion
turbines
is
about
8,000,
so
the
coverage
in
the
Inventory
Database
of
the
estimated
existing
combustion
turbine
population
is
approximately
60
percent.
The
profiles
presented
below
4­
2
are
based
in
the
2,072
combustion
turbines
in
the
Inventory
Database
above
1
MW
of
capacity
with
valid
information
for
inclusion
in
the
analyses
conducted
for
this
rule.

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.


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.


Fuel
type:
Natural
gas
is
the
most
common
fuel
consumed
by
units
in
the
population.
About
28
percent
(
579
units)
use
distillate
oil,
which
is
more
commonly
known
as
diesel
fuel.
A
relatively
small
number
(
53
units)
consume
other
fuels,
such
as
landfill
gas,
crude
oil,
and
residual
fuel
oil.

Although
only
28
percent
of
units
use
distillate
oil,
in
terms
of
the
total
MW
capacity
of
the
population,
distillate
oil
fuels
a
disproportionate
percentage,
nearly
43
percent.
This
implies
either
that
many
of
the
mid­
to
large­
sized
turbines
are
fueled
by
distillate
oil,
that
natural
gas
is
more
common
in
smaller
units,
or
that
a
combination
of
the
two
explains
this
fact.


Hours
of
Operation:
Nearly
half
of
all
turbines
(
925
units)
operate
more
than
7,500
hours
per
year
(
see
Table
4­
2).
A
year
consists
of
approximately
8,760
hours.
Although
488
units
operate
less
than
500
hours
per
year,
only
414
units
operate
between
500
and
7,500
hours
per
year.
Information
on
annual
hours
of
operation
was
unavailable
for
245
(
or
12
percent)
of
the
2,072
units.
Because
the
4­
3
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
4
785
215
227
325
242
221
57
0
100
200
300
400
500
600
700
800
900
1
to
5
5
to
10
10
to
25
25
to
50
50
to
100
100
to
200
>
200
MW
Capacity
Range
Number
of
Units
Figure
4­
1.
Number
of
Units
by
MW
Capacity
Table
4­
2.
Stationary
Combustion
Turbine
Projections
Total
Number
of
New
Units
Utility
Turbines
Base
load
energy
(
combined
cycle)
136
Peak
power
(
simple
cycle)
66
Total
utility
turbines
202
Nonutility
Turbines
Small
3
Medium
9
Large
4
Total
nonutility
turbines
16
Total
in
5th
year
218
Average
per
year
44
4­
5
vast
majority
of
those
units
were
located
on
pipelines,
which
operate
24
hours
a
day,
or
at
electric
utility
plants,
many
of
the
245
units
probably
operate
more
than
7,500
hours
a
year.


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.


Simple
vs.
combined
cycle:
Information
was
not
available
from
the
Inventory
Database
on
the
type
of
turbine.
However,
based
on
industry
sales
data,
a
breakdown
of
1998
industry
orders
shows
that
32
percent
of
the
orders
were
for
peak
SCCTs
and
the
remaining
68
percent
were
for
CCCTs.
Sixty
percent
of
the
buyers
were
merchant
plants,
10
percent
were
independent
power
producers
(
IPPs),
and
the
remaining
30
percent
were
rate­
base
utility
generators
(
Siemens
Westinghouse,
1999).

4.2
Projected
Growth
of
Combustion
Turbines
The
Agency
estimates
there
will
be
a
total
of
218
new
stationary
combustion
turbines
over
the
next
5
years
(
see
Table
4­
2).
This
projection
is
based
on
information
supplied
from
the
turbine
manufacturing
industry,
state
permit
data
compiled
by
EPA,
and
Gas
Turbine
World's
1999­
2000
Handbook
on
Gas
Turbine
Orders
and
Installations.

4.2.1
Comparison
of
Alternative
Growth
Estimates
Specific
growth
projections
for
combustion
turbines
vary
with
respect
to
the
timing
of
the
construction
of
new
units.
Table
4­
3
shows
that
according
to
1998
projections
made
by
the
Department
of
Energy
(
DOE),
U.
S.
electric
utilities
were
planning
to
install
316
new
units
between
1998
and
2007.
The
units
are
expected
to
average
165
MW.
The
majority
of
these
units
are
projected
to
be
CCCTs
(
DOE,
1999d).
According
to
a
second
study,
the
Department
of
Energy
projects
300
GW
of
new
generation
capacity
will
be
needed
by
the
year
2020
(
Reuters
News
Service,
1999).

Because
the
electric
utility
industry
accounts
for
over
90
percent
of
the
projected
new
units
and
97
percent
of
the
projected
new
capacity
in
MW
and
nearly
half
of
the
existing
units
and
72
percent
of
the
existing
capacity
in
MW,
the
remainder
of
this
section
focuses
on
the
trends
in
the
electric
utility
industry.
4­
6
488
106
111
90
107
925
0
100
200
300
400
500
600
700
800
900
1,000
<
500
500
to
1,500
1,500
to
3,500
3,500
to
5,500
5,500
to
7,500
>
7,500
Annual
Hours
of
Unit
Operation
Number
of
Units
Figure
4­
3.
Number
of
Units
by
Annual
Hours
of
Operation
Note:
Excludes
245
units
for
which
information
on
annual
hours
of
operation
was
unavailable.
132
228
183
624
149
294
217
0
100
200
300
400
500
600
700
<
500
500
to
5,000
5,000
to
10,000
10,000
to
50,000
50,000
to
100,000
100,000
to
500,000
>
500,000
Annual
MWh
Equivalent
Number
of
Units
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.
4­
7
Table
4­
3.
Planned
Capacity
Additions
at
U.
S.
Public
Utilities,
1998
through
2007,
as
of
January
1,
1998
Year
Number
of
Units
Generator
Nameplate
Capacity
(
MW)

U.
S.
Total
316
52,044
1998
60
2,020
1999
25
2,298
2000
31
3,875
2001
31
5,843
2002
35
5,978
2003
34
8,201
2004
26
5,707
2005
31
7,576
2006
22
5,879
2007
21
4,667
Notes:
Total
may
not
equal
the
sum
of
components
because
of
independent
rounding.

Source:
U.
S.
Department
of
Energy,
Energy
Information
Administration.
1999c.
Electric
Power
Annual
1998.
Volumes
I
and
II.
Washington,
DC:
U.
S.
Department
of
Energy.

4.3
Number
of
Affected
Stationary
Combustion
Turbines
We
estimate
that
20
percent
of
the
stationary
combustion
turbines
affected
by
this
rule
will
be
located
at
major
sources.
This
estimate
is
based
on
an
examination
by
EPA
of
permit
data,
which
indicated
that
utility
turbines
will
primarily
be
installed
at
greenfield
power
plants
where
no
other
sources
of
HAP
emissions
will
be
present.
Greenfield
power
plants
that
had
a
total
capacity
of
more
than
the
calculated
MW
were
assumed
to
be
major
sources,
while
those
that
were
less
were
assumed
to
be
area
sources.
Industrial
turbines
were
all
assumed
to
go
into
brownfield
sites
that
were
already
major
HAP
sites.
Based
on
this
analysis
of
permit
data,
it
is
expected
that
twenty
percent
of
new
turbines
will
be
major
sources.
As
a
result,
the
environmental
and
energy
impacts
presented
here
reflect
these
estimates.
Existing
sources
are
not
required
to
comply
with
emission
limitations,
recordkeeping,
or
reporting
requirements
in
the
rule.

For
new
stationary
combustion
turbines,
218
new
turbines
are
projected
to
come
online
by
the
fifth
year
after
promulgation
as
shown
in
Table
4­
2;
20
percent
or
44
are
4­
8
expected
to
be
at
major
sources.
All
of
these
44
turbines
are
expected
to
require
installation
of
an
oxidation
catalyst
to
meet
the
emission
limitations
in
the
rule
for
new
sources.
A
breakdown
of
these
44
turbines
shows
that
27
new
base
load
energy
turbines
and
13
peak
power
turbines
will
be
affected
in
the
next
5
years.
For
new
nonutility
turbines,
3
new
units
will
be
affected
in
the
next
5
years.

Based
on
the
description
in
the
previous
two
paragraphs,
44
stationary
combustion
turbines
will
have
to
apply
an
oxidation
catalyst
to
meet
the
emission
limitations
associated
with
this
rule.
In
the
fifth
year
after
promulgation,
those
44
turbines
are
expected
to
require
performance
testing.
This
total
includes
the
approximately
9
new
turbines
(
which
is
20
percent
of
44)
that
come
online
that
year
and
are
required
to
conduct
an
annual
performance
test
to
demonstrate
compliance.

4.4
HAP
and
Other
Emission
Reductions
The
rule
will
reduce
total
national
HAP
emissions
by
an
estimated
98
tons/
year
in
the
fifth
year
after
the
standards
are
promulgated.
The
emissions
reductions
achieved
by
the
rule
would
be
come
from
the
sources
that
install
an
oxidation
catalyst
control
system.
We
estimate
that
new
stationary
combustion
turbines
located
at
a
major
source
will
install
oxidation
catalyst
control
to
comply
with
the
standards.

To
estimate
the
baseline
HAP
emissions
and
reductions
associated
with
this
rule,
national
HAP
emissions
in
the
absence
of
the
rule
were
calculated
using
an
emission
factor
from
the
emissions
database.
We
assumed
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
rule.
It
was
also
assumed
that
half
of
the
turbines
installed
in
the
next
five
years
would
be
simple
cycle
and
the
other
half
combined
cycle.
We
then
assumed
a
HAP
reduction
of
95
percent,
achieved
by
using
oxidation
catalyst
emission
control
devices,
and
applied
this
reduction
to
the
baseline
HAP
emissions
to
estimate
total
national
HAP
emission
reduction.

In
addition
to
HAP
emission
reductions,
the
rule
will
reduce
criteria
air
pollutant
emissions,
primarily
CO
emissions,
though
there
will
be
a
very
small
amount
of
PM
and
VOC
emission
reductions
as
well.
Oxidation
catalyst
control
systems
have
been
demonstrated
to
reduce
CO
emissions
by
95
percent.
PM
emissions
are
very
low
from
stationary
combustion
turbines
since
virtually
all
of
the
affected
turbines
burn
natural
gas
or
4­
9
similar
gaseous
fuels.
Very
few
existing
turbines
burn
oils,
and
we
do
not
believe
any
new
affected
turbines
in
the
next
five
years
will
exclusively
use
an
oil
fuel.
Any
turbines
that
are
built
to
use
oils
are
likely
to
be
dual
fuel­
fired,
which
means
they
can
operate
off
of
two
different
types
of
fuel
that
are
likely
to
be
natural
gas
and
diesel
oil.
In
any
event,
oxidation
catalyst
control
systems
will
reduce
PM
emissions
by
25
to
50
percent.
Oxidation
catalyst
control
systems
will
reduce
VOC
emissions
as
well.
The
control
efficiency
depends
on
the
specific
compounds.
However,
we
believe
that
VOC
(
and
hydrocarbon
[
HC])
emissions
from
combustion
turbines
that
are
not
HAP
are
very
low
and
we
have
been
unable
to
quantify
emission
reductions
for
these
pollutants.

4.5
Energy
and
Other
Impacts
from
Direct
Application
of
Control
Measures
The
only
energy
impact
from
the
direct
application
of
oxidation
catalyst
control
systems
is
the
pressure
drop
across
the
oxidation
catalyst
bed
of
typically
1
to
1­
1/
2
inches
of
water
pressure
drop.
According
to
information
contained
in
the
Gas
Turbine
World
1999­
2000
Handbook
(
GTWH),
a
rough
rule
of
thumb
for
heavy
frame
turbines,
which
are
the
types
of
turbines
which
we
believe
will
mostly
be
installed
in
the
next
five
years,
is
that
every
four
inches
of
water
pressure
outlet
loss
is
equivalent
to
a
0.6
percent
heat
rate
loss
resulting
in
a
0.6
percent
power
output
loss.
(
Heat
rate
is
a
measure
of
the
amount
of
inlet
heat
input
to
a
turbine
required
to
produce
a
certain
amount
of
power.
When
the
turbine
heat
rate
increases,
more
inlet
heat
is
required
to
produce
the
same
amount
of
power
resulting
in
a
decrease
in
the
thermal
efficiency.)

Vendors
state
that
an
oxidation
catalyst
system
can
be
designed
so
that
the
maximum
pressure
drop
across
the
control
device
does
not
exceed
1.5
inches
of
water
pressure
drop
including
the
catalyst
system
and
housing.
Therefore,
the
heat
rate
increase
is
expected
to
be
about
0.15
percent
(
1/
4
x
0.6
percent)
increase
per
inch
of
water
pressure
drop
increase
in
the
turbine
outlet.
(
Other
studies
by
Gas
Technology
Institute
have
indicated
that
this
value
is
0.105
percent
per
inch
of
turbine
outlet
pressure
drop.
However
we
chose
to
use
the
GTWH
value
for
this
calculation.)
Therefore
for
a
1.5
inch
pressure
drop
across
an
oxidation
catalyst
system,
the
power
output
loss
is
estimated
to
be
0.225
percent
(
1.5
x
0.15).
This
represents
the
energy
impact
which
is
very
low.

4.5.1
Water
Impacts
Oxidation
catalyst
systems
do
not
use
water
or
produce
water
so
the
water
impacts
are
expected
to
be
very
low.
4­
10
4.5.2
Solid
Waste
Impacts
Oxidation
catalyst
are
made
with
precious
metals.
When
the
catalyst
charge
is
replaced
(
about
every
six
years),
the
old
catalyst
is
usually
sent
to
a
catalyst
metal
processor
who
reclaims
the
precious
metals
and
the
owner/
operator
gets
a
reimbursement
from
the
processor.
Therefore,
because
the
spent
catalyst
is
recycled,
the
solid
waste
impact
is
very
small.

4.6
Trends
in
the
Electric
Utility
Industry
Most
industry
and
government
forecasts
project
sizable
growth
of
new
electric
power
generation
capacity
in
the
near
future
to
meet
the
increase
in
consumer
demand
for
electricity
and
the
retirement
of
aging
coal
and
nuclear
units.
Experts
agree
that
this
new
capacity
will
mainly
come
from
SCCTs
and
CCCT
units
fueled
by
natural
gas.
Two
factors
have
contributed
to
recent
and
projected
dominance
of
gas
combustion
turbines
to
meet
the
demand
for
new
generation
capacity:


Technology
advances
in
combustion
turbines
have
increased
efficiency.


Deregulation
of
the
electric
utility
industry
has
opened
the
market
to
smaller
independent
operators
with
applications
ideally
suited
for
combustion
turbines.

