Document ID: EPA-HQ-OAR-2002-0058-0610
Agency: epa
Document Type: Supporting & Related Material
Title: 
Posted Date: 2004-02-26T05:00Z

Regulatory
Impact
Analysis
for
the
Industrial
Boilers
and
Process
Heaters
NESHAP
Final
Report
viii
EPA­
452/
R­
04­
002
February
2004
Regulatory
Impact
Analysis
for
the
Industrial
Boilers
and
Process
Heaters
NESHAP
U.
S.
Environmental
Protection
Agency
Office
of
Air
Quality
Planning
and
Standards
Air
Quality
Strategies
and
Standards
Division
Innovative
Strategies
and
Economics
Group
Research
Triangle
Park,
NC
ix
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
3
2
Boiler
and
Process
Heater
Technologies
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2­
1
2.1
Characteristics
of
Steam
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2­
2
2.2
Fossil­
Fuel
Boiler
Characterization
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2­
4
2.2.1
Industrial,
Commercial,
and
Institutional
Boilers
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2­
5
2.2.2
Heat
Transfer
Configurations
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2­
5
2.2.3
Major
Design
Types
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2­
6
2.2.3.1
Stoker­
Fired
Boilers
(
Coal)
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2­
6
2.2.3.2
Pulverized
Coal
Boilers
(
Coal)
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2­
6
2.2.3.3
Fluidized
Bed
Combustion
(
FBC)
Boilers
(
Coal)
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2­
7
2.2.3.4
Tangentially
Fired
Boilers
(
Coal,
Oil,
Natural
Gas)
.
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2­
7
2.2.3.5
Wall­
fired
Boilers
(
Coal,
Oil,
Natural
Gas)
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2­
8
2.3
Process
Heater
Characterization
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2­
8
2.3.1
Classes
of
Process
Heaters
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2­
8
2.3.2
Major
Design
Types
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2­
9
2.3.2.1
Combustion
Chamber
Set­
Ups
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2­
10
2.3.2.2
Combustion
Air
Supply
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2­
10
2.3.2.3
Tube
Configurations
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2­
11
2.3.2.4
Burners
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2­
12
x
3
Profile
of
Affected
Units
and
Facilities
and
Compliance
Costs
.
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3­
1
3.1
Profile
of
Existing
Boiler
and
Process
Heaters
Units
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3­
1
3.1.1
Distribution
of
Existing
Boilers
and
Facilities
by
Industry
.
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3­
2
3.1.2
Technical
Characteristics
of
Existing
Boilers
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3­
2
3.1.2.1
Final
Rule
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3­
2
3.2
Methodology
for
Estimating
Cost
Impacts
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3­
5
3.3
Projection
of
New
Boilers
and
Process
Heaters
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3­
14
3.4
National
Engineering
Population,
Cost
Estimates,
and
Cost­
Effectiveness
Estimates
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3­
15
4
Profiles
of
Affected
Industries
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4­
1
4.1
Textile
Mill
Products
(
SIC
22/
NAICS
313)
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4­
1
4.2
Lumber
and
Wood
Products
(
SIC
24/
NAICS
321)
.
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4­
1
4.2.1
Supply
Side
of
the
Industry
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4­
2
4.2.1.1
Production
Processes
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4­
2
4.2.1.2
Types
of
Output
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4­
4
4.2.1.3
Major
By­
Products
and
Co­
Products
.
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4­
4
4.2.1.4
Costs
of
Production
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4­
4
4.2.1.5
Capacity
Utilization
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4­
5
4.2.2
Demand
Side
of
the
Industry
.
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4­
5
4.2.3
Product
Characteristics
.
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4­
6
4.2.4
Uses
and
Consumers
of
Outputs
.
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4­
6
4.2.5
Organization
of
the
Industry
.
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4­
6
4.2.6
Markets
and
Trends
.
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4­
9
4.3
Furniture
and
Related
Product
Manufacturing
(
SIC
25/
NAICS
337)
.
.
.
.
.
.
.
4­
9
4.4
Paper
and
Allied
Products
(
SIC
26/
NAICS
322)
.
.
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4­
10
4.4.1
Supply
Side
of
the
Industry
.
.
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4­
11
4.4.1.1
Production
Process
.
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4­
11
4.4.1.2
Types
of
Output
.
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4­
12
4.4.1.3
Major
By­
Products
and
Co­
Products
.
.
.
.
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.
.
4­
12
xi
4.4.1.4
Costs
of
Production
.
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4­
13
4.4.1.5
Capacity
Utilization
.
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4­
13
4.4.2
Demand
Side
of
the
Industry
.
.
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4­
14
4.4.2.1
Product
Characteristics
.
.
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.
.
4­
14
4.4.2.2
Uses
and
Consumers
of
Products
.
.
.
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.
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.
.
4­
14
4.4.3
Organization
of
the
Industry
.
.
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.
4­
14
4.4.4
Markets
and
Trends
.
.
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.
.
4­
16
4.5
Medicinal
Chemicals
and
Botanical
Products
and
Pharmaceutical
Preparations
(
SICs
2833,
2834/
NAICS
32451)
.
.
.
.
.
.
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.
4­
16
4.5.1
Supply
Side
of
the
Industry
.
.
.
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.
.
4­
17
4.5.1.1
Production
Processes
.
.
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.
4­
17
4.5.1.2
Types
of
Output
.
.
.
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.
.
4­
18
4.5.1.3
Major
By­
Products
and
Co­
Products
.
.
.
.
.
.
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.
.
.
.
.
.
.
.
4­
18
4.5.1.4
Costs
of
Production
.
.
.
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4­
18
4.5.1.5
Capacity
Utilization
.
.
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4­
20
4.5.2
Demand
Side
of
the
Industry
.
.
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.
4­
20
4.5.3
Organization
of
the
Industry
.
.
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4­
21
4.5.4
Markets
and
Trends
.
.
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4­
23
4.6
Industrial
Organic
Chemicals
Industry
(
SIC
2869/
NAICS
3251)
.
.
.
.
.
.
.
.
.
4­
24
4.6.1
Supply
Side
of
the
Industry
.
.
.
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4­
24
4.6.1.1
Production
Processes
.
.
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.
4­
24
4.6.1.2
Types
of
Output
.
.
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4­
25
4.6.1.3
Major
By­
Products
and
Co­
Products
.
.
.
.
.
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.
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.
.
4­
26
4.6.1.4
Costs
of
Production
.
.
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4­
26
4.6.1.5
Capacity
Utilization
.
.
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.
4­
26
4.6.2
Demand
Side
of
the
Industry
.
.
.
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.
4­
28
4.6.3
Organization
of
the
Industry
.
.
.
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.
4­
28
4.6.4
Markets
and
Trends
.
.
.
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.
4­
28
4.7
Electric
Services
(
SIC
4911/
NAICS
22111)
.
.
.
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.
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.
4­
28
4.7.1
Electricity
Production
.
.
.
.
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4­
29
4.7.1.1
Generation
.
.
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.
4­
31
4.7.1.2
Transmission
.
.
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.
4­
32
4.7.1.3
Distribution
.
.
.
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4­
32
4.7.2
Cost
of
Production
.
.
.
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.
.
4­
32
4.7.3
Organization
of
the
Industry
.
.
.
.
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.
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.
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.
4­
33
xii
4.7.3.1
Utilities
.
.
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4­
34
4.7.3.2
Nonutilities
.
.
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.
4­
36
4.7.4
Demand
Side
of
the
Industry
.
.
.
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.
4­
36
4.7.4.1
Electricity
Consumption
.
.
.
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.
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.
4­
36
4.7.4.2
Trends
in
the
Electricity
Market
.
.
.
.
.
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.
4­
38
5
Economic
Analysis
Methodology
.
.
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.
.
5­
1
5.1
Background
on
Economic
Modeling
Approaches
.
.
.
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.
.
5­
1
5.1.1
Modeling
Dimension
1:
Scope
of
Economic
Decisionmaking
.
.
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.
5­
2
5.1.2
Modeling
Dimension
2:
Interaction
Between
Economic
Sectors
.
.
.
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.
5­
3
5.2
Selected
Modeling
Approach
for
Boilers
and
Process
Heaters
Analysis
.
.
.
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.
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.
5­
4
5.2.1
Directly
Affected
Markets
.
.
.
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.
.
5­
5
5.2.1.1
Electricity
Market
.
.
.
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.
5­
7
5.2.1.2
Petroleum
Market
.
.
.
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.
.
5­
7
5.2.1.3
Goods
and
Services
Markets:
Agriculture,
Manufacturing,
Mining,
Commercial,
and
Transportation
.
.
.
.
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.
5­
8
5.2.2
Indirectly
Affected
Markets
.
.
.
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.
5­
11
5.2.2.1
Market
for
Coal
.
.
.
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.
5­
11
5.2.2.2
Natural
Gas
Market
.
.
.
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.
5­
11
5.2.2.3
Goods
and
Services
Markets
.
.
.
.
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.
.
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.
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.
.
.
5­
12
5.2.2.4
Impact
on
Residential
Sector
.
.
.
.
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.
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.
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.
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.
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.
.
5­
12
5.3
Operationalizing
the
Economic
Impact
Model
.
.
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.
5­
12
5.3.1
Computer
Model
.
.
.
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.
5­
14
5.3.2
Calculating
Changes
in
Social
Welfare
.
.
.
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.
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.
.
5­
17
6
Economic
Impact
Analysis
Results
.
.
.
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.
.
6­
1
6.1
Social
Cost
Estimates
.
.
.
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.
.
.
6­
1
6.2
National
Market­
Level
Impacts
.
.
.
.
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.
.
6­
2
6.3
Executive
Order
13211
(
Energy
Effects)
.
.
.
.
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.
.
6­
5
xiii
6.4
Conclusions
.
.
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.
6­
6
7
Small
Entity
Impacts
.
.
.
.
.
.
.
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.
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.
.
.
.
.
.
7­
1
7.1
Background
on
Small
Entity
Screenings
.
.
.
.
.
.
.
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.
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.
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.
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.
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.
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.
.
.
.
.
.
7­
1
7.2
Identifying
Small
Entities
.
.
.
.
.
.
.
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.
.
.
7­
2
7.3
Analysis
of
Facility­
Level
and
Parent­
Level
Data
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
.
.
.
7­
3
7.4
Small
Entity
Impacts
.
.
.
.
.
.
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.
.
.
7­
7
7.5
Affected
Government
Entities
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
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.
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.
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.
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.
.
.
.
7­
7
7.6
Assessment
of
SBREFA
Screening
.
.
.
.
.
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.
.
.
7­
11
8
Emissions
Inventories
and
Air
Quality
Changes
.
.
.
.
.
.
.
.
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.
.
.
.
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.
.
.
8­
1
8.1
Results
in
Brief
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
.
.
.
8­
1
8.2
Introduction
.
.
.
.
.
.
.
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.
.
.
8­
1
8.3
Baseline
Emissions
.
.
.
.
.
.
.
.
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.
.
.
.
.
.
8­
2
8.3.1
EPA's
Baseline
Inventory
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
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.
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.
.
.
.
.
.
.
.
8­
2
8.3.2
The
MACT
Floor
.
.
.
.
.
.
.
.
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.
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.
.
.
.
.
8­
3
8.4
Air
Quality
Impacts
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
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.
.
.
.
.
.
.
.
8­
6
8.4.1
EPA's
Baseline
Inventory
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
.
.
.
.
.
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.
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.
.
.
.
.
.
.
8­
6
8.4.2
EPA's
Baseline
Inventory
.
.
.
.
.
.
.
.
.
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.
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.
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.
.
.
8­
7
8.4.2.1
MACT
Floor
Option
.
.
.
.
.
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.
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.
.
.
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.
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.
.
.
.
.
.
8­
7
8.4.3
Visibility
Degradation
Estimates
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
8­
11
8.4.4
Residential
Visibility
Improvements
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
8­
12
8.4.5
Recreational
Visibility
Improvements
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
8­
13
9
Qualitative
Assessment
of
Benefits
of
Emission
Reductions
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
9­
1
9.1
Identification
of
Potential
Benefit
Categories
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
9­
1
xiv
9.2
Qualitative
Description
of
Air
Related
Benefits
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
9­
1
9.2.1
Benefits
of
Reducing
HAP
Emissions
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
9­
1
9.2.1.1
Health
Benefits
of
HAP
Reductions
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
9­
2
9.2.1.2
Welfare
Benefits
of
HAP
Reductions
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
9­
6
9.2.2
Benefits
of
Reducing
Other
Pollutants
Due
to
HAP
Controls
.
.
.
.
.
.
.
9­
7
9.2.2.1
Benefits
of
Particulate
Matter
Reductions
.
.
.
.
.
.
.
.
.
.
.
.
.
9­
7
9.2.2.2
Benefits
of
Sulfur
Dioxide
Reductions
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
9­
8
9.3
Lack
of
Approved
Methods
to
Quantify
HAP
Benefits
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
9­
8
9.4
Summary
.
.
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.
.
9­
9
10
Quantified
Benefits
.
.
.
.
.
.
.
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.
.
.
10­
1
10.1
Results
in
Brief
.
.
.
.
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.
.
10­
1
10.2
Introduction
.
.
.
.
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.
.
.
10­
2
10.3
Overview
of
Benefits
Analysis
Methodology
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
10­
3
10.3.1
Methods
for
Estimating
Benefits
from
Air
Quality
Improvements
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
.
.
10­
6
10.3.2
Methods
for
Describing
Uncertainty
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
10­
8
10.4
Phase
One
Analysis:
Modeled
Air
Quality
Change
and
Health
Effects
Resulting
from
a
Portion
of
Emission
Reductions
at
Boiler
and
Process
Heater
Sources
.
.
.

10­
12
10.4.1
Quantifying
Individual
Health
Effect
Endpoints
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
10­
15
10.4.1.1
Concentration­
Response
Functions
for
Premature
Mortality.
.
.
.
.
10­
16
10.4.2
Valuing
Individual
Health
Effect
Endpoints
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
10­
21
10.4.2.1
Valuation
of
Reductions
in
Premature
Mortality
Risk
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
.
.
.
.
.
.
.
.
.
.
.
10­
25
10.4.2.2
Valuation
of
Reductions
in
Chronic
Bronchitis
.
.
.
.
.
.
.
10­
28
10.4.3
Results
of
Phase
One
Analysis:
Benefits
Resulting
from
a
Portion
of
Emission
Reductions
at
Boiler
and
Process
Heater
Sources
.
.
.
.
.
.
10­
29
10.5
Phase
Two
Analysis:
Benefit
Transfer
Valuation
of
Remaining
Emission
Reductions
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
.
.
.
.
.
.
.
.
10­
33
10.5.1
SO2
Benefits
Transfer
Values
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
10­
34
xv
10.5.2
PM
Benefits
Transfer
Values
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
10­
36
10.5.3
Application
of
Benefits
Transfer
Values
to
Phase
Two
Emission
Reductions
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
10­
40
10.6
Total
Benefits
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
.
.
.
.
.
.
.
10­
43
10.7
Limitations
of
the
Analysis
.
.
.
.
.
.
.
.
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.
.
.
.
.
.
.
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.
.
.
.
.
.
10­
47
10.7.1
Uncertainties
and
Assumptions
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
10­
47
10.7.2
Unquantified
Effects
.
.
.
.
.
.
.
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.
.
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.
.
.
.
10­
48
10.8
Benefit­
Cost
Comparisons
.
.
.
.
.
.
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.
.
10­
50
References
.
.
.
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.
.
.
.
.
.
R­
1
Appendix
A
Estimating
Economic
Impacts
in
Markets
Affected
by
the
Boilers
and
Process
Heaters
MACT
.
.
.
.
.
.
.
.
.
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.
.
.
A­
1
Appendix
B
Assumptions
and
Sensitivity
Analysis
.
.
.
.
.
.
.
.
.
.
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.
.
.
.
.
.
B­
1
Appendix
C
Air
Quality
Changes
for
the
Above­
the­
Floor
Option
(
Option
1A)
.
.
.
.
.
.
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.
.
C­
1
Appendix
D
Derivation
of
Quantified
Benefits
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
.
.
.
.
.
.
D­
1
Appendix
E
Impacts
Based
on
Low­
Risk
Threshold
Cutoffs
for
Hydrochloric
Acid
and
Manganese
.
.
.
.
.
.
.
.
.
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.
.
.
.
.
.
E­
1
xvi
LIST
OF
FIGURES
Number
Page
2­
1
Generating
Electricity:
Steam
Turbines
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
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.
.
.
.
.
.
.
.
.
.
.
.
.
.
2­
4
3­
1
Characteristics
of
Units
Affected
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
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.
.
.
.
.
.
.
.
.
.
.
.
3­
5
4­
1
Traditional
Electric
Power
Industry
Structure
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
4­
30
4­
2
Utility
and
Nonutility
Generation
and
Shares
by
Class,
1985
and
1995
.
.
.
.
.
.
.
.
.
.
4­
35
4­
3
Annual
Electricity
Sales
by
Sector
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
4­
38
5­
1
Links
Between
Energy
and
Goods
and
Services
Markets
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
6
5­
2
Market
Effects
of
Regulation­
Induced
Costs
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
8
5­
3
Fuel
Market
Interactions
with
Facility­
Level
Production
Decisions
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
10
5­
4
Operationalizing
the
Estimation
of
Economic
Impact
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
13
5­
5
Changes
in
Economic
Welfare
with
Regulation
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
18
7­
1
Parent
Size
by
Employment
Range
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
.
.
.
.
.
.
.
.
.
.
7­
6
7­
2
Number
of
Parents
by
Sales
Range
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
7­
7
8­
1
Recreational
Visibility
Regions
for
Continental
U.
S.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
8­
15
10­
1
Steps
in
Phase
One
of
the
Benefits
Analysis
for
the
Industrial
Boilers/
Process
Heaters
NESHAP.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
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.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
10­
13
xvii
LIST
OF
TABLES
Number
Page
3­
1
Units
and
Facilities
Affected
by
the
Final
Rule
by
Industry
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
3­
3
3­
2
Testing
and
Monitoring
Costs
for
Units
Covered
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
3­
11
3­
3
Cost
Effectiveness
(
C/
E)
of
Industrial
Boiler
and
Process
Heater
MACT
on
Existing
Units
and
Subcategories
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
3­
13
3­
4
New
Unit
Projections
by
Industry,
MACT
Floor
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
3­
16
3­
5
Unit
Cost
and
Population
Estimates
for
the
Final
Rule
by
Industry,
2005
.
.
.
.
.
.
.
.
.
3­
18
3­
6
Unit
Cost
and
Population
Estimates
for
the
Option
1A
Above­
the­
Floor
Alternative
by
Industry,
2005
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
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.
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.
.
.
.
.
.
.
.
.
.
3­
21
4­
1
Lumber
and
Wood
Products
Markets
Likely
to
Be
Affected
by
the
Regulation
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
.
.
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.
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.
.
.
.
.
.
.
.
.
.
4­
2
4­
2
Value
of
Shipments
for
the
Lumber
and
Wood
Products
Industry
(
SIC
24/
NAICS
321),
1987
 
1996
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
4­
3
4­
3
Inputs
for
the
Lumber
and
Wood
Products
Industry
(
SIC
24/
NAICS
321),
1987
 
1996
4­
5
4­
4
Capacity
Utilization
Ratios
for
Lumber
and
Wood
Products
Industry,
1991
 
1996
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
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.
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.
.
.
.
.
.
.
.
4­
6
4­
5
Size
of
Establishments
and
Value
of
Shipments
for
the
Lumber
and
Wood
Products
Industry
(
SIC
24/
NAICS
321)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
4­
7
4­
6
Measures
of
Market
Concentration
for
Lumber
and
Wood
Products
Markets
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
.
.
.
.
.
.
.
.
.
.
4­
8
4­
7
Paper
and
Allied
Products
Industry
Markets
Likely
to
Be
Affected
by
Regulation
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
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.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
4­
10
4­
8
Value
of
Shipments
for
the
Paper
and
Allied
Products
Industry
(
SIC
26/
NAICS
322),
1987
 
1996
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
4­
11
4­
9
Inputs
for
the
Paper
and
Allied
Products
Industry
(
SIC
26/
NAICS
322),
1987
 
1996
4­
13
4­
10
Capacity
Utilization
Ratios
for
the
Paper
and
Allied
Products
Industry,
1991
 
1996
.
4­
14
4­
11
Size
of
Establishments
and
Value
of
Shipments
for
the
Paper
and
Allied
Products
Industry
(
SIC
26/
NAICS
322)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
4­
15
4­
12
Measurements
of
Market
Concentration
for
Paper
and
Allied
Products
Markets
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
4­
16
4­
13
Value
of
Shipments
for
the
Medicinals
and
Botanicals
and
Pharmaceutical
Preparations
Industries,
1987
 
1996
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
4­
17
4­
14
Inputs
for
Medicinal
Chemicals
and
Botanical
Products
Industry
(
SIC
2833/
NAICS
32451),
1987
 
1996
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
4­
19
xviii
4­
15
Inputs
for
the
Pharmaceutical
Preparations
Industry
(
SIC
2834/
NAICS
32451),
1987
 
1996
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
4­
20
4­
16
Capacity
Utilization
Ratios
for
the
Medicinal
Chemicals
and
Botanical
Products
(
SIC
2833/
NAICS
32451)
and
Pharmaceutical
Preparations
(
SIC
2834/
NAICS
32451)
Industries,
1991
 
1996
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
4­
21
4­
17
Size
of
Establishments
and
Value
of
Shipments
for
the
Medicinal
Chemicals
and
Botanical
Products
(
SIC
2833/
NAICS
32451)
and
Pharmaceutical
Preparations
(
SIC
2834/
NAICS
32451)
Industries
.
.
.
.
.
.
.
.
.
.
.
.
.
4­
22
4­
18
Measures
of
Market
Concentration
for
the
Medicinal
Chemicals
and
Botanical
Products
(
SIC
2833/
NAICS
32451)
and
Pharmaceutical
Preparations
(
SIC
2834/
NAICS
32451)
Industries
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
4­
23
4­
19
Value
of
Shipments
for
the
Industrial
Organic
Chemicals,
N.
E.
C.
Industry
(
SIC
2869/
NAICS
3251),
1987­
1996
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
4­
25
4­
20
Inputs
for
the
Industrial
Organic
Chemicals
Industry
(
SIC
2869/
NAICS
3251),
1987
 
1996
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
4­
27
4­
21
Capacity
Utilization
Ratios
for
the
Industrial
Organic
Chemicals
Industry
(
SIC
2869/
NAICS
3251),
1991
 
1996
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
4­
27
4­
22
Size
of
Establishments
and
Value
of
Shipments
for
the
Industrial
Organic
Chemicals
Industry
(
SIC
2869/
NAICS
3251)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
4­
29
4­
23
Net
Generation
by
Energy
Source,
1995
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
4­
31
4­
24
Total
Expenditures
in
1996
($
103)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
4­
33
4­
25
Number
of
Electricity
Suppliers
in
1999
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
4­
34
4­
26
U.
S.
Electric
Utility
Retail
Sales
of
Electricity
by
Sector,
1989
Through
1998
(
106
kWh)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
4­
37
4­
27
Key
Parameters
in
the
Cases
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
4­
39
5­
1
Comparison
of
Modeling
Approaches
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
2
5­
2
Supply
and
Demand
Elasticities
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
15
5­
3
Fuel
Price
Elasticities
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
17
6­
1
Social
Cost
Estimates
($
1998
106):
Final
Rule
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
1
6­
2
Distribution
of
Social
Costs
by
Sector/
Market:
Final
Rule
($
1998
106)
.
.
.
.
.
.
.
.
.
.
.
6­
3
6­
3
Market­
Level
Impacts
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
4
7­
1
Summary
of
Small
Entity
Impacts
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
7­
1
7­
2
Facility­
Level
and
Parent­
Level
Data
by
Industry
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
7­
4
7­
3
Small
Parent
Entities
by
Industry
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
7­
8
7­
4
Summary
Statistics
for
SBREFA
Screening
Analysis
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
7­
10
7­
5
Regional
Distribution
of
Municipal
Systems
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
7­
11
7­
6
Selected
Municipal
Utilities'
Capacity,
Usage,
and
Consumer
Types
.
.
.
.
.
.
.
.
.
.
.
.
7­
12
7­
7
Supplemental
Screening
Analysis
for
Small
Governmental
Jurisdictions
.
.
.
.
.
.
.
.
.
.
7­
13
xix
7­
8
Profit
Margins
for
Industry
Sectors
with
Affected
Small
Businesses
.
.
.
.
.
.
.
.
.
.
.
.
.
7­
14
8­
1
Summary
of
Nationwide
Baseline
Emissions
and
Emission
Reductions
for
the
MACT
Floor,
Existing
Units
Only
in
2005
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
8­
4
8­
2
HAP
Emission
Reductions
for
the
MACT
Floor
Option,
2005
Existing
Units
Only
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
8­
6
8­
3
Summary
of
2005
Base
Case
PM
Air
Quality
and
Changes
Due
to
MACT
Floor
Option:
Industrial
Boiler/
Process
Heater
Source
Categories
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
8­
8
8­
4
Distribution
of
PM2.5
Air
Quality
Improvements
Over
2005
Population
Due
to
MACT
Floor
Option:
Industrial
Boiler/
Process
Heater
Source
Categories
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
8­
9
8­
5
Summary
of
Absolute
and
Relative
Changes
in
PM
Air
Quality
Due
to
MACT
Floor
Option:
Industrial
Boiler/
Process
Heater
Source
Categories
.
.
.
.
.
.
.
.
.
.
.
.
.
.
8­
10
8­
6
Distribution
of
Populations
Experiencing
Visibility
Improvements
in
2005
Due
to
MACT
Floor
Option:
Industrial
Boiler/
Process
Heater
Source
Categories
.
.
.
.
.
.
.
.
.
.
.
.
.
.
8­
12
8­
7
Summary
of
2005
Baseline
Visibility
and
Changes
by
Region
for
to
MACT
Floor
Option:
Residential
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
8­
13
8­
8
Summary
of
2005
Baseline
Visibility
and
Changes
by
Region
for
to
MACT
Floor
Option:
Recreational
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
8­
14
10­
1
Summary
of
Results:
Estimated
PM­
Related
Benefits
of
the
Industrial
Boilers
and
Process
Heaters
NESHAP
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
10­
2
10­
2
Estimate
of
Emission
Reductions
for
Phases
One
and
Two
of
the
Benefit
Analysis
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
10­
5
10­
3
Primary
Sources
of
Uncertainty
in
the
Benefit
Analysis
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
10­
11
10­
4
PM­
Related
Health
Outcomes
and
Studies
Included
in
the
Base
Analysis
.
.
.
.
.
.
.
.
10­
18
10­
5
Unit
Values
Used
for
Economic
Valuation
of
Health
Endpoints
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
10­
22
10­
6
Phase
One
Analysis:
Base
Estimate
of
Annual
Benefits
Associated
with
Approximately
50%
of
the
Emission
Reductions
from
the
Industrial
Boilers/
Process
Heaters
NESHAP
­
MACT
Floor
Regulatory
Option
in
2005,
Using
Air
Quality
Modeling
&
the
CAPMS
Benefit
Model
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
10­
30
10­
7
Phase
One
Analysis:
Base
Estimate
for
Annual
Benefits
Associated
with
Approximately
50%
of
the
Emission
Reductions
from
the
Industrial
Boilers/
Process
Heaters
NESHAP
­
Above
the
MACT
Floor
Regulatory
Option
in
2005,
Using
Air
Quality
Modeling
&
the
CAPMS
Benefit
Model
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
10­
32
10­
7
Boilers/
Process
Heaters
NESHAP
­
Above
the
MACT
Floor
Regulatory
Option
in
2005,
Using
Air
Quality
Modeling
&
the
CAPMS
Benefit
Model
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
10­
39
10­
8
SO2
Benefit
Transfer
Values
Based
on
Data
From
Phase
One
Analysis­
MACT
Floor
Regulatory
Option
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
10­
35
xx
10­
9
SO2
Benefit
Transfer
Values
Based
on
Data
From
Phase
One
Analysis­
Above
the
MACT
Floor
Regulatory
Option
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
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.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
10­
36
10­
10
PM
Benefit
Transfer
Values
Based
on
Data
From
Phase
One
Analysis­
MACT
Floor
Regulatory
Option
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
10­
38
10­
11
PM
Benefit
Transfer
Values
Based
on
Data
From
Phase
One
Analysis­
MACT
Floor
Regulatory
Option
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
.
.
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.
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.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
10­
39
10­
12
Phase
Two
Analysis:
Base
Estimate
of
Annual
Health
Benefits
Associated
with
Non­
Inventory
Emission
Reductions
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
­
MACT
Floor
Regulatory
Option
in
2005,
Using
Benefit
Transfer
Values..
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
10­
41
10­
13
Phase
Two
Analysis:
Base
Estimate
of
Annual
Health
Benefits
Associated
with
Non­
Inventory
Emission
Reductions
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
­
Above
the
Floor
MACT
Floor
Regulatory
Option
in
2005,
Using
Benefit
Transfer
Values..
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
10­
42
10­
14
Total
Annual
Benefits
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
­
MACT
Floor
Regulatory
Option
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
10­
45
10­
15
Total
Annual
Benefits
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
­
Above
the
MACT
Floor
Regulatory
Option
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
10­
46
10­
16
Significant
Uncertainties
and
Biases
Associated
with
the
Industrial
Boilers/
Process
Heaters
Benefit
Analysis
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
10­
48
10­
17
Unquantified
Benefit
Categories
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
10­
49
10­
18
Annual
Net
Benefits
of
the
Industrial
Boilers
and
Process
Heaters
NESHAP
in
2005
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
10­
53
C­
1
Summary
of
Nationwide
Baseline
Emissions
and
Emission
Reductionsa
for
Option
1A
(
in
tons/
year),
Existing
Units
Onlyb,
c
in
2005
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
C­
1
C­
2
HAP
Emission
Reductions
for
Option
1A,
2005
Existing
Units
Only
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
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.
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.
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.
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.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
C­
2
C­
3
Summary
of
2005
Base
Case
PM
Air
Quality
and
Changes
Due
to
MACT
Above­
the­
Floor
Option:
Industrial
Boiler/
Process
Heater
xxi
Source
Categories
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
C­
3
C­
4
Distribution
of
PM2.5
Air
Quality
Improvements
Over
2005
Population
Due
to
MACT
Above­
the­
Floor
Option:
Industrial
Boiler/
Process
Heater
Source
Categories.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
C­
4
C­
5
Summary
of
Absolute
and
Relative
Changes
in
PM
Air
Quality
Due
to
MACT
Above­
the­
Floor
Option:
Industrial
Boiler/
Process
Heater
Source
Categories
.
.
.
.
.
.
.
C­
5
C
 
6
Distribution
of
Populations
Experiencing
Visibility
Improvements
in
2005
Due
to
MACT
Above­
the­
Floor
Option:
Industrial
Boiler/
Process
Heater
Source
Categories.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
C­
6
C­
7
Summary
of
2005
Baseline
Visibility
and
Changes
by
Region
Due
to
MACT
Above­
the­
Floor
Option:
Residential
(
Average
Annual
Deciviews)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
C­
7
C­
8
Summary
of
2005
Baseline
Visibility
and
Changes
by
Region
for
MACT
Above­
the­
Floor
Option:
Recreational
(
Average
Annual
Deciviews)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
C­
8
D­
1(
a)
Results
of
Air
Quality
and
Benefit
Analyses
for
the
Phase
One
Analysis
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
MACT
Floor
in
2005
(
SO2
Reductions
Only)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
D­
4
D­
1(
b)
Results
of
Air
Quality
and
Benefit
Analyses
for
the
Phase
Two
Analysis
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
MACT
Floor
in
2005
(
SO2
Reductions
Only)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
D­
5
D­
2(
a)
Results
of
Air
Quality
and
Benefit
Analyses
for
the
Phase
One
Analysis
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
MACT
Floor
in
2005
(
PM
Reductions
Only)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
D­
6
D­
2(
b)
Results
of
Air
Quality
and
Benefit
Analyses
for
the
Phase
Two
Analysis
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
MACT
Floor
in
2005
(
PM
Reductions
Only)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
D­
7
D­
3(
a)
Results
of
Air
Quality
and
Benefit
Analyses
for
the
Phase
One
Analysis
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
MACT
Floor
in
2005
(
PM
and
SO2
Reductions
Only)
.
..
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
D­
8
D­
3(
b)
Results
of
Air
Quality
and
Benefit
Analyses
for
the
Phase
Two
Analysis
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
MACT
Floor
in
2005
(
PM
and
SO2
Reductions
Only)
.
..
.
.
.
.
.
.
.
.
..
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
D­
9
D­
4
Total
Benefits
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
­
MACT
Floor
in
2005
(
Combined
Estimates
of
Reduced
Incidences
and
Monetized
Benefits
from
Phase
One
and
Two
Analyses)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
D­
10
D­
5(
a)
Results
of
Air
Quality
and
Benefit
Analyses
for
the
Phase
One
Analysis
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
Above
the
MACT
Floor
in
2005
(
SO2
Reductions
Only).
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
D­
11
xxii
D­
5(
b)
Results
of
Air
Quality
and
Benefit
Analyses
for
the
Phase
Two
Analysis
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
Above
the
MACT
Floor
in
2005
(
SO2
Reductions
Only)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
D­
12
D­
6(
a)
Results
of
Air
Quality
and
Benefit
Analyses
for
the
Phase
One
Analysis
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
Above
the
MACT
Floor
in
2005
(
PM
Reductions
Only)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
D­
13
D­
6(
b)
Results
of
Air
Quality
and
Benefit
Analyses
for
the
Phase
Two
Analysis
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
Above
the
MACT
Floor
in
2005
(
PM
Reductions
Only)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
D­
14
D­
7(
a)
Results
of
Air
Quality
and
Benefit
Analyses
for
the
Phase
One
Analysis
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
Above
the
MACT
Floor
in
2005
(
PM
and
SO2
Reductions
Only)
.
..
.
.
.
.
.
.
.
.
..
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
D­
15
D­
7(
b)
Results
of
Air
Quality
and
Benefit
Analyses
for
the
Phase
Two
Analysis
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
Above
the
MACT
Floor
in
2005
(
PM
and
SO2
Reductions
Only)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
D­
16
D­
8
Total
Benefits
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
­
Above
the
MACT
Floor
in
2005
(
Combined
Estimates
of
Reduced
Incidences
and
Monetized
Benefits
from
Phase
One
and
Two
Analyses).
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
D­
17
Select
List
of
Acronyms
and
Abbreviations
BOC
­
Bureau
of
Census
CAA
­
Clean
Air
Act
COPD
­
Chronic
Obstructive
Pulmonary
Disease
dv
­
Deciview
DOC
­
Department
of
Commerce
DOE
­
Department
of
Energy
EIA
­
Energy
Information
Administration
EO
­
Executive
Order
EPA
­
Environmental
Protection
Agency
FERC­
Federal
Energy
Regulatory
Commission
HAP
­
Hazardous
Air
Pollutant
ICI
­
Industrial/
Commercial/
Institutional
ICR
­
Information
Collection
Request
lb
­
Pound
LDs
­
Loss
Days
LRS
­
Lower
Respiratory
Symptoms
MACT
­
Maximum
Achievable
Control
Technology
mmBtu­
million
British
Thermal
Units
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
PM
­
Particulate
Matter
ppbdv
­
Parts
Per
Billion,
dry
volume
ppm
­
Parts
Per
Million
PRA
­
Paperwork
Reduction
Act
of
1995
RIA
­
Regulatory
Impact
Analysis
viii
RFA
­
Regulatory
Flexibility
Act
SAB
­
Science
Advisory
Board
SBA
­
Small
Business
Administration
SBREFA
­
Small
Business
Regulatory
Enforcement
Fairness
Act
of
1996
SIC
­
Standard
Industrial
Classification
SO2
­
Sulfur
Dioxide
TAC
­
Total
Annual
Cost
tpd
­
Tons
Per
Day
tpy
­
Tons
Per
Year
UMRA
­
Unfunded
Mandates
Reform
Act
URS
­
Upper
Respiratory
Symptoms
VSL
­
Value
of
Statistical
Life
VOCs
­
Volatile
Organic
Compounds
WLDs
­
Work
Loss
Days
ES­
1
EXECUTIVE
SUMMARY
EPA
is
issuing
a
rule
to
reduce
hazardous
air
pollutant
(
HAPs)
emissions
from
existing
and
new
industrial
boilers
and
process
heaters
that
are
major
sources.
This
rule
is
a
National
Emission
Standards
for
Hazardous
Air
Pollutants
(
NESHAP),
and
will
reduce
HAP
emissions
by
requiring
affected
industrial
boilers
and
process
heaters
to
meet
emissions
limits
in
order
to
comply
with
the
Maximum
Achievable
Control
Technology
(
MACT)
floor
for
these
sources.
This
MACT
floor
level
of
control
is
the
minimum
level
these
sources
must
meet
to
comply
with
the
rule.
The
major
HAPs
whose
emissions
will
be
reduced
are
hydrochloric
acid,
hydrofluoric
acid,
arsenic,
beryllium,
cadmium,
and
nickel.
The
rule
will
also
lead
to
emission
reductions
of
other
pollutants
such
as
particulate
matter
(
PM10
and
PM2.5),
sulfur
dioxide
(
SO2),
and
mercury
(
Hg).

The
rule
requires
emissions
reductions
necessary
to
meet
the
MACT
by
having
affected
existing
sources
comply
with
emissions
limits
defined
in
terms
of
pound
per
mmBTU
heat
input
of
emissions
rate
for
each
HAP.
For
new
sources,
the
definition
for
emissions
limits
is
based
on
the
source
using
the
most
stringent
control
technology
for
reduction
of
each
HAP.

The
rule
is
expected
to
reduce
HAP
emissions
from
existing
sources
by
about
59,000
tons
per
year
by
2005.
Of
this
amount,
roughly
43,000
tons
is
hydrochloric
acid,
and
there
is
1,100
tons
in
reductions
of
heavy
metals
such
as
arsenic,
chromium,
lead
and
nickel,
among
others.
The
rule
is
also
expected
to
reduce
PM10
emissions
from
existing
sources
by
560,000
tons
per
year,
and
SO2
emissions
from
existing
sources
by
113,000
tons
per
year
by
2005.
Hg
emissions
will
be
reduced
by
1.7
tons
per
year.
The
rule
will
reduce
HAP
emissions
from
new
sources
by
about
73
tons
in
2005
and
PM10
emissions
by
65
tons
in
2005.
The
annual
compliance
costs
to
existing
sources,
which
include
the
costs
of
control
and
monitoring,
recordkeeping
and
reporting
requirements,
are
estimated
at
$
863
million
(
1999
dollars).
For
new
sources,
the
annual
compliance
costs
are
estimated
at
$
19
million
(
1999
dollars).
The
EPA
is
unable
to
monetize
the
benefits
of
the
HAP
emissions
reductions
due
to
insufficient
scientific
data,
but
is
able
to
monetize
the
benefits
of
the
PM10
and
SO2
emissions
reductions.
The
EPA's
base
estimate
of
the
monetized
benefits
associated
with
the
rule
is
$
16.3
billion
+
B
(
1999
dollars).
The
estimated
difference
between
monetized
benefits
and
costs
for
the
proposed
rule
is
$
15.5
billion
+
B
(
1999
dollars).
The
value
of
B
is
the
potential
value
of
the
large
number
of
unmonetized
benefits
associated
with
this
rule,
including
health
effects
such
as
reductions
in
cancer
leading
to
mortality,
genotoxicity,
liver
and
kidney
damage,
and
cardiovascular
impairment,
and
welfare
effects
such
as
corrosion
of
materials
and
crop
yield
reductions.

There
are
industries
in
43
2­
digit
Standard
Industrial
Classification
(
SIC)
codes
and
3­
digit
North
American
Industrial
Classification
System
(
NAICS)
that
are
affected
by
the
rule,
but
the
changes
in
product
price
and
output
are
estimated
to
be
no
greater
than
0.02
percent
for
any
of
these
affected
industries.
Effects
on
energy
markets
are
expected
to
result
in
no
more
than
a
0.05
percent
in
electricity
rates,
and
petroleum
and
natural
gas
prices.
In
addition,
coal
prices
and
output
will
decline
overall
due
to
a
reduction
in
coal
demand.
Based
on
the
energy
impacts
analysis,
the
Agency
concluded
that
there
is
no
significant
adverse
effect
on
the
supply,
distribution,
and
use
of
energy
associated
with
this
rule.
While
the
economic
impacts
of
the
above
the
floor
option
are
also
low,
the
total
costs
to
consumers
and
producers
(
the
social
costs)
are
more
than
double
those
for
the
final
rule.

Of
the
576
entities
affected
by
this
rule,
185
(
or
31
percent)
are
identified
as
small
entities.
Of
these
small
entities,
31
of
them
have
compliance
costs
of
1
percent
of
sales
or
greater,
and
10
of
these
ES­
2
31
have
compliance
costs
of
3
percent
or
greater.
Based
of
the
relatively
low
number
of
small
entities
affected
and
the
size
of
the
price
increases
these
entities
will
face,
the
Agency
certifies
that
there
will
not
be
significant
impact
on
a
substantial
number
of
small
entities
(
SISNOSE)
associated
with
this
rule.

CHAPTER
1
INTRODUCTION
AND
REGULATORY
ALTERNATIVES
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
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,
referred
to
hereafter
as
the
Act)
for
industrial,
commercial
and
institutional
(
ICI)
boilers
and
process
heaters.
These
combustion
devices
are
used
in
the
production
processes
of
numerous
industries
in
the
U.
S.
The
hazardous
air
pollutants
(
HAPs)
are
generated
by
the
combustion
of
fossil
fuels
and
biomass
in
boilers
and
process
heaters.
The
primary
HAPs
emitted
by
ICI
boilers
and
process
heaters
include
arsenic,
beryllium,
cadmium,
lead,
hydrochloric
acid,
mercury,
and
other
HAPs.
In
addition,
ICI
boilers
and
process
heaters
also
emit
non­
HAP
pollutants
such
as
sulfur
dioxide
and
particulate
matter.
To
inform
this
rulemaking,
the
Innovative
Strategies
and
Economics
Group
(
ISEG)
of
EPA's
Office
of
Air
Quality
Planning
and
Standards
(
OAQPS)
has
developed
a
regulatory
impact
analysis
(
RIA)
to
estimate
the
potential
impacts
of
the
regulation.
This
report
presents
the
results
of
a
set
of
analyses
conducted
by
EPA
in
order
to
assess
the
impacts
of
the
regulation
and
other
alternatives
considered
by
the
Agency.
Compliance
costs,
economic
impacts,
small
entity
impacts,
energy
effects
impacts,
air
quality
changes,
and
benefits
are
included
in
this
RIA.

1.1
Agency
Requirements
for
an
RIA
Congress
and
the
Executive
Office
have
imposed
statutory
and
administrative
requirements
for
conducting
various
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
as
amended
by
EO
13258
requires
a
more
comprehensive
analysis
of
benefits
and
costs
for
proposed
significant
regulatory
actions.
1
The
Executive
Order
defines
"
significant"
regulatory
action
as
one
that
is
likely
to
result
in
a
rule
that
may:

1)
Have
an
annual
effect
on
the
economy
of
$
100
million
or
more
or
adversely
affect
in
a
material
way
the
economy,
a
sector
of
the
economy,
productivity,
competition,
jobs,
the
environment,
public
health
or
safety,
or
state,
local,
or
tribal
governments
or
communities;

2)
Create
a
serious
inconsistency
or
otherwise
interfere
with
an
action
taken
or
planned
by
another
agency;

3)
Materially
alter
the
budgetary
impact
of
entitlements,
grants,
user
fees,
or
loan
programs,
or
the
rights
and
obligation
of
recipients
thereof;

4)
Raise
novel
legal
or
policy
issues
arising
out
of
legal
mandates,
the
President's
priorities,
or
the
principles
set
forth
in
the
Executive
Order.

Pursuant
to
the
terms
of
Executive
Order
12866
as
amended
by
EO
13258,
it
has
been
determined
that
this
rule
is
a
"
significant
regulatory
action"
because
the
annual
costs
of
complying
with
the
rule
are
expected
to
exceed
$
100
million.
Consequently,
this
action
was
submitted
to
OMB
for
review
under
Executive
Order
12866
as
amended
by
EO
13258.
2
Where
appropriate,
agencies
can
propose
and
justify
alternative
definitions
of
"
small
entity."
This
RIA
and
the
screening
analysis
for
small
entities
rely
on
the
SBA
definitions.

1­
2
1.1.1
Regulatory
Flexibility
Act
and
Small
Business
Regulatory
Enforcement
Fairness
Act
of
1996
The
Regulatory
Flexibility
Act
(
RFA)
of
1980
(
PL
96­
354)
generally
requires
that
agencies
conduct
a
screening
analysis
to
determine
whether
a
regulation
adopted
through
notice­
and­
comment
rulemaking
will
have
a
significant
impact
on
a
substantial
number
of
small
entities
(
SISNOSE),
including
small
businesses,
governments,
and
organizations.
If
a
regulation
will
have
such
an
impact,
agencies
must
prepare
an
Initial
Regulatory
Flexibility
Analysis,
and
comply
with
a
number
of
procedural
requirements
to
solicit
and
consider
flexible
regulatory
options
that
minimize
adverse
economic
impacts
on
small
entities.
Agencies
must
then
prepare
a
Final
Regulatory
Flexibility
Analysis
that
provides
an
analysis
of
the
effect
on
small
entities
from
consideration
of
flexible
regulatory
options.
The
RFA's
analytical
and
procedural
requirements
were
strengthened
by
the
Small
Business
Regulatory
Enforcement
Fairness
Act
(
SBREFA)
of
1996
to
include
the
formation
of
a
panel
if
a
proposed
rule
was
determined
to
have
a
SISNOSE.
This
panel
would
be
made
up
of
representatives
of
the
EPA,
the
Small
Business
Administration
(
SBA),
and
OMB.

For
reasons
explained
more
fully
in
Chapter
7
of
this
RIA
and
the
economic
impact
analysis
for
this
proposed
rule,
EPA
has
determined
that
there
is
no
SISNOSE
for
this
rule.
While
there
are
some
impacts
to
some
small
firms
as
estimated
in
the
economic
impact
analysis,
these
impacts
are
not
sufficient
for
a
SISNOSE.
Therefore,
the
EPA
has
not
prepared
a
Regulatory
Flexibility
Analysis
for
this
rule.

The
RFA
and
SBREFA
require
the
use
of
definitions
of
"
small
entities,"
including
small
businesses,
governments,
and
organizations
such
as
non­
profits,
published
by
the
SBA.
2
Screening
analyses
of
economic
impacts
presented
in
Chapter
7
of
this
RIA
examine
potential
impacts
on
small
entities.

1.1.2
Unfunded
Mandates
Reform
Act
of
1995
The
Unfunded
Mandates
Reform
Act
(
UMRA)
of
1995
(
PL­
4)
was
enacted
to
focus
attention
on
federal
mandates
that
require
other
governments
and
private
parties
to
expend
resources
without
federal
funding,
to
ensure
that
Congress
considers
those
costs
before
imposing
mandates,
and
to
encourage
federal
financial
assistance
for
intergovernmental
mandates.
The
Act
establishes
a
number
of
procedural
requirements.
The
Congressional
Budget
Office
is
required
to
inform
Congressional
committees
about
the
presence
of
federal
mandates
in
legislation,
and
must
estimate
the
total
direct
costs
of
mandates
in
a
bill
in
any
of
the
first
five
years
of
a
mandate,
if
the
total
exceeds
$
50
million
for
intergovernmental
mandates
and
$
100
million
for
private­
sector
mandates.

Section
202
of
UMRA
directs
agencies
to
provide
a
qualitative
and
quantitative
assessment
(
or
a
"
written
statement")
of
the
anticipated
costs
and
benefits
of
a
Federal
mandate
that
results
in
annual
expenditures
of
$
100
million
or
more.
The
assessment
should
include
costs
and
benefits
to
State,
local,
and
tribal
governments
and
the
private
sector,
and
identify
any
disproportionate
budgetary
impacts.
Section
205
of
the
Act
requires
agencies
to
identify
and
consider
alternatives,
including
the
least
costly,
most
cost­
effective,
or
least
burdensome
alternative
that
achieves
the
objectives
of
the
rule.

Since
this
rule
may
cause
a
mandate
to
the
private
sector
of
more
than
$
100
million,
EPA
did
provide
an
analysis
of
the
impacts
of
this
rule
on
State
and
local
governments
to
support
compliance
with
Section
202
of
UMRA.
A
summary
of
this
analysis
is
in
Chapter
6
of
this
RIA.
There
are
government
entities
affected
by
this
proposed
regulation,
and
these
are
primarily
municipalities
that
own
industrial
boilers
that
may
need
to
comply.

1.1.3
Paperwork
Reduction
Act
of
1995
1­
3
The
Paperwork
Reduction
Act
of
1995
(
PRA)
requires
Federal
agencies
to
be
responsible
and
publicly
accountable
for
reducing
the
burden
of
Federal
paperwork
on
the
public.
EPA
has
submitted
an
OMB­
83I
form,
along
with
a
supporting
statement,
to
the
OMB
in
compliance
with
the
PRA.
The
OMB­
83I
and
the
supporting
statement
explains
the
need
for
additional
information
collection
requirements
and
provides
respondent
burden
estimates
for
additional
paperwork
requirements
to
State
and
local
governments
associated
with
this
proposed
rule.

1.1.4
Executive
Order
12898
Executive
Order
12898,
"
Federal
Actions
to
Address
Environmental
Justice
in
Minority
Populations
and
Low­
Income
Populations,"
requires
Federal
agencies
to
consider
the
impact
of
programs,
policies,
and
activities
on
minority
populations
and
low­
income
populations.
Disproportionate
adverse
impacts
on
these
populations
should
be
avoided
to
the
extent
possible.
According
to
EPA
guidance,
agencies
are
to
assess
whether
minority
or
low­
income
populations
face
risk
or
exposure
to
hazards
that
is
significant
(
as
defined
by
the
National
Environmental
Policy
Act)
and
that
"
appreciably
exceeds
or
is
likely
to
appreciably
exceed
the
risk
or
rate
to
the
general
population
or
other
appropriate
comparison
group."
(
EPA,
1996).
This
guidance
outlines
EPA's
Environmental
Justice
Strategy
and
discusses
environmental
justice
issues,
concerns,
and
goals
identified
by
EPA
and
environmental
justice
advocates
in
relation
to
regulatory
actions.
The
industrial
boilers
and
process
heaters
rule
is
expected
to
provide
health
and
welfare
benefits
to
populations
around
the
United
States,
regardless
of
race
or
income.

1.1.5
Executive
Order
13045
Executive
Order
13045,
"
Protection
of
Children
from
Environmental
Health
Risks
and
Safety
Risks,"
directs
Federal
agencies
developing
health
and
safety
standards
to
include
an
evaluation
of
the
health
and
safety
effects
of
the
regulations
on
children.
Regulatory
actions
covered
under
the
Executive
Order
include
rulemakings
that
are
economically
significant
under
Executive
Order
12866,
and
that
concern
an
environmental
health
risk
or
safety
risk
that
the
agency
has
reason
to
believe
may
disproportionately
affect
children.
EPA
has
developed
internal
guidelines
for
implementing
E.
O.
13045
(
EPA,
1998).

The
industrial
boilers
and
process
heaters
rule
is
a
"
significant
economic
action,"
because
the
annual
costs
are
expected
to
exceed
$
100
million.
Exposure
to
the
HAPs
whose
emissions
will
be
reduced
by
this
rule
are
known
to
affect
the
health
of
children
and
other
sensitive
populations.
However,
this
rule
is
not
expected
to
have
a
disproportionate
impact
on
children.

1.1.6
Executive
Order
13211
Executive
Order
13211,
"
Actions
Concerning
Regulations
That
Significantly
Affect
Energy
Supply,
Distribution,
or
Use,"
was
published
in
the
Federal
Register
on
May
22,
2001
(
66
FR
28355).
This
executive
order
requires
Federal
Agencies
to
weigh
and
consider
the
effect
of
regulations
on
supply,
distribution,
and
use
of
energy.
To
comply
with
this
executive
order,
Federal
Agencies
are
to
prepare
and
submit
a
"
Statement
of
Energy
Effects"
for
"
significant
energy
actions."
The
executive
order
defines
"
significant
energy
action"
as
the
following:

1)
an
action
that
is
a
significant
regulatory
action
under
Executive
Order
12866
or
any
successor
order,
and
2)
is
likely
to
have
a
significant
adverse
effect
on
the
supply,
distribution,
or
use
of
energy;
or
3)
that
is
designated
by
the
Administrator
of
the
Office
of
Information
and
Regulatory
Affairs
as
a
significant
energy
action.

An
analysis
of
the
effects
of
this
rule
on
supply,
distribution,
and
use
of
energy
was
conducted
as
part
of
the
economic
impact
analysis
and
is
summarized
in
Chapter
7.

1.2
Scope
and
Purpose
of
the
Regulation
1­
4
Section
112
of
the
CAA
requires
EPA
to
promulgate
regulations
for
the
control
of
HAP
emissions
from
each
source
category
listed
under
section
112(
c).
The
statute
requires
the
regulations
to
reflect
the
maximum
degree
of
reductions
in
emissions
of
HAP
that
is
achievable
taking
into
consideration
the
cost
of
achieving
emissions
reductions,
any
nonair
quality
health
and
environmental
impacts,
and
energy
requirements.
This
level
of
control
is
commonly
referred
to
as
MACT.
The
MACT
regulation
can
be
based
on
the
emissions
reductions
achievable
through
application
of
measures,
processes,
methods,
systems,
or
techniques
including,
but
not
limited
to:
(
1)
reducing
the
volume
of,
or
eliminating
emissions
of,
such
pollutants
through
process
changes,
substitutions
of
materials,
or
other
modifications;
(
2)
enclosing
systems
or
processes
to
eliminate
emissions;
(
3)
collecting,
capturing,
or
treating
such
pollutants
when
released
from
a
process,
stack,
storage
or
fugitive
emission
point;
(
4)
design,
equipment,
work
practices,
or
operational
standards
as
provided
in
subsection
112(
h);
or
(
5)
a
combination
of
the
above.

For
new
sources,
MACT
standards
cannot
be
less
stringent
than
the
emission
control
achieved
in
practice
by
the
best­
controlled
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
for
categories
and
subcategories
with
30
or
more
sources,
or
the
best­
performing
5
sources
for
categories
or
subcategories
with
fewer
than
30
sources.

In
essence,
these
MACT
standards
would
ensure
that
all
major
sources
of
air
toxic
emissions
achieve
the
level
of
control
already
being
achieved
by
the
better­
controlled
and
lower­
emitting
sources
in
each
category.
This
approach
provides
assurance
to
citizens
that
each
major
source
of
toxic
air
pollution
will
be
required
to
effectively
control
its
emissions.
A
major
source
of
HAP
emissions
is
any
stationary
source
or
group
of
stationary
sources
located
within
a
contiguous
area
and
under
common
control
that
emits
or
has
the
potential
to
emit
any
single
HAP
at
a
rate
of
9.07
Mg
(
10
tons)
or
more
per
year
or
any
combination
of
HAPs
at
a
rate
of
22.68
Mg
(
25
tons)
or
more
a
year.
At
the
same
time,
this
approach
provides
a
level
economic
playing
field,
ensuring
that
facilities
that
employ
cleaner
processes
and
good
emission
controls
are
not
disadvantaged
relative
to
competitors
with
poorer
controls.

1.2.1
Regulatory
Background
In
September
1996,
the
EPA
chartered
the
Industrial
Combustion
Coordinated
Rulemaking
(
ICCR)
advisory
committee
under
the
Federal
Advisory
Committee
Act
(
FACA).
The
committee's
objective
was
to
develop
recommendations
for
regulations
for
several
combustion
source
categories
under
sections
112
and
129
of
the
CAA.
The
ICCR
advisory
committee,
known
as
the
Coordinating
Committee,
formed
Source
Work
Groups
for
the
various
combustion
types
covered
under
the
ICCR.
One
of
the
work
groups
was
formed
to
research
issues
related
to
boilers.
Another
was
formed
to
research
issues
related
to
process
heaters.
The
Boiler
and
Process
Heater
Work
Groups
submitted
recommendations,
information,
and
data
analysis
results
to
the
Coordinating
Committee,
which
in
turn
considered
them
and
submitted
recommendations
and
information
to
EPA.
The
Committee's
recommendations
were
considered
by
EPA
in
developing
these
proposed
standards
for
boilers
and
process
heaters.
The
Committee's
2­
year
charter
expired
in
September
1998.

Following
the
expiration
of
the
ICCR
FACA
charter,
EPA
decided
to
combine
boilers
with
units
in
the
process
heater
source
category
covering
indirect
fired
units,
and
to
regulate
both
under
this
NESHAP.
This
was
done
because
indirect
fired
process
heaters
and
boilers
are
similar
devices,
burn
similar
fuel,
have
similar
emission
characteristics,
and
emissions
from
each
can
be
controlled
using
similar
control
devices
or
techniques.

1.2.2
Regulatory
Authority
Section
112
of
the
CAA
requires
that
EPA
promulgate
regulations
requiring
the
control
of
HAP
emissions
from
major
sources
and
certain
area
sources.
The
control
of
HAP
is
achieved
through
promulgation
of
emission
standards
under
sections
112(
d)
and
(
f)
and,
in
appropriate
circumstances,
work
practice
standards
under
section
112(
h)
of
the
CAA.

An
initial
list
of
categories
of
major
and
area
sources
of
HAP
selected
for
regulation
in
accordance
with
section
112(
c)
of
the
CAA
was
published
in
the
Federal
Register
on
July
16,
1992
(
57
FR
31576).
Industrial
boilers,
commercial
and
institutional
boilers,
and
process
heaters
are
three
of
the
1­
5
listed
174
categories
of
sources.
The
listing
was
based
on
the
Administrator's
determination
that
they
may
reasonably
be
anticipated
to
emit
several
of
the
188
listed
HAP
in
quantities
sufficient
to
designate
them
as
major
sources.

This
rule
affects
industrial
boilers,
institutional
and
commercial
boilers,
and
process
heaters.
In
this
rule
process
heaters
are
defined
as
units
in
which
the
combustion
gases
do
not
directly
come
into
contact
with
process
gases
in
the
combustion
chamber
(
e.
g.
indirect
fired).
Boiler
means
an
enclosed
device
using
controlled
flame
combustion
and
having
the
primary
purpose
of
recovering
thermal
energy
in
the
form
of
steam
or
hot
water.
A
waste
heat
boiler
(
or
heat
recovery
steam
generator)
is
a
device
that
recovers
normally
unused
energy
and
converts
it
to
usable
heat.
Waste
heat
boilers
are
excluded
from
this
rule.
A
hot
water
heater
is
a
closed
vessel
in
which
water
is
heated
by
combustion
of
gaseous
fuel
and
is
withdrawn
for
use
external
to
the
vessel
at
pressures
not
exceeding
160
psig.
Hot
water
heaters
are
excluded
from
this
rule.

Boilers
and
process
heaters
emit
particulate
matter,
volatile
organic
compounds,
and
hazardous
air
pollutants,
depending
on
the
material
burned.
Solid
and
liquid
fuel­
fired
units
emit
metals,
halogenated
compounds
and
organic
compounds.
Gas
fuel­
fired
units
emit
mostly
organic
compounds.

The
affected
source
is
each
individual
industrial,
commercial,
or
institutional
boiler
or
process
heater
located
at
a
major
facility.
The
affected
source
does
not
include
units
that
are
municipal
waste
combustors
(
40
CFR
part
60,
subparts
AAAA,
BBBB
or
Cb),
medical
waste
incinerators
(
40
CFR
part
60,
subpart
Ce
and
Ec),
fossil
fuel
fired
electric
utility
steam
generating
units,
commercial
and
industrial
solid
waste
incineration
units
(
40
CFR
part
60
subparts
CCCC
or
DDDD),
recovery
boilers
or
furnaces
(
40
CFR
part
63,
subpart
MM),
or
hazardous
waste
combustion
units
required
to
have
a
permit
under
section
3005
of
the
Solid
Waste
Disposal
Act
or
are
subject
to
40
CFR
part
63,
subpart
EEE.

The
rule
applies
to
an
owner
or
operate
a
boiler
or
process
heater
at
a
major
source
meeting
the
requirements
in
section
II.
C.
A
major
source
of
HAP
emissions
is
any
stationary
source
or
group
of
stationary
sources
located
within
a
contiguous
area
and
under
common
control
that
emits
or
has
the
potential
to
emit
any
single
HAP
at
a
rate
of
9.07
Mg
(
10
tons)
or
more
per
year
or
any
combination
of
HAP
at
a
rate
of
22.68
Mg
(
25
tons)
or
more
a
year.

An
affected
operator
must
meet
the
emission
limits
for
the
subcategories
in
Table
1­
1
of
this
preamble
for
each
of
the
pollutants
listed.
Emission
limits
were
developed
for
new
and
existing
sources;
and
for
large,
small,
and
limited
use
solid,
liquid,
and
gas
fuel
fired
units.
Large
units
are
those
with
heat
input
capacities
greater
than
10
MMBtu/
hr.
Small
units
are
those
with
heat
input
capacities
less
than
or
equal
to
10
MMBtu/
hr.
Limited
use
units
are
those
with
capacity
utilizations
less
than
or
equal
to
10
percent
as
required
in
a
federally
enforceable
permit.

If
your
new
or
existing
boiler
or
process
heater
is
permitted
to
burn
a
solid
fuel,
or
any
combination
of
solid
fuel
with
liquid
or
gaseous
fuel,
the
unit
is
in
one
of
the
solid
subcategories.
If
your
new
or
reconstructed
boiler
or
process
heater
burns
a
liquid
fuel,
or
a
liquid
fuel
in
combination
with
a
gaseous
fuel,
the
unit
is
in
one
of
the
liquid
subcategories.
If
your
new
or
existing
boiler
or
process
heater
burns
a
gaseous
fuel
only,
the
unit
is
in
the
gas
subcategory
and
is
not
required
to
meet
any
emission
limit.

Table
1­
1.
EMISSION
LIMITS
FOR
BOILERS
AND
PROCESS
HEATERS
(
lb/
MMBtu)
1­
6
Source
Subcategory
PM
or
Total
Selected
Metals
HCl
Mercury
(
Hg)
Carbon
Monoxide
(
CO
­
ppm
@
3%
oxygen)

New
Boiler
or
Process
Heater
Solid
Fuel,
Large
Unit
0.04
or
0.00007
0.016
0.0000026
200
Solid
Fuel,
Small
Unit
0.04
or
0.00007
0.032
0.0000026
­­

Solid
Fuel,
Limited
Use
0.04
or
0.00007
0.032
0.0000026
200
Liquid
Fuel,

Large
Unit
0.068
­­
0.00045
200
Liquid
Fuel,
Small
Unit
0.068
­­
0.0009
­­
­­

Liquid
Fuel,
Limited
Use
0.068
­­
0.0009
­­
200
Gaseous
Fuel,
Large
Unit
­­
­­
­­
­­
200
Gaseous
Fuel,
Small
Unit
­­
­­
­­
­­

Gaseous
Fuel,
Limited
Use
­­
­­
­­
­­
200
Existing
Boiler
or
Process
Heater
Solid
Fuel,
Large
Unit
0.062
or
0.001
0.048
0.000004
­­

Solid
Fuel,
Small
Unit
­­
­­
­­
­­
­­

Solid
Fuel,
Limited
Use
0.21
or
0.001
­­
­­
­­

Liquid
Fuel,

Large
Unit
­­
­­
­­
­­
­­

Liquid
Fuel,
Small
Unit
­­
­­
­­
­­
­­

Liquid
Fuel,
Limited
Use
­­
­­
­­
­­
­­

Gaseous
Fuel
­­
­­
­­
­­
­­

For
solid
fuel­
fired
boilers
or
process
heaters,
we
are
allowing
sources
to
choose
one
of
two
emission
limit
options:
(
1)
existing
and
new
affected
sources
may
choose
to
limit
PM
emissions
to
the
1­
7
level
listed
in
Table
1
of
this
preamble
or
(
2)
existing
and
new
affected
sources
may
choose
to
limit
total
selected
metals
emissions
to
the
level
listed
in
Table
1
of
the
preamble.