Over
the
next
5
years
deregulation
of
the
electric
power
industry
will
be
the
main
factor
influencing
the
growth
of
combustion
turbines
to
generate
electric
power.
Deregulation
is
influencing
the
demand
for
utility
combustion
turbines
in
the
following
ways:

1.
Competitive
markets
for
wholesale
power
are
leading
to
the
replacement
of
less­
efficient
coal
and
nuclear
power
plants.
Because
of
advances
in
gas
turbine
technology,
new
SCCTs
and
CCCTs
are
more
economical
compared
to
new
oil
and
coal
power
plants
and
less­
efficient
existing
plants.

2.
Competitive
markets
for
wholesale
power
have
led
to
an
increased
demand
for
bulk
transmission
resources.
However,
economic
and
political
factors
continue
to
limit
the
growth
in
new
transmission
corridors.
Combustion
turbine
units
that
are
smaller
in
size
and
more
environmentally
friendly
(
compared
to
coal
or
nuclear
power
plants)
can
be
placed
throughout
the
grid
(
referred
to
as
distributed
generation)
to
alleviate
transmission
constraints.
1Most
industry
experts
agree
that
(
at
least
in
the
short
run)
deregulation
will
lead
to
four
major
regional
power
markets
in
the
U.
S.
Bulk
transmission
interfaces
between
these
four
regional
markets
will
continue
to
be
capacity
strained,
implying
that
electricity
prices
may
continue
to
vary
from
region
to
region.
In
addition,
there
will
be
local
metropolitan
areas
or
geographically
isolated
areas,
such
as
San
Francisco,
where
transmission
constraints
will
restrict
"
perfect"
competition.
In
these
areas,
small­
scale
distributed
generation,
such
as
CCCTs,
will
be
able
to
command
price
premiums
for
electric
power.

4­
11
3.
Deregulation
has
opened
the
market
to
merchant
power
producers
and
IPPs.
The
smaller­
scale
combustion
turbine
power
plants
are
ideal
for
these
market
players
who
generally
serve
niche
markets
where
there
are
capacity
shortages
or
where
industrial
steam
loads
are
high.
1
5­
1
SECTION
5
PROFILES
OF
AFFECTED
INDUSTRIES
This
section
contains
profiles
of
the
major
industries
affected
by
the
regulation
of
stationary
combustion
turbines.
The
Agency
anticipates
that
most
of
the
direct
costs
of
the
regulation
will
be
borne
by
the
electric
services
(
NAICS
22111)
sector.
However,
the
crude
oil
and
natural
gas
extraction
(
NAICS
211)
and
natural
gas
pipelines
(
NAICS
486)
sectors
will
be
indirectly
affected
through
changes
in
industry
production
and
fuel
switching.
Together,
these
energy
sectors
account
for
about
90
percent
of
the
existing
combustion
turbines
(
greater
than
1
MW)
identified
by
the
Agency
in
the
Inventory
Database.
The
remaining
combustion
turbines
are
spread
across
a
wide
variety
of
industries,
most
notably
chemicals
and
allied
products,
petroleum
products,
health
services,
and
national
security
agencies,
and
are
primarily
used
for
self­
generated
electricity
or
co­
generated
electricity
and
process
steam.
Direct
costs
on
these
industries
are
expected
to
be
minimal.

The
Agency
projects
that
growth
in
new
combustion
turbines
that
will
be
affected
by
the
regulation
will
also
be
concentrated
in
the
electric
services,
crude
oil
and
natural
gas
extraction,
and
natural
gas
industries.
This
section
contains
background
information
on
these
three
industries
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
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
5­
2
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
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
5­
3
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
capitalintensive
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
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.
5­
4
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.
Large
C/
I
Customers
Small
C/
I
Customers
Residential
Customers
Transformer
Generation
Electricity
Distribution
High
Voltage
Lines
Transmission
Power
Plants
Figure
5­
1.
Traditional
Electric
Power
Industry
Structure
5­
5
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
gasdesulfurization
systems,
coal
will
likely
remain
the
fuel
of
choice
for
most
existing
generating
facilities
over
the
near
term.

Natural
gas
accounts
for
approximately
10
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.

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.

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

system
planning
and
expanding,


maintaining
power
quality
and
stability,
and

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.
1The
electric
power
supply
chain
includes
all
generation,
transmission,
distribution,
administrative,
and
market
activities
needed
to
deliver
electric
power
to
consumers.

5­
6
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.
1
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.

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.

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.
5­
7
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
three­
quarters
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
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
8
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.
Electricity
Waste
Heat
Intersystem
Exchange
Private
Lines
 
 
 
Surplus
Electricity
Purchased
 
Fuel
Source:
Coal,
Natural
Gas,
Water,
etc.

Surplus
Electricity
Purchased
Self­
Generation
Large
C/
I
Customers
Small
C/
I
Customers
Residential
Customers
Local
Distribution
System
Reliability
and
Control
Bulk
Transmission
IPP
Generation
Local
Utility
Generation
Competing
Utility
Generation
(
outside
service
territory)

Figure
5­
2.
Electric
Utility
Industry
5­
9
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
1985
and
1995,
nonutility
generators
increased
their
share
of
electricity
generation
from
4
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
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
10
a
Includes
facilities
classified
in
more
than
one
of
the
following
FERC
designated
categories:
cogenerator
QF,
small
power
producer
QF,
or
exempt
wholesale
generator.
Cogen
=
Cogenerator.
EWG
=
Exempt
wholesale
generator.
Other
Non­
QF
=
Nocogenerator
Non­
QF.
QF
=
Qualifying
facility.
SPP
=
Small
power
producer.
Note:
Sum
of
components
may
not
equal
total
due
to
independent
rounding.
Classes
for
nonutility
generation
are
determined
by
the
class
of
each
generating
unit.
Sources:
Utility
data:
U.
S.
Department
of
Energy,
Energy
Information
Administration
(
EIA).
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);
1985
nonutility
data:
Shares
of
generation
estimated
by
EIA;
total
generation
from
Edison
Electric
Institute
(
EEI).
1998.
Statistical
Yearbook
of
the
Electric
Utility
Industry
1998.
November.
Washington,
DC;
1995
nonutility
data:
U.
S.
Department
of
Energy,
Energy
Information
Administration
(
EIA).
1996b.
Electric
Power
Annual
1995.
Volumes
I
and
II.
DOE/
EIA­
0348(
95)/
1.
Washington,
DC:
U.
S.
Department
of
Energy.

Figure
5­
3.
Utility
and
Nonutility
Generation
and
Shares
by
Class,
1988
and
1998
5­
11
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
self­
generate
power
using
combustion
turbines
and
sell
excess
power
back
to
the
grid.
As
with
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.
5­
12
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
highvoltage
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
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
5­
13
(
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
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.
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
14
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
transportation,
communications,
finance,
and
energy.
The
major
drivers
for
deregulation
of
electric
power
included
the
following:

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


the
erosion
of
economies
of
scale
in
generation
with
advances
in
combustion
turbine
technology;


complexity
of
providing
a
regulated
industry
with
the
incentives
to
make
socially
efficient
investment
choices;


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
5­
15

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
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:


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.


Individual
transactions
will
replace
aggregated
supply
meeting
aggregated
demand.
It
will
be
necessary
to
continuously
assess
each
individual's
performance.


Transaction
sizes
will
shrink.
Instead
of
dealing
only
in
hundreds
and
thousands
of
MW,
it
will
be
necessary
to
accommodate
transactions
of
a
few
MW
and
less.
2Nonutility
power
producers
have
approximately
10
percent
of
the
capacity
of
utility
power
producers.

5­
16

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.
2
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
electricitygenerating
capacity.
Table
5­
5
illustrates
that,
from
1995
through
1999,
manufacturing
facilities
consistently
had
the
capacity
to
produce
over
two­
thirds
of
nonutility
electricity
generation.

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.
5­
17
Table
5­
4.
Industry
Capability
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.
2000.
Electric
Power
Annual,
1999,
Vol.
2.
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).
2000.
Electric
Power
Annual
1999,
Volume
II.
Washington,
DC:
U.
S.
Department
of
Energy.
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
solidsa
15
334
Petroleum
only
137
22,476
Gas
only
117
10,840
Other
solids/
coala
1
2
Solids/
petroleumb
72
10,796
Solids/
gasb
232
36,763
Solids/
petroleum/
gasb
1
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
onlya
1
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
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
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
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.

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.
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
 
 
Renewablea
10
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
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
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
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
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).

5.2
Oil
and
Gas
Extraction
(
NAICS
211)

The
crude
petroleum
and
natural
gas
industry
encompasses
the
oil
and
gas
extraction
process
from
the
exploration
for
oil
and
natural
gas
deposits
through
the
transportation
of
the
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.
5­
24
product
from
the
production
site.
The
primary
products
of
this
industry
are
natural
gas,
natural
gas
liquids,
and
crude
petroleum.

5.2.1
Introduction
The
United
States
is
home
to
half
of
the
major
oil
and
gas
companies
operating
around
the
globe.
Although
small
firms
account
for
nearly
45
percent
of
U.
S.
crude
oil
and
natural
gas
output,
the
domestic
oil
and
gas
industry
is
dominated
by
20
integrated
petroleum
and
natural
gas
refiners
and
producers,
such
as
Exxon
Mobil,
BP
Amoco,
and
Chevron
(
Lillis,
1998).
Despite
the
presence
of
many
large
global
players,
the
industry
experiences
a
more
turbulent
business
cycle
than
most
other
major
U.
S.
industries.
Because
the
industry
imports
60
percent
of
the
crude
oil
used
as
an
input
into
refineries,
it
is
susceptible
to
fluctuations
in
crude
oil
output
and
prices,
which
are
strongly
influenced
by
the
Organization
of
Petroleum
Exporting
Countries
(
OPEC).
OPEC
is
a
cartel
consisting
of
most
of
the
world's
largest
petroleum­
producing
countries
that
acts
to
increase
the
profits
of
member
countries.
In
contrast,
natural
gas
markets
in
the
United
States
are
competitive
and
relatively
stable.
Most
natural
gas
used
in
the
United
States
comes
from
domestic
and
Canadian
sources.

NAICS
211
includes
five
major
industry
groups
(
see
Table
5­
11):


NAICS
211111
(
SIC
1311):
Crude
petroleum
and
natural
gas.
Firms
in
this
industry
are
primarily
involved
in
operating
oil
and
gas
fields.
These
firms
may
also
explore
for
crude
oil
and
natural
gas,
drill
and
complete
wells,
and
separate
crude
oil
and
natural
gas
components
from
natural
gas
liquids
and
produced
fluids.


NAICS
211112
(
SIC
1321):
Natural
gas
liquids
(
NGL).
NGL
firms
separate
NGLs
from
crude
oil
and
natural
gas
at
the
site
of
production.
Propane
and
butane
are
NGLs.


NAICS
213111
(
SIC
1381):
Drilling
oil
and
gas
wells.
Firms
in
this
industry
drill
oil
and
natural
gas
wells
on
a
contract
or
fee
basis.


NAICS
213112/
54136
(
SIC
1382):
Oil
and
gas
field
exploration
services.
Firms
in
this
industry
perform
geological,
geophysical,
and
other
exploration
services.


NAICS
213112
(
SIC
1389):
Oil
and
gas
field
services,
not
elsewhere
classified.
Companies
in
this
industry
perform
services
on
a
contract
or
fee
basis
that
are
not
classified
in
the
above
industries.
Services
include
drill­
site
preparations,
such
as
building
foundations
and
excavating
pits,
and
maintenance.
5­
25
In
1997,
more
than
6,800
crude
oil
and
natural
gas
extraction
companies
(
NAICS
211111)
generated
$
75
billion
in
revenues.
Revenues
for
1997
were
approximately
5
percent
higher
than
revenues
in
1992,
although
the
number
of
companies
and
employees
declined
11.5
and
42.5
percent,
respectively.

Table
5­
12
shows
the
NGL
extraction
industry
(
NAICS
211112)
experienced
a
decline
in
the
number
of
companies,
establishments,
and
employees.
The
industry's
revenues
declined
nearly
8.0
percent
between
1992
and
1997,
from
$
27
billion
per
year
to
$
24.8
billion
per
year.

Revenues
for
NAICS
213111,
drilling
oil
and
gas
wells,
more
than
doubled
between
1992
and
1997.
In
1992,
the
industry
employed
47,700
employees
at
1,698
companies
and
generated
$
3.6
billion
in
annual
revenues.
By
the
end
of
1997,
the
industry's
annual
revenues
were
$
7.3
billion,
a
106
percent
improvement.
Although
the
total
number
of
companies
and
establishments
decreased
from
1992
levels,
industry
employment
increased
13
percent
to
53,865.

The
recent
transition
from
the
SIC
system
to
the
North
American
Industrial
Classification
System
(
NAICS)
changed
how
some
industries
are
organized
for
information
collection
purposes
and
thus
how
certain
economic
census
data
are
aggregated.
Some
SIC
codes
were
combined,
others
were
separated,
and
some
activities
were
classified
under
one
NAICS
code
and
the
remaining
activities
classified
under
another.
The
oil
and
gas
field
services
industry
is
an
example
of
an
industry
code
that
was
reclassified.
Under
NAICS,
SIC
1382,
Oil
and
Gas
Exploration
Services,
and
SIC
1389,
Oil
and
Gas
Services
Not
Elsewhere
Classified,
were
combined.
The
geophysical
surveying
and
mapping
services
portion
of
SIC
Table
5­
11.
Crude
Petroleum
and
Natural
Gas
Industries
Likely
to
Be
Affected
by
the
Regulation
SIC
NAICS
Description
1311
211111
Crude
Petroleum
and
Natural
Gas
1321
211112
Natural
Gas
Liquids
1381
213111
Drilling
Oil
and
Gas
Wells
1382
213112
Oil
and
Gas
Exploration
Services
54136
Geophysical
Surveying
and
Mapping
Services
1389
213112
Oil
and
Gas
Field
Services,
N.
E.
C.
5­
26
1382
was
reclassified
and
grouped
into
NAICS
54136.
The
adjustments
to
SIC
1382/
89
have
made
comparison
between
the
1992
and
1997
economic
censes
difficult
at
this
time.
The
U.
S.
Census
Bureau
has
yet
to
publish
a
comparison
report.
Thus,
for
this
industry
only
1997
census
data
are
presented.
For
that
year,
nearly
6,400
companies
operated
under
SIC
1382/
89
(
NAICS
213112),
employing
more
than
100,000
people
and
generating
$
11.5
billion
in
revenues.
Table
5­
12.
Summary
Statistics,
Crude
Oil
and
Natural
Gas
Extraction
and
Related
Industries
NAICS
Industry
Number
of
Companies
Number
of
Establishments
Revenues
($
1997
103)
Employees
211111
Crude
Oil
and
Natural
Gas
Extraction
1992
7,688
9,391
71,622,600
174,300
1997
6,802
7,781
75,162,580
100,308
211112
Natural
Gas
Liquid
Extraction
1992
108
591
26,979,200
12,000
1997
89
529
24,828,503
10,549
213111
Drilling
Oil
and
Gas
Wells
1992
1,698
2,125
3,552,707
47,700
1997
1,371
1,638
7,317,963
53,865
213112
Oil
and
Gas
Field
Services
1997
6,385
7,068
11,547,563
106,339
Sources:
U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1999a.
1997
Economic
Census,
Mining
Industry
Series:
Crude
Petroleum
and
Natural
Gas
Extraction.
EC97N­
2111A.
Washington,
DC:
U.
S.
Department
of
Commerce.