If
you
do
not
use
an
add­
on
control
or
use
an
add­
on
control
other
than
a
wet
scrubber,
you
must
maintain
opacity
level
to
less
than
or
equal
to
the
level
established
during
the
compliance
test
for
mercury
and
PM
or
total
selected
metals,
and
maintain
the
fuel
chlorine
content
to
less
than
or
equal
to
the
operating
level
established
during
the
HCl
compliance
test.

If
you
use
a
wet
scrubber,
you
must
maintain
the
minimum
pH,
pressure
drop
and
liquid
flowrate
above
the
operating
levels
established
during
the
performance
tests.

If
you
use
a
dry
scrubber,
you
must
maintain
opacity
level
and
the
minimum
sorbent
injection
rate
established
during
the
performance
test.

If
you
use
an
ESP
in
combination
with
a
wet
scrubber
and
cannot
monitor
the
opacity,
you
must
maintain
the
average
secondary
current
and
voltage
or
total
power
input
established
during
the
performance
test.

There
is
an
alternative
compliance
procedure
and
operating
limit
for
meeting
the
total
selected
metals
emission
limit
option.
If
you
have
no
control
or
do
not
want
to
take
credit
of
metals
reductions
with
your
existing
control
device,
and
can
show
that
total
metals
in
the
fuel
would
be
less
than
the
metals
emission
level,
then
you
can
monitor
the
metals
fuel
analysis
to
meet
the
metals
emissions
limitations.
Similarly,
if
you
have
no
control
or
do
not
want
to
take
credit
of
mercury
reduction
with
your
existing
control
device,
and
can
show
that
mercury
in
the
fuel
would
be
less
than
the
mercury
emission
level,
then
you
can
monitor
the
mercury
fuel
analysis
to
meet
the
mercury
emission
limitations.

1.2.3
Regulatory
Alternatives
and
Control
Technologies
1.2.3.1
MACT
Floor
Development
We
considered
several
approaches
to
identifying
MACT
floor
for
existing
industrial,
commercial,
and
institutional
boilers
and
process
heaters.
First,
we
considered
using
emissions
data
on
boilers
and
process
heaters
to
set
the
MACT
floor.
However,
after
review
of
the
data
available,
we
determined
that
emissions
information
was
inadequate
to
set
MACT
floors.
We
then
considered
using
State
regulations
and
permits
to
set
the
MACT
floors.
However,
we
found
no
State
regulations
or
State
permits
which
specifically
limit
HAP
emissions
from
these
sources.

Consequently,
we
concluded
that
the
only
reasonable
approach
for
determining
MACT
floors
is
to
base
it
on
control
technology.
Information
was
available
on
the
control
technologies
employed
by
the
population
of
boilers
identified
by
the
EPA.
We
considered
several
possible
control
technologies
(
i.
e.,
factors
that
influence
emissions),
including
fuel
substitution,
process
changes
and
work
practices,
and
add­
on
control
technologies.

We
first
considered
whether
fuel
switching
would
be
an
appropriate
control
option
for
sources
in
each
subcategory.
Both
fuel
switching
to
other
fuels
used
in
the
subcategory
and
fuels
from
other
subcategories
were
considered.
This
consideration
included
determining
whether
switching
fuels
would
achieve
lower
HAP
emissions.
A
second
consideration
was
whether
fuel
switching
could
be
technically
done
on
boilers
and
process
heaters
in
the
subcategory
considering
the
existing
design
of
boilers
and
process
heaters.
We
also
considered
the
availability
of
the
alternative
fuel.

After
considering
these
factors,
we
determined
that
fuel
switching
was
not
an
appropriate
control
technology
to
be
included
in
determining
the
MACT
floor
level
of
control
for
any
subcategory.
This
decision
was
based
on
the
overall
effect
of
fuel
switching
on
HAP
emissions,
technical
and
design
considerations
discussed
in
section
III.
A
of
this
preamble,
and
concerns
about
fuel
availability.

Based
on
the
data
available
in
the
emissions
database,
we
determined
that
while
fuel
switching
from
solid
fuels
to
gaseous
or
liquid
fuels
would
decrease
PM
and
some
metals
emissions,
emissions
of
some
organic
HAP
would
also
increase,
resulting
in
uncertain
benefits.
We
determined
that
it
would
be
inappropriate
in
a
MACT
rulemaking,
that
is
technology
based,
to
consider
a
technology
that
potentially
1­
8
will
result
in
an
increase
in
a
HAP
regardless
of
its
potential
to
reduce
other
HAP
without
determining
the
overall
benefit.
Determining
the
benefits
of
fuel
switching
would
require
an
assessment
of
the
risk
associated
which
each
HAP
emitted
and
a
determination
of
which
fuel
results
in
the
overall
lower
risk
taking
into
account
the
available
control
technology
for
each
fuel.
This
assessment
will
be
performed
in
a
future
rulemaking.

A
similar
determination
was
made
when
considering
fuel
switching
to
"
cleaner"
fuels
within
a
subcategory.
For
example,
the
term
"
clean
coal"
refers
to
coal
that
is
lower
in
sulfur
content
and
not
necessarily
lower
in
HAP
content.
Data
gathered
by
EPA
also
indicates
that
within
specific
coal
types
HAP
content
can
vary
significantly.
Switching
to
a
"
clean
coal"
may
increase
emissions
of
some
HAP.
Therefore,
fuel
switching
to
a
"
cleaner"
coal
would
not
be
an
appropriate
option.
Fuel
switching
from
coal
to
biomass
would
result
in
similar
impacts
on
HAP
emissions.
While
metallic
HAP
emissions
would
be
reduced,
emissions
of
organics
would
increase
based
on
information
in
the
emissions
database.

Another
factor
considered
was
the
availability
of
alternative
fuels.
Natural
gas
pipelines
are
not
available
in
all
regions
of
the
U.
S.,
and
natural
gas
is
simply
not
available
as
a
fuel
for
many
industrial,
commercial,
and
institutional
boilers
and
process
heaters.
Moreover,
even
where
pipelines
provide
access
to
natural
gas,
supplies
of
natural
gas
may
not
be
adequate.
For
example,
it
is
common
practice
in
cities
during
winter
months
(
or
periods
of
peak
demand)
to
prioritize
natural
gas
usage
for
residential
areas
before
industrial
usage.
Requiring
EPA
regulated
combustion
units
to
switch
to
natural
gas
would
place
an
even
greater
strain
on
natural
gas
resources.
Consequently,
even
where
pipelines
exist
some
units
would
not
be
able
to
run
at
normal
of
full
capacity
during
these
times
if
shortages
were
to
occur.
Therefore,
under
any
circumstances,
there
would
be
some
units
that
could
not
comply
with
a
requirement
to
switch
to
natural
gas.

Similar
problems
for
fuel
switching
to
biomass
could
arise.
Existing
sources
burning
biomass
generally
are
combusting
a
recovered
material
from
the
manufacturing
or
agriculture
process.
Industrial,
commercial,
and
institutional
facilities
that
are
not
associated
with
the
wood
products
industry
or
agriculture
may
not
have
access
to
a
sufficient
supply
of
biomass
materials
to
replace
their
fossil
fuel.

There
are
many
concerns
with
switching
fuels
on
sources
designed
and
operated
to
burn
specific
fuels.
Changes
to
the
fuel
type
(
solid,
liquid,
or
gas)
will
require
extensive
changes
to
the
fuel
handling
and
feeding
system
(
e.
g.,
a
stoker
using
wood
as
fuel
would
need
to
be
redesigned
to
handle
fuel
oil
or
gaseous
fuel).
Additionally,
burners
and
combustion
chamber
designs
are
generally
not
capable
of
handling
different
fuel
types,
and
generally
cannot
accommodate
increases
or
decreases
in
the
fuel
volume
and
shape.
Design
changes
to
allow
different
fuel
use,
in
some
cases,
may
reduce
the
capacity
and
efficiency
of
the
boiler
or
process
heater.
Reduced
efficiency
may
result
in
a
greater
degree
of
incomplete
combustion
and,
thus,
an
increase
in
organic
HAP
emissions.
For
the
reasons
discussed
above,
we
decided
that
fuel
switching
to
"
cleaner"
solid
fuels
or
to
liquid
or
gaseous
fuels
would
not
be
appropriate
or
available
as
a
MACT
floor
level.

We
also
determined
that
using
process
changes
or
work
practices
were
not
appropriate
in
developing
MACT
floors.
HAP
emissions
from
boilers
and
process
heaters
are
primarily
dependent
upon
the
composition
of
the
fuel.
Fuel
dependent
HAP
are
metals,
including
mercury,
and
acid
gases.
Fuel
dependent
HAP
are
typically
controlled
by
removing
them
from
the
flue
gas
after
combustion.
Therefore,
they
are
not
affected
by
the
operation
of
the
boiler
or
process
heater.
Consequently,
process
changes
would
be
ineffective
in
reducing
these
fuel­
related
HAP
emissions.

On
the
other
hand,
organic
HAP
can
be
formed
from
incomplete
combustion
of
the
fuel.
Data
are
not
available
that
definitively
show
that
organic
HAP
emissions
are
related
to
the
operation
of
the
boiler
or
process
heater.
Some
studies
indicate
that
organic
HAP
are
greatly
influence
by
time,
turbulence
and
temperature.
Other
studies
indicate
that
organic
HAP
emissions
are
not
affected
by
the
operation
of
the
unit.
The
measurement
of
CO
is
generally
an
indicator
of
incomplete
combustion
since
CO
will
burn
to
carbon
dioxide
if
adequate
oxygen
is
available.
Correcting
incomplete
combustion
may
be
accomplished
through
providing
more
combustion
air.
Therefore,
we
consider
monitoring
and
maintaining
CO
emission
levels
to
be
associated
with
minimizing
organic
HAP
emission
levels
and,
thus,
CO
monitoring
would
be
a
good
indicator
of
combustion
efficiency
and
organic
HAP
emissions.
1­
9
In
summary,
we
determined
that
considering
process
changes
and
work
practices
would
not
be
appropriate
in
developing
MACT
floors
for
existing
units.
We
are
requesting
comment,
and
information
on
emission
reductions,
on
whether
there
are
other
GCP
practices
that
would
be
appropriate
for
minimizing
organic
HAP
emissions
from
industrial,
commercial,
and
institutional
boilers
and
process
heaters.

Consequently,
we
concluded
that
add­
on
control
technology
is
the
only
factor
that
significantly
controls
HAP
emissions.

In
order
to
determine
the
MACT
floor
based
on
add­
on
control
technologies,
we
first
examined
the
population
database
of
existing
sources.
Units
not
meeting
the
definition
of
an
industrial,
commercial,
or
institutional
boiler
or
process
heater,
and
units
located
at
area
sources
were
removed
from
the
database.
The
remaining
units
were
divided
first
into
three
subcategories
based
on
fuel
state:
gaseous
fuel­
fired,
liquid
fuel­
fired,
and
solid
fuel­
fired
units.
Each
of
these
three
subcategories
was
then
further
divided
into
subcategories
based
on
capacity:
(
1)
large
boilers
and
process
heaters
(
units
with
heat
inputs
greater
than
10
MMBtu/
hr);
(
2)
small
units
(
with
a
maximum
rated
heat
input
capacity
of
10
MMBtu/
hr
or
less);
and
(
3)
limited
use
units
with
capacity
utilization
less
than
10
percent.

We
identified
the
types
of
air
pollution
control
techniques
currently
used
by
existing
boilers
and
process
heaters
in
each
subcategory.
We
ranked
those
controls
according
to
their
effectiveness
in
removing
the
different
categories
of
pollutants;
including
metallic
HAP
and
PM,
inorganic
HAP
such
as
acid
gases,
mercury,
and
organic
HAP.
The
EPA
ranked
these
existing
control
technologies
by
incorporating
recommendations
made
by
the
ICCR,
and
by
reviewing
emissions
test
data,
previous
EPA
studies,
and
other
literature,
as
well
as
by
using
engineering
judgement.

Based
upon
the
emissions
reduction
potential
of
existing
air
pollution
control
techniques,
we
listed
all
the
boilers
and
process
heaters
in
the
population
database
in
order
of
decreasing
control
device
effectiveness
for
each
subcategory.
Then
the
technology
basis
of
the
existing
source
MACT
floor
was
determined
for
each
pollutant
category
by
identifying
the
best­
performing
12
percent
of
units.
We
then
selected
the
technology
used
by
the
median
unit
in
the
best
performing
12
percent
of
units
(
i.
e.,
the
boiler
or
process
heater
unit
representing
the
94th
percentile)
as
the
technology
associated
with
the
MACT
floor
level
of
control
for
each
subcategory.
As
previously
described,
emissions
data
for
this
category
is
insufficient
to
identify
the
best­
performing
units.
The
most
appropriate
way
to
identify
the
average
emission
limitation
achieved
by
the
best­
performing
12
percent
of
existing
sources
is
to
identify
the
technology
used
by
the
unit
in
the
middle
of
the
range
of
the
best
performing
12
percent
of
units,
i.
e.,
the
median
unit).

After
establishing
the
technology
basis
for
the
existing
source
MACT
floor
for
each
subcategory
and
each
type
of
pollutant,
the
EPA
examined
the
emissions
data
available
for
boilers
and
process
heaters
controlled
by
these
technologies
to
determine
achievable
emission
levels.
The
resulting
emission
levels
associated
with
the
existing
source
MACT
floors
for
each
pollutant
are
based
on
the
average
of
the
lowest
three
run
average
test
data
from
units
using
the
technology
associated
with
the
MACT
floor
level
of
control,
and
by
incorporating
operational
variability
using
results
from
multiple
tests
on
these
best
performing
units.
This
approach
reasonably
ensures
that
the
emission
limit
selected
as
the
MACT
floor
represents
a
level
of
control
that
can
be
consistently
achieved
by
a
unit
in
the
subcategory
using
the
control
technology
associated
with
the
MACT
floor.
This
approach
is
reasonable
because
the
most
informative
way
to
predict
the
worst
reasonably
foreseeable
performance
of
the
bestcontrolled
units,
with
available
data,
is
to
examine
the
available
long­
term
performance
of
the
best
performing
units
that
had
multiple
test
results.
In
other
words,
the
EPA
considers
all
units
with
the
same
control
technology
that
is
properly
designed
and
operated
to
be
equally
well
controlled,
even
if
the
emission
test
results
from
such
units
vary
considerably.

The
level
of
control
"
achieved"
by
the
average
of
the
top
performing
12
percent
of
units
is
best
represented
by
the
average
emissions
observed
from
all
units
using
the
same
technology
as
that
employed
by
the
unit
representing
the
median
of
the
top
12
percent.

The
EPA's
review
of
emissions
data
indicates
that
some
boilers
and
process
heaters
within
each
subcategory
may
be
able
to
meet
the
floor
emission
levels
without
using
the
air
pollution
control
technology
that
is
associated
with
the
MACT
floor.
This
is
to
be
expected,
given
the
variety
of
fuel
types,
fuel
input
rates,
and
boiler
designs
included
within
each
subcategory
and
the
resulting
variability
1­
10
in
emission
rates.
Thus,
for
instance,
boilers
or
process
heaters
within
the
large
unit
solid
fuel
subcategory
that
burn
lower
percentages
of
solid
fuels
may
be
able
to
achieve
the
emission
levels
for
the
large
unit
solid
fuel
subcategory
without
the
need
for
additional
control
devices.

Furthermore,
solid
fuels,
especially
coal,
are
very
heterogeneous
and
can
vary
in
composition
by
location.
Coal
analysis
data
obtained
from
the
electric
utility
industry
in
another
rulemaking
contained
information
on
the
mercury,
chlorine,
and
ash
content
of
various
coals.
A
preliminary
review
of
this
data
indicate
that
the
composition
can
vary
greatly
from
location
to
location,
and
also
within
location.
Based
on
the
range
of
variation
of
mercury,
chlorine,
and
ash
content
in
coal,
it
is
possible
for
a
unit
with
a
lower
performing
control
system
to
have
emission
levels
lower
than
a
unit
considered
to
be
included
in
the
best
performing
12
percent
of
the
units.

This
situation
is
reflected
in
the
emissions
information
used
to
set
the
MACT
floor
emission
limits.
In
some
instances
there
are
boilers
with
ESP's
or
other
controls
that
achieve
similar,
or
lower,
outlet
emission
levels
of
non­
mercury
metallic
HAP,
PM,
or
mercury
to
fabric
filters.
In
most
cases,
this
is
due
to
concentrations
entering
these
other
control
devices
being
lower,
even
though
the
percent
reduction
achieved
is
lower
than
fabric
filters.

Additionally,
the
design
of
some
control
devices
may
have
a
substantial
effect
on
the
their
emission
reduction
capability.
For
example,
fabric
filters
are
largely
insensitive
to
the
physical
characteristics
of
the
inlet
gas
stream.
Thus,
their
design
does
not
vary
widely,
and
emissions
reductions
are
expected
to
be
similar
(
e.
g.
99
percent
reduction
of
PM).
However,
ESP
design
can
vary
significantly.

Consequently,
since
fuel
substitution
has
been
determined
not
to
be
an
appropriate
MACT
floor
control
technology,
EPA
still
considers
the
fabric
filter
to
be
the
best­
performing
control
for
nonmercury
metallic
HAPs,
PM,
and
mercury
and
only
emissions
information
for
fabric
filters
was
used
to
develop
emission
limits.
A
detailed
discussion
of
the
MACT
floor
methodology
is
presented
in
the
memorandum
"
MACT
Floor
Analysis
for
New
and
Existing
Sources
in
the
Industrial,
Commercial,
and
Institutional
Boilers
and
Process
Heaters
Source
Categories"
in
the
docket.

Existing
Solid
Fuel
Boilers
and
Process
Heaters
Large
Units
­
Heat
Inputs
Greater
than
10
MMBtu/
hr.

The
most
effective
control
technologies
identified
for
removing
non­
mercury
metallic
HAP
and
PM
are
fabric
filters.
About
14
percent
of
solid
fuel­
fired
boilers
and
process
heater
use
fabric
filters.
Because
this
is
the
technology
used
by
the
94th
percentile
(
the
median
of
the
best­
performing
12
percent),
the
EPA
considers
a
fabric
filter
to
be
the
technology
basis
for
the
MACT
floor
for
nonmercury
metallic
HAP
control
for
existing
boilers
and
process
heaters
in
this
subcategory.

The
most
effective
control
technologies
identified
for
removing
inorganic
HAP
that
are
acid
gases,
such
as
hydrogen
chloride,
are
wet
scrubbers
and
packed
bed
scrubbers.
These
technologies
are
used
by
about
12
percent
of
the
boilers
and
process
heaters
in
the
solid
fuel
subcategory.
About
10
percent
of
solid­
fired
boilers
and
process
heaters
use
wet
scrubbers,
and
approximately
1
percent
use
packed
bed
scrubbers.
Because
wet
scrubbers
are
the
technology
used
by
the
94th
percentile
(
median
of
the
best­
performing
12
percent),
the
EPA
considers
a
wet
scrubber
to
be
the
technology
basis
for
the
MACT
floor
for
acid
gas
control
for
existing
boilers
and
process
heaters
in
the
solid
fuel
subcategory.
The
MACT
floor
emission
level
based
on
wet
scrubbers
and
incorporating
operational
variability
is
0.048
lb
HCl/
MMBtu.

Based
on
test
information
on
utility
boilers,
we
have
concluded
that
fabric
filters
are
most
effective
in
controlling
mercury,
and
units
having
them
would
constitute
the
best
controlled
mercury
sources.
As
discussed
previously,
more
than
6
percent
of
sources
in
the
subcategory
have
fabric
filters.
The
MACT
floor
emission
level
based
on
fabric
filters
and
incorporating
operational
variability
is
0.000004
lb
mercury/
MMBtu.

For
organic
HAP,
we
assessed
whether
maintaining
and
monitoring
CO
levels
would
be
part
of
the
MACT
floor,
and
determined
that
less
than
6
percent
of
the
units
in
this
subcategory
do
so.
Therefore,
we
concluded
the
MACT
floor
for
existing
sources
in
this
subcategory
is
no
emissions
reductions
for
organic
HAP.
1­
11
Therefore,
the
EPA
determined
that
the
combination
of
fabric
filter
and
wet
scrubber
control
technologies
forms
the
basis
for
the
MACT
floor
level
of
control
for
existing
solid
fuel
boilers
or
process
heaters
in
this
subcategory.
We
recognize
that
some
boilers
and
process
heaters
that
use
technologies
other
than
those
used
as
the
basis
of
the
MACT
floor
can
achieve
the
MACT
floor
emission
levels.
For
example,
emission
test
data
show
that
many
boilers
with
well­
designed
and
operated
ESP
can
meet
the
MACT
floor
emission
levels
for
non­
mercury
metallic
HAP
and
PM,
even
though
the
floor
emission
level
for
these
pollutants
is
based
on
a
fabric
filter
(
however,
we
would
not
expect
that
all
units
using
ESP
would
be
able
to
meet
the
rule).

Small
Units
­
Heat
Inputs
Less
than
or
Equal
to
10
MMBtu/
hr.

Less
than
6
percent
of
the
units
in
this
subcategory
used
control
techniques
that
would
reduce
non­
mercury
metallic
HAP
and
PM,
mercury,
and
inorganic
HAP,
such
as
HCl.
Also,
maintaining
and
monitoring
CO
levels
was
used
by
less
than
6
percent
of
the
units
in
the
subcategory.

Therefore,
we
determined
that
the
MACT
floor
emission
level
for
existing
units
for
any
of
the
pollutant
categories
in
this
subcategory
is
no
emissions
reductions.

Limited
Use
Units
­
Capacity
Utilizations
Less
than
or
Equal
to
10
Percent.

The
most
effective
control
technologies
identified
for
removing
non­
mercury
metallic
HAP
and
PM
are
ESP
and
fabric
filters.
Less
than
2
percent
of
solid
fuel­
fired
boilers
and
process
heater
in
this
subcategory
use
fabric
filters,
and
14
percent
use
ESP.
Because
ESP
are
the
technology
used
by
the
94th
percentile
(
the
median
of
the
best­
performing
12
percent),
the
EPA
considers
an
ESP
to
be
the
technology
basis
for
the
MACT
floor
for
non­
mercury
metallic
HAP
control
for
existing
boilers
and
process
heaters
in
the
solid
fuel
subcategory.
A
PM
level
is
set
as
a
surrogate
for
non­
mercury
metallic
HAP
control.
The
MACT
floor
emission
level
based
on
ESPs,
considering
operational
variability,
is
0.021
lb
PM/
MMBtu.
We
are
also
providing
an
alternative
metals
limit
of
0.001
lb
metals/
MMBtu
which
can
be
used
to
show
compliance
in
cases
where
metal
HAP
emissions
are
low
in
proportion
to
PM
emissions.

Similar
control
technology
analyses
were
done
for
the
boilers
and
process
heaters
in
this
subcategory
for
the
other
pollutant
groups
of
interest,
including
inorganic
HAP,
organic
HAP
and
mercury.
Less
than
6
percent
of
the
units
in
this
subcategory
have
controls
that
would
reduce
emissions
of
organic
HAP,
mercury,
and
inorganic
HAP,
so
the
existing
source
MACT
floor
for
those
pollutants
is
no
emissions
reductions.
Therefore,
we
determined
that
ESP
control
technology,
which
achieves
nonmercury
metallic
HAP
and
PM
control
forms
the
basis
for
the
MACT
floor
level
of
control
for
existing
solid
fuel
boilers
and
process
heaters
in
this
subcategory.

Existing
Liquid
Fuel
Boilers
and
Process
Heaters
Emissions
data
for
liquid
subcategories
was
inadequate
to
identify
the
best­
performing
sources
for
reasons
described
in
section
D
of
the
preamble.
We
also
found
no
State
regulations
or
permits
which
specifically
limit
HAP
emissions
from
these
sources.
Therefore,
we
examined
control
technology
data
to
identify
a
MACT
floor.
We
found
that
less
than
6
percent
of
the
units
in
each
of
the
liquid
subcategories
used
control
techniques
that
would
reduce
non­
mercury
metallic
HAP
and
PM,
mercury,
organic
HAP,
or
inorganic
HAP
(
such
as
HCl).
Therefore,
we
determined
that
the
control
technique
associated
with
the
94th
percentile
(
the
median
of
the
best­
performing
12
percent)
could
not
be
identified.

Therefore,
we
are
unable
to
identify
the
best
performing
12
percent
of
units
in
the
subcategories.
In
light
of
this
analysis,
we
concluded
the
MACT
floor
for
existing
sources
in
these
liquid
subcategory
is
no
emissions
reductions
for
non­
mercury
metallic
HAP,
mercury,
inorganic
HAP,
and
organic
HAP.

Existing
Gaseous
Fuel
Boilers
and
Process
Heaters
Emissions
data
for
gas
subcategories
was
inadequate
to
identify
the
best­
performing
sources
for
reasons
described
in
section
D
of
the
preamble.
We
also
found
no
State
regulations
or
permits
which
specifically
limit
HAP
emissions
from
these
sources.
Therefore,
we
examined
control
technology
data
1­
12
to
identify
a
MACT
floor.
We
found
that
no
existing
units
in
the
gaseous
fuel­
fired
subcategories
were
using
control
technologies
that
achieve
consistently
lower
emission
rates
than
uncontrolled
sources
for
any
of
the
pollutant
groups
of
interest.
Therefore,
we
are
unable
to
identify
the
best
performing
12
percent
of
units
in
the
subcategories.
Consequently,
the
EPA
determined
that
no
existing
source
MACT
floor
based
on
control
technologies
could
be
identified
for
gaseous
fuel­
fired
units.
Therefore,
we
concluded
the
MACT
floor
for
existing
sources
in
this
subcategory
is
no
emissions
reductions
for
nonmercury
metallic
HAP,
mercury,
inorganic
HAP,
and
organic
HAP.

1.2.3.2
Consideration
of
Options
Beyond
the
Floor
for
Existing
Units
Once
the
MACT
floor
determinations
were
done
for
each
subcategory,
the
EPA
considered
various
regulatory
options
more
stringent
than
the
MACT
floor
level
of
control
(
i.
e.,
technologies
or
other
work
practices
that
could
result
in
lower
emissions)
for
the
different
subcategories.

Maintaining
and
monitoring
CO
levels
was
identified
as
a
possible
control
for
organic
HAPs.
However,
less
than
6
percent
of
the
sources
in
the
existing
source
subcategories
used
this
control
method
and
it
was
not
considered
the
MACT
floor
control
technology.
We
then
looked
at
it
as
an
above­
thefloor
option.
However,
information
was
not
available
to
estimate
the
HAP
emissions
reductions
that
would
be
associated
with
CO
monitoring
and
emission
limits.
This
option
would
also
require
a
high
cost
to
install
and
operate
CO
monitors.
Given
the
cost
and
the
uncertain
emissions
reductions
that
might
be
achieved,
we
chose
to
not
require
CO
monitoring
and
emission
limits
as
MACT.

The
following
sections
discuss
the
above­
the­
floor
options
analyzed
to
control
emissions
of
metallic
HAP,
mercury,
and
inorganic
HAP.
Based
on
the
analysis
described
in
these
sections,
the
EPA
decided
to
not
go
beyond
the
MACT
floor
level
of
control
for
the
rule
for
any
of
the
subcategories
of
existing
sources.

Existing
Solid
Fuel
Units
Large
Units
­
Heat
Inputs
Greater
than
10
MMBtu/
hr.
Besides
fuel
switching
(
see
section
III.
D
of
this
preamble),
we
identified
a
better
designed
and
operated
fabric
filter
(
the
MACT
floor
for
new
units)
as
a
control
technology
that
could
achieve
greater
emissions
reductions
of
metallic
HAP
and
PM
emissions
than
the
MACT
floor
level
of
control
(
i.
e.,
a
typical
existing
fabric
filter).
Consequently,
the
EPA
analyzed
the
emissions
reductions
and
additional
cost
of
adopting
an
emission
limit
representative
of
the
performance
of
a
unit
with
a
better
designed
and
operated
fabric
filter.
The
additional
annualized
cost
to
comply
with
this
emission
limit
was
estimated
to
be
approximately
500
million
dollars
with
an
additional
emission
reduction
of
approximately
100
tons
of
metallic
HAP.
The
results
indicated
that
while
additional
emissions
reductions
would
be
realized,
the
costs
would
be
too
high
to
consider
it
a
feasible
above
the
floor
option.
Non­
air
quality
health,
environmental
impacts,
and
energy
effects
were
not
significant
factors,
because
there
would
be
little
difference
in
the
non­
air
quality
health
and
environmental
impacts
of
replacing
existing
fabric
filters
with
improved
performance
fabric
filters.
Therefore,
we
did
not
select
these
controls
as
MACT.
Fuel
switching
was
not
considered
a
feasible
beyond­
the­
floor
option
for
the
same
reasons
described
in
section
III.
E
of
the
proposal
preamble.

We
identified
packed
bed
scrubbers
as
a
control
technology
that
could
achieve
greater
emissions
reductions
of
inorganic
HAP,
like
HCl,
than
the
MACT
floor
level
of
control
(
i.
e.,
a
wet
scrubber).
Consequently,
the
EPA
analyzed
the
emissions
reductions
and
additional
cost
of
adopting
an
emission
limit
representative
of
the
performance
of
a
unit
with
a
packed
bed
scrubber.
The
additional
annualized
cost
to
comply
with
this
emission
limit
(
using
a
packed
bed
scrubber)
was
estimated
to
be
approximately
900
million
dollars
with
an
additional
emission
reduction
of
approximately
20,000
tons
of
HCl.
The
results
indicated
that
while
additional
emissions
reductions
would
be
realized,
the
costs
would
be
too
high
to
consider
it
a
feasible
above
the
floor
option.
Non­
air
quality
health,
environmental
impacts,
and
energy
effects
were
not
significant
factors,
because
there
would
be
little
difference
in
the
non­
air
quality
health
and
environmental
impacts
between
packed
bed
scrubbers
and
wet
scrubbers.
Therefore,
we
did
not
select
these
controls
as
MACT.
1­
13
In
reviewing
potential
regulatory
options
for
existing
sources,
the
EPA
identified
one
existing
industrial
boiler
that
was
using
a
technology,
carbon
injection,
used
in
other
industries
to
achieve
greater
control
of
mercury
emissions
than
the
MACT
floor
level
of
control.
However,
emission
data
indicated
that
this
unit
was
not
achieving
mercury
emission
reductions.
The
EPA
does
not
have
information
that
would
show
carbon
injection
is
effective
for
reducing
mercury
emissions
from
industrial,
commercial,
and
institutional
boilers
and
process
heaters.
Therefore,
carbon
injection
was
not
evaluated
as
a
regulatory
option.

However,
the
EPA
requests
comments
on
whether
carbon
injection
should
be
considered
as
a
beyond­
the­
floor
option
and
whether
existing
industrial,
commercial,
or
institutional
boilers
and
process
heaters
could
use
carbon
injection
technology,
or
other
control
techniques
to
consistently
achieve
mercury
emission
levels
that
are
lower
than
levels
from
similar
sources
with
the
MACT
floor
level
of
control.
The
EPA
is
aware
that
research
continues
on
ways
to
improve
mercury
capture
by
PM
controls,
sorbent
injection,
and
the
development
of
novel
techniques.
The
EPA
requests
comment
and
information
on
the
effectiveness
of
such
control
technologies
in
reducing
mercury
emissions.

Small
Units
­
Heat
Inputs
Less
than
or
Equal
to
10
MMBtu/
hr.

The
EPA
could
not
identify
a
technology­
based
level
of
control
for
the
MACT
floor
for
this
subcategory.
To
control
non­
mercury
metallic
HAP
and
mercury,
we
analyzed
the
above
the
floor
option
of
a
fabric
filter
which
was
identified
as
the
most
effective
control
device
for
non­
mercury
metallic
HAP
and
mercury.
To
control
inorganic
HAP
such
as
hydrogen
chloride,
we
analyzed
the
above
the
floor
option
of
a
wet
scrubber
since
it
was
identified
as
the
least
cost
option.

The
total
annualized
cost
of
complying
with
the
fabric
filter
option
was
estimated
to
be
$
10
million,
with
an
estimated
emission
reduction
of
1.9
tons
per
year
of
non­
mercury
metallic
HAP
and
0.003
tons
of
mercury.
The
annualized
cost
of
complying
with
the
wet
scrubber
option
was
estimated
to
be
$
11
million,
with
an
emission
reduction
of
48
per
year
of
HCl.
The
results
of
this
analysis
indicated
that
while
additional
emissions
reductions
could
be
realized,
the
costs
would
be
too
high
to
consider
them
feasible
options.
Therefore,
we
did
not
select
these
controls
as
MACT.
Non­
air
quality
health,
environmental
impacts,
and
energy
effects
were
not
significant
factors.

Limited
Use
Units
­
Capacity
Utilizations
Less
than
or
Equal
to
10
Percent.
The
MACT
floor
level
of
control
for
this
subcategory
for
non­
mercury
metallic
HAP
control
is
an
ESP.
Although
fabric
filters
were
identified
as
being
more
effective,
many
ESP
can
achieve
similar
levels.
Any
additional
emission
reduction
from
using
a
fabric
filter
would
be
minimal
and
costly
considering
retrofit
costs
for
existing
units
that
already
have
ESP.
Therefore,
an
above­
the­
floor
option
for
metallic
HAP
was
not
analyzed
in
detail,
and
we
did
not
select
fabric
filters
as
MACT.
However,
an
above
the
floor
option
of
a
fabric
filter
was
analyzed
for
mercury
control.
The
total
annualized
costs
of
the
fabric
filter
option
was
estimated
to
be
an
additional
$
21
million,
with
an
estimated
emission
reduction
of
0.04
tons
of
mercury.

The
EPA
could
not
identify
a
technology­
based
level
of
control
for
the
MACT
floor
for
inorganic
HAP
in
this
subcategory.
To
control
inorganic
HAP,
we
analyzed
the
above­
the­
floor
option
of
a
wet
scrubber
since
it
was
identified
as
the
least
cost
option.
The
total
annualized
costs
of
the
wet
scrubber
option
was
estimated
to
be
$
49
million,
with
an
estimated
emission
reduction
of
463
tons
per
year
of
HCl.

The
results
of
the
above
the
floor
options
analyses
indicated
that
while
additional
emissions
reductions
could
be
realized,
the
costs
would
be
too
high
to
consider
them
feasible
options.
Therefore,
we
did
not
select
these
controls
as
MACT.
Non­
air
quality
health,
environmental
impacts,
and
energy
effects
were
not
significant
factors.

Existing
Liquid
Fuel
Units
For
the
liquid
fuel
subcategories,
the
EPA
could
not
identify
a
technology­
based
level
of
control
for
the
MACT
floor.
For
beyond­
the­
floor
options
for
the
liquid
subcategory,
the
EPA
identified
several
PM
controls
(
e.
g.,
fabric
filters,
electrostatic
precipitators,
and
venturi
scrubbers)
that
would
reduce
non­
mercury
metallic
HAP
emissions.
For
the
above­
the­
floor
analysis,
we
analyzed
the
cost
and
emission
reduction
of
applying
a
high
efficiency
PM
control
device,
such
as
a
fabric
filter,
since
these
would
be
more
likely
to
be
installed
for
units
firing
liquid
fuel.
We
identified
wet
scrubbers
as
a
1­
14
technology
option
beyond
the
floor
for
reduction
of
inorganic
HAP,
such
as
HCl.
We
identified
fabric
filters
as
a
technology
option
beyond
the
floor
for
reduction
of
mercury.
Consequently,
the
EPA
analyzed
the
emissions
reductions
and
additional
cost
of
applying
high
efficiency
PM
controls
and
wet
scrubbers
on
liquid
fuel­
fired
units.
The
additional
total
annualized
cost
of
a
high
efficiency
PM
control
device
(
such
as
a
fabric
filter)
was
estimated
to
be
$
460
million,
with
an
additional
estimated
emission
reduction
of
1,500
tons
per
year
for
non­
mercury
metallic
HAP
and
3
tons
per
year
for
mercury.
The
annualized
cost
of
a
wet
scrubbers
was
estimated
to
be
an
additional
$
480
million,
with
an
additional
HCl
reduction
of
30
tons
per
year.
The
results
indicated
that
while
additional
emissions
reductions
would
be
realized,
the
costs
would
be
too
high
to
consider
them
feasible
options.
Non­
air
quality
health,
environmental
impacts,
and
energy
effects
were
not
significant
factors.
Therefore,
the
EPA
chose
to
not
select
these
controls
as
MACT
for
existing
liquid
units.

Existing
Gas­
fired
Units
For
the
gaseous
fuel
subcategories,
the
EPA
could
not
identify
a
technology­
based
level
of
control
for
the
MACT
floor.
The
great
majority,
if
not
all,
of
the
emissions
from
gas­
fired
units
are
organic
HAP.
As
discussed
in
section
III.
E
of
the
preamble,
CO
monitoring
and
emission
limits
were
considered
as
an
above
the
floor
option
but
was
not
selected
as
MACT
given
the
costs
and
uncertain
reductions
achieved.
Therefore,
no
above
the
floor
control
technique
was
analyzed
for
organic
HAPs,
and
MACT
is
no
emission
reduction
of
non­
mercury
metallic
HAP
and
mercury,
inorganic
HAP,
and
organic
HAP.

Fuel
Switching
as
a
Beyond­
the­
floor
Option
For
the
solid
fuel
and
liquid
fuel
subcategories,
fuel
switching
to
natural
gas
is
a
regulatory
option
more
stringent
than
the
MACT
floor
level
of
control
that
would
reduce
mercury,
metallic
HAP,
and
inorganic
HAP
emissions.
We
determined
that
fuel
switching
was
not
an
appropriate
above­
thefloor
option
for
the
reasons
discussed
in
sections
III.
A
and
III.
D
of
this
proposal
preamble.
In
some
cases,
organic
HAP
would
be
increased
by
fuel
switching.
Additionally,
the
estimated
emissions
reductions
that
would
be
achieved
if
solid
and
liquid
fuel
units
switched
to
natural
gas
were
compared
with
the
estimated
cost
of
converting
existing
solid
fuel
and
liquid
fuel
units
to
fire
natural
gas.
The
annualized
cost
of
fuel
switching
was
estimated
to
be
$
12
billion.
The
additional
emission
reduction
associated
with
it
was
estimated
to
be
1,500
tons
per
year
for
metallic
HAP,
11
tons
per
year
for
mercury,
and
13,000
tons
per
year
for
inorganic
HAP.
Additional
detail
on
the
calculation
procedures
is
provided
in
the
memorandum
"
Development
of
Fuel
Switching
Costs
and
Emissions
reductions
for
Industrial,
Commercial,
and
Institutional
Boilers
and
Process
Heaters"
in
the
docket.

1.2.3.3
EPA
Response
to
Recent
Court
Decisions
in
Developing
the
Emission
Limitations
In
developing
the
emission
limitations,
we
tried
to
be
responsive
to
the
recent
court
decisions
from
National
Lime
Association
v.
EPA
and
Cement
Kiln
Recycling
Coalition
v.
EPA,
regarding
the
methodology
used
for
determining
the
MACT
floor.
In
response,
we
determined
that
the
most
acceptable
and
appropriate
approach
for
determining
the
MACT
floor
appears
to
be
using
only
emission
data.
As
discussed
and
explained
in
section
II.
E
of
the
proposal
preamble,
we
determined
that
for
these
source
categories
and
the
subcategories
established
the
use
of
only
the
available
emission
data
would
be
inappropriate
for
determining
the
MACT
floor
for
existing
and
new
units.
If
only
the
available
emission
data
(
from
a
population
of
units
that
is
deemed
unrepresentative)
is
used,
the
resulting
MACT
floor
emission
levels
would
be,
in
most
many
cases,
unachievable.
This
is
because
the
concentration
of
HAP
(
metals,
HCl,
mercury)
vary
greatly
within
each
fuel
type.
Some
even
have
fuel
analysis
levels
below
the
detection
limit.
Therefore,
some
units
without
any
add­
on
controls
have
emission
levels
below
those
with
add­
on
controls.
Section
III.
E
of
the
proposal
preamble
explains
in
more
detail
the
approach
used
to
develop
the
MACT
floors
for
each
subcategory
and
why
the
approach
is
appropriate
for
the
subcategories
regulated
by
this
rule
and
why
the
mandating
of
fuel
choice
(
using
low
HAP­
containing
fuel)
is
also
inappropriate.

In
terms
of
subcategorizing,
the
main
difficulty
of
establishing
a
separate
subcategory
for
each
specific
fuel
type
is
that
many
industrial
boilers
burn
a
combination
of
fuels.
Determining
which
subcategory
applies
if
the
mixture
varies
would
be
problematic.
Would
the
applicable
emission
limits
change
each
time
the
fuel
mixture
changes?
How
would
compliance
be
determine
and
how
would
1­
15
continuous
compliance
be
monitored?
Because
of
these
concerns,
EPA
chose
not
to
further
subcategorize
sources
by
each
specific
fuel
type.

However,
if
we
were
to
further
subcategorize
solid­
fuel
units
into
separate
fossil
and
non­
fossil
subcategories,
we
would
first
determine
if
the
MACT
floor
could
be
developed,
for
either
subcategory,
based
on
emissions
information.
If
not,
then
we
would
look
at
developing
MACT
floors
based
on
control
technologies.
First
we
would
determine
if
fuel
switching
or
work
practices
could
be
used.
Based
on
the
MACT
floor
analysis
for
solid­
fuel
fired
boilers,
it
is
expected
that
emissions
information
and
fuel
switching
would
not
be
appropriate
to
develop
the
MACT
floors
for
a
solid
fossil
or
solid
nonfossil
subcategory.
Similarly,
there
would
be
an
insufficient
number
of
boilers
or
process
heaters
that
would
be
meeting
CO
limits
to
set
a
level
for
existing
units.
However,
new
units
would
likely
be
subject
to
a
CO
limit
and
monitoring.

In
order
to
determine
the
MACT
floor
based
on
add­
on
control
technologies,
we
would
follow
similar
procedures
described
in
section
III.
E
of
the
preamble.
We
would
examine
the
population
database
of
existing
sources
and
subcategorize
solid
fossil
and
non­
fossil
fuel
fired
boilers
into
each
of
the
following
three
subcategories
based
on
capacity:
(
1)
large
boilers
and
process
heaters
(
units
with
heat
inputs
greater
than
10
MMBtu/
hr);
(
2)
small
units
(
with
a
maximum
rated
heat
input
capacity
of
10
MMBtu/
hr
or
less);
and
(
3)
limited
use
units
with
capacity
utilization
less
than
10
percent.

We
would
identify
the
types
of
air
pollution
control
techniques
currently
used
by
existing
boilers
and
process
heaters
in
each
subcategory.
Then
we
would
rank
those
controls
according
to
their
effectiveness
in
removing
the
different
categories
of
pollutants;
including
metallic
HAP
and
PM,
inorganic
HAP
such
as
acid
gases,
mercury,
and
organic
HAP.

Based
upon
the
emissions
reduction
potential
of
existing
air
pollution
control
techniques,
we
would
list
all
the
boilers
and
process
heaters
in
the
population
database
in
order
of
decreasing
control
device
effectiveness
for
each
subcategory.
Then
the
technology
basis
of
the
existing
source
MACT
floor
would
be
determined
for
each
pollutant
category
by
identifying
the
best­
performing
12
percent
of
units.
We
would
then
selected
the
technology
used
by
the
median
unit
in
the
best
performing
12
percent
of
units
(
i.
e.,
the
boiler
or
process
heater
unit
representing
the
94th
percentile)
as
the
technology
associated
with
the
MACT
floor
level
of
control
for
each
subcategory.

After
establishing
the
technology
basis
for
the
existing
source
MACT
floor
for
each
subcategory
and
each
type
of
pollutant,
we
would
examine
the
emissions
data
available
for
boilers
and
process
heaters
controlled
by
these
technologies
to
determine
achievable
emission
levels.
The
resulting
emission
levels
associated
with
the
existing
source
MACT
floors
for
each
pollutant
would
be
based
on
the
average
of
the
lowest
three
run
average
test
data
from
units
using
the
technology
associated
with
the
MACT
floor
level
of
control,
and
by
incorporating
operational
variability
using
results
from
multiple
tests
on
these
best
performing
units.

The
preliminary
MACT
floor
control
technology
for
solid
fossil­
fuel
fired
units
would
be
a
combination
of
a
fabric
filter
and
a
scrubber.
The
preliminary
MACT
floor
control
technology
for
solid
non­
fossil­
fuel
fired
units
would
be
a
combination
of
an
ESP
and
a
scrubber.

1.2.3.4
How
did
EPA
Determine
the
Emission
Limitations
for
New
Units?

All
standards
established
pursuant
to
section
112
of
the
CAA
must
reflect
MACT,
the
maximum
degree
of
reduction
in
emissions
of
air
pollutants
that
the
Administrator,
taking
into
consideration
the
cost
of
achieving
such
emissions
reductions,
and
any
non­
air
quality
health
and
environmental
impacts
and
energy
requirements,
determines
is
achievable
for
each
category.
The
CAA
specifies
that
the
degree
of
reduction
in
emissions
that
is
deemed
achievable
for
new
boilers
and
process
heaters
must
be
at
least
as
stringent
as
the
emissions
control
that
is
achieved
in
practice
by
the
bestcontrolled
similar
unit.
However,
the
EPA
may
not
consider
costs
or
other
impacts
in
determining
the
MACT
floor.
The
EPA
may
require
a
control
option
that
is
more
stringent
than
the
floor
(
beyond­
thefloor
if
the
Administrator
considers
the
cost,
environmental,
and
energy
impacts
to
be
reasonable.

Determining
the
MACT
floor
for
New
Units
1­
16
Similar
to
the
MACT
floor
process
used
for
existing
units,
we
considered
several
approaches
to
identifying
MACT
floors
for
new
industrial,
commercial,
and
institutional
boilers
and
process
heaters.
First,
we
considered
using
emissions
data
on
boilers
and
process
heaters
to
set
the
MACT
floor.
However,
after
review
of
the
data
available,
we
determined
that
emissions
information
was
inadequate
to
set
MACT
floors.
We
also
reviewed
State
regulations
and
permits
for
these
sources,
but
found
no
State
regulations
or
State
permits
which
specifically
limit
HAP
emissions
from
industrial,
commercial,
and
institutional
boilers
and
process
heaters.

Consequently,
we
concluded
that
the
only
reasonable
approach
for
determining
MACT
floors
is
to
base
it
on
control
technology.
Data
were
available
on
the
control
technologies
employed
by
the
population
of
boilers
identified
by
the
EPA.
We
considered
several
possible
control
technologies
(
i.
e.,
factors
that
influence
emissions),
including
fuel
substitution,
process
changes
and
work
practices,
and
add­
on
control
technologies.

We
first
considered
whether
fuel
switching
would
be
an
appropriate
control
option
for
sources
in
each
subcategory.
Both
fuel
switching
to
other
fuels
used
in
the
subcategory
and
fuels
from
other
subcategories
were
considered.
This
consideration
included
determining
whether
switching
fuels
would
achieve
lower
HAP
emissions.
A
second
consideration
was
whether
fuel
switching
could
be
technically
done
on
boilers
and
process
heaters
in
the
subcategory
considering
the
existing
design
of
boilers
and
process
heaters.
We
also
considered
the
availability
of
the
alternative
fuel.

As
discussed
in
section
III.
D
of
the
proposal
preamble,
based
on
the
data
available
in
the
emissions
database,
we
determined
that
while
fuel
switching
would
decrease
some
HAPs,
emissions
of
some
organic
HAPs
would
increase,
resulting
in
uncertain
benefits.
We
determined
that
it
would
be
inappropriate
in
a
MACT
rulemaking,
that
is
technology
based,
to
consider
a
technology
that
potentially
will
result
in
an
increase
in
a
HAP
regardless
of
its
potential
to
reduce
other
HAP
without
determining
the
overall
benefit.
A
detailed
discussion
of
the
consideration
of
fuel
switching
is
discussed
in
proposal
preamble
section
III.
D.

We
also
determined
that
using
process
changes
or
work
practices
were
not
appropriate
in
most
cases
for
developing
MACT
floors.
HAP
emissions
from
boilers
and
process
heaters
are
primarily
dependent
upon
the
composition
of
the
fuel.
Fuel
dependent
HAP
are
metals,
including
mercury,
and
acid
gases.
Fuel
dependent
HAP
are
typically
controlled
by
removing
them
from
the
flue
gas
after
combustion.
Therefore,
they
are
not
affected
by
the
operation
of
the
boiler
or
process
heater.
Consequently,
process
changes
would
be
ineffective
in
reducing
their
emissions.
The
exception
to
this
conclusion
is
monitoring
and
maintaining
CO
levels.
The
measurement
of
CO
is
generally
an
indicator
of
incomplete
combustion
since
CO
will
burn
to
carbon
dioxide
if
adequate
oxygen
is
available.
Correcting
incomplete
combustion
may
be
accomplished
through
providing
more
combustion
air.
Therefore,
we
consider
monitoring
and
maintaining
CO
emission
levels
to
be
associated
with
minimizing
organic
HAP
emission
levels
and,
thus,
CO
monitoring
would
be
a
good
indicator
of
combustion
efficiency
and
organic
HAP
emissions.
As
discussed
in
the
final
preamble,
CO
is
considered
a
surrogate
for
organic
HAP
emissions
in
this
rule.

To
determine
if
CO
monitoring
would
be
the
basis
of
the
new
source
MACT
floor
for
organic
emissions
control,
we
examined
available
information.
The
population
databases
did
not
contain
information
on
existing
units
monitoring
CO
emissions.
We
reviewed
State
regulations
applicable
to
boilers
and
process
heaters
that
required
the
use
of
CO
monitoring
to
maintain
a
specific
CO
limit.
The
analysis
of
the
State
regulations
indicated
that
at
least
one
of
the
boilers
and
process
heaters
in
the
large
and
limited
use
subcategories
for
solid
fuel,
liquid
fuel,
and
gaseous
fuel
were
required
to
monitor
CO
emissions
and
meet
a
CO
limit
of
200
parts
per
million.
Therefore,
the
new
source
MACT
floor
level
of
control
includes
a
CO
emission
limit
of
200
parts
per
million
for
large
and
limited
use
units.

We
concluded
that,
except
for
CO
monitoring
for
organic
HAP,
add­
on
control
technology
is
the
only
factor
that
significantly
controls
emissions.
To
determine
the
MACT
floor
for
new
sources,
the
EPA
reviewed
the
population
database
of
existing
major
sources.

Based
upon
the
emission
reduction
potential
of
existing
air
pollution
control
devices,
the
EPA
listed
all
the
boilers
and
process
heaters
in
the
population
database
in
order
of
decreasing
control
device
effectiveness
for
each
subcategory
and
each
type
of
pollutant.
Once
the
ranking
of
all
existing
boilers
and
process
heaters
was
completed
for
each
subcategory
and
type
of
pollutant,
the
EPA
determined
the
1­
17
technology
basis
of
the
new
source
MACT
floor
by
identifying
the
best­
controlled
source
using
the
air
pollution
control
rankings.

After
establishing
the
technology
basis
for
the
new
source
MACT
floor
for
each
subcategory
and
each
type
of
pollutant,
the
EPA
examined
the
emissions
data
available
for
boilers
and
process
heaters
controlled
by
these
technologies
to
determine
achievable
emission
levels
for
PM
(
as
a
surrogate
for
non­
mercury
metallic
HAP),
total
selected
non­
mercury
metallic
HAP,
mercury,
HCl
(
as
a
surrogate
for
inorganic
HAP),
and
CO
(
as
a
surrogate
for
organic
HAP).
This
approach
is
reasonable
because
the
most
informative
way
to
predict
the
worst
reasonably
foreseeable
performance
of
the
best­
controlled
unit,
with
available
data,
is
to
examine
the
performance
of
other
units
that
use
the
same
technology.
In
other
words,
the
EPA
considers
all
units
with
the
same
control
technology
to
be
equally
well
controlled,
and
each
unit
with
the
best
control
technology
is
a
"
best
controlled
similar
unit"
even
if
the
emission
test
results
from
such
units
vary
considerably.

Accordingly,
we
selected
as
the
floor
for
new
units
the
level
of
control
that
was
being
achieved
in
practice
by
the
best­
controlled
similar
source,
that
is,
the
source
with
emissions
representing
the
performance
of
the
most
effective
control
technology
under
the
worst
reasonably
foreseeable
circumstances.
A
detailed
description
of
the
MACT
floor
determination
is
in
the
memorandum
"
MACT
Floor
Analysis
for
New
and
Existing
Sources
in
the
Industrial,
Commercial,
and
Institutional
Boilers
and
Process
Heaters
Source
Categories"
in
the
docket.

New
Solid
Fuel­
fired
Units
Large
Units
­
Heat
Inputs
Greater
than
10
MMBtu/
hr.
The
most
effective
control
technology
identified
for
removing
PM
from
boilers
in
this
subcategory
is
fabric
filters.
Therefore,
the
EPA
considers
a
fabric
filter
to
be
the
technology
basis
for
the
new
source
MACT
floor
for
non­
mercury
metallic
HAP
emissions.
The
MACT
floor
emission
level
based
on
fabric
filters
is
0.04
lb
PM/
MMBtu.
This
PM
emission
level
was
selected
from
a
subset
of
fabric
filters
contained
in
the
database.
This
subset
includes
fabric
filters
assumed
to
be
subject
or
achieving
the
NSPS
for
industrial
boilers.
The
NSPS
(
40
CFR
60.40b),
which
represent
best
demonstrated
technology
for
criteria
pollutants,
is
based
on
the
use
of
a
fabric
filter
for
PM
and
requires
the
use
of
a
scrubber
for
sulfur
dioxide.
Therefore,
fabric
filters
subjected
to
the
NSPS
are
assumed
to
be
better
designed,
and
operated
than
those
built
prior
to
the
NSPS.

We
are
also
providing
an
alternative
metals
limit
of
0.00007
lb
metals/
MMBtu
which
can
be
used
to
show
compliance
in
cases
where
metal
HAP
emissions
are
low
in
proportion
to
PM
emissions.
The
emissions
database
indicates
that
some
biomass
units
have
low
metals
content
but
high
PM
emissions.
The
emission
level
for
metals
was
selected
from
metals
test
data
associated
with
PM
emission
tests
from
fabric
filters
that
met
the
MACT
floor
PM
emission
level.
The
most
effective
control
technologies
identified
for
removing
inorganic
HAP
including
acid
gases,
such
as
HCl,
are
wet
scrubbers
and
packed
bed
scrubbers.
Wet
scrubbers
is
a
generic
term
that
is
most
often
used
to
describe
venturi
scrubbers,
but
can
include
packed
bed
scrubbers,
impingement
scrubbers,
etc.
One
percent
of
boilers
and
process
heaters
in
this
subcategory
reported
using
a
packed
bed
scrubber.
Emission
test
data
from
other
industries
suggests
that
packed
bed
scrubbers
achieve
consistently
lower
emission
levels
than
wet
scrubbers.
Therefore,
the
EPA
considers
a
packed
bed
scrubber
to
be
the
technology
basis
for
the
new
source
MACT
floor
for
acid
gas
control
for
boilers
and
process
heaters
in
the
solid
fuel
subcategory.
The
MACT
floor
emission
level
based
on
packed
scrubbers
is
0.016
lb
HCl/
MMBtu.

For
mercury
control,
one
technology,
carbon
injection,
that
has
demonstrated
mercury
reductions
in
other
source
categories
(
i.
e.,
municipal
waste
combustors),
was
identified
as
being
used
on
one
existing
industrial
boiler.
However,
test
data
on
this
carbon
injection
system
indicated
that
this
unit
was
not
achieving
mercury
emissions
reductions.
Therefore,
we
did
not
consider
carbon
injection
to
be
a
MACT
floor
control
technology
for
industrial,
commercial,
and
institutional
boilers
and
process
heaters.
Data
from
electric
utility
boilers
indicate
that
fabric
filters
can
achieve
mercury
emissions
reductions.
Therefore,
the
EPA
considers
a
fabric
filter
to
be
the
control
technology
basis
for
controlling
mercury
in
this
subcategory.
The
MACT
floor
emission
level
based
on
fabric
filters
is
0.0000026
lb
mercury/
MMBtu.

Similar
control
technology
analysis
was
done
for
the
boilers
and
process
heaters
in
this
subcategory
for
organic
HAP.
One
control
technique,
controlling
inlet
temperature
to
the
PM
control
1­
18
device,
that
has
demonstrated
controlling
downstream
formation
of
dioxins
in
other
source
categories
(
e.
g.,
municipal
waste
combustors)
was
analyzed
for
industrial
boilers.
Inlet
and
outlet
dioxins
test
data
were
available
on
four
boilers
controlled
with
PM
control
devices.
In
all
cases,
no
increase
in
dioxins
emissions
were
indicated
across
the
PM
control
device
even
at
high
inlet
temperatures.
However,
we
are
requesting
comment
on
controls
that
would
achieve
reductions
of
organic
HAP,
including
any
additional
data
that
might
be
available.
The
EPA
did
find
that
CO
monitoring
can
reduce
organic
HAP
emissions,
and
has
included
it
in
the
new
source
MACT
floors
as
described
under
section
III.
F.
of
this
preamble.

In
light
of
this
analysis,
the
EPA
determined
that
the
combination
of
a
fabric
filter,
a
packed
bed
scrubber,
and
CO
monitoring
forms
the
control
technology
basis
for
the
new
source
MACT
floor
for
boilers
and
process
heaters
in
this
subcategory.

Small
Units
­
Heat
Inputs
Less
than
or
Equal
to
10
MMBtu/
hr.
The
most
effective
control
technologies
identified
for
removing
non­
mercury
metallic
HAP
used
by
units
in
this
subcategory
are
fabric
filters.
Therefore,
the
EPA
considers
fabric
filters
to
be
the
technology
basis
for
the
new
source
MACT
floor
for
non­
mercury
metallic
HAP
control
in
this
subcategory.
The
most
effective
control
technology
identified
for
units
in
this
subcategory
for
removing
acid
gases,
such
as
HCl,
are
wet
scrubbers.
The
most
effective
control
technologies
identified
for
removing
mercury
used
by
units
in
this
subcategory
are
fabric
filters.

The
EPA
identified
no
control
technology
being
used
in
the
existing
population
of
boilers
and
process
heaters
that
consistently
achieved
lower
emission
rates
than
uncontrolled
levels,
such
that
a
best­
controlled
similar
source
for
organic
HAP
could
be
identified.
We
concluded
the
MACT
floor
for
new
sources
in
this
subcategory
is
no
emissions
reductions
for
organic
HAP.
Furthermore,
CO
monitoring
is
not
required
for
small
boilers
and
process
heaters
by
any
State
rules.

Thus,
the
EPA
determined
that
the
combination
of
a
fabric
filter
and
a
wet
scrubber
forms
the
control
technology
basis
for
the
new
source
MACT
floor
for
boilers
and
process
heaters
in
this
subcategory.

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

The
MACT
floor
emission
level
based
on
emissions
data
for
fabric
filters
on
solid
fuel­
fired
boilers
is
0.04
lb
PM/
MMBtu
or
0.00007
lb
selected
non­
mercury
metals/
MMBtu,
and
0.0000026
mercury/
MMBtu.
The
MACT
floor
emission
level
based
on
wet
scrubbers
is
0.032
lb
HCl/
MMBtu.
.

Limited
Use
Units
­
Capacity
Utilizations
Less
than
or
Equal
to
10
Percent.
The
most
effective
control
technologies
identified
for
removing
non­
mercury
metallic
HAP
and
mercury
used
by
units
in
this
subcategory
are
fabric
filters.
Therefore,
the
EPA
considers
fabric
filters
to
be
the
technology
basis
for
the
new
source
MACT
floor
for
non­
mercury
metallic
HAP
and
mercury
control
in
this
subcategory.
The
most
effective
control
technology
identified
for
units
in
this
subcategory
for
removing
acid
gases,
such
as
hydrogen
chloride,
are
wet
scrubbers.

The
EPA
did
find
that
monitoring
CO
is
used
by
at
least
one
unit
and
can
reduce
organic
HAP
emissions,
and
has
included
it
in
the
new
source
MACT
floor
for
this
subcategory
as
described
under
section
III.
F
of
this
preamble.

Therefore,
based
on
this
analysis,
the
EPA
determined
that
the
combination
of
a
fabric
filter,
a
wet
scrubber,
and
CO
monitoring
forms
the
control
technology
basis
for
the
new
source
MACT
floor
for
boilers
and
process
heaters
in
this
subcategory.
1­
19
Consequently,
we
determined
that
emissions
information
from
units
greater
than
10
MMBtu/
hr
heat
input
could
be
used
to
establish
MACT
floor
levels
for
this
subcategory
because
the
fuels
and
controls
are
similar.
The
MACT
floor
emission
level
based
on
fabric
filters
is
0.04
lb
PM/
MMBtu
or
0.00007
lb
metals/
MMBtu,
and
0.0000026
mercury/
MMBtu.
The
MACT
floor
emission
level
based
on
wet
scrubbers
is
0.032
lb
HCl/
MMBtu.

New
Liquid
Fuel­
fired
Units
Large
Units
­
Heat
Inputs
Greater
than
10
MMBtu/
hr.
The
most
effective
control
technologies
identified
for
removing
non­
mercury
metallic
HAP
and
PM
from
units
in
this
subcategory
are
fabric
filters.
Therefore,
the
EPA
considers
a
fabric
filter
to
be
the
technology
basis
for
the
new
source
MACT
floor
for
non­
mercury
metallic
HAP.
A
PM
level
is
set
as
a
surrogate
for
non­
mercury
metallic
HAP
control.
The
MACT
floor
emission
level
based
on
emission
data
for
fabric
filters
on
liquid
fuel
fired
boilers
is
0.068
lb
PM/
MMBtu.
Unlike
for
solid
fuel
subcategories,
we
are
not
aware
of
any
liquid
fuels
that
are
low
in
metals
but
would
have
high
PM
emissions.
Therefore,
we
do
not
have
an
alternative
metals
standard
for
the
liquid
subcategories.

The
most
effective
control
technologies
identified
for
removing
inorganic
HAP
that
are
acid
gases,
such
as
HCl,
are
packed
bed
scrubbers.
Therefore,
the
EPA
considers
a
packed
bed
scrubber
to
be
the
technology
basis
for
the
new
source
MACT
floor
for
acid
gas
control
for
boilers
and
process
heaters
in
the
liquid
fuel
subcategory.
The
MACT
floor
emission
level
based
on
packed
scrubbers
is
0.00045
lb
HCl/
MMBtu.

Similar
control
technology
analyses
were
done
for
the
boilers
and
process
heaters
in
this
subcategory
for
mercury
and
organic
HAP.

Information
in
the
emissions
database
or
from
other
source
categories
does
not
show
that
control
technologies,
such
as
fabric
filters
or
wet
scrubbers,
achieve
reductions
in
mercury
emissions
from
liquid
fuel­
fired
industrial,
commercial,
and
institutional
boilers
and
process
heaters.
Therefore,
EPA
identified
no
control
technology
being
used
in
the
existing
population
of
boilers
and
process
heaters
in
these
subcategories
that
consistently
achieved
lower
emission
rates
than
uncontrolled
levels,
such
that
a
best­
controlled
similar
source
for
organic
HAP
could
be
identified.
However,
we
did
find
that
monitoring
CO
is
a
good
combustion
practice
that
can
reduce
organic
HAP
emissions,
and
has
included
it
in
the
new
source
MACT
floor
as
described
under
section
III.
D
of
this
preamble.
We
concluded
the
MACT
floor
for
new
sources
in
this
subcategory
is
no
emissions
reductions
for
mercury.

In
light
of
this
analysis,
the
EPA
determined
that
the
combination
of
a
fabric
filter,
a
packed
bed
scrubber,
and
CO
monitoring
forms
the
control
technology
basis
for
the
new
source
MACT
floor
for
boilers
and
process
heaters
in
this
subcategory.

Small
Units
­
Heat
Inputs
Less
than
or
Equal
to
10
MMBtu/
hr.
The
most
effective
control
technologies
identified
for
removing
non­
mercury
metallic
HAP
used
by
units
in
this
subcategory
are
fabric
filters.
Therefore,
the
EPA
considers
fabric
filters
to
be
the
technology
basis
for
the
new
source
MACT
floor
for
non­
mercury
metallic
HAP
control
in
this
subcategory.
The
most
effective
control
technology
identified
for
units
in
this
subcategory
for
removing
acid
gases,
such
as
hydrogen
chloride,
are
wet
scrubbers.

Information
in
the
emissions
database
or
from
other
source
categories
does
not
show
that
other
control
technologies,
such
as
fabric
filters
or
wet
scrubbers,
achieve
reductions
in
mercury
emissions
from
liquid
fuel­
fired
industrial,
commercial,
and
institutional
boilers
and
process
heaters.
Therefore,
EPA
could
not
identify
a
control
technology
being
used
in
the
existing
population
of
boilers
and
process
heaters
that
consistently
achieved
lower
emission
rates
than
uncontrolled
levels,
such
that
a
bestcontrolled
similar
source
for
mercury
or
organic
HAP
could
be
identified.
We
concluded
the
MACT
floor
for
new
sources
in
this
subcategory
is
no
emissions
reductions
for
mercury
or
organic
HAP.

Thus,
the
EPA
determined
that
the
combination
of
a
fabric
filter
and
a
wet
scrubber
forms
the
control
technology
basis
for
the
new
source
MACT
floor
for
boilers
and
process
heaters
in
this
subcategory.

The
emissions
test
database
did
not
contain
test
data
for
boilers
and
process
heaters
less
than
10
MMBtu/
hr
heat
input.
In
order
to
develop
emission
levels
for
this
subcategory,
we
decided
to
use
1­
20
information
from
units
in
the
large
liquid
subcategory.
We
considered
this
to
be
an
appropriate
methodology
because
although
the
units
in
this
subcategory
are
different
enough
to
warrant
their
own
subcategory
(
i.
e.,
different
designs
and
emissions),
emissions
of
the
specific
types
of
HAP
for
which
limits
are
being
proposed
(
HCl
and
metals)
are
expected
to
be
more
related
to
the
type
of
fuel
burned
and
the
type
of
control
than
to
unit
design.
Consequently,
we
determined
that
emissions
information
from
units
greater
than
10
MMBtu/
hr
heat
input
could
be
used
to
establish
MACT
floor
levels
for
this
subcategory
because
the
fuels
and
controls
are
similar.
The
MACT
floor
emission
level
based
on
fabric
filters
is
0.068
lb
PM/
MMBtu.
The
MACT
floor
emission
level
based
on
wet
scrubbers
is
0.0009
lb
HCl/
MMBtu.

Limited
Use
Units
­
Capacity
Utilizations
Less
than
or
Equal
to
10
Percent.
The
most
effective
control
technologies
identified
for
removing
non­
mercury
metallic
HAP
used
by
units
in
this
subcategory
are
fabric
filters.
Therefore,
the
EPA
considers
fabric
filters
to
be
the
technology
basis
for
the
new
source
MACT
floor
for
non­
mercury
metallic
HAP
control
in
this
subcategory.
The
most
effective
control
technology
identified
for
units
in
this
subcategory
for
removing
acid
gases,
such
as
hydrogen
chloride,
are
wet
scrubbers.

Information
in
the
emissions
database
or
from
other
source
categories
does
not
show
that
other
control
technologies,
such
as
fabric
filters
or
wet
scrubbers,
achieve
reductions
in
mercury
emissions
from
liquid
fuel­
fired
industrial,
commercial,
and
institutional
boilers
and
process
heaters.
The
EPA
identified
no
control
technology
being
used
in
the
existing
population
of
boilers
and
process
heaters
that
consistently
achieved
lower
emission
rates
than
uncontrolled
levels,
such
that
a
best­
controlled
similar
source
for
mercury
could
be
identified.
We
concluded
the
MACT
floor
for
new
sources
in
this
subcategory
is
no
emissions
reductions
for
mercury.

We
did
find
that
monitoring
CO
can
reduce
organic
HAP
emissions
and
is
used
by
at
least
one
unit
in
this
subcategory,
and
have
included
it
in
the
new
source
MACT
floor
as
described
under
section
III.
D
of
this
preamble.
Therefore,
based
on
this
analysis,
the
EPA
determined
that
the
combination
of
a
fabric
filter,
a
wet
scrubber,
and
CO
monitoring
forms
the
control
technology
basis
for
the
new
source
MACT
floor
for
boilers
and
process
heaters
in
this
subcategory.

The
emissions
test
database
did
not
contain
test
data
for
limited
use
liquid­
fired
boilers
and
process
heaters.
In
order
to
develop
emission
levels
for
this
subcategory,
we
decided
to
use
information
from
units
in
the
large
liquid
subcategory.
Consequently,
we
determined
that
emissions
information
from
units
greater
than
10
MMBtu/
hr
heat
input
could
be
used
to
establish
MACT
floor
levels
for
this
subcategory
because
the
fuels
and
controls
are
similar.
The
MACT
floor
emission
level
based
on
fabric
filters
is
0.068
lb
PM/
MMBtu.
The
MACT
floor
emission
level
based
on
wet
scrubbers
is
0.0009
lb
HCl/
MMBtu.

Gaseous
Fuel
Subcategories
No
existing
units
were
using
control
technologies
that
achieve
consistently
lower
emission
rates
than
uncontrolled
sources
for
any
of
the
pollutant
groups
of
interest,
except
organic
HAP.
At
least
one
unit
in
the
population
database
in
the
large
and
limited
use
gaseous
fuel
subcategories
is
required
to
monitor
CO.
Therefore,
the
MACT
floor
for
gaseous
fuel­
fired
units
includes
a
CO
monitoring
requirement
and
emission
limit,
as
described
in
section
III.
D
of
this
preamble,
but
it
does
not
include
any
emission
limits
for
PM,
metallic
HAP,
mercury,
or
inorganic
HAP
based
on
the
utilization
of
addon
control
technology.

How
EPA
Considered
Beyond
the
Floor
Options
for
New
Units
The
MACT
floor
level
of
control
for
new
units
is
based
on
the
emission
control
that
is
achieved
in
practice
by
the
best
controlled
similar
source
within
each
of
the
subcategories.
No
technologies
were
identified
that
would
achieve
non­
mercury
metals
reduction
greater
than
the
new
source
floors
(
i.
e.,
fabric
filters)
for
the
liquid
and
solid
subcategories
or
CO
monitoring
for
the
solid,
liquid,
and
gaseous
subcategories.
For
inorganic
HAP
control,
we
determined
that
packed
bed
scrubbers
achieve
higher
emissions
reductions
than
MACT
floors
consisting
of
a
wet
scrubber.
Packed
bed
scrubbers
are
the
technology
basis
of
the
MACT
floor
for
the
large
unit
subcategory,
but
wet
scrubbers
were
the
technology
basis
of
the
floors
for
the
small
unit
and
limited
unit
subcategories.
Therefore,
we
examined
1­
21
the
cost
and
emission
reductions
of
applying
a
packed
bed
scrubber
as
a
beyond
the
floor
option
for
new
solid
and
liquid
units
within
the
small
and
limited
use
subcategories.
We
determined
that
costs
were
excessive
for
the
limited
emission
reduction
that
would
be
achieved.
Non­
air
quality
health,
environmental
impacts,
and
energy
effects
were
not
significant
factors,
because
there
would
be
little
difference
in
the
non­
air
quality
health
and
environmental
impacts
between
packed
bed
scrubbers
and
wet
scrubbers.
Therefore,
the
EPA
did
not
select
this
beyond­
the­
floor
option,
and
the
proposed
new
source
MACT
level
of
control
for
PM,
metallic
HAP,
and
inorganic
HAP
(
HCl)
is
the
same
as
the
MACT
floor
level
of
control
for
all
of
the
subcategories.

In
reviewing
potential
regulatory
options
beyond
the
new
source
MACT
floor
level
of
control,
the
EPA
identified
one
existing
solid
fuel­
fired
industrial
boiler
that
was
using
carbon
injection
technology
for
mercury
control.
However,
emission
data
obtained
from
this
unit
indicated
that
it
was
not
achieving
mercury
emission
reductions
from
the
uncontrolled
levels.
Moreover,
we
do
not
have
information
to
otherwise
show
that
carbon
injection
is
effective
for
reducing
mercury
emissions
from
industrial,
commercial,
and
institutional
boilers
and
process
heaters.
Information
in
the
emissions
database
or
from
other
source
categories
does
not
show
that
other
control
technologies,
such
as
fabric
filters
or
wet
scrubbers,
achieve
reductions
in
mercury
emissions
from
liquid
fuel­
fired
industrial,
commercial,
and
institutional
boilers
and
process
heaters.
Therefore,
carbon
injection,
for
solid
fuel
units,
and
other
control
techniques,
for
liquid
fuel
units,
were
not
evaluated
as
regulatory
options.

For
the
solid
fuel
and
liquid
fuel
subcategories,
fuel
switching
to
natural
gas
is
a
potential
regulatory
option
beyond
the
new
source
floor
level
of
control
that
would
reduce
mercury
and
metallic
HAP
emissions.
However,
based
on
current
trends
within
the
industry,
the
EPA
projects
that
the
majority
of
new
boilers
and
process
heaters
will
be
built
to
fire
natural
gas
as
opposed
to
solid
and
liquid
fuels
such
that
the
overall
emissions
reductions
associated
with
this
option
would
be
minimal.
Furthermore,
organic
HAP
may
be
increased
by
fuel
switching.
Limited
emissions
reductions
in
combination
with
the
high
cost
of
fuel
switching
and
considerations
about
the
availability
and
technical
feasibility
of
fuel
switching
makes
this
an
unreasonable
regulatory
option
that
was
not
considered
further.
Non­
air
quality
health,
environmental
impacts,
and
energy
effects
were
not
significant
factors.
No
beyond­
the­
floor
options
for
gas­
fired
boilers
were
identified.

Based
on
the
analysis
discussed
above,
the
EPA
decided
to
not
go
beyond
the
MACT
floor
level
of
control
for
new
sources
for
MACT
in
the
rule.

1.2.4
Considerations
of
Possible
Risk­
Based
Alternatives
to
Reduce
Impacts
to
Sources
The
Agency
has
made
every
effort
in
developing
this
rule
to
minimize
the
cost
to
the
regulated
community
and
allow
maximum
flexibility
in
compliance
options
consistent
with
our
statutory
obligations.
However,
we
recognize
that
the
rule
may
still
require
some
facilities
to
take
costly
steps
to
further
control
emissions
even
though
their
emissions
may
not
result
in
exposures
which
could
pose
an
excess
individual
lifetime
cancer
risk
greater
than
one
in
one
million
or
which
exceed
thresholds
determined
to
provide
an
ample
margin
of
safety
for
protecting
public
health
and
the
environment
from
the
effects
of
hazardous
air
pollutants.
We
therefore
solicited
comment
on
whether
there
are
further
ways
to
structure
the
rule
to
focus
on
the
facilities
which
pose
significant
risks
and
avoid
the
imposition
of
high
costs
on
facilities
that
pose
little
risk
to
public
health
and
the
environment.

Representatives
of
the
plywood
and
composite
wood
products
industry
provided
EPA
with
descriptions
of
three
mechanisms
that
they
believed
could
be
used
to
implement
more
cost­
effective
reductions
in
risk.
The
docket
for
today's
rule
contains
"
white
papers"
prepared
by
industry
that
outline
their
proposed
approaches
(
see
docket
number
A­
98­
44,
Item
#
II­
D­
525).
These
approaches
could
be
effective
in
focusing
regulatory
controls
on
facilities
that
pose
significant
risks
and
avoiding
the
imposition
of
high
costs
on
facilities
that
pose
little
risk
to
public
health
or
the
environment,
and
we
sought
public
comment
on
the
utility
of
each
of
these
approaches
with
respect
to
this
rule.

One
of
the
approaches,
an
applicability
cutoff
for
threshold
pollutants,
would
be
implemented
under
the
authority
of
CAA
section
112(
d)(
4);
the
second
approach,
subcategorization
and
delisting,
would
be
implemented
under
the
authority
of
CAA
sections
112(
c)(
1)
and
112(
c)(
9);
and,
the
third
approach,
would
involve
the
use
of
a
concentration­
based
applicability
threshold.
We
sought
comments
1
See
63
FR
18754,
18765­
66
(
April
15,
1998)
(
Pulp
and
Paper
Combustion
Sources
Proposed
NESHAP)

4
"
Draft
Revised
Guidelines
for
Carcinogen
Risk
Assessment."
NCEA­
F­
0644.
USEPA,
Risk
Assessment
Forum,
July
1999.
pp
3­
9ff.
http://
www.
epa.
gov/
ncea/
raf/
pdfs/
cancer_
gls.
pdf
1­
22
on
whether
these
approaches
are
legally
justified
and
asked
for
information
that
could
be
used
to
support
such
approaches.

The
approach
the
Agency
has
chosen
to
include
in
the
final
rule
is
the
first
approach
­
an
applicability
cutoff
for
threshold
pollutants.
The
threshold
pollutants
for
which
an
applicability
cutoff
is
applied
are
hydrochloric
acid
(
Hcl)
and
a
series
of
eight
metals
known
as
the
total
selected
metals
(
TSM).

1.2.4.1
Applicability
Cutoffs
for
Threshold
Pollutants
Under
Section
112(
d)(
4)
of
the
CAA
This
approach
is
an
"
applicability
cutoff"
for
threshold
pollutants
that
is
based
on
EPA's
authority
under
CAA
section
112(
d)(
4).
A
"
threshold
pollutant"
is
one
for
which
there
is
a
concentration
or
dose
below
which
adverse
effects
are
not
expected
to
occur
over
a
lifetime
of
exposure.
For
such
pollutants,
section
112(
d)(
4)
allows
EPA
to
consider
the
threshold
level,
with
an
ample
margin
of
safety,
when
establishing
emissions
standards.
Specifically,
section
112(
d)(
4)
allows
EPA
to
establish
emission
standards
that
are
not
based
upon
the
maximum
achievable
control
technology
(
MACT)
specified
under
section
112(
d)(
2)
for
pollutants
for
which
a
health
threshold
has
been
established.
Such
standards
may
be
less
stringent
than
MACT.
Historically,
EPA
has
interpreted
112(
d)(
4)
to
allow
us
to
avoid
further
regulation
of
categories
of
sources
that
emit
only
threshold
pollutants,
if
those
emissions
result
in
ambient
levels
that
do
not
exceed
the
threshold,
with
an
ample
margin
of
safety.
3
In
the
past,
EPA
routinely
treated
carcinogens
as
non­
threshold
pollutants.
The
EPA
recognizes
that
advances
in
risk
assessment
science
and
policy
may
affect
the
way
EPA
differentiates
between
threshold
and
non­
threshold
HAP.
The
EPA's
draft
Guidelines
for
Carcinogen
Risk
Assessment4
suggest
that
carcinogens
be
assigned
non­
linear
dose­
response
relationships
where
data
warrant.
Moreover,
it
is
possible
that
dose­
response
curves
for
some
pollutants
may
reach
zero
risk
at
a
dose
greater
than
zero,
creating
a
threshold
for
carcinogenic
effects.
It
is
possible
that
future
evaluations
of
the
carcinogens
emitted
by
this
source
category
would
determine
that
one
or
more
of
the
carcinogens
in
the
category
is
a
threshold
carcinogen
or
is
a
carcinogen
that
exhibits
a
non­
linear
dose­
response
relationship
but
does
not
have
a
threshold.

The
dose­
response
assessments
for
formaldehyde
and
acetaldehyde
are
currently
undergoing
revision
by
the
EPA.
As
part
of
this
revision
effort,
EPA
is
evaluating
formaldehyde
and
acetaldehyde
as
potential
non­
linear
carcinogens.
The
revised
dose­
response
assessments
will
be
subject
to
review
by
the
EPA
Science
Advisory
Board,
followed
by
full
consensus
review,
before
adoption
into
the
EPA
Integrated
Risk
Information
System
(
IRIS).
At
this
time,
EPA
estimates
that
the
consensus
review
will
be
completed
sometime
in
2004.
The
revision
of
the
dose­
response
assessments
could
affect
the
potency
factors
of
these
HAP,
as
well
as
their
status
as
threshold
or
non­
threshold
pollutants.
At
this
time,
the
outcome
is
not
known.
In
addition
to
the
current
reassessment
by
EPA,
there
have
been
several
reassessments
of
the
toxicity
of
and
carcinogenicity
of
formaldehyde
in
recent
years,
including
work
by
the
World
Health
Organization
and
the
Canadian
Ministry
of
Health.

1.2.4.2
Applicability
Cutoffs
for
Hydrogen
Chloride
Controls
Under
Section
112(
d)(
4)

of
the
CAA
1­
23
HCl
Compliance
Alternative.

As
an
alternative
to
the
requirement
for
each
large
solid
fuel­
fired
boiler
to
demonstrate
compliance
with
the
HCl
emission
limit
in
the
final
rule,
you
may
demonstrate
compliance
with
a
healthbased
facility­
wide
HCl
equivalent
allowable
emission
limit.

The
procedures
for
demonstrating
eligibility
for
the
HCl
compliance
alternative
(
as
outlined
in
appendix
A
of
the
final
rule)
are:

(
1)
You
must
include
in
your
demonstration
every
emission
point
within
the
facility
that
emits
a
respiratory
toxicant
included
on
EPA's
list
of
hazardous
air
pollutants.

(
2)
You
must
conduct
HCl
and
chlorine
emissions
tests
for
every
emission
point
covered
under
subpart
DDDDD.

(
3)
You
must
obtain
either
through
emission
testing
or
through
the
development
and
documentation
of
best
engineering
estimates
of
maximum
emissions
of
respiratory
toxicants
from
all
emission
points
at
the
facility
not
covered
under
subpart
DDDDD
of
part
63
from
which
a
respiratory
toxicant
might
reasonably
be
emitted.

(
4)
You
must
determine
the
total
maximum
hourly
mass
HCl­
equivalent
emission
rate
for
your
facility
by
summing
the
maximum
hourly
toxicity­
weighted
emission
rates
of
all
appropriate
respiratory
toxicants
(
calculated
using
the
maximum
rated
capacities
of
the
units)
for
each
of
the
units
at
your
facility.

(
5)
Use
the
look­
up
table
in
the
appendix
A
of
subpart
DDDDD
to
determine
if
your
facility
is
in
compliance
with
health­
based
HCl­
equivalent
emission
limit.

(
6)
Select
the
maximum
allowable
HCl­
equivalent
emission
rate
from
the
look­
up
table
in
appendix
A
of
subpart
DDDDD
of
part
63
for
your
facility
using
the
average
stack
height
of
your
subpart
DDDDD
emission
units
as
your
stack
height
and
the
minimum
distance
between
any
respiratory
toxicant
emission
point
at
the
facility
and
the
closest
boundary
of
the
nearest
residential
(
or
residentially
zoned)
area
as
your
fenceline
distance.

(
7)
Your
facility
is
in
compliance
if
your
maximum
HCl­
equivalent
emission
rate
does
not
exceed
the
value
specified
in
the
look­
up
table
in
appendix
A
of
subpart
DDDDD.

(
8)
As
an
alternative
to
using
the
look­
up
table,
you
may
conduct
a
site­
specific
compliance
demonstration
(
as
outlined
in
appendix
A
of
subpart
DDDDD
of
part
63)
which
demonstrate
that
your
facility
cannot
cause
an
individual
chronic
inhalation
exposure
from
respiratory
toxicants
which
can
exceed
a
Hazard
Index
(
HI)
value
of
1.0.

1.2.4.3
Applicability
Cutoffs
for
Total
Selected
Metals
Controls
Under
Section
112(
d)(
4)

of
the
CAA
In
lieu
of
complying
with
the
emission
standard
for
TSM
in
subpart
DDDDD
of
part
63
based
on
the
sum
of
emissions
for
the
eight
selected
metals
(
arsenic,
cadmium,
chromium,
mercury,
manganese,
nickel,
lead,
and
),
you
may
demonstrate
eligibility
for
complying
with
the
TSM
standard
based
on
excluding
manganese
emissions
from
the
summation
of
TSM
emissions
for
the
affected
source
unit.

The
procedures
for
demonstrating
eligibility
for
the
TSM
compliance
alternative
(
as
outlined
in
appendix
A
of
the
subpart
DDDDD)
are:

(
1)
You
must
include
in
your
demonstration
every
emission
point
within
the
facility
that
emits
a
CNS
toxicant
included
on
EPA's
list
of
hazardous
air
pollutants.

(
2)
You
must
conduct
manganese
emissions
tests
for
every
emission
point
covered
under
subpart
DDDDD
that
emits
manganese.

(
3)
You
must
obtain
either
through
emission
testing
or
through
the
development
and
documentation
of
best
engineering
estimates
of
maximum
emissions
of
CNS
toxicants
from
all
emission
points
at
the
facility
not
covered
under
subpart
DDDDD
from
which
a
CNS
toxicant
might
reasonably
be
emitted.
1­
24
(
4)
You
must
determine
the
total
maximum
hourly
manganese
equivalent
emission
rate
from
your
facility
by
summing
the
maximum
hourly
toxicity­
weighted
emission
rates
of
all
appropriate
CNS
toxicants
(
calculated
using
the
maximum
rated
heat
input
capacities)
for
each
of
the
units
at
your
facility.

(
5)
Use
the
look­
up
table
in
appendix
A
of
subpart
DDDDD
to
determine
if
your
facility
is
eligible
for
complying
with
the
TSM
limit
based
on
the
sum
of
emissions
for
seven
metals
(
excluding
manganese)
for
the
affected
source
units.

(
6)
Select
the
maximum
allowable
manganese­
equivalent
emission
rate
from
the
look­
up
table
in
appendix
A
of
subpart
DDDDD
for
your
facility
using
the
average
stack
height
of
your
subpart
DDDDD
emission
units
as
your
stack
height
and
the
minimum
distance
between
any
CNS
toxicant
emission
point
at
the
facility
and
the
closest
boundary
of
the
nearest
residential
(
or
residentially
zoned)
area
as
your
fenceline
distance.

(
7)
Your
facility
is
eligible
if
your
maximum
manganese­
equivalent
emission
rate
does
not
exceed
the
value
specified
in
the
look­
up
table
in
appendix
A
of
subpart
DDDDD.

(
8)
As
an
alternative
to
using
look­
up
table
to
determine
if
your
facility
is
eligible
for
the
TSM
compliance
alternative,
you
may
conduct
a
site­
specific
compliance
demonstration
(
as
outlined
in
appendix
A
of
subpart
DDDDD)
which
demonstrates
that
your
facility
cannot
cause
an
individual
chronic
inhalation
exposure
from
CNS
toxicants
which
can
exceed
a
HI
value
of
1.0.

If
you
elect
to
demonstrate
eligibility
for
either
of
the
health­
based
compliance
alternatives,
you
must
submit
certified
documentation
supporting
compliance
with
the
procedures
at
least
1
year
before
the
compliance
date.

You
must
submit
supporting
documentation
including
documentation
of
all
maximum
capacities,
existing
control
devices
used
to
reduce
emissions,
stack
parameters,
and
property
boundary
distances
to
each
on­
site
source
of
HCl­
equivalent
and/
or
manganese­
equivalent
emissions.

You
must
keep
records
of
the
information
used
in
developing
the
eligibility
demonstration
for
your
affected
source.

To
be
eligible
for
either
health­
based
compliance
alternative,
the
parameters
that
defined
your
affected
source
as
eligible
for
the
health­
based
compliance
alternatives
(
including,
but
not
limited
to,
fuel
type,
type
of
control
devices,
process
parameters
documented
as
worst­
case
conditions
during
the
emissions
testing
used
for
your
eligibility
demonstration)
must
be
incorporated
as
Federally
enforceable
limits
into
your
title
V
permit.
If
you
do
not
meet
these
criteria,
then
your
affected
source
is
subject
to
the
applicable
emission
limits,
operating
limits,
and
work
practice
standards
in
Subpart
DDDDD.

If
you
intend
to
change
key
parameters
(
including
distance
of
stack
to
the
property
boundary)
that
may
result
in
lower
allowable
health­
based
emission
limits,
you
must
recalculate
the
limits
under
the
provisions
of
this
section,
and
submit
documentation
supporting
the
revised
limits
prior
to
initiating
the
change
to
the
key
parameter.

If
you
intend
to
install
a
new
solid
fuel­
fired
boiler
or
process
heater
or
change
any
existing
emissions
controls
that
may
result
in
increasing
HCl­
equivalent
and/
or
manganese­
equivalent
emissions,
you
must
recalculate
the
total
maximum
hourly
HCl­
equivalent
and/
or
manganese­
equivalent
emission
rate
from
your
affected
source,
and
submit
certified
documentation
supporting
continued
eligibility
under
the
revised
information
prior
to
initiating
the
new
installation
or
change
to
the
emissions
controls.

Facilities
that
could
not
demonstrate
that
they
are
eligible
to
be
included
in
the
low­
risk
subcategory
would
be
subject
to
MACT
and
possible
future
residual
risk
standards.

1.3
Other
Federal
Programs
There
are
a
number
of
other
federal
programs
that
affect
air
pollutant
emissions
from
these
sources.
The
effects
of
similar
federal
programs
are
the
following:
1­
25

The
commercial
and
industrial
solid
waste
incinerators
(
CISWI)
standards
(
in
40
CFR
60
subparts
CCCC
and
DDDD)
regulate
commercial
and
industrial
non­
hazardous
solid
waste
incinerators.
These
standards
are
final
as
of
Dec.
1,
2000.
Sources
subject
to
the
CISWI
rules
are
exempt
from
the
requirements
of
this
NESHAP.

The
utility
HAPs
study
Report
to
Congress
provides
information
used
to
determine
whether
fossil
fuel
fired
utility
boilers
should
be
regulated
in
a
future
MACT
standard.
A
fossil
fuelfired
utility
boiler
is
a
fossil
fuel­
fired
combustion
unit
with
a
heat
input
greater
than
25
megawatts
that
serves
a
generator
producing
electricity
for
sale.
Fossil
fuel­
fired
utility
boilers
are
exempt
from
this
regulation.
Non­
fossil
fuel­
fired
utility
are,
however,
covered
by
this
proposed
standard.

EPA's
Office
of
Solid
Waste
is
in
the
process
of
developing
MACT
standards
for
hazardous
waste
boilers.
Boilers
burning
hazardous
waste
are
not
included
in
this
regulation.

Previously,
EPA
had
codified
new
source
performance
standards
(
NSPS)
for
industrial
boilers
in
1986
(
in
40
CFR
60
subparts
Db
and
Dc)
and
revised
portions
of
them
in
1999.
The
NSPS
regulates
emissions
of
particulate
matter
(
PM),
sulfur
dioxide
(
SO2),
and
nitrogen
oxides
(
NOx)
from
boilers
constructed
after
June
19,
1984.
Source
subject
to
the
NSPS
are
still
subject
to
this
NESHAP
because
the
NESHAP
regulates
sources
of
hazardous
air
pollutants
while
the
NSPS
does
not.
However,
in
developing
the
NESHAP
for
industrial/
commercial/
institutional
boilers
and
process
heaters
EPA
minimized
the
monitoring,
recordkeeping
requirements,
and
testing
requirements
so
as
not
to
duplicate
requirements.

1.4
Scope
of
the
Analyses
in
the
RIA
The
MACT
floor
will
affect
approximately
5,600
existing
and
new
units.
EPA
developed
annual
compliance
costs
for
model
units
in
each
of
83
different
model
unit
types.
EPA
then
linked
the
annualized
compliance
costs
from
the
model
units
to
the
estimated
existing
population
of
boilers
and
process
heaters
to
obtain
national
impact
estimates.
In
addition,
the
Agency
projected
entrance
of
new
boilers
and
process
heaters
through
the
year
2005,
and
linked
the
annualized
compliance
costs
to
these
projected
new
units.

The
impacts
of
national
compliance
costs,
including
impacts
to
both
existing
and
new
units,
on
affected
markets
was
then
estimated
using
a
computerized
market
model.
EPA
used
changes
in
prices
and
quantities
in
energy
markets
and
final
product
markets
to
estimate
the
firm­,
industry­,
market­,
and
societal­
level
impacts
associated
with
the
regulation.
EPA
then
estimated
changes
in
particulate
matter
(
PM)
concentrations
associated
with
this
regulation
using
an
air
quality
model
and
then
estimated
the
benefits
associated
with
these
changes
in
PM
concentrations.
To
estimate
the
benefits,
the
Agency
used
an
in­
house
model
to
calculate
benefits
and
then
monetize
them
for
emission
reductions
in
areas
where
the
assignment
of
controls
to
affected
sources
is
well­
defined.
The
Agency
then
used
a
benefits
transfer
technique
to
apply
the
benefits
estimates
from
reductions
at
sources
with
well­
defined
control
assignments
to
calculate
benefits
in
areas
where
the
assignment
of
controls
is
not
well­
assigned.
Finally,
the
Agency
compared
the
benefits
to
the
costs
of
the
regulation.

Results
of
these
analyses
are
presented
for
the
final
rule
(
MACT
floor)
and
Option
1A.
Results
of
the
costs
and
some
economic
impact
information
are
presented
for
Option
1B.
There
is
insufficient
information
for
estimating
the
economic
impacts
and
small
entity
impacts
associated
with
Option
1B,
and
the
benefits
estimate
for
this
option
is
the
same
as
that
for
Option
1A
since
there
are
no
additional
emissions
reductions
expected.

1.5
Organization
of
the
Report
The
remainder
of
this
report
is
divided
into
ten
chapters
that
describe
the
analysis
methodologies
and
presents
the
analyses
results:

Chapter
2
provides
background
information
on
boiler
and
process
heater
technologies.
1­
26

Chapter
3
profiles
existing
boilers
and
process
heaters
by
capacity,
fuel
type,
and
industry
and
presents
projections
of
the
future
population
of
units
in
2005.

Chapter
4
profiles
the
industries
with
the
largest
number
of
affected
facilities.
Included
are
profiles
of
the
lumber
and
wood
products
(
SIC
24/
NAICS
321),
furniture
and
related
product
manufacturing
(
SIC
25/
NAICS
337),
paper
and
allied
products
(
SIC
26/
NAICS
322),
and
electrical
services
(
SIC
49/
NAICS
221)
industries.

Chapter
5
describes
the
methodology
for
assessing
the
economic
impacts
of
the
National
Emission
Standard
for
Hazardous
Air
Pollutants
(
NESHAP).

Chapter
6
presents
the
results
of
the
economic
analysis,
including
market,
industry,
and
social
cost
impacts.

Chapter
7
provides
the
Agency's
analysis
of
the
regulation's
impact
on
small
entities.

Chapter
8
presents
the
Agency's
analysis
of
the
changes
in
air
quality
associated
with
compliance
with
the
regulation,
and
a
description
of
the
emissions
inventories
used
in
the
air
quality
analysis.

Chapter
9
presents
the
results
of
the
qualitative
benefits
associated
with
implementation
of
this
regulation.

Chapter
10
presents
the
results
of
the
quantitative
and
monetized
benefits
associated
with
implementation
of
this
regulation
and
a
comparison
of
the
benefits
to
the
costs
of
the
rule.

In
addition
to
these
chapters,
there
are
five
appendicies
as
well.
Appendix
A
provides
information
on
the
databases
and
equations
used
in
the
economic
impact
analysis,
and
Appendix
B
provides
details
on
assumptions
behind
the
operation
of
the
economic
model,
along
with
results
of
sensitivity
analyses.
Appendix
C
provides
some
results
from
the
air
quality
modeling
conducted
to
determine
reductions
in
concentrations
of
PM
associated
with
the
emissions
reductions
expected
to
take
place.
These
results
are
for
the
above­
the­
floor
option
1A
only.
Appendix
D
contains
the
results
of
sensitivity
analyses
and
alternative
calculations
for
our
benefits
estimates.
Finally,
Appendix
E
contains
impact
estimates
associated
with
the
health­
based
compliance
alternatives
for
HCl
and
Mn
sources.
1­
27
References
Federal
Register,
1993.
Executive
Order
12866,
Regulatory
Planning
and
Review.
Vol.
58,
October
4,
1993,
pg.
51735.

Federal
Register,
2001.
Executive
Order
13211,
Actions
Concerning
Regulations
That
Significantly
Affect
Energy
Supply,
Distribution,
or
Use.
Vol.
66,
May
22,
2001,
pg.
28355.

Federal
Register,
2002.
Executive
Order
13258,
Amending
Executive
Order
12866
­
Regulatory
Planning
and
Review.
Vol.
67
,
February
28,
2002,
pg.
9385.

U.
S.
Environmental
Protection
Agency,
1996.
Guidance
for
Providing
Environmental
Justice
Concerns
in
EPA's
NEPA
Compliance
Analyses
(
Review
Draft).
Office
of
Federal
Activities,
Washington,
D.
C.,
July
12,
1996.

U.
S.
Environmental
Protection
Agency,
1996.
Memorandum
from
Trovato
and
Kelly
to
Assistant
Administrators.
Subject:
"
Implementation
of
Executive
Order
13045,
Protection
of
Children
from
Environmental
Health
and
Safety
Risks."
April
21,
1998.
2­
1
CHAPTER
2
BOILER
AND
PROCESS
HEATER
TECHNOLOGIES
The
three
categories
of
combustion
devices
affected
under
the
regulations
are
industrial
boilers,
commercial
and
institutional
(
ICI)
boilers,
and
process
heaters.
Although
their
primary
function
is
to
transfer
heat
generated
from
fuel
combustion
to
materials
used
in
the
production
process,
the
applications
for
boilers
and
process
heaters
are
somewhat
different.
As
a
result,
the
primary
industries
using
boilers
may
not
be
the
same
as
those
using
process
heaters.
It
is
important
to
note
that
throughout
this
report
the
terms
"
boilers
and
process
heaters,"
and
"
units"
are
synonymous
with
"
ICI
boilers
and
process
heaters."
Utility
boilers
primarily
engaged
in
generating
electricity
are
not
covered
by
the
NESHAP
under
analysis
and
are
therefore
excluded
from
this
analysis.

Boilers
are
combustion
devices
used
to
produce
steam
or
heat
water.
Steam
is
produced
in
boilers
by
heating
water
until
it
vaporizes.
The
steam
is
then
channeled
to
applications
within
a
facility
or
group
of
facilities
via
pipes.
Steam
is
an
important
power
and
heating
source
for
the
U.
S.
economy.
It
is
used
in
the
preparation
or
manufacturing
of
many
key
products,
such
as
paper,
petroleum
products,
furniture,
and
chemicals.
Steam
is
also
used
to
heat
buildings
and
to
generate
the
majority
of
the
electricity
consumed
in
this
country.
There
are
literally
thousands
of
boilers
currently
being
used
in
the
United
States
throughout
a
wide
variety
of
industries.

Process
heaters
are
primarily
used
as
heat
transfer
units
in
which
heat
from
fuel
combustion
is
transferred
to
process
fluids,
although
they
may
also
be
used
to
transfer
heat
to
other
nonfluid
materials
or
to
heat
transfer
materials
for
use
in
a
process
unit
(
not
including
generation
of
steam).
Process
heaters
are
generally
used
in
heat
transfer
applications
where
boilers
are
inadequate.
Often
these
are
uses
in
which
heat
must
be
transferred
at
temperatures
in
excess
of
90

to
204

C
(
200

to
400

F).
Process
heaters
are
used
in
the
petroleum
refining
and
petrochemical
industries,
with
minor
applications
in
the
asphalt
concrete,
gypsum,
iron
and
steel,
and
wood
and
forest
products
industries.

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

2.1
Characteristics
of
Steam
Steam,
an
odorless,
invisible
gas
of
vaporized
water,
may
be
interspersed
with
water
droplets,
which
gives
it
a
cloudy
appearance.
It
is
produced
naturally
when
underground
water
is
heated
by
volcanic
processes
and
mechanically
using
boilers
and
other
heating
processes.
When
water
is
heated
at
atmospheric
pressure,
it
remains
in
liquid
form
until
its
temperature
exceeds
212

F,
the
boiling
point
of
water.
Additional
heat
does
not
raise
the
water's
temperature
but
rather
vaporizes
the
water,
converting
it
into
steam.
However,
if
water
is
heated
under
pressure,
such
as
in
a
boiler,
the
boiling
point
is
higher
than
212

F
and
more
heat
is
required
to
generate
steam.
Once
all
the
water
has
been
vaporized
into
steam,
the
addition
of
heat
causes
the
temperature
and
volume
to
increase.
Steam's
heating
and
work
capabilities
increase
as
it
is
produced
under
greater
pressure
coupled
with
higher
temperatures.
As
steam
escapes
from
the
boiler,
it
can
be
directed
through
pipes
to
drive
mechanical
processes
or
to
provide
heat.

The
steam
used
in
most
utility,
industrial,
and
commercial
applications
is
referred
to
as
"
clean
steam."
Clean
steam
encompasses
steam
purities
ranging
from
pure,
solid­
free
steam
used
in
critical
processes
to
filtered
steam
for
less
demanding
applications.
The
various
types
of
clean
steam
differ
in
steam
purity
and
steam
quality.
Steam
purity
is
a
quantitative
measure
of
contamination
of
steam
caused
by
dissolved
particles
in
the
vapor
or
by
tiny
droplets
of
water
that
may
remain
in
the
steam.
2­
2
Steam
quality
is
a
measure
of
how
much
liquid
water
is
mixed
in
with
the
dry
steam
(
Fleming,
1992).
Firms
select
the
levels
of
steam
quality
and
steam
purity
for
their
applications
based
on
the
sensitivity
of
their
equipment
to
impurities,
water
droplet
size,
and
condensation
as
well
as
the
requirements
for
their
production
process.
Using
clean
steam
minimizes
the
risk
of
product
contamination
and
prolongs
equipment
life.
Although
there
are
infinite
possible
levels
of
water
purity
and
quality,
the
term
"
clean
steam"
generally
refers
to
three
basic
types
of
steam:

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

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

pure
steam
 
similar
to
clean
steam
except
that
it
is
always
produced
from
deionized
and
distilled
water.

Steam
applications
can
be
categorized
by
the
amount
of
pressure
required:
hot
water,
low
pressure,
and
high
pressure.
Low
pressure
is
0
to
15
pounds
per
square
inch
(
psi)
and
high
pressure
steam
is
above
15
psi
(
Plant
Engineering,
1991).
Hot
water
systems,
which
generate
little
steam,
are
primarily
used
for
comfort
applications,
such
as
hot
water
for
a
building.
Low
pressure
applications
include
process
heat
and
space
heating.
High
pressure
steam
applications
are
more
frequently
used
in
industrial
and
utility
applications.
Some
high
pressure
applications
require
that
the
steam
be
superheated,
a
process
which
ensures
that
the
steam
is
free
of
water
droplets,
to
avoid
damaging
sensitive
equipment.

Electric
cogenerators,
such
as
large
factories
and
processing
facilities,
use
steam
to
drive
turbines
to
generate
electricity.
A
conventional
steam
electric
power
plant
burns
fossil
fuels
(
coal,
gas,
or
oil)
in
a
boiler,
releasing
heat
that
boils
water
and
converts
it
into
high­
pressure
steam
(
see
Figure
2­
1).
The
steam
enters
a
turbine
where
it
expands
and
pushes
against
blades
to
turn
the
generator
shaft
and
create
electric
current.
In
this
way,
the
thermal
energy
of
steam
becomes
mechanical
energy,
which
is
converted
into
electricity.
Steam
used
to
drive
turbines
generates
most
of
the
electric
power
in
the
United
States
(
TXU,
2000).

Industrial
operations
use
steam
to
perform
work
such
as
powering
complex
machinery
operations,
in
the
same
way
that
electric
utilities
use
steam
to
rotate
turbines.
Textile
mills,
pulp
and
paper
mills,
and
other
manufacturing
outfits
are
examples
of
facilities
that
use
steam
to
run
machinery.
Steam
also
provides
heat
and
pressure
for
manufacturing
processes.
Industrial
establishments
use
steam
to
provide
heat
for
drying
or
to
heat
and
separate
materials.
For
example,
the
paper
industry
uses
steam
to
heat
rollers
that
dry
paper
during
the
final
stages
of
the
production
process.
Petroleum
refineries
and
chemical
producers
use
steam
to
heat
petroleum,
raw
materials,
and
other
inputs
to
separate
inputs
into
their
constituent
components
or
to
facilitate
chemical
interactions.
In
addition
to
these
applications,
steam
is
employed
in
many
other
industrial
processes,
including
textile
production,
wood
working,
furniture
making,
metal
working,
food
preparation,
and
the
manufacture
of
chemicals.
Substitutes
for
using
steam
as
process
heat
include
electrical
heating
equipment,
infrared,
and
other
radiant
drying
techniques.
Electricity
may
be
used
to
power
machinery,
as
well.
However,
switching
from
steampowered
to
electricity­
powered
machinery
would
require
significant
equipment
retrofits
or
replacement.
2­
3
Figure
2­
1.
Generating
Electricity:
Steam
Turbines
Source:
Texas
Utilities
(
TXU).
2000.
"
Generating
Electricity:
Steam
Turbines."
As
obtained
in
September
2000.
<
http://
www.
txu.
com/
knowledge/
energy_
lib/
generating01.
html>.

Other
steam
applications
include
heating,
sanitation,
food
processing
and
preparation,
and
cleaning.
In
addition
to
using
boilers
to
heat
water,
factories,
hospitals,
government
buildings,
schools
and
other
large
buildings
use
boiler­
generated
steam
to
provide
space
heating.
Substitutes
for
boilers
in
heating
air
and
water
include
electrical
water
and
space
heaters;
furnaces;
and
other
heating,
ventilation,
and
air
conditioning
equipment.

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

2.2.1
Industrial,
Commercial,
and
Institutional
Boilers
Industrial,
commercial,
and
institutional
boilers
are
primarily
used
for
process
heating,
electrical
or
mechanical
power
generation,
and/
or
space
heating.
Industrial
boilers
are
used
in
all
major
industrial
sectors
but
primarily
by
the
paper
products,
chemical,
food,
and
petroleum
industries.
It
is
2­
4
estimated
that
the
heat
input
capacity
for
these
boilers
is
typically
between
10
and
250
MMBtu/
hr;
however,
larger
industrial
boilers
do
exist
and
are
similar
to
utility
boilers
(
EPA,
1997b).
Commercial/
institutional
boilers
are
generally
smaller
than
the
industrial
units,
with
heat
input
capacities
generally
below
10
MMBtu/
hr.
These
units
normally
supply
the
steam
and
hot
water
for
space
heating
in
a
wide
range
of
locations,
including
wholesale
and
retail
trade,
office
buildings,
hotels,
restaurants,
hospitals,
schools,
museums,
government
buildings,
and
airports.
Five
hundred
ninety­
three
of
the
3,615
units
potentially
affected
by
the
floor
alternative
for
the
proposed
regulation
are
commercial/
institutional
units.

A
boiler
system
includes
the
boiler
itself,
associated
piping
and
valves,
operation
and
safety
controls,
water
treatment
system,
and
peripheral
equipment
such
as
pollution
control
devices,
economizers,
or
superheaters
(
Plant
Engineering,
1991).
Most
boilers
are
made
of
steel,
cast
iron,
or
copper.
The
primary
fuels
used
by
boilers
are
coal,
oil,
and
natural
gas,
but
some
use
electricity,
waste
gases,
or
biomass.

Boilers
may
either
be
erected
onsite
(
field­
erected
boilers)
or
assembled
at
a
factory
(
packaged
boilers).
Packaged
boilers
are
typically
lower
in
initial
cost
and
more
simple
to
install.
However,
fielderected
boilers
may
have
lower
operating
costs,
less
maintenance,
and
greater
flexibility
because
the
furnace
or
convection
pattern
chosen
to
meet
required
steam
pressure,
capacity,
and
fuel
specifications
is
tailored
to
the
boiler's
potential
use
(
Plant
Engineering,
1991).
Applications
requiring
more
than
100,000
pounds
of
steam
per
hour
are
usually
equipped
with
a
field­
erected
boiler.

2.2.2
Heat
Transfer
Configurations
The
heat
transfer
configuration
of
a
boiler
refers
to
the
method
by
which
heat
is
transferred
to
the
water.
The
four
primary
boiler
configurations
are
watertube,
firetube,
cast
iron,
and
tubeless.
Most
industrial
users
tend
to
rely
on
either
watertube
or
firetube
configurations.

In
a
watertube
boiler,
combustion
heat
is
transferred
to
water
flowing
through
tubes
lining
the
furnace
walls
and
boiler
passes.
The
furnace
watertubes
absorb
primarily
radiative
heat,
while
the
watertubes
in
the
boiler
passes
gain
heat
by
convective
heat
transfer.
These
units
have
a
wide
range
of
heat
input
capacities
(
ICI
units
range
from
0.4
to
1,500
MMBtu/
hr)
and
can
be
either
field
erected
or
packaged.
1
Watertube
boilers
with
heat
input
capacities
greater
than
200
MMBtu/
hr
are
typically
field
erected.

Because
firetube,
cast
iron,
and
tubeless
heat
transfer
configurations
typically
have
heat
input
capacities
below
10
MMBtu/
hr,
they
will
not
generally
be
covered
by
theNESHAP.
Therefore,
this
profile
focuses
on
those
boiler
types
that
use
watertube
heat
transfer
configurations.

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

2.2.3.1
Stoker­
Fired
Boilers
(
Coal)

These
units
use
underfeed
air
to
combust
the
coal
char
on
a
stationary
grate,
combined
with
one
or
more
levels
of
overfire
air
introduced
above
the
grate.
There
are
three
types
of
stoker
units:

spreader
stokers,

underfeed
stokers,
and

overfeed
stokers.

Stokers
generally
burn
all
types
of
coal,
with
the
exception
of
overfeed
stokers,
which
do
not
burn
coking
bituminous
coals.
Stokers
can
also
burn
other
types
of
solid
fuel,
such
as
wood,
wood
waste,
and
bagasse.
Spreader
stokers
are
the
most
common
of
these
boiler
types
and
have
heat
input
capacities
that
typically
range
from
5
to
550
MMBtu/
hr.
However,
some
of
these
boilers
have
capacities
as
high
as
1,500
MMBtu/
hr.
Smaller
stoker
units
(
i.
e.,
those
with
heat
input
capacities
less
than
100
MMBtu/
hr)
are
generally
packaged,
while
larger
units
are
usually
field
erected.
2­
5
2.2.3.2
Pulverized
Coal
Boilers
(
Coal)

Combustion
in
pulverized
coal­
fired
units
takes
place
almost
entirely
while
the
coal
is
suspended,
unlike
in
stoker
units
in
which
the
coal
burns
on
a
grate.
Finely
ground
coal
is
typically
mixed
with
primary
combustion
air
and
fed
to
the
burner
or
burners,
where
it
is
ignited
and
mixed
with
secondary
combustion
air.
Depending
on
the
location
of
the
burners
and
the
direction
of
coal
injection
into
the
furnace,
pulverized
coal­
fired
boilers
can
be
classified
into
three
different
firing
types:

single
and
opposed
wall,

tangential,
and

cyclone.

Of
these
types,
wall
and
tangential
configurations
are
the
most
common.
These
firing
methods
are
described
further
in
Sections
2.2.3.4
and
2.2.3.5.

2.2.3.3
Fluidized
Bed
Combustion
(
FBC)
Boilers
(
Coal)

FBC
is
an
integrated
technology
for
reducing
sulfur
dioxide
(
SO2)
and
NOx
emissions
during
the
combustion
of
coal.
In
a
typical
FBC
boiler,
crushed
coal
and
inert
material
(
sand,
silica,
alumina,
or
ash)
and/
or
a
sorbent
(
limestone)
are
maintained
in
a
highly
turbulent
suspended
state
by
the
upward
flow
of
primary
air
from
the
windbox
located
directly
below
the
combustion
floor.
This
fluidized
state
provides
a
large
amount
of
surface
contact
between
the
air
and
solid
particles,
which
promotes
uniform
and
efficient
combustion
at
lower
furnace
temperatures
than
conventional
coal­
fired
boilers.
Once
the
hot
gases
leave
the
combustion
chamber,
they
pass
through
the
convective
sections
of
the
boiler,
which
are
similar
or
identical
to
components
used
in
conventional
boilers.

For
the
FBCs
currently
in
use
in
all
sectors,
coal
is
the
primary
fuel
source,
followed
in
descending
order
by
biomass,
coal
waste,
and
municipal
waste.
The
heat
input
capacities
of
all
ICI
FBC
units
generally
range
from
1.4
to
1,075
MMBtu/
hr.

2.2.3.4
Tangentially
Fired
Boilers
(
Coal,
Oil,
Natural
Gas)

The
tangentially
fired
boiler
is
based
on
the
concept
of
a
single
flame
zone
within
the
furnace.
The
fuel­
air
mixture
projects
from
the
four
corners
of
the
furnace
along
a
line
tangential
to
an
imaginary
cylinder
located
along
the
furnace
centerline.
As
fuel
and
air
are
fed
to
the
burners
and
the
fuel
is
combusted,
a
rotating
"
fireball"
is
formed.
Primarily
because
of
their
tangential
firing
pattern,
which
leads
to
larger
flame
volumes
and
flame
interaction,
uncontrolled
tangentially
fired
boilers
generally
emit
relatively
lower
NOx
than
other
uncontrolled
boiler
designs.

Utilities
primarily
use
this
type
of
boiler.
Coal
is
the
most
common
fuel
used
by
these
units.
Tangentially
fired
boilers
operated
by
utilities
are
typically
larger
than
400
MW,
while
industrial
ones
almost
always
have
heat
input
capacities
over
100
MMBtu/
hr.
In
general,
most
units
with
heat
input
capacities
over
100
MMBtu/
hr
are
field
erected.

2.2.3.5
Wall­
fired
Boilers
(
Coal,
Oil,
Natural
Gas)

Wall­
fired
boilers
are
characterized
by
multiple
individual
burners
located
on
a
single
wall
or
on
opposing
walls
of
the
furnace.
In
contrast
to
tangentially
fired
boilers,
each
of
the
burners
in
a
wallfired
boiler
has
a
relatively
distinct
flame
zone,
and
the
burners
in
wall­
fired
boilers
do
not
tilt.
Superheated
steam
temperatures
are
instead
controlled
by
excess
air
levels,
heat
input,
flue
gas
recirculation,
and/
or
steam
attemperation
(
water
spray).
Depending
on
the
design
and
location
of
the
burners,
wall­
fired
boilers
are
referred
to
as
single
wall
or
opposed
wall.

Wall­
fired
boilers
are
used
to
burn
coal,
oil,
or
natural
gas,
and
some
designs
feature
multifuel
capability.
Almost
all
industrial
wall­
fired
boilers
have
heat
input
capacities
greater
than
100
MMBtu/
hr.
Opposed­
wall
boilers
in
particular
are
usually
much
larger
than
250
MMBtu/
hr
heat
input
capacity
and
are
much
more
common
in
utility
rather
than
in
industrial
operations.
Because
of
their
size,
most
wall­
fired
units
are
field
erected.
Field­
erected
watertube
boilers
strictly
designed
for
oil
firing
are
more
compact
than
coal­
fired
boilers
with
the
same
heat
input,
because
of
the
more
rapid
combustion
characteristics
of
fuel
oil.
Field­
erected
watertube
boilers
fired
by
natural
gas
are
even
more
compact
because
of
the
rapid
combustion
rate
of
the
gaseous
fuel,
the
low
flame
luminosity,
and
the
ash­
free
content
of
natural
gas.
2­
6
2.3
Process
Heater
Characterization
Process
heaters
are
heat
transfer
units
in
which
heat
from
fuel
combustion
is
transferred
to
materials
used
in
a
production
process.
The
process
fluid
stream
is
heated
primarily
for
one
of
two
reasons:
to
raise
the
temperature
for
additional
processing
or
to
make
chemical
reactions
occur.
This
section
describes
the
different
classes
of
process
heaters
and
major
design
types.

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

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

direct­
fired
process
heater
 
any
process
heater
in
which
the
combustion
gases
mix
with
and
exhaust
to
the
atmosphere
from
the
same
stack(
s)
or
vent(
s)
with
gases
originating
from
the
process
or
material
being
processed.

Indirect­
fired
units
are
used
in
situations
where
direct
flame
contact
with
the
material
being
processed
is
undesirable
because
of
problems
with
contamination
and
ignition
of
the
process
material.
Direct­
fired
units
are
used
where
such
problems
are
not
an
important
factor.
Emissions
of
indirect­
fired
units
consist
solely
of
the
products
of
combustion
(
including
those
of
incomplete
combustion).
On
the
other
hand,
direct­
fired
units
will
generate
emissions
consisting
not
only
of
the
products
of
combustion,
but
also
the
process
material(
s).
This
means
that
the
emissions
from
indirect­
fired
process
heaters
will
be
generic
to
the
fuel
in
use
and
are
common
across
industries
while
emissions
from
direct­
fired
process
heaters
are
unique
to
a
given
process
and
may
vary
widely
depending
on
the
process
material.
Only
indirect­
fired
process
heaters
are
considered
under
this
proposed
regulation.
Many
direct­
fired
process
heaters
are
being
considered
under
separate
MACT­
development
projects.

In
addition
to
the
distinction
between
direct­
and
indirect­
fired
heaters,
process
heaters
may
also
be
considered
either
heated
feed
or
reaction
feed.
Heated
feed
process
heaters
are
used
to
heat
a
process
fluid
stream
before
additional
processing.
These
types
of
process
heaters
are
used
as
preheaters
for
various
operations
in
the
petroleum
refining
industry
such
as
distillation,
catalytic
cracking,
hydroprocessing,
and
hydroconversion.
In
addition,
heated
feed
process
heaters
are
used
widely
in
the
chemical
manufacturing
industry
as
fired
reactors
(
e.
g.,
steam­
hydrocarbon
reformers
and
olefins
pyrolysis
furnaces),
feed
preheaters
for
nonfired
reactors,
reboilers
for
distillation
operations,
and
heaters
for
heating
transfer
oils.
Reaction
feed
process
heaters
are
used
to
provide
enough
heat
to
cause
chemical
reactions
to
occur
inside
the
tubes
being
heated.
Many
chemical
reactions
do
not
occur
at
room
temperature
and
require
the
application
of
heat
to
the
reactants
to
cause
the
reaction
to
take
place.
Applications
include
steam­
hydrocarbon
reformers
used
in
ammonia
and
methanol
manufacturing,
pyrolysis
furnaces
used
in
ethylene
manufacturing,
and
thermal
cracking
units
used
in
refining
operations.

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

2.3.2.1
Combustion
Chamber
Set­
Ups
Process
heaters
contain
a
radiant
heat
transfer
area
in
the
combustion
chamber.
This
area
heats
the
process
fluid
stream
in
the
tubes
by
flame
radiation.
Equipment
found
in
this
area
includes
the
burner(
s)
and
the
combustion
chamber(
s).
Most
heat
transfer
to
the
process
fluid
stream
occurs
here,
but
these
tubes
do
not
necessarily
constitute
a
majority
of
the
tubes
in
which
the
process
fluid
flows.

Most
process
heaters
also
use
a
convective
heat
transfer
section
to
recover
residual
heat
from
the
hot
combustion
gases
by
convective
heat
transfer
to
the
process
fluid
stream.
This
section
is
located
after
the
radiant
heat
transfer
section
and
also
contains
tubes
filled
with
process
fluid.
The
first
few
rows
of
tubes
in
this
section
are
called
shield
tubes
and
are
subject
to
some
radiant
heat
transfer.
Typically,
the
process
fluid
flows
through
the
convective
section
prior
to
entering
the
radiant
section
to
2­
7
preheat
the
process
fluid
stream.
The
temperature
of
the
flue
gas
upon
entering
the
convective
section
usually
ranges
from
800

C
to
1,000

C
(
1,500

F
to
2,000

F).
Preheating
in
the
convective
section
improves
the
efficiency
of
the
process
heater,
particularly
if
the
tube
design
includes
fins
or
other
extended
surface
areas.
An
extended
tube
surface
area
can
improve
efficiency
by
10
percent.
Extended
tubes
can
reduce
flue
gas
temperatures
from
800

C
to
1,000

C
to
(
1,500

F
to
2,000

F)
to
120

C
to
260

C
(
250

F
to
500

F).

2.3.2.2
Combustion
Air
Supply
Air
for
combustion
is
supplied
to
the
burners
via
either
natural
draft
(
ND)
or
mechanical
draft
(
MD)
systems.
Natural
draft
heaters
use
ductwork
systems
to
route
air,
usually
at
ambient
conditions,
to
the
burners.
MD
heaters
use
fans
in
the
ductwork
system
to
supply
air,
usually
preheated,
to
the
burners.
The
combustion
air
supply
must
have
sufficient
pressure
to
overcome
the
burner
system
pressure
drops
caused
by
ducting,
burner
registers,
and
dampers.
The
pressure
inside
the
firebox
is
generally
a
slightly
negative
draft
of
approximately
49.8
to
125
Pascals
(
Pa)
at
the
radiant­
to­
convective
section
transition
point.
The
negative
draft
is
achieved
in
ND
systems
via
the
stack
effect
and
in
MD
systems
via
fans
or
blowers.

ND
combustion
air
supply
uses
the
stack
effect
to
induce
the
flow
of
combustion
air
in
the
heater.
The
stack
effect,
or
thermal
buoyancy,
is
caused
by
the
density
difference
between
the
hot
flue
gas
in
the
stack
and
the
significantly
cooler
ambient
air
surrounding
the
stack.
Approximately
90
percent
of
all
gas­
fired
heaters
and
76
percent
of
all
oil­
fired
heaters
use
ND
combustion
air
supply
(
EPA,
1993).

There
are
three
types
of
MD
combustion
air
supply:
forced
draft,
induced
draft,
and
balanced
draft.
The
draft
types
are
named
according
to
the
position,
relative
to
the
combustion
chamber,
of
the
fans
used
to
create
the
pressure
difference
in
the
process
heater.
All
three
types
of
MD
heaters
rely
on
the
fans
to
supply
combustion
air
and
remove
flue
gas.
In
forced
draft
combustion
air
supply
systems,
the
fan
is
located
upstream
from
the
combustion
chamber,
supplying
combustion
air
to
the
burners.
The
air
pressure
supplied
to
the
burners
in
a
forced
draft
heater
is
typically
in
the
range
of
0.747
to
2.49
kilopascals
(
kPa).
Though
combustion
air
is
supplied
to
the
burners
under
positive
pressure,
the
remainder
of
the
process
heater
operates
under
negative
pressure
caused
by
the
stack
effect.
In
induced
draft
combustion
air
systems,
the
fan
is
located
downstream
of
the
combustion
chamber,
creating
negative
pressure
inside
the
combustion
chamber.

This
negative
pressure
draws,
or
induces,
combustion
air
into
the
burner
registers.
Balanced
draft
combustion
air
systems
use
fans
placed
both
upstream
and
downstream
(
forced
and
induced
draft)
of
the
combustion
chamber.

There
are
advantages
and
disadvantages
for
both
ND
and
MD
combustion
air
supply.
One
advantage
to
natural
draft
heaters
is
that
they
do
not
require
the
fans
and
equipment
associated
with
MD
combustion
air
supply.
However,
control
over
combustion
air
flow
is
not
as
precise
in
ND
heaters
as
in
MD
heaters.
MD
heaters,
unlike
ND
heaters,
provide
the
option
of
using
alternate
sources
of
combustion
oxygen,
such
as
gas
turbine
exhaust.
They
also
allow
the
use
of
combustion
air
preheat.
Combustion
air
preheat
has
limited
application
in
ND
heaters
due
to
the
pressure
drops
associated
with
combustion
air
preheaters.

Combustion
air
preheaters
are
often
used
to
increase
the
efficiency
of
MD
process
heaters.
The
maximum
thermal
efficiency
obtainable
with
current
air
preheat
equipment
is
92
percent.
Preheaters
allow
heat
to
be
transferred
to
the
combustion
air
from
flue
gas,
steam,
condensate,
hydrocarbon,
or
other
hot
streams.
The
preheater
increases
the
efficiency
of
the
process
heater
because
some
of
the
thermal
energy
is
reclaimed
that
would
have
been
exhausted
from
the
hot
streams
via
cooling
towers.
If
the
thermal
energy
is
from
a
hot
stream
other
than
the
flue
gas,
the
entire
plant's
efficiency
is
increased.
The
benefit
of
higher
thermal
efficiency
is
that
less
fuel
is
required
to
operate
the
heater.

2.3.2.3
Tube
Configurations
The
orientation
of
the
tubes
through
which
a
process
fluid
stream
flows
is
also
taken
into
consideration
when
designing
a
process
heater.
The
tubes
in
the
convective
section
are
oriented
horizontally
in
most
process
heaters
to
allow
cross­
flow
convection.
However,
the
tubes
in
the
radiant
area
may
be
oriented
either
horizontally
or
vertically.
The
orientation
is
chosen
on
a
case­
by­
case
basis
2­
8
according
to
the
design
specifications
of
the
individual
process
heater.
For
example,
the
arbor,
or
wicket,
type
of
heater
is
a
specialty
design
to
minimize
the
pressure
drop
across
the
tubes.

2.3.2.4
Burners
Many
different
types
of
burners
are
used
in
process
heaters.
Burner
selection
depends
on
several
factors
including
process
heat
flux
requirements,
fuel
type,
and
draft
type.
The
burner
chosen
must
provide
a
radiant
heat
distribution
that
is
consistent
with
the
configuration
of
the
tubes
carrying
process
fluid.
Also,
the
number
and
location
of
the
burner(
s)
depend
on
the
process
heater
application.

Many
burner
flame
shapes
are
possible,
but
the
most
common
types
are
flat
and
conical.
Flat
flames
are
generally
used
in
applications
that
require
high
temperatures
such
as
ethylene
pyrolysis
furnaces,
although
some
ethylene
furnaces
use
conical
flames
to
achieve
uniform
heat
distribution.
Long
conical
flames
are
used
in
cases
where
a
uniform
heat
distribution
is
needed
in
the
radiant
section.

Fuel
compatibility
is
also
important
in
burner
selection.
Burners
may
be
designed
for
combustion
of
oil,
gas,
or
a
gas/
oil
mixture.
Gas­
fired
burners
are
simpler
in
operation
and
design
than
oil­
fired
burners
and
are
classified
as
either
premix
or
raw
gas
burners.
In
premix
burners,
50
to
60
percent
of
the
air
necessary
for
combustion
is
mixed
with
the
gas
prior
to
combustion
at
the
burner
tip.
This
air
is
induced
into
the
gas
stream
as
the
gas
expands
through
orifices
in
the
burner.
The
remainder
of
the
air
necessary
for
combustion
is
provided
at
the
burner
tip.
Raw
gas
burners
receive
fuel
gas
without
any
premixed
combustion
air.
Mixing
occurs
in
the
combustion
zone
at
the
burner
tip.

Oil­
fired
burners
are
classified
according
to
the
method
of
fuel
atomization
used.
Atomization
is
needed
to
increase
the
mixing
of
fuel
and
combustion
air.
Three
types
of
fuel
atomization
commonly
used
are
mechanical,
air,
and
steam.
Steam
is
the
most
widely
used
method
because
it
is
the
most
economical,
provides
the
best
flame
control,
and
can
handle
the
largest
turndown
ratios.
Typical
steam
requirements
are
0.07
to
0.16
kilogram
(
kg)
steam/
kg
of
oil.

Combination
burners
can
burn
100
percent
oil,
100
percent
gas,
or
any
combination
of
oil
and
gas.
A
burner
with
this
capability
generally
has
a
single
oil
nozzle
in
the
center
of
a
group
of
gas
nozzles.
The
air
needed
for
combustion
can
be
controlled
separately
in
this
type
of
burner.
Another
option
is
to
base
load
the
burners
with
one
fuel
and
to
add
the
other
fuel
to
meet
increases
in
load
demand.
Combination
burners
add
flexibility
to
the
process
heater,
especially
when
the
composition
of
the
fuel
is
variable.

The
location
and
number
of
burners
needed
for
a
process
heater
are
also
determined
on
an
individual
basis.
Burners
can
be
located
on
the
ceiling,
walls,
or
floor
of
the
combustion
chamber.
Floor­
and
wall­
fired
units
are
the
most
common
burner
types
found
in
process
heaters
because
they
are
both
efficient
and
flexible.
In
particular,
floor­
mounted
burners
integrate
well
with
the
use
of
combustion
air
preheat,
liquid
fuels,
and
alternate
sources
of
combustion
oxygen
such
as
turbine
exhaust.