U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1995a.
1992
Census
of
Mineral
Industries,
Industry
Series:
Crude
Petroleum
and
Natural
Gas.
MIC92­
I­
13A.
Washington,
DC:
U.
S.
Department
of
Commerce.
5­
27
5.2.2
Supply
Side
Characterizing
the
supply
side
of
the
industry
involves
describing
the
production
processes,
the
types
of
output,
major
by­
products,
costs
of
production,
and
capacity
utilization.

5.2.2.1
Production
Processes
There
are
four
major
processes
in
the
oil
and
gas
extraction
industry:
exploration,
well
development,
production,
and
site
abandonment
(
EPA,
1999b).
Exploration
is
the
search
for
rock
formations
associated
with
oil
and/
or
natural
gas
deposits.
Nearly
all
oil
and
natural
gas
deposits
are
located
in
sedimentary
rock.
Certain
geological
clues,
such
as
porous
rock
with
an
overlying
layer
of
low­
permeability
rock,
help
guide
exploration
companies
to
a
possible
source
of
hydrocarbons.
While
exploring
a
potential
site,
the
firm
conducts
geophysical
prospecting
and
exploratory
drilling.

After
an
economically
viable
field
is
located,
the
well
development
process
begins.
Well
holes,
or
well
bores,
are
drilled
to
a
depth
of
between
1,000
and
30,000
feet,
with
an
average
depth
of
about
5,500
feet
(
EPA,
1999b).
The
drilling
procedure
is
the
same
for
both
onshore
and
offshore
sites.
A
steel
or
diamond
drill
bit,
which
may
be
anywhere
between
4
inches
and
3
feet
in
diameter,
is
used
to
chip
off
rock
to
increase
the
depth
of
the
hole.
The
drill
bit
is
connected
to
the
rock
by
several
pieces
of
hardened
pipe
known
collectively
as
the
drill
string.
As
the
hole
is
drilled,
casing
is
placed
in
the
well
to
stabilize
the
hole
and
prevent
caving.
Drilling
fluid
is
pumped
down
through
the
center
of
the
drill
string
to
lubricate
the
equipment.
The
fluid
returns
to
the
surface
through
the
space
between
the
drill
string
and
the
rock
formation
or
casing.
Once
the
well
has
been
drilled,
rigging,
derricks,
and
other
production
equipment
are
installed.
Onshore
fields
are
equipped
with
a
pad
and
roads;
ships,
floating
structures,
or
a
fixed
platform
are
procured
for
offshore
fields.

Production
is
the
process
of
extracting
hydrocarbons
through
the
well
and
separating
saleable
components
from
water
and
silt.
Oil
and
natural
gas
are
naturally
occurring
coproducts
and
most
production
sites
handle
crude
oil
and
gas
from
more
than
one
well.
Once
the
hydrocarbons
are
brought
to
the
surface,
they
are
separated
into
a
spectrum
of
substances,
including
liquid
hydrocarbons,
gas,
and
water
and
other
nonsaleable
constituents.
After
being
extracted,
crude
oil
is
always
delivered
to
a
refinery
for
processing;
natural
gas
may
be
processed
at
the
field
or
at
a
natural
gas
processing
plant
to
remove
impurities.
Natural
gas
is
separated
from
crude
oil
by
passing
the
hydrocarbons
through
one
or
two
decreasing
pressure
chambers.
Excess
water
is
removed
from
the
crude
oil,
at
which
point
the
oil
is
5­
28
about
98
percent
pure,
a
purity
sufficient
for
storage
or
transport
to
a
refinery
(
EPA,
1999b).
Excess
water
is
returned
to
the
well
to
facilitate
the
production
process,
but
silt
is
discarded.
If
enough
natural
pressure
does
not
exist
in
the
reservoir
to
force
the
hydrocarbons
through
the
well,
then
the
reservoir
is
pressurized
using
pumps
or
excess
water
to
lift
the
hydrocarbons.

Natural
gas
is
conditioned
using
a
dehydration
and
a
sweetening
process,
which
removes
hydrogen
sulfide
and
carbon
dioxide,
so
that
it
is
of
high
enough
quality
to
pass
through
transmission
systems.
The
gas
may
be
conditioned
at
the
field
or
at
one
of
the
623
operating
gas­
processing
facilities
located
in
gas­
producing
states,
such
as
Texas,
Louisiana,
Oklahoma,
and
Wyoming.
These
plants
also
produce
the
nation's
NGLs,
propane
and
butane
(
NGSA
et
al.,
2000c).

Site
abandonment
occurs
when
a
site
lacks
the
potential
to
produce
economic
quantities
of
natural
gas
or
when
a
production
well
is
no
longer
economically
viable.
The
well(
s)
are
plugged
using
long
cement
plugs
and
steel
plated
caps,
and
supporting
production
equipment
is
disassembled
and
moved
offsite.

5.2.2.2
Types
of
Output
The
oil
and
gas
industry's
principal
products
are
crude
oil,
natural
gas,
and
NGLs
(
see
Tables
5­
13
and
5­
14).
Refineries
process
crude
oil
into
several
petroleum
products.
These
products
include
motor
gasoline
(
40
percent
of
crude
oil);
diesel
and
home
heating
oil
(
20
percent);
jet
fuels
(
10
percent);
waxes,
asphalts,
and
other
nonfuel
products
(
5
percent);
feedstocks
for
the
petrochemical
industry
(
3
percent);
and
other
lesser
products
(
DOE,
EIA,
1999d).

Natural
gas
is
produced
from
either
oil
wells
(
known
as
"
associated
gas")
or
wells
that
are
drilled
for
the
primary
purpose
of
obtaining
natural
gas
(
known
as
"
nonassociated
gas")
(
see
Table
5­
14).
Methane
is
the
predominant
component
of
natural
gas
(
about
85
percent),
but
ethane
(
about
10
percent),
propane,
and
butane
are
also
significant
components
(
see
Table
5­
13).
Propane
and
butane,
the
heavier
components
of
natural
gas,
exist
as
liquids
when
cooled
and
compressed.
These
latter
two
components
are
usually
separated
and
processed
as
NGLs
(
EPA,
1999b).
5­
29
Table
5­
13.
U.
S.
Supply
of
Crude
Oil
and
Petroleum
Products
(
103
barrels),
1998
Commodity
Field
Production
Refinery
Production
Imports
Crude
Oil
2,281,919
3,177,584
Natural
Gas
Liquids
642,202
245,918
82,081
Ethane/
ethylene
221,675
11,444
6,230
Propane/
propylene
187,369
200,815
50,146
Normal
butane/
butylene
54,093
29,333
8,612
Isobutane/
isobutylene
66,179
4,326
5,675
Other
112,886
11,418
Other
Liquids
69,477
211,266
Finished
Petroleum
Products
69,427
5,970,090
437,515
Finished
motor
gasoline
69,427
2,880,521
113,606
Finished
aviation
gasoline
7,118
43
Jet
fuel
556,834
45,143
Kerosene
27,848
466
Distillate
fuel
oil
1,249,881
76,618
Residual
fuel
oil
277,957
100,537
Naptha
89,176
22,388
Other
oils
78,858
61,554
Special
napthas
24,263
2,671
Lubricants
67,263
3,327
Waxes
8,355
613
Petroleum
coke
260,061
263
Asphalt
and
road
oil
181,910
10,183
Still
gas
239,539
Miscellaneous
products
20,506
103
Total
3,063,025
6,216,008
3,908,446
Source:
U.
S.
Department
of
Energy,
Energy
Information
Administration
(
EIA).
1999f.
Petroleum
Supply
Annual
1998,
Volume
I.
Washington,
DC:
U.
S.
Department
of
Energy.
5­
30
5.2.2.3
Major
By­
products
The
engines
that
provide
pumping
action
at
wells
and
push
crude
oil
and
natural
gas
through
pipes
to
processing
plants,
refineries,
and
storage
locations
produce
HAPs.
HAPs
produced
in
engines
include
formaldehyde,
acetaldehyde,
acrolein,
and
methanol.

5.2.2.4
Costs
of
Production
The
42
percent
decrease
in
the
number
of
people
employed
by
the
crude
oil
and
natural
gas
extraction
industry
between
1992
and
1997
was
matched
by
a
corresponding
40
percent
decrease
in
the
industry's
annual
payroll
(
see
Table
5­
15).
During
the
same
period,
industry
outlays
for
supplies,
such
as
equipment
and
other
supplies,
increased
over
32
percent,
and
capital
expenditures
nearly
doubled.
Automation,
mergers,
and
corporate
downsizing
have
made
this
industry
less
labor­
intensive
(
Lillis,
1998).

Unlike
the
crude
oil
and
gas
extraction
industry,
the
NGL
extraction
industry's
payroll
increased
over
6
percent
even
though
total
industry
employment
declined
12
percent.
The
industry's
expenditures
on
capital
projects,
such
as
investments
in
fields,
production
facilities,
and
other
investments,
increased
11.4
percent
between
1992
and
1997.
The
cost
of
supplies
did,
however,
decrease
13
percent
from
$
23.3
billion
in
1992
to
$
20.3
billion
in
1997.

Employment
increased
in
Drilling
Oil
and
Gas
Wells.
In
1992,
the
industry
employed
47,700
people,
increasing
13
percent
to
53,865
in
1997.
During
a
period
where
industry
revenues
increased
over
100
percent,
the
industry's
payroll
increased
41
percent
and
the
cost
of
supplies
increased
182
percent.
Table
5­
14.
U.
S.
Natural
Gas
Production,
1998
Gross
Withdrawls
Production
(
106
cubic
feet)

From
gas
wells
17,558,621
From
oil
wells
6,365,612
Less
losses
and
repressuring
5,216,477
Total
18,707,756
Source:
U.
S.
Department
of
Energy,
Energy
Information
Administration
(
EIA).
1999e.
Natural
Gas
Annual
1998.
Washington,
DC:
U.
S.
Department
of
Energy.
5­
31
5.2.2.5
Capacity
Utilization
U.
S.
annual
oil
and
gas
production
is
a
small
percentage
of
total
U.
S.
reserves.
In
1998,
oil
producers
extracted
approximately
1.5
percent
of
the
nation's
proven
crude
oil
reserves
(
see
Table
5­
16).
A
slightly
lesser
percentage
of
natural
gas
was
extracted
(
1.4
percent),
and
an
even
smaller
percentage
of
NGLs
was
extracted
(
0.9
percent).
The
Table
5­
15.
Costs
of
Production,
Crude
Oil
and
Natural
Gas
Extraction
and
Related
Industries
NAICS
Industry
Employees
Payroll
($
1997
103)
Cost
of
Supplies
Used,
Purchased
Machinery
Installed,
Etc.
($
1997
103)
Capital
Expenditures
($
1997
103)

211111
Crude
Oil
and
Natural
Gas
Extraction
1992
174,300
$
8,331,849
$
16,547,510
$
10,860,260
1997
100,308
$
4,968,722
$
21,908,191
$
21,117,850
211112
Natural
Gas
Liquid
Extraction
1992
12,000
$
509,272
$
23,382,770
$
609,302
1997
10,549
$
541,593
$
20,359,528
$
678,479
213111
Drilling
Oil
and
Gas
Wells
1992
47,700
$
1,358,784
$
1,344,509
$
286,509
1997
53,865
$
1,918,086
$
7,317,963
$
2,209,300
213112
Oil
and
Gas
Field
Services
1997
106,339
$
3,628,416
$
3,076,039
$
1,165,018
Sources:
U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1999a.
1997
Economic
Census,
Mining,
Industry
Series:
Crude
Petroleum
and
Natural
Gas
Extraction.
EC97N­
2111A.
Washington,
DC:
U.
S.
Department
of
Commerce.

U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1995a.
1992
Census
of
Mineral
Industries,
Industry
Series:
Crude
Petroleum
and
Natural
Gas.
MIC92­
I­
13A.
Washington,
DC:
U.
S.
Department
of
Commerce.
5­
32
United
States
produces
approximately
40
percent
(
2,281
million
barrels)
of
its
annual
crude
oil
consumption,
importing
the
remainder
of
its
crude
oil
from
Canada,
Latin
America,
Africa,
and
the
Middle
East
(
3,178
million
barrels).
Approximately
17
percent
(
3,152
billion
cubic
feet)
of
U.
S.
natural
gas
supply
is
imported.
Most
imported
natural
gas
originates
in
Canadian
fields
in
the
Rocky
Mountains
and
off
the
Coast
of
Nova
Scotia
and
New
Brunswick.

5.2.3
Demand
Side
Characterizing
the
demand
side
of
the
industry
involves
describing
product
characteristics.
Crude
oil,
or
unrefined
petroleum,
is
a
complex
mixture
of
hydrocarbons
that
is
the
most
important
of
the
primary
fossil
fuels.
Refined
petroleum
products
are
used
for
petrochemicals,
lubrication,
heating,
and
fuel.
Petrochemicals
derived
from
crude
oil
are
the
source
of
chemical
products
such
as
solvents,
paints,
plastics,
synthetic
rubber
and
fibers,
soaps
and
cleansing
agents,
waxes,
jellies,
and
fertilizers.
Petroleum
products
also
fuel
the
engines
of
automobiles,
airplanes,
ships,
tractors,
trucks,
and
rockets.
Other
applications
include
fuel
for
electric
power
generation,
lubricants
for
machines,
heating,
and
asphalt
(
Berger
and
Anderson,
1978).
Because
the
market
for
crude
oil
is
global
and
its
price
set
by
OPEC,
slight
increases
in
the
cost
of
producing
crude
oil
in
the
United
States
will
have
little
effect
on
the
price
of
products
that
use
crude
oil
as
an
intermediate
good.
Production
cost
increases
will
be
absorbed
by
the
producer,
not
passed
along
to
consumers.
Table
5­
16.
Estimated
U.
S.
Oil
and
Gas
Reserves,
Annual
Production,
and
Imports,
1998
Category
Reserves
Annual
Production
Imports
Crude
oil
(
106
barrels)
152,453
2,281
3,178
Natural
gas
(
109
cubic
feet)
1,330,930
18,708
3,152
Natural
gas
liquids
(
106
barrels)
26,792
246
NA
Sources:
U.
S.
Department
of
Energy,
Energy
Information
Administration
(
EIA).
1999h.
U.
S.
Crude
Oil,
Natural
Gas,
and
Natural
Gas
Liquids
Reserves
1998
Annual
Report.
Washington,
DC:
U.
S.
Department
of
Energy.