The
number
of
burners
in
a
heater
can
range
from
1
to
over
100.
In
the
refinery
industry,
the
average
number
of
burners
is
estimated
at
24
in
ND
heaters
with
an
average
design
heat
release
of
69.4
million
Btu
per
hour
(
MMBtu/
hr).
The
average
number
of
burners
is
estimated
at
20
in
MD
heaters
with
ambient
combustion
air
and
an
average
design
heat
release
of
103.6
MMBtu/
hr.
The
average
number
of
burners
is
estimated
at
14
in
MD
heaters
with
combustion
air
preheat
and
an
average
design
heat
release
of
135.4
MMBtu/
hr.
In
general,
the
smaller
the
number
of
burners,
the
simpler
the
heater
will
be.
However,
multiple
burners
provide
a
more
uniform
temperature
distribution.
3­
9
References
U.
S.
Environmental
Protection
Agency,
Office
of
Air
Quality
Planning
and
Standards,
1993.
Alternative
Control
Techniques
Document
­
NOx
Emissions
from
Process
Heaters
(
Revised).
Research
Triangle
Park,
NC.

U.
S.
Environmental
Protection
Agency,
Office
of
Air
Quality
Planning
and
Standards,
1997.
Regulatory
Impact
Analysis
of
Air
Pollution
Regulations:
Utility
and
Industrial
Boilers.
Research
Triangle
Park,
NC.

Fleming,
Ian.
1992.
"
Just
How
Clean
is
your
Steam?
Minimizing
Risk
of
Product
Contamination
and
Prolonging
Filter
Life."
Manufacturing
Chemist
63(
10):
pp.
37­
39.

Plant
Engineering.
1991.
"
Boiler
Systems."
Plant
Engineering
45(
14):
pp.
92­
94.

Texas
Utilities
(
TXU).
2000.
"
Generating
Electricity:
Steam
Turbines."
As
obtained
in
September
2000.
Found
on
the
Internet
at
http://
www.
txu.
com/
knowledge/
energy_
lib/
generating01.
html.

CHAPTER
3
PROFILE
OF
AFFECTED
UNITS
AND
FACILITIES,
AND
COMPLIANCE
COSTS
3­
1
The
floor­
level
MACT,
which
is
the
final
industrial
boilers
and
process
heaters
rule
will
affect
existing
and
new
ICI
boilers
and
process
heaters
that
have
input
capacity
greater
than
10
million
Btus
and
are
fueled
by
fossil
and
nonfossil
fuel
solids
and
liquids.
In
addition,
two
above­
the­
floor
alternatives
were
investigated
at
proposal,
Options
1A
and
1B.
Option
1A
broadens
the
scope
of
affected
units
to
include
those
fueled
by
residual
fuel
oil
and
units
of
covered
fuel
types
with
input
capacities
less
than
10
million
Btus.
Option
1B
further
expands
the
affected
population
to
include
all
distillate
fuel
oil
and
natural
gas­
fueled
units.
Although
descriptive
statistics
on
the
Option
1B
population
are
included
in
this
section,
this
alternative
was
not
analyzed
for
this
RIA.
More
information
on
these
options
can
be
found
in
the
preamble
to
the
proposed
regulation.

The
economic
impact
estimates
presented
in
Chapter
6
and
the
small
entity
screening
analysis
presented
in
Chapter
7
are
based
on
the
estimated
stock
of
existing
units
and
the
projection
of
new
units
through
the
year
2005.
They
are
also
based
on
the
compliance
costs
associated
with
the
applying
a
regulatory
alternative
to
these
units.
This
chapter
begins
with
a
review
of
the
industry
distribution
and
technical
characteristics
of
existing
boilers
and
process
heaters
contained
in
the
Agency's
Inventory
Database.
It
also
presents
projected
growth
estimates
for
boilers
and
process
heaters
through
the
year
2005,
a
description
of
how
costs
are
estimated,
and
the
national
engineering
cost
estimates
and
costeffectiveness
(
cost/
ton)
estimates
by
pollutant
controlled.

3.1
Profile
of
Existing
Boiler
and
Process
Heaters
Units
This
section
profiles
existing
boilers
and
process
heaters,
collectively
referred
to
as
"
units,"
with
respect
to
business
applications,
industry
of
parent
company,
and
fuel
use.
The
unit
population
database
in
combination
with
the
model
units
that
helped
in
preparing
that
database
were
used
to
determine
which
types
of
boilers,
fuel,
and
control
devices
were
in
the
existing
unit
population
so
that
corresponding
emission
factors
could
be
developed
for
all
combinations.
The
development
of
the
population
database
and
the
model
units
are
discussed
in
the
memoranda,
"
Development
of
the
Population
Database
for
the
Industrial,
Commercial,
and
Institutional
Boiler
and
Process
Heater
National
Emission
Standard
for
Hazardous
Air
Pollutants
(
NESHAP)"
and
"
Development
of
the
Model
Units
for
the
Industrial,
Commercial,
and
Institutional
Boiler
and
Process
Heater
National
Emission
Standard
for
Hazardous
Air
Pollutants
(
NESHAP)."
The
units
contained
in
the
Inventory
Database
are
based
on
information
from
the
Aerometric
Information
Retrieval
System
(
AIRS)
and
Ozone
Transport
Assessment
Group
(
OTAG)
databases,
state
and
local
permit
records,
and
the
combustion
source
Information
Collection
Request
(
ICR)
conducted
by
the
Agency
in
1997.
The
list
of
units
contained
in
the
Inventory
Database
was
reviewed
and
updated
by
industry
and
environmental
stakeholders
as
part
of
the
Industrial
Combustion
Coordinated
Rulemaking
(
ICCR),
chartered
under
the
Federal
Advisory
Committee
Act
(
FACA).

The
entire
Inventory
Database
contains
more
than
58,000
ICI
boilers
and
process
heaters;
however,
only
about
4,000
are
estimated
to
be
affected
by
the
floor
alternative.
Of
these
existing
units,
a
little
over
half
had
sufficient
information
on
operating
parameters
to
be
included
in
the
floor­
level
EIA.
The
number
of
potentially
affected
units
included
in
the
profile
for
the
floor
alternative
was
2,186.
The
number
of
units
included
in
the
profile
was
3,580
for
Option
1A
and
22,117
for
Option
1B.

3.1.1
Distribution
of
Existing
Boilers
and
Facilities
by
Industry
Tables
3­
1
through
3­
3
present
the
number
of
existing
boilers
and
process
heaters
and
the
number
of
facilities
owning
units
by
two­
digit
SIC
code
and
three­
digit
NAICS
code
that
may
be
affected
by
the
floor
or
above­
the­
floor
alternatives.
For
the
floor
alternative,
the
industries
with
the
largest
number
of
potentially
affected
units
are
the
furniture,
paper,
lumber,
and
electrical
services
industries.
These
four
industries
alone
account
for
nearly
60
percent
of
affected
units.
Almost
all
the
process
heaters
are
in
the
lumber
industry.
(
Chapter
4
presents
industry
profiles
for
the
lumber
and
wood
products,
electrical
services,
and
paper
industries,
among
others.)
The
remaining
units
are
primarily
distributed
across
the
manufacturing
sector
and
service
industries.
The
distribution
of
units
affected
by
the
Option
1A
alternative
is
similar
to
that
for
the
floor
alternative,
although
both
the
number
of
units
and
the
number
of
facilities
is
greater
for
the
Option
1A
alternative.
For
Option
1B,
the
industries
with
the
greatest
number
of
units
shifts
to
oil
and
gas
exploration,
chemical
and
transportation
equipment
manufacturing,
and
petroleum
refining.

3.1.2
Technical
Characteristics
of
Existing
Boilers
3­
2
Figure
3­
1
characterizes
the
population
of
2,186
(
3,580;
22,117)
units
identified
in
the
Inventory
Database
by
capacity
range,
fuel
type,
and
level
of
preexisting
control
for
each
alternative.
Throughout
most
of
this
section,
the
values
in
the
text
are
for
the
MACT
floor
alternative.
Those
for
the
above­
the­
floor
alternatives
follow
in
parentheses,
first
for
Option
1A
then
for
Option
1B.
3­
3
Table
3­
1.
Units
and
Facilities
Affected
by
the
Floor
Alternative
by
Industrya
SIC
Code
NAICS
Code
Description
Boilers
Heaters
Total
Units
Facilities
01
111
Agriculture
 
Crops
3
0
3
3
02
112
Agriculture
 
Livestock
0
0
0
0
07
115
Agricultural
Services
0
0
0
0
10
212
Metal
Mining
9
0
9
4
12
212
Coal
Mining
2
0
2
1
13
211
Oil
and
Gas
Extraction
0
0
0
0
14
212
Mining/
Quarrying
 
Nonmetallic
Minerals
8
0
8
4
17
235
Construction
 
Special
Trade
Contractors
0
0
0
0
20
311
Food
and
Kindred
Products
138
0
138
60
21
312
Tobacco
Products
11
0
11
7
22
313
Textile
Mill
Products
135
0
135
71
23
315
Apparel
and
Other
Products
from
Fabrics
2
0
2
2
24
321
Lumber
and
Wood
Products
335
25
360
262
25
337
Furniture
and
Fixtures
234
0
234
154
26
322
Paper
and
Allied
Products
321
0
321
194
27
511
Printing,
Publishing,
and
Related
Industries
0
0
0
0
28
325
Chemicals
and
Allied
Products
171
3
174
70
29
324
Petroleum
Refining
and
Related
Industries
11
0
11
8
30
326
Rubber
and
Miscellaneous
Plastics
Products
17
0
17
13
31
316
Leather
and
Leather
Products
1
0
1
1
32
327
Stone,
Clay,
Glass,
and
Concrete
Products
9
0
9
7
33
331
Primary
Metal
Industries
41
0
41
16
34
332
Fabricated
Metal
Products
16
0
16
10
35
333
Industrial
Machinery
and
Computer
Equipment
23
0
23
12
36
335
Electronic
and
Electrical
Equipment
5
0
5
5
37
336
Transportation
Equipment
102
0
102
41
38
334
Scientific,
Optical,
and
Photographic
Equip.
8
0
8
4
39
339
Miscellaneous
Manufacturing
Industries
2
0
2
2
40
482
Railroad
Transportation
4
0
4
1
42
484
Motor
Freight
and
Warehousing
5
0
5
1
46
486
Pipelines,
Except
Natural
Gas
0
0
0
0
(
continued)
3­
4
Table
3­
1.
Units
and
Facilities
Affected
by
the
Floor
Alternative
by
Industrya
(
continued)

SIC
Code
NAICS
Code
Description
Boilers
Heaters
Total
Units
Facilities
49
221
Electric,
Gas,
and
Sanitary
Services
318
0
318
160
50
421
Wholesale
Trade
 
Durable
Goods
3
0
3
2
51
422
Wholesale
Trade
 
Nondurable
Goods
2
0
2
1
55
441
Automotive
Dealers
and
Gasoline
Service
Stations
0
0
0
0
58
722
Eating
and
Drinking
Places
0
0
0
0
60
522
Depository
Institutions
0
0
0
0
59
445
 
454
Miscellaneous
Retail
0
0
0
0
70
721
Hotels
and
Other
Lodging
Places
1
0
1
1
72
812
Personal
Services
0
0
0
0
76
811
Miscellaneous
Repair
Services
2
0
2
1
80
621
Health
Services
37
0
37
18
81
541
Legal
Services
0
0
0
0
82
611
Educational
Services
105
0
105
45
83
624
Social
Services
2
0
2
1
86
813
Membership
Organizations
0
0
0
0
87
541
Engineering,
Accounting,
Research,
Management
and
Related
Services
2
0
2
2
89
711/
514
Services,
N.
E.
C.
2
0
2
1
91
921
Executive,
Legislative,
and
General
Administration
1
0
1
1
92
922
Justice,
Public
Order,
and
Safety
29
0
29
9
94
923
Administration
of
Human
Resources
1
0
1
1
96
926
Administration
of
Economic
Programs
4
0
4
3
97
928
National
Security
and
International
Affairs
29
0
29
11
NA
SIC
Information
Not
Available
7
0
7
4
2,158
28
2,186
1,214
a
Based
on
the
Inventory
Database.
3­
5
Table
3­
2.
Units
and
Facilities
Affected
by
the
Option
1A
Alternative
by
Industrya
SIC
Code
NAICS
Code
Description
Boilers
Heaters
Total
Units
Facilities
01
111
Agriculture
 
Crops
6
0
6
6
02
112
Agriculture
 
Livestock
0
0
0
0
07
115
Agricultural
Services
0
0
0
0
10
212
Metal
Mining
10
1
11
5
12
212
Coal
Mining
2
0
2
1
13
211
Oil
and
Gas
Extraction
8
10
18
4
14
212
Mining/
Quarrying
 
Nonmetallic
Minerals
10
0
10
5
17
235
Construction
 
Special
Trade
Contractors
2
0
2
1
20
311
Food
and
Kindred
Products
163
0
163
72
21
312
Tobacco
Products
22
0
22
11
22
313
Textile
Mill
Products
247
3
250
134
23
315
Apparel
and
Other
Products
from
Fabrics
4
0
4
4
24
321
Lumber
and
Wood
Products
434
28
462
337
25
337
Furniture
and
Fixtures
310
0
310
209
26
322
Paper
and
Allied
Products
503
0
503
272
27
511
Printing,
Publishing,
and
Related
Industries
8
0
8
6
28
325
Chemicals
and
Allied
Products
332
101
433
163
29
324
Petroleum
Refining
and
Related
Industries
54
108
162
50
30
326
Rubber
and
Miscellaneous
Plastics
Products
56
0
56
37
31
316
Leather
and
Leather
Products
22
0
22
12
32
327
Stone,
Clay,
Glass,
and
Concrete
Products
40
2
42
25
33
331
Primary
Metal
Industries
83
2
85
33
34
332
Fabricated
Metal
Products
44
0
44
28
35
333
Industrial
Machinery
and
Computer
Equipment
46
0
46
25
36
335
Electronic
and
Electrical
Equipment
45
0
45
29
37
336
Transportation
Equipment
158
0
158
61
38
334
Scientific,
Optical,
and
Photographic
Equip.
33
0
33
16
39
339
Miscellaneous
Manufacturing
Industries
14
0
14
10
40
482
Railroad
Transportation
4
0
4
1
42
484
Motor
Freight
and
Warehousing
5
2
7
3
46
486
Pipelines,
Except
Natural
Gas
3
3
6
5
(
continued)
3­
6
Table
3­
2.
Units
and
Facilities
Affected
by
the
Option
1A
Alternative
by
Industrya
(
continued)

SIC
Code
NAICS
Code
Description
Boilers
Heaters
Total
Units
Facilities
49
221
Electric,
Gas,
and
Sanitary
Services
371
1
372
185
50
421
Wholesale
Trade
 
Durable
Goods
3
0
3
2
51
422
Wholesale
Trade
 
Nondurable
Goods
2
0
2
1
55
441
Automotive
Dealers
and
Gasoline
Service
Stations
0
1
1
1
58
722
Eating
and
Drinking
Places
0
0
0
0
60
522
Depository
Institutions
0
0
0
0
59
445
 
454
Miscellaneous
Retail
1
0
1
1
70
721
Hotels
and
Other
Lodging
Places
1
0
1
1
72
812
Personal
Services
0
0
0
0
76
811
Miscellaneous
Repair
Services
2
0
2
1
80
621
Health
Services
40
0
40
19
81
541
Legal
Services
0
0
0
0
82
611
Educational
Services
114
0
114
50
83
624
Social
Services
3
0
3
2
86
813
Membership
Organizations
0
0
0
0
87
541
Engineering,
Accounting,
Research,
Management
and
Related
Services
6
0
6
5
89
711/
514
Services,
N.
E.
C.
2
0
2
1
91
921
Executive,
Legislative,
and
General
Administration
2
0
2
2
92
922
Justice,
Public
Order,
and
Safety
33
0
33
10
94
923
Administration
of
Human
Resources
1
0
1
1
96
926
Administration
of
Economic
Programs
4
0
4
3
97
928
National
Security
and
International
Affairs
41
0
41
13
NA
SIC
Information
Not
Available
24
0
24
18
3,318
262
3,580
1,881
a
Based
on
the
Inventory
Database.
3­
7
Table
3­
3.
Units
and
Facilities
Affected
by
the
Option
1B
Alternative
by
Industrya
SIC
Code
NAICS
Code
Description
Boilers
Heaters
Total
Units
Facilities
01
111
Agriculture
 
Crops
7
0
7
6
02
112
Agriculture
 
Livestock
6
0
6
1
07
115
Agricultural
Services
3
0
3
1
10
212
Metal
Mining
55
6
61
20
12
212
Coal
Mining
20
6
26
5
13
211
Oil
and
Gas
Extraction
497
657
1,154
371
14
212
Mining/
Quarrying
 
Nonmetallic
Minerals
48
1
49
19
17
235
Construction
 
Special
Trade
Contractors
2
0
2
1
20
311
Food
and
Kindred
Products
441
3
444
145
21
312
Tobacco
Products
69
0
69
30
22
313
Textile
Mill
Products
755
6
761
347
23
315
Apparel
and
Other
Products
from
Fabrics
4
0
4
4
24
321
Lumber
and
Wood
Products
561
40
601
412
25
337
Furniture
and
Fixtures
499
10
509
297
26
322
Paper
and
Allied
Products
981
0
981
493
27
511
Printing,
Publishing,
and
Related
Industries
333
3
336
134
28
325
Chemicals
and
Allied
Products
2,265
415
2,680
913
29
324
Petroleum
Refining
and
Related
Industries
322
729
1,051
184
30
326
Rubber
and
Miscellaneous
Plastics
Products
508
36
544
268
31
316
Leather
and
Leather
Products
91
2
93
44
32
327
Stone,
Clay,
Glass,
and
Concrete
Products
423
13
436
184
33
331
Primary
Metal
Industries
754
197
951
314
34
332
Fabricated
Metal
Products
771
102
873
388
35
333
Industrial
Machinery
and
Computer
Equipment
402
19
421
191
36
335
Electronic
and
Electrical
Equipment
430
13
443
203
37
336
Transportation
Equipment
803
207
1,010
291
38
334
Scientific,
Optical,
and
Photographic
Equip.
180
2
182
71
39
339
Miscellaneous
Manufacturing
Industries
123
36
159
65
40
482
Railroad
Transportation
4
0
4
1
42
484
Motor
Freight
and
Warehousing
5
2
7
3
46
486
Pipelines,
Except
Natural
Gas
8
3
11
7
(
continued)
3­
8
Table
3­
3.
Units
and
Facilities
Affected
by
the
Option
1B
Alternative
by
Industrya
(
continued)

SIC
Code
NAICS
Code
Description
Boilers
Heaters
Total
Units
Facilities
49
221
Electric,
Gas,
and
Sanitary
Services
1,227
140
1,367
615
50
421
Wholesale
Trade
 
Durable
Goods
4
0
4
2
51
422
Wholesale
Trade
 
Nondurable
Goods
2
0
2
1
55
441
Automotive
Dealers
and
Gasoline
Service
Stations
0
2
2
2
58
722
Eating
and
Drinking
Places
0
3
3
1
60
522
Depository
Institutions
3
0
3
1
59
445
 
454
Miscellaneous
Retail
1
0
1
1
70
721
Hotels
and
Other
Lodging
Places
3
0
3
2
72
812
Personal
Services
2
0
2
1
76
811
Miscellaneous
Repair
Services
58
0
58
28
80
621
Health
Services
27
0
27
25
81
541
Legal
Services
2
0
2
0
82
611
Educational
Services
144
0
144
57
83
624
Social
Services
4
0
4
2
86
813
Membership
Organizations
1
0
1
1
87
541
Engineering,
Accounting,
Research,
Management
and
Related
Services
6
0
6
5
89
711/
514
Services,
N.
E.
C.
2
0
2
1
91
921
Executive,
Legislative,
and
General
Administration
7
0
7
5
92
922
Justice,
Public
Order,
and
Safety
36
0
36
10
94
923
Administration
of
Human
Resources
2
0
2
2
96
926
Administration
of
Economic
Programs
11
0
11
5
97
928
National
Security
and
International
Affairs
51
3
54
15
NA
SIC
Information
Not
Available
6,163
335
6,498
2,378
19,126
2,991
22,117
8,573
a
Based
on
the
Inventory
Database.
3­
9
Input
Capacity
(
million
Btu)
Preexisting
Control
Technology
Fuel
Type
Coal
31%

Coal
and
Wood
5%
Wood
18%
Other
3%
Other
Biomass
9%
Bagasse
2%
>
250
23%
10
to
100
52%

100
to
250
25%

Input
Capacity
(
million
Btu)
Preexisting
Control
Technology
Fuel
Type
Cyclone
36%
No
Control
13%
Wet
Scrubber
12%
Fabric
Filter
16%
ESP
23%
Coal
49%

Coal
and
Wood
7%
Wood
22%
Other
4%
Other
Biomass
14%
Bagasse
4%

Input
Capacity
(
million
Btu)
Preexisting
Control
Technology
Fuel
Type
Cyclone
5%

No
Control
88%
Wet
Scrubber
2%
Fabric
Filter
3%
ESP
3%

Coal
5%

Natural
Gas
78%
Distillate
Fuel
Oil
6%
Residual
Fuel
Oil
5%
Wood,
Bagasse,
and
Other
6%
0
to
10
1%
Floor
Alternative
(
n=
2,186)

Option
1A
Alternative
(
n=
3,580)

>
250
16%
10
to
100
51%

100
to
250
20%
0
to
10
13%

Cyclone
26%

No
Control
41%
Wet
Scrubber
8%
Fabric
Filter
10%
ESP
15%
Residual
Fuel
Oil
32%

Option
1B
Alternative
(
n=
22,117)

>
250
5%

10
to
100
36%
100
to
250
7%
0
to
10
52%

Figure
3­
1.
Characteristics
of
Units
Affected
by
Alternatives
3­
10
3.1.2.1
Floor
Alternative

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

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

Control
Level:
Eighty­
three
percent
of
units
have
some
type
of
control
device
already
installed;
289
do
not.
Typical
control
devices
include
fabric
filters,
wet
scrubbers,
and
electrostatic
precipitators.

3.1.2.2
Option
1A
Alternative

Capacity
Range:
About
half
of
the
3,580
units
affected
by
this
alternative
have
input
capacities
between
10
and
100
MMBtu/
hr.
Twenty
percent
have
capacities
between
100
and
250,
16
percent
have
capacities
greater
than
250,
and
13
percent
have
capacities
less
than
10
MMBtu/
hr.

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

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

3.1.2.3
Option
1B
Alternative

Capacity
Range:
More
than
half
of
the
22,117
units
affected
by
the
Option
1B
alternative
have
input
capacities
less
than
10
MMBtu/
hr.
Thirty­
six
percent
have
input
capacities
between
10
and
100
MMBtu/
hr.
The
remaining
12
percent
have
input
capacities
in
excess
of
100
MMBtu/
hr.

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

Control
Level:
Eighty­
eight
percent
of
the
affected
units
have
no
preexisting
control
equipment.

3.2
Methodology
for
Estimating
Cost
Impacts
The
predominant
type
of
control
measure
that
is
considered
in
the
analysis
of
emission
reductions
needed
for
sources
to
achieve
the
MACT
floor,
which
is
the
proposed
alternative,
as
well
as
other
alternatives,
are
add­
on
control
technologies.
Add­
on
control
techniques
are
those
technologies
that
are
applied
to
the
vent
gas
stream
of
the
boiler
or
process
heater
to
reduce
emissions.
The
boiler
and
process
heaters
population
database
includes
information
on
all
control
techniques
that
are
applied
to
industrial,
commercial,
institutional
boilers
and
process
heaters.
Generally,
they
can
be
grouped
into
PM
control
or
acid
gas
control.
The
most
common
technologies,
and
the
ones
analyzed
for
the
impacts
analysis,
include
fabric
filters,
ESP's,
packed
scrubbers,
venturi
scrubbers,
and
spray
dryers.
In
addition,
when
add­
on
technologies
are
used,
the
cost
of
ductwork
and
associated
equipment
also
needed
to
be
considered.
3­
11
Components
of
capital
cost
include:

S
purchased
equipment
cost
of
the
primary
device
and
auxiliary
equipment,

S
instrumentation,

S
sales
tax
and
freight,
and
S
installation
costs.
Installation
costs
include
foundations
and
support,
handling
and
erection,
electrical,
piping,
insulation,
and
painting,
engineering,
construction
and
field
expenses,
contractor
fees,
start­
up,
performance
tests,
and
contingencies.

Components
of
annual
cost
include:

S
raw
materials,

S
utilities
(
electricity,
fuel,
steam,
air,
water),

S
waste
treatment
and
disposal,

S
labor
(
operating,
supervisory,
maintenance),

S
maintenance
materials,

S
replacement
parts,

S
overhead,

S
property
taxes,

S
insurance,

S
administration
charges,
and
S
capital
recovery
costs.

For
this
analysis,
costs
were
estimated
in
1999
dollars.
Capital
recovery
was
calculated
assuming
7
percent
interest
rate
over
the
life
of
the
equipment.
The
use
of
this
interest
rate
is
based
on
Office
of
Management
and
Budget
(
OMB)
guidance
(
Circular
A­
94,
October
29,
1992).

The
algorithms
used
to
estimate
these
costs
were
obtained
from
previous
EPA
studies.
These
cost
algorithms
are
included
as
appendicies
to
the
cost
methodology
memorandum
in
the
public
docket.
Inputs
for
the
algorithms
used
in
the
impacts
analysis
are
also
presented
in
this
memorandum.

Fabric
filter
The
algorithms
used
to
estimate
capital
and
annual
costs
of
fabric
filters
were
obtained
from
EPA's
EPA
Air
Pollution
Control
Cost
Manual.
Algorithms
were
provided
for
4
types
of
fabric
filters:
shaker,
reversed
air,
pulse­
jet
modular,
and
pulse­
jet
common.
The
cost
algorithms
for
estimating
capital
costs
reduced
to
basic
equations
for
each
are
provided
in
Appendix
A­
1
of
the
cost
methodology
memorandum
(
henceforth
called
the
"
cost
memo").
Capital
costs
are
based
on
the
gross
cloth
area
of
the
fabric
filter,
which
is
a
function
of
the
gas
inlet
flow
rate.
Algorithms
for
calculating
annual
costs
are
provided
in
Appendix
A­
2
of
the
cost
memo.
Annual
costs
include
dust
disposal,
electricity,
maintenance,
labor,
bag
replacement,
maintenance
labor,
compressed
air,
overhead,
administrative,
property
taxes,
and
insurance.
Capital
recovery
is
annualized
over
20
years
at
7
percent
interest.
Appendix
A­
3
of
the
cost
memo
presents
the
values
for
the
inputs
used
in
this
analysis
and
the
reasons
for
their
use.

Electrostatic
Precipitator
The
algorithms
used
to
estimate
capital
and
annual
costs
of
ESPs
were
obtained
from
EPA's
Air
Pollution
Control
Cost
Manual.
Capital
costs
are
based
on
the
total
collection
plate
area,
which
is
calculated
from
the
gas
inlet
flow
rate
and
the
required
removal
efficiency.
The
cost
algorithms
for
estimating
capital
costs
of
ESPs
reduced
to
basic
equations
are
provided
in
Appendix
B­
1
of
the
cost
3­
12
memo.
Algorithms
for
calculating
annual
costs
are
provided
in
Appendix
B­
2
of
the
cost
memo.
Annual
costs
include
dust
disposal,
electricity,
maintenance,
labor,
maintenance
labor,
overhead,
administrative,
property
taxes,
and
insurance.
Capital
recovery
is
annualized
at
7
percent
interest.
Appendix
B­
3
of
the
cost
memo
presents
the
values
for
the
inputs
used
in
this
analysis
and
the
reasons
for
their
use.

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

Packed
Bed
Scrubber
The
algorithms
used
to
estimate
capital
and
annual
costs
of
packed
bed
scrubbers
were
obtained
from
EPA's
Air
Pollution
Control
Cost
Manual.
The
capital
costs
are
comprised
of
the
scrubber
tower,
packing,
pumps,
and
fans.
Capital
costs
are
based
primarily
on
gas
flow
rate
and
removal
efficiency.
The
cost
algorithms
for
estimating
capital
costs
of
packed
scrubber
equipment
reduced
to
their
basic
equations
for
each
are
provided
in
Appendix
D­
1
of
the
cost
memo.
The
cost
algorithms
for
estimating
annual
costs
of
packed
scrubbers
are
provided
in
Appendix
D­
2
of
the
cost
memo.
Annual
costs
include
caustic,
wastewater
disposal,
water,
electricity,
maintenance,
labor,
overhead,
administrative,
property
taxes,
and
insurance.
Capital
recovery
is
an
annualized
cost
estimated
using
a
7
percent
interest
rate.
Appendix
D­
3
of
the
cost
memo
presents
the
values
for
the
inputs
used
in
this
analysis
and
the
reasons
for
their
use.

Spray
Dryer
The
algorithms
used
to
estimate
capital
and
annual
costs
of
spray
dryers
were
obtained
from
previous
EPA
studies.
Capital
costs
include
the
cost
of
the
spray
dryer
and
pumps.
Capital
costs
are
based
on
the
gas
flow
rate.
The
cost
algorithms
for
estimating
capital
costs
of
spray
dryer
equipment
reduced
to
basic
equations
are
provided
in
Appendix
E­
1
of
the
cost
memo.
The
cost
algorithms
for
estimating
annual
costs
for
spray
dryers
are
provided
in
Appendix
E­
2
of
the
cost
memo.
Annual
costs
include
lime,
water,
electricity,
maintenance,
labor,
maintenance
labor,
overhead,
administrative,
property
taxes,
and
insurance.
Capital
recovery
is
an
annualized
cost
estimated
using
a
7
percent
interest
rate.
Appendix
E­
3
of
the
cost
memo
presents
the
values
for
the
inputs
used
in
this
analysis
and
the
reasons
for
their
use.

Ductwork
The
algorithms
used
to
estimate
capital
and
annual
costs
of
ductwork
were
obtained
from
EPA's
Air
Pollution
Control
Cost
Manual.
Capital
costs
include
500
feet
of
ductwork,
elbows,
and
fans.
The
500
feet
of
ductwork
was
based
on
engineering
judgement
and
previous
experience
on
the
distance
between
emission
points
and
control
devices
in
chemical
facilities
and
the
availability
of
space
for
retrofitting
controls.
Costs
are
based
on
ductwork
diameter,
which
is
calculated
from
the
gas
flow
rate.
The
cost
algorithms
for
estimating
capital
costs
and
annual
costs
reduced
to
basic
equations
are
provided
in
Appendix
F­
1
of
the
cost
memo.
Annual
costs
include
electricity,
maintenance,
maintenance
labor,
overhead,
administrative,
property
taxes,
and
insurance.
Capital
recovery
is
an
annualized
cost
estimated
using
a
7
percent
interest
rate.
Required
inputs
to
the
ductwork
algorithms
are
provided
in
the
input
tables
provided
in
Appendices
A­
3,
B­
3,
C­
3,
D­
3,
and
E­
3
of
the
cost
memo.
5
The
monitoring
costs
reported
for
existing
units
are
not
the
cost
of
continuous
emission
monitors
(
CEM),
but
the
costs
associated
with
monitoring
the
process
parameters
of
the
control
device.
Installation
of
these
process
monitors
are
integral
to
the
control
device
and
would
be
installed
with
or
without
the
monitoring
requirements
of
the
MACT.
Therefore,
even
though
we
present
these
monitoring
costs
separately,
they
are
included
in
the
overall
reported
control
costs
and
should
not
be
considered
as
an
additional
cost
for
emission
monitoring.

3­
13
Good
Combustion
Practices
Few
sources
in
the
population
database
specifically
reported
using
good
combustion
practices.
Boilers
and
process
heaters
within
each
subcategory
might
use
any
of
a
wide
variety
of
different
work
practices,
depending
on
the
characteristics
of
the
individual
unit.

Consequently,
any
uniform
requirements
or
set
of
work
practices
that
would
meaningfully
reflect
the
use
of
good
combustion
practices,
or
that
could
be
meaningfully
implemented
across
any
subcategory
of
boilers
and
process
heaters
could
not
be
identified.

Additionally,
few
of
the
GCP's
have
been
documented
to
reduce
organic
HAP
emissions,
and
they
could
not
be
considered
in
the
MACT
analysis.
One
GCP
that
may
effect
organic
HAP
emissions
is
maintaining
CO
emission
levels.
CO
is
generally
an
indicator
of
incomplete
combustion
because
CO
will
burn
to
carbon
dioxide
if
adequate
oxygen
is
available.
Controlling
CO
emissions
is
a
mechanism
for
ensuring
combustion
efficiency,
and
therefore
may
be
viewed
as
a
kind
of
GCP.

Capital
and
annual
costs
for
CO
monitoring
is
presented
in
Appendix
G
of
the
cost
memo.
The
costing
information
was
obtained
from
a
previous
EPA
study.
Capital
costs
are
comprised
of
the
initial
cost
of
the
equipment.
Annual
costs
include
operating
and
maintenance
costs,
annual
and
quarterly
checks,
recordkeeping
and
reporting,
taxes,
insurance,
and
administrative
costs.
Annualized
costs
such
as
capital
recovery
costs
are
calculated
assuming
an
equipment
life
of
20
years
and
an
interest
rate
of
7
percent.

Testing
and
Monitoring
Costs
The
rule
includes
emission
limits
for
HCl,
PM,
metallic
HAP,
and
mercury.
Additionally,
as
mentioned
in
Chapter
1
of
this
RIA
and
the
preamble,
the
rule
allows
sources
to
meet
requirements
by
monitoring
fuel
content
instead
of
emissions.
Consequently,
testing
and
monitoring
costs
of
meeting
the
standards
were
incorporated
into
the
cost
estimates.
Capital
costs
for
testing
include
initial
stack
tests
for
PM,
HCl,
and
metals
for
fossil
fuels,
and
materials
and
fuel
analysis
for
biomass.
Capital
cost
components
include
operation
and
maintenance
costs
and
capital
recovery
assuming
the
initial
capital
investment
is
annualized
over
a
5
year
period
at
7
percent
interest.
Monitoring
costs
are
included
for
opacity
monitoring,
HCl
monitoring,
and
scrubber
parametric
monitoring.
5
Monitoring
costs
include
the
capital
cost
of
monitoring
equipment,
and
the
annual
costs
of
capital
recovery
assuming
the
initial
capital
investment
is
annualized
over
a
20
year
period
at
7
percent
interest.
Annual
monitoring
costs
also
include
operation
and
maintenance
as
well
as
other
additional
costs.
The
testing
and
monitoring
costs
are
shown
in
Table
3­
4.
Appendix
G
of
the
cost
memo
includes
further
details
on
these
costs.
Information
used
to
estimate
testing
and
monitoring
costs
were
obtained
from
previous
EPA
studies.

Table
3­
4.
Testing
and
Monitoring
Costs
for
Units
Covered
by
the
Proposed
Rule
3­
14
Material
or
Fuel
No.
of
Industrial
Boilers
No.
of
Process
Heaters
Total
Capital
Investment
of
Testing
and
Monitoring
($)
Total
Annual
Costs
of
Testing
($)
Total
Annual
Costs
of
Monitoring
($)
Annual
Capital
Recovery
­
Testing
and
Monitoring
(
1999$)
Total
Annual
Costs
of
Testing
and
Monitoring
(
1999$)

Regular
Use
Units
Coal
2,328
0
151,169,238
63,608,655
59,828,340
8,265,169
123,436,995
Coal/
Wood/
NFFa
Liquid/
NFF
Solid
169
0
8,847,579
2,444,456
1,302,784
280,698
3,747,240
Gas
30,473
13,481
0
0
0
0
0
Gas/
Wood/
Other
Biomass/
Liquid
FF
201
0
9,831,749
2,909,994
2,327,840
447,120
5,237,834
Distillate
Liquid
FF
2,921
353
0
0
0
0
0
NFF
Liquid/
NFF
Solid/
Gas
115
11
7,452,131
3,074,918
2,930,348
404,077
6,005,266
Wood
663
42
26,446,200
5,268,614
6,392,240
1,411,706
11,660,854
Wood/
Other
Biomass/
NFF
Liquid/
NFF
Solid
147
0
8,180,852
3,003,146
2,001,492
299,112
5,004,638
Residual
Liquid
FF
2,036
674
0
0
0
0
0
Bagasse/
Other
132
0
5,821,106
490,000
2,891,728
412,546
3,381,728
Total
for
Regular
Use
Units
39,185
14,561
217,748,855
80,799,783
77,674,772
11,520,428
158,114,555
Limited
Use
Units
Coal
198
0
6,427,715
1,584,000
1,716,416
457,169
3,330,416
Coal/
Wood/
NFF
Liquid/
NFF
Solid
4
0
119,600
32,000
29,772
8,268
61,772
Gas
2,314
624
0
0
0
0
0
Gas/
Wood/
Other
Biomass/
Liquid
FF
8
0
290,366
64,000
105,020
21,366
169,020
Distillate
Liquid
FF
672
31
0
0
0
0
0
NFF
Liquid/
NFF
Solid/
Gas
4
1
156,800
40,000
39,696
11,024
79,696
Wood
28
0
1,074,549
224,000
331,200
80,279
555,200
Wood/
Other
Biomass/
NFF
Liquid/
NFF
Solid
6
0
194,000
48,000
49,620
13,780
97,620
Residual
Liquid
FF
533
31
0
0
0
0
0
Material
or
Fuel
No.
of
Industrial
Boilers
No.
of
Process
Heaters
Total
Capital
Investment
of
Testing
and
Monitoring
($)
Total
Annual
Costs
of
Testing
($)
Total
Annual
Costs
of
Monitoring
($)
Annual
Capital
Recovery
­
Testing
and
Monitoring
(
1999$)
Total
Annual
Costs
of
Testing
and
Monitoring
(
1999$)

3­
15
Total
for
Limited
Use
Units
3,767
687
8,263,030
1,992,000
2,271,724
591,886
4,263,724
Grand
Total
42,952
15,248
226,011,885
82,791,783
79,946,496
12,112,314
162,738,279
a
NFF
=
costs
for
units
that
are
not
fossil
fueled;
FF
=
units
that
are
fossil
fueled.

Costs
to
Control
Non­
Air
Effects
Related
to
Rule
Implementation
The
EPA
estimated
the
additional
water
usage
that
would
result
from
the
MACT
floor
level
of
control
to
be
110
million
gallons
per
year
for
existing
sources
and
0.6
million
gallons
per
year
for
new
sources.
In
addition
to
the
increased
water
usage,
an
additional
3.7
million
gallons
per
year
of
wastewater
would
be
produced
for
existing
sources
and
0.6
million
gallons
per
year
for
new
sources.
The
EPA
estimated
the
additional
solid
waste
that
would
result
from
the
MACT
floor
level
of
control
to
be
102,000
tons
per
year
for
existing
sources
and
1
ton
per
year
for
new
sources.
The
costs
($
900,000)
of
handling
the
additional
solid
waste
generated
from
applying
MACT
floor
technology
are
accounted
for
in
the
control
cost
estimates
for
ESP
and
fabric
filter
applications.
The
costs
($
20,000)
of
treating
wastewater
from
venturi
and
packed
bed
scrubber
are
also
accounted
for
in
the
control
cost
estimates.

Cost
Uncertainties
The
primary
limitation
to
the
cost
estimates
developed
for
the
proposed
rule
is
that
costs
were
calculated
for
model
units
rather
than
each
individual
boiler
or
process
heater.
Consequently,
the
costs
do
not
characterize
any
"
real"
unit.
This
was
done
for
practical
reasons.
Because
there
are
over
60,000
units
in
the
U.
S.,
it
would
not
be
possible
to
gather
unit­
specific
information
for
each
unit
necessary
for
estimating
costs,
such
as
flue
gas
temperatures
and
flow
rates.
Additionally,
emission
information
was
only
available
for
less
than
1
percent
of
the
units.
In
order
to
estimate
costs
and
emission
reductions
of
the
proposed
rule,
model
units
were
developed
to
represent
the
population
of
boilers
and
process
heaters
in
the
U.
S.
While
sufficient
information
was
not
available
for
characterizing
each
unit,
sufficient
emissions
and
process
information
were
available
to
develop
model
units.
Each
unit
in
the
U.
S.
was
then
assigned
to
a
model
based
on
their
size
and
fuel
burned.
It
also
should
be
noted
that
the
costing
methodology
is
the
cost
algorithms
for
the
control
devices
provide
a
cost
range
of
+/­
30
percent.
This
aspect
of
the
costing
methodology
reflects
the
degree
of
variability
typically
found
in
study­
level
cost
estimates.
This
is
also
the
degree
of
variability
found
in
the
cost
methodology
employed
in
the
EPA
Air
Pollution
Control
Cost
Manual,
which
is
an
important
reference
for
the
cost
estimates
supplied
in
the
RIA.
Cost
information
available
to
owners
and
operators
of
boilers
and
process
heaters
will
be
more
specific
and
accurate.
Consequently,
the
cost
estimates
may
overestimate
or
underestimate
costs.

3.3
Projection
of
New
Boilers
and
Process
Heaters
Energy
Information
Administration
fuel
consumption
forecasts
were
used
in
conjunction
with
existing
model
boiler
population
data
to
project
the
number
and
type
of
new
boilers
to
be
installed
by
2005.
EPA
used
the
following
steps
to
calculate
new
boiler
population
estimates:

1.
Calculate
the
percentage
change
in
industrial
fuel
consumption.
Energy
Information
Administration
data
were
used
to
obtain
industrial
and
commercial
fuel
use
projections.
The
percentage
change
in
consumption
(
1998
to
2005)
in
the
industrial
and
commercial
sectors
was
calculated
for
the
following
fuel
categories
using
1998
as
the
base
year
(
the
same
year
that
the
model
boiler
algorithms
are
based
on):
steam
coal
(
2.6%),
natural
gas
(
6.3%),
residual
fuel
oil
(­
7.4%),
distillate
fuel
oil
(
12.0%),
and
biomass
(
11.5%).
It
should
be
noted
that
1998
was
a
3­
16
Number
of
New
Units

Total
energy
consumed
(
2005)
[
MMBtu/
yr]

Avg
capacity
[
MMBtu/
hr]
×
8,760
[
hr/
yr]
 
Number
of
Units
(
1998)
year
of
below
average
energy
prices,
and
that
current
and
potential
future
energy
prices
are
higher
than
the
historical
average.
If
real
fuel
prices
increase
faster
than
the
EIA's
projections,
then
conservation
measures
may
lead
to
fewer
projected
boilers
and
process
heaters.
This
trend
would
lead
to
an
overestimate
(
upward
bias)
of
the
impact
estimates
presented
in
this
report.

2.
Estimate
the
number
of
new
boilers
by
model
number­
fuel
type.
To
predict
the
number
of
new
boilers
in
operation
by
2005,
EPA
applied
the
percentage
difference
for
each
fuel
category
to
the
1998
fuel
consumption
of
boilers
represented
by
the
boiler
models
to
calculate
total
energy
consumed
by
boilers
in
2005
for
each
model
number.
The
number
of
new
boilers
per
model
was
calculated
by
dividing
the
model
fuel
forecasts
by
the
annual
fuel
consumption
of
one
unit
and
then
subtracting
the
number
of
units
present
in
1998,
as
follows:

Following
these
steps,
EPA
projects
that
1,458
boilers
and
374
process
heaters
to
be
installed
between
1998
and
2005
will
be
affected
by
the
new
source
MACT
floor
and
the
Option
1A
alternative.
The
only
new
ICI
boilers
and
process
heaters
that
will
be
unaffected
are
those
natural
gas
and
distillate
fuel
units
that
have
input
capacities
less
than
10
MMBtu/
hr.
These
projections
were
developed
by
model
unit
type,
not
by
industry.
To
assess
the
distribution
of
the
boilers
and
process
heaters
estimated
to
be
operating
in
2005
across
industries,
EPA
attached
unit­
level
weights
by
model
number
to
each
unit
in
the
Inventory
Database.
These
weights
allow
each
unit
in
the
Inventory
Database
to
represent
a
number
(
or
fraction)
of
units
that
are
predicted
to
be
in
use
by
the
end
of
2005.
The
weights
were
then
summed
by
two­
digit
SIC
code
to
estimate
the
distribution
of
units
by
industry.

Table
3­
6
presents
the
projected
number
of
new
boilers
and
process
heaters
for
the
MACT
floor
and
Option1A
above­
the­
floor
alternatives.
Industries
with
the
estimated
greatest
concentrations
of
new
units
include
chemicals
and
allied
products
(
295),
petroleum
refining
(
198),
electric
services
(
134),
and
paper
and
allied
products
(
96).
New
source
estimates
by
industry
were
not
developed
for
the
Option
1B
above­
the­
floor
alternative.

3.4
National
Engineering
Population,
Cost
Estimates,
and
Cost­
Effectiveness
Estimates
The
Agency
estimates
that
in
2005
5,562
units
(
existing
units
and
new
units)
may
be
affected
by
the
floor
alternative
and
9,163
units
may
be
affected
by
the
Option
1A
above­
the­
floor
alternative.
These
populations
were
used
to
estimate
national
engineering
costs.
The
population
estimates
were
determined
by
unit
configuration,
not
by
industry.
Thus,
the
distribution
of
units
by
industry
shown
in
Tables
3­
6
and
3­
7
was
determined
by
weighting
existing
units
by
the
estimates
by
unit
configuration
and
tallying
weighted
units
by
SIC
code.
The
average
cost
of
control
by
unit
configuration
was
multiplied
by
the
weighted
number
of
units
to
determine
industry­
level
control
cost
estimates.

Table
3­
8
presents
industry­
level
population
and
cost
estimates
for
boilers
and
process
heaters
for
both
the
floor
and
above­
the­
floor
alternatives.
The
distribution
of
weighted
units
across
industries
mirrors
that
of
the
analysis
population
even
though
it
was
determined
by
weighting
units
by
configuration,
not
industry­
level
growth
estimates.
The
floor
cost
of
control
for
the
estimated
5,562
boilers
and
process
heaters
is
$
863.0
million,
with
an
average
per­
unit
additional
control
cost
of
$
155,157.
The
Option
1A
cost
of
control
for
the
9,163
potentially
affected
units
is
$
1,995.8
million,
with
an
average
per­
unit
cost
of
$
217,811.

The
Agency
estimates
that
Option
1B
will
potentially
affect
62,215
boilers
and
process
heaters.
The
Option
1B
cost
of
control
for
the
62,215
potentially
affected
units
is
$
2,944.8
million.
Option
1B
costs
are
not
presented
by
industry
because
approximately
one­
third
of
the
units
did
not
have
SIC
code
(
and,
hence,
no
NAICS
code)
information.
3­
17
To
provide
additional
information
on
the
magnitude
of
the
cost
estimates,
Table
3­
5
shows
the
cost­
effectiveness
(
cost/
ton
reduced
estimates)
for
the
HAP
and
non­
HAP
pollutants
whose
emissions
are
reduced
by
this
rule.

Table
3­
5.
Cost
Effectiveness
(
C/
E)
of
Industrial
Boiler
and
Process
Heater
MACT
on
Existing
Units
and
Subcategories.

Total
Annualized
Costs
Large
Solid
fuel
Subcategory
Large
Solid
fuel
Subcategory
­
Coal
Only
Large
Solid
fuel
Subcategory
­
Wood
Only
Limited
Use
Solid
fuel
Subcategory
Control
Costs
($)
833,273,781b
810,422,230
669,353,690
141,068,540
22,851,551
PM
Emissions
Reduction
(
Tons/
Year)
565,900
563,060
359,920
203,140
2,840
C/
E
($/
ton
PM)
1,472a
1,439
1,860
694
8,046
Metals
Emissions
Reduction
(
Tons/
Year)
1,093
1,087
591
496
6
C/
E
($/
ton
metals)
762,373a
745,558a
1,132,578a
284,412a
3,808,592a
HCl
Emissions
Reduction
(
Tons/
Year)
46,515
46,515
45,136
1,379
­­­
3­
18
C/
E
($/
ton
HCl)
17,914a
17,422a
14,830a
102,298a
­­­

HAP
Emissions
Reduction
(
Tons/
Year)
47,608
47,602
45,727
1,875
6
C/
E
($/
ton
HAP)
17,502
17,025
14,638
75,236
3,808,500
a
The
cost­
effectiveness
value
is
based
on
the
total
annualized
cost
of
the
rule
and
not
on
the
cost
for
controlling
the
specific
pollutant,
and,
thus,
overstates
the
cost/
ton
for
the
specific
HAP
or
other
pollutant.

b
Costs
are
in
1999
dollars.
Emission
reductions
are
calculated
for
2005.
3­
19
Table
3­
6.
New
Unit
Projections
by
Industry,
MACT
Floor
and
Option
1A
Alternatives
SIC
Code
NAICS
Code
Floor
Alternative
Option
1A
Alternative
Description
New
Units
Cost
New
Units
Cost
01
111
Agriculture
 
Crops
 
 
 
 
02
112
Agriculture
 
Livestock
 
 
 
 
07
115
Agricultural
Services
 
 
 
 
10
212
Metal
Mining
6
$
47,040
6
$
47,040
12
212
Coal
Mining
1
$
7,840
1
$
7,840
13
211
Oil
and
Gas
Extraction
89
$
697,760
89
$
697,760
14
212
Mining/
Quarrying
 
Nonmetallic
Minerals
6
$
87,740
6
$
87,740
17
235
Construction
 
Special
Trade
Contractors
 
 
 
 
20
311
Food
and
Kindred
Products
63
$
801,836
63
$
11,170,93
1
21
312
Tobacco
Products
7
$
54,880
7
$
54,880
22
313
Textile
Mill
Products
73
$
1,329,391
73
$
1,463,682
23
315
Apparel
and
Other
Products
from
Fabrics
 
 
 
 
24
321
Lumber
and
Wood
Products
61
$
1,748,655
61
$
10,621,23
2
25
337
Furniture
and
Fixtures
47
$
1,354,701
47
$
4,306,979
26
322
Paper
and
Allied
Products
96
$
1,526,704
96
$
15,984,33
2
27
511
Printing,
Publishing,
and
Related
Industries
19
$
148,960
19
$
148,960
28
325
Chemicals
and
Allied
Products
295
$
3,793,738
295
$
3,883,243
29
324
Petroleum
Refining
and
Related
Industries
198
$
1,552,320
198
$
1,552,320
30
326
Rubber
and
Miscellaneous
Plastics
Products
44
$
385,660
44
$
385,660
31
316
Leather
and
Leather
Products
5
$
39,200
5
$
39,200
32
327
Stone,
Clay,
Glass,
and
Concrete
Products
37
$
549,975
37
$
549,975
33
331
Primary
Metal
Industries
80
$
2,873,492
80
$
2,873,492
34
332
Fabricated
Metal
Products
53
$
496,920
53
$
496,920
35
333
Industrial
Machinery
and
Computer
Equipment
35
$
396,500
35
$
396,500
36
335
Electronic
and
Electrical
Equipment
40
$
313,600
40
$
313,600
37
336
Transportation
Equipment
80
$
1,133,423
80
$
1,357,219
38
334
Scientific,
Optical,
and
Photographic
Equipment
11
$
86,240
11
$
86,240
39
339
Miscellaneous
Manufacturing
Industries
9
$
162,323
9
$
254,722
40
482
Railroad
Transportation
 
 
 
 
42
484
Motor
Freight
and
Warehousing
1
$
48,540
1
$
48,540
(
continued)
3­
20
Table
3­
6.
New
Unit
Projections
by
Industry,
MACT
Floor
and
Option
1A
Alternatives
(
continued)

SIC
Code
NAICS
Code
Floor
Alternative
Option
1A
Alternative
Description
New
Units
Cost
New
Units
Cost
46
486
Pipelines,
Except
Natural
Gas
1
$
7,840
1
$
7,840
49
221
Electric,
Gas,
and
Sanitary
Services
134
$
2,094,546
134
$
10,490,757
50
421
Wholesale
Trade
 
Durable
Goods
 
 
 
 
51
422
Wholesale
Trade
 
Nondurable
Goods
 
 
 
 
55
441
Automotive
Dealers
and
Gasoline
Service
Stations
 
 
 
 
58
722
Eating
and
Drinking
Places
 
 
 
 
59
445
 
454
Miscellaneous
Retail
 
 
 
 
60
522
Depository
Institutions
 
 
 
 
70
721
Hotels
and
Other
Lodging
Places
 
 
 
 
72
812
Personal
Services
1
$
7,840
1
$
7,840
76
811
Miscellaneous
Repair
Services
 
 
 
 
80
621
Health
Services
6
$
209,840
6
$
209,840
81
541
Legal
Services
 
 
 
 
82
611
Educational
Services
19
$
815,855
19
$
815,855
83
624
Social
Services
 
 
 
 
86
813
Membership
Organizations
 
 
 
 
87
541
Engineering,
Accounting,
Research,
Management
and
Related
Services
2
$
388,350
2
$
388,350
89
711/
514
Services,
N.
E.
C.
 
 
 
 
91
921
Executive,
Legislative,
and
General
Administration
 
 
 
 
92
922
Justice,
Public
Order,
and
Safety
4
$
153,460
4
$
153,460
94
923
Administration
of
Human
Resources
 
 
 
 
96
926
Administration
of
Economic
Programs
 
 
 
 
97
928
National
Security
and
International
Affairs
2
$
97,080
2
$
97,080
NA
SIC
Information
Not
Available
307
$
2,497,327
307
$
2,586,832
State
Parent
is
a
State
Government
 
 
 
 
1,832
$
25,909,574
1,832
$
71,586,861
3­
21
Table
3­
7.
Unit
Cost
and
Population
Estimates
for
the
Floor
Alternative
by
Industry,
2005
SIC
Code
NAICS
Code
Total
Units
Total
Cost
Description
Floor
Units
Percent
Floor
Costs
(
by
Unit)
Percent
01
111
Agriculture
 
Crops
5
0.08%
$
628,943
0.07%
02
112
Agriculture
 
Livestock
 
0.00%
 
0.00%
07
115
Agricultural
Services
 
0.00%
 
0.00%
10
212
Metal
Mining
27
0.48%
$
6,651,678
0.77%
12
212
Coal
Mining
6
0.10%
$
683,026
0.08%
13
211
Oil
and
Gas
Extraction
89
1.60%
$
697,760
0.08%
14
212
Mining/
Quarrying
 
Nonmetallic
Minerals
25
0.46%
$
8,253,479
0.96%
17
235
Construction
 
Special
Trade
Contractors
 
0.00%
 
0.00%
20
311
Food
and
Kindred
Products
312
5.60%
$
37,774,020
4.38%
21
312
Tobacco
Products
28
0.51%
$
6,014,216
0.70%
22
313
Textile
Mill
Products
360
6.47%
$
74,152,804
8.59%
23
315
Apparel
and
Other
Products
from
Fabrics
4
0.08%
$
679,510
0.08%
24
321
Lumber
and
Wood
Products
483
8.68%
$
48,896,055
5.67%
25
337
Furniture
and
Fixtures
311
5.59%
$
29,632,880
3.43%
26
322
Paper
and
Allied
Products
565
10.15%
$
123,008,263
14.25%
27
511
Printing,
Publishing,
and
Related
Industries
19
0.34%
$
148,960
0.02%
28
325
Chemicals
and
Allied
Products
644
11.58%
$
116,236,183
13.47%
29
324
Petroleum
Refining
and
Related
Industries
217
3.91%
$
4,620,563
0.54%
30
326
Rubber
and
Miscellaneous
Plastics
Products
73
1.32%
$
6,356,835
0.74%
31
316
Leather
and
Leather
Products
7
0.13%
$
607,530
0.07%
32
327
Stone,
Clay,
Glass,
and
Concrete
Products
57
1.02%
$
6,253,678
0.72%
33
331
Primary
Metal
Industries
159
2.85%
$
27,110,619
3.14%
34
332
Fabricated
Metal
Products
87
1.56%
$
10,042,680
1.16%
35
333
Industrial
Machinery
and
Computer
Equipment
84
1.51%
$
11,208,392
1.30%

36
335
Electronic
and
Electrical
Equipment
52
0.93%
$
3,744,828
0.43%
37
336
Transportation
Equipment
300
5.39%
$
55,440,341
6.42%
38
334
Scientific,
Optical,
and
Photographic
Equipment
26
0.46%
$
3,511,206
0.41%

39
339
Miscellaneous
Manufacturing
Industries
12
0.22%
$
826,346
0.10%
40
482
Railroad
Transportation
9
0.16%
$
1,251,062
0.14%
42
484
Motor
Freight
and
Warehousing
12
0.22%
$
2,128,148
0.25%

(
continued)
3­
22
Table
3­
7.
Unit
Cost
and
Population
Estimates
for
the
Floor
Alternative
by
Industry,
2005
(
continued)

SIC
Code
NAICS
Code
Total
Units
Total
Cost
Description
Floor
Units
Percent
Floor
Costs
(
by
Unit)
Percent
46
486
Pipelines,
Except
Natural
Gas
1
0.02%
$
7,840
0.00%

49
221
Electric,
Gas,
and
Sanitary
Services
718
12.91%
$
150,341,645
17.42%

50
421
Wholesale
Trade
 
Durable
Goods
6
0.12%
$
2,154,760
0.25%

51
422
Wholesale
Trade
 
Nondurable
Goods
4
0.07%
$
1,673,511
0.19%

55
441
Automotive
Dealers
and
Gasoline
Service
Stations
 
0.00%
 
0.00%

58
722
Eating
and
Drinking
Places
 
0.00%
 
0.00%

59
445
 
454
Miscellaneous
Retail
 
0.00%
 
0.00%

60
522
Depository
Institutions
 
0.00%
 
0.00%

70
721
Hotels
and
Other
Lodging
Places
2
0.04%
$
567,811
0.07%

72
812
Personal
Services
1
0.02%
$
7,840
0.00%

76
811
Miscellaneous
Repair
Services
4
0.08%
$
625,531
0.07%

80
621
Health
Services
86
1.55%
$
15,172,212
1.76%

81
541
Legal
Services
 
0.00%
 
0.00%

82
611
Educational
Services
251
4.52%
$
60,490,956
7.01%

83
624
Social
Services
5
0.08%
$
820,191
0.10%

86
813
Membership
Organizations
 
0.00%
 
0.00%

87
541
Engineering,
Accounting,
Research,
Management
and
Related
Services
38
0.68%
$
2,240,544
0.26%

89
711/
514
Services,
N.
E.
C.
2
0.04%
$
918,360
0.11%

91
921
Executive,
Legislative,
and
General
Administration
2
0.04%
$
312,765
0.04%

92
922
Justice,
Public
Order,
and
Safety
69
1.23%
$
13,707,649
1.59%

94
923
Administration
of
Human
Resources
2
0.04%
$
314,316
0.04%

96
926
Administration
of
Economic
Programs
8
0.15%
$
2,300,308
0.27%

97
928
National
Security
and
International
Affairs
64
1.16%
$
18,018,010
2.09%

NA
SIC
Information
Not
Available
326
5.86%
$
6,747,652
0.78%

State
Parent
is
a
state
government
 
0.00%
 
0.00%

5,562
$
862,981,906
3­
23
Table
3­
8.
Unit
Cost
and
Population
Estimates
for
the
Option
1A
Above­
the­
Floor
Alternative
by
Industry,
2005
SIC
Code
NAICS
Code
Total
Units
Total
Cost
Description
Option
1A
Units
Percent
Option
1A
Costs
(
by
Unit)
Percent
01
111
Agriculture
 
Crops
11
0.12%
$
1,633,841
0.08%
02
112
Agriculture
 
Livestock
 
0.00%
 
0.00%
07
115
Agricultural
Services
 
0.00%
 
0.00%
10
212
Metal
Mining
34
0.37%
$
8,952,098
0.45%
12
212
Coal
Mining
6
0.06%
$
683,026
0.03%
13
211
Oil
and
Gas
Extraction
137
1.50%
$
6,070,001
0.30%
14
212
Mining/
Quarrying
 
Nonmetallic
Minerals
31
0.34%
$
17,958,177
0.90%
17
235
Construction
 
Special
Trade
Contractors
2
0.03%
$
230,525
0.01%
20
311
Food
and
Kindred
Products
376
4.10%
$
122,487,346
6.14%
21
312
Tobacco
Products
56
0.61%
$
13,685,614
0.69%
22
313
Textile
Mill
Products
673
7.34%
$
147,094,726
7.37%
23
315
Apparel
and
Other
Products
from
Fabrics
10
0.11%
$
1,213,586
0.06%
24
321
Lumber
and
Wood
Products
620
6.77%
$
89,961,854
4.51%
25
337
Furniture
and
Fixtures
421
4.60%
$
50,045,573
2.51%
26
322
Paper
and
Allied
Products
1,050
11.46%
$
323,736,302
16.22%
27
511
Printing,
Publishing,
and
Related
Industries
37
0.40%
$
1,824,933
0.09%
28
325
Chemicals
and
Allied
Products
1,359
14.83%
$
293,027,205
14.68%
29
324
Petroleum
Refining
and
Related
Industries
677
7.38%
$
73,172,001
3.67%
30
326
Rubber
and
Miscellaneous
Plastics
Products
178
1.94%
$
18,100,195
0.91%
31
316
Leather
and
Leather
Products
66
0.72%
$
6,924,480
0.35%
32
327
Stone,
Clay,
Glass,
and
Concrete
Products
154
1.68%
$
17,509,996
0.88%
33
331
Primary
Metal
Industries
271
2.95%
$
65,174,064
3.27%
34
332
Fabricated
Metal
Products
165
1.80%
$
22,066,661
1.11%
35
333
Industrial
Machinery
and
Computer
Equipment
151
1.65%
$
26,418,385
1.32%

36
335
Electronic
and
Electrical
Equipment
167
1.82%
$
18,770,867
0.94%
37
336
Transportation
Equipment
453
4.95%
$
107,402,909
5.38%
38
334
Scientific,
Optical,
and
Photographic
Equipment
104
1.13%
$
13,638,983
0.68%

39
339
Miscellaneous
Manufacturing
Industries
37
0.41%
$
4,222,427
0.21%
40
482
Railroad
Transportation
9
0.10%
$
2,240,871
0.11%
42
484
Motor
Freight
and
Warehousing
19
0.21%
$
3,475,610
0.17%

(
continued)
3­
24
Table
3­
8.
Unit
Cost
and
Population
Estimates
for
the
Option
1A
Above­
the­
Floor
Alternative
by
Industry,
2005
(
continued)

SIC
Code
NAICS
Code
Total
Units
Total
Cost
Description
Option
1A
Units
Percent
Option
1A
Costs
(
by
Unit)
Percent
46
486
Pipelines,
Except
Natural
Gas
19
0.21%
$
1,959,589
0.10%

49
221
Electric,
Gas,
and
Sanitary
Services
865
9.44%
$
331,479,389
16.61%

50
421
Wholesale
Trade
 
Durable
Goods
6
0.07%
$
2,675,296
0.13%

51
422
Wholesale
Trade
 
Nondurable
Goods
4
0.04%
$
2,693,380
0.13%

55
441
Automotive
Dealers
and
Gasoline
Service
Stations
2
0.02%
$
195,421
0.01%

58
722
Eating
and
Drinking
Places
 
0.00%
 
0.00%

59
445
 
454
Miscellaneous
Retail
3
0.03%
$
259,585
0.01%

60
522
Depository
Institutions
 
0.00%
 
0.00%

70
721
Hotels
and
Other
Lodging
Places
2
0.02%
$
849,114
0.04%

72
812
Personal
Services
1
0.01%
$
7,840
0.00%

76
811
Miscellaneous
Repair
Services
4
0.05%
$
1,120,435
0.06%

80
621
Health
Services
93
1.01%
$
22,545,605
1.13%

81
541
Legal
Services
 
0.00%
 
0.00%

82
611
Educational
Services
273
2.98%
$
91,770,778
4.60%

83
624
Social
Services
8
0.08%
$
1,448,405
0.07%

86
813
Membership
Organizations
 
0.00%
 
0.00%

87
541
Engineering,
Accounting,
Research,
Management
and
Related
Services
49
0.54%
$
5,016,627
0.25%

89
711/
514
Services,
N.
E.
C.
2
0.02%
$
1,211,582
0.06%

91
921
Executive,
Legislative,
and
General
Administration
5
0.06%
$
845,423
0.04%

92
922
Justice,
Public
Order,
and
Safety
77
0.85%
$
21,308,885
1.07%

94
923
Administration
of
Human
Resources
2
0.02%
$
314,316
0.02%

96
926
Administration
of
Economic
Programs
8
0.09%
$
4,200,975
0.21%

97
928
National
Security
and
International
Affairs
96
1.05%
$
36,080,306
1.81%

NA
SIC
Information
Not
Available
368
4.01%
$
12,099,975
0.61%

State
Parent
is
a
state
government
 
0.00%
 
0.00%

9,163
$
1,995,805,181
4­
25
References
Eastern
Research
Group.
Memorandum
to
Jim
Eddinger,
U.
S.
Environmental
Protection
Agency,
Office
of
Air
Quality
Planning
and
Standards.
Development
of
the
Population
Database
for
the
Industrial/
Commercial/
Institutional
Boiler
and
Indirect­
Fired
Process
Heater
National
Emission
Standard
for
Hazardous
Air
Pollutants
(
NESHAP).
May
18,
2000.

Eastern
Research
Group.
Memorandum
to
Jim
Eddinger,
U.
S.
Environmental
Protection
Agency,
Office
of
Air
Quality
Planning
and
Standards.
Development
of
Model
Units
for
the
Industrial/
Commercial/
Institutional
Boiler
and
Indirect­
Fired
Process
Heater
National
Emission
Standard
for
Hazardous
Air
Pollutants
(
NESHAP).
July,
2000.

U.
S.
Environmental
Protection
Agency,
Office
of
Air
Quality
Planning
and
Standards.
Industrial
Combustion
Coordinated
Rulemaking,
Inventory
Database
V4.1­
Boilers.
February
26,
1999.

U.
S.
Environmental
Protection
Agency,
Office
of
Air
Quality
Planning
and
Standards.
Industrial
Combustion
Coordinated
Rulemaking,
Inventory
Database
V4
­
Process
Heaters.
November
13,
1998.

CHAPTER
4
PROFILES
OF
AFFECTED
INDUSTRIES
4­
1
This
chapter
contains
profiles
of
the
major
industries
affected
by
the
MACT
for
industrial
boilers
and
process
heaters.
Included
are
profiles
of
the
following
industries:

Textile
Mill
Products
(
SIC
22/
NAICS
313)

Lumber
and
Wood
Products
(
SIC
24/
NAICS
321)

Furniture
and
Related
Product
Manufacturing
(
SIC
25/
NAICS
337)

Paper
and
Allied
Products
(
SIC
26/
NAICS
322)

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

Industrial
Organic
Chemicals
(
SIC
2869/
NAICS
3251)

Electric
Services
(
SIC
4911/
NAICS
22111)

4.1
Textile
Mill
Products
(
SIC
22/
NAICS
313)

The
textile
industry
is
one
of
the
few
industries
found
throughout
the
world,
from
the
most
industrialized
countries
to
the
poorest.
This
industry
includes
firms
producing
the
following
products:
broadwoven
fabric;
weft,
lace,
and
warp
knit
fabrics;
carpets
and
rugs;
spun
yarn
products;
and
man­
made
fibers.
The
United
States
has
typically
run
a
trade
deficit
in
the
textiles
sector
in
recent
years,
importing
about
$
1.3
billion
more
than
was
exported
in
1995.
Although
trade
has
become
an
increasingly
important
part
of
this
industry,
trade
in
this
segment
is
relatively
small
compared
with
trade
in
the
downstream
apparel
segment.
In
1996,
the
total
value
of
shipments
for
the
textile
industry
was
$
80,242
million.

4.2
Lumber
and
Wood
Products
(
SIC
24/
NAICS
321)

The
lumber
and
wood
products
industry
comprises
a
large
number
of
establishments
engaged
in
logging;
operating
sawmills
and
planing
mills;
and
manufacturing
structural
wood
panels,
wooden
containers,
and
other
wood
products.
Table
4­
1
lists
the
lumber
and
wood
products
markets
that
are
likely
to
be
affected
by
the
regulation
on
boilers.
Most
products
are
produced
for
the
domestic
market,
but
exports
increasingly
account
for
a
larger
proportion
of
sales
(
Haltmaier,
1998).
The
largest
consumers
of
lumber
and
wood
products
are
the
remodeling
and
construction
industries.

Table
4­
1.
Lumber
and
Wood
Products
Markets
Likely
to
Be
Affected
by
the
Regulation
SIC
NAICS
Description
2421
321113
Sawmills
and
Planing
Mills,
General
2434
33711
Wood
Kitchen
Cabinets
2449
32192
Wood
Containers,
N.
E.
C.

2491
32114
Wood
Preserving
2493
321219
Reconstituted
Wood
Products
2499
321999
Wood
Products,
N.
E.
C.

Source:
Industrial
Combustion
Coordinated
Rulemaking
(
ICCR).
1998.
Data/
Information
Submitted
to
the
Coordinating
Committee
at
the
Final
Meeting
of
the
Industrial
Combustion
Coordinated
Rulemaking
Federal
Advisory
Committee.
EPA
Docket
Numbers
A­
94­
63,
II­
K­
4b2
through
­
4b5.
Research
Triangle
Park,
North
Carolina.
September
16­
17.
4­
2
In
1996,
the
lumber
and
wood
products
industry's
total
value
of
shipments
was
$
85,724.0
million.
As
seen
in
Table
4­
2,
shipment
values
increased
steadily
through
the
late
1980s
before
declining
slightly
through
the
early
1990s
as
new
construction
starts
and
furniture
purchases
declined
(
Haltmaier,
1998).
Shipment
values
recovered,
however,
as
the
economy
expanded
in
the
mid­
1990s.

4.2.1
Supply
Side
of
the
Industry
This
section
describes
the
lumber
industry's
production
processes,
output,
costs
of
production,
and
capacity
utilization.

4.2.1.1
Production
Processes
Sawn
lumber.
Sawn
lumber
is
softwood
or
hardwood
trimmed
at
a
sawmill
for
future
uses
in
construction,
flooring,
furniture,
or
other
markets.
Softwoods,
such
as
Douglas
fir
and
spruce,
are
used
for
framing
in
residential
or
light­
commercial
construction.
Hardwoods,
such
as
maple
and
oak,
are
used
in
flooring,
furniture,
crating,
and
other
applications.

Lumber
is
prepared
at
mills
using
a
four­
step
process.
First,
logs
are
debarked
and
trimmed
into
cants,
or
partially
finished
lumber.
The
cants
are
then
cut
to
specific
lengths.
Logs
are
generally
kept
wet
during
storage
to
prevent
cracking
and
to
keep
them
supple.
However,
after
being
cut,
the
boards
undergo
a
drying
process,
either
in
open
air
or
in
a
kiln,
to
reduce
the
moisture
content.
The
drying
process
may
take
several
months
and
varies
according
to
the
plant's
climate
and
the
process
used.
Finally,
the
lumber
may
be
treated
with
a
surface
protectant
to
prevent
sap
stains
and
prepare
it
for
export
(
EPA,
1995a).

Reconstituted
wood
products.
Reconstituted
wood
products,
such
as
particleboard,
medium
density
fiberboard,
hardboard,
and
oriented
strandboard,
are
made
from
raw
wood
that
is
combined
with
resins
and
other
additives
and
processed
into
boards.
The
size
of
the
wood
particles
used
varies
from
sawdust
to
strands
of
wood.
Once
combined,
the
ingredients
are
formed
into
a
mat
and
then,
at
high
temperatures,
pressed
into
a
board.
A
final
finishing
process
prepares
the
boards
for
delivery.

Wood
preserving.
Wood
is
treated
with
preservative
to
protect
it
from
mechanical,
physical,
and
chemical
influences
(
EPA,
1995a).
Treatment
agents
are
either
water­
based
inorganics,
such
as
copper
arsenate
(
78
percent),
or
oil­
borne
organics,
such
as
creosote
(
21
percent)
(
EPA,
1995a).
Wood
Table
4­
2.
Value
of
Shipments
for
the
Lumber
and
Wood
Products
Industry
(
SIC
24/
NAICS
321),
1987­
1996
Year
Value
of
Shipments
(
1992
$
106)

1987
85,383.4
1988
85,381.2
1989
85,656.8
1990
86,203.0
1991
81,666.0
1992
81,564.8
1993
74,379.6
1994
79,602.0
1995
87,574.6
1996
85,724.0
Sources:
U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1996.
1992
Census
of
Manufactures,
Subject
Series:
General
Summary.
Washington,
DC:
Government
Printing
Office.

U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1990
 
1998.
Annual
Survey
of
Manufactures
[
Multiple
Years].
Washington,
DC:
Government
Printing
Office.
4­
3
preservatives
are
usually
applied
using
a
pressure
treatment
process
or
a
dipping
tank.
Producers
achieve
the
best
results
when
the
lumber's
moisture
content
is
reduced
to
a
point
where
the
preservative
can
be
easily
soaked
into
the
wood.
Treated
wood
is
then
placed
in
a
kiln
or
stacked
in
a
low­
humidity
climate
to
dry.

4.2.1.2
Types
of
Output
The
lumber
and
wood
products
industry
produces
essential
inputs
into
the
construction,
remodeling,
and
furniture
sectors.
Lumber
and
reconstituted
wood
products
are
produced
in
an
array
of
sizes
and
can
be
treated
to
enhance
their
value
and
shelf­
life.
These
products
are
intermediate
goods;
they
are
purchased
by
other
industries
and
incorporated
into
higher
value­
added
products.
In
addition
to
sawmills,
the
lumber
and
wood
products
industry
includes
kitchen
cabinets,
wood
containers,
and
other
wooden
products
used
for
fabricating
finished
goods
for
immediate
consumption.

4.2.1.3
Major
By­
Products
and
Co­
Products
Shavings,
sawdust,
and
wood
chips
are
the
principal
co­
products
of
sawn
lumber.
Paper
mills
and
makers
of
reconstituted
wood
products
frequently
purchase
this
material
as
an
input.
By­
products
are
limited
to
emissions
from
the
drying
process
and
from
use
of
preservatives.

Very
little
solid
waste
is
generated
by
reconstituted
wood
products
manufacturing.
Because
the
production
process
incorporates
all
parts
of
the
sawn
log,
little
is
left
over
as
waste.
However,
air
emissions
from
dryers
are
a
source
of
emissions.

Wood
preserving
results
in
two
types
of
by­
products:
air
emissions
and
process
debris.
As
preservatives
dry,
either
in
a
kiln
or
outside,
they
emit
various
chemicals
into
the
air.
At
plants
with
dipping
processes,
wood
chips,
stones,
and
other
debris
build
up
in
the
dipping
tank.
The
debris
is
routinely
collected
and
disposed
of.

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

4.2.1.5
Capacity
Utilization
Full
production
capacity
is
broadly
defined
as
the
maximum
level
of
production
an
establishment
can
obtain
under
normal
operating
conditions.
The
capacity
utilization
ratio
is
the
ratio
of
the
actual
production
level
to
the
full
production
level.
Table
4­
4
presents
the
historical
trends
in
capacity
utilization
for
the
lumber
and
wood
products
industry.
The
varying
capacity
utilization
ratios
reflect
adjusting
production
levels
and
new
production
facilities
going
on­
or
off­
line.
The
capacity
utilization
ratio
for
the
industry
in
1996
was
78;
the
average
over
the
last
6
years
was
79
percent.

4.2.2
Demand
Side
of
the
Industry
This
section
describes
the
demand
side
of
the
market,
including
product
characteristics,
the
uses
and
consumers
of
the
final
products,
organization
of
the
industry,
and
markets
and
trends.

4.2.3
Product
Characteristics
4­
4
Lumber
and
wood
products
are
valued
both
for
their
physical
attributes
and
their
relative
low
cost.
Wood
is
available
in
varying
degrees
of
durability,
shades,
and
sizes
and
can
be
easily
shaped.
Lumber
and
wood
products
have
long
been
the
principal
raw
materials
for
the
residential
and
light
commercial
construction
industries,
the
remodeling
industry,
and
the
furniture
industry.

Table
4­
4.
Capacity
Utilization
Ratios
for
Lumber
and
Wood
Products
Industry,
1991­
1996
1991
1992
1993
1994
1995
1996
78
80
81
80
77
78
Note:
All
values
are
percentages.

Source:
U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1998.
Survey
of
Plant
Capacity:
1996.
Washington,
DC:
Government
Printing
Office.
Table
4­
3.
Inputs
for
the
Lumber
and
Wood
Products
Industry
(
SIC
24/
NAICS
321),
1987
 
1996
Year
Labor
Materials
(
1992
$
106)
New
Capital
Investment
(
1992
$
106)
Quantity
(
103)
Payroll
(
1992
$
106)

1987
698.4
15,555.5
50,509.2
2,234.3
1988
702.4
15,800.0
51,341.0
2,099.4
1989
684.2
15,381.3
51,742.2
2,329.9
1990
677.7
15,612.9
53,369.0
2,315.3
1991
623.6
14,675.8
50,416.3
2,006.5
1992
655.8
13,881.8
48,570.0
1,760.1
1993
685.4
11,798.9
45,300.3
1,538.1
1994
718.5
12,212.5
48,535.6
1,956.8
1995
740.2
13,915.4
53,732.9
2,553.1
1996
738.7
13,933.7
52,450.1
2,659.9
Sources:
U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1996.
1992
Census
of
Manufactures,
Subject
Series:
General
Summary.
Washington,
DC:
Government
Printing
Office.

U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1990
 
1998.
Annual
Survey
of
Manufactures
[
Multiple
Years].
Washington,
DC:
Government
Printing
Office.
4­
5
Wood
is
readily
available
because
over
one­
third
of
the
United
States
is
forested.
The
ready
supply
of
wood
reduces
its
costs.

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

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

Market
structure
can
affect
the
size
and
distribution
of
regulatory
impacts.
Concentration
ratios
are
often
used
to
evaluate
the
degree
of
competition
in
a
market,
with
low
concentration
indicating
the
presence
of
a
competitive
market,
and
higher
concentration
suggesting
less­
competitive
markets.
Firms
in
less­
concentrated
industries
are
more
likely
to
be
price
takers,
while
firms
in
more­
concentrated
industries
are
more
likely
to
influence
market
prices.
Typical
measures
include
four­
and
eight­
firm
concentration
ratios
(
CR4
and
CR8)
and
Herfindahl­
Hirschmann
indices
(
HHI).
The
CR4
for
lumber
and
wood
products
subsectors
represented
in
the
boilers
inventory
database
ranges
between
13
and
50,
meaning
that,
in
each
subsector,
the
top
firms'
combined
sales
ranged
from
13
to
50
percent
of
that
respective
subsector's
total
sales.
The
CR8
ranges
from
47
to
66
(
U.
S.
Department
of
Commerce,
1995d).

Although
there
is
no
objective
criterion
for
determining
market
structure
based
on
the
values
of
concentration
ratios,
the
1992
Department
of
Justice's
(
DOJ's)
Horizontal
Merger
Guidelines
provide
4­
6
criteria
for
doing
so
based
on
HHIs.
According
to
these
criteria,
industries
with
HHIs
below
1,000
are
Table
4­
5.
Size
of
Establishments
and
Value
of
Shipments
for
the
Lumber
and
Wood
Products
Industry
(
SIC
24/
NAICS
321)

1987
1992
Average
Number
of
Employees
in
Establishment
Number
of
Facilities
Value
of
Shipments
(
1992
$
106)
Number
of
Facilities
Value
of
Shipments
(
1992
$
106)

1
to
4
employees
14,562
2,769.7
15,921
3,288.9
5
to
9
employees
6,702
4,264.4
7,669
5,030.4
10
to
19
employees
5,353
6,982.3
5,331
6,902.8
20
to
49
employees
4,160
28,551.3
3,924
26,964.9
50
to
99
employees
1,702
(
D)
1,615
(
D)

100
to
249
employees
1,190
24,583.3
1,082
34,051.4
250
to
499
employees
260
12,093.4
219
(
D)

500
to
999
employees
47
3,907.9
39
3,331.4
1,000
to
2,499
employees
4
2,231.3
4
598.6
2,500
or
more
employees
2
(
D)
3
1,396.4
Total
33,987
85,383.4
35,807
81,564.8
(
D)
=
undisclosed
Sources:
U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1991.
1987
Census
of
Manufactures,
Subject
Series:
General
Summary.
Washington,
DC:
Government
Printing
Office.

U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1996.
1992
Census
of
Manufactures,
Subject
Series:
General
Summary.
Washington,
DC:
Government
Printing
Office.
4­
7
considered
unconcentrated
(
i.
e.,
more
competitive),
those
with
HHIs
between
1,000
and
1,800
are
considered
moderately
concentrated
(
i.
e.,
moderately
competitive),
and
those
with
HHIs
above
1,800
are
considered
highly
concentrated
(
i.
e.,
less
competitive)
(
DOJ,
1992).
Firms
in
less­
concentrated
industries
are
more
likely
to
be
price
takers,
while
firms
in
more­
concentrated
industries
are
more
likely
to
be
able
to
influence
market
prices.
The
unconcentrated
nature
of
the
markets
is
also
indicated
by
HHIs
of
1,000
or
less
(
DOJ,
1992).
Table
4­
6
presents
various
measures
of
market
concentration
for
sectors
within
the
lumber
and
wood
products
industry.
All
lumber
and
wood
products
industries
are
considered
unconcentrated
and
competitive.

4.2.6
Markets
and
Trends
The
U.
S.
market
for
lumber
and
wood
products
is
maturing,
and
manufacturers
are
looking
to
enter
other
markets.
Although
91
percent
of
the
industry's
products
are
consumed
by
the
U.
S.
domestic
market,
the
share
of
exports
increases
each
year.
Exports
more
than
doubled
in
value
from
$
3
billion
in
1986
to
$
7.3
billion
in
1996
(
Haltmaier,
1998).
The
U.
S.
market
grew
only
2
percent
between
1986
and
1996.
American
manufacturers
are
focusing
on
growing
construction
markets
in
Canada,
Mexico,
and
the
Pacific
Rim,
with
products
such
as
durable
hardwood
veneer
products
and
reconstituted
wood
boards
(
EPA,
1995a).

4.3
Furniture
and
Related
Product
Manufacturing
(
SIC
25/
NAICS
337)
Table
4­
6.
Measures
of
Market
Concentration
for
Lumber
and
Wood
Products
Markets
SIC
Description
CR4
CR8
HHI
Number
of
Companie
s
Number
of
Facilities
2421
Saw
Mills
and
Planing
Mills
14
20
78
5,302
6004
2434
Wood
Kitchen
Cabinets
19
25
156
4,303
4323
2449
Wood
Containers,
N.
E.
C.
34
47
414
217
225
2491
Wood
Preserving
17
28
152
408
486
2493
Reconstituted
Wood
Products
50
66
765
193
288
2499
Wood
Products,
N.
E.
C.
13
19
70
2,656
2754
Sources:
U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1995d.
1992
Concentration
Ratios
in
Manufacturing.
Washington,
DC:
Government
Printing
Office.

U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1996.
1992
Census
of
Manufactures,
Subject
Series:
General
Summary.
Washington,
DC:
Government
Printing
Office.
4­
8
More
than
20,000
establishments
in
the
United
States
produce
furniture
and
furniture­
related
products.
These
establishments
are
located
across
the
United
States
but
are
traditionally
most
concentrated
in
southern
states,
such
as
North
Carolina,
Mississippi,
Alabama,
and
Tennessee.
According
to
the
"
1997
Economic
Census,"
these
establishments
employed
more
than
600,000
people
and
paid
annual
wages
of
nearly
$
15
billion.
The
overall
industry­
wide
value
of
shipments
was
$
63.9
billion
that
year
(
U.
S.
Department
of
Commerce,
2001).

This
industry
is
in
a
state
of
change:
rapid
U.
S.
economic
growth
translated
into
vigorous
sales
of
household
and
office
funiture,
but
this
trend
is
unlikely
to
continue
as
the
U.
S.
economy
cools
after
its
record
run.
Adding
to
industry
fluctuation
is
the
merger
of
two
large
firms,
Lay­
Z­
Boy
and
LADD
Furniture.
Although
the
industry
includes
a
multitude
of
niche
market
players,
it
is
really
dominated
by
a
few
large
companies
that
operate
several
subsidiaries,
each
with
its
own
brand
identity.
It
is
unclear
whether
the
merger
between
two
key
players
in
the
market
will
compel
other
large
manufacturers
to
pursue
mergers
and
acquisitions.

What
is
clear,
however,
is
that
large
U.
S.
manufacturers
will
seek
to
leverage
their
brand
identities
into
wider
profit
margins
by
operating
direct
sales
establishments
and
co­
branding.
Manufacturers
that
are
moving
into
retail
and
distribution
include
Bassett
Furniture,
Thomasville
Furniture,
Ethan
Allen
Interiors,
and
Drexel.
Co­
branding
efforts
are
aimed
at
capitalizing
on
the
combined
power
of
two
identities,
such
as
the
Thomas
Kinkade
Collection
from
Lay­
Z­
Boy
and
popular
artist
Thomas
Kinkade
and
the
Ernest
Hemingway
Collection
from
Thomasville.
The
overarching
goal
is
to
enhance
margins
and
ward
off
invigorated
competition
from
foreign
companies
that
have
used
this
strategy
to
capture
U.
S.
market
share,
such
as
the
Swedish
manufacturer
Ikea
(
Lemm,
2000).

U.
S.
imports
of
household
furniture
totaled
nearly
$
7
billion
in
1998.
Between
1992
and
1998,
furniture
imports
grew
at
an
annualized
rate
of
nearly
15
percent.
Jamie
Lemm,
an
analyst
with
the
U.
S.
Department
of
Commerce's
Office
of
Consumer
Goods
attributes
this
growth
to
changes
in
U.
S.
manufacturing
and
markets:

A
portion
of
[
the]
increase
can
be
attributed
to
the
labor­
intensive
furniture
parts
imported
by
U.
S.
manufacturers
to
enhance
product
lines,
but
the
increase
also
signifies
the
growing
importance
of
the
U.
S.
market
to
foreign
firms.
While
some
U.
S.
manufacturers
operate
showrooms,
galleries,
and
retail
outlets
in
foreign
markets,
few
sell
internationally
on
a
large
scale.
In
1998,
U.
S.
furniture
exports
totaled
$
1.6
billion,
accounting
for
only
6
percent
of
all
U.
S.
product
shipments.

4.4
Paper
and
Allied
Products
(
SIC
26/
NAICS
322)

The
paper
and
allied
products
industry
is
one
of
the
largest
manufacturing
industries
in
the
United
States.
In
1996,
the
industry
shipped
nearly
$
150
billion
in
paper
commodities.
The
industry
produces
a
wide
range
of
wood
pulp,
primary
paper
products,
and
paperboard
products
such
as
printing
and
writing
papers,
industrial
papers,
tissues,
container
board,
and
boxboard.
The
industry
also
includes
manufacturers
that
"
convert"
primary
paper
and
paperboard
into
finished
products
like
envelopes,
packaging,
and
shipping
containers
(
EPA,
1995b).
Paper
and
allied
products
industry
subsectors
that
are
likely
to
be
affected
by
the
proposed
regulation
are
listed
in
Table
4­
7.
4­
9
Table
4­
8
lists
the
paper
and
allied
products
industry's
value
of
shipments
from
1987
to
1996.
The
industry's
performance
is
tied
to
raw
material
prices,
labor
conditions,
and
worldwide
inventories
and
demand
(
EPA,
1995b).
Performance
over
the
10­
year
period
was
typical
of
most
manufacturing
industries.
The
industry
expanded
in
the
late
1980s,
then
contracted
as
demand
tapered
off
as
the
industry
suffered
recessionary
effects.
In
the
two
years
after
1994,
the
industry's
value
of
shipments
increased
9.3
percent
to
$
149.5
billion.

4.4.1
Supply
Side
of
the
Industry
4.4.1.1
Production
Process
The
manufacturing
paper
and
allied
products
industry
is
capital­
and
resource­
intensive,
consuming
large
amounts
of
pulp
wood
and
water
in
the
manufacturing
process.
Approximately
half
of
all
paper
and
allied
products
establishments
are
integrated
facilities,
meaning
that
they
produce
both
pulp
and
paper
onsite
The
remaining
half
produce
only
paper
products;
few
facilities
produce
only
pulp
(
EPA,
1995b).
Table
4­
7.
Paper
and
Allied
Products
Industry
Markets
Likely
to
Be
Affected
by
Regulation
SIC
NAICS
Industry
Description
2611
32211
Pulp
Mills
2621
32212
Paper
Mills
2676
322291
Sanitary
Paper
Products
Source:
Industrial
Combustion
Coordinated
Rulemaking
(
ICCR).
1998.
Data/
Information
Submitted
to
the
Coordinating
Committee
at
the
Final
Meeting
of
the
Industrial
Combustion
Coordinated
Rulemaking
Federal
Advisory
Committee.
EPA
Docket
Numbers
A­
94­
63,
II­
K­
4b2
through
­
4b5.
Research
Triangle
Park,
North
Carolina.
September
16­
17.
4­
10
The
paper
and
paperboard
manufacturing
process
can
be
divided
into
three
general
steps:
pulp
making,
pulp
processing,
and
paper/
paperboard
production.
Paper
and
paperboard
are
manufactured
using
what
is
essentially
the
same
process.
The
principal
difference
between
the
two
products
is
that
paperboard
is
thicker
than
paper's
0.3
mm.

Producers
manufacture
pulp
mixtures
by
using
chemicals,
machines,
or
both
to
reduce
raw
material
into
small
fibers.
In
the
case
of
wood,
the
most
common
pulping
material,
chemical
pulping
actions
release
cellulose
fibers
by
selectively
destroying
the
chemical
bonds
that
bind
the
fibers
together
(
EPA,
1995b).
Impurities
are
removed
from
the
pulp,
which
then
may
be
bleached
to
improve
brightness.
Only
about
20
percent
of
pulp
and
paper
mills
practice
bleaching
(
EPA,
1995b).
The
pulp
may
also
be
further
processed
to
aid
in
the
paper­
making
process.

During
the
paper­
making
stage,
the
pulp
is
strengthened
and
then
converted
into
paper.
Pulp
can
be
combined
with
dyes,
resins,
filler
materials,
or
other
additives
to
better
fulfill
specifications
for
the
final
product.
Next,
the
water
is
removed
from
the
pulp,
leaving
the
pulp
on
a
wire
or
wire
mesh
conveyor.
The
fibers
bond
together
as
they
are
carried
through
heated
presses
and
rollers.
The
paper
is
stored
on
large
rolls
before
being
shipped
for
conversion
into
another
product,
such
as
envelopes
and
boxes,
or
cut
into
paper
sheets
for
immediate
consumption.

4.4.1.2
Types
of
Output
The
paper
and
allied
products
industry's
output
ranges
from
writing
papers
to
containers
and
packaging.
Paper
products
include
printing
and
writing
papers;
paperboard
boxes;
corrugated
and
solid
fiber
boxes;
fiber
cans,
drums,
and
similar
products;
sanitary
food
containers;
building
paper;
packaging;
bags;
sanitary
paper
napkins;
envelopes;
stationary
products;
and
other
converted
paper
products.
Table
4­
8.
Value
of
Shipments
for
the
Paper
and
Allied
Products
Industry
(
SIC
26/
NAICS
322),
1987
 
1996
Year
Value
of
Shipments
(
1992
$
106)

1987
129,927.8
1988
136,829.4
1989
138,978.3
1990
136,175.7
1991
132,225.0
1992
133,200.7
1993
131,362.2
1994
136,879.9
1995
135,470.3
1996
149,517.1
Sources:
U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1996.
1992
Census
of
Manufactures,
Subject
Series:
General
Summary.
Washington,
DC:
Government
Printing
Office.

U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1990
 
1998.
Annual
Survey
of
Manufactures,
[
Multiple
Years].
Washington,
DC:
Government
Printing
Office.
4­
11
4.4.1.3
Major
By­
Products
and
Co­
Products
The
paper
and
allied
products
industry
is
the
largest
user
of
industrial
process
water
in
the
United
States.
In
1988,
a
typical
mill
used
between
16,000
and
17,000
gallons
of
water
per
ton
of
paper
produced.
The
equivalent
amount
of
waste
water
discharged
each
day
is
about
16
million
cubic
meters
(
EPA,
1995b).
Most
facilities
operate
waste
water
treatment
facilities
on
site
to
remove
biological
oxygen
demand
(
BOD),
total
suspended
solids
(
TSS),
and
other
pollutants
before
discharging
the
water
into
a
nearby
waterway.

4.4.1.4
Costs
of
Production
Historical
statistics
for
the
costs
of
production
for
the
paper
and
allied
products
industry
are
listed
in
Table
4­
9.
From
1987
to
1996,
industry
payroll
generally
ranged
from
approximately
$
19
to
20
billion.
Employment
peaked
at
633,200
people
in
1989
and
declined
slightly
to
630,600
people
by
1996.
Materials
costs
averaged
$
74.4
billion
a
year
and
new
capital
investment
averaged
$
8.3
billion
a
year.

4.4.1.5
Capacity
Utilization
Table
4­
10
presents
the
trend
in
capacity
utilization
for
the
paper
and
allied
products
industry.
The
varying
capacities
reflect
adjusting
production
levels
and
new
production
facilities
going
on­
or
off­
line.
The
average
capacity
utilization
ratio
for
the
paper
and
allied
products
industry
between
1991
and
1996
was
approximately
80,
with
capacity
declining
slightly
in
recent
years.
Table
4­
9.
Inputs
for
the
Paper
and
Allied
Products
Industry
(
SIC
26/
NAICS
322),
1987
 
1996
Labor
Year
Quantity
(
103)
Payroll
(
1992
$
106)
Materials
(
1992
$
106)
New
Capital
Investment
(
1992
$
106)

1987
611.1
20,098.6
70,040.6
6,857.5
1988
619.8
19,659.0
73,447.4
8,083.8
1989
633.2
19,493.1
75,132.5
10,092.9
1990
631.2
19,605.2
74,568.8
11,267.2
1991
624.7
19,856.3
72,602.5
9,353.9
1992
626.3
20,491.9
73,188.0
7,962.4
1993
626.3
20,602.6
73,062.6
7,265.2
1994
621.4
20,429.7
76,461.6
6,961.7
1995
629.2
18,784.3
79,968.6
7,056.8
1996
630.6
19,750.0
75,805.9
8,005.9
Sources:
U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1996.
1992
Census
of
Manufactures,
Subject
Series:
General
Summery.
Washington,
DC:
Government
Printing
Office.

U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1990
 
1998.
Annual
Survey
of
Manufactures
[
Multiple
Years].
Washington,
DC:
Government
Printing
Office.
4­
12
4.4.2
Demand
Side
of
the
Industry
4.4.2.1
Product
Characteristics
Paper
is
valued
for
its
diversity
in
product
types,
applications,
and
low
cost
due
to
ready
access
to
raw
materials.
Manufacturers
produce
papers
of
varying
durabilities,
textures,
and
colors.
Consumers
purchasing
large
quantities
of
papers
may
have
papers
tailored
to
their
specification.
Papers
may
be
simple
writing
papers
or
newsprint
for
personal
consumption
and
for
the
printing
and
publishing
industry
or
durable
for
conversion
into
shipping
cartons,
drums,
or
sanitary
boxes.
Inputs
in
the
paper
production
process
are
readily
available
in
the
United
States
because
one­
third
of
the
country
is
forested,
and
facilities
generally
have
ready
access
to
waterways.

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

4.4.3
Organization
of
the
Industry
In
1992,
4,264
companies
produced
paper
and
allied
products
and
operated
6,416
facilities.
By
way
of
comparison,
4,215
companies
controlled
1,732
facilities
in
1987.
Although
the
number
of
small
firms
and
facilities
increased
during
those
5
years,
the
industry
is
dominated
by
high­
volume,
low­
cost
producers
(
Haltmaier,
1998).
Even
though
they
account
for
only
45
percent
of
all
facilities,
those
with
50
or
more
employees
contribute
more
than
93
percent
of
the
industry's
total
value
of
shipments
(
see
Table
4­
11).
(
According
to
the
Small
Business
Administration,
those
companies
employing
fewer
than
500
employees
are
"
small.")

For
paper
and
allied
products
markets
likely
to
be
affected
by
the
proposed
boilers
regulation,
the
CR4
ranged
between
29
and
68
in
1992
(
see
Table
4­
12).
This
means
that,
in
each
subsector,
the
top
firms'
combined
sales
ranged
from
29
to
68
percent
of
their
respective
industry's
total
sales.
For
example,
in
the
Table
4­
10.
Capacity
Utilization
Ratios
for
the
Paper
and
Allied
Products
Industry,
1991
 
1996
1991
1992
1993
1994
1995
1996
78
80
81
80
77
78
Note:
All
values
are
percentages.

Source:
U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1998.
Survey
of
Plant
Capacity:
1996.
Washington,
DC:
Government
Printing
Office.
4­
13
sanitary
paper
products
industry,
the
CR4
ratios
indicate
that
a
few
firms
control
68
percent
of
the
Table
4­
11.
Size
of
Establishments
and
Value
of
Shipments
for
the
Paper
and
Allied
Products
Industry
(
SIC
26/
NAICS
322)

1987
1992
Number
of
Employees
in
Establishment
Number
of
Facilities
Value
of
Shipments
($
106)
Number
of
Facilities
Value
of
Shipments
($
106)

1
to
4
employees
729
640.6
786
216
4
to
9
employees
531
(
D)
565
483
10
to
19
employees
888
1,563.4
816
1,456.5
20
to
49
employees
1,433
18,328.6
1,389
6,366.6
50
to
99
employees
1,018
(
D)
1,088
12,811.5
100
to
249
employees
1,176
32,141.7
1,253
35,114.0
250
to
499
employees
308
24,221.1
298
22,281.2
500
to
999
employees
145
28,129.1
159
31,356.5
1,000
to
2,499
employees
63
24,903.1
62
23,115.4
2,500
or
more
employees
1
(
D)

Total
1,732
129,927.8
6,416
133,200.7
(
D)
=
undisclosed
Sources:
U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1990c.
1987
Census
of
Manufactures,
Industry
Series:
Pulp,
Paper,
and
Board
Mills.
Washington,
DC:
Government
Printing
Office.

U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1995c.
1992
Census
of
Manufactures,
Industry
Series:
Pulp,
Paper,
and
Board
Mills.
Washington,
DC:
Government
Printing
Office.
4­
14
market.
This
sector's
moderately
concentrated
nature
is
Table
4­
12.
Measurements
of
Market
Concentration
for
Paper
and
Allied
Products
Markets
SIC
Description
CR4
CR8
HHI
Number
of
Companies
Number
of
Facilities
2611
Pulp
Mills
48
75
858
29
45
2621
Paper
Mills
29
49
392
127
280
2676
Sanitary
Paper
Products
68
82
1,451
80
150
Sources:
U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1995d.
1992
Concentration
Ratios
in
Manufacturing.
Washington,
DC:
Government
Printing
Office.

U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1995c.
1992
Census
of
Manufactures,
Industry
Series:
Pulp,
Paper,
and
Board
Mills.
Washington,
DC:
Government
Printing
Office.
4­
15
also
indicated
by
its
HHI
of
1,451
(
DOJ,
1992).
The
remaining
two
sectors'
HHIs
indicate
that
their
respective
markets
are
unconcentrated
(
i.
e.,
competitive).

4.4.4
Markets
and
Trends
The
Department
of
Commerce
projects
that
shipments
of
paper
and
allied
products
will
increase
through
2002
by
an
annual
average
of
2.5
percent
(
Haltmaier,
1998).
Because
nearly
all
of
the
industry's
products
are
consumer
related,
shipments
will
be
most
affected
by
the
health
of
the
U.
S.
and
global
economy.
The
United
States
is
a
key
competitor
in
the
international
market
for
paper
products
and,
after
Canada,
is
the
largest
exporter
of
paper
products.
According
to
Haltmaier
(
1998),
the
largest
paper
and
allied
products
exporters
in
the
world
are
Canada
(
with
23
percent
of
the
market),
the
United
States
(
10
to
15
percent),
Finland
(
8
percent),
and
Sweden
(
7
percent).

4.5
Medicinal
Chemicals
and
Botanical
Products
and
Pharmaceutical
Preparations
(
SICs
2833,
2834/
NAICS
32451)

The
pharmaceutical
preparations
industry
(
SIC
2834/
NAICS
32451)
and
the
medicinal
chemicals
and
botanical
products
industry
(
SIC
2833/
NAICS
32451)
are
both
primarily
engaged
in
the
research,
development,
manufacture,
and/
or
processing
of
medicinal
chemicals
and
pharmaceutical
products.
Apart
from
manufacturing
drugs
for
human
and
veterinary
consumption,
the
industries
grind,
grade,
and
mill
botanical
products
that
are
inputs
for
other
industries.
Typically,
most
facilities
cross
over
into
both
industries
(
EPA,
1997a).
Products
include
drugs,
vitamins,
herbal
remedies,
and
production
inputs,
such
as
alkaloids
and
other
active
medicinal
principals.

Table
4­
13
presents
both
industries'
value
of
shipments
from
1987
to
1996.
Medicinals
and
botanicals'
performance
during
the
late
1980s
and
early
1990s
was
mixed.
However,
shipments
increased
steadily
from
1994
to
1996,
increasing
37.7
percent
as
natural
products
such
as
herbs
and
vitamins
became
more
popular
(
EPA,
1997a).
Pharmaceutical
preparations'
shipments
increased
steadily
over
the
10­
year
period.
From
1987
to
1996,
the
industry's
shipments
increased
24.3
percent
to
$
55.1
billion
in
1996.
Table
4­
13.
Value
of
Shipments
for
the
Medicinals
and
Botanicals
and
Pharmaceutical
Preparations
Industries,
1987
 
1996
Year
SIC
2833
Medicinals
&
Botanicals
($
106)
SIC
2834
Pharmaceutical
Preparations
($
106)

1987
4,629.1
44,345.7
1988
5,375.4
46,399.1
1989
5,708.9
48,083.6
1990
5,535.8
49,718.0
1991
6,637.7
49,866.3
1992
6,438.5
50,417.9
1993
5,669.2
50,973.5
1994
5,774.7
53,144.7
1995
6,404.1
53,225.9
1996
7,952.8
55,103.6
Sources:
U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1995a.
1992
Census
of
Manufactures,
Industry
Series:
Drug
Industry.
Washington,
DC:
Government
Printing
Office.

U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1990
 
1998.
Annual
Survey
of
Manufactures
[
Multiple
Years].
Washington,
DC:
Government
Printing
Office.
4­
16
4.5.1
Supply
Side
of
the
Industry
4.5.1.1
Production
Processes
The
medicinals
and
botanical
products
industry
and
the
pharmaceutical
preparations
industry
share
similar
production
processes.
Many
products
of
the
former
are
inputs
in
the
latter's
production
process.
There
are
three
manufacturing
stages:
research
and
development,
preparation
of
bulk
ingredients,
and
formulation
of
the
final
product.

The
research
and
development
stage
is
a
long
process
both
to
ensure
the
validity
and
benefit
of
the
end
product
and
to
satisfy
the
requirements
of
stringent
federal
regulatory
committees.
(
The
pharmaceutical
industry
operates
under
strict
oversight
of
the
Food
and
Drug
Administration
[
FDA].)
Therefore,
every
stage
in
the
development
of
new
drugs
is
thoroughly
documented
and
studied.
After
a
new
compound
is
discovered,
it
is
subjected
to
numerous
laboratory
and
animal
tests.
Results
are
presented
to
the
FDA
via
applications
that
present
and
fully
disclose
all
findings
to
date.
As
research
and
development
proceeds,
studies
are
gradually
expanded
to
involve
human
trials
of
the
new
compound.
Should
FDA
approve
the
compound,
the
new
product
is
readied
for
mass
production.

To
ensure
a
uniform
product,
all
ingredients
are
prepared
in
bulk
using
batch
processes.
Companies
produce
enough
of
each
ingredient
to
satisfy
projected
sales
demand
(
EPA,
1997a).
Prior
to
production,
all
equipment
is
thoroughly
cleaned,
prepared,
and
validated
to
prevent
any
contaminants
from
entering
the
production
cycle.
Most
ingredients
are
prepared
by
chemical
synthesis,
a
method
whereby
primary
ingredients
undergo
a
complex
series
of
processes,
including
many
intermediate
stages
and
chemical
reactions
in
a
step­
by­
step
fashion
(
EPA,
1997a).

After
the
bulk
materials
are
prepared,
they
are
converted
into
a
final
usable
form.
Common
forms
include
tablets,
pills,
liquids,
creams,
and
ointments.
Equipment
used
in
this
final
stage
is
prepared
in
the
same
manner
as
that
involved
in
the
bulk
preparation
process.
Clean
and
validated
machinery
is
used
to
process
and
package
the
pharmaceuticals
for
shipment
and
consumption.

4.5.1.2
Types
of
Output
Both
industries
produce
pharmaceutical
and
botanical
products
for
end
consumption
and
intermediate
products
for
the
industries'
own
applications.
Products
include
vitamins,
herbal
remedies,
and
alkaloids.
Prescription
and
over­
the­
counter
drugs
are
produced
in
liquid,
tablet,
cream,
and
other
forms.

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

4.5.1.4
Costs
of
Production
Table
4­
14
presents
SIC
2833
industry's
costs
of
production
and
employment
statistics
from
1987
to
1996.
Employment
was
stable
during
the
late
1980s
before
steadily
growing
in
the
1990s.
In
1987,
medicinals
and
botanicals
employed
11,600
people.
By
1996,
the
industry
employed
16,800,
an
increase
of
4­
17
nearly
45
percent.
Materials
costs
matched
the
increase
in
shipments
over
this
same
period.
Industry
growth
also
fed
new
capital
investments,
which
averaged
$
191.2
million
a
year
in
the
late
1980s
and
$
515.6
million
a
year
in
the
early
to
mid­
1990s.

SIC
2834'
s
costs
of
production
and
employment
for
1987
to
1996
are
presented
in
Table
4­
15.
The
number
of
people
employed
by
the
industry
ranged
between
123,000
and
144,000;
employment
peaked
in
1990
before
declining
by
21,000
jobs
by
the
end
of
1992.
During
this
10­
year
period,
the
cost
of
materials
rose
42.1
percent.
The
increase
is
associated
with
increased
product
shipments
and
the
development
of
new,
more
expensive
medications
(
Haltmaier,
1998).
New
capital
investment
averaged
$
2.3
billion
a
year.

4.5.1.5
Capacity
Utilization
Table
4­
16
presents
the
trend
in
these
ratios
from
1991
to
1996
for
both
industries.
The
varying
capacity
ratios
reflect
adjusting
production
volumes
and
new
production
facilities
and
capacity
going
both
on­
and
off­
line.
In
1996,
the
capacity
utilization
ratios
for
SICs
2833
and
2834
were
84
and
67,
respectively.
Table
4­
14.
Inputs
for
Medicinal
Chemicals
and
Botanical
Products
Industry
(
SIC
2833/
NAICS
32451),
1987
 
1996
Labor
Year
Quantity
(
103)
Payroll
($
106)
Materials
($
106)
New
Capital
Investment
($
106)

1987
11.6
520.2
2,229.3
158.2
1988
11.3
494.4
2,658.8
194.9
1989
11.4
504.9
3,118.4
263.4
1990
10.9
476.4
2,902.4
218.9
1991
12.5
568.6
3,368.2
512.9
1992
13.0
587.1
3,245.9
550.5
1993
13.0
584.3
2,638.4
470.0
1994
13.9
572.6
2,755.2
480.3
1995
14.1
625.0
3,006.0
356.2
1996
16.8
752.1
3,793.9
752.1
Sources:
U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1995a.
1992
Census
of
Manufactures,
Industry
Series:
Drug
Industry.
Washington,
DC:
Government
Printing
Office.

U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1990
 
1998.
Annual
Survey
of
Manufactures,
[
Multiple
Years].
Washington,
DC:
Government
Printing
Office.
4­
18
Table
4­
15.
Inputs
for
the
Pharmaceutical
Preparations
Industry
(
SIC
2834/
NAICS
32451),
1987­
1996
Labor
New
Capital
Investment
($
106)
Year
Quantity
(
103)
Payroll
($
106)
Materials
($
106)

1987
131.6
5,759.2
11,693.7
2,032.7
1988
133.4
5,447.2
12,634.8
2,234.0
1989
141.8
6,177.5
12,874.2
2,321.4
1990
143.8
6,223.9
13,237.6
2,035.3
1991
129.1
5,275.8
13,546.6
1,864.7
1992
122.8
4,949.4
13,542.5
2,450.0
1993
128.2
5,184.2
13,508.7
2,385.2
1994
134.2
5,368.4
13,526.1
2,531.9
1995
143.0
5,712.4
15,333.6
2,856.1
1996
136.9
5,547.3
16,611.1
2,317.0
Sources:
U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1995a.
1992
Census
of
Manufactures,
Industry
Series:
Drug
Industry.
Washington,
DC:
Government
Printing
Office.

U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1990
 
1998.
Annual
Survey
of
Manufactures,
[
Multiple
Years].
Washington,
DC:
Government
Printing
Office.
4­
19
4.5.2
Demand
Side
of
the
Industry
New
product
introductions
and
improvements
on
older
medications
by
the
drug
industry
have
greatly
improved
the
health
and
well­
being
of
the
U.
S.
population
(
Haltmaier,
1998).
Products
help
alleviate
or
reduce
physical,
mental,
and
emotional
ailments
or
reduce
the
severity
of
symptoms
associated
with
disease,
age,
and
degenerative
conditions.
Dietary
supplements,
such
as
vitamins
and
herbal
remedies,
ensure
that
consumers
receive
nutrients
of
which
they
may
not
ordinarily
consume
enough.
Products
are
available
in
a
range
of
dosage
types,
such
as
tablets
and
liquids.
Table
4­
16.
Capacity
Utilization
Ratios
for
the
Medicinal
Chemicals
and
Botanical
Products
(
SIC
2833/
NAICS
32451)
and
Pharmaceutical
Preparations
(
SIC
2834/
NAICS
32451)
Industries,
1991­
1996
1991
1992
1993
1994
1995
1996
SIC
2833/
NAICS
32451
84
86
89
80
90
84
SIC
2834/
NAICS
32451
76
74
70
67
63
67
Note:
Capacity
utilization
ratio
is
the
ratio
of
the
actual
production
level
to
the
full
production
level.
All
values
are
percentages.

Source:
U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1998.
Survey
of
Plant
Capacity:
1996.
Washington,
DC:
Government
Printing
Office.
4­
20
Although
prescription
medications
are
increasingly
distributed
through
third
parties,
such
as
hospitals
and
health
maintenance
organizations,
the
general
population
remains
the
end
user
of
pharmaceutical
products.
As
the
average
age
of
the
U.
S.
population
adjusts
to
reflect
large
numbers
of
older
people,
the
variety
and
number
of
drugs
consumed
increases.
An
older
population
will
generally
consume
more
medications
to
maintain
and
improve
quality
of
life
(
Haltmaier,
1998).

4.5.3
Organization
of
the
Industry
In
1992,
208
companies
produced
medicinal
chemicals
and
botanical
products
and
operated
225
facilities
(
see
Table
4­
17).
The
number
of
companies
and
facilities
in
1992
was
the
same
as
that
of
1987,
although
shipment
values
increased
almost
40
percent.
The
average
facility
employed
more
people
in
1992
than
in
1987.
In
fact,
the
number
of
facilities
employing
50
or
more
people
grew
from
37
to
45.
These
facilities
accounted
for
the
lion's
share
of
the
industry's
shipments.
According
to
the
Small
Business
Administration,
companies
in
this
SIC
code
are
considered
small
if
they
employ
fewer
than
750
employees.
It
is
unclear
what
percentage
of
the
facilities
listed
in
Table
4­
17
are
small
companies.

In
1992,
585
companies
manufactured
pharmaceutical
preparations
and
operated
691
facilities.
By
way
of
comparison,
640
companies
operated
732
facilities
in
1987.
Although
the
number
of
facilities
declined
by
41,
no
particular
category
lost
or
gained
an
exceptional
number
of
facilities.
The
biggest
movement
was
in
the
five
to
nine
employees
category,
which
lost
35
facilities.
4­
21
Table
4­
17.
Size
of
Establishments
and
Value
of
Shipments
for
the
Medicinal
Chemicals
and
Botanical
Products
(
SIC
2833/
NAICS
32451)
and
Pharmaceutical
Preparations
(
SIC
2834/
NAICS
32451)
Industries
1987
1992
Number
of
Employees
in
Establishment
Number
of
Facilities
Value
of
Shipments
($
106)
Number
of
Facilities
Value
of
Shipments
($
106)
SIC
2833/
NAICS
32451
1
to
4
employees
61
20.7
62
23.8
5
to
9
employees
34
38.6
42
58.3
10
to
19
employees
46
237.0
47
357.1
20
to
49
employees
47
287.3
29
182.0
50
to
99
employees
15
273.6
25
653.9
100
to
249
employees
12
520.6
10
5,163.4
250
to
499
employees
5
753.0
4
(
D)
500
to
999
employees
4
2478.2
3
(
D)
1,000
to
2,499
employees
1
(
D)
3
(
D)
Total
225
4629.1
225
6,438.5
SIC
2834/
NAICS
32451
1
to
4
employees
158
58.7
152
115.6
5
to
9
employees
108
178.8
73
105.4
10
to
19
employees
102
320.3
101
284.6
20
to
49
employees
117
932.5
110
815.7
50
to
99
employees
66
1231.0
65
1,966.8
100
to
249
employees
76
3596.0
77
2,912.4
250
to
499
employees
50
9239.7
56
11,394.6
500
to
999
employees
23
4946.9
30
10,077.7
1,000
to
2,499
employees
24
15,100.9
21
14,525.7
2,500
employees
or
more
8
8740.9
6
8,219.4
Total
732
44,345.7
691
50,417.9
(
D)
=
undisclosed
Sources:
U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1990a.
1987
Census
of
Manufactures,
Industry
Series:
Drug
Industry.
Washington,
DC:
Government
Printing
Office.

U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1995a.
1992
Census
of
Manufactures,
Industry
Series:
Drug
Industry.
Washington,
DC:
Government
Printing
4­
22
In
both
years,
facilities
4­
23
with
more
than
50
employees
accounted
for
at
least
95
percent
of
the
industry's
shipments.

Table
4­
18
presents
the
measures
of
market
concentration
for
both
industries.
For
the
medicinals
and
botanicals
industry,
the
CR4
was
76
in
1992,
and
the
CR8
was
84
(
U.
S.
Department
of
Commerce,
1995b).
The
highly
concentrated
nature
of
the
market
is
further
indicated
by
an
HHI
of
2,999
(
DOJ,
1992).
According
to
the
Department
of
Justice's
Horizontal
Merger
Guidelines,
industries
with
HHIs
above
1,800
are
less
competitive.

The
pharmaceuticals
preparations
industry
is
less
concentrated
than
the
medicinal
chemicals
and
botanical
products
industry.
For
SIC
2834,
the
CR4
and
CR8
were
26
and
42,
respectively,
in
1992.
The
industry's
HHI
was
341,
indicating
a
competitive
market.

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

4.6
Industrial
Organic
Chemicals
Industry
(
SIC
2869/
NAICS
3251)

The
industrial
organic
chemicals
(
not
elsewhere
classified)
industry
(
SIC
2869/
NAICS
3251)
produces
organic
chemicals
for
end­
use
applications
and
for
inputs
into
numerous
other
chemical
manufacturing
industries.
In
nominal
terms,
it
was
the
single
largest
segment
of
the
$
367
billion
chemical
and
allied
products
industry
(
SIC
28)
in
1996,
accounting
for
approximately
17
percent
of
the
industry's
shipments.

All
organic
chemicals
are,
by
definition,
carbon­
based
and
are
divided
into
two
general
categories:
commodity
and
specialty.
Commodity
chemical
manufacturers
compete
on
price
and
produce
large
volumes
of
staple
chemicals
using
continuous
manufacturing
processes.
Specialty
chemicals
cater
to
custom
Table
4­
18.
Measures
of
Market
Concentration
for
the
Medicinal
Chemicals
and
Botanical
Products
(
SIC
2833/
NAICS
32451)
and
Pharmaceutical
Preparations
(
SIC
2834/
NAICS
32451)
Industries
SIC
NAICS
Industry
CR4
CR8
HHI
Number
of
Companie
s
Number
of
Facilities
2833
32451
Medicinal
Chemicals
and
Botanical
Products
76
84
2,999
208
225
2834
32451
Pharmaceutical
Preparations
26
42
341
585
691
Sources:
U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1995b.
1992
Concentration
Ratios
in
Manufacturing.
Washington,
DC:
Government
Printing
Office.

U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1995a.
1992
Census
of
Manufactures,
Industry
Series:
Drug
Industry.
Washington,
DC:
Government
Printing
Office.
4­
24
markets,
using
batch
processes
to
produce
a
diverse
range
of
chemicals.
Specialty
chemicals
generally
require
more
technical
expertise
and
research
and
development
than
the
more
standardized
commodity
chemicals
industry
(
EPA,
1995c).
Consequently,
specialty
chemical
manufacturers
have
a
greater
value
added
to
their
products.
End
products
for
all
industrial
organic
chemical
producers
are
as
varied
as
synthetic
perfumes,
flavoring
chemicals,
glycerin,
and
plasticizers.

Table
4­
19
presents
the
shipments
of
industrial
organic
chemicals
from
1987
to
1996.
In
real
terms,
the
industry's
shipments
rose
in
the
late
1980s
to
a
high
of
$
54.9
billion
before
declining
in
the
early
1990s
as
the
U.
S.
economy
went
into
recession.
By
the
mid­
1990s,
the
industry
recovered,
as
product
values
reached
record
highs
(
Haltmaier,
1998).
Between
1993
and
1996,
the
industry's
shipments
grew
7.3
percent
to
$
57.7
billion.

4.6.1
Supply
Side
of
the
Industry
4.6.1.1
Production
Processes
Processes
used
to
manufacture
industrial
organic
chemicals
are
as
varied
as
the
end­
products
themselves.
There
are
thousands
of
possible
ingredients
and
hundreds
of
processes.
Therefore,
the
discussion
that
follows
is
a
general
description
of
the
ingredients
and
stages
involved
in
a
typical
manufacturing
process.

Essentially
a
set
of
ingredients
(
feedstocks)
is
combined
in
a
series
of
reactions
to
produce
end
products
and
intermediates
(
EPA,
1995c).
The
typical
chemical
synthesis
processes
incorporate
multiple
feedstocks
in
a
series
of
chemical
reactions.
Commodity
chemicals
are
produced
in
a
continuous
reactor,
and
specialty
chemicals
are
produced
in
batches.
Specialty
chemicals
may
undergo
a
series
of
reaction
steps,
as
opposed
to
commodity
chemicals'
one
continuous
reaction
because
a
finite
amount
of
ingredients
are
prepared
and
used
in
the
production
process.
Reactions
usually
take
place
at
high
temperatures,
with
one
or
two
additional
components
being
intermittently
added.
As
the
production
advances,
by­
products
are
Table
4­
19.
Value
of
Shipments
for
the
Industrial
Organic
Chemicals,
N.
E.
C.
Industry
(
SIC
2869/
NAICS
3251),
1987­
1996
Year
Value
of
Shipments
(
1992
$
106)

1987
48,581.7
1988
53,434.7
1989
54,962.9
1990
53,238.8
1991
51,795.6
1992
54,254.2
1993
53,805.2
1994
57,357.1
1995
59,484.3
1996
57,743.3
Sources:
U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1995b.
1992
Census
of
Manufactures,
Industry
Series:
Industrial
Organic
Chemicals.
Washington,
DC:
Government
Printing
Office.

U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1990
 
1998.
Annual
Survey
of
Manufactures,
Multiple
Years.
Washington,
DC:
Government
Printing
Office.
4­
25
removed
using
separation,
distillation,
or
refrigeration
techniques.
The
final
product
may
undergo
a
drying
or
pelletizing
stage
to
form
a
more
manageable
substance.

4.6.1.2
Types
of
Output
Miscellaneous
industrial
organic
chemicals
comprise
nine
general
categories
of
products:

aliphitic
and
other
acyclic
organic
chemicals
(
ethylene);
acetic,
chloroaceptic,
adipic,
formic,
oxalic,
and
tartaric
acids
and
their
metallic
salts;
chloral,
formaldehyde,
and
methylamine;

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

polyhydric
alcohols
(
synthetic
glycerin,
etc.);

synthetic
perfume
and
flavoring
materials
(
citral,
methyl,
oinone,
etc.);

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

cyclic
and
acyclic
plasticizers
(
phosphoric
acid,
etc.);

synthetic
tanning
agents;

chemical
warfare
gases;
and

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

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

4.6.1.4
Costs
of
Production
Of
all
the
factors
of
production,
employment
in
industrial
organic
chemicals
fluctuated
most
often
between
1987
and
1996
(
see
Table
4­
20).
During
that
time,
employment
fell
8.18
percent
to
92,100,
after
a
high
of
101,000
in
1991.
Most
jobs
lost
were
at
the
production
level
(
Haltmaier,
1998).
Facilities
became
far
more
computerized,
incorporating
advanced
technologies
into
the
production
process.
Even
with
the
drop
in
employment,
payroll
was
$
200
million
more
in
1995
than
in
1987.
The
cost
of
materials
fluctuated
between
$
29
and
$
36
billion
for
these
years,
and
new
capital
investment
averaged
$
3,646
million
a
year.
4­
26
4.6.1.5
Capacity
Utilization
Table
4­
21
presents
the
trend
in
capacity
utilization
ratios
from
1991
to
1996
for
the
industrial
organic
chemicals
industry.
The
varying
capacity
utilization
ratios
reflect
changes
in
production
volumes
and
new
production
facilities
and
capacities
going
on­
and
off­
line.
The
capacity
utilization
ratio
for
the
industry
averaged
85.3
over
the
6­
year
period
presented.

4.6.2
Demand
Side
of
the
Industry
Industrial
organic
chemicals
are
components
of
many
chemical
products.
Most
of
the
chemical
sectors
(
classified
under
SIC
28)
are
downstream
users
of
organic
chemicals.
These
sectors
either
purchase
commodity
chemicals
or
enter
into
contracts
with
industrial
organic
chemical
producers
to
obtain
specialty
chemicals.
Consumers
include
inorganic
chemicals
(
SIC
281),
plastics
and
synthetics
(
SIC
282),
drugs
(
283),
soaps
and
cleaners
(
SIC
284),
paints
and
allied
products
(
SIC
286),
and
miscellaneous
chemical
products
(
SIC
289).
Table
4­
20.
Inputs
for
the
Industrial
Organic
Chemicals
Industry
(
SIC
2869/
NAICS
3251),
1987
 
1996
Year
Labor
Materials
(
1992
$
106)
New
Capital
Investment
(
1992
$
106)
Quantity
(
103)
Payroll
(
1992
$
106)

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

U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1990
 
1998.
Annual
Survey
of
Manufactures.
Washington,
DC:
Government
Printing
Office.
4­
27
4.6.3
Organization
of
the
Industry
Although
the
industry's
value
of
shipments
increased
nearly
12
percent
between
1987
and
1992,
the
number
of
facilities
producing
industrial
organic
chemicals
only
increased
by
6
percent.
Facilities
with
100
or
more
employees
continued
to
account
for
the
majority
of
the
industry's
shipment
values.
For
example,
in
1992,
28
percent
of
all
facilities
had
100
or
more
employees
(
see
Table
4­
22),
and
these
facilities
produced
89
percent
of
the
industry's
shipment
values.
The
average
number
of
facilities
per
firm
was
1.4
in
both
years.
According
to
the
Small
Business
Administration,
an
industrial
organic
chemicals
company
is
considered
small
if
the
total
number
of
employees
does
not
exceed
500.
It
is
unclear
what
percentage
of
facilities
are
owned
by
small
businesses.

The
industrial
organic
chemicals
(
not
elsewhere
classified)
industry
is
unconcentrated
and
competitive.
The
CR4
was
29
and
the
CR8
43;
the
industry's
HHI
was
336.

4.6.4
Markets
and
Trends
The
U.
S.
industrial
organic
chemical
industry
is
expected
to
expand
through
2002
at
an
annual
rate
of
1.4
percent
(
Haltmaier,
1998).
U.
S.
producers
face
increasing
competition
domestically
and
abroad
as
chemical
industries
in
developing
nations
gain
market
share
and
increase
exports
to
the
United
States.
American
producers
will,
however,
benefit
from
decreasing
costs
for
raw
materials
and
energy
and
productivity
gains.
Table
4­
21.
Capacity
Utilization
Ratios
for
the
Industrial
Organic
Chemicals
Industry
(
SIC
2869/
NAICS
3251),
1991
 
1996
1991
1992
1993
1994
1995
1996
SIC
2869/
NAICS
3251
86
81
91
89
84
84
Note:
The
capacity
utilization
ratio
is
the
ratio
of
the
actual
production
level
to
the
full
production
level.

All
values
are
percentages.

Source:
U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1998.
Survey
of
Plant
Capacity:
1996.
Washington,
DC:
Government
Printing
Office.
4­
28
4.7
Electric
Services
(
SIC
4911/
NAICS
22111)

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
profile
provides
background
information
on
the
U.
S.
electric
power
industry
and
discusses
current
industry
characteristics
and
trends
that
will
influence
the
future
generation
and
consumption
of
electricity.
It
is
important
to
note
that
through
out
this
report
the
terms
"
boilers,"
"
process
heaters,"
and
"
units"
are
synonymous
with
"
ICI
boilers"
and
"
process
heaters."
Boilers
primarily
engaged
in
the
generation
of
electricity
are
not
covered
by
the
NESHAP
under
analysis
and
are
therefore
excluded
from
this
analysis.
Utility
sources
are
not
affected
by
this
NESHAP
except
for
a
small
number
of
nonfossil
fuel
units
within
this
industry.
Those
units
in
this
industry
that
are
affected
may
be
engaged
in
activities
such
as
heating
and
mechanized
work.

4.7.1
Electricity
Production
Figure
4­
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.
Table
4­
22.
Size
of
Establishments
and
Value
of
Shipments
for
the
Industrial
Organic
Chemicals
Industry
(
SIC
2869/
NAICS
3251)

1987
1992
Number
of
Employees
in
Establishment
Number
of
Facilities
Value
of
Shipments
(
1992
$
106)
Number
of
Facilities
Value
of
Shipments
(
1992
$
106)

1
to
4
employees
97
552.8
100
102.6
5
to
9
employees
80
200.9
80
208.7
10
to
19
employees
91
484.7
97
533.9
20
to
49
employees
137
1,749.9
125
1,701.5
50
to
99
employees
99
2556.3
106
3,460.9
100
to
249
employees
110
10,361.2
111
8,855.9
250
to
499
employees
41
17,156.9
41
9,971.1
500
to
999
employees
27
9,615.5
30
13,755.0
1,000
to
2,499
employees
11
9,184.6
10
9,051.0
2,500
or
more
employees
6
7,156.9
5
6,613.5
Sources:
U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1995b.
1992
Census
of
Manufactures,
Industry
Series:
Industrial
Organic
Chemicals.
Washington,
DC:
Government
Printing
Office.

U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1990b.
1987
Census
of
Manufactures,
Industry
Series,
Paints
and
Allied
Products.
Washington,
DC:
Government
Printing
Office.
4­
29
Commercial
and
retail
customers
were
in
essence
"
captive,"
and
rates
and
service
quality
were
primarily
determined
by
public
utility
commissions.

The
majority
of
utilities
are
interconnected
and
belong
to
a
regional
power
pool.
Pooling
arrangements
enable
facilities
to
coordinate
the
economic
dispatch
of
generation
facilities
and
manage
transmission
congestion.
In
addition,
pooling
diverse
loads
can
increase
load
factors
and
decrease
costs
by
sharing
reserve
capacity.

4.7.1.1
Generation
As
shown
in
Table
4­
23,
coal­
fired
plants
have
historically
accounted
for
the
bulk
of
electricity
generation
in
the
United
States.
With
abundant
national
coal
reserves
and
advances
in
pollution
abatement
technology,
such
as
advanced
scrubbers
for
pulverized
coal
and
flue
gas­
desulfurization
systems,
coal
will
likely
remain
the
fuel
of
choice
for
most
existing
generating
facilities
over
the
near
term.

Natural
gas
accounts
for
approximately
10
percent
of
current
generation
capacity
but
is
expected
to
grow;
advances
in
natural
gas
exploration
and
extraction
technologies
and
new
coal
gasification
have
contributed
to
the
use
of
natural
gas
for
power
generation.

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.