U.
S.
Department
of
Energy,
Energy
Information
Administration
(
EIA).
1999f.
Petroleum
Supply
Annual
1998,
Volume
I.
Washington
DC:
U.
S.
Department
of
Energy.
5­
33
Natural
gas
is
a
colorless,
flammable
gaseous
hydrocarbon
consisting
for
the
most
part
of
methane
and
ethane.
The
largest
single
application
for
natural
gas
is
as
a
domestic
or
industrial
fuel.
However,
other
specialized
applications
have
emerged
over
the
years,
such
as
a
nonpolluting
fuel
for
buses
and
other
motor
vehicles.
Carbon
black,
a
pigment
made
by
burning
natural
gas
with
little
air
and
collecting
the
resulting
soot,
is
an
important
ingredient
in
dyes,
inks,
and
rubber
compounding
operations.
Also,
much
of
the
world's
ammonia
is
manufactured
from
natural
gas;
ammonia
is
used
either
directly
or
indirectly
in
urea,
hydrogen
cyanide,
nitric
acid,
and
fertilizers
(
Tussing
and
Tippee,
1995).

5.2.4
Organization
of
the
Industry
Many
oil
and
gas
firms
are
merging
to
remain
competitive
in
both
the
global
and
domestic
marketplaces.
By
merging
with
their
peers,
these
companies
may
reduce
operating
expenses
and
reap
greater
economies
of
scale
than
they
would
otherwise.
Recent
mergers,
such
as
BP
Amoco
and
Exxon
Mobil,
have
reduced
the
number
of
companies
and
facilities
operating
in
the
United
States.
Currently,
there
are
20
domestic
major
oil
and
gas
companies,
and
only
40
major
global
companies
in
the
world
(
Conces,
2000).
Most
U.
S.
oil
and
gas
firms
are
concentrated
in
states
with
significant
oil
and
gas
reserves,
such
as
Texas,
Louisiana,
California,
Oklahoma,
and
Alaska.

Tables
5­
17
through
5­
20
present
the
number
of
facilities
and
value
of
shipments
by
facility
employee
count
for
each
of
the
four
NIACS
211
industries.
In
1997,
6,802
oil
and
gas
extraction
companies
operated
7,781
facilities,
an
average
of
1.14
facilities
per
company
(
see
Table
5­
17).
Facilities
with
more
than
100
employees
produced
more
than
55
percent
of
the
industry's
value
of
shipments.
Although
the
number
of
companies
and
the
number
of
facilities
operating
in
1992
were
both
greater
then
than
in
1997,
the
distribution
of
shipment
values
by
employee
size
was
similar
to
that
of
1992.

Facilities
employing
fewer
than
50
people
in
the
NGLs
extraction
industry
accounted
for
64
percent,
or
$
15.8
billion,
of
the
industry's
total
value
of
shipments
in
1997
(
see
Table
5­
18).
Four
hundred
eighty­
seven
of
the
industry's
529
facilities
are
in
that
employment
category.
This
also
means
that
a
relatively
small
number
of
larger
facilities
produced
36
percent
of
the
industry's
annual
output,
in
terms
of
dollar
value.
The
number
of
facilities
with
zero
to
four
employees
and
the
number
with
50
or
more
employees
decreased
during
the
5­
year
period,
accounting
for
most
of
the
10.5
percent
decline
in
the
number
of
facilities
from
1992
to
1997.
The
average
number
of
facilities
per
company
was
5.5
and
5.9
in
1992
and
1997,
respectively.
5­
34
As
mentioned
earlier,
the
oil
and
gas
well
drilling
industry's
1997
value
of
shipments
were
106
percent
larger
than
1992'
s
value
of
shipments
(
see
Table
5­
19).
However,
the
number
of
companies
primarily
involved
in
this
industry
declined
by
327
over
5
years,
and
487
facilities
closed
during
the
same
period.
The
distribution
of
the
number
of
facilities
by
employment
size
shifted
towards
those
that
employed
20
or
more
people.
In
1997,
those
facilities
earned
two­
thirds
of
the
industry's
revenues.
Table
5­
17.
Size
of
Establishments
and
Value
of
Shipments,
Crude
Oil
and
Natural
Gas
Extraction
Industry
(
NAICS
211111),
1997
and
1992
1997
1992
Average
Number
of
Employees
in
Facility
Number
of
Facilities
Value
of
Shipments
($
1997
103)
Number
of
Facilities
Value
of
Shipments
($
1997
103)

0
to
4
employees
5,249
$
5,810,925
6,184
$
5,378,330
5
to
9
employees
1,161
$
3,924,929
1,402
$
3,592,560
10
to
19
employees
661
$
4,843,634
790
$
4,504,830
20
to
49
employees
412
$
10,538,529
523
$
8,820,100
50
to
99
employees
132
$
8,646,336
203
$
5,942,130
100
to
249
employees
105
154
$
11,289,730
250
to
499
employees
40
68
$
8,135,850
500
to
999
employees
14
$
41,318,227
46
$
14,693,630
1,000
to
2,499
employees
5
18
$
9,265,530
2,500
or
more
employees
2
3
D
Total
7,781
$
75,162,580
9,391
$
71,622,600
D
=
undisclosed
Sums
do
not
add
to
totals
due
to
independent
rounding.

Sources:
U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1999a.
1997
Economic
Census,
Mining,
Industry
Series:
Crude
Petroleum
and
Natural
Gas
Extraction.
EC97N­
2111A.
Washington,
DC:
U.
S.
Department
of
Commerce.

U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1995a.
1992
Census
of
Mineral
Industries,
Industry
Series:
Crude
Petroleum
and
Natural
Gas.
MIC92­
I­
13A.
Washington,
DC:
U.
S.
Department
of
Commerce.
5­
35
In
1997,
6,385
companies
operated
7,068
oil
and
gas
field
services
facilities,
an
average
of
1.1
facilities
per
company.
Most
facilities
employed
four
or
fewer
employees;
however,
those
facilities
with
20
or
more
employees
accounted
for
the
majority
of
the
industry's
revenues
(
see
Table
5­
20).
Table
5­
18.
Size
of
Establishments
and
Value
of
Shipments,
Natural
Gas
Liquids
Industry
(
NAICS
211112),
1997
and
1992
1997
1992
Average
Number
of
Employees
in
Facility
Number
of
Facilities
Value
of
Shipments
($
1997
103)
Number
of
Facilities
Value
of
Shipments
($
1997
103)

0
to
4
employees
143
$
1,407,192
190
$
2,668,000
5
to
9
employees
101
$
1,611,156
92
$
1,786,862
10
to
19
employees
122
$
4,982,941
112
$
5,240,927
20
to
49
employees
121
$
7,828,439
145
$
10,287,200
50
to
99
employees
35
$
5,430,448
36
$
4,789,849
100
to
249
employees
3
D
14
$
2,205,819
250
to
499
employees
3
D
2
D
500
to
999
employees
1
D
0
 
1,000
to
2,499
employees
0
 
0
 
2,500
or
more
employees
0
 
0
 
Total
529
$
24,828,503
591
$
26,979,200
D
=
undisclosed
Sums
do
not
add
to
totals
due
to
independent
rounding.

Sources:
U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1999b.
1997
Economic
Census,
Mining,
Industry
Series:
Natural
Gas
Liquid
Extraction.
EC97N­
2111b.
Washington,
DC:
U.
S.
Department
of
Commerce.

U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1995b.
1992
Census
of
Mineral
Industries,
Industry
Series:
Natural
Gas
Liquids.
MIC92­
I­
13B.
Washington,
DC:
U.
S.
Department
of
Commerce.
5­
36
5.2.5
Markets
and
Trends
Between
1990
and
1998,
crude
oil
consumption
increased
1.4
percent
per
year,
and
natural
gas
consumption
increased
2.0
percent
per
year.
The
increase
in
natural
gas
consumption
came
mostly
at
the
expense
of
coal
consumption
(
EPA,
1999b).
The
Energy
Information
Administration
(
EIA),
a
unit
of
the
Department
of
Energy,
anticipates
that
natural
gas
consumption
will
continue
to
grow
at
a
similar
rate
through
the
year
2020
to
32
trillion
cubic
feet/
year
(
DOE,
EIA,
1999d).
They
also
expect
crude
oil
consumption
to
grow
at
an
annual
rate
of
less
than
1
percent
over
the
same
period.
Table
5­
19.
Size
of
Establishments
and
Value
of
Shipments,
Drilling
Oil
and
Gas
Wells
Industry
(
NAICS
213111),
1997
and
1992
1997
1992
Average
Number
of
Employees
in
Facility
Number
of
Facilities
Value
of
Shipments
($
1997
103)
Number
of
Facilities
Value
of
Shipments
($
1997
103)

0
to
4
employees
825
$
107,828
1,110
$
254,586
5
to
9
employees
215
$
231,522
321
$
182,711
10
to
19
employees
197
$
254,782
244
$
256,767
20
to
49
employees
200
$
1,008,375
233
$
572,819
50
to
99
employees
95
$
785,804
120
$
605,931
100
to
249
employees
75
$
1,069,895
70
$
816,004
250
to
499
employees
10
$
435,178
19
$
528,108
500
to
999
employees
14
$
1,574,139
5
$
97,254
1,000
to
2,499
employees
6
D
3
$
238,427
2,500
or
more
employees
1
D
 
 
Total
1,638
$
7,317,963
2,125
$
3,552,707
D
=
undisclosed
Sums
do
not
add
to
totals
due
to
independent
rounding.

Sources:
U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1999c.
1997
Economic
Census,
Mining,
Industry
Series:
Drilling
Oil
and
Gas
Wells.
EC97N­
2131A.
Washington,
DC:
U.
S.
Department
of
Commerce.

U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1995c.
1992
Census
of
Mineral
Industries,
Industry
Series:
Oil
and
Gas
Field
Services.
MIC92­
I­
13C.
Washington,
DC:
U.
S.
Department
of
Commerce.
5­
37
5.3
Natural
Gas
Pipelines
The
natural
gas
pipeline
industry
(
NAICS
4862)
comprises
establishments
primarily
engaged
in
the
pipeline
transportation
of
natural
gas
from
processing
plants
to
local
distribution
systems.
Also
included
in
this
industry
are
natural
gas
storage
facilities,
such
as
depleted
gas
fields
and
aquifers.

5.3.1
Introduction
The
natural
gas
industry
can
be
divided
into
three
segments,
or
links:
production,
transmission,
and
distribution.
Natural
gas
pipeline
companies
are
the
second
link,
performing
the
vital
function
of
linking
gas
producers
with
the
local
distribution
companies
and
their
customers.
Pipelines
transmit
natural
gas
from
gas
fields
or
processing
plants
Table
5­
20.
Size
of
Establishments
and
Value
of
Shipments,
Oil
and
Gas
Field
Services
(
NAICS
213112),
1997
and
1992
1997
Average
Number
of
Employees
at
Facility
Number
of
Facilities
Value
of
Shipments
($
1997
103)

0
to
4
employees
4,122
$
706,396
5
to
9
employees
1,143
$
571,745
10
to
19
employees
835
$
904,356
20
to
49
employees
629
$
1,460,920
50
to
99
employees
211
$
1,480,904
100
to
249
employees
84
$
1,175,766
250
to
499
employees
21
$
754,377
500
to
999
employees
13
$
1,755,689
1,000
to
2,499
employees
9
D
2,500
or
more
employees
1
D
Total
7,068
$
11,547,563
D
=
undisclosed
Sums
do
not
add
to
totals
due
to
independent
rounding.

Source:
U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1999d.
1997
Economic
Census,
Mining,
Industry
Series:
Support
Activities
for
Oil
and
Gas
Operations.
EC97N­
2131B.
Washington,
DC:
U.
S.
Department
of
Commerce.
5­
38
through
high
compression
steel
pipe
to
their
customers.
By
the
end
of
1998,
there
were
more
than
300,000
miles
of
transmission
lines
(
OPS,
2000).

The
interstate
pipeline
companies
that
linked
the
producing
and
consuming
markets
functioned
mainly
as
resellers
or
merchants
of
gas
until
about
the
1980s.
Rather
than
acting
as
common
carriers
(
i.
e.,
providers
only
of
transportation),
pipelines
typically
bought
and
resold
the
gas
to
a
distribution
company
or
to
some
other
downstream
pipelines
that
would
later
resell
the
gas
to
distributers.
Today,
virtually
all
pipelines
are
common
carriers,
transporting
gas
owned
by
other
firms
instead
of
wholesaling
or
reselling
natural
gas
(
Tussing
and
Tippee,
1995).

According
to
the
U.
S.
Bureau
of
the
Census,
the
natural
gas
pipeline
industry's
revenues
totaled
$
19.6
billion
in
1997.
Pipeline
companies
operated
1,450
facilities
and
employed
35,789
people
(
see
Table
5­
21).
The
industry's
annual
payroll
is
nearly
$
1.9
billion.

As
noted
previously,
the
recent
transition
from
the
SIC
system
to
the
NAICS
changed
how
some
industries
are
organized
for
information
collection
purposes
and
thus
how
certain
economic
census
data
are
aggregated.
Some
SIC
codes
were
combined,
others
were
separated,
and
some
activities
were
classified
under
one
NAICS
code
and
the
remaining
activities
classified
under
another.
The
natural
gas
transmission
(
pipelines)
industry
is
an
example
of
an
industry
code
that
was
reclassified.
Under
NAICS,
SIC
4922,
natural
gas
transmission
(
pipelines),
and
a
portion
of
SIC
4923,
natural
gas
distribution,
were
combined.
The
adjustments
have
made
comparison
between
the
1992
and
1997
economic
censes
Table
5­
21.
Summary
Statistics
for
the
Natural
Gas
Pipeline
Industry
(
NAICS
4862),
1997
Establishments
1,450
Revenue
($
103)
$
19,626,833
Annual
payroll
($
103)
$
1,870,950
Paid
employees
35,789
Source:
U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
2000.
1997
Economic
Census,
Transportation
and
Warehousing:
Geographic
Area
Series.
EC97T48A­
US.
Washington,
DC:
Government
Printing
Office.
5­
39
difficult
at
this
time.
The
U.
S.
Census
Bureau
has
yet
to
publish
a
comparison
report.
Thus,
for
this
industry
only
1997
census
data
are
presented.

5.3.2
Supply
Side
Characterizing
the
supply
side
involves
describing
services
provided
by
the
industry,
by­
products,
the
costs
of
production,
and
capacity
utilization.

5.3.2.1
Service
Description
Natural
gas
is
delivered
from
gas
processing
plants
and
fields
to
distributers
via
a
nationwide
network
of
over
300,000
miles
of
transmission
pipelines
(
NGSA
et
al.,
2000a).
The
majority
of
pipelines
are
composed
of
steel
pipes
that
measure
from
20
to
42
inches
in
diameter
and
operate
24
hours
a
day.
Natural
gas
enters
pipelines
at
gas
fields,
storage
facilities,
or
gas
processing
plants
and
is
"
pushed"
through
the
pipe
to
the
city
gate
or
interconnections,
the
point
at
which
distribution
companies
receive
the
gas.
Pipeline
operators
use
sophisticated
computer
and
mechanical
equipment
to
monitor
the
safety
and
efficiency
of
the
network.

Reciprocating
stationary
combustion
engines
compress
and
provide
the
pushing
force
needed
to
maintain
the
flow
of
gas
through
the
pipeline.
When
natural
gas
is
transmitted,
it
is
compressed
to
reduce
the
volume
of
gas
and
to
maintain
pushing
pressure.
The
gas
pressure
in
pipelines
is
usually
between
300
and
1,300
psi,
but
lesser
and
higher
pressures
may
be
used.
To
maintain
compression
and
keep
the
gas
moving,
compressor
stations
are
located
every
50
to
100
miles
along
the
pipeline.
Most
compressors
are
large
reciprocating
engines
powered
by
a
small
portion
of
the
natural
gas
being
transmitted
through
the
pipeline.

There
are
over
8,000
gas
compressing
stations
along
U.
S.
gas
pipelines,
each
equipped
with
one
or
more
engines.
The
combined
output
capability
of
U.
S.
compressor
engines
is
over
20
million
hp
(
NGSA
et
al.,
2000a).
Nearly
5,000
engines
have
individual
output
capabilities
from
500
to
over
8,000
hp.
The
replacement
cost
of
this
subset
of
larger
engines
is
estimated
by
the
Gas
Research
Institute
to
be
$
18
billion
(
Whelan,
1998).

Before
or
after
natural
gas
is
delivered
to
a
distribution
company,
it
may
be
stored
in
an
underground
facility.
Underground
storage
facilities
are
most
often
depleted
oil
and/
or
gas
fields,
aquifers,
or
salt
caverns.
Natural
gas
storage
allows
distribution
and
pipeline
companies
to
serve
their
customers
more
reliably
by
withdrawing
more
gas
from
storage
during
peak­
use
periods
and
reduces
the
time
needed
to
respond
to
increased
gas
demand
5­
40
(
NGSA
et
al.,
2000b).
In
this
way,
storage
guarantees
continuous
service,
even
when
production
or
pipeline
transportation
services
are
interrupted.

5.3.2.2
By­
products
According
to
the
Natural
Gas
Supply
Association
(
NGSA),
about
3
percent
of
the
natural
gas
moved
through
pipelines
escapes.
The
engines
that
provide
pumping
action
at
plants
and
push
crude
oil
and
natural
gas
through
pipelines
to
customers
and
storage
facilities
produce
HAPs.
As
noted
previously,
HAPs
produced
in
engines
include
formaldehyde,
acetaldehyde,
acrolein,
and
methanol.

5.3.2.3
Costs
of
Production
Between
1996
and
2000,
pipeline
firms
committed
over
$
14
billion
to
177
expansion
and
new
construction
projects.
These
projects
added
over
15,000
miles
and
36,178
million
cubic
feet
per
day
(
MMcf/
d)
capacity
to
the
transmission
pipeline
system.
Table
5­
22
summarizes
the
investments
made
in
pipeline
projects
during
the
past
5
years.
Building
new
pipelines
is
more
expensive
than
expanding
existing
pipelines.
For
the
period
covered
in
the
table,
the
average
cost
per
project
mile
was
$
862,000.
However,
the
costs
for
pipeline
expansions
averaged
$
542,000,
or
29
cents
per
cubic
foot
of
capacity
added.
New
pipelines
averaged
$
1,157,000
per
mile
at
48
cents
per
cubic
foot
of
capacity.

Pipelines
must
pay
for
the
natural
gas
that
is
consumed
to
power
the
compressor
engines.
The
amount
consumed
and
the
price
paid
have
fluctuated
in
recent
years.
In
1998,
pipelines
consumed
635,477
MMcf
of
gas,
paying,
on
average,
$
2.01
per
1,000
cubic
feet.
Pipelines
used
less
natural
gas
in
1998
than
in
previous
years;
the
price
paid
for
that
gas
fluctuated
between
$
1.49
and
$
2.29
between
1994
and
1997
(
see
Table
5­
23).
For
companies
that
transmit
natural
gas
through
their
own
pipelines
the
cost
of
the
natural
gas
consumed
is
considered
a
business
expense.

5.3.2.4
Capacity
Utilization
During
the
past
15
years,
interstate
pipeline
capacity
has
increased
significantly.
In
1990,
the
transmission
pipeline
system's
capacity
was
74,158
MMcf/
day
(
see
Table
5­
24).
By
the
end
of
1997,
capacity
reached
85,847
MMcf/
day,
an
increase
of
approximately
16
percent.
The
system's
usage
has
increased
at
a
faster
rate
than
capacity.
The
average
daily
flow
was
60,286
MMcf/
day
in
1997,
a
22
percent
increase
over
1990'
s
rates.
Currently,
the
system
operates
at
approximately
72
percent
of
capacity.
5­
41
Table
5­
22.
Summary
Profile
of
Completed
and
Proposed
Natural
Gas
Pipeline
Projects,
1996
to
2000
All
Type
Projects
New
Pipelines
Expansions
Year
Number
of
Projects
System
Mileage
New
Capacity
(
MMcf/
d)
Project
Costs
($
106)
Average
Cost
per
Mile
($
103)
Costs
per
Cubic
Foot
Capacity
(
cents)
Average
Cost
per
Mile
($
103)
Costs
per
Cubic
Foot
Capacity
(
cents)
Average
Cost
per
Mile
($
103)
Costs
per
Cubic
Foot
Capacity
(
cents)

1996
26
1,029
2,574
$
552
$
448
21
$
983
17
$
288
27
1997
42
3,124
6,542
$
1,397
$
415
21
$
554
22
$
360
21
1998
54
3,388
11,060
$
2,861
$
1,257
30
$
1,301
31
$
622
22
1999
36
3,753
8,205
$
3,135
$
727
37
$
805
46
$
527
31
2000
19
4,364
7,795
$
6,339
$
1,450
81
$
1,455
91
$
940
57
Total
177
15,660
36,178
$
14,285
$
862
39
$
1,157
48
$
542
29
Note:
Sums
may
not
add
to
totals
because
of
independent
rounding.

Source:
U.
S.
Department
of
Energy,
Energy
Information
Administration
(
EIA).
1999d.
Natural
Gas
1998:
Issues
and
Trends.
Washington,
DC:

U.
S.
Department
of
Energy.
5­
42
5.3.3
Demand
Side
Most
pipeline
customers
are
local
distribution
companies
that
deliver
natural
gas
from
pipelines
to
local
customers.
Many
large
gas
users
will
buy
from
marketers
and
enter
into
special
delivery
contracts
with
pipelines.
However,
local
distribution
companies
(
LDCs)
serve
most
residential,
commercial,
and
light
industrial
customers.
LDCs
also
use
compressor
engines
to
pump
natural
gas
to
and
from
storage
facilities
and
through
the
gas
lines
in
their
service
area.
Table
5­
23.
Energy
Usage
and
Cost
of
Fuel,
1994­
1998
Year
Pipeline
Fuel
(
MMcf)
Average
Price
($
per
1,000
cubic
feet)

1994
685,362
1.70
1995
700,335
1.49
1996
711,446
2.27
1997
751,470
2.29
1998
635,477
2.01
Source:
U.
S.
Department
of
Energy,
Energy
Information
Administration
(
EIA).
1999e.
Natural
Gas
Annual
1998.
Washington,
DC:
US
Department
of
Energy.

Table
5­
24.
Transmission
Pipeline
Capacity,
Average
Daily
Flows,
and
Usage
Rates,
1990
and
1997
1990
1997
Percent
Change
Capacity
(
MMcf
per
day)
74,158
85,847
16
Average
Flow
(
MMcf
per
day)
49,584
60,286
22
Usage
Rate
(
percent)
68
72
4
Source:
U.
S.
Department
of
Energy,
Energy
Information
Administration.
1999d.
Natural
Gas
1998:
Issues
and
Trends.
Washington,
DC:
US
Department
of
Energy.
5­
43
While
economic
considerations
strongly
favor
pipeline
transportation
of
natural
gas,
liquified
natural
gas
(
LNG)
emerged
during
the
1970s
as
a
transportation
option
for
markets
inaccessible
to
pipelines
or
where
pipelines
are
not
economically
feasible.
Thus,
LNG
is
a
substitute
for
natural
gas
transmission
via
pipelines.
LNG
is
natural
gas
that
has
been
liquified
by
lowering
its
temperature.
LNG
takes
up
about
1/
600
of
the
space
gaseous
natural
gas
takes
up,
making
transportation
by
ship
possible.
However,
virtually
all
of
the
natural
gas
consumed
in
the
United
States
reaches
its
consumer
market
via
pipelines
because
of
the
relatively
high
expense
of
transporting
LNG
and
its
volatility.
Most
markets
that
receive
LNG
are
located
far
from
pipelines
or
production
facilities,
such
as
Japan
 
the
world's
largest
LNG
importer,
Spain,
France,
and
Korea
(
Tussing
and
Tippee,
1995).

5.3.4
Organization
of
the
Industry
Much
like
other
energy­
related
industries,
the
natural
gas
pipeline
industry
is
dominated
by
large
investor­
owned
corporations.
Smaller
companies
are
few
because
of
the
real
estate,
capital,
and
operating
costs
associated
with
constructing
and
maintaining
pipelines
(
Tussing
and
Tippee,
1995).
Many
of
the
large
corporations
are
merging
to
remain
competitive
as
the
industry
adjusts
to
restructuring
and
increased
levels
of
competition.
Increasingly,
new
pipelines
are
built
by
partnerships:
groups
of
energy­
related
companies
share
capital
costs
through
joint
ventures
and
strategic
alliances
(
DOE,
EIA,
1999d).
Ranked
by
system
mileage,
the
largest
pipeline
companies
in
the
United
States
are
El
Paso
Energy
(
which
recently
merged
with
Southern
Natural
Gas
Co.),
Enron,
Williams
Cos.,
Coastal
Corp.,
and
Duke
Energy
(
see
Table
5­
25).
El
Paso
Energy
and
Coastal
intend
to
merge
in
mid­
2000.

5.3.5
Markets
and
Trends
During
the
past
decade,
interstate
pipeline
capacity
has
increased
16
percent.
Many
existing
pipelines
underwent
expansion
projects,
and
15
new
interstate
pipelines
were
constructed.
In
1999
and
2000,
proposals
for
pipeline
expansions
and
additions
called
for
a
$
9.5
billion
investment,
an
increase
of
16.0
billion
cubic
feet
per
day
of
capacity
(
DOE,
EIA,
1999d).

The
EIA
(
1999d)
expects
natural
gas
consumption
to
grow
steadily,
with
demand
forecasted
to
reach
32
trillion
cubic
feet
by
2020.
The
expected
increase
in
natural
gas
demand
has
significant
implications
for
the
natural
gas
pipeline
system.
5­
44
The
EIA
(
1999d)
expects
the
interregional
pipeline
system,
a
network
that
connects
the
lower
48
states
and
the
Canadian
provinces,
to
grow
at
an
annual
rate
of
0.7
percent
between
2001
and
2020.
However,
natural
gas
consumption
is
expected
to
grow
at
more
than
twice
that
annual
rate,
1.8
percent,
over
that
same
period.
The
majority
of
the
growth
in
consumption
is
expected
to
be
fueled
by
the
electric
generation
sector.
According
to
the
EIA,
a
key
issue
is
what
kinds
of
infrastructure
changes
will
be
required
to
meet
this
demand
and
what
the
financial
and
environmental
costs
will
be
of
expanding
the
pipeline
network.

The
EIA
addresses
the
discrepancy
between
annual
consumption
growth
and
interregional
pipeline
capacity
growth
with
the
following
explanation:
"
Overall,
interregional
pipeline
capacity
(
including
imports)
is
projected
to
grow
at
an
annual
rate
of
only
about
0.7
percent
between
2001
and
2020
(
compared
with
3.7
percent
between
1997
Table
5­
25.
Five
Largest
Natural
Gas
Pipeline
Companies
by
System
Mileage,
2000
Company
Headquarters
Sales
($
1999
106)
Employment
(
1999)
Miles
of
Pipeline
El
Paso
Energy
Corporation
Incl.
El
Paso
Natural
Gas
Co.
Southern
Natural
Gas
Co.
Tennessee
Gas
Pipe
Line
Co.
Houston,
TX
$
5,782
4,700
40,200
Enron
Corporation
Incl.
Northern
Border
Pipe
Line
Co.
Northern
Natural
Gas
Co.
Transwestern
Pipeline
Co.
Houston,
TX
$
40,112
17,800
32,000
Williams
Companies,
Inc.
Incl.
Transcontinental
Gas
Pipe
Line
Northwest
Pipe
Line
Co.
Texas
Gas
Pipe
Line
Co.
Tulsa,
OK
$
8,593
21,011
27,000
The
Coastal
Corporation
Incl.
ANR
Pipeline
Co.
Colorado
Interstate
Gas
Co.
Houston,
TX
$
8,197
13,000
18,000
Duke
Energy
Corporation
Incl.
Panhandle
Eastern
Pipeline
Co.
Algonquin
Gas
Transmission
Co.
Texas
Eastern
Transmission
Co.
Charlotte,
NC
$
21,742
21,000
11,500
Sources:
Heil,
Scott
F.,
Ed.
Ward's
Business
Directory
of
U.
S.
Private
and
Public
Companies
1998,
Volume
5.
Detroit,
MI:
Gale
Research
Inc.

Sales,
employment,
and
system
mileage:
Hoover's
Incorporated.
1998.
Hoover's
Company
Profiles.
Austin,
TX:
Hoover's
Incorporated.
<
http://
www.
hoovers.
com/>.
5­
45
and
2000
and
3.8
percent
between
1990
and
2000).
However,
EIA
also
forecasts
that
consumption
will
grow
at
a
rate
of
27
Bcf
per
day
(
1.8
percent
annually)
during
the
same
period.
The
difference
between
these
two
growth
estimates
is
predicted
upon
the
assumption
that
capacity
additions
to
support
increased
demand
will
be
local
expansions
of
facilities
within
regions
(
through
added
compression
and
pipeline
looping)
rather
than
through
new
long­
haul
(
interregional)
systems
or
large­
scale
expansions"
(
1999d,
p.
125).
6­
1
SECTION
6
ECONOMIC
ANALYSIS
METHODS
This
section
presents
the
methodology
for
analyzing
the
economic
impacts
of
the
NESHAP.
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
greater
than
$
100
million.
Also,
Executive
Order
13211
requires
EPA
to
consider
for
6­
2
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:


the
scope
of
economic
decisionmaking
accounted
for
in
the
model
and

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
the
regulation's
impact.
6­
3
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

affected
producers

unaffected
producers

consumers

foreign
trade
EIA
Without
Behavioral
Responses

Assumes
firm
absorbs
all
control
costs

Typically
uses
discounted
cash
flow
analysis
to
evaluate
burden
of
control
costs

Includes
depreciation
schedules
and
corporate
tax
implications

Does
not
adjust
for
changes
in
market
price

Does
not
adjust
for
changes
in
plant
production
6­
4

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.