Table
4­
23.
Net
Generation
by
Energy
Source,
1995
Energy
Source
Utility
Generators
(
MWh)
Nonutility
Generators
(
MWh)
Total
(
MWh)

Fossil
fuels
2,021,064
287,696
2,308,760
Coal
1,652,914
63,440
Natural
gas
307,306
213,437
Petroleum
60,844
3,957
Nuclear
673,402
 
673,402
Hydroelectric
293,653
14,515
308,168
Renewable/
other
6,409
98,295
104,704
Total
2,994,582
400,505
3,395,033
Sources:
U.
S.
Department
of
Energy,
Energy
Information
Administration.
1996.
Electric
Power
Annual,
1995.
Vol.
1.
DOE/
EIA­
0348(
95/
1).
Washington,
DC:
U.
S.
Department
of
Energy.

U.
S.
Department
of
Energy,
Energy
Information
Administration.
1999b.
The
Changing
Structure
of
the
Electric
Power
Industry
1999:
Mergers
and
Other
Corporate
Combinations.
Washington,
DC:
U.
S.
Department
of
Energy.
4­
30
4.7.1.2
Transmission
Transmission
refers
to
high
voltage
lines
used
to
link
generators
to
substations
where
power
is
stepped
down
for
local
distribution.
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
Large
C/
I
Customers
Small
C/
I
Customers
Residential
Customers
Transformer
Generation
Electricity
Distribution
High
Voltage
Lines
Transmission
Power
Plants
Figure
4­
1.
Traditional
Electric
Power
Industry
Structure
4­
31

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.

4.7.1.3
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.

4.7.2
Cost
of
Production
Table
4­
24
shows
total
industry
expenditures
by
production
activities.
Generation
accounts
for
approximately
75.6
percent
of
the
cost
of
delivered
electric
power
in
1996.
Transmission
and
distribution
accounted
for
2.5
percent
and
5.6
percent,
respectively.
Customer
accounts
and
sales
and
administrative
costs
accounted
for
the
remaining
16.3
percent
of
the
cost
of
delivered
power.

4.7.3
Organization
of
the
Industry
Because
the
restructuring
plans
and
time
tables
are
made
at
the
state
level,
the
issues
of
asset
ownership
and
control
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.
This
section
focuses
on
the
generation
segment
of
the
market
because
all
the
boilers
affected
by
the
regulation
are
involved
in
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
4­
25,
approximately
42
percent
of
suppliers
are
utilities
and
58
percent
are
nonutilities.
Utilities
include
investorowned
cooperatives,
and
municipal
systems.
Of
the
approximately
3,100
4­
32
Table
4­
24.
Total
Expenditures
in
1996
($
103)

Utility
Ownership
Generation
Transmission
Distributio
n
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).
1998b.
Financial
Statistics
of
Major
Publicly
Owned
Electric
Utilities,
1997.
Washington,
DC:
U.
S.
Department
of
Energy.

U.
S.
Department
of
Energy,
Energy
Information
Administration
(
EIA).
1997.
Financial
Statistics
of
Major
U.
S.
Investor­
Owned
Electric
Utilities,
1996.
Washington,
DC:
U.
S.
Department
of
Energy.
4­
33
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
4­
2
illustrates
this
shift
in
the
share
of
utility
and
nonutility
generation.

4.7.3.1
Utilities
There
are
four
categories
of
utilities:
investor­
owned
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.

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.

Table
4­
25.
Number
of
Electricity
Suppliers
in
1999
Electricity
Suppliers
Number
Percent
Utilities
3,124
42%
Investor­
owned
utilities
222
Cooperatives
875
Municipal
systems
1,885
Public
power
districts
73
State
projects
55
Federal
agencies
14
Nonutilities
4,247
58%
Nonutilities
(
excluding
EWGs)
4,103
Exempt
wholesale
generators
144
Total
7,371
100%

Source:
U.
S.
Department
of
Energy,
Energy
Information
Administration
(
EIA).
1999b.
The
Changing
Structure
of
the
Electric
Power
Industry
1999:
Mergers
and
Other
Corporate
Combinations.
Washington,
DC:
U.
S.
Department
of
Energy.
4­
34
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).
1996.
Electric
Power
Annual
1995.
Volumes
I
and
II.
DOE/
EIA­
0348(
95)/
1.
Washington,
DC:
U.
S.
Department
of
Energy;
Table
8
(
and
previous
issues);
1985
nonutility
data:
Shares
of
generation
estimated
by
EIA;
total
generation
from
Edison
Electric
Institute
(
EEI).
1998.
Statistical
Yearbook
of
the
Electric
Utility
Industry
1998.
November.
Washington,
DC;
1995
nonutility
data:
U.
S.
Department
of
Energy,
Energy
Information
Administration
(
EIA).
1996.
Electric
Power
Annual
1995.
Volumes
I
and
II.
DOE/
EIA­
0348(
95)/
1.
Washington,
DC:
U.
S.
Department
of
Energy.

Figure
4­
2.
Utility
and
Nonutility
Generation
and
Shares
by
Class,
1988
and
1998
4­
35
Rural
electric
cooperatives
are
formed
and
owned
by
groups
of
residents
in
rural
areas
to
supply
power
to
those
areas.
Cooperatives
generally
purchase
from
other
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.

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.

4.7.3.2
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,
1998a).
More
than
4,200
nonutilities
operate
in
the
United
States.

4.7.4
Demand
Side
of
the
Industry
4.7.4.1
Electricity
Consumption
This
section
analyzes
the
growth
projections
for
electricity
consumption
as
well
as
the
price
elasticity
of
demand
for
electricity.
Growth
in
electricity
consumption
has
traditionally
paralleled
gross
domestic
product
growth.
However,
improved
energy
efficiency
of
electrical
equipment,
such
as
highefficiency
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
4­
26
shows
consumption
by
sector
of
the
economy
over
the
past
10
years.
The
table
shows
that
since
1989
electricity
sales
have
increased
at
least
10
percent
in
all
four
sectors.
The
commercial
sector
has
experienced
the
largest
increase,
followed
by
residential
consumption.

In
the
future,
residential
demand
is
expected
to
be
at
the
forefront
of
increased
electricity
consumption.
Between
1997
and
2020,
residential
demand
is
expected
to
increase
at
1.6
percent
annually.
Commercial
growth
in
demand
is
expected
to
be
approximately
1.4
percent,
while
4­
36
industry
is
expected
to
increase
demand
by
1.1
percent
(
DOE,
EIA,
1999a).
Figure
4­
3
shows
the
annual
electricity
sales
by
sector
from
1970
with
projections
through
2020.

The
literature
suggests
that
electricity
consumption
is
relatively
price
inelastic.
Consumers
are
generally
unable
or
unwilling
to
forego
a
large
amount
of
consumption
as
the
price
increases.
Numerous
studies
have
investigated
the
short­
run
elasticity
of
demand
for
electricity.
Overall,
the
studies
suggest
that,
for
a
1
percent
increase
in
the
price
of
electricity,
demand
will
decrease
by
0.15
percent.
However,
as
Table
4­
27
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,
1999c).
Table
4­
26.
U.
S.
Electric
Utility
Retail
Sales
of
Electricity
by
Sector,
1989
Through
1998
(
106
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).
1999d.
Electric
Power
Annual
1998.
Volumes
I
and
II.
Washington,
DC:
U.
S.
Department
of
Energy.

U.
S.
Department
of
Energy,
Energy
Information
Administration
(
EIA).
1996.
Electric
Power
Annual
1995.
Volumes
I
and
II.
Washington,
DC:
U.
S.
Department
of
Energy.
4­
37
4.7.4.2
Trends
in
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

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
Figure
4­
3.
Annual
Electricity
Sales
by
Sector
4­
38
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.
4­
39
Table
4­
27.
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
4­
40
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.

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.

References
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.
4­
41
Lemm,
Jamie.
2000.
"
Household
Furniture."
In
U.
S.
Industry
&
Trade
Outlook
2000.
New
York:
DRI/
McGraw­
Hill,
Standard
&
Poor's,
and
U.
S.
Department
of
Commerce/
International
Trade
Administration.

U.
S.
Department
of
Commerce,
Bureau
of
the
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1995a.
1992
Census
of
Manufactures,
Industry
Series:
Industrial
Organic
Chemicals.
Washington,
DC:
Government
Printing
Office.

U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1995b.
1992
Concentration
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in
Manufacturing.
Washington,
DC:
Government
Printing
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U.
S.
Department
of
Commerce,
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of
the
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2001.
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1997
Economic
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United
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As
obtained
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March
13,
2001.
<
http://
www.
census.
gov/
epcd/
ec97/
us/
US000_
31.
HTM>.

U.
S.
Department
of
Energy,
Energy
Information
Administration
(
EIA).
1998.
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).
1999a.
"
Annual
Energy
Outlook
1999
 
Market
Trend
 
Electricity."
http://
www.
eia.
doe.
gov/
oiaf/
aeo99/
electricity.
html.
As
accessed
November
15,
1999.

U.
S.
Department
of
Energy,
Energy
Information
Administration
(
EIA).
1999b.
The
Changing
Structure
of
the
Electric
Power
Industry
1999:
Mergers
and
Other
Corporate
Combinations.
Washington,
DC:
U.
S.
Department
of
Energy.

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

U.
S.
Department
of
Justice.
1992.
Horizontal
Merger
Guidelines.
Washington,
DC:
U.
S.
Department
of
Justice.

U.
S.
Environmental
Protection
Agency
(
EPA),
Office
of
Compliance
Sector
Notebook
Project.
1995a.
Profile
of
the
Lumber
and
Wood
Products
Industry.
Washington,
DC.

U.
S.
Environmental
Protection
Agency
(
EPA),
Office
of
Compliance
Sector
Notebook
Project.
1995b.
Profile
of
the
Pulp
and
Paper
Industry.
Washington,
DC:
U.
S.
Environmental
Protection
Agency.

U.
S.
Environmental
Protection
Agency
(
EPA),
Office
of
Compliance
Sector
Notebook
Project.
1995c.
Profile
of
the
Organic
Chemical
Industry.
Washington,
DC:
U.
S.
Environmental
Protection
Agency.

U.
S.
Environmental
Protection
Agency
(
EPA).
1997a.
EPA
Office
of
Compliance
Sector
Notebook
Project:
Profile
of
the
Pharmaceutical
Manufacturing
Industry.
Washington,
DC:
U.
S.
Environmental
Protection
Agency.
5­
42
U.
S.
Environmental
Protection
Agency
(
EPA).
1997b.
Regulatory
Impact
Analysis
of
Air
Pollution
Regulations:
Utility
and
Industrial
Boilers.
Research
Triangle
Park,
NC:
U.
S.
Environmental
Protection
Agency.

CHAPTER
5
ECONOMIC
ANALYSIS
METHODOLOGY
The
rule
to
control
emissions
of
HAPs
from
industrial,
commercial,
and
institutional
boilers
and
process
heaters
will
affect
almost
all
sectors
of
the
U.
S.
economy.
Several
markets
will
bear
the
direct
compliance
costs.
In
addition,
sectors
that
consume
energy
will
also
bear
indirect
costs
through
higher
prices
for
energy.
Finally,
consumers
of
goods
and
services
will
experience
impacts
from
higher
market
prices.

This
chapter
presents
the
methodology
for
analyzing
the
economic
impacts
of
the
NESHAP.
This
economic
analysis
provides
the
economic
data
and
supporting
information
needed
by
EPA
to
support
its
regulatory
determination.
The
methodology
to
operationalize
this
theory
is
based
on
microeconomic
theory
and
the
methods
developed
for
earlier
EPA
studies.
These
methods
are
tailored
to
and
extended
for
this
analysis,
as
appropriate,
to
meet
EPA's
requirements
for
an
EIA
of
controls
placed
on
boilers
and
process
heaters.

This
methodology
chapter
includes
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
with
emphasis
on
the
links
between
energy
markets
and
the
markets
for
goods
and
services.
Appendix
A
of
this
RIA
includes
a
description
of
the
model's
baseline
data
set
and
specifications.

5.1
Background
on
Economic
Modeling
Approaches
5­
1
In
general,
the
EIA
methodology
needs
to
allow
EPA
to
consider
the
effects
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
determining
the
approach
for
this
study.
The
advantages
and
disadvantages
of
different
modeling
approaches
are
discussed
below.

5.1.1
Modeling
Dimension
1:
Scope
of
Economic
Decisionmaking
Models
incorporating
different
levels
of
economic
decisionmaking
can
generally
be
categorized
as
with
behavior
responses
and
without
behavior
responses
(
accounting
approach).
Table
5­
1
provides
a
brief
comparison
of
the
two
approaches.
The
nonbehavioral
approach
essentially
holds
fixed
all
interactions
between
facility
production
and
market
forces.
It
assumes
that
firms
absorb
all
control
costs
and
consumers
do
not
face
any
of
the
costs
of
regulation.
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
determine
the
regulation's
impact.

In
contrast,
the
behavioral
approach
is
grounded
in
economic
theory
related
to
producer
and
consumer
behavior
in
response
to
changes
in
market
conditions.
Owners
of
affected
facilities
are
economic
agents
that
can,
and
presumably
will,
make
adjustments
such
as
changing
production
rates
or
altering
input
mixes
that
will
generally
affect
the
market
environment
in
which
they
operate.
As
producers
change
their
behavior
in
response
to
regulation,
consumers
are
typically
faced
with
changes
in
prices
that
cause
them
to
alter
the
quantity
that
they
are
willing
to
purchase.
In
essence,
this
approach
models
the
expected
reallocation
of
society's
resources
in
response
to
a
regulation.
The
changes
in
price
and
production
from
the
market­
level
impacts
are
used
to
estimate
the
distribution
of
social
costs
between
consumers
and
producers.

5.1.2
Modeling
Dimension
2:
Interaction
Between
Economic
Sectors
Table
5­
1.
Comparison
of
Modeling
Approaches
EIA
With
Behavioral
Responses
°
Incorporates
control
costs
into
production
function
°
Includes
change
in
quantity
produced
°
Includes
change
in
market
price
°
Estimates
impacts
for

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
5­
2
Because
of
the
large
number
of
markets
potentially
affected
by
the
regulation
on
boilers
and
process
heaters,
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,
the
regulation
affects
all
commodities
and
markets
to
some
extent.
For
example,
controls
on
boilers
and
process
heaters
may
indirectly
affect
almost
all
markets
for
goods
and
services
to
some
extent
because
the
cost
of
fuel
(
an
input
in
the
provision
of
most
goods
and
services)
is
likely
to
increase
with
the
regulation
in
effect.
However,
the
impact
of
rising
fuel
prices
will
differ
greatly
between
different
markets
depending
on
how
important
fuel
is
as
an
input
in
that
market.

The
appropriate
level
of
market
interactions
to
be
included
in
the
EIA
is
determined
by
the
scope
of
the
regulation
across
industries
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
into
three
groups:

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.
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
prices
and
quantities
across
all
markets
simultaneously.
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.

5.2
Selected
Modeling
Approach
for
Boilers
and
Process
Heaters
Analysis
To
conduct
the
analysis
for
the
boilers
and
process
heaters
MACT,
the
Agency
used
a
market
modeling
approach
that
incorporates
behavioral
responses
in
a
multiple­
market
partial
equilibrium
model
as
described
above.
This
approach
allows
for
a
more
realistic
assessment
of
the
distribution
of
impacts
across
different
groups
than
the
nonbehavioral
approach,
which
may
be
especially
important
in
accurately
assessing
the
impacts
of
a
significant
rule
affecting
numerous
industries.
Because
of
the
size
and
complexity
of
this
regulation,
it
is
important
to
use
a
behavioral
model
to
examine
the
distribution
of
costs
across
society.
Because
the
regulations
on
boilers
and
process
heaters
primarily
affect
energy
costs,
an
input
into
many
production
processes,
complex
market
interactions
need
to
be
captured
to
provide
an
accurate
picture
of
the
distribution
of
regulatory
costs.
Because
of
the
large
number
of
affected
industries
under
this
MACT,
an
appropriate
model
should
include
multiple
markets
and
the
interactions
between
them.
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
regulation's
impact.
6These
markets
are
defined
at
the
two­
and
three­
digit
NAICS
code
level.
This
allows
for
a
fairly
disaggregated
examination
of
the
regulation's
impact
on
producers.
However,
if
the
costs
of
the
regulation
are
concentrated
on
a
particular
subset
of
one
of
these
markets,
then
treating
the
cost
as
if
it
fell
on
the
entire
NAICS
code
may
still
underestimate
the
impacts
on
the
subset
of
producers
affected
by
the
regulation.

5­
3
The
model
used
for
this
analysis
includes
energy,
agriculture,
manufacturing,
mining,
commercial,
and
transportation
markets
affected
by
the
controls
placed
on
boilers
and
process
heaters.
6
The
energy
markets
are
divided
into
natural
gas,
petroleum
products,
coal,
and
electricity.
The
residential
sector
is
treated
as
a
single
representative
demander
in
the
energy
markets.

Figure
5­
1
presents
an
overview
of
the
key
market
linkages
included
in
the
economic
impact
model
used
for
analyzing
the
boilers
and
process
heaters
MACT.
The
analysis'
emphasis
is
on
the
energy
supply
chain
and
the
consumption
of
energy
by
producers
of
goods
and
services.
The
industries
most
directly
affected
by
the
boilers
and
process
heaters
MACT
are
the
electricity
industry,
chemical
industry
and
pulp
and
paper
industry.
However,
changes
in
the
equilibrium
prices
and
quantities
of
energy
and
goods
and
services
affect
all
sectors
of
the
economy.
(
See
Figure
5­
1.)
This
analysis
explicitly
models
the
linkages
between
these
market
segments
to
capture
both
the
direct
costs
of
compliance
and
the
indirect
costs
due
to
changes
in
prices.
For
example,
production
costs
will
increase
for
chemical
companies
using
boilers
and
process
heaters
as
a
result
of
the
capital
investments
and
monitoring
costs,
as
well
as
the
resulting
increase
in
the
price
of
electricity
used
as
an
energy
input
in
the
production
process.

The
economic
model
also
captures
behavioral
changes
of
producers
of
goods
and
services
that
feedback
into
the
energy
markets.
Changes
in
production
levels
and
fuel
switching
in
the
manufacturing
process
affect
the
demand
for
Btus
in
fuel
markets.
The
change
in
output
is
determined
by
the
size
of
the
cost
increase
per
Btu
(
typically
variable
cost
per
output),
the
facility's
production
function
(
slope
of
supply
curve),
and
the
demand
characteristics
of
the
facility's
downstream
market
(
other
market
suppliers
and
market
demanders).
For
example,
if
consumers'
demand
for
a
product
is
not
very
sensitive
to
price,
then
producers
can
pass
the
majority
of
the
cost
of
the
regulation
through
to
consumers
and
output
may
not
change
appreciably.
However,
if
only
a
small
proportion
of
market
output
is
produced
by
producers
affected
by
the
regulation,
then
competition
will
prevent
the
affected
producers
from
raising
their
prices
significantly.

One
possible
feedback
pathway
that
this
analysis
does
not
model
is
technical
changes
in
the
manufacturing
process.
For
example,
if
the
cost
of
Btus
increases,
a
facility
may
use
measures
to
increase
manufacturing
efficiency
or
capture
waste
heat.
Facilities
could
also
possibly
change
the
5­
4
 
demand
oil
Oil
Supply
Exogenous
Demand
Endogenous
 
demand
NG
Gas
 
demand
coal
Coal
Industry
A
Btu
Production
Manufacturing
Process
Industry
B
Regulatory
Costs
Energy
Consumption
Fuel
Markets
 
supply
product
A
Product
A
Supply
Endogenous
Demand
Exogenous
Goods
and
Services
Markets
Industry
Z
Residential
Households
Commercial
Businesses
 
demand
elec
Electricity
Electricity
Market
Supply
Exogenous
Demand
Endogenous
   
Transportation
Figure
5­
1.
Links
Between
Energy
and
Goods
and
Services
Markets
5­
5
input
mix
that
they
use,
substituting
other
inputs
for
fuel.
These
facility­
level
responses
will
also
act
to
reduce
pollution,
but
including
these
responses
is
beyond
the
scope
of
this
analysis.

5.2.1
Directly
Affected
Markets
Markets
where
boilers
and
process
heaters
are
used
as
an
input
to
production
are
considered
to
be
directly
affected.
As
outlined
in
Chapter
3,
facilities
using
several
types
of
boilers
or
process
heaters
will
be
required
to
add
controls.
In
addition,
a
larger
population
of
boilers
and
process
heaters
will
incur
monitoring
costs
to
comply
with
the
regulation.
Therefore,
the
regulation
will
increase
their
production
costs
and
cause
these
directly
affected
firms
to
reduce
the
quantity
that
they
are
willing
to
supply
at
any
given
price.

5.2.1.1
Electricity
Market
Boilers
are
used
to
generate
power
throughout
the
electricity
industry.
Even
though
utility
boilers
are
not
covered
under
this
regulation,
the
Agency
estimates
over
300
industrial,
commercial,
and
institutional
boilers
involved
in
providing
electric
services
(
SIC
4911/
NAICS22111)
will
be
affected.
Most
of
these
are
owned
by
municipal
electric
service
providers.

For
this
study,
the
electricity
market
was
modeled
as
a
nationally
competitive
market.
The
electricity
market
is
modeled
this
ways
primarily
due
to
tractability
concerns.
Given
the
difficulty
in
ascertaining
how
many
States
would
decide
to
deregulate
their
electricity
markets,
a
competitive
electricity
market
was
the
most
reasonable
approach
for
this
modeling
exercise.
The
direct
costs
of
compliance
on
affected
boilers
lead
to
an
upward
shift
in
the
total
market
supply
for
electricity.
Figure
5­
2
illustrates
the
shifts
in
the
supply
curve
for
a
representative
energy
market.
In
addition
to
the
direct
costs,
the
market
for
electricity
will
also
be
indirectly
affected
through
changes
in
fuel
prices.
Electricity
generators
are
extremely
large
consumers
of
coal,
natural
gas,
and
petroleum
products.
For
example,
some
of
the
impact
of
control
costs
on
the
petroleum
industry
will
be
on
the
electricity
industry
in
the
form
of
higher
prices.
Indirect
costs
will
also
lead
to
an
upward
shift
in
the
supply
curve.

The
demand
for
electricity
is
derived
by
aggregating
across
the
goods
and
services
markets
and
the
residential
sector.
Because
of
direct
compliance
costs
on
the
goods
and
services
markets,
the
demand
curve
for
electricity
will
shift
downward.
Therefore,
it
is
ambiguous
whether
equilibrium
quantity
will
rise
or
fall.
The
changes
in
the
price
and
quantity
are
determined
by
the
relative
magnitude
of
the
shifts
in
the
price
elasticities
of
the
supply
and
demand
curves.
5­
6
P
1
P
0
Q
11
Q
10
(
a)
Producers
bearing
control
costs
(
affected)
S
11
S
10
$

Quantity
$
$

Quantity
Q
20
Q
21
(
b)
Producers
bearing
no
control
costs
(
unaffected)
S
20
Quantity
(
c)
Total
Market
Q
T1
Q
T0
D
S
T0
S
T1
P0
=
market
price
without
regulation
P1
=
market
price
with
regulation
S10
=
supply
function
for
affected
firms
without
regulation
S11
=
supply
function
for
affected
firms
with
regulation
Q10
=
quantity
sold
for
affected
firms
without
regulation
Q11
=
quantity
sold
for
affected
firms
with
regulation
S20
=
supply
function
for
unaffected
firms
both
with
and
without
regulation
Q20
=
quantity
sold
for
unaffected
firms
without
regulation
Q21
=
quantity
sold
for
unaffected
firms
with
regulation
ST0
=
total
market
supply
function
without
regulation
ST1
=
total
market
supply
function
with
regulation
QT0
=
total
market
quantity
sold
without
regulation
QT1
=
total
market
quantity
sold
with
regulation
Figure
5­
2.
Market
Effects
of
Regulation­
Induced
Costs
5.2.1.2
Petroleum
Market
Control
costs
associated
with
boilers
and
process
heaters
will
increase
the
cost
of
refining
petroleum
products.
The
supply
curve
for
petroleum
products
will
shift
upward
by
the
proportional
increase
in
total
production
costs
caused
by
the
control
costs
on
boilers
and
process
heaters.
For
petroleum
products,
a
single
composite
product
was
used
to
model
market
adjustment
because
boilers
and
process
heaters
are
used
throughout
the
refinement
process,
from
distillation
to
reformulation.
In
addition,
examining
the
full
heterogeneity
of
petroleum
products
and
the
impacts
to
all
specific
end
products
would
require
a
model
of
much
greater
complexity
than
this
one.
As
a
result,
assigning
costs
to
specific
end
products
and
estimating
economic
impacts
to
them,
such
as
fuel
oil
#
2
or
reformulated
gasoline,
is
difficult.
The
use
of
a
composite
product
tends
to
understate
the
impacts
for
petroleum
products
where
compliance
costs
as
a
percentage
of
production
costs
are
greater
than
average
and
overstate
impacts
for
products
where
compliance
costs
as
a
percentage
of
production
costs
are
less
than
average.
5­
7
Btu
Production
Decision
Output
Market
 
Fuel
Use
 
Output
 
$/
Btu
Production
Decision
$/
Btu
 
$/
Btu
Fuel
Markets
Compliance
Costs
Figure
5­
3.
Fuel
Market
Interactions
with
Facility­
Level
Production
Decisions
5.2.1.3
Goods
and
Services
Markets:
Agriculture,
Manufacturing,
Mining,
Commercial,
and
Transportation
Many
manufacturing
facilities
use
boilers
and
process
heaters
in
their
production
processes
to
generate
steam
and
process
heat.
Commercial
entities
use
boilers
for
space
heating
and
to
generate
supplementary
electricity.
In
addition
to
the
direct
costs
of
the
regulation,
goods
and
services
markets
are
indirectly
affected
through
price
increases
in
the
energy
markets.

Directly
affected
producers
are
segmented
into
sectors
defined
at
the
two­
or
three­
digit
NAICS
code
level.
A
partial
equilibrium
analysis
was
conducted
for
each
sector
to
model
the
supply
and
demand.
Changes
in
production
levels
and
fuel
switching
due
to
the
regulation's
impact
on
the
price
of
Btus
were
then
linked
back
into
the
energy
markets.

The
impact
of
the
regulation
on
producers
in
these
sectors
was
modeled
as
an
increase
in
the
cost
of
Btus
used
in
the
production
process.
In
this
context,
Btus
refer
to
the
generic
energy
requirements
used
to
generate
process
heat,
process
steam,
or
shaft
power.
Compliance
costs
associated
with
the
regulation
will
increase
the
cost
of
Btu
production
in
the
manufacturing
sectors.
The
cost
of
Btu
production
for
industry
increases
because
of
both
direct
control
costs
on
boilers
and
process
heaters
owned
by
manufacturers,
and
increases
in
the
price
of
fuels.
Because
Btus
are
an
input
into
the
production
process,
these
price
increases
lead
to
an
upward
shift
in
the
facility
(
and
industry)
supply
curves
as
shown
in
Figure
5­
2,
leading
to
a
change
in
the
equilibrium
market
price
and
quantity.

The
changes
in
equilibrium
supply
and
demand
in
each
market
are
modeled
to
estimate
the
regulation's
impact
on
each
sector.
In
a
perfectly
competitive
market,
the
point
where
supply
equals
demand
determines
the
market
price
and
quantity,
so
market
price
and
quantity
are
determined
by
solving
the
model
for
the
price
where
the
quantity
supplied
and
the
quantity
demanded
are
equal.
The
size
of
the
regulation­
induced
shifts
in
the
supply
curve
is
a
function
of
the
total
direct
control
costs
associated
with
boilers
and
process
heaters
and
the
indirect
fuel
costs
(
determined
by
the
change
in
fuel
price
and
intensity
of
use)
in
each
goods
and
services
market.
The
proportional
shift
in
the
supply
curve
is
determined
by
the
ratio
of
total
control
costs
(
both
direct
and
indirect)
to
total
revenue.

This
impact
on
the
price
of
Btus
facing
industrial
users
feeds
back
to
the
fuel
market
in
two
ways
(
see
Figure
5­
3).
The
first
is
through
the
company's
input
decision
concerning
the
fuel(
s)
that
will
be
used
for
its
manufacturing
process.
As
the
cost
of
Btus
increases,
firms
may
switch
fuels
and/
or
change
production
processes
to
increase
energy
efficiency
and
reduce
the
number
of
Btus
required
per
unit
of
output.
Fuel
switching
impacts
were
modeled
using
cross­
price
elasticities
of
demand
between
energy
sources.
For
example,
a
cross­
price
elasticity
of
demand
between
natural
gas
and
electricity
of
0.5
implies
that
a
1
percent
increase
in
the
price
of
electricity
will
lead
to
a
0.5
percent
increase
in
the
demand
for
7Long­
run
production
decisions
of
fuel
switching
and
increased
energy
efficiency
are
captured
by
the
crossand
own­
price
elasticities
in
the
energy
markets.

5­
8
natural
gas.
Own­
price
elasticities
of
demand
are
used
to
estimate
the
change
in
the
use
of
fuel
by
demanders.
For
example,
a
demand
elasticity
of
 
0.175
for
electricity
implies
that
a
1
percent
increase
in
the
price
of
electricity
will
lead
to
a
0.175
percent
decrease
in
the
quantity
of
electricity
demanded.

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,
energy
price
increases
lead
to
an
upward
shift
in
the
facility
supply
curves
(
not
modeled
individually).
This
leads
to
an
upward
shift
in
the
industry
supply
curve
when
the
shifts
at
the
facility
level
are
aggregated
across
facilities.
A
shift
in
the
industry
supply
curve
leads
to
a
change
in
the
equilibrium
market
price
and
quantity.
In
a
perfectly
competitive
market,
the
point
where
supply
equals
demand
determines
the
new
market
price
and
quantity.
The
Agency
modeled
the
feedback
into
the
energy
market
by
assuming
that
the
percentage
change
in
output
in
the
manufacturing
sectors
translates
into
a
equivalent
percentage
change
in
the
demand
for
energy
(
Btus).
This
implies
that
there
are
constant
returns
to
scale
from
energy
inputs
in
the
manufacturing
process
over
the
relevant
range
of
output
and
time
period
of
analysis.
This
is
an
appropriate
assumption
for
this
analysis
because
the
output
changes
in
these
sectors
being
modeled
are
relatively
small
(
always
less
than
1
percent)
and
reflect
short­
run
production
decisions.
7
The
Agency
assumed
that
the
demand
curves
for
goods
and
services
in
all
sectors
are
unchanged
by
the
regulation.
However,
because
the
demand
function
quantifies
the
change
in
quantity
demanded
in
response
to
a
change
in
price,
the
baseline
demand
conditions
are
important
in
determining
the
regulation's
impact.
The
key
demand
parameters
are
the
elasticities
of
demand
with
respect
to
changes
in
the
price
of
goods
and
services.
For
these
markets,
a
"
reasonable"
range
of
elasticity
values
is
assigned
based
on
estimates
from
similar
commodities.
Because
price
changes
are
anticipated
to
be
small,
the
point
elasticities
at
the
original
price
and
quantity
should
be
applicable
throughout
the
relevant
range
of
prices
and
quantities
examined
in
this
model.

For
more
information
on
how
these
energy
markets
are
modeled
in
this
analysis,
please
refer
to
Appendix
B
of
the
RIA.

5.2.2
Indirectly
Affected
Markets
In
addition
to
the
many
markets
that
are
directly
affected
by
the
regulation
on
boilers
and
process
heaters,
some
markets
feel
the
regulation's
impacts
despite
having
no
direct
costs
resulting
from
the
regulation.
Firms
in
these
markets
generally
face
changes
in
the
price
of
energy
that
affect
their
production
decisions.

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

The
demand
for
coal
from
the
industrial
sectors
will
be
affected
by
differences
in
compliance
costs
by
fuel
type
applied
to
boilers
and
process
heaters
in
the
industrial
sectors.
Because
compliance
costs
are
high
for
coal­
fired
units,
manufacturers
will
switch
away
from
coal
units
toward
natural
gas
units
with
lower
compliance
costs.
However,
the
overall
impact
on
the
demand
for
coal
is
ambiguous
because
the
relative
increase
in
the
cost
of
producing
Btus
by
burning
coal
will
be
offset
by
the
relative
decrease
in
the
price
of
coal.
Similarly,
the
demand
for
coal
by
utility
generators
will
be
affected
through
changes
in
the
relative
price
of
alternative
(
noncoal)
energy
sources
and
direct
costs
on
coal
boilers.

5.2.2.2
Natural
Gas
Market
The
natural
gas
market
is
included
in
the
economic
model
to
complete
coverage
of
the
energy
markets.
EPA
projects
that
there
are
no
direct
and
minimal
indirect
impacts
on
the
production
costs
of
natural
gas.
However,
the
demand
for
natural
gas
will
increase
because
of
the
relative
decrease
in
the
price
of
natural
gas
and
the
lower
relative
compliance
costs
for
gas­
fired
boilers
and
process
heaters.
5­
9
5.2.2.3
Goods
and
Services
Markets
Some
goods
and
services
markets
do
not
include
any
boilers
or
process
heaters
and
are
therefore
not
directly
affected
by
the
regulation.
However,
these
markets
will
still
be
affected
indirectly
because
of
the
changes
in
energy
prices
that
they
will
face
following
the
regulation.
There
will
be
a
tendency
for
these
users
to
shift
away
from
electricity
and
petroleum
products
and
towards
natural
gas
and
coal.

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

5.3
Operationalizing
the
Economic
Impact
Model
Figure
5­
4
illustrates
the
linkages
used
to
operationalize
the
estimation
of
economic
impacts
associated
with
the
compliance
costs.
Compliance
costs
placed
on
boilers
and
process
heaters
shift
the
supply
curve
for
electricity
and
petroleum
products.
Adjustments
in
the
electricity
and
petroleum
energy
markets
determine
the
share
of
the
cost
increases
that
producers
(
electric
service
providers
and
petroleum
companies)
and
consumers
(
product
manufacturers,
commercial
business,
and
residential
households)
bear.

The
supply
and
demand
relationships
between
the
energy
markets
are
fully
modeled.
For
example,
changes
in
electricity
production
feed
back
and
affect
the
demand
for
coal,
natural
gas
and
petroleum
products.
Similar
changes
in
refinery
production
affect
the
petroleum
industry's
demand
for
electricity.

Manufacturers
experience
supply
curve
shifts
due
to
control
costs
on
affected
boilers
and
process
heaters
they
operate
and
changes
in
prices
for
natural
gas,
petroleum,
electricity,
and
coal.
The
share
of
these
costs
borne
by
producers
and
consumers
is
determined
by
the
new
equilibrium
price
and
quantity
in
the
goods
and
services
markets.
Changes
in
manufacturers'
Btu
demands
due
to
fuel
switching
and
changes
in
production
levels
feed
back
into
the
energy
markets.

Adjustments
in
price
and
quantity
in
all
markets
occur
simultaneously.
A
computer
model
was
used
to
numerically
simulate
market
adjustments
by
iterating
over
commodity
prices
until
equilibrium
is
reached
(
i.
e.,
until
the
quantity
supplied
equals
the
quantity
demanded
in
all
markets
being
modeled).
Using
the
results
provided
by
the
model,
economic
impacts
of
the
regulation
(
changes
in
consumer
and
producer
surplus)
were
estimated
for
all
sectors
of
the
economy
being
modeled.
5­
10
 
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
(
 
Fuel
Prices)

P
 
Q
Q
Energy
Consumption
Goods
and
Services
Markets
Fuel
Markets
Fuel
Prices
Fuel
Prices
Fuel
Prices
Fuel
Prices
 
Production
Process
(
Fuel
Switching)
 
Production
Levels
Supply
Price
P
=
market
price
of
output
Q
=
quantity
sold
of
output
   
Transportation
Commercial
Businesses
Fuel
Prices
Regulatory
Costs
Fuel
Prices
Residential
Households
Figure
5­
4.
Operationalizing
the
Estimation
of
Economic
Impact
8Pechan
reports
the
results
of
their
literature
review
in
Appendix
B.
Point
estimates
are
provided
by
SIC
code.

5­
11
5.3.1
Computer
Model
The
computer
model
comprises
a
series
of
computer
spreadsheet
modules.
The
modules
integrate
the
engineering
cost
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.

Current
prices
and
production
levels
are
used
to
calibrate
the
baseline
scenario
(
without
regulation)
for
the
model.
Then,
the
compliance
costs
associated
with
the
regulation
are
introduced
as
a
"
shock"
to
the
system,
and
the
supply
and
demand
for
market
commodities
are
allowed
to
adjust
to
account
for
the
increased
production
costs
resulting
from
the
regulation.
Using
an
iterative
process,
if
the
supply
does
not
equal
demand
in
all
markets,
a
new
set
of
prices
is
"
called
out"
and
sent
back
to
producers
and
consumers
to
"
ask"
what
quantities
they
would
supply
and
demand
based
on
these
new
prices.
This
technique
is
referred
to
as
an
auctioneer
approach
because
new
prices
are
continually
called
out
until
an
equilibrium
set
of
prices
is
determined
(
i.
e.,
where
supply
equals
demand
for
all
markets).

Supply
and
demand
quantities
are
computed
at
each
price
iteration.
The
market
supply
for
each
market
is
obtained
by
using
a
mathematical
specification
of
the
supply
function,
and
the
key
parameter
is
the
point
elasticity
of
supply
at
the
baseline
condition.
Supply
elasticities
are
traditionally
the
most
difficult
to
obtain
from
prior
sources
and
analyses.
As
a
result,
EPA
used
an
assumed
value
of
0.75
for
21
of
the
25
manufacturing,
agriculture,
other
mining,
transportation,
and
commercial
industries.
The
remaining
4
supply
elasticities
(
for
the
textile
mills,
textile
products,
primary
metals,
and
other
mining
industries)
were
obtained
from
a
previous
report
conducted
for
EPA
by
E.
H.
Pechan
and
Associates,
Inc
(
1997),
and
studies
by
Warfield,
et
al
(
2001)
and
the
U.
S.
International
Trade
Commission
(
2001)
8.
EPA
is
currently
using
the
last
two
studies
to
study
the
economic
impacts
of
MACT
standards
for
the
Fabric
Coatings,
Taconite,
and
Steel
Industries.
Table
5­
2
lists
the
supply
elasticities
for
the
markets
used
in
the
model.

The
demand
curves
for
the
energy
markets
are
the
sum
of
demand
responses
across
all
markets.
The
demand
for
energy
in
the
manufacturing
sectors
is
a
derived
demand
calculated
using
baseline
energy
usage
and
changes
associated
with
fuel
switching
and
changes
in
output
levels.
Similarly,
the
energy
demand
in
residential
sectors
is
obtained
through
mathematical
specification
of
a
demand
function
(
see
Appendix
A).

The
demand
for
goods
and
service
in
the
two­
and
three­
digit
NAICS
code
manufacturing
sectors
is
obtained
by
using
a
mathematical
specification
of
the
demand
function.
Demand
elasticity
estimates
are
more
readily
available
from
literature
searches.
The
majority
of
demand
elasticities
for
the
manufacturing
sectors
were
obtained
from
the
E.
H.
Pechan
and
Associates,
Inc.
report
(
1997)
prepared
for
the
RIA
of
the
PM
NAAQS
in
1997.
This
document
reports
results
of
a
substantive
literature
search
for
elasticity
estimates
for
use
in
conducting
an
analysis
of
the
NAAQS.
Point
estimates
are
reported
for
22
of
the
25
and
are
derived
from
previous
EPA
analyses
and
selected
working
papers.
Absent
information
for
the
remaining
3
industries
(
the
transportation,
construction,
and
commercial
sectors),
we
have
assumed
a
demand
elasticity
value
of
­
1.0.
Table
5­
2
lists
the
demand
elasticities
for
the
markets
used
in
the
model.

EPA
modeled
fuel
switching
using
secondary
data
developed
by
the
U.
S.
Department
of
Energy
for
the
National
Energy
Modeling
System
(
NEMS).
Table
5­
3
contains
fuel
price
elasticities
of
demand
for
electricity,
natural
gas,
petroleum
products,
and
coal.
The
diagonal
elements
in
the
table
represent
ownprice
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.

5.3.2
Calculating
Changes
in
Social
Welfare
The
boilers
and
process
heaters
MACT
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
5­
12
example,
a
share
of
control
costs
that
originate
in
the
energy
markets
is
passed
through
the
goods
and
services
markets
and
borne
by
both
the
producers
and
consumers
of
their
products.
5­
13
Table
5­
2.
Supply
and
Demand
Elasticities
Supply
Elasticities
Demand
Elasticities
Industrial
Residentiala
Transportation
Commercial
Petroleum
0.58b
Derived
 
0.28
Derived
Derived
Natural
Gas
0.41b
Derived
 
0.26
Derived
Derived
Electricity
0.75c
Derived
 
0.23
Derived
Derived
Coal
1.00b
Derived
 
0.26
Derived
Derived
NAICS
Description
Supplyd
Demandd
311
Food
0.75c
 
0.30
312
Beverage
and
Tobacco
Products
0.75c
 
1.30
313
Textile
Mills
0.37e
 
0.85e
314
Textile
Product
Mills
0.37e
 
0.85e
315
Apparel
0.75c
 
1.80
316
Leather
and
Allied
Products
0.75c
 
1.20
321
Wood
Products
0.75d
 
0.20
322
Paper
1.20c
 
1.09
323
Printing
and
Related
Support
0.75c
 
1.80
325
Chemicals
0.75c
 
1.50
326
Plastics
and
Rubber
Products
0.75c
 
1.80
327
Nonmetallic
Mineral
Products
0.75c
 
0.90
331
Primary
Metals
3.50f
 
0.80
332
Fabricated
Metal
Products
0.75c
 
0.20
333
Machinery
0.75c
 
0.50
334
Computer
and
Electronic
Products
0.75c
 
0.30
335
Electrical
Equipment,
Appliances,
and
Components
0.75c
 
0.50
336
Transportation
Equipment
0.75c
 
1.00c
337
Furniture
and
Related
Products
0.75c
 
3.40
339
Miscellaneous
0.75c
 
0.60
11
Agricultural
Sector
0.75c
 
1.80
(
continued)
5­
14
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
goods
and
services
markets;

change
in
consumer
surplus
in
the
goods
and
services
markets;
and

change
in
consumer
surplus
in
the
residential
sector.

Figure
5­
5
illustrates
the
change
in
producer
and
consumer
surplus
in
the
intermediate
energy
market
and
the
goods
and
services
markets.
For
example,
assume
a
simple
world
with
only
one
energy
market,
wholesale
electricity,
and
one
product
market,
pulp
and
paper.
If
the
regulation
increases
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
5­
5(
a),
the
pulp
and
paper
manufacturers
are
the
consumers
of
electricity,
so
the
change
in
consumer
surplus
is
displayed.
This
change
in
consumer
surplus
in
the
energy
market
is
captured
by
the
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
5­
5(
b)
shows
the
change
in
producer
surplus
in
the
energy
market,
where
B
represents
an
increase
in
producer
surplus
and
C
represents
a
decrease.
Table
5­
2.
Supply
and
Demand
Elasticities
(
continued)

NAICS
Description
Supplyd
Demandd
23
Construction
Sector
0.75c
 
1.00c
21
Other
Mining
Sector
0.43
 
0.30
48
Transportation
0.75c
 
0.70
Commercial
Commercial
0.75c
 
1.00c
a
U.
S.
Department
of
Energy,
Energy
Information
Administration
(
EIA).
"
Issues
in
Midterm
Analysis
and
Forecasting
1999
 
Table
1."
<
http://
www.
eia.
doe.
gov/
oaif/
issues/
pricetbl1.
html>.
As
obtained
on
May
8,
2000a.

b
Dahl,
Carol
A.,
and
Thomas
E.
Duggan.
1996.
"
U.
S.
Energy
Product
Supply
Elasticities:
A
Survey
and
Application
to
the
U.
S.
Oil
Market."
Resource
and
Energy
Economics18:
243­
263.

c
Assumed
value.

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

e
Warfield,
et
al.
2001.
"
Multifiber
Arrangement
Phaseout:
Implications
for
the
U.
S.
Fibers/
Textiles/
Fabricated
Products
Complex."
www.
fibronet.
com.
tw/
mirron/
ncs/
9312/
mar.
html>
As
obtained
September
19,
2001.

f
U.
S.
International
Trade
Commission
(
USITC).
November
21,
2001.
Memorandum
to
the
Commission
from
Craig
Thomsen,
John
Giamalua,
John
Benedetto,
Joshua
Levy,
International
Economists.
Investigation
No.
TA­
201­
73:
STEEL­
Remedy
Memorandum.
5­
15
As
shown
in
Figures
5­
5(
c)
and
5­
5(
d),
the
cost
affects
the
pulp
and
paper
industry
by
shifting
up
the
supply
curve
in
the
pulp
and
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
product
market.
Thus,
to
avoid
double­
counting,
the
change
in
consumer
surplus
in
the
intermediate
energy
market
was
not
quantified;
instead
the
total
change
in
social
welfare
was
calculated
as
Change
in
Social
Welfare
=

 
PSE
+

 
PSF
+

 
CSF
+

 
CSR
(
5.1)
Table
5­
3.
Fuel
Price
Elasticities
Inputs
Own
and
Cross
Elasticities
Electricity
Natural
Gas
Coal
Residual
Distillate
Electricity
 
0.074
0.092
0.605
0.080
0.017
Natural
Gas
0.496
 
0.229
1.087
0.346
0.014
Steam
Coal
0.021
0.061
 
0.499
0.151
0.023
Residual
0.236
0.036
0.650
 
0.587
0.012
Distillate
0.247
0.002
0.578
0.044
 
0.055
Source:
U.
S.
Department
of
Energy,
Energy
Information
Administration
(
EIA).
January
2000b.
Model
Documentation
Report:
Industrial
Sector
Demand
Module
of
the
National
Energy
Modeling
System.
DOE/
EIA­
M064(
2000).
Washington,
DC:
U.
S.
Department
of
Energy.
5­
16
S
D
S 

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

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

A
B
C
E
F
Figure
5­
5.
Changes
in
Economic
Welfare
with
Regulation
where
 
PSE
=
change
in
producer
surplus
in
the
energy
markets;

 
PSF
=
change
in
producer
surplus
in
the
goods
and
services
markets;

 
CSF
=
change
in
consumer
surplus
in
the
goods
and
services
markets;
and
 
CSR
=
change
in
consumer
surplus
in
the
commercial,
residential,
and
transportation
energy
markets.

Appendix
A
contains
the
mathematical
algorithms
used
to
calculate
the
change
in
producer
and
consumer
surplus
in
the
appropriate
markets.
The
market
analysis
is
conducted
for
the
year
2005
and
incorporates
both
growth
in
supply
and
demand.
The
data
for
2005
are
based
on
projections
of
Department
of
Energy
data
and
Census
data,
as
well
as
projections
based
on
the
engineering
data
used
in
preparing
the
profile
data
6­
17
that
is
an
input
to
this
analysis.
Appendix
A
contains
more
information
on
the
specific
data
sets
and
how
they
are
used
to
construct
a
baseline
data
set
for
2005
for
use
in
this
analysis.
Both
new
and
existing
sources
are
evaluated
using
the
same
analysis
approach.

Appendix
B
contains
a
list
of
key
assumptions
that
underlie
the
model
used
to
calculate
economic
impacts
in
this
report,
and
also
the
results
of
sensitivity
analyses
conducted
which
reflect
the
outcomes
from
varying
key
parameters
such
as
demand
and
supply
elasticities.

The
engineering
control
costs
presented
in
Chapter
3
are
inputs
(
regulatory
"
shocks")
in
the
market
model
approach.
The
magnitude
and
distribution
of
the
regulatory
costs'
impact
on
the
economy
depend
on
the
relative
size
of
the
impact
on
individual
markets
(
relative
shift
of
the
market
supply
curves)
and
the
behavioral
responses
of
producers
and
consumers
in
each
market
(
measured
by
the
price
elasticities
of
supply
and
demand).

CHAPTER
6
ECONOMIC
IMPACT
ANALYSIS
RESULTS
The
underlying
objective
of
the
EIA
is
to
evaluate
the
effect
of
the
regulation
on
the
welfare
of
affected
stakeholders
and
society
in
general.
Although
the
engineering
cost
analysis
presented
in
Chapter
3
does
represent
an
estimate
of
the
resources
required
to
comply
with
the
rule
under
baseline
economic
conditions,
the
analysis
does
not
account
for
the
fact
that
the
regulations
may
cause
the
economic
conditions
to
change.
For
instance,
producers
may
reduce
production
in
the
face
of
higher
production
costs,
thereby
reducing
market
supply.
Moreover,
the
control
costs
may
be
passed
along
to
other
parties
through
various
economic
exchanges.
Therefore,
EPA
developed
an
analytical
structure
and
economic
model
to
measure
and
6­
1
track
these
effects
(
described
in
detail
in
Chapter
5
and
the
economic
impact
analysis).
In
this
section,
we
report
quantitative
estimates
of
these
welfare
impacts
and
their
distribution
across
stakeholders.
This
includes
the
impact
on
energy
markets
as
well.

6.1
Results
in
Brief
The
economic
impacts
associated
with
the
rule
are
relatively
low.
Price
increases
of
less
than
0.02
percent
are
expected
to
occur
across
the
many
products,
both
energy
and
manufacturing,
that
will
be
affected
by
this
rule.
Reductions
in
output
are
expected
to
be
about
0.02
percent,
also.
Manufacturing
industries
such
as
paper,
wood
products,
and
textiles
are
expected
to
be
the
most
impacted.
Energy
prices
and
outputs
will
also
experience
small
changes,
with
the
largest
change
in
energy
price
being
a
0.05
percent
increase
in
electricity
rates.
While
the
price
and
output
changes
associated
with
Option
1A
are
also
low,
the
social
costs
increase
by
over
$
1
billion.

6.2
Social
Cost
Estimates
Table
6­
1
summarizes
the
economic
impact
estimates
for
existing
and
new
source
units.
Under
the
MACT
floor
alternative,
EPA
estimates
the
total
change
in
social
welfare
is
estimated
to
be
$
862.9
million.
Under
the
Option
1A,
welfare
impacts
are
over
twice
as
high
as
the
MACT
floor
alternative
with
social
welfare
changes
estimated
to
equal
$
1,995.5
million.
Both
of
these
estimates
are
slightly
smaller
(
less
than
$
0.3
million)
than
the
estimated
baseline
engineering
costs
as
a
result
of
behavior
changes
by
producers
and
consumers
that
reflect
lower
cost
alternatives.
Possible
behavior
responses
include
changes
in
consumption
and
production
patterns
and
fuel
switching.

EPA
also
estimated
the
distribution
of
social
costs
between
producers
and
consumers
and
report
the
distribution
of
impacts
across
sectors/
markets
in
Tables
6­
2
and
6­
3.
Values
in
the
text
are
impacts
from
the
floor
alternative;
those
in
parentheses
are
impacts
from
the
Option
1A
alternative.
The
market
analysis
estimates
that
consumers
will
bear
$
414.3
million
($
955.3
million),
or
48
(
48)
percent
of
the
total
social
cost,
because
of
the
increased
prices
and
lower
consumption
levels
in
these
markets.
Producer
surplus
is
projected
to
decrease
by
$
448.7
million
($
1,040.2
million),
or
52
(
52)
percent
of
the
total
social
cost
as
result
of
direct
control
costs,
higher
energy
costs,
and
reductions
in
output.

With
exception
of
the
natural
gas
market,
energy
producers
are
expected
to
experience
producer
surplus
losses.
Under
the
MACT
floor,
electricity,
petroleum,
and
coal
producer
surplus
is
projected
to
decline
by
approximately
$
35
million.
This
value
increases
to
$
113
million
under
Option
1A.
In
contrast,
natural
gas
producer
surplus
is
projected
to
increase
by
$
2
to
$
4
million
as
they
benefit
from
increased
demand
from
industries
switching
from
petroleum
and
electricity.

The
majority
welfare
impacts
fall
on
the
agriculture,
manufacturing,
and
mining
industries.
EPA
estimates
total
welfare
losses
of
$
609.8
million
($
1,444.3
million)
for
these
sectors.
Manufacturing
Table
6­
1.
Social
Cost
Estimates
($
1998
106)

Change
in
Social
Welfare,
MACT
Floor
Change
in
Social
Welfare,
Option
1A
Baseline
engineering
costs
$
863.0
$
1,995.8
Social
costs
with
market
adjustments
$
862.9
$
1,995.5
Difference
between
engineering
and
social
costs
$
0.1
$
0.3
6­
2
industries
with
large
number
of
boilers
and
process
heaters
and
industries
that
consume
electricity
experience
the
majority
these
losses
(
e.
g.,
chemicals
and
allied
products,
paper,
textile
mill
products,
and
food).
Consumers
in
these
industries
experience
losses
of
$
295.2
million
($
709.9
million)
and
producers
bear
$
314.6
million
($
734.4
million).
The
cost
of
this
rule
to
producers
as
a
percentage
of
baseline
2005
shipments
is
0.011
(
0.026)
percent.

EPA
also
examined
the
impact
on
the
commercial,
transportation
and
residential
sectors.
The
total
welfare
loss
for
the
commercial
sector
is
estimated
to
be
$
167.1
million
($
301.8
million).
Therefore,
the
regulatory
burden
associated
with
the
MACT
is
estimated
as
0.001
(
0.002)
total
2005
commercial
sector
revenues.
Consumers
in
this
sector
bear
approximately
$
71.6
million
($
129.3
million)
and
producers
bear
$
95.5
million
($
172.5
million)
of
these
impacts.
In
contrast,
the
total
welfare
loss
for
the
transportation
sector
is
estimated
to
be
$
9.0
million
($
46.5
million).
The
regulatory
burden
associated
with
the
rule
is
estimated
as
0.003
(
0.015)
percent
of
total
2005
6­
3
Table
6­
2.
Distribution
of
Social
Costs
by
Sector/
Market:
Floor
Alternative
($
1998
106)

Change
in:
Sectors/
Marke
ts
Producer
Surplus
Consumer
Surplus
Social
Welfare
Energy
Markets
Petroleum
 
$
1.9
Natural
gas
$
4.1
Electricity
 
$
33.7
Coal
 
$
2.7
Subtotal
 
$
34.2
NAICS
Code
SIC
Code
Description
311
20
(
pt)
Food
 
$
28.2
 
$
11.3
 
$
39.4
312
20
(
pt);
21
Beverage
and
Tobacco
Products
 
$
2.4
 
$
4.1
 
$
6.5
313
22
(
pt)
Textile
Mills
 
$
22.7
 
$
52.0
 
$
74.7
314
22
(
pt)
Textile
Product
Mills
 
$
0.1
 
$
0.1
 
$
0.2
315
23
Apparel
 
$
0.4
 
$
1.1
 
$
1.5
316
31
Leather
and
Allied
Products
 
$
0.3
 
$
0.4
 
$
0.7
321
24
Wood
Products
 
$
39.1
 
$
10.4
 
$
49.5
322
26
Paper
 
$
66.1
 
$
60.0
 
$
126.1
323
27
Printing
and
Related
Support
 
$
0.2
 
$
0.4
 
$
0.6
325
28
Chemicals
 
$
40.9
 
$
81.8
 
$
122.8
326
30
Plastics
and
Rubber
Products
 
$
2.2
 
$
5.4
 
$
7.6
327
32
Nonmetallic
Mineral
Products
 
$
3.4
 
$
4.0
 
$
7.4
331
33
Primary
Metals
 
$
25.2
 
$
5.7
 
$
30.9
332
34
Fabricated
Metal
Products
 
$
8.5
 
$
2.3
 
$
10.8
333
35
Machinery
 
$
7.3
 
$
4.9
 
$
12.2
334
36
(
pt)
Computer
and
Electronic
Products
 
$
3.6
 
$
1.4
 
$
5.0
335
36
(
pt)
Electrical
Equipment,
Appliances,
and
Components
 
$
2.5
 
$
1.6
 
$
4.1
336
37
Transportation
Equipment
 
$
24.6
 
$
32.8
 
$
57.3
337
25
Furniture
and
Related
Products
 
$
5.4
 
$
24.6
 
$
30.1
339
39
Miscellaneous
 
$
0.8
 
$
0.7
 
$
1.5
11
01­
08
Agricultural
Sector
 
$
0.6
 
$
1.3
 
$
1.9
23
15­
17
Construction
Sector
 
$
0.8
 
$
1.1
 
$
1.9
21
10;
14
Other
Mining
Sector
 
$
10.1
 
$
7.0
 
$
17.2
48
40­
47
(
pt)
Transportation
 
$
4.7
 
$
4.3
 
$
9.0
42;
44­
45;
49;
51­
56;
61­
62;
71­
72;
81
40­
48
(
pt);
50­
99
Commercial
 
$
71.6
 
$
95.5
 
$
167.1
Residential
NA
 
$
42.7
 
$
42.7
Grand
Total
 
$
414.3
 
$
448.7
 
$
862.9
NA
=
Not
applicable.
6­
4
Table
6­
3.
Distribution
of
Social
Costs
by
Sector/
Market:
Option
1A
Alternative
($
1998
106)

Change
in:
Sectors/
Marke
ts
Producer
Surplus
Consumer
Surplus
Social
Welfare
Energy
Markets
Petroleum
 
$
27.3
Natural
gas
$
2.4
Electricity
 
$
79.5
Coal
 
$
6.4
Subtotal
 
$
110.8
NAICS
Code
SIC
Code
Description
311
20
(
pt)
Food
 
$
90.0
 
$
36.0
 
$
126.0
312
20
(
pt);
21
Beverage
and
Tobacco
Products
 
$
5.4
 
$
9.3
 
$
14.7
313
22
(
pt)
Textile
Mills
 
$
45.0
 
$
103.2
 
$
148.2
314
22
(
pt)
Textile
Product
Mills
 
$
0.1
 
$
0.3
 
$
0.4
315
23
Apparell
 
$
0.9
 
$
2.1
 
$
3.0
316
31
Leather
and
Allied
Products
 
$
2.7
 
$
4.3
 
$
7.1
321
24
Wood
Products
 
$
72.0
 
$
19.2
 
$
91.2
322
26
Paper
 
$
173.1
 
$
157.2
 
$
330.3
323
27
Printing
and
Related
Support
 
$
0.4
 
$
1.0
 
$
1.4
325
28
Chemicals
 
$
102.4
 
$
204.7
 
$
307.1
326
30
Plastics
and
Rubber
Products
 
$
6.1
 
$
14.6
 
$
20.7
327
32
Nonmetallic
Mineral
Products
 
$
9.1
 
$
10.9
 
$
20.0
331
33
Primary
Metals
 
$
59.5
 
$
13.6
 
$
73.1
332
34
Fabricated
Metal
Products
 
$
18.6
 
$
5.0
 
$
23.6
333
35
Machinery
 
$
17.1
 
$
11.4
 
$
28.5
334
36
(
pt)
Computer
and
Electronic
Products
 
$
12.0
 
$
4.8
 
$
16.8
335
36
(
pt)
Electrical
Equipment,
Appliances,
and
Components
 
$
11.7
 
$
7.8
 
$
19.6
336
37
Transportation
Equipment
 
$
47.8
 
$
63.7
 
$
111.4
337
25
Furniture
and
Related
Products
 
$
9.2
 
$
41.8
 
$
51.0
339
39
Miscellaneous
 
$
3.2
 
$
2.5
 
$
5.7
11
01­
08
Agricultural
Sector
 
$
1.5
 
$
3.6
 
$
5.1
23
15­
17
Construction
Sector
 
$
3.2
 
$
4.3
 
$
7.5
21
10;
14
Other
Mining
Sector
 
$
18.9
 
$
13.1
 
$
32.0
48
40­
47
(
pt)
Transportation
 
$
24.1
 
$
22.5
 
$
46.5
42;
44­
45;
49;
51­
56;
61­
62;
71­
72;
81
40­
48
(
pt);
50­
99
Commercial
 
$
129.3
 
$
172.5
 
$
301.8
Residential
NA
 
$
92.0
 
$
92.0
Grand
Total
 
$
955.3
 
$
1,040.2
 
$
1,995.5
6­
5
transportation
sector
revenues.
Transportation
consumers
bear
approximately
$
4.7
million
($
24.1
million)
and
producers
bear
$
4.3
million
($
22.5
million)
of
these
impacts.
Finally,
the
social
cost
burden
to
residential
consumers
of
energy,
$
42.7
million
($
92.0
million),
is
0.037
(
0.078)
percent
of
annual
residential
energy
expenditures
in
2005.

Sensitivity
analyses
of
how
social
costs
behave
with
changes
in
the
demand
and
supply
elasticities
are
available
in
Appendix
B.

6.3
National
Market­
Level
Impacts
Increases
in
the
costs
of
production
in
the
energy
and
final
product
markets
due
to
the
regulation
are
expected
to
result
in
changes
in
prices,
production,
and
consumption
from
baseline
levels.
As
shown
in
Table
6­
4,
the
electricity
market
price
increases
by
0.050
(
0.108)
percent,
while
production/
consumption
decreases
by
0.011
(
0.026)
percent
as
a
result
of
additional
control
costs.
A
significant
share
of
electricity
is
produced
in
the
United
States
using
coal
as
a
primary
input.
Therefore,
projected
reductions
in
electricity
production
also
lead
to
a
decrease
in
demand
for
coal.
As
a
result,
the
price
and
quantities
of
coal
are
projected
to
fall
by
0.007
(
0.020)
percent
and
0.010
(
0.024)
percent,
respectively.
In
the
petroleum
market,
the
model
projects
small
price
and
quantity
effects
(
i.
e.,
less
than
0.01
percent).
In
the
natural
gas
market,
the
model
projects
the
market
price
will
rise
in
response
to
increased
demand
(
0.005
percent
under
both
alternatives).
The
price
increase
is
the
result
of
additional
control
costs
and
increased
demand.
Production
and
consumption
quantities
also
increase
in
this
market
(
0.002
percent
under
the
floor
alternative
and
0.001
percent
under
Option
1A)
as
a
result
of
increased
demand.

Additional
control
costs
and
higher
energy
costs
associated
with
the
regulation
lead
to
higher
goods
and
services
prices
in
all
markets
and
a
decline
in
output.
However,
the
changes
are
generally
very
small.
Under
the
MACT
Floor,
three
markets
have
price
increases
greater
than
or
equal
to
0.02
percent
 
Wood
Product(
NAICS
321),
Paper
(
NAICS
322),
and
Textile
Mills
(
NAICS
313).
Under
Option
1A,
these
three
markets
have
price
increases
greater
than
or
equal
to
0.05
percent.
The
producers
in
these
sectors
are
expected
to
face
higher
per­
unit
control
costs
relative
to
other
industries.
In
addition,
these
industries
are
also
electricity­
intensive;
therefore,
costs
of
production
also
increase
as
a
result
of
higher
electricity
prices.