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.


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
MACT,
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.
1Technical
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
MACT.
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.
1
6­
6
 
demand
oil
Oil
Supply
Exogenous
Demand
Endogenous
 
demand
NG
Gas
 
demand
coal
Coal
Industry
A
Btu
Production
Manufacturing
Process
Industry
C
Industry
B
Regulatory
Costs
Energy
Consumption
 
demand
elec
Electricity
Electricity
Market
Fuel
Markets
 
supply
product
A
Product
A
Supply
Endogenous
Demand
Exogenous
Intermediate
or
Final
Product
Markets
   

Figure
6­
1.
Links
Between
Energy
and
Final
Product
Markets
2The
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.
3A
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.
2
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.
3
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
input
fuel
prices
(
i.
e.,
a
supply
shift)
and
changes
in
demand
from
final
product
and
service
6­
8
a)
Without
Regulation
b)
With
Control
Costs
Price
$/
kWh
Quantity
(
kWh)
 
P
Price
$/
kWh
P
0
Q
0
Existing
Sources
New
Sources
Quantity
(
kWh)
 
Q
Existing
Source
Shift
New
Source
Shift
Figure
6­
2.
Electricity
Market
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
4The
supply
curve
for
new
sources
is
assumed
to
be
horizontal,
reflecting
a
constant
marginal
cost
of
production
for
new
sources.

6­
9
S
1
S
0
Btu
Price
($/
Btu)

D
0
D
1
S
1
S
0
Btu
Price
($/
Btu)

D
0
D
1
 
Q
 
P
a)
Demand
Increase
b)
Demand
Decrease
 
P
 
Q
Figure
6­
3.
Potential
Market
Effects
of
the
MACT
on
Petroleum,
Natural
Gas,
or
Coal
responses
from
existing
sources.
4
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
werecompensated
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
6
shows
the
elasticities
of
demand
used
for
the
commercial,
residential,
and
transportation
sectors.

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
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
Energy
Information
Administration.
2000.
"
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.
6­
11
Btu
Production
Decision
Output
Market
 
Fuel
Use
 
Output
 
$/
Btu
Production
Decision
$/
Btu
 
$/
Btu
Fuel
Markets
Compliance
Costs
Figure
6­
4.
Fuel
Market
Interactions
with
Facility­
Level
Production
Decisions
conducted
for
each
of
these
model
the
supply
and
demand
of
final
products.
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.
6­
12
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
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
(

$
/
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.
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
13
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
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.
6­
14
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
15
 
demand
elec
Electricity
Electricity
Market
 
demand
oil
Oil
Assume
Supply
Model
Demand
 
demand
NG
Gas
 
demand
coal
Coal
Industry
A
Btu
Production
Manufacturing
Process
Industry
Z
Industry
B
Regulatory
Costs
 

P
 
Q
Q
Energy
Consumption
Final
Product
Markets
Fuel
Markets
Fuel
Prices
Fuel
Prices
Fuel
Prices
Fuel
Prices
 
Production
Process
(
Fuel
Switching)
 
Production
Levels
Product
Supply
Product
Price
P
=
market
price
of
final
output
Q
=
quantity
sold
of
final
output
   
Residential
Households
Commercial
Businesses
Fuel
Prices
Figure
6­
5.
Operationalizing
the
Estimation
of
Economic
Impact
6­
16
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.

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:


change
in
producer
surplus
in
the
energy
markets,


change
in
producer
surplus
in
the
final
product
and
service
markets,


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.
6­
17
S
D
S 

D
(
a)
Change
in
Consumer
Surplus
in
the
Energy
Market
(
c)
Change
in
Consumer
Surplus
in
Final
Product
Markets
(
b)
Change
in
Producer
Surplus
in
the
Energy
Market
(
d)
Change
in
Producer
Surplus
in
Final
Product
Markets
P
P
2
Q
P
1
Q
2
Q
1
S
D
S 

P
P
B
Q
P
A
Q
B
Q
A
S
D
S 
P
P
B
Q
P
A
Q
B
Q
A
P
P
2
Q
P
1
Q
2
Q
1
S
D
S 

A
B
C
E
F
Figure
6­
6.
Changes
in
Economic
Welfare
with
Regulation
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
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
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
6­
18
Change
in
Social
Welfare
=


PSE
+


PSF
+


CSF
+


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.
1All
costs
are
reported
in
1998
dollars.

7­
1
SECTION
7
ECONOMIC
IMPACT
ANALYSIS
Control
measures
implemented
to
comply
with
the
regulation
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
engineering
control
costs
of
the
regulatory
alternatives
and
presents
the
economic
impact
estimates,
including
energy
impacts,
of
the
regulation.

7.1
Engineering
Control
Cost
Inputs
The
cost
impacts
associated
with
the
regulation
in
the
fifth
year
after
promulgation
comprise
capital
and
annual
operating,
performance
testing,
monitoring,
recordkeeping,
and
reporting
costs.
The
Department
of
Energy
(
DOE)
projects
the
218
new
combustion
turbines
will
begin
operation
during
the
5­
year
period
between
2002
and
2007.
Of
these
new
turbines,
it
is
estimated
that
approximately
44
units
(
20
percent)
will
be
located
at
major
HAP
sources
and
be
required
to
comply
with
the
combustion
turbine
NESHAP.

EPA
estimates
the
annualized
capital
costs
of
these
add­
on
controls
for
44
new
stationary
combustion
turbines
(
170
MW)
are
$
42.6
million
(
see
Table
7­
1).
1
Additional
annual
costs
include
performance
testing,
monitoring,
recordkeeping,
reporting,
and
the
annual
costs
of
the
oxidation
catalyst
control
system
and
CEMS
yielding
a
total
annual
cost
of
$
43.3
million
for
affected
units.
All
new
sources
will
be
required
to
conduct
an
initial
performance
test
to
demonstrate
compliance.
In
addition,
EPA
estimates
that
every
year
most
of
the
"
nonaffected"
new
sources
(
70
percent)
may
have
to
perform
an
initial
notification
to
comply
with
the
regulation.
The
total
cost
for
initial
notification
for
123
new
turbines
is
estimated
to
be
approximately
$
12,000.
For
more
details
on
the
derivation
of
these
costs,
refer
to
the
"
Cost
Analysis
for
Impacts
Associated
with
Stationary
Combustion
Turbine
MACT,"
a
memo
that
is
in
the
public
docket.
2Revenue
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.
Engineering
Cost
Analysis
for
the
Stationary
Combustion
Turbine
MACT
Standard
($
1998)

Combine
per
Turbine
Number
of
Affected
Turbines
Total
Cost
Capital
Costs
CEMS
$
3,000
44
$
132,000
Oxidation
catalyst
$
3,255,377
44
$
143,236,588
Total
Capital
Cost
$
143,368,588
Annual
Costs
CEMS
$
427
44
$
18,788
Oxidation
catalyst
$
969,499
44
$
42,657,956
Performance
tests
$
12,350
44
$
543,400
Monitoring,
recordkeeping,
reporting
$
2,709
44
$
119,201
Initial
notification
only
98
123
$
11,993
Total
Annual
Cost
(
1998$)
$
43,351,338
aRevenues
and
costs
are
in
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
as
the
ratio
of
control
costs
to
the
revenue
of
the
affected
portion
of
the
industry2
(
see
Table
7­
2).
As
shown,
new
affected
sources
with
add­
on
controls
and
testing
requirements
have
the
largest
supply
shift
(
1.8
percent
for
base
load
energy
and
3.5
percent
for
peak
power).
The
supply
shifters
for
the
remaining
segments
are
all
less
than
0.1
percent.
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
 
unaffected
95.08
169.0
0.00
0.00
New
unaffected
1.07
1.9
0.00
0.00
New
affected
 
notification
only
2.59
4.6
0.01
0.00
New
affected
 
notification
and
capital
0.92
1.6
29.04
1.77
Total
100.00
177.6
29.05
0.02
Peak
Power
Existing
 
unaffected
95.08
42.2
0.00
0.00
New
unaffected
1.07
0.5
0.00
0.00
New
affected
 
notification
only
2.59
1.1
0.00
0.00
New
affected
 
notification
and
capital
0.92
0.4
14.30
3.48
Total
100.00
44.4
14.31
0.03
Total
222.1
43.35
aRevenues
and
costs
are
in
1998$.

Figure
7­
1
illustrates
the
supply
shifts
and
shows
the
with­
regulation
supply
curve
S
1.
In
this
example,
the
regulation
leads
to
an
increased
supply
by
unaffected
existing
units,
crowding
out
the
new
units
with
add­
on
capital
costs.

7.2
Market­
Level
Results
The
model
projects
the
MACT
standard
will
increase
base
load
electricity
price
by
0.529
percent
and
peak
power
prices
by
0.717
percent
(
see
Table
7­
3).
Domestic
production
declines
by
0.534
and
0.665
percent,
respectively.

The
analysis
also
shows
the
impact
on
distribution
of
electricity
supply
(
see
Table
7­
4).
First,
it
delays
entry
of
affected
new
units
with
add­
on
controls
and
testing
requirements
because
price
does
not
sufficiently
increase
to
cover
the
costs
of
production
for
these
units.
Second,
the
increase
in
the
price
of
electricity
will
make
it
profitable
for
existing
unaffected
sources
to
increase
supply,
displacing
approximately
0.92
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.
7­
4
C
E
F
Projected
new
source
growth
G
S
1
S
0
D
kWh
Price
($/
kWh)

(
Projected
Demand)

B
=
New
unaffected
unit
supply
B+
C
=
Increase
in
supply
from
existing
units
D
=
New
notification
only
F
=
Decreased
quantity
demanded
due
to
price
increase
G
=
Affected
supply
that
delays
entry
into
the
market
until
demand
sufficiently
grows
a
=
Supply
shift
for
new
monitoring
only
units
b
=
Supply
shift
for
new
testing
and
capital
equipment
units
D
B
S
0
b
a
Figure
7­
1.
Market
for
Baseload
Electricity
7­
5
Table
7­
3.
Market­
Level
Impacts
of
Stationary
Combustion
Turbines
MACT
Standard:
2005
Percent
Change
Energy
Markets
Price
Quantitya
Petroleum
0.019
0.010
Natural
Gas
0.052
0.018
Base
Electricity
0.529
 
0.534
Peak
Electricity
0.717
 
0.665
Coal
 
0.244
 
0.244
Industrial
Sectors
NAICS
Description
Description
Percent
Change
Price
Quantity
311
Food
0.001
 
0.001
312
Beverage
and
Tobacco
Products
0.000
 
0.001
313
Textile
Mills
0.002
 
0.003
314
Textile
Product
Mills
0.001
 
0.001
315
Apparel
0.000
0.000
316
Leather
and
Allied
Products
0.001
 
0.001
321
Wood
Products
0.002
 
0.002
322
Paper
0.002
 
0.003
323
Printing
and
Related
Support
0.001
 
0.001
325
Chemicals
0.002
 
0.004
326
Plastics
and
Rubber
Products
0.002
 
0.003
327
Nonmetallic
Mineral
Products
0.004
 
0.004
331
Primary
Metals
0.005
 
0.005
332
Fabricated
Metal
Products
0.003
 
0.001
333
Machinery
0.001
 
0.001
334
Computer
and
Electronic
Products
0.001
0.000
335
Electrical
Equipment,
Appliances,
and
Components
0.001
 
0.001
336
Transportation
Equipment
0.001
 
0.001
337
Furniture
and
Related
Products
0.001
 
0.001
339
Miscellaneous
0.001
 
0.001
11
Agricultural
Sector
0.003
 
0.005
23
Construction
Sector
0.012
 
0.012
21
Other
Mining
Sector
0.002
 
0.001
Commercial
Sector
0.002
 
0.002
aActual
value
for
all
0.000
entries
for
the
various
sectors
is
>
 
0.001
and
<
0.
7­
6
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
less
than
0.3
percent.

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
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
$
43.4
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
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
Table
7­
4.
Changes
in
Market
Shares
for
Electricity
Suppliers
Baseline
Shares
(%)
With
Regulation
Shares
(%)

Existing
 
unaffected
95.42
96.32
New
unaffected
1.07
1.07
New
affected
 
testing
only
2.59
2.60
New
affected
 
testing
and
capital
0.92
0.00
7­
7
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
$
7.8
million.
The
social
cost
estimate
is
18
percent
of
the
estimated
engineering
costs
as
a
result
of
behavioral
changes
of
producers
and
consumers.
The
major
behavioral
change
is
that
units
with
testing
and
add­
on
capital
controls
are
crowded
out
of
the
new
source
market;
hence
these
costs
are
not
incurred
by
society.
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.

The
analysis
also
shows
important
distributional
impacts
across
stakeholders.
For
example,
the
model
projects
consumers
will
bear
a
burden
of
$
860
million,
as
a
result
of
higher
energy
prices.
In
contrast,
producer
surplus
increases
by
$
853
million
as
energy
producers,
particularly
the
electricity
industry,
become
more
profitable
with
higher
prices.

7.4
Executive
Order
13211
(
Energy
Effects)

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:

°
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
°
that
is
designated
by
the
Administrator
of
the
Office
of
Information
and
Regulatory
Affairs
as
a
significant
energy
action."
7­
8
Given
the
magnitude
of
the
annual
costs,
no
Statement
of
Energy
Effects
will
be
completed.
However,
to
provide
some
information
on
the
impacts
of
the
rule
on
affected
Table
7­
5.
Distribution
of
Social
Costs
of
Stationary
Combustion
Turbines
MACT
Standard:
2005
($
1998
106)

Change
in:

Sectors/
Markets
Producer
Surplus
Consumer
Surplus
Social
Welfare
Energy
Sector
Petroleum
(
NAICS
32411,
4861)
$
55.56
NA
NA
Natural
Gas
(
NAICS
21111,
4862,
2212)
$
45.41
NA
NA
Electricity
(
NAICS
22111,
221122,
221121)
$
1,297.01
NA
NA
Coal
(
NAICS
2121)
 
$
76.94
NA
NA
Subtotal:
$
1,321.05
NA
NA
Change
in:
Industrial
Sector
NAICS
Description
Producer
Surplus
Consumer
Surplus
Social
Welfare
311
Food
 
$
6.5
 
$
4.9
 
$
11.4
312
Beverage
and
Tobacco
Products
 
$
0.8
 
$
0.4
 
$
1.2
313
Textiles
Mills
 
$
3.3
 
$
1.7
 
$
5.0
314
Textile
Product
Mills
 
$
0.6
 
$
0.3
 
$
0.9
315
Apparel
 
$
0.5
 
$
0.4
 
$
0.9
316
Leather
and
Allied
Products
 
$
0.1
 
$
0.1
 
$
0.1
321
Wood
Products
 
$
2.0
 
$
1.5
 
$
3.5
322
Paper
 
$
8.5
 
$
4.3
 
$
12.8
323
Printing
and
Related
Support
 
$
1.7
 
$
0.7
 
$
2.5
325
Chemicals
 
$
22.9
 
$
9.5
 
$
32.5
326
Plastics
and
Rubber
Products
 
$
6.2
 
$
2.6
 
$
8.7
327
Nonmetallic
Mineral
Products
 
$
4.1
 
$
3.1
 
$
7.1
331
Primary
Metals
 
$
15.2
 
$
11.4
 
$
26.7
332
Fabricated
Metal
Products
 
$
1.9
 
$
6.9
 
$
8.8
333
Machinery
 
$
1.9
 
$
2.8
 
$
4.7
334
Computer
and
Electronic
Products
 
$
1.8
 
$
4.6
 
$
6.4
335
Electrical
Equipment,
Appliances,
and
Components
 
$
1.1
 
$
1.6
 
$
2.7
336
Transportation
Equipment
 
$
3.8
 
$
5.7
 
$
9.6
337
Furniture
and
Related
Products
 
$
1.0
 
$
0.4
 
$
1.5
339
Miscellaneous
 
$
0.9
 
$
1.1
 
$
2.0
11
Agricultural
Sector
 
$
12.7
 
$
5.3
 
$
18.0
23
Construction
Sector
 
$
131.7
 
$
98.7
 
$
230.4
21
Other
Mining
Sector
 
$
0.7
 
$
1.6
 
$
2.3
Industrial
Sector
Subtotal:
 
$
229.9
 
$
169.7
 
$
399.6
Commercial
Sector
 
$
238.7
 
$
179.0
 
$
417.7
Residential
Sector
NA
 
$
454.9
 
$
454.9
Transportation
Sector
NA
 
$
56.7
 
$
56.7
Subtotal
 
$
468.6
 
$
860.3
 
$
1,328.9
Grand
Total
$
852.5
 
$
860.3
 
7.8
7­
9
energy
markets,
the
following
estimates
have
been
prepared
Energy
Price
Effects.
As
described
in
the
market­
level
results
section,
electricity
prices
are
projected
to
increase
by
less
than
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
20.4
billion
kWh
and
a
delay
of
new
installed
capacity
of
7,480
MW.
Note
these
effects
have
been
mitigated
to
some
degree
in
two
ways:

°
The
delay
in
installed
capacity
is
offset
by
increased
supply
from
existing
unaffected
sources,
implying
that
fewer
older
units
may
be
retired
as
a
result
of
the
regulation.

°
Sectors
previously
using
electricity
in
the
baseline
will
switch
to
other
energy
sources
(
see
below).

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
2,000
barrels
per
day.
Similarly,
natural
gas
production/
consumption
is
projected
to
increase
by
11.7
million
cubic
feet
per
day.
The
model
also
projects
decreases
in
coal
production/
consumption
of
approximately
8,000
short
tons
per
year.
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.
1Public
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
2
8.1
Identifying
Small
Businesses
As
described
in
Section
3
of
this
report,
the
Agency
has
projected
that
approximately
218
new
combustion
turbines
will
begin
operation
during
the
5­
year
period
between
2002
and
2007.
Of
this
population
approximately
20
percent
of
the
new
turbines
are
projected
to
be
located
at
major
sources.
Thus
approximately
44
sources
would
be
required
to
comply
with
the
combustion
turbines
NESHAP.
No
existing
combustion
turbines
will
be
effected
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
business
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.
1
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.
As
with
the
total
population,
not
all
units
owned
by
small
entities
will
incur
costs
as
a
result
of
the
regulation.
However,
because
we
do
not
have
the
information
to
determine
which
units
will
be
affected,
we
have
included
all
potentially
affected
small
entities
in
the
screening
analysis,
recognizing
that
this
yields
an
overestimate
of
the
impacts
on
small
entities.
2The
Inventory
Database
also
contains
small
turbines
that
are
not
included
in
Table
8­
1.
These
units,
frequently
referred
to
as
"
micro
turbines,"
did
not
meet
the
1
MW
size
requirements
and
are
excluded
from
this
rule.
Six
hundred
thirty­
five
units
at
204
facilities
in
the
Inventory
Database
had
unit
capacities
under
1
MW.
As
a
result,
a
large
number
of
small
entities
potentially
purchasing
combustion
turbines
in
the
future
will
not
be
affected
by
the
regulation
due
to
the
rule's
size
cutoff.

8­
3
Table
8­
1
presents
the
distribution
of
small
entities
by
business
type.
2
As
is
the
case
with
the
majority
of
turbine
operators,
ownership
of
turbines
in
the
Inventory
Database
by
small
companies
is
concentrated
in
the
electric
services
industry.
In
fact,
22
of
small
entities
are
municipalities
that
own
and
operate
local
utility
systems.
The
remaining
entities
are
either
small
energy
(
e.
g.,
oil
and
gas)
firms
or
small
manufacturing
companies.

To
assess
the
potential
impact
of
this
rule
on
the
29
small
companies
and
government
entities
that
own
combustion
turbines,
the
Agency
considered
the
regulatory
control
costs
presented
in
Section
7.
For
this
screening­
level
analysis,
annual
compliance
costs
were
defined
as
the
annualized
costs
of
performance
tests,
monitoring,
recordkeeping,
and
reporting
imposed
on
each
company
or
government
entity
assuming
that
it
owned
or
were
to
install
one
turbine.
The
total
annualized
cost
associated
with
these
activities
is
$
25,119
(
1998
dollars).
Control
costs
of
oxidation
catalysts
and
CEMs
were
not
included
in
the
screening
analysis
because
the
Agency
estimates
that
only
a
small
number
units
per
year
will
require
these
add­
on
capital
costs.
It
is
highly
unlikely
that
small
entities
will
be
installing
170
MW
turbines
and
would
be
required
to
install
this
equipment.

The
results
of
this
initial
screening
analysis
are
shown
in
Table
8­
2.
If
each
entity
owned
or
were
to
install
one
turbine,
the
annual
compliance
costs,
as
a
percentage
of
annual
revenues,
for
small
companies
and
government
organizations
would
range
from
0.01
to
0.46
percent.
The
average
(
median)
compliance
cost­
to­
sales
ratio
(
CSR)
is
0.11
percent.
As
shown,
none
of
the
small
entities
are
affected
above
the
1
percent
level.

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.
8­
4
Table
8­
1.
Number
of
Units
Greater
than
1
MW
at
Small
Parents
by
Industry
NAICS
Description
Number
of
Units
Number
of
Units
Greater
than
1
MW
Owned
by
Small
Parents
Number
of
Small
Parents
112
Animal
Production
1
211
Oil
and
Gas
Extraction
365
5
2
212
Mining
(
Except
Oil
and
Gas)
3
221
Utilities
983
35
22
233
Building,
Developing,
and
General
Contracting
1
235
Special
Trade
Contractors
2
311
Food
Manufacturing
18
321
Wood
Products
Manufacturing
3
2
1
322
Paper
Manufacturing
17
324
Petroleum
and
Coal
Products
Manufacturing
34
325
Chemical
Manufacturing
63
1
1
326
Plastics
and
Rubber
Products
Manufacturing
4
327
Nonmetallic
Mineral
Product
Manufacturing
1
331
Primary
Metal
Manufacturing
13
332
Fabricated
metal
Product
Manufacturing
2
333
Machinery
Manufacturing
2
334
Computer
and
Electronic
Product
Manufacturing
6
335
Electrical
Equipment,
Appliance,
and
Component
Manufacturing
1
336
Transportation
Equipment
Manufacturing
3
1
1
337
Furniture
and
Related
Product
Manufacturing
1
339
Miscellaneous
Manufacturing
3
422
Wholesale
Trade,
Nondurable
Goods
6
486
Pipeline
Transportation
448
7
2
488
Support
Activities
for
Transportation
1
513
Broadcasting
and
Telecommunications
1
522
Credit
Intermediation
and
Related
Activities
3
541
Professional,
Scientific,
and
Technical
Services
2
561
Administrative
and
Support
Services
1
611
Educational
Services
10
622
Hospitals
23
721
Accommodation
1
923
Administration
of
Human
Resource
Programs
1
926
Administration
of
Economic
Programs
1
928
National
Security
and
International
Affairs
42
Unknown
Industry
Classification
Unknown
6
TOTAL
2,072
51
29
8­
5
Table
8­
2.
Summary
Statistics
for
SBREFA
Screening
Analysis:
Recommended
Alternative
Total
Number
of
Small
Entities
29
Average
Annual
Compliance
Cost
per
Small
Entitya
$
15,059
Number
Share
(%)

Entities
with
Sales/
Revenue
Data
29
100
Compliance
costs
are
<
1%
of
sales
0
0
Compliance
costs
are
$
1
to
3%
of
sales
0
0
Compliance
costs
are
$
3%
of
sales
0
0
Compliance
Cost­
to­
Sales/
Revenue
Ratios
Average
0.07
Median
0.04
Maximum
0.28
Minimum
0.01
aAssumes
no
market
responses
(
i.
e.,
price
and
output
adjustments)
by
regulated
entities.

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
six
three­
digit
NAICS
codes
are
affected
by
this
rule,
and
the
small
business
definition
applied
to
each
industry
by
NAICS
code
is
that
listed
in
the
SBA
size
standards
(
13
CFR
121).
3The
increasing
trend
is
for
local
governments
to
engage
in
municipal
aggregation
and
purchase
long­
and
shortterm
power
contracts
through
the
emerging
wholesale
markets
(
see
Cliburn,
2001).

8­
6
After
considering
the
economic
impacts
of
today's
rule
on
small
entities,
this
analysis
determines
this
action
will
not
have
a
significant
economic
impact
on
a
substantial
number
of
small
entities.
This
certification
is
based
on
two
analytical
approaches:

C
examining
the
hypothetical
impacts
on
small
entities
based
on
the
existing
combustion
turbines
inventory,
and
presuming
that
the
existing
mix
of
combustion
turbines
among
industries
is
a
good
approximation
of
the
mix
of
new
turbines
that
will
be
installed
over
the
next
5
years,
and
C
considering
influences
on
the
decision
by
small
entities
to
install
new
turbines.

First,
based
on
the
existing
combustion
turbines
inventory,
this
analysis
determines
that
only
29
small
entities
out
of
300
small
entities
would
have
been
impacted
by
this
rule
if
it
had
affected
existing
sources.
These
29
small
entities
own
51
affected
turbines
in
the
existing
combustion
turbines
inventory,
which
represents
only
2.5
percent
of
the
existing
turbines
overall.
Of
these
entities,
22
of
these
entities
are
small
communities
and
seven
are
small
firms.
None
of
the
29
affected
small
entities
are
estimated
to
have
compliance
costs
that
exceed
1
percent
of
their
revenues.
Based
on
industry
profit
margin
(
i.
e.,
profits
per
sales)
data
for
the
electric
services
industry
(
92
percent
of
all
affected
turbines)
shown
in
the
industry
profile,
the
average
return
on
sales
for
the
industries
is
4.6
percent.
It
should
be
noted
that
a
comparison
of
profits
with
costs
for
small
communities
in
this
analysis
is
valid,
for
the
small
communities
manage
the
electric
services
they
own
in
a
similar
fashion
to
the
small
firms
affected
by
this
rule.
No
small
entity
is
estimated
to
have
compliance
cost
to
sales
of
greater
than
the
average
return
on
sales.
In
addition,
the
rule
is
likely
to
also
increase
profits
at
the
many
small
firms
and
increase
revenues
for
the
many
small
communities
using
turbines
that
are
not
affected
by
the
rule
as
a
result
of
the
very
slight
increase
in
market
prices.

Second,
another
approach
to
examining
small
entity
impacts
is
to
look
at
the
influences
on
purchases
of
new
turbines
by
small
entities
in
the
next
5
years.
It
is
very
likely
that
the
ongoing
deregulation
of
the
electric
power
industry
across
the
nation
will
minimize
the
rule's
impacts
on
small
entities.
Increased
competition
in
the
electric
power
industry
is
forecasted
to
decrease
the
market
price
for
wholesale
electric
power.
Open
access
to
the
grid
and
lower
market
prices
for
electricity
will
make
it
less
attractive
for
local
communities
to
purchase
and
operate
new
combustion
turbines.
3
Regardless
of
either
analytical
approach,
8­
7
the
Agency
concludes
that
this
rule
will
not
have
a
significant
impact
on
a
substantial
number
of
small
entities.

Although
this
rule
will
not
have
a
significant
economic
impact
on
a
substantial
number
of
small
entities,
EPA
nonetheless
has
tried
to
reduce
the
impact
of
this
rule
on
small
entities.
In
this
rule,
the
Agency
is
applying
the
minimum
level
of
control
and
the
minimum
level
of
monitoring,
recordkeeping,
and
reporting
to
affected
sources
allowed
by
the
CAA.
In
addition,
as
mentioned
earlier
in
the
preamble,
turbines
with
capacities
under
1.0
MW
are
not
covered
by
this
rule.
This
provision
should
reduce
the
level
of
small
entity
impacts.
EPA
continues
to
be
interested
in
the
potential
impacts
of
the
rule
on
small
entities
and
welcomes
comments
on
issues
related
to
such
impacts.
R­
1
REFERENCES
1998­
99
GTW
Handbook.
"
Turnkey
Combined
Cycle
Plant
Budget
Price
Levels."
Fairfield,
CT:
Pequot
Pub.
Pgs
19­
26.

Berger,
Bill
D.
and
Kenneth
E.
Anderson.
1978.
Modern
Petroleum:
A
Basic
Primer
of
the
Industry.
Tulsa,
OK:
The
Petroleum
Publishing
Co.

Cliburn,
J.
K.
2001.
"
Local
Governments
Turn
to
Municipal
Aggregation."
Public
Power
Magazine.
(
January
 
February).

Conces,
Elaine.
2000.
"
Hoover's
Online
 
Energy
Industry
Snapshot."
As
obtained
on
April
18,
2000.
<
http://
www.
hoovers.
com/
industry/
snapshot/
0,2204,16,00.
html>.

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
Application
Economics
18:
243­
263.

Edison
Electric
Institute
(
EEI).
1998.
Statistical
Yearbook
of
the
Electric
Utility
Industry
1997.
November.
Washington,
DC.

Edison
Electric
Institute
(
EEI).
1999.
"
The
Rise
of
the
Power
Marketer."
<
http://
www.
eei.
org/
issues/
comp­
reg/
6riseofp.
htm>.
As
obtained
on
August
11,
1999.

General
Electric
Corporation.
GE
Power
Plants.
<
www.
ge.
com>.
As
obtained
on
November
3,
1999.