Although
the
impacts
on
price
and
quantity
in
the
goods
and
services
markets
are
estimated
to
be
small,
one
possible
effect
of
modeling
market
impacts
at
the
two
and
three
digit
NAICS
code
level
is
that
fuel­
intensive
industries
within
the
larger
NAICS
code
definition
may
be
affected
more
significantly
than
the
average
industry
for
that
NAICS
code.
Thus,
the
changes
in
price
and
6­
6
Table
6­
4.
Market­
Level
Impacts
MACT
Floor
Percent
Change
Option
1A
Percent
Change
Sectors/
Markets
Price
Quantity
Price
Quantity
Energy
Markets
Petroleum
0.002%
0.000%
0.019%
 
0.005%
Natural
gas
0.005%
0.002%
0.005%
0.001%
Electricity
0.050%
 
0.011%
0.108%
 
0.026%
Coal
 
0.007%
 
0.010%
 
0.020%
 
0.024%
NAICS
Code
SIC
Code
Description
311
20
(
pt)
Food
0.006%
 
0.002%
0.019%
 
0.006%
312
20
(
pt);
21
Beverage
and
Tobacco
Products
0.003%
 
0.004%
0.007%
 
0.009%
313
22
(
pt)
Textile
Mills
0.025%
 
0.021%
0.050%
 
0.043%
314
22
(
pt)
Textile
Product
Mills
0.000%
0.000%
0.000%
0.000%
315
23
Apparel
0.000%
 
0.001%
0.001%
 
0.001%
316
31
Leather
and
Allied
Products
0.002%
 
0.003%
0.025%
 
0.030%
321
24
Wood
Products
0.041%
 
0.008%
0.075%
 
0.015%
322
26
Paper
0.026%
 
0.028%
0.068%
 
0.074%
323
27
Printing
and
Related
Support
0.000%
0.000%
0.000%
 
0.001%
325
28
Chemicals
0.009%
 
0.013%
0.021%
 
0.032%
326
30
Plastics
and
Rubber
Products
0.001%
 
0.002%
0.003%
 
0.005%
327
32
Nonmetallic
Mineral
Products
0.003%
 
0.003%
0.009%
 
0.008%
331
33
Primary
Metals
0.011%
 
0.009%
0.026%
 
0.021%
332
34
Fabricated
Metal
Products
0.003%
 
0.001%
0.007%
 
0.001%
333
35
Machinery
0.002%
 
0.001%
0.005%
 
0.002%
334
36
(
pt)
Computer
and
Electronic
Products
0.001%
0.000%
0.002%
 
0.001%
335
36
(
pt)
Electrical
Equipment,
Appliances,
and
Components
0.002%
 
0.001%
0.009%
 
0.004%

336
37
Transportation
Equipment
0.004%
 
0.004%
0.007%
 
0.007%
337
25
Furniture
and
Related
Products
0.008%
 
0.026%
0.013%
 
0.044%
339
39
Miscellaneous
0.001%
0.000%
0.003%
 
0.002%
11
01­
08
Agricultural
Sector
0.000%
0.000%
0.001%
 
0.001%
23
15­
17
Construction
Sector
0.000%
0.000%
0.000%
0.000%
21
10;
14
Other
Mining
Sector
0.012%
 
0.004%
0.023%
 
0.007%
48
40­
47
(
pt)
Transportation
0.001%
 
0.001%
0.007%
 
0.005%
42;
44­
45;
49;
51­
56;
61­
62;
71­
72;
81
40­
48
(
pt);
50­
99
Commercial
0.000%
0.000%
0.001%
 
0.001%

pt
=
Part.
9Conversion
factors
for
heat
rates
were
obtained
from
AEO
2002,
Appendix
H.
These
factors
vary
by
year
to
year;
2010
values
are
reported
in
this
Appendix.

6­
7
quantity
should
be
interpreted
as
an
average
for
the
whole
NAICS
code,
not
necessarily
for
each
disaggregated
industry
within
that
NAICS
code.

6.4
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."

EPA
has
provided
additional
information
on
the
impacts
of
the
rule
on
affected
energy
markets
below.
9
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
415
million
kWh
under
the
MACT
floor
and
980
million
kWh
under
Option
1A.

Impacts
on
Petroleum,
Natural
Gas,
and
Coal
Supply,
Distribution,
and
Use.
The
model
projects
decreases
in
petroleum
production/
consumption
of
approximately
68
barrels
per
day
under
the
MACT
floor
and
975
barrels
per
day
under
Option
1A.
In
contrast,
natural
gas
production/
consumption
is
projected
to
increase
by
1.1
million
cubic
feet
per
day
under
the
MACT
floor
and
600,000
cubic
feet
per
day
under
Option
1A
This
is
the
result
of
fuel
switching
in
response
to
relative
price
changes.
Finally,
the
model
also
projects
less
than
a
1,000
tons
per
day
decrease
in
coal
production/
consumption
under
both
scenarios
in
response
to
reduced
output
from
the
electricity
sector
(
a
significant
consumer
of
coal).
Based
on
these
results,
the
Agency
concludes
that
the
industrial
boiler
and
process
heater
NESHAP
will
not
have
a
significant
adverse
effect
on
the
supply,
distribution,
or
use
of
energy.

6.5
Conclusions
The
decrease
in
social
surplus
estimated
using
the
market
analysis
is
$
862.9
million
($
1,955.5
million).
This
estimate
is
slightly
smaller
than
the
estimated
baseline
engineering
costs
because
the
market
model
accounts
for
behavioral
changes
of
producers
and
consumers.
Although
the
rule
affects
boilers
and
process
heaters
used
in
energy
industries,
energy
producers
only
incur
less
than
6
percent
of
the
total
social
cost
of
the
regulation.
This
burden
is
spread
across
numerous
markets
because
the
price
of
energy
increases
slightly
as
a
result
of
the
regulation,
which
increases
the
cost
of
production
for
all
markets
that
use
energy
as
part
of
their
production
process.

The
remaining
share
of
the
social
cost
is
mostly
borne
by
the
manufacturing
sectors
which
operate
the
majority
of
the
boilers
and
process
heaters
affected
by
the
regulation.
Manufacturing
industries
bearing
the
largest
social
costs
include
percent
 
Wood
Products
(
NAICS
321),
Paper
(
NAICS
322),
and
Textile
Mills
(
NAICS
313).
However,
the
market
model
predicts
that
changes
in
these
industries'
price
and
quantity
do
not
exceed
0.02
percent
under
the
floor
alternative
and
0.05
percent
under
Option
1A..
7­
8
Because
of
the
minimal
changes
in
price
and
quantity
estimated
for
most
of
the
affected
markets,
EPA
expects
that
there
would
be
no
discernable
impact
on
international
trade.
Although
an
increase
in
the
price
of
U.
S.
products
relative
to
those
of
foreign
producers
is
expected
to
decrease
exports
and
increase
imports,
the
changes
in
price
due
to
the
industrial
boilers
and
process
heaters
MACT
are
generally
too
small
to
significantly
influence
trade
patterns.
There
may
also
be
a
small
decrease
in
employment,
but
because
the
impact
of
the
regulation
is
spread
across
so
many
industries
and
the
decreases
in
market
quantities
are
so
small,
it
is
unlikely
that
any
particular
industry
will
face
a
significant
decrease
in
employment.

CHAPTER
7
SMALL
BUSINESS
IMPACTS
This
chapter
investigates
the
potential
impact
the
regulation
will
have
on
small
entities.
The
Agency
has
identified
185
small
entities
that
will
be
affected
by
the
MACT
floor
alternative
for
the
industrial
boilers
and
process
heaters
NESHAP.
For
these
entities,
the
average
cost­
to­
sales
ratio
(
CSR)
is
0.78
percent
and
the
average
annual
control
cost
(
in
1999
dollars)
is
$
198,675.

7.1
Results
in
Brief
7­
1
As
listed
in
Table
7­
1,
34
of
the
185
affected
entities
will
incur
annual
compliance
costs
that
are
greater
than
or
equal
to
1
percent
of
their
annual
sales
or
revenues,
and
10
of
these
34
are
expected
to
incur
annual
compliance
costs
of
3
percent
or
greater
of
annual
sales
or
revenues.
As
explained
later
in
this
chapter,
the
Agency
has
certified
that
this
rule
will
not
impose
a
significant
impact
on
a
substantial
number
of
small
entities.
This
certification
is
based
on
the
results
shown
for
the
MACT
floor
alternative
and
on
the
results
of
the
economic
impact
analysis
shown
in
Chapter
6.
For
Option
1A,
as
listed
in
Table
7­
1,
there
are
almost
twice
as
many
small
entities
affected
(
369),
and
148
(
or
40
percent)
of
these
incur
annual
compliance
costs
of
greater
than
or
equal
to
1
percent
of
their
annual
sales
or
revenues,
and
45
(
or
12
percent)
of
the
total
incur
annual
compliance
costs
of
3
percent
or
greater
of
annual
sales
or
revenues.

7.2
Background
on
Small
Business
Screenings
The
regulatory
costs
imposed
on
domestic
producers
and
government
entities
to
reduce
air
emissions
from
boilers
and
process
heaters
will
have
a
direct
impact
on
owners
of
the
affected
facilities.
Firms
or
individuals
that
own
the
facilities
with
boilers
and
process
heaters
are
typically
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
Regulatory
Flexibility
Act
(
RFA)
generally
requires
an
agency
to
prepare
a
regulatory
flexibility
analysis
of
any
rule
subject
to
notice
and
comment
rulemaking
requirements
under
the
Administrative
Procedure
Act
or
any
other
statute
unless
the
agency
certifies
that
the
rule
will
not
have
a
significant
economic
impact
on
a
substantial
number
of
small
entities.
Small
entities
include
small
businesses,
small
organizations,
and
small
governmental
jurisdictions.

For
purposes
of
assessing
the
impacts
of
today's
rule
on
small
entities,
small
entity
is
defined
as:
(
1)
a
small
business
according
to
Small
Business
Administration
(
SBA)
size
standards
by
the
North
American
Industry
Classification
System
(
NAICS)
category
of
the
owning
entity.
The
range
of
small
business
size
standards
for
the
40
affected
industries
ranges
from
500
to
1,000
employees,
except
for
petroleum
refining
and
electric
utilities.
In
these
latter
two
industries,
the
size
standard
is
1,500
employees
and
a
mass
throughput
of
75,000
barrels/
day
or
less,
and
4
million
kilowatt­
hours
of
production
or
less,
respectively.
(
2)
a
small
governmental
jurisdiction
that
is
a
government
of
a
city,
county,
town,
school
district
or
special
district
with
a
population
of
less
than
50,000;
and
(
3)
a
small
organization
that
is
any
not­
for­
profit
enterprise
which
is
independently
owned
and
operated
and
is
not
dominant
in
its
field.
Table
7­
1.
Summary
of
Small
Entity
Impacts
MACT
Floor
Alternative
Option
1A
Alternative
Number
of
small
entities
185
369
Total
number
of
entities
576
970
Average
annual
control
cost
per
small
entity
$
198,675
$
269,842
Average
control
cost/
sales
ratio
0.78%
1.65%

Number
of
small
entities
with
cost­
to­
sales
ratios

1
percent
34
148
Number
of
small
entities
with
cost­
to­
sales
ratios

3
percent
10
45
10The
ICCR
Inventory
Database
contains
data
for
boilers,
process
heaters,
incinerators,
landfill
gas
flares,
turbines,
and
internal
combustion
engines.

7­
2
This
section
investigates
characteristics
of
businesses
and
government
entities
that
own
existing
boilers
and
process
heaters
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.

7.3
Identifying
Small
Businesses
To
support
the
economic
impact
analysis
of
the
regulation,
EPA
identified
2,186
(
3,580)
boilers
and
process
heaters
located
at
commercial,
industrial,
and
government
facilities
that
would
be
affected
by
the
regulation.
The
population
of
boilers
and
process
heaters
was
developed
from
the
EPA
ICCR
Inventory
Database
version
4.1.10
The
list
of
boilers
and
process
heaters
contained
in
these
databases
was
developed
from
information
in
the
AIRS
and
OTAG
databases,
state
and
local
permit
records,
and
the
combustion
source
ICR
conducted
by
the
Agency.
Industry
and
environmental
stakeholders
reviewed
the
units
contained
in
these
databases
as
part
of
the
ICCR
FACA
process.
In
addition,
stakeholders
contributed
to
the
databases
by
identifying
and
including
omitted
units.
Information
was
extracted
from
the
ICCR
databases
to
support
the
ICI
boilers
and
process
heaters
NESHAP.
This
modified
database
containing
information
on
only
boilers
and
process
heaters
is
referred
to
as
the
Inventory
Database.

The
small
entities
screening
analysis
for
the
regulation
is
based
on
the
evaluation
of
existing
owners
of
boilers
and
process
heaters
for
which
information
was
available.
It
is
assumed
that
the
size
and
ownership
distribution
of
units
in
the
Inventory
Database
is
representative
of
the
entire
estimated
population
of
existing
boilers
and
process
heaters.
In
addition,
it
is
assumed
that
new
sources
included
in
the
2005
population
will
also
be
representative
of
the
Inventory
Database.
However,
because
our
analysis
is
based
on
a
subset
of
the
total
population
of
boilers
and
process
heaters,
the
number
of
entities
identified
as
highly
affected
in
this
analysis
may
not
be
identical
to
the
actual
impact
of
the
regulation
on
small
entities.

The
remainder
of
this
section
presents
cost
and
sales
information
on
small
companies
and
government
organizations
that
own
existing
boilers
and
process
heaters.
Also,
in
this
section,
as
in
previous
sections,
the
values
from
the
Inventory
Database
in
the
text
are
for
the
floor
alternative.
Following
in
parentheses
are
those
for
the
Option
1A
alternative.

7.4
Analysis
of
Facility­
Level
and
Parent­
Level
Data
The
2,186
(
3,580)
units
in
the
Inventory
Database
with
full
information
were
linked
to
1,214
(
1,881)
existing
facilities.
As
shown
in
Table
7­
2,
these
1,186
(
1,521)
facilities
are
owned
by
576
(
970)
parent
companies.
The
average
number
of
facilities
per
company
is
approximately
2.0
(
2.2);
however,
as
is
also
illustrated
in
Table
7­
2,
several
large
entities
in
the
health
services
industry
and
government
sectors
own
many
facilities
with
boilers
and
process
heaters.
7­
3
Table
7­
2.
Facility­
Level
and
Parent­
Level
Data
by
Industry
Floor
Alternative
Option
1A
Alternative
SIC
Code
NAICS
Code
Description
Number
of
Units
Number
of
Facilities
Number
of
Parent
Companies
Avg.
Number
of
Facilities
Per
Parent
Entity
Number
of
Units
Number
of
Facilities
Number
of
Parent
Companies
Avg.
Number
of
Facilities
Per
Parent
Entity
01
111
Agriculture
 
Crops
3
3
3
1.0
6
6
6
1.0
02
112
Agriculture
 
Livestock
 
 
 
 
 
 
 
 
07
115
Agricultural
Services
 
 
 
 
 
 
 
 
10
212
Metal
Mining
9
4
2
2.0
11
5
2
2.5
12
212
Coal
Mining
2
1
 
 
2
1
 
 
13
211
Oil
and
Gas
Extraction
 
 
 
 
18
4
1
4.0
14
212
Mining/
Quarrying
 
Nonmetallic
Minerals
8
4
3
1.3
10
5
4
1.3
17
235
Construction
 
Special
Trade
 
 
 
 
2
1
1
1.0
20
311
Food
and
Kindred
Products
138
60
32
1.9
163
72
38
1.9
21
312
Tobacco
Products
11
7
4
1.8
22
11
6
1.8
22
313
Textile
Mill
Products
135
71
33
2.2
250
134
73
1.8
23
315
Apparel
&
Other
Products
from
Fabrics
2
2
1
2.0
4
4
3
1.3
24
321
Lumber
and
Wood
Products
360
262
122
2.1
462
337
175
1.9
25
337
Furniture
and
Fixtures
234
154
67
2.3
310
209
100
2.1
26
322
Paper
and
Allied
Products
321
194
68
2.9
503
272
100
2.7
27
511
Printing,
Publishing,
and
Related
Industries
 
 
 
 
8
6
3
2.0
28
325
Chemicals
and
Allied
Products
174
70
41
1.7
433
163
91
1.8
29
324
Petroleum
Refining
and
Related
Industries
11
8
9
0.9
162
50
31
1.6
30
326
Rubber
and
Misc.
Plastics
Products
17
13
9
1.4
56
37
24
1.5
(
continued)
7­
4
Table
7­
2.
Facility­
Level
and
Parent­
Level
Data
by
Industry
(
continued)

Floor
Alternative
Option
1A
Alternative
SIC
Code
NAICS
Code
Description
Number
of
Units
Number
of
Facilities
Number
of
Parent
Companies
Avg.
Number
of
Facilities
Per
Parent
Entity
Number
of
Units
Number
of
Facilities
Number
of
Parent
Companies
Avg.
Number
of
Facilities
Per
Parent
Entity
31
316
Leather
and
Leather
Products
1
1
1
1.0
22
12
8
1.5
32
327
Stone,
Clay,
Glass,
and
Concrete
Products
9
7
4
1.8
42
25
15
1.7
33
331
Primary
Metal
Industries
41
16
10
1.6
85
33
22
1.5
34
332
Fabricated
Metal
Products
16
10
7
1.4
44
28
18
1.6
35
333
Industrial
Machinery
and
Computer
Equip.
23
12
9
1.3
46
25
20
1.3
36
335
Electronic
and
Electrical
Equipment
5
5
3
1.7
45
29
19
1.5
37
336
Transportation
Equipment
102
41
12
3.4
158
61
26
2.3
38
334
Scientific,
Optical,
and
Photographic
Equipment
8
4
3
1.3
33
16
9
1.8
39
339
Misc.
Manufacturing
Industries
2
2
2
1.0
14
10
9
1.1
40
482
Railroad
Transportation
4
1
1
1.0
4
1
1
1.0
42
484
Motor
Freight
and
Warehousing
5
1
1
1.0
7
3
3
1.0
46
486
Pipelines,
Except
Natural
Gas
 
 
 
 
6
5
1
5.0
49
221
Electric,
Gas,
and
Sanitary
Services
318
160
80
2.0
372
185
98
1.9
50
421
Wholesale
Trade
 
Durable
Goods
3
2
1
2.0
3
2
1
2.0
51
422
Wholesale
Trade
 
Nondurable
Goods
2
1
1
1.0
2
1
1
1.0
55
441
Automotive
Dealers
and
Gasoline
Service
Stations
 
 
 
 
1
1
1
1.0
58
722
Eating
and
Drinking
Places
 
 
 
 
 
 
 
 
59
445
 
454
Miscellaneous
Retail
 
 
 
 
1
1
1
1.0
60
522
Depository
Institutions
 
 
 
 
 
 
 
 
(
continued)
7­
5
Table
7­
2.
Facility­
Level
and
Parent­
Level
Data
by
Industry
(
continued)

Floor
Alternative
Option
1A
Alternative
SIC
Code
NAICS
Code
Description
Number
of
Units
Number
of
Facilities
Number
of
Parent
Companies
Avg.
Number
of
Facilities
Per
Parent
Entity
Number
of
Units
Number
of
Facilities
Number
of
Parent
Companies
Avg.
Number
of
Facilities
Per
Parent
Entity
70
721
Hotels
and
Other
Lodging
Places
1
1
1
1.0
1
1
1
1.0
72
812
Personal
Services
 
 
 
 
 
 
 
 
76
811
Misc.
Repair
Services
2
1
 
 
2
1
 
 
80
621
Health
Services
37
18
2
9.0
40
19
2
9.5
81
541
Legal
Services
 
 
 
 
 
 
 
 
82
611
Educational
Services
105
45
30
1.5
114
50
35
1.4
83
624
Social
Services
2
1
 
 
3
2
2
1.0
86
813
Membership
Organizations
 
 
 
 
 
 
 
 
87
541
Engineering,
Accounting,

Research,
Management
and
Related
Services
2
2
1
2.0
6
5
2
2.5
89
711/
514
Services,
N.
E.
C.
2
1
 
 
2
1
 
 
91
921
Executive,
Legislative,
and
General
Administration
1
1
 
 
2
2
1
2.0
92
922
Justice,
Public
Order,
and
Safety
29
9
 
 
33
10
 
 
94
923
Administration
of
Human
Resources
1
1
 
 
1
1
 
 
96
926
Administration
of
Economic
Programs
4
3
1
3.0
4
3
1
3.0
97
928
National
Security
and
International
Affairs
29
11
2
5.5
41
13
2
6.5
NA
SIC
Information
Not
Available
7
4
 
 
24
18
2
9.0
State
Parent
is
a
state
government
 
 
10
 
 
 
11
 
Total
2,186
1,214
576
2.0
3,580
1,881
970
2.2
Source:
Industrial
Combustion
Coordinated
Rulemaking
(
ICCR).
1998.
Data/
Information
Submitted
to
the
Coordinating
Committee
at
the
Final
Meeting
of
the
Industrial
Combustion
Coordinated
Rulemaking
Federal
Advisory
Committee.
EPA
Docket
Numbers
A­
94­
63,
II­
K­
4b2
through
­
4b5.
Research
Triangle
Park,

North
Carolina.
September
16­
17.
11Total
annualized
cost
is
compared
to
tax
revenue
to
assess
the
relative
impact
on
local
governments.

7­
6
10
12
31
125
52
121
141
55
0
50
100
150
200
<
25
25
to
49
50
to
99
100
to
499
500
to
999
1,000
to
4,999
5,000
to
24,999
>
25,000
Parent
Employment
Number
of
Parents
Figure
7­
1.
Parent
Size
by
Employment
Range,
Floor
Alternative
*
Excludes
29
parent
entities
for
which
employment
information
was
unavailable.
Employment
and
sales
are
typically
used
as
measures
of
business
size.
Employment,
sales,
population,
and
tax
revenue
data
(
when
applicable)
were
collected
for
the
576
(
970)
parent
companies
and
government
entities.
11
Figure
7­
1
shows
the
distribution
of
employees
by
parent
company
for
the
floor
alternative.
Employment
for
parent
companies
ranges
from
5
to
608,000
employees.
One
hundred
seventyeight
or
more
of
the
firms
have
fewer
than
500
employees,
and
55
companies
have
more
than
25,000
employees.
The
distribution
of
parents
by
employment
range
for
the
above­
the­
floor
alternative
is
similar
to
the
floor
alternative.

Sales
provide
another
measure
of
business
size.
Figure
7­
2
presents
the
sales
distribution
for
affected
parent
companies
for
the
floor
alternative.
The
median
sales
figure
for
affected
companies
is
$
300
million
($
200
million),
and
the
average
sales
figure
is
$
4.1
billion
($
3.5
billion)
(
excluding
the
federal
government).
As
shown
in
Figure
7­
2,
revenue
and
sales
figures
vary
greatly
across
the
population:
209
firms
and
governments
affected
by
the
floor
alternative
have
annual
revenues
less
than
$
100
million
per
year.
These
figures
include
all
sales
associated
with
the
parent
company,
not
just
facilities
affected
by
the
12Small
business
guidelines
typically
define
small
businesses
based
on
employment,
and
the
threshold
varies
from
industry
to
industry.
For
example,
in
the
paints
and
allied
products
industry,
a
business
with
fewer
than
500
employees
is
considered
a
small
business;
whereas
in
the
industrial
gases
industry,
a
business
with
fewer
than
1,000
employees
is
considered
small.
However,
for
a
few
industries,
usually
services,
sales
are
used
as
the
criterion.
For
example,
in
the
veterinary
hospital
industry,
companies
with
less
than
$
5
million
in
annual
sales
are
defined
as
small
businesses.

7­
7
7
18
128
56
110
51
133
20
33
17
0
50
100
150
200
<
5
5
to
9
10
to
49
50
to
99
100
to
499
500
to
999
1,000
to
4,999
5,000
to
9,999
10,000
to
24,999
>
25,000
Parent
Sales
($
106)
Number
of
Parents
Figure
7­
2.
Number
of
Parents
by
Sales
Range,
Floor
Alternative
*
Excludes
3
parent
entities
for
which
sales
or
revenue
information
was
unavailable.

regulation
(
i.
e.,
facilities
with
boilers
or
process
heaters).
The
distribution
for
the
Option
1A
above­
thefloor
alternative
is
similar
to
that
for
the
floor
alternative.

Based
on
SBA
guidelines,
185
(
369)
of
the
companies
were
identified
as
small
businesses.
12
Small
businesses
by
business
type
are
presented
in
Table
7­
3.
The
lumber
and
wood
products
industry
contains
the
largest
number
of
the
small
businesses
with
84
(
134),
followed
by
furniture
and
fixtures
with
28
(
55),
electric
services
with
26
(
30),
and
paper
and
allied
products
with
13
(
30).
The
remaining
small
businesses
are
distributed
across
40
different
two­
digit
SIC
code
groupings.
7­
8
Table
7­
3.
Small
Parent
Companies
by
Industry
Floor
Alternative
Option
1A
Alternative
SIC
Code
NAICS
Code
Description
Number
of
Parent
Companies
Number
of
Small
Parent
Companies
Number
of
Parent
Companies
Number
of
Small
Parent
Companies
01
111
Agriculture
 
Crops
3
 
6
1
02
112
Agriculture
 
Livestock
 
 
 
 
07
115
Agricultural
Services
 
 
 
 
10
212
Metal
Mining
2
2
2
2
12
212
Coal
Mining
 
 
 
 
13
211
Oil
and
Gas
Extraction
 
 
1
1
14
212
Mining/
Quarrying
 
Nonmetallic
Minerals
3
 
4
 
17
235
Construction
 
Special
Trade
Contractors
 
 
1
1
20
311
Food
and
Kindred
Products
32
12
38
15
21
312
Tobacco
Products
4
 
6
 
22
313
Textile
Mill
Products
33
5
73
27
23
315
Apparel
and
Other
Products
from
Fabrics
1
 
3
2
24
321
Lumber
and
Wood
Products
122
84
175
134
25
337
Furniture
and
Fixtures
67
28
100
55
26
322
Paper
and
Allied
Products
68
13
100
30
27
511
Printing,
Publishing,
and
Related
Industries
 
 
3
2
28
325
Chemicals
and
Allied
Products
41
4
91
19
29
324
Petroleum
Refining
and
Related
Industries
9
2
31
9
30
326
Rubber
and
Misc.
Plastics
Products
9
1
24
4
31
316
Leather
and
Leather
Products
1
1
8
4
32
327
Stone,
Clay,
Glass,
and
Concrete
Products
4
 
15
3
33
331
Primary
Metal
Industries
10
1
22
3
34
332
Fabricated
Metal
Products
7
3
18
5
(
continued)
7­
9
Table
7­
3.
Small
Parent
Companies
by
Industry
(
continued)

Floor
Alternative
Option
1A
Alternative
SIC
Code
NAICS
Code
Description
Number
of
Parent
Companies
Number
of
Small
Parent
Companies
Number
of
Parent
Companies
Number
of
Small
Parent
Companies
35
333
Industrial
Machinery
and
Computer
Equip.
9
1
20
5
36
335
Electronic
and
Electrical
Equipment
3
 
19
 
37
336
Transportation
Equipment
12
1
26
5
38
334
Scientific,
Optical,
and
Photographic
Equip.
3
 
9
1
39
339
Miscellaneous
Manufacturing
Industries
2
 
9
1
40
482
Railroad
Transportation
1
 
1
 
42
484
Motor
Freight
and
Warehousing
1
 
3
1
46
486
Pipelines,
Except
Natural
Gas
 
 
1
 
49
221
Electric,
Gas,
and
Sanitary
Services
80
26
98
30
50
421
Wholesale
Trade
 
Durable
Goods
1
 
1
 
51
422
Wholesale
Trade
 
Nondurable
Goods
1
 
1
 
55
441
Automotive
Dealers
and
Gasoline
Service
Stations
 
 
1
1
58
722
Eating
and
Drinking
Places
 
 
 
 
59
445
 
454
Miscellaneous
Retail
 
 
1
1
60
522
Depository
Institutions
 
 
 
 
70
721
Hotels
and
Other
Lodging
Places
1
 
1
 
72
812
Personal
Services
 
 
 
 
76
811
Misc.
Repair
Services
 
 
 
 
80
621
Health
Services
2
1
2
1
81
541
Legal
Services
 
 
 
 
82
611
Educational
Services
30
 
35
3
83
624
Social
Services
 
 
2
1
(
continued)
7­
10
Table
7­
3.
Small
Parent
Companies
by
Industry
(
continued)

Floor
Alternative
Option
1A
Alternative
SIC
Code
NAICS
Code
Description
Number
of
Parent
Companies
Number
of
Small
Parent
Companies
Number
of
Parent
Companies
Number
of
Small
Parent
Companies
86
813
Membership
Organizations
 
 
 
 
87
541
Engineering,
Accounting,
Research,
Management
and
Related
Services
1
 
2
 
89
711/
514
Services,
N.
E.
C.
 
 
 
 
91
921
Executive,
Legislative,
and
General
Administration
 
 
1
 
92
922
Justice,
Public
Order,
and
Safety
 
 
 
 
94
923
Administration
of
Human
Resources
 
 
 
 
96
926
Administration
of
Economic
Programs
1
 
1
 
97
928
National
Security
and
International
Affairs
2
 
2
 
NA
SIC
Information
Not
Available
 
 
2
2
State
Parent
is
a
State
Government
10
 
11
 
Total
576
185
970
369
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.

Fifty­
nine
governmental
jurisdictions
are
affected
by
the
final
rule.
The
entities
operate
290
units
located
at
121
facilities.
Thirteen
of
these
jurisdictions
are
classified
as
small
because
they
serve
a
population
of
50,000
or
fewer.
The
affected
small
governments
operate
13
units
at
13
facilities.
More
information
on
impacts
to
these
entities
can
be
found
in
Section
7.6.

7.5
Small
Business
Impacts
Table
7­
4
presents
a
summary
of
the
ratio
of
floor
and
above­
the­
floor
control
costs
to
sales
for
affected
large
and
small
entities.
The
average
CSR
is
0.14
(
0.23)
percent
for
large
entities
7­
11
Table
7­
4.
Summary
Statistics
for
SBREFA
Screening
Analysis:
Floor
and
Above­
the­
Floor
Cost­
to­
Sales
Ratios
Floor
Option
1A
Total
Number
of
Small
Entities
185
369
Average
Annual
Compliance
Cost
per
Small
Entity
$
198,675
$
269,842
Entities
with
Sales/
Revenue
Data
Compliance
costs
are
<
1%
of
sales
141
176
Compliance
costs
are

1
to
3%
of
sales
34
148
Compliance
costs
are

3%
of
sales
10
45
Compliance
Cost­
to­
Sales/
Revenue
Ratios
Average
0.78
1.65
Median
0.50
0.77
Maximum
7.83
38.83
Minimum
0.011
0.009
7­
12
(
excluding
the
federal
government)
and
0.78
(
1.65)
percent
for
small
entities.
Forty­
four
(
193)
small
parents
had
floor
CSRs
greater
than
1
percent,
assuming
add­
on
control
is
employed
to
meet
the
standard.
For
these
44
(
193)
parent
companies,
the
CSRs
ranged
from
1.00
(
1.00)
percent
to
7.83
(
38.83)
percent.
Ten
(
45)
entities
out
of
these
44
(
193)
had
CSRs
ratios
greater
than
3
percent.

7.6
Affected
Government
Entities
The
RFA
as
amended
by
SBREFA
provides
the
following
standard
definition
of
"
small
governmental
jurisdiction":
a
city,
county,
town,
township,
village,
school
district,
or
special
district
with
a
population
of
less
than
fifty
thousand.
Using
this
definition,
EPA
identified
thirteen
small
governmental
jurisdictions
that
own
and
operate
"
public
power"
producers
with
affected
boilers.
For
this
part
of
the
small
entity
analysis,
which
focuses
on
affected
government
entities,
public
power
producers
are
defined
as
nonprofit
publicly
owned
electrical
utilities
operated
by
municipalities,
counties,
and
states
or
other
publicly
owned
bodies
such
as
public
utility
districts.
This
excludes
rural
electric
cooperatives.

As
illustrated
in
Table
7­
5,
the
vast
majority
of
small
municipal
systems
with
affected
boilers
are
located
in
the
Midwest
(
11
systems
or
85
percent).
Four
of
the
eleven
municipal
systems
are
located
in
Minnesota,
with
two
in
Indiana
and
two
in
Michigan.

Table
7­
5.
Regional
Distribution
of
Municipal
Systems
Regional
Distribution
#
of
Facilities
East
Vermont
1
Midwest
Indiana
2
Iowa
1
Michigan
2
Minnesota
4
Ohio
1
Wisconsin
1
West
California
1
Total
13
Historically
municipal
utilities
were
set
up
to
provide
residents
of
a
community
with
reliable
energy.
For
example,
the
residential
sector
accounts
more
than
two
thirds
of
total
consumers
in
all
cases
(
see
Table
7­
6).
However
the
residential
sector
generally
represents
smallest
group
in
terms
of
total
energy
consumption.
The
industrial
and
commercial
sectors
consume
approximately
70
percent
of
total
energy
supplied.
Power
not
consumed
by
the
residential,
commercial
or
industrial
sectors
is
sold
into
wholesale
energy
market.

Table
7­
6.
Selected
Municipal
Utilities'
Capacity,
Usage
and
Consumer
Types
7­
13
Distribution
of
Energy
Usage
by
Customer
Type
Distribution
of
Customers
RO
W
ID
Capacit
y
(
MW)
Energy
Usage
Residentia
l
Commerc
ial
Industri
al
Total
Consumer
Residenti
al
Commercia
l
Industri
al
1
50.5
332,524,000
27%
NA
NA
19,313
82%
15%
3.7%

2
115
371,823,000
36%
28%
16%
15,615
87%
11%
0.3%

3
24.3
388,066,000
19%
10%
70%
9,082
84%
14%
1.0%

4
22.2
185,191,000
26%
14%
58%
6,235
86%
13%
1.6%

5
34.5
147,335,000
26%
27%
44%
5,955
86%
14%
0.3%

6
23
573,003,000
8%
NA
NA
7,207
90%
7%
1.0%

7
35
338,903,000
38%
8%
51%
13,247
87%
11%
1.3%

8
46
194,753,000
22%
NA
NA
6,890
85%
13%
0.1%

9
103.1
837,175,000
NA
NA
NA
NA
NA
NA
NA
10
32
218,208,000
40%
3%
55%
10,829
88%
3%
8.4%

11
26
267,201,000
16%
NA
NA
9,471
75%
24%
0.3%

12
34
95,642,000
33%
67%
NA
5,747
83%
17%
0.3%

Source:
Giles,
Ellen
F.
2000.
platts
Directory
of
Electric
Power
Producers
and
Distributors
109th
Edition
of
the
Electrical
World
Directory.
New
York:
McGraw
Hill.

Public
power
producers
do
not
pay
state
or
local
taxes.
However,
they
typically
are
under
agreement
to
make
annual
contributions
to
state
and
local
government
operating
funds.
In
addition,
they
are
not
guaranteed
at
rate
of
return
(
as
regulated
public
utilities
are),
however,

their
rates
are
set
by
agreement
with
local
councils
and
these
rates
are
typically
adjusted
to
reflect
changes
in
operating
costs.

Municipal
utilities
have
the
ability
to
generate
capital
through
the
issuance
of
tax
exempt
municipal
bonds.
These
municipal
bonds
are
exempt
from
federal
income
tax
which
allows
the
publicly
owned
utilities
to
finance
capital
projects
at
a
more
affordable
rate.
13Based
on
SBA
guidelines
for
determining
small
businesses.

7­
14
Additionally
the
local
governments
investing
in
municipal
utilities
generally
issue
revenue
bonds
rather
than
general
obligation
bonds.
This
ensures
that
the
debit
can
be
paid
back
through
revenues
from
the
generation
of
electricity
and
does
not
obligate
the
local
government
or
community
tax
base.

As
shown
in
Table
7­
7,
the
average
total
annual
compliance
costs
per
entity
are
$
223
thousand
under
the
floor
alternative
and
increase
to
$
548
thousand
for
the
above
 
the­
floor
alternative
(
Option
1A).
For
the
floor
alternative,
the
median
cost­
to­
revenue
ratio
is
0.94
percent
and
ratios
range
from
less
than
0.5
percent
to
8
percent.
Three
of
the
affected
small
governments
have
cost­
to­
revenue
ratios
at
or
above
3
percent.
Similar
analysis
for
the
above
the
MACT
floor
alternative
shows
the
median
cost­
to­
revenue
ratio
is
2.2
percent
and
ratios
range
from
less
than
0.5
percent
to
16
percent.
Five
of
the
thirteen
affected
small
governments
have
cost­
to­
revenue
ratios
at
or
above
3
percent.

Table
7­
7.
Summary
of
Impacts
to
Small
Government
Entities
Floor
Option
1A
Total
Number
of
Small
Entities
13
13
Average
Total
Annual
Compliance
Cost
(
TACC)
per
Small
Entity
($)
$
223
$
548
Compliance
Costs
are
<
1%
of
Revenue
7
2
Compliance
Costs
are
1
to
3%
of
Revenue
3
6
Compliance
Costs
are
>=
3%
of
Revenue
3
5
Average
Compliance
Cost
as
a
%
of
Revenue
1.67
4.18
Median
0.94
2.21
Maximum
7.83
16.30
Minimum
0.02
0.02
Source:
American
Public
Power
Association
(
APPA).
2002.
Straight
Answers
to
False
Charges
about
Public
Power.
Washington
D.
C.:
APPA.
As
obtained
on
November
13,
2003
at
http://
www.
appanet.
org/
about/
publicpower/
index.
cfm
.

7.6
Assessment
of
SBREFA
Screening
This
analysis
indicates
that
over
two­
thirds
of
the
parent
companies
affected
by
the
industrial
boilers
and
process
heaters
standard
are
large
companies.
13
The
relatively
small
proportion
of
small
businesses
affected
by
the
regulation
at
the
floor
level
is
due
in
part
to
the
exclusion
of
ICI
boilers
and
process
heaters
with
less
than
10
MMBtu
input
capacity
that
also
use
a
fossil
fuel
liquid
or
gas
as
primary
fuel.
As
a
result,
a
large
share
of
small
boilers
and
process
heaters,
which
are
presumably
owned
disproportionately
by
smaller
entities,
will
not
incur
compliance
costs.
The
Agency
estimates
that
approximately
57
percent
of
the
U.
S.
population
are
less
than
10
MMBtus
or
are
emergency
units
and,
hence,
are
excluded
from
the
proposed
regulation
for
the
floor
alternative.
These
units
are
included,
however,
in
the
Option
1A
above­
the­
floor
alternative,
except
where
they
consume
a
fossil
fuel
liquid
or
gas
other
than
residual
fuel
oil.

Of
the
small
businesses
affected
by
the
regulation,
the
majority
are
in
the
lumber
and
wood
products,
furniture
and
fixtures,
paper
and
allied
products,
and
electric,
gas
and
sanitary
services
sectors.
As
shown
in
Table
7­
5,
the
median
profit
margin
for
these
four
sectors
is
approximately
7­
15
3
percent.
Table
7­
5
also
shows
the
profit
margins
for
the
other
industry
sectors
with
affected
small
businesses.
All
profit
margins
of
industry
sectors
with
affected
small
businesses
are
above
2
percent.

After
considering
the
economic
impact
of
today's
rule
on
small
entities,
EPA
certifies
that
this
action
will
not
have
a
significant
impact
on
a
substantial
number
of
small
entities.
In
accordance
with
the
RFA,
as
amended
by
the
SBREFA,
5
U.
S.
C.
601,
et.
seq.,
EPA
conducted
an
assessment
of
the
standard
on
small
businesses
within
the
industries
affected
by
the
rule.
Based
on
SBA
size
definitions
for
the
affected
industries
and
reported
sales
and
employment
data,
the
Agency
identified
185
of
the
576
companies,
or
32
percent,
owning
affected
facilities
as
small
businesses.
Although
small
businesses
represent
32
percent
of
the
companies
within
the
SBREFA
screening
population,
they
are
expected
to
incur
only
8
percent
of
the
total
compliance
costs
of
$
445.6
million
(
1998$)
for
the
evaluated
576
firms.
Only
ten
small
firms
have
compliance
costs
equal
to
or
greater
than
3
percent
of
their
sales.
In
addition,
only
24
small
firms
have
CSRs
between
1
and
3
percent.

An
EIA
was
performed
to
estimate
the
changes
in
product
price
and
production
quantities
for
this
rule.
As
mentioned
in
the
summary
of
economic
impacts
earlier
in
this
report,
the
estimated
changes
in
prices
and
output
for
affected
firms
are
no
more
than
0.04
percent.

This
analysis
indicates
that
the
rule
should
not
generate
a
significant
impact
on
a
substantial
number
of
small
entities
for
following
reasons.
First,
only
31
small
firms
(
or
17
percent
of
all
affected
small
firms)
have
compliance
costs
equal
to
or
greater
than
1
percent
of
their
sales.
Of
these,
only
ten
small
firms
(
or
5
percent
of
all
affected
small
firms)
have
compliance
costs
equal
to
or
greater
than
3
percent
of
their
sales.
Second,
the
EIA
results
show
minimal
impacts
on
prices
and
output
from
affected
firms,
including
small
entities,
due
to
implementing
this
rule.
This
analysis
therefore
allows
us
to
certify
that
there
will
not
be
a
significant
impact
on
a
substantial
number
of
small
entities
from
the
implementing
this
rule.

This
rule
will
not
have
a
significant
economic
impact
on
a
substantial
number
of
small
entities
as
a
result
of
several
decisions
EPA
made
regarding
the
development
of
this
rulemaking
which
resulted
in
limiting
the
impact
of
this
rule
on
small
entities.
First,
as
mentioned
earlier,
EPA
identified
small
units
(
heat
input
of
10
MMBtu/
hr
or
less)
and
limited­
use
boilers
(
operate
less
than
10
percent
of
the
time)
as
separate
subcategories
from
large
units.
Many
small
and
limited­
use
units
are
located
at
small
entities.
As
also
discussed
earlier,
the
result
of
the
MACT
floor
analysis
for
these
subcategories
of
existing
sources
was
that
no
MACT
floor
could
be
identified
except
for
the
limited­
use
solid
fuel
subcategory,
which
is
less
stringent
than
the
MACT
floor
for
large
units.
Furthermore,
the
results
of
the
above­
the­
floor
analysis
for
these
subcategories
indicated
that
the
costs
would
be
too
high
to
be
Table
7­
5.
Profit
Margins
for
Industry
Sectors
with
Affected
Small
Businesses
SIC
Code
NAICS
Code
Description
Median
Profit
Margin
20
311
Food
and
Kindred
Products
3.6%

22
313
Textile
Mill
Products
2.1%

24
321
Lumber
and
Wood
Products
3.0%

25
337
Furniture
and
Fixtures
3.0%

26
322
Paper
and
Allied
Products
3.3%

28
325
Chemicals
and
Allied
Products
2.7%

49
221
Electric,
Gas,
and
Sanitary
Services
7.5%

Source:
Dun
&
Bradstreet.
1997.
Industry
Norms
&
Key
Business
Ratios.
Desktop
Edition
1996­
97.
Murray
Hill,
NJ:
Dun
&
Bradstreet,
Inc.
7­
16
considered
feasible.
Consequently,
this
rule
contains
no
emission
limitations
for
any
of
the
existing
small
and
limited­
use
subcategories
except
the
existing
limited­
use
solid
fuel
subcategory.
In
addition,
the
alternative
metals
emission
limit
resulted
in
minimizing
the
impacts
on
small
entities
because
some
of
the
potential
entities
burning
a
fuel
containing
very
little
metals
are
small
entities.
Finally,
the
riskbased
alternative
compliance
options
for
HCl
and
manganese
sources
may
also
serve
to
mitigate
impacts
to
small
entities.

References
U.
S.
Environmental
Protection
Agency,
Office
of
Air
Quality
Planning
and
Standards.
Industrial
Combustion
Coordinated
Rulemaking,
Inventory
Database
V4.1­
Boilers.
February
26,
1999.

U.
S.
Environmental
Protection
Agency,
Office
of
Air
Quality
Planning
and
Standards.
Industrial
Combustion
Coordinated
Rulemaking,
Inventory
Database
V4
­
Process
Heaters.
November
13,
1998.

U.
S.
Small
Business
Administration.
Small
Business
Size
Standards
by
NAICS
Codes.
February
22,
2002.
Found
on
the
Internet
at
http://
www.
sba.
gov/
size/
Table­
of­
Small­
Business­
Size­
Standards­
from­
final­
rule.
html.

References
Federal
Register,
2001.
Executive
Order
13211,
Actions
Concerning
Regulations
That
Significantly
Affect
Energy
Supply,
Distribution,
or
Use.
Vol.
66,
May
22,
2001,
pg.
28355.
8­
17
CHAPTER
8
EMISSIONS
INVENTORIES
AND
AIR
QUALITY
CHANGES
8.1
Results
in
Brief
An
analysis
of
changes
in
air
quality
associated
with
implementation
of
the
industrial
boilers
and
process
heaters
MACT
rule
shows
that
the
majority
of
the
U.
S.
population
in
2005
will
live
in
8­
18
areas
with
predicted
improvement
in
annual
average
visibility
of
between
0.4
to
0.6
deciviews
resulting
from
the
rule.
Almost
4
percent
of
the
projected
2005
U.
S.
population
are
predicted
to
experience
improved
annual
average
visibility
of
greater
than
0.25
deciviews.
Furthermore,
roughly
10
percent
of
the
projected
2005
U.
S.
population
will
benefit
from
reductions
in
annual
average
visibility
of
greater
than
0.1
deciviews.
The
mean
improvement
across
all
U.
S.
counties
is
0.05
deciviews,
or
almost
2
percent
from
baseline
visibility
levels.
In
urban
areas
(
i.
e.,
areas
with
a
population
of
250,000
or
more),
the
mean
improvement
in
annual
visibility
was
0.06
deciviews.
In
rural
areas
(
i.
e.
all
non­
urban
areas),
the
mean
improvement
in
visibility
was
0.04
deciviews
in
2005.

On
average,
the
Eastern
U.
S.
experienced
slightly
larger
absolute
but
smaller
relative
improvements
in
visibility
than
the
Western
U.
S.
from
the
emission
reductions
associated
with
this
rule.

8.2
Introduction
Executive
Order
12866
as
amended
by
E.
O.
13258
contains
as
one
its
requirements
the
assessment
of
benefits
for
any
major
rule,
where
a
major
rule
is
one
that
meets
one
or
more
of
the
4
criteria
listed
in
Chapter
1
of
this
RIA.
Since
this
regulation
is
a
major
rule
according
to
the
Executive
Order,
we
have
undertaken
to
estimate
the
benefits
associated
with
implementation
of
this
regulation.
Assessing
the
benefits
requires
knowledge
of
the
emission
reductions
resulting
from
application
of
this
rule,
the
change
in
air
quality
due
to
the
emission
reductions,
and
the
locations
where
these
emission
reductions
and
air
quality
changes
take
place.
This
chapter
of
the
RIA
presents
the
baseline
emissions
upon
which
the
emission
reductions
are
calculated
and
the
changes
in
air
quality
resulting
from
the
emission
reductions.

While
this
regulation
is
intended
to
reduce
HAP
emissions,
including
mercury,
from
industrial
boilers
and
process
heaters,
it
also
provides
reductions
in
non­
HAP
species
such
as
particulate
matter
(
PM)
and
sulfur
dioxide
(
SO2).
Reductions
in
PM
and
SO2
are
those
that
are
the
focus
of
the
benefits
assessment,
for
we
currently
have
sufficient
information
to
monetize
the
benefits
from
reductions
of
these
pollutants.
We
currently
lack
sufficient
information
to
monetize
the
benefits
from
the
HAP
and
mercury
reductions
from
this
regulation.
It
is
quite
possible
that
the
benefits
from
the
58,575
tons
of
HAP
reductions
and
the
1.7
tons
of
mercury
emission
reductions
may
be
substantial.

8.3
Baseline
Emissions
We
measure
air
quality
impact
as
a
change
in
concentration
in
PM
in
the
counties
affected
by
the
emission
reductions
taking
place
due
to
implementation
of
this
regulation.
In
this
case,
changes
in
particulate
matter
less
than
10
microns
(
PM10)
and
changes
in
the
particulate
matter
fraction
of
less
than
2.5
microns
(
PM2.5)
are
calculated
in
this
analysis.
Calculations
of
changes
in
both
PM
fractions
are
necessary
in
order
to
provide
a
more
complete
assessment
of
benefits.
In
addition,
changes
in
visibility
are
also
estimated
in
order
to
calculate
the
benefits
associated
with
this
category
of
effects.
In
order
to
determine
the
air
quality
impact
of
the
emission
reductions,
we
first
calculated
a
baseline,
then
took
the
PM
and
SO2
emission
reductions
prepared
in
the
engineering
analysis,
estimated
the
PM2.5
reductions
from
the
PM10
reductions,
and
then
entered
the
emission
reductions
into
an
air
quality
model.
This
section
describes
how
the
baseline
inventories
were
determined.

8.3.1
EPA's
Baseline
Inventory
8­
1
Initially,
our
plan
was
to
utilize
the
same
baseline
and
control
scenarios
being
analyzed
to
estimate
the
control
costs.
The
baseline
inventory
for
the
control
costs
is
the
Industrial
Combustion
Coordinated
Rulemaking
(
ICCR)
inventory
database,
which
was
developed
to
support
the
rulemakings
for
the
Combustion
Turbines
and
Reciprocating
Internal
Combustion
Engine
MACTs
as
well
as
this
MACT.
However,
we
were
unable
to
use
this
baseline
inventory
because
it
did
not
contain
a
number
of
data
fields
necessary
for
air
quality
modeling
and
possessed
incomplete
data
at
the
unit
level
necessary
for
such
modeling.
Instead,
we
included
1996
National
Emission
Trends
(
NET)
inventory
data
for
these
sources
to
augment
the
ICCR
data
in
order
to
prepare
an
inventory
with
sufficient
data
for
the
air
quality
modeling.
The
NET
inventory
provides
baseline
emissions
data
of
criteria
pollutants
from
point,
area,
and
mobile
sources.
Version
3.12
of
the
NET
is
being
used
to
prepare
the
baseline
inventory
for
this
air
quality
analysis.
The
ICCR
inventory
provides
the
PM
and
SO2
emissions.
All
other
pollutant
emissions
used
to
establish
the
baseline
inventory
are
taken
from
the
NET.
Readers
desiring
more
information
about
the
inventory
methodologies
or
results
should
consult
those
documents
for
details.

The
baseline
reflects
air
quality
and
emissions
present
in
1996,
therefore,
it
reflects
controls
from
various
air
pollution
programs
that
are
implemented
by
1996.
To
the
extent
that
additional
controls
are
implemented
before
2005,
the
year
of
analysis
in
this
report,
the
air
quality
results
would
differ
but
the
extent
of
the
difference
cannot
be
determined.
To
our
knowledge,
only
phase
II
of
the
the
Acid
Rain
Program
which
was
implemented
at
utility
sources
nationwide
in
2000
could
influence
baseline
emission
inventories.
For
more
details
see
Pechan,
2001.

The
analysis
uses
a
baseline
inventory
with
a
base
year
of
1996
to
estimate
the
benefits
of
the
regulation
in
2005.
We
determined
that
minimal
changes
in
unit
population
and
baseline
emissions
would
occur
between
the
current
time
and
2005,
so
that
the
use
of
this
inventory
without
imposition
of
growth
factors
was
deemed
adequate.

8.3.2
The
MACT
floor
and
Other
Emissions
Reduction
Scenarios
Table
8­
1
summarizes
the
baseline
PM10,
PM2.5,
and
SO2
emissions
and
emission
reductions
nationwide
for
the
MACT
floor
option.
Baseline
emission
and
emission
reductions
nationwide
for
Option
1A,
an
above­
the­
MACT
floor
option,
are
presented
in
Appendix
C
of
the
RIA.
These
regulatory
options
are
described
in
Chapter
1
of
the
RIA.
The
air
quality
analysis
presumes
no
change
in
volatile
organic
compound
(
VOC),
nitrogen
oxides
(
NOx),
carbon
monoxide
(
CO),
and
ammonia
(
NH3)
emissions.
Hence,
the
baseline
emissions
for
these
pollutants
are
not
shown
in
this
table.
For
these
baseline
emissions,
refer
to
Pechan,
2001.

The
split
of
emission
reductions
shown
in
the
latter
two
columns
results
from
the
assignment
of
specific
control
devices
to
only
a
portion
of
the
affected
units.
The
emissions
reductions
associated
with
this
portion,
which
is
slightly
more
than
half
of
the
known
affected
units,
can
be
included
in
the
benefits
model
(
described
in
Chapter
10
of
the
RIA)
for
calculation
of
the
benefits
from
these
reductions.
This
is
true
since
these
emission
reductions
can
be
linked
to
decreased
exposures
to
affected
populations.
For
the
emission
reductions
from
the
other
affected
others,
we
employ
a
benefits
transfer
method
that
takes
the
benefits
values
estimated
for
the
units
with
assigned
control
devices
and
transfers
them
to
these
remaining
emission
reductions
to
estimate
the
resulting
monetized
benefits.
For
more
information
on
the
benefits
transfer
method,
refer
to
Chapter
10.

As
mentioned
earlier
in
this
chapter,
we
conducted
no
air
quality
modeling
for
the
HAP
or
the
mercury
emission
reductions
that
occur
from
implementation
of
this
regulation.
These
emission
reductions
are
listed
in
Table
8­
2.
For
a
description
of
how
HAP
emissions
and
emission
factors
are
8­
2
estimated
for
this
rule,
refer
to
the
emission
factors/
emissions
estimates
memo
in
the
public
docket
(
ERG,
2002).

Table
8­
1.
Summary
of
Nationwide
Baseline
Emissions
and
Emission
Reductionsa
for
the
MACT
floor,
Existing
Units
Onlyb,
c
in
2005
Pollutant
Source
Type
1996
Baseline
Emissions
(
tons/
year)
MACT
Floor
Option
Emission
Known
Affected
Units
Unknown
Affected
Units
Total
Emission
Reductions
for
MACT
floor
option
Option
1A
Emission
Reductions
Known
Unknown
Total
Affected
Affected
Units
Units
SO2
Point
3,745,790
82,542
30,394
112,936
95,361
41,372
136,733
Area
1,397,425
­

Motor
Vehicle
302,938
­

Nonroad
840,167
­

PM10
Point
1,167,995
266,491
298,109
564,600
313,947
255,282
569,229
Area
30,771,607
­

Motor
Vehicle
294,764
­

Nonroad
463,579
­
8­
3
PM2.5
Point
576,022
75,095
84,125
159,220
94,565
76,894
171,459
Area
6,675,777
­

Motor
Vehicle
230,684
­

Nonroad
410,334
­
a
Reductions
are
Baseline
Emissions
­
Control
Scenario
Emissions.
All
emissions
estimates
are
in
tons.

b
The
totals
reflect
emissions
for
the
48
contiguous
States,
excluding
Alaska
and
Hawaii.

cThe
totals
do
not
reflect
new
source
emissions
and
emission
reductions.
These
emission
reductions
were
not
considered
in
the
air
quality
modeling
since
they
were
far
smaller
that
those
for
existing
units
(
484
tons
for
PM10
from
new
units,
versus
564,600
tons
from
existing
units).
The
differences
between
such
emission
reductions
for
PM2.5
are
identical,
since
PM2.5
emissions
are
derived
from
PM10
emissions.
Also,
the
differences
between
SO2
emission
reductions
for
existing
and
new
units
are
just
as
great.

Table
8­
2.
HAP
Emission
Reductions
for
the
MACT
floor
option,
2005
Existing
Sources
Only
Pollutant
Emission
Reductions
(
tons/
year)

MACT
floor
HCl
42,100
Pb
105
Hg
1.7
Non­
mercury
metalsa
1,080
Selected
inorganicsb
18,000
Total
HAP
reductions
58,350
aNon­
mercury
metals
include:
arsenic,
beryllium,
cadmium,
chromium,
manganese,
and
nickel.

bSelected
inorganics
include:
chlorine,
hydrofluoric
acid,
and
phosphorus.

8.4
Air
Quality
Impacts
This
section
summarizes
the
methods
for
and
results
of
estimating
air
quality
for
the
baseline
and
control
scenarios.
Based
on
the
emissions
inventories
described
above,
ambient
particulate
matter
(
PM10
and
PM2.5)
concentrations
are
projected
from
the
S­
R
Matrix
developed
from
the
Climatological
Regional
Dispersion
Model
(
CRDM).
In
Section
8.3.1,
we
provide
brief
background
on
the
S­
R
Matrix
model.
In
Section
8.3.2,
we
estimate
PM
air
quality,
and
in
Section
8.3.3,
we
estimate
visibility
degradation.
Visibility
degradation
(
i.
e.,
regional
haze),
is
developed
using
empirical
estimates
of
light
extinction
coefficients
and
efficiencies
in
combination
with
modeled
reductions
in
pollutant
concentrations.
14
The
PM
Calculator
Tool
can
be
found
on
the
Internet
at
www.
epa.
gov/
chief/
software/
pmcalc/
index.
html.

8­
4
8.4.1.
PM
Air
Quality
Modeling
EPA
used
the
emissions
inputs
described
above
with
a
national­
scale
source­
receptor
(
S­
R)
Matrix
to
evaluate
the
effects
of
the
milestone
reductions
on
ambient
concentrations
of
both
PM10
and
PM2.5.
Ambient
concentrations
of
PM
are
composed
of
directly
emitted
particles
and
of
secondary
aerosols
of
sulfate,
nitrate,
ammonium,
and
organics.

The
S­
R
Matrix
was
developed
from
multiple
simulations
of
the
CRDM
using
meteorological
data
for
1990
coupled
with
emissions
data
from
version
2.0
of
the
1990
National
Particulate
Inventory
(
NPI).
Relative
to
more
sophisticated
and
resource­
intensive
three­
dimensional
modeling
approaches,
the
CRDM
and
its
associated
S­
R
Matrix
do
not
fully
account
for
all
the
complex
chemical
interactions
that
take
place
in
the
atmosphere
in
the
secondary
formation
of
PM.
Instead
it
relies
on
more
simplistic
species
dispersion
 
transport
mechanisms
supplemented
with
chemical
conversion
at
the
receptor
location.

The
S­
R
Matrix
consists
of
fixed­
coefficients
that
reflect
the
relationship
between
annual
average
PM
concentration
values
at
a
single
receptor
in
each
county
(
i.
e.,
a
hypothetical
monitor
sited
at
the
county
population
centroid)
and
the
contribution
by
PM
species
to
this
concentration
from
each
emission
source
(
E.
H.
Pechan,
1996).
The
modeled
receptors
include
all
U.
S.
county
centroids
as
well
as
receptors
in
10
Canadian
provinces
and
29
Mexican
cities/
states.
The
methodology
used
here
for
estimating
PM
air
quality
concentrations
is
detailed
in
Pechan­
Avanti
(
2000)
and
is
similar
to
the
method
used
in
the
July
1997
PM
and
Ozone
NAAQS
RIA
(
U.
S.
EPA,
1997e)
and
the
RIA
for
the
final
Regional
Haze
Rule
(
U.
S.
EPA,
1999a),
and
the
Tier
2/
Gasoline
Sulfur
Rule
(
US
EPA,
1999c).

8.4.2
PM
Air
Quality
Results
This
section
presents
the
projected
reductions
in
particulate
matter
concentrations
resulting
from
reductions
in
SO2
and
PM10,
with
PM2.5
emissions
being
derived
from
the
PM10
emissions
using
the
PM
Calculator
tool14
for
the
final
rule
(
MACT
floor).
The
results
for
the
above­
the­
floor
option,
Option
1A,
are
presented
in
Appendix
C
of
the
RIA.

8.4.2.1
MACT
Floor
Option
Table
8­
3
provides
a
summary
of
the
predicted
ambient
PM10
and
PM2.5
concentrations
from
the
S­
R
matrix
for
the
2005
baseline
and
changes
associated
with
the
rule.
The
results
indicate
that
the
predicted
change
in
PM
concentrations
is
composed
almost
entirely
of
reductions
in
fine
particulates
(
PM2.5)
with
little
or
no
reduction
in
coarse
particles
(
PM10
less
PM2.5).
Therefore,
the
observed
changes
in
PM10
are
composed
primarily
of
changes
in
PM2.5.
In
addition
to
the
standard
frequency
statistics
(
e.
g.,
minimum,
maximum,
average,
median),
Table
8­
3
provides
the
population­
weighted
average
which
better
reflects
the
baseline
levels
and
predicted
changes
for
more
populated
areas
of
the
nation.
This
measure,
therefore,
will
better
reflect
the
potential
benefits
of
these
predicted
changes
through
exposure
changes
to
these
populations.
As
shown,
the
average
annual
mean
concentrations
of
PM2.5
across
all
U.
S.
grid­
cells
declines
by
roughly
0.8
percent,
or
0.09

g/
m3.
The
population­
8­
5
weighted
average
annual
mean
PM2.5
concentration
declined
by
0.7
percent,
or
0.10

g/
m3,
which
is
roughly
similar
in
absolute
terms
to
the
spatial
average.
This
indicates
the
rule
generates
roughly
equivalent
absolute
air
quality
improvements
in
less
populated,
rural
areas
as
in
more
populated,
urban
areas.

Table
8­
3.

Summary
of
2005
Base
Case
PM
Air
Quality
and
Changes
Due
to
MACT
Floor
Option:
Industrial
Boiler/
Process
Heater
Source
Categories
Statistic
2005
Baseline
Changea
Percent
Change
PM10
Minimum
Annual
Mean
(

g/
m3)
b
6.09
­
0.07
­
1.2%

Maximum
Annual
Mean
(

g/
m3)
b
69.30
­
0.03
­
0.1%

Average
Annual
Mean
(

g/
m3)
22.68
­
0.32
­
1.4%

Median
Annual
Mean
(

g/
m3)
21.84
­
0.36
­
1.6%

Population­
Weighted
Average
Annual
Mean
(

g/
m3)
c
28.79
­
0.33
­
1.1%

PM2.5
Minimum
Annual
Mean
(

g/
m3)
b
0.74
­
0.01
0.0%

Maximum
Annual
Mean
(

g/
m3)
b
30.35
­
0.71
­
2.3%

Average
Annual
Mean
(

g/
m3)
11.15
­
0.09
­
0.8%

Median
Annual
Mean
(

g/
m3)
11.11
­
0.11
­
1.1%

Population­
Weighted
Average
Annual
Mean
(

g/
m3)
c
13.50
­
0.10
­
0.7%

a
The
change
is
defined
as
the
control
case
value
minus
the
baseline
value.

b
The
baseline
minimum
(
maximum)
is
the
value
for
the
populated
county
with
the
lowest
(
highest)
annual
average.
The
change
relative
to
the
baseline
is
the
observed
change
for
the
populated
county
with
the
lowest
(
highest)
annual
average
in
the
baseline.

c
Calculated
by
summing
the
product
of
the
projected
2005
county
population
and
the
estimated
2005
PM
concentration
for
that
county,
and
then
dividing
by
the
total
population
in
the
48
contiguous
States.

Table
8­
4
provides
information
on
the
2005
populations
that
will
experience
improved
PM
air
quality.
There
are
significant
populations
that
live
in
areas
with
meaningful
reductions
in
annual
mean
PM2.5
concentrations
resulting
from
the
rule.
As
shown,
just
over
2
percent
of
the
2005
U.
S.
population
are
predicted
to
experience
reductions
of
greater
than
0.5

g/
m3.
Furthermore,
almost
8
percent
of
the
2005
U.
S.
population
will
benefit
from
reductions
in
annual
mean
PM2.5
concentrations
of
greater
than
0.2

g/
m3
and
slightly
over
28
percent
will
live
in
areas
with
reductions
of
greater
than
0.1

g/
m3.
This
information
indicates
how
widespread
the
improvements
in
PM
air
quality
are
expected
to
be
and
the
large
populations
that
will
benefit
from
these
improvements.

Table
8­
4.

Distribution
of
PM2.5
Air
Quality
Improvements
Over
2005
Population
Due
to
MACT
Floor
Option:
Industrial
Boiler/
Process
Heater
Source
Categories
8­
6
2005
Population
Change
in
Annual
Mean
PM2.5
Concentrations
(

g/
m3)
Number
(
millions)
Percent
(%)

0
>
 
PM2.5
Conc

0.05
105.0
37.1%

0.05
>
 
PM2.5
Conc

0.1
56.3
19.9%

0.1
>
 
PM2.5
Conc

0.25
57.2
20.2%

0.25
>
 
PM2.5
Conc

0.5
17.1
6.1%

0.5
>
 
PM2.5
Conc

1.0
4.5
1.6%

1.0
>
 
PM2.5
Conc

2.0
1.3
0.5%

 
PM2.5
Conc
>
2.0
0.2
0.1%

a
The
change
is
defined
as
the
control
case
value
minus
the
baseline
value.

Table
8­
5
provides
additional
insights
on
the
changes
in
PM
air
quality
resulting
from
the
final
rule.
The
information
presented
previously
in
Table
8­
3
illustrated
the
absolute
and
relative
changes
for
different
points
along
the
distribution
of
baseline
2005
PM
concentration
levels,
e.
g.,
the
change
reflects
the
lowering
of
the
minimum
predicted
baseline
concentration
rather
than
the
minimum
predicted
change
for
2005.
The
latter
is
the
focus
of
Table
8­
5
as
it
presents
the
distribution
of
predicted
changes
in
both
absolute
terms
(
i.
e.,

g/
m3)
and
relative
terms
(
i.
e.,
percent)
across
individual
grid­
cells.
Therefore,
it
provides
more
information
on
the
range
of
predicted
changes
that
as
shown,
the
absolute
reduction
in
annual
mean
PM10
concentration
ranged
from
a
low
of
0.00

g/
m3
to
a
high
of
16.89

g/
m3,
while
the
relative
(
or
percent)
reduction
ranged
from
a
low
of
0.0
percent
to
a
high
of
50.5
percent.
Alternatively,
for
mean
PM2.5,
the
absolute
reduction
ranged
from
0.00
to
4.65

g/
m3,
while
the
relative
reduction
ranged
from
0.0
to
29.4
percent.