Haltmaier,
Susan.
1998.
"
Electricity
Production
and
Sales."
In
U.
S.
Industry
&
Trade
Outlook
`
98,
DRI/
McGraw­
Hill,
Standard
&
Poor's,
and
U.
S.
Department
of
Commerce/
international
Trade
Administration.
New
York:
McGraw­
Hill.
pp.
5­
1
to
5­
9.

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

Heil,
Scott
F.,
Ed.
1998.
Ward's
Business
Directory
of
U.
S.
Private
and
Public
Companies
1998,
Volume
5.
Detroit,
MI:
Gale
Research
Inc.
R­
2
Hoover's
Incorporated.
1998.
Hoover's
Company
Profiles.
Austin,
TX:
Hoover's
Incorporated.
<
http://
www.
hoovers.
com/>.

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.

Lillis,
Kevin.
1998.
"
Crude
Petroleum
and
Natural
Gas."
In
U.
S.
Industry
and
Trade
Outlook
`
98.
New
York:
DRI/
McGraw­
Hill,
Standard
&
Poor's,
and
U.
S.
Department
of
Commerce/
International
Trade
Administration.
pp.
3­
1
to
3­
8.

Natural
Gas
Supply
Association
(
NGSA)
et
al.
2000a.
"
Transportation
of
Natural
Gas."
<
http://
www.
naturalgas.
org/
TRANS.
htm>.
As
obtained
on
March
22,
2000.

Natural
Gas
Supply
Association
(
NGSA)
et
al.
2000b.
"
Storage
of
Natural
Gas."
<
http://
www.
naturalgas.
org/
STOR2.
htm>.
As
obtained
on
March
22,
2000.

Natural
Gas
Supply
Association
(
NGSA)
et
al.
2000c.
"
Natural
Gas
Production."
<
http://
www.
naturalgas.
org/
PRODUCT.
HTM>.
As
obtained
on
March
22,
2000.

Office
of
Pipeline
Safety
(
OPS),
U.
S.
Department
of
Transportation.
2000.
"
Annual
Mileage
Totals:
Transmission
&
Distribution."
<
http://
www.
ops.
dot.
gov/
gtannual.
htm>.
As
obtained
on
March
22,
2000.

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.

Reuters
News
Service.
November
10,
1999.
"
EIA
Sees
Cheaper
Power,
Rising
Carbon,
Less
Nukes."
Reuters
News
Service.

Taylor,
Melanie.
May
17,
2000.
Memorandum:
Cost­
Effectiveness
Strategies
of
Abovethe
Floor
MACT
Options
for
Existing
Stationary
Combustion
Turbines.
To:
Sinis
Roy,
EPA/
OAQPS/
ESD/
Combustion
Group.

Seimens
Westinghouse.
August
31,
1999.
Presentation.

Siemens.
Fossil
Power
Generation.
<
www.
siemens.
de/
kwv/
e/
foa/
f/
products/
gvd.
htm>.
As
obtained
on
November
3,
1999.
R­
3
Tussing,
Arlon
R.,
and
Bob
Tippee.
1995.
The
Natural
Gas
Industry:
Evolution,
Structure,

and
Economics.
2nd
Edition.
Tulsa,
OK:
PennWell
Publishing
Company.

U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1995a.
1992
Census
of
Mineral
Industries,
Industry
Series:
Crude
Petroleum
and
Natural
Gas.
MIC92­
I­
13A.
Washington,
DC:
U.
S.
Department
of
Commerce.

U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1995b.
1992
Census
of
Mineral
Industries,
Industry
Series:
Natural
Gas
Liquids.
MIC92­
I­
13B.
Washington,
DC:
U.
S.
Department
of
Commerce.

U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1995c.
1992
Census
of
Mineral
Industries,
Industry
Series:
Oil
and
Gas
Field
Services.
MIC92­
I­
13C.
Washington,
DC:
U.
S.
Department
of
Commerce.

U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1999a.
1997
Economic
Census,
Mining,
Industry
Series:
Crude
Petroleum
and
Natural
Gas
Extraction.
EC97N­
2111A.
Washington,
DC:
U.
S.
Department
of
Commerce.

U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1999b.
1997
Economic
Census,
Mining,
Industry
Series:
Natural
Gas
Liquid
Extraction.
EC97N­
2111b.
Washington,
DC:
U.
S.
Department
of
Commerce.

U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1999c.
1997
Economic
Census,
Mining,
Industry
Series:
Drilling
Oil
and
Gas
Wells.
EC97N­
2131A.
Washington,
DC:
U.
S.
Department
of
Commerce.

U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1999d.
1997
Economic
Census,
Mining,
Industry
Series:
Support
Activities
for
Oil
and
Gas
Operations.
EC97N­
2131B.
Washington,
DC:
U.
S.
Department
of
Commerce.

U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
2000.
1997
Economic
Census,
Transportation
and
Warehousing:
Geographic
Area
Series.
EC97T48A­
US.
Washington,
DC:
Government
Printing
Office.

U.
S.
Department
of
Energy,
Energy
Information
Administration
(
EIA).
1996a.
The
Changing
Structure
of
the
Electric
Power
Industry:
An
Update.
DOE/
EIA­
0562(
96).
Washington,
DC:
U.
S.
Department
of
Energy.
R­
4
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.

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.

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).
1998b.
The
Changing
Structure
of
the
Electric
Power
Industry:
Selected
Issues,
1998.
DOE/
EIA­
0562(
98).
Washington,
DC:
U.
S.
Department
of
Energy.

U.
S.
Department
of
Energy,
Energy
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.

U.
S.
Department
of
Energy,
Energy
Information
Administration
(
EIA).
"
Annual
Energy
Outlook
1999
 
Market
Trend
 
Electricity."
<
http://
www.
eia.
doe.
gov/
oiaf/
aeo99/
electricity.
html>.
As
accessed
November
15,
1999a.

U.
S.
Department
of
Energy,
Energy
Information
Administration
(
EIA),
Office
of
Integrated
Analysis
and
Forecasting.
"
Competitive
Electricity
Price
Projections."
<
http://
www.
eia.
doe.
gov/
oia/
elepri97/
chap3.
html>.
As
obtained
on
November
15,
1999b.

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).
1999d.
Natural
Gas
1998:
Issues
and
Trends.
Washington,
DC:
U.
S.
Department
of
Energy.

U.
S.
Department
of
Energy,
Energy
Information
Administration
(
EIA).
1999e.
Natural
Gas
Annual
1998.
Washington,
DC:
U.
S.
Department
of
Energy.
R­
5
U.
S.
Department
of
Energy,
Energy
Information
Administration
(
EIA).
1999f.
Petroleum
Supply
Annual
1998,
Volume
I.
Washington
DC:
U.
S.
Department
of
Energy.

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.

U.
S.
Department
of
Energy,
Energy
Information
Administration
(
EIA).
1999h.
U.
S.
Crude
Oil,
Natural
Gas,
and
Natural
Gas
Liquids
Reserves
1998
Annual
Report.
Washington,
DC:
U.
S.
Department
of
Energy.

U.
S.
Department
of
Energy,
Energy
Information
Administration
(
EIA).
2000.
Electric
Power
Annual
1999,
Volume
II.
Washington,
DC:
U.
S.
Department
of
Energy.

U.
S.
Department
of
Energy,
Energy
Information
Administration
(
EIA).
"
Supplement
Tables
to
the
AEO
2000."
<
http://
www.
eia.
doe.
gov/
oiaf/
aeo/
supplement/
index.
html>.
As
obtained
on
June
20,
2001.

U.
S.
Environmental
Protection
Agency.
1999a.
Economic
Analysis
Resource
Document.
Research
Triangle
Park,
NC:
Office
of
Air
Quality
Planning
and
Standards.

U.
S.
Environmental
Protection
Agency.
1999b.
EPA
Office
of
Compliance
Sector
Notebook
Project:
Profile
of
the
Oil
and
Gas
Extraction
Industry.
Washington,
DC:
U.
S.
Environmental
Protection
Agency.

Whelan,
Michael.
1998.
"
Improving
Compressor
Station
Performance:
Getting
at
the
Heart
of
the
Matter."
<
http://
www.
gri.
org/
pub/
content/
sep/
19990923/
145119/
wtcompressor12.
html>.
A­
1
(
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

characterized
the
supply
and
demand
in
the
energy
markets,


characterized
supply
and
demand
responses
in
industrial
and
commercial
markets,


introduced
a
policy
"
shock"
into
the
electricity
market
by
using
control
costinduced
shifts
in
the
supply
functions
of
affected
supply
segments
(
new
and
existing
sources),


introduced
indirect
shifts
in
market
supply
functions
resulting
from
changes
in
energy
prices

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
(
Q
Si)
using
a
single
representative
supplier
with
an
upward­
sloping
supply
curve.
The
Cobb­
Douglas
(
CD)
function
specification
is
A­
2
(
A.
2)

(
A.
3)
where
=
the
supply
of
energy
product
i,

A
i
=
a
parameter
that
calibrates
the
supply
equation
to
replicate
the
estimated
2005
level
of
production
(
Btu),

p
i
=
the
2005
($/
Btu)
market
price
for
product
i,
and
c
i
=
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
(
P
0i).
With
regulation,
affected
sources
are
willing
to
supply
their
generation
capacity
if
the
new
price
(
P
1i)
exceeds
costs
(
baseline
+
direct
+
indirect)
:

A.
1.2
Demand
Side
Modeling
Market
demand
in
the
energy
markets
(
Q
Di)
is
expressed
as
the
sum
of
the
energy,
residential,
transportation,
industrial,
and
commercial
sectors:
A­
3
(
A.
4)

(
A.
5)

(
A.
6)
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
q
D
is
demand
for
energy,
Q
D
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):
1The
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.

2The
approach
is
based
on
a
mathematical
model
of
tax
incidence
analysis
decribed
in
Nicholson
(
1998)
pages
444­
445.

A­
4
(
A.
7)
where
 
is
the
fuel
share1,
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
price2:

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
=
Q
D)
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)
Q
0
 
0.5( 
Q)
( 
P)],
(
A.
8)

where
Q
0
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:
3Multiplying
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)
Q
1
 
0.5
( 
Q)
( 
P)]
(
P
1
Q
1)/(
P
1
Q
1)


CS
=
 
[
%

P
 
0.5
(%

P)
(%

Q)]
(
P
1
Q
1).
(
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/
Q
1)
 
 
P)(
Q
1
 
 
Q)]+
0.5
[(
CC/
Q
1
 
 
P)
( 
Q)],
(
A.
10)

where
CC/
Q
1
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,
3
and
compliance
costs:

 
PS
=
 
[((
CC/
Q
1)
 
 
P)(
Q
1
 
 
Q)]+
0.5
[((
CC/
Q
1)
 
 
P)( 
Q)](
P
1
Q
1)/(
P
1
Q
1)

 
PS
=
 
[(%
cost
shift
 
% 
P)(
1
 
% 
Q)+
0.5
(%
cost
shift
 
% 
P
)(% 
Q)][
P
1
Q
1]

 
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
NESHAP,
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
power
markets.
The
80/
20
percent
was
obtained
from
discussions
with
industry
experts.
B­
2
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
870.4
852.5
835.2
Change
in
consumer
surplus
 
878.6
 
860.3
 
842.7
Change
in
social
welfare
 
8.1
 
7.8
 
7.5
Table
B­
2.
Sensitivity
Analysis:
Elasticity
of
Supply
in
the
Electricity
Markets
ES
=
 
25%
Base
Case
ES
=
+
25%

Change
in
producer
surplus
942.4
852.5
778.8
Change
in
consumer
surplus
 
951.2
 
860.3
 
785.8
Change
in
social
welfare
 
8.8
 
7.8
 
7.0
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
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
853.0
852.5
851.9
Change
in
consumer
surplus
 
860.9
 
860.3
 
859.8
Change
in
social
welfare
 
7.8
 
7.8
 
7.8
B­
4
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
852.5
194.2
Change
in
consumer
surplus
 
860.3
 
208.6
Change
in
social
welfare
 
7.8
 
14.3
TECHNICAL
REPORT
DATA
(
Please
read
Instructions
on
reverse
before
completing)

1.
REPORT
NO.

EPA­
452/
R­
03­
014
2.
3.
RECIPIENT'S
ACCESSION
NO.

4.
TITLE
AND
SUBTITLE
Economic
Impact
Analysis
of
the
Final
Stationary
Combustion
Turbines
NESHAP:
Final
Report
5.
REPORT
DATE
August
2003
6.
PERFORMING
ORGANIZATION
CODE
7.
AUTHOR(
S)
8.
PERFORMING
ORGANIZATION
REPORT
NO.

RTI
Project
Number
7647­
004­
385
9.
PERFORMING
ORGANIZATION
NAME
AND
ADDRESS
RTI
International
Center
for
Regulatory
Economics
and
Policy
Research,
Hobbs
Bldg.
Research
Triangle
Park,
NC
27709
10.
PROGRAM
ELEMENT
NO.

11.
CONTRACT/
GRANT
NO.

68­
D­
99­
024
12.
SPONSORING
AGENCY
NAME
AND
ADDRESS
Director
Office
of
Air
Quality
Planning
and
Standards
Office
of
Air
and
Radiation
U.
S.
Environmental
Protection
Agency
Research
Triangle
Park,
NC
27711
13.
TYPE
OF
REPORT
AND
PERIOD
COVERED
14.
SPONSORING
AGENCY
CODE
EPA/
200/
04
15.
SUPPLEMENTARY
NOTES
16.
ABSTRACT
This
report
evaluates
the
economic
impacts
of
the
Final
Stationary
Combustion
Turbines
NESHAP.
The
social
costs
of
the
rule
are
estimated
by
incorporating
the
expected
costs
of
compliance
in
a
partial
equilibrium
model
and
projecting
the
market
impacts.
The
report
also
provides
the
screening
analysis
for
small
business
impacts.

17.
KEY
WORDS
AND
DOCUMENT
ANALYSIS
a.
DESCRIPTORS
b.
IDENTIFIERS/
OPEN
ENDED
TERMS
c.
COSATI
Field/
Group
economic
impacts
small
business
impacts
social
costs
Air
Pollution
Control
Economic
Impact
Analysis
Regulatory
Flexibility
Analysis
18.
DISTRIBUTION
STATEMENT
Release
Unlimited
19.
SECURITY
CLASS
(
Report)

Unclassified
21.
NO.
OF
PAGES
156
20.
SECURITY
CLASS
(
Page)

Unclassified
22.
PRICE
EPA
Form
2220­
1
(
Rev.
4­
77)
PREVIOUS
EDITION
IS
OBSOLETE
United
States
Office
of
Air
Quality
Planning
and
Standards
Publication
No.
EPA­
452/
R­
03­
014
Environmental
Protection
Air
Quality
Strategies
and
Standards
Division
August
2003
Agency
Research
Triangle
Park,
NC