Table
8­
5.

Summary
of
Absolute
and
Relative
Changes
in
PM
Air
Quality
Due
to
MACT
Floor
Option:
Industrial
Boiler/
Process
Heater
Source
Categories
Statistic
PM10
Annual
Mean
PM2.5
Annual
Mean
Absolute
Change
from
2005
Baseline
(

g/
m3)
a
Minimum
0.00
0.00
Maximum
­
16.89
­
4.65
Average
­
0.32
­
0.09
8­
7
Median
­
0.16
­
0.05
Population­
Weighted
Average
c
­
0.33
­
0.10
Relative
Change
from
2005
Baseline
(%)
b
Minimum
0.00%
0.00%

Maximum
­
50.52%
­
29.37%

Average
­
1.32%
­
0.70%

Median
­
0.78%
­
0.50%

Population­
Weighted
Average
c
­
1.26%
­
0.71%

a
The
absolute
change
is
defined
as
the
control
case
value
minus
the
baseline
value
for
each
county.

b
The
relative
change
is
defined
as
the
absolute
change
divided
by
the
baseline
value,
or
the
percentage
change,
for
each
county.
The
information
reported
in
this
section
does
not
necessarily
reflect
the
same
county
as
is
portrayed
in
the
absolute
change
section.

c
Calculated
by
summing
the
product
of
the
projected
2005
county
population
and
the
estimated
2005
county
PM
absolute/
relative
measure
of
change,
and
then
dividing
by
the
total
population
in
the
48
contiguous
states.

For
this
standard,
the
MACT
floor
was
chosen
as
the
final
alternative.
For
more
information
on
the
choice
of
this
option
as
the
alternative,
please
refer
to
Chapter
1
of
this
RIA
and
the
preamble.

It
should
be
noted
that
air
quality
modeling
runs
using
the
S­
R
matrix
are
available
for
cases
in
which
only
PM
emission
reductions
occur
and
only
SO2
reductions
occur.
These
runs
are
necessary
as
inputs
to
the
benefits
transfer
method
that
estimates
monetized
benefits
for
emissions
from
sources
that
are
not
linked
to
a
specific
control
device.
Results
from
these
pollutant­
specific
runs
are
presented
in
the
technical
support
document
(
Pechan,
2001).
The
benefits
transfer
method
is
explained
in
Chapter
10,
and
results
from
the
use
of
that
method
are
also
shown
in
that
chapter.

8.4.3.
Visibility
Degradation
Estimates
Visibility
degradation
is
often
directly
proportional
to
decreases
in
light
transmittal
in
the
atmosphere.
Scattering
and
absorption
by
both
gases
and
particles
decrease
light
transmittance.
To
quantify
changes
in
visibility,
our
analysis
computes
a
light­
extinction
coefficient,
based
on
the
work
of
Sisler
(
1996),
which
shows
the
total
fraction
of
light
that
is
decreased
per
unit
distance.
This
coefficient
accounts
for
the
scattering
and
absorption
of
light
by
both
particles
and
gases,
and
accounts
for
the
higher
extinction
efficiency
of
fine
particles
compared
to
coarse
particles.
Fine
particles
with
significant
light­
extinction
efficiencies
include
sulfates,
nitrates,
organic
carbon,
elemental
carbon
(
soot),
and
soil
(
Sisler,
1996).

Based
upon
the
light­
extinction
coefficient,
we
also
calculated
a
unitless
visibility
index,
called
a
"
deciview,"
which
is
used
in
the
valuation
of
visibility.
The
deciview
metric
provides
a
linear
scale
for
perceived
visual
changes
over
the
entire
range
of
conditions,
from
clear
to
hazy.
Under
many
scenic
conditions,
the
average
person
can
generally
perceive
a
change
of
one
deciview.
The
higher
the
deciview
value,
the
worse
the
visibility.
Thus,
an
improvement
in
visibility
is
a
decrease
in
deciview
value.
8­
8
Table
8­
6
provides
the
distribution
of
visibility
improvements
across
the
2005
U.
S.
population
resulting
from
the
industrial
boilers
and
process
heaters
rule.
The
majority
of
the
2005
U.
S.
population
live
in
areas
with
predicted
improvement
in
annual
average
visibility
of
between
0.4
to
0.6
deciviews
resulting
from
the
rule.
As
shown,
almost
4
percent
of
the
2005
U.
S.
population
are
predicted
to
experience
improved
annual
average
visibility
of
greater
than
0.25
deciviews.
Furthermore,
roughly
10
percent
of
the
2005
U.
S.
population
will
benefit
from
reductions
in
annual
average
visibility
of
greater
than
0.1
deciviews.
The
information
provided
in
Table
8­
6
indicates
how
widespread
the
improvements
in
visibility
are
expected
to
be
and
the
share
of
populations
that
will
benefit
from
these
improvements.

Because
the
visibility
benefits
analysis
distinguishes
between
general
regional
visibility
degradation
and
that
particular
to
Federally­
designated
Class
I
areas
(
i.
e.,
national
parks,
forests,
recreation
areas,
wilderness
areas,
etc.),
we
separated
estimates
of
visibility
degradation
into
"
residential"
and
"
recreational"
categories.
The
estimates
of
visibility
degradation
for
the
"
recreational"
category
apply
to
Federally­
designated
Class
I
areas,
while
estimates
for
the
"
residential"
category
apply
to
non­
Class
I
areas.
Deciview
estimates
are
estimated
using
outputs
from
the
S­
R
matrix
for
the
2005
baseline
and
the
MACT
floor,
which
are
the
same
scenarios
for
which
changes
in
PM10
and
PM2.5
concentrations
are
estimated
and
shown
earlier
in
this
chapter.
Deciview
estimates
for
Option
1A
are
presented
in
Appendix
C
of
this
RIA
Table
8­
6.

Distribution
of
Populations
Experiencing
Visibility
Improvements
in
2005
Due
to
MACT
Floor
Option:
Industrial
Boiler/
Process
Heater
Source
Categories
2005
Population
Improvements
in
Visibility
a
(
annual
average
deciviews)
Number
(
millions)
Percent
(%)

 
Deciview
=
0
46.0
16.3%

0
>
 
Deciview

0.05
168.5
59.5%

0.05
>
 
Deciview

0.1
41.1
14.5%

0.1
>
 
Deciview

0.15
11.5
4.1%

0.15
>
 
Deciview

0.25
5.9
2.1%

0.25
>
 
Deciview

0.5
3.7
3.1%

 
Deciview
>
0.5
1.1
0.4%

a
The
change
is
defined
as
the
MACT
Floor
control
case
deciview
level
minus
the
baseline
deciview
level.

8.4.4
Residential
Visibility
Improvements
Air
quality
modeling
results
predict
that
the
rule
will
create
improvements
in
visibility
through
the
country.
In
Table
8­
7,
we
summarize
residential
visibility
improvements
across
the
Eastern
and
Western
U.
S.
in
2005.
The
baseline
annual
average
visibility
for
all
U.
S.
counties
is
21.2
deciviews.
The
mean
improvement
across
all
U.
S.
counties
is
0.05
deciviews,
or
almost
2
percent.
In
urban
areas
8­
9
(
i.
e.,
areas
with
a
population
of
250,000
or
more),
the
mean
improvement
in
annual
visibility
was
0.06
deciviews.
In
rural
areas
(
i.
e.
all
non­
urban
areas),
the
mean
improvement
in
visibility
was
0.04
deciviews
in
2005.

On
average,
the
Eastern
U.
S.
experienced
slightly
larger
absolute
but
smaller
relative
improvements
in
visibility
than
the
Western
U.
S.
from
the
industrial
boilers
and
process
heaters
emission
reductions.
In
Eastern
U.
S.,
the
mean
improvement
was
0.05
deciviews
from
an
average
baseline
of
22.00
deciviews.
Western
counties
experienced
a
mean
improvement
of
0.01
deciviews
from
an
average
baseline
of
17.82
deciviews
projected
in
2005.
Overall,
the
data
suggest
that
the
rule
has
the
potential
to
provide
some
improvements
in
visibility
across
the
U.
S.
in
2005.

Table
8­
7.

Summary
of
2005
Baseline
Visibility
and
Changes
by
Region
for
the
MACT
Floor
Option:
Residential
(
Annual
Average
Deciviews)

Regionsa
2005
Baseline
Changeb
Percent
Change
Eastern
U.
S.
22.00
­
0.05
­
0.2%

Urban
22.95
­
0.06
­
0.3%

Rural
21.62
­
0.05
­
0.2%

Western
U.
S.
17.82
­
0.01
­
0.1%

Urban
19.19
­
0.01
­
0.1%

Rural
17.55
­
0.01
­
0.1%

National,
all
counties
21.19
­
0.05
­
0.2%

Urban
22.49
­
0.06
­
0.3%

Rural
20.72
­
0.04
­
0.2%

a
Eastern
and
Western
regions
are
separated
by
100
degrees
West
longitude.
Background
visibility
conditions
differ
by
region.

b
An
improvement
in
visibility
is
a
decrease
in
deciview
value.
The
change
is
defined
as
the
MACT
Floor
control
case
deciview
level
minus
the
baseline
deciview
level.

8.4.5.
Recreational
Visibility
Improvements
In
Table
8­
8,
we
summarize
recreational
visibility
improvements
by
region
in
2005
in
Federal
Class
I
areas.
These
recreational
visibility
regions
are
shown
in
Figure
8­
1.
As
shown,
the
national
improvement
in
visibility
for
these
areas
is
0.1
percent,
or
0.02
deciviews.
Predicted
relative
visibility
improvements
are
the
largest
in
the
Eastern
U.
S.
as
shown
for
the
Southeast
(
0.4%),
and
the
Northeast/
Midwest
(
2.3%).
The
Southwest
and
California
regions
are
predicted
to
have
the
smallest
relative
visibility
improvement
at
0.0
percent,
or
0.00
deciview
decline
from
the
baseline.
8­
10
Table
8­
8.

Summary
of
2005
Baseline
Visibility
and
Changes
by
Region
for
the
MACT
Floor
Option:
Recreational
(
Annual
Average
Deciviews)

Class
I
Visibility
Regionsa
2005
Baseline
Changeb
Percent
Change
Southeast
21.49
­
0.08
­
0.4%

Southwest
17.18
0.00
0.0%

California
19.86
0.00
0.0%

Northeast/
Midwest
20.64
­
0.04
­
0.2%

Rocky
Mountain
17.29
­
0.01
­
0.1%

Northwest
20.62
­
0.01
­
0.1%

National
Average
(
unweighted)
19.17
­
0.02
­
0.1%

a
Regions
are
pictured
in
Figure
8­
1
and
are
defined
in
the
technical
support
document
to
the
Heavy
Duty
Vehicle/
Diesel
Fuel
TSD,
U.
S.
EPA,
2001.

b
An
improvement
in
visibility
is
a
decrease
in
deciview
value.
The
change
is
defined
as
the
MACT
Floor
control
case
deciview
level
minus
the
baseline
deciview
level.
8­
11
Nor
thwest
Rocky
Mountain
Nor
theast/
Midwest
Southeast
Southwest
California
Study
Region
Transfer
Region
Note:
Study
regions
were
represented
in
the
Chestnut
and
Rowe
(
1990a,
1990b)
studies
used
in
evaluating
the
benefits
of
visibility
improvements,
while
transfer
regions
used
extrapolated
study
results.
These
are
referred
to
in
the
Heavy
Duty
Vehicle/
Diesel
Fuel
Benefits
TSD
(
U.
S.
EPA,
2000).

Figure
8­
1.
Recreational
Visibility
Regions
for
Continental
U.
S.
8­
12
References
Eastern
Research
Group.
Memorandum
to
Jim
Eddinger,
U.
S.
Environmental
Protection
Agency,
Office
of
Air
Quality
Planning
and
Standards.
"
Development
of
Average
Emission
Factors
and
Baseline
Emissions
Estimates
for
the
Industrial,
Commercial,
and
Institutional
Boiler
and
Process
Heater
NESHAP."
Draft
Memorandum.
May
23,
2002.

E.
H.
Pechan
&
Associates,
Inc.
"
Emissions
and
Air
Quality
Impacts
of
NESHAP
for
Industrial,
Commercial,
and
Institutional
Boilers
and
Process
Heaters."
Revised
Final
Report.
March,
2001.

Sisler,
J.
"
Spatial
and
Seasonal
Patterns
and
Long
Term
Variability
of
the
Composition
of
Haze
in
the
United
States
(
An
Analysis
of
Data
from
the
IMPROVE
Network),"
report
prepared
for
the
Cooperative
Institute
for
Research
in
the
Atmosphere,
Colorado
State
University,
1996.

U.
S.
Environmental
Protection
Agency,
Regulatory
Impact
Analysis:
Heavy­
Duty
Engine
and
Vehicle
Standards
and
Highway
Diesel
Fuel
Sulfur
Control
Requirements.
Prepared
by:
Office
of
Air
and
Radiation.
Available
at
http://
www.
epa.
gov/
otaq/
diesel.
htm.
December,
2000.
9­
13
CHAPTER
9
QUALITATIVE
ASSESSMENT
OF
BENEFITS
OF
EMISSION
REDUCTIONS
The
emission
reductions
achieved
by
this
environmental
regulation
will
provide
benefits
to
society
by
improving
environmental
quality.
In
this
chapter,
and
the
following
chapter,
information
is
provided
on
the
types
and
levels
of
social
benefits
anticipated
from
the
Industrial
and
Commercial
Boilers
and
Process
Heaters
NESHAP.
This
chapter
discusses
the
health
and
welfare
effects
associated
with
the
HAPs
and
other
pollutants
emitted
by
affected
boilers
and
process
heaters.
The
following
chapter
places
a
monetary
value
on
a
portion
of
the
benefits
that
are
described
here.

In
general,
the
reduction
of
HAP
emissions,
including
mercury,
resulting
from
the
regulation
will
reduce
human
and
environmental
exposure
to
these
pollutants
and
thus,
reduce
potential
adverse
health
and
welfare
effects.
This
chapter
provides
a
general
discussion
of
the
various
components
of
total
benefits
that
may
be
gained
from
a
reduction
in
HAPs
and
mercury
through
this
NESHAP.
The
rule
will
also
achieve
reductions
of
particulate
matter
(
PM),
both
coarse
(
PM10)
and
fine
(
PM2.5)
particle
fractions,
and
sulfur
dioxide
(
SO2),
which
results
in
additional
health
and
welfare
benefits
above
those
achieved
by
the
HAP
reductions.
HAP
benefits
are
presented
separately
from
the
benefits
associated
with
other
pollutant
reductions.

9.1
Identification
of
Potential
Benefit
Categories
The
benefit
categories
associated
with
the
emission
reductions
predicted
for
this
regulation
can
be
broadly
categorized
as
those
benefits
which
are
attributable
to
reduced
exposure
to
HAPs,
and
those
attributable
to
reduced
exposure
to
other
pollutants.
Several
of
the
HAPs
associated
with
this
regulation
have
been
classified
as
known
or
probable
human
carcinogens.
As
a
result,
one
of
the
benefits
of
the
proposed
regulation
is
a
reduction
in
the
risk
of
cancer.
Other
benefit
categories
include:
reduced
incidence
of
neurological
effects
and
irritations
of
the
lungs
and
skin,
reduced
mortality
and
other
morbidity
effects
associated
with
PM
and
SO2
(
as
it
transforms
into
PM).
In
addition
to
health
impacts
occurring
as
a
result
of
reductions
in
HAPs
and
other
pollutant
emissions,
there
are
welfare
impacts
which
can
also
be
identified.
In
general,
welfare
impacts
include
effects
on
crops
and
other
plant
life,
materials
damage,
soiling,
visibility
impairment,
and
acidification
of
water
bodies.
Each
category
is
discussed
separately
in
the
following
section.

9.2
Qualitative
Description
of
Air
Related
Benefits
The
health
and
welfare
benefits
of
HAPs,
including
mercury,
PM,
and
SO2
reductions
are
summarized
separately
in
the
discussions
below.

9.2.1
Benefits
of
Reducing
HAP
Emissions
According
to
baseline
emission
estimates,
the
source
categories
affected
by
this
currently
emits
approximately
102,927
tons
per
year
of
HAPs
at
existing
sources
including
about
11
tons
of
mercury
and
it
is
estimated
that
by
the
year
2005,
new
boilers
and
process
heaters
will
emit
1,548
tons
9­
14
per
year
of
HAPs
and
0.4
tons
of
mercury.
This
totals
104,474
tons
of
HAPs
and
11.4
tons
of
mercury
annually
at
all
boiler
and
process
heater
sources.
The
regulation
will
reduce
approximately
58,575
tons
of
emissions
of
HAPs
and
1.9
tons
of
mercury
at
new
and
existing
sources
by
2005.
For
more
information
on
these
HAP
emissions
and
emission
reductions,
please
refer
to
Chapter
8
of
this
RIA
and
the
docket
for
this
rule.

Human
exposure
to
these
HAPs
may
occur
directly
through
inhalation
or
indirectly
through
ingestion
of
food
or
water
contaminated
by
HAPs
or
through
exposure
to
the
skin.
HAPs
may
also
enter
terrestrial
and
aquatic
ecosystems
through
atmospheric
deposition.
HAPs
can
be
deposited
on
vegetation
and
soil
through
wet
or
dry
deposition.
HAPs
may
also
enter
the
aquatic
environment
from
the
atmosphere
via
gas
exchange
between
surface
water
and
the
ambient
air,
wet
or
dry
deposition
of
particulate
HAPs
and
particles
to
which
HAPs
adsorb,
and
wet
or
dry
deposition
to
watersheds
with
subsequent
leaching
or
runoff
to
bodies
of
water
(
EPA,
1992a).
This
analysis
is
focused
only
on
the
air
quality
benefits
of
HAP
reduction.

9.2.1.1
Health
Benefits
of
HAP
and
Mercury
Reductions.

The
HAP
emission
reductions
achieved
by
this
rule
are
expected
to
reduce
exposure
to
ambient
concentrations
of
arsenic,
cadmium,
chromium,
hydrogen
chloride,
hydrogen
flouride,
lead,
manganese,
mercury,
and
nickel,
which
will
reduce
a
variety
of
adverse
health
effects
considering
both
cancer
and
noncancer
endpoints.
Information
for
each
pollutant
to
be
reduced
by
this
rule
is
obtained
from
the
Integrated
Risk
Information
System
(
IRIS),
an
EPA
system
for
disseminating
information
about
the
effects
of
several
chemicals
emitted
to
the
air
and
/
or
water,
and
classifying
these
chemicals
by
cancer
risk
(
IRIS,
2000).
These
adverse
health
effects
include
chronic
health
disorders
(
e.
g.,
irritation
of
the
lung,
skin,
and
mucus
membranes
and
effects
on
the
blood,
digestive
tract,
kidneys,
and
central
nervous
system),
and
acute
health
disorders
(
e.
g.,
lung
irritation
and
congestion,
alimentary
effects
such
as
nausea
and
vomiting,
and
effects
on
the
central
nervous
system).
EPA
has
classified
several
of
these
HAPs
as
known
or
probable
human
carcinogens.

The
EPA
does
not
have
the
type
of
current
detailed
data
on
each
of
the
facilities
covered
by
the
emissions
standards
for
this
source
category,
and
the
people
living
around
the
facilities,
that
would
be
necessary
to
conduct
an
analysis
to
determine
the
actual
population
exposures
to
the
HAP
emitted
from
these
facilities
and
potential
for
resultant
health
effects.
Therefore,
the
EPA
does
not
know
the
extent
to
which
the
adverse
health
effects
described
above
occur
in
the
populations
surrounding
these
facilities.
However,
to
the
extent
the
adverse
effects
do
occur,
the
rule
will
reduce
emissions
and
subsequent
exposures.
Health
effects
associated
with
the
significant
HAPs
emitted
from
boilers
and
process
heaters
are
discussed
below.

Arsenic
Acute
(
short
term)
high­
level
inhalation
exposure
to
arsenic
dust
or
fumes
has
resulted
in
gastrointestinal
effects
(
nausea,
diarrhea,
abdominal
pain),
and
central
and
peripheral
nervous
system
disorders.
Chronic
(
long­
term)
inhalation
exposure
to
inorganic
arsenic
in
humans
is
associated
with
irritation
of
the
skin
and
mucous
membranes.
Human
data
suggest
a
relationship
between
inhalation
exposure
of
women
working
at
or
living
near
metal
smelters
and
an
increased
risk
of
reproductive
effects,
such
as
spontaneous
abortions.
Inorganic
arsenic
exposure
in
humans
by
the
inhalation
route
has
been
shown
to
be
strongly
associated
with
lung
cancer,
while
ingestion
of
inorganic
arsenic
in
humans
has
been
linked
to
a
form
of
skin
cancer
and
also
to
bladder,
liver,
and
lung
cancer.
EPA
has
classified
inorganic
arsenic
as
a
Group
A,
known
human
carcinogen.

Cadmium
The
acute
(
short­
term)
effects
of
cadmium
inhalation
in
humans
consist
mainly
of
effects
on
the
lung,
such
as
pulmonary
irritation.
Chronic
(
long­
term)
inhalation
or
oral
exposure
to
cadmium
9­
15
leads
to
a
build­
up
of
cadmium
in
the
kidneys
that
can
cause
kidney
disease.
Cadmium
has
been
shown
to
be
a
developmental
toxicant
in
animals,
resulting
in
fetal
malformations
and
other
effects,
but
no
conclusive
evidence
exists
in
humans.
An
association
between
cadmium
exposure
and
an
increased
risk
of
lung
cancer
has
been
reported
from
human
studies,
but
these
studies
are
inconclusive
due
to
confounding
factors.
Animal
studies
have
demonstrated
an
increase
in
lung
cancer
from
long­
term
inhalation
exposure
to
cadmium.
EPA
has
classified
cadmium
as
a
Group
B1,
probable
carcinogen.

Chromium
Chromium
may
be
emitted
in
two
forms,
trivalent
chromium
(
chromium
III)
or
hexavalent
chromium
(
chromium
VI).
The
respiratory
tract
is
the
major
target
organ
for
chromium
VI
toxicity,
for
acute
(
short­
term)
and
chronic
(
long­
term)
inhalation
exposures.
Shortness
of
breath,
coughing,
and
wheezing
have
been
reported
from
acute
exposure
to
chromium
VI,
while
perforations
and
ulcerations
of
the
septum,
bronchitis,
decreased
pulmonary
function,
pneumonia,
and
other
respiratory
effects
have
been
noted
from
chronic
exposure.
Limited
human
studies
suggest
that
chromium
VI
inhalation
exposure
may
be
associated
with
complications
during
pregnancy
and
childbirth,
while
animal
studies
have
not
reported
reproductive
effects
from
inhalation
exposure
to
chromium
VI.
Human
and
animal
studies
have
clearly
established
that
inhaled
chromium
VI
is
a
carcinogen,
resulting
in
an
increased
risk
of
lung
cancer.
EPA
has
classified
chromium
VI
as
a
Group
A,
human
carcinogen.

Chromium
III
is
less
toxic
than
chromium
VI.
The
respiratory
tract
is
also
the
major
target
organ
for
chromium
III
toxicity,
similar
to
chromium
VI.
Chromium
III
is
an
essential
element
in
humans,
with
a
daily
intake
of
50
to
200
micrograms
per
day
recommended
for
an
adult.
The
body
can
detoxify
some
amount
of
chromium
VI
to
chromium
III.
EPA
has
not
classified
chromium
III
with
respect
to
carcinogenicity.
For
this
rule,
EPA
has
not
determined
the
species
of
chromium
emitted
at
industrial
boilers
and
process
heaters.

Hydrogen
chloride
Hydrogen
chloride,
also
called
hydrochloric
acid,
is
corrosive
to
the
eyes,
skin,
and
mucous
membranes.
Acute
(
short­
term)
inhalation
exposure
may
cause
eye,
nose,
and
respiratory
tract
irritation
and
inflammation
and
pulmonary
edema
in
humans.
Chronic
(
long­
term)
occupational
exposure
to
hydrochloric
acid
has
been
reported
to
cause
gastritis,
bronchitis,
and
dermatitis
in
workers.
Prolonged
exposure
to
low
concentrations
may
also
cause
dental
discoloration
and
erosion.
No
information
is
available
on
the
reproductive
or
developmental
effects
of
hydrochloric
acid
in
humans.
In
rats
exposed
to
hydrochloric
acid
by
inhalation,
altered
estrus
cycles
have
been
reported
in
females
and
increased
fetal
mortality
and
decreased
fetal
weight
have
been
reported
in
offspring.
EPA
has
not
classified
hydrochloric
acid
for
carcinogenicity.

Hydrogen
fluoride
Acute
(
short
term)
inhalation
exposure
to
gaseous
hydrogen
fluoride
can
cause
severe
respiratory
damage
in
humans,
including
severe
irritation
and
pulmonary
edema.

Lead
Lead
is
a
very
toxic
element,
causing
a
variety
of
effects
at
low
dose
levels.
Brain
damage,
kidney
damage,
and
gastrointestinal
distress
may
occur
from
acute
(
short­
term)
exposure
to
high
levels
of
lead
in
humans.
Chronic
(
long­
term)
exposure
to
lead
in
humans
results
in
effects
on
the
blood,
central
nervous
system
(
CNS),
blood
pressure,
and
kidneys.
Children
are
particularly
sensitive
to
the
chronic
effects
of
lead,
with
slowed
cognitive
development,
reduced
growth
and
other
effects
reported.
Reproductive
effects,
such
as
decreased
sperm
count
in
men
and
spontaneous
abortions
in
women,
have
been
associated
with
lead
exposure.
The
developing
fetus
is
at
particular
risk
from
maternal
lead
exposure,
with
low
birth
weight
and
slowed
postnatal
neurobehavioral
development
noted.
Human
studies
are
inconclusive
regarding
lead
exposure
and
cancer,
while
animal
studies
have
reported
an
15
In
addition
to
the
information
provided
in
IRIS,
another
detailed
discussion
of
the
benefits
of
reducing
lead
emissions
can
be
found
in
the
Final
Report
to
Congress
on
Benefits
and
Costs
of
the
Clean
Air
Act,
1970
to
1990
(
EPA
410­
R­
97­
002).

9­
16
increase
in
kidney
cancer
from
lead
exposure
by
the
oral
route.
EPA
has
classified
lead
as
a
Group
B2
pollutant,
probable
human
carcinogen15.

Manganese
Health
effects
in
humans
have
been
associated
with
both
deficiencies
and
excess
intakes
of
manganese.
Chronic
(
long­
term)
exposure
to
low
levels
of
manganese
in
the
diet
is
considered
to
be
nutritionally
essential
in
humans,
with
a
recommended
daily
allowance
of
2
to
5
milligrams
per
day
(
mg/
d).
Chronic
exposure
to
high
levels
of
manganese
by
inhalation
in
humans
results
primarily
in
central
nervous
system
(
CNS)
effects.
Visual
reaction
time,
hand
steadiness,
and
eye­
hand
coordination
were
affected
in
chronically­
exposed
workers.
Manganism,
characterized
by
feelings
of
weakness
and
lethargy,
tremors,
a
mask­
like
face,
and
psychological
disturbances,
may
result
from
chronic
exposure
to
higher
levels.
Impotence
and
loss
of
libido
have
been
noted
in
male
workers
afflicted
with
manganism
attributed
to
inhalation
exposures.
EPA
has
classified
manganese
in
Group
D,
not
classifiable
as
to
carcinogenicity
in
humans.

Nickel
Nickel
is
an
essential
element
in
some
animal
species,
and
it
has
been
suggested
it
may
be
essential
for
human
nutrition.
Nickel
dermatitis,
consisting
of
itching
of
the
fingers,
hand
and
forearms,
is
the
most
common
effect
in
humans
from
chronic
(
long­
term)
skin
contact
with
nickel.
Respiratory
effects
have
also
been
reported
in
humans
from
inhalation
exposure
to
nickel.
No
information
is
available
regarding
the
reproductive
or
developmental
effects
of
nickel
in
humans,
but
animal
studies
have
reported
such
effects.
Human
and
animal
studies
have
reported
an
increased
risk
of
lung
and
nasal
cancers
from
exposure
to
nickel
refinery
dusts
and
nickel
subsulfide.
Animal
studies
of
soluble
nickel
compounds
(
i.
e.,
nickel
carbonyl)
have
reported
lung
tumors.
EPA
has
classified
nickel
refinery
subsulfide
as
Group
A,
human
carcinogens
and
nickel
carbonyl
as
a
Group
B2,
probable
human
carcinogen.

Mercury
Mercury
emitted
from
industrial
boiles
and
other
natural
and
man­
made
sources
is
carried
by
winds
through
the
air
and
eventually
is
deposited
to
water
and
land.
Recent
estimates
(
which
are
highly
uncertain)
of
annual
total
global
mercury
emissions
from
all
sources
(
natural
and
anthropogenic)
are
about
5,000
to
5,500
tons
per
year
(
tpy).
Of
this
total,
about
1,000
tpy
are
estimated
to
be
natural
emissions
and
about
2,000
tpy
are
estimated
to
be
contributions
through
the
natural
global
cycle
of
reemissions
of
mercury
associated
with
past
anthropogenic
activity.
Current
anthropogenic
emissions
account
for
the
remaining
2,000
tpy.
Point
sources
such
as
fuel
combustion;
waste
incineration;
industrial
processes;
and
metal
ore
roasting,
refining,
and
processing
are
the
largest
point
source
categories
on
a
world­
wide
basis.
Given
the
global
estimates
noted
above,
U.
S.
anthropogenic
mercury
emissions
are
estimated
to
account
for
roughly
3
percent
of
the
global
total,
and
U.
S.
utilities
are
estimated
to
account
for
about
1
percent
of
total
global
emissions.
Mercury
exists
in
three
forms:
elemental
mercury,
inorganic
mercury
compounds
(
primarily
mercuric
chloride),
and
organic
mercury
compounds
(
primarily
methylmercury).
Mercury
is
usually
released
in
an
elemental
form
and
later
converted
into
methylmercury
by
bacteria.
Methylmercury
is
more
toxic
to
humans
than
other
forms
of
mercury,
in
part
because
it
is
more
easily
absorbed
in
the
body
(
EPA,
1996).

If
the
deposition
is
directly
to
a
water
body,
then
the
processes
of
aqueous
fate,
transport,
and
transformation
begin.
If
deposition
is
to
land,
then
terrestrial
fate
and
transport
processes
occur
first
and
then
aqueous
fate
and
transport
processes
occur
once
the
mercury
has
cycled
into
a
water
body.
In
both
cases,
mercury
may
be
returned
to
the
atmosphere
through
resuspension.
In
water,
mercury
is
transformed
to
methylmercury
through
biological
processes
and
for
exposures
affected
by
this
rulemaking,
methylmercury
is
considered
to
be
the
form
of
greatest
concern.
Once
mercury
has
been
transformed
into
methylmercury,
it
can
be
ingested
by
the
lower
trophic
level
organisms
where
it
can
9­
1
bioaccumulate
in
fish
tissue
(
i.
e.,
concentrations
of
mercury
remain
in
the
fish's
system
for
a
long
period
of
time
and
accumulates
in
the
fish
tissue
as
predatory
fish
consume
other
species
in
the
food
chain).
Fish
and
wildlife
at
the
top
of
the
food
chain
can,
therefore,
have
mercury
concentrations
that
are
higher
than
the
lower
species,
and
they
can
have
concentrations
of
mercury
that
are
higher
than
the
concentration
found
in
the
water
body
itself.
In
addition,
when
humans
consume
fish
contaminated
with
methylmercury,
the
ingested
methymercury
is
almost
completely
absorbed
into
the
blood
and
distributed
to
all
tissues
(
including
the
brain);
it
also
readily
passes
through
the
placenta
to
the
fetus
and
fetal
brain
(
EPA,
2001a).

Based
on
the
findings
of
the
National
Research
Council,
EPA
has
concluded
that
benefits
of
Hg
reductions
would
be
most
apparent
at
the
human
consumption
stage,
as
consumption
of
fish
is
the
major
source
of
exposure
to
methylmercury.
At
lower
levels,
documented
Hg
exposure
effects
may
include
more
subtle,
yet
potentially
important,
neurodevelopmental
effects.
Some
subpopulations
in
the
U.
S.,
such
as:
Native
Americans,
Southeast
Asian
Americans,
and
lower
income
subsistence
fishers,
may
rely
on
fish
as
a
primary
source
of
nutrition
and/
or
for
cultural
practices.
Therefore,
they
consume
larger
amounts
of
fish
than
the
general
population
and
may
be
at
a
greater
risk
to
the
adverse
health
effects
from
Hg
due
to
increased
exposure.
In
pregnant
women,
methylmercury
can
be
passed
on
to
the
developing
fetus,
and
at
sufficient
exposure
may
lead
to
a
number
of
neurological
disorders
in
children.
Thus,
children
who
are
exposed
to
low
concentrations
of
methylmercury
prenatally
may
be
at
increased
risk
of
poor
performance
on
neurobehavioral
tests,
such
as
those
measuring
attention,
fine
motor
function,
language
skills,
visual­
spatial
abilities
(
like
drawing),
and
verbal
memory.
The
effects
from
prenatal
exposure
can
occur
even
at
doses
that
do
not
result
in
effects
in
the
mother.
Mercury
may
also
affect
young
children
who
consume
fish
contaminated
with
Hg.
Consumption
by
children
may
lead
to
neurological
disorders
and
developmental
problems,
which
may
lead
to
later
economic
consequences.

In
response
to
potential
risks
of
mercury­
contaminated
fish
consumption,
EPA
and
FDA
have
issued
fish
consumption
advisories
which
provide
recommended
limits
on
consumption
of
certain
fish
species
for
different
populations.
EPA
and
FDA
are
currently
developing
a
joint
advisory
that
has
been
released
in
draft
form.
This
newest
draft
FDA­
EPA
fish
advisory
recommends
that
women
and
young
children
reduce
the
risks
of
Hg
consumption
in
their
diet
by
moderating
their
fish
consumption,
diversifying
the
types
of
fish
they
consume,
and
by
checking
any
local
advisories
that
may
exist
for
local
rivers
and
streams.
This
collaborative
FDA­
EPA
effort
will
greatly
assist
in
educating
the
most
susceptible
populations.
Additionally,
the
reductions
of
Hg
from
this
regulation
may
potentially
lead
to
fewer
fish
consumption
advisories
(
both
from
federal
or
state
agencies),
which
will
benefit
the
fishing
community.
Currently
44
states
have
issued
fish
consumption
advisories
for
non­
commercial
fish
for
some
or
all
of
their
waters
due
to
contamination
of
mercury.
The
scope
of
FCA
issued
by
states
varies
considerably,
with
some
warnings
applying
to
all
water
bodies
in
a
state
and
others
applying
only
to
individual
lakes
and
streams.
Note
that
the
absence
of
a
state
advisory
does
not
necessarily
indicate
that
there
is
no
risk
of
exposure
to
unsafe
levels
of
mercury
in
recreationally
caught
fish.
Likewise,
the
presence
of
a
state
advisory
does
not
indicate
that
there
is
a
risk
of
exposure
to
unsafe
levels
of
mercury
in
recreationally
caught
fish,
unless
people
consume
these
fish
at
levels
greater
than
those
recommended
by
the
fish
advisory.

Reductions
in
methylmercury
concentrations
in
fish
should
reduce
exposure,
subsequently
reducing
the
risks
of
mercury­
related
health
effects
in
the
general
population,
to
children,
and
to
certain
subpopulations.
Fish
consumption
advisories
(
FCA)
issued
by
the
States
may
also
help
to
reduce
exposures
to
potential
harmful
levels
of
methylmercury
in
fish
(
although
some
studies
have
shown
limited
knowledge
of
and
compliance
with
advisories
by
at
risk
populations
(
May
and
Burger,
1996;
Burger,
2000)).
To
the
extent
that
reductions
in
mercury
emissions
reduces
the
probability
that
a
water
body
will
have
a
FCA
issued,
there
are
a
number
of
benefits
that
will
result
from
fewer
advisories,
including
increased
fish
consumption,
increased
fishing
choices
for
recreational
fishers,
increased
producer
and
consumer
surplus
for
the
commercial
fish
market,
and
increased
welfare
for
subsistence
fishing
populations.
9­
2
There
is
a
great
deal
of
variability
among
individuals
in
fish
consumption
rates;
however,
critical
elements
in
estimating
methylmercury
exposure
and
risk
from
fish
consumption
include
the
species
of
fish
consumed,
the
concentrations
of
methylmercury
in
the
fish,
the
quantity
of
fish
consumed,
and
how
frequently
the
fish
is
consumed.
The
typical
U.
S.
consumer
eating
a
wide
variety
of
fish
from
restaurants
and
grocery
stores
is
not
in
danger
of
consuming
harmful
levels
of
methylmercury
from
fish
and
is
not
advised
to
limit
fish
consumption.
Those
who
regularly
and
frequently
consume
large
amounts
of
fish,
either
marine
or
freshwater,
are
more
exposed.
Because
the
developing
fetus
may
be
the
most
sensitive
to
the
effects
from
methylmercury,
women
of
child­
bearing
age
are
regarded
as
the
population
of
greatest
interest.
The
EPA,
Food
and
Drug
Administration,
and
many
States
have
issued
fish
consumption
advisories
to
inform
this
population
of
protective
consumption
levels.

The
EPA's
1997
Mercury
Study
RTC
supports
a
plausible
link
between
anthropogenic
releases
of
Hg
from
industrial
and
combustion
sources
in
the
U.
S.
and
methylmercury
in
fish.
However,
these
fish
methylmercury
concentrations
also
result
from
existing
background
concentrations
of
Hg
(
which
may
consist
of
Hg
from
natural
sources,
as
well
as
Hg
which
has
been
re­
emitted
from
the
oceans
or
soils)
and
deposition
from
the
global
reservoir
(
which
includes
Hg
emitted
by
other
countries).
Given
the
current
scientific
understanding
of
the
environmental
fate
and
transport
of
this
element,
it
is
not
possible
to
quantify
how
much
of
the
methylmercury
in
locally­
caught
fish
consumed
by
the
U.
S.
population
is
contributed
by
U.
S.
emissions
relative
to
other
sources
of
Hg
(
such
as
natural
sources
and
re­
emissions
from
the
global
pool).
As
a
result,
the
relationship
between
Hg
emission
reductions
from
Utility
Units
and
methylmercury
concentrations
in
fish
cannot
be
calculated
in
a
quantitative
manner
with
confidence.
In
addition,
there
is
uncertainty
regarding
over
what
time
period
these
changes
would
occur.
This
is
an
area
of
ongoing
study.

Given
the
present
understanding
of
the
Hg
cycle,
the
flux
of
Hg
from
the
atmosphere
to
land
or
water
at
one
location
is
comprised
of
contributions
from:
the
natural
global
cycle;
the
cycle
perturbed
by
human
activities;
regional
sources;
and
local
sources.
Recent
advances
allow
for
a
general
understanding
of
the
global
Hg
cycle
and
the
impact
of
the
anthropogenic
sources.
It
is
more
difficult
to
make
accurate
generalizations
of
the
fluxes
on
a
regional
or
local
scale
due
to
the
site­
specific
nature
of
emission
and
deposition
processes.
Similarly,
it
is
difficult
to
quantify
how
the
water
deposition
of
Hg
leads
to
an
increase
in
fish
tissue
levels.
This
will
vary
based
on
the
specific
characteristics
of
the
individual
lake,
stream,
or
ocean.

9.2.1.2
Welfare
Benefits
of
HAP
Reductions.

The
welfare
effects
of
exposure
to
HAPs
have
received
less
attention
from
analysts
than
the
health
effects.
However,
this
situation
is
changing,
especially
with
respect
to
the
effects
of
toxic
substances
on
ecosystems.
Over
the
past
ten
years,
ecotoxicologists
have
started
to
build
models
of
ecological
systems
which
focus
on
interrelationships
in
function,
the
dynamics
of
stress,
and
the
adaptive
potential
for
recovery.
Chronic
sub­
lethal
exposures
may
affect
the
normal
functioning
of
individual
species
in
ways
that
make
it
less
than
competitive
and
therefore
more
susceptible
to
a
variety
of
factors
including
disease,
insect
attack,
and
decreases
in
habitat
quality
(
EPA,
1991).
All
of
these
factors
may
contribute
to
an
overall
change
in
the
structure
(
i.
e.,
composition)
and
function
of
the
ecosystem.

The
adverse,
non­
human
biological
effects
of
HAP
emissions
include
ecosystem
and
recreational
and
commercial
fishery
impacts.
Atmospheric
deposition
of
HAPs
directly
to
land
may
affect
terrestrial
ecosystems.
Atmospheric
deposition
of
HAPs
also
contributes
to
adverse
aquatic
ecosystem
effects.
This
not
only
has
adverse
implications
for
individual
wildlife
species
and
ecosystems
as
a
whole,
but
also
the
humans
who
may
ingest
contaminated
fish
and
waterfowl.

A
number
of
wildlife
species
are
a
risk
from
consuming
mercury­
contaminated
fish
(
Duvall
and
Baron,
2000).
Mercury
can
affect
reproductive
success
in
birds
and
mammals
which
may
affect
9­
3
population
levels
(
Peakall,
1996).
This
can
affect
human
welfare
in
several
ways.
If
changes
in
populations
reduces
biological
diversity
in
an
area
this
may
impact
the
total
ecological
system.
To
the
extent
that
people
value
biological
diversity
(
existence
value),
there
may
be
benefits
to
preventing
this
loss.
Also,
hunters
may
experience
direct
losses
if
populations
of
game
birds
or
animals
are
reduced.
Hunters
may
also
experience
welfare
losses
if
game
birds
or
animals
are
not
fit
for
consumption.
Hunters
may
also
be
affected
if
predator
populations
are
reduced
from
reduced
availability
of
prey
species.
In
addition
to
hunting,
other
non­
consumptive
uses
of
wildlife
including
bird
or
wildlife
viewing
may
be
impacted
by
reductions
in
bird
and
animal
populations.
In
one
special
case,
that
of
the
endangered
Florida
panther,
there
may
be
special
value
placed
on
reducing
the
risks
of
species
loss.

In
general,
HAP
emission
reductions
achieved
through
the
Industrial
Boilers
and
Process
Heaters
NESHAP
should
reduce
the
associated
adverse
environmental
impacts.

9.2.2
Benefits
of
Reducing
Other
Pollutants
Due
to
HAP
Controls
As
is
mentioned
above,
controls
that
will
be
required
on
boilers
and
process
heaters
to
reduce
HAPs
will
also
reduce
emissions
of
other
pollutants,
namely:
PM10,
PM2.5,
and
SO2.
According
to
baseline
emission
estimates,
the
source
categories
affected
by
this
proposal
currently
emit
approximately
766,000
tons
per
year
of
PM10,
217,000
tons
per
year
of
PM2.5,
and
3,405,000
tons
per
year
of
SO2
at
existing
sources.
It
is
estimated
that
by
the
year
2005,
new
boilers
and
process
heaters
will
emit
3,600
tons
per
year
of
PM10,
1,000
tons
of
PM2.5,
and
38,200
tons
of
SO2.
This
totals
769,600
tons
of
PM10,
218,000
tons
of
PM2.5,
and
3,443,200
tons
of
SO2
annually
at
all
boiler
and
process
heater
sources.
The
regulation
will
reduce
approximately
562,500
tons
of
PM10
emissions,
159,000
tons
of
PM2.5,
and
113,000
tons
of
SO2
at
new
and
existing
sources
by
2005.
For
more
information
on
these
HAP
emissions
and
emission
reductions,
please
refer
to
Chapter
8
of
this
RIA
and
the
docket
for
this
rule.
The
adverse
effects
from
PM
(
both
coarse
and
fine)
and
SO2
emissions
are
presented
below.

9.2.2.1
Benefits
of
Particulate
Matter
Reductions.
Scientific
studies
have
linked
PM
(
alone
or
in
combination
with
other
air
pollutants)
with
a
series
of
health
effects
(
EPA,
1996).
Coarse
(
PM10)
particles
can
accumulate
in
the
respiratory
system
and
aggravate
health
problems
such
as
asthma.
Fine
(
PM2.5)
particles
can
penetrate
deep
into
the
lungs
to
contribute
to
a
number
of
the
health
effects.
These
health
effects
include
decreased
lung
function
and
alterations
in
lung
tissue
and
structure
and
in
respiratory
tract
defense
mechanisms
which
may
be
manifest
in
increased
respiratory
symptoms
and
disease
or
in
more
severe
cases,
increased
hospital
admissions
and
emergency
room
visits
or
premature
death.
Children,
the
elderly,
and
people
with
cardiopulmonary
disease,
such
as
asthma,
are
most
at
risk
from
these
health
effects.

PM
also
causes
a
number
of
adverse
effects
on
the
environment.
Fine
PM
is
the
major
cause
of
reduced
visibility
in
parts
of
the
U.
S.,
including
many
of
our
national
parks
and
wilderness
areas.
Other
environmental
impacts
occur
when
particles
deposit
onto
soil,
plants,
water,
or
materials.
For
example,
particles
containing
nitrogen
and
sulfur
that
deposit
onto
land
or
water
bodies
may
change
the
nutrient
balance
and
acidity
of
those
environments,
leading
to
changes
in
species
composition
and
buffering
capacity.

Particles
that
are
deposited
directly
onto
leaves
of
plants
can,
depending
on
their
chemical
composition,
corrode
leaf
surfaces
or
interfere
with
plant
metabolism.
Finally,
PM
causes
soiling
and
erosion
damage
to
materials.

Thus,
reducing
the
emissions
of
PM
and
PM
precursors
from
boilers
and
process
heater
sources
can
help
to
improve
some
of
the
effects
mentioned
above
­
either
those
related
to
primary
PM
emissions,
or
the
effects
of
secondary
PM
generated
by
the
combination
of
SO2
with
other
pollutants
in
the
atmosphere.
9­
4
9.2.2.2
Benefits
of
Sulfur
Dioxide
Reductions.
Very
high
concentrations
of
sulfur
dioxide
(
SO2)
affect
breathing
and
ambient
levels
have
been
hypothesized
to
aggravate
existing
respiratory
and
cardiovascular
disease.
Potentially
sensitive
populations
include
asthmatics,
individuals
with
bronchitis
or
emphysema,
children
and
the
elderly.
SO2
is
also
a
primary
contributor
to
acid
deposition,
or
acid
rain,
which
causes
acidification
of
lakes
and
streams
and
can
damage
trees,
crops,
historic
buildings
and
statues.
In
addition,
sulfur
compounds
in
the
air
contribute
to
visibility
impairment
in
large
parts
of
the
country.
This
is
especially
noticeable
in
national
parks.

PM
can
also
be
formed
from
SO2
emissions.
Secondary
PM
is
formed
in
the
atmosphere
through
a
number
of
physical
and
chemical
processes
that
transform
gases,
such
as
SO2,
into
particles.
Overall,
emissions
of
SO2
can
lead
to
some
of
the
effects
discussed
in
this
section
­
either
those
directly
related
to
SO2
emissions,
or
the
effects
of
ozone
and
PM
resulting
from
the
combination
of
SO2
with
other
pollutants.

9.3
Lack
of
Approved
Methods
to
Quantify
HAP
Benefits
The
most
significant
effect
associated
with
the
HAPs
that
are
controlled
with
the
rule
is
the
potential
incidence
of
cancer.
In
previous
analyses
of
the
benefits
of
reductions
in
HAPs,
EPA
has
quantified
and
monetized
the
benefits
of
potential
reductions
in
the
incidences
of
cancer
(
EPA,
1992b,
1995).
In
some
cases,
EPA
has
also
quantified
(
but
not
monetized)
reductions
in
the
number
of
people
exposed
to
non­
cancer
HAP
risks
above
no­
effect
levels
(
EPA,
1995).

Monetization
of
the
benefits
of
reductions
in
cancer
incidences
requires
several
important
inputs,
including
central
estimates
of
cancer
risks,
estimates
of
exposure
to
carcinogenic
HAPs,
and
estimates
of
the
value
of
an
avoided
case
of
cancer
(
fatal
and
non­
fatal).
In
the
above
referenced
analyses,
EPA
relied
on
unit
risk
factors
(
URF)
developed
through
risk
assessment
procedures.
The
unit
risk
factor
is
a
quantitative
estimate
of
the
carcinogenic
potency
of
a
pollutant,
often
expressed
as
the
probability
of
contracting
cancer
from
a
70
year
lifetime
continuous
exposure
to
a
concentration
of
one
µ
g/
m3
of
a
pollutant.
These
URFs
are
designed
to
be
conservative,
and
as
such,
are
more
likely
to
represent
the
high
end
of
the
distribution
of
risk
rather
than
a
best
or
most
likely
estimate
of
risk.

In
a
typical
analysis
of
the
expected
health
benefits
of
a
regulation
(
see
for
example
the
benefit
analysis
of
the
Interstate
Air
Quality
Rule),
health
effects
are
estimated
by
applying
changes
in
pollutant
concentrations
to
best
estimates
of
risk
obtained
from
epidemiological
studies.
As
the
purpose
of
a
benefit
analysis
is
to
describe
the
benefits
most
likely
to
occur
from
a
reduction
in
pollution,
use
of
high­
end,
conservative
risk
estimates
over­
estimate
of
the
expected
benefits
of
the
regulation.
For
this
reason,
we
will
not
attempt
to
quantify
the
health
benefits
of
reductions
in
HAPs
unless
best
estimates
of
risks
are
available.
While
we
used
high­
end
risk
estimates
in
past
analyses,
recent
advice
from
the
EPA
Science
Advisory
Board
(
SAB)
and
internal
methods
reviews
have
suggested
that
we
avoid
using
high­
end
estimates
in
current
analyses.
EPA
is
working
with
the
SAB
to
develop
better
methods
for
analyzing
the
benefits
of
reductions
in
HAPs.

While
not
appropriate
as
part
of
a
primary
estimate
of
benefits,
to
estimate
the
potential
baseline
risks
posed
by
the
industrial
boiler
and
process
heater
source
categories
and
the
potential
impact
of
applicability
cutoffs
discussed
in
Chapter
3
of
this
RIA,
EPA
performed
a
"
rough"
risk
assessment,
described
below.
There
are
large
uncertainties
regarding
all
components
of
the
risk
quantification
step,
including
location
of
emission
reductions,
emission
estimates,
air
concentrations,
exposure
levels
and
dose­
response
relationships.
However,
if
these
uncertainties
are
properly
identified
and
characterized,
it
is
possible
to
provide
upper­
bound
estimates
of
the
potential
reduction
in
inhalation
cancer
incidence
associated
with
this
rule.
It
is
important
to
keep
in
mind
that
these
estimates
will
not
cover
non­
inhalation
based
cancer
risks
and
non­
cancer
health
effects.
9­
5
To
estimate
the
potential
baseline
risks
posed
by
the
industrial
boiler
and
process
heater
source
categories,
EPA
performed
a
crude
risk
analysis
of
the
industrial
boiler
and
process
heater
source
categories
that
focused
only
on
cancer
risks.
The
results
of
the
analysis
are
based
on
approaches
for
estimating
cancer
incidence
that
carry
significant
assumptions,
uncertainties,
and
limitations.
Based
on
the
assessment,
if
this
proposed
rule
is
implemented
at
all
affected
facilities,
annual
cancer
incidence
is
estimated
to
be
reduced
on
the
order
of
tens
of
cases/
year.
Due
to
the
uncertainties
associated
with
the
analysis,
annual
cancer
incidence
could
be
higher
or
lower
than
these
estimates.
(
Details
of
this
assessment
are
available
in
the
docket.)

For
non­
cancer
health
effects,
previous
analyses
have
estimated
changes
in
populations
exposed
above
the
reference
concentration
level
(
RfC).
However,
this
requires
estimates
of
populations
exposed
to
HAPs
from
controlled
sources.
Due
to
data
limitations,
we
do
not
have
sufficient
information
on
emissions
from
specific
sources
and
thus
are
unable
to
model
changes
in
population
exposures
to
ambient
concentrations
of
HAPs
above
the
RfC.
As
a
result,
we
are
unable
to
place
a
monetary
value
of
the
HAP
benefits
associated
with
this
rule.

9.4
Summary
The
HAPs
that
are
reduced
as
a
result
of
implementing
the
Industrial
Boilers
and
Process
Heaters
NESHAP
will
produce
a
variety
of
benefits,
some
of
which
include:
the
reduction
in
the
incidence
of
cancer
to
exposed
populations,
neurotoxicity,
irritation,
and
crop
or
plant
damage.
The
rule
will
also
produce
benefits
associated
with
reductions
in
fine
and
coarse
PM
and
SO2
emissions.
Exposure
to
PM
(
either
directly
or
through
secondary
formation
from
SO2)
can
lead
to
several
health
effects,
including
premature
death
and
increased
hospital
admissions
and
emergency
room
visits,
increased
respiratory
symptoms
and
disease,
decreased
lung
function,
and
alterations
in
lung
tissue
and
structure
and
in
respiratory
tract
defense
mechanisms.
Children,
the
elderly,
and
people
with
cardiopulmonary
disease,
such
as
asthma,
are
most
at
risk
from
these
health
effects.
It
can
also
form
a
haze
that
reduces
the
visibility
of
scenic
areas,
can
cause
acidification
of
water
bodies,
and
have
other
impacts
on
soil,
plants,
and
materials.
High
concentrations
of
SO2
affect
breathing
and
may
aggravate
existing
respiratory
and
cardiovascular
disease,
which
is
more
likely
to
affect
asthmatics,
individuals
with
bronchitis
or
emphysema,
children
and
the
elderly.
SO2
is
also
a
primary
contributor
to
acid
deposition,
or
acid
rain,
which
causes
acidification
of
lakes
and
streams
and
can
damage
trees,
crops,
historic
buildings
and
statues.
In
addition,
sulfur
compounds
in
the
air
contribute
to
visibility
impairment
in
large
parts
of
the
country.
This
is
especially
noticeable
in
national
parks.
9­
6
REFERENCES:

EPA,
2000.
U.
S.
Environmental
Protection
Agency.
Integrated
Risk
Information
System;
website
access
available
at
www.
epa.
gov/
ngispgm3/
iris.
Data
as
of
December
2000.

EPA,
1991.
U.
S.
Environmental
Protection
Agency.
Ecological
Exposure
and
Effects
of
Airborne
Toxic
Chemicals:
An
Overview.
EPA/
6003­
91/
001.
Environmental
Research
Laboratory.
Corvallis,
OR.
1991.

EPA,
1992a.
U.
S.
Environmental
Protection
Agency.
Regulatory
Impact
Analysis
for
the
National
Emissions
Standards
for
Hazardous
Air
Pollutants
for
Source
Categories:
Organic
Hazardous
Air
Pollutants
from
the
Synthetic
Organic
Chemical
Manufacturing
Industry
and
Seven
Other
Processes.
Draft
Report.
Office
of
Air
Quality
Planning
and
Standards.
Research
Triangle
Park,
NC.
EPA­
450/
3­
92­
009.
December
1992.

EPA,
1992b.
U.
S.
Environmental
Protection
Agency.
Draft
Regulatory
Impact
Analysis
of
National
Emissions
Standards
for
Hazardous
Air
Pollutants
for
By
Product
Coke
Oven
Charging,
Door
Leaks,
and
Topside
Leaks.
Office
of
Air
Quality
Planning
and
Standards,
Research
Triangle
Park,
NC.
1992.

EPA,
1995.
U.
S.
Environmental
Protection
Agency.
Regulatory
Impact
Analysis
for
the
Petroleum
Refinery
NESHAP.
Revised
Draft
for
Promulgation.
Office
of
Air
Quality
Planning
and
Standards,
Research
Triangle
Park,
N.
C.
1995.

EPA,
1996.
Review
of
the
National
Ambient
Air
Quality
Standards
for
Particulate
Matter:
Assessment
of
Scientific
and
Technical
Information.
Office
of
Air
Quality
Planning
and
Standards,
Research
Triangle
Park,
N.
C.;
EPA
report
no.
EPA/
4521R­
96­
013.
10­
1
10.0
QUANTIFIED
BENEFITS
10.1
Results
in
Brief
In
this
section,
we
calculate
monetary
benefits
for
the
reductions
in
ambient
PM
concentrations
resulting
from
the
emission
reductions
described
in
Chapters
3
and
9.
Benefits
related
to
PM10
and
PM2.5
reductions
are
calculated
using
a
combination
of
two
approaches:
(
1)
a
direct
valuation
based
on
air
quality
analysis
of
modeled
PM
and
SO2
reductions
at
specific
industrial
boilers/
process
heaters,
and
(
2)
a
benefits
transfer
approach
which
uses
dollar
per
ton
values
generated
from
the
air
quality
analysis
completed
in
the
first
approach
to
value
reductions
from
non­
specific
sources.
Incremental
benefits
(
in
1999
dollars)
from
boilers
and
process
heater
PM
and
SO2
emission
reductions
are
approximately
$
16
billion
for
the
MACT
floor.
We
also
evaluated
an
above
the
floor
regulatory
option
that
is
more
stringent
than
final
rule's
MACT
floor.
Total
annual
benefits
of
the
above
the
floor
option
are
$
17
billion.
Although
the
benefits
of
the
more
stringent
option
are
greater
than
the
MACT
floor,
there
are
other
costs
and
economic
impacts
that
deem
it
an
inferior
regulatory
option.
Thus,
the
final
rule
is
based
on
the
selection
of
the
MACT
floor.

This
benefits
analysis
does
not
quantify
all
potential
benefits
or
disbenefits
associated
with
PM
and
SO2
reductions.
This
analysis
also
does
not
quantify
the
benefits
associated
with
reductions
in
hazardous
air
pollutants
(
HAP).
The
magnitude
of
the
unquantified
benefits
associated
with
omitted
categories
and
pollutants,
such
as
avoided
cancer
cases,
damage
to
ecosystems,
or
materials
damage
to
industrial
equipment
and
national
monuments,
is
not
known.
However,
to
the
extent
that
unquantified
benefits
exceed
unquantified
disbenefits,
the
estimated
benefits
presented
above
will
be
an
underestimate
of
actual
benefits.
There
are
many
other
sources
of
uncertainty
in
the
estimates
of
quantified
benefits.
These
sources
of
uncertainty,
along
with
the
methods
for
estimating
monetized
benefits
for
this
NESHAP
and
a
more
detailed
analysis
of
the
results
are
presented
below.
10­
2
Table
10­
1.
Summary
of
Results:
Estimated
PM­
Related
Benefits
of
the
Industrial
Boilers
and
Process
Heaters
NESHAP
Estimation
Method
Total
BenefitsA,
B
(
millions
1999$)

MACT
Floor:

Using
a
3%
discount
rate
Using
a
7%
discount
rate
$
16
+
B
$
15
+
B
Above
the
MACT
Floor:

Using
a
3%
discount
rate
Using
a
7%
discount
rate
$
17
+
B
$
16
+
B
A
Benefits
of
HAP
emission
reductions
are
not
quantified
in
this
analysis
and,
therefore,
are
not
presented
in
this
table.
The
quantifiable
benefits
are
from
emission
reductions
of
SO
2
and
PM
only.
For
notational
purposes,
unquantified
benefits
are
indicated
with
a
"
B"
to
represent
additional
monetary
benefits.
A
detailed
listing
of
unquantified
SO
2,
PM
,
and
HAP
related
health
effects
is
provided
in
Table
10­
13.

B
Results
reflect
the
use
of
two
different
discount
rates;
a
3%
rate
which
is
recommended
by
EPA's
Guidelines
for
Preparing
Economic
Analyses
(
US
EPA,
2000a),
and
7%
which
is
recommended
by
OMB
Circular
A­
94
(
OMB,
1992).

10.2
Introduction
This
chapter
presents
the
methods
used
to
estimate
the
monetary
benefits
of
the
reductions
in
PM
and
SO
2
emissions
associated
with
control
requirements
resulting
from
the
Industrial
Boilers/
Process
Heaters
NESHAP.
Results
are
presented
for
the
emission
controls
described
in
Chapter
3.
The
benefits
that
result
from
the
rule
include
both
the
primary
impacts
from
application
of
control
technologies
or
changes
in
operations
and
processes,
and
the
secondary
effects
of
the
controls.
The
regulation
induced
reductions
in
PM
and
SO
2
emissions
also
described
in
Chapter
3
will
result
in
changes
in
the
physical
damages
associated
with
exposure
to
elevated
ambient
concentrations
of
PM.
These
damages
include
changes
in
both
human
health
and
welfare
effects
categories.
Benefits
are
calculated
for
the
nation
as
a
whole,
assuming
that
controls
are
implemented
at
major
sources
(
sources
emitting
>
10
tons
of
a
HAP
annual,
or
>
25
tons
of
two
or
more
HAPs
annually).

The
remainder
of
this
chapter
provides
the
following:

Subsection
3
provides
an
overview
of
the
benefits
methodology.

Subsection
4
discusses
Phase
One
of
the
analysis:
modeled
air
quality
change
and
health
effects
resulting
from
a
portion
of
emission
reductions
at
a
subset
of
boiler
and
process
heaters
sources

Subsection
5
discusses
Phase
Two
of
the
analysis:
Benefit
transfer
valuation
of
remaining
emission
reductions
10­
3

Subsection
6
discusses
total
benefit
estimated
by
combining
the
results
of
Phases
1
and
2.

Subsection
7
discusses
potential
benefit
categories
that
are
not
quantified
due
to
data
and/
or
methodological
limitations,
and
provides
a
list
of
analytical
uncertainties,
limitations,
and
biases.

10.3
Overview
of
Benefits
Analysis
Methodology
This
section
documents
the
general
approach
used
to
estimate
benefits
resulting
from
emissions
reductions
from
boiler
and
process
heater
sources.
We
follow
the
basic
methodology
described
in
the
Regulatory
Impact
Analysis
of
the
Heavy
Duty
Engine/
Diesel
Fuel
rule
[
hereafter
referred
to
as
the
HDD
RIA]
(
US
EPA,
2000),
as
well
as
discussions
provided
in
the
Proposed
Non­
Road
Diesel
Engines
rule
(
NRD
rule)
and
the
Integrated
Air
Quality
Rule
(
IAQR).

Since
proposal
of
the
Industrial
Boilers
and
Process
Heaters
NESHAP,
the
benefit
methodology
utilized
by
EPA
has
been
updated
to
reflect
the
current
science
in
air
quality
modeling
and
benefits
modeling.
EPA
has
carefully
considered
the
differences
in
methodology
from
proposal.
Based
on
the
IAQR
benefit
analysis
document,
we
determined
that
the
NESHAP's
analysis
from
proposal
does
not
include
additional
benefit
endpoints
(
i.
e.,
infant
mortality,
heart
attacks,
and
asthma
exacerbation),
which
would
increase
the
total
benefit
estimate
from
proposal.
The
IAQR
also
uses
a
newer
study
of
premature
mortality
due
to
PM,
which
would
increase
the
benefit
estimate
from
proposal.
The
VSL
estimate
for
premature
mortality
has
been
lowered
slightly
from
$
6
million
to
$
5.5
million
in
the
IAQR,
which
would
decrease
the
benefit
estimate
from
proposal.
Finally,
an
updated
air
quality
model
(
i.
e.,
REMSAD)
would
also
increase
our
total
benefit
estimate
in
this
analysis.
Although
the
overall
impact
on
total
benefits
is
not
determinable
without
a
full
reassessement
of
benefits,
it
is
unlikely
that
our
comparison
of
benefits
to
costs
would
not
reveal
a
substantially
different
conclusion
(
e.
g.,
we
still
expect
benefits
to
exceed
costs
by
a
substantial
amount).
Therefore,
we
did
not
update
the
benefit
analysis
from
proposal
as
it
would
not
impact
the
benefit­
cost
comparison
for
this
rule.

On
September
26,
2002,
the
National
Academy
of
Sciences
(
NAS)
released
a
report
on
its
review
of
the
Agency's
methodology
for
analyzing
the
health
benefits
of
measures
taken
to
reduce
air
pollution.
The
report
focused
on
EPA's
approach
for
estimating
the
health
benefits
of
regulations
designed
to
reduce
concentrations
of
airborne
particulate
matter
(
PM).

In
its
report,
the
NAS
said
that
EPA
has
generally
used
a
reasonable
framework
for
analyzing
the
health
benefits
of
PM­
control
measures.
It
recommended,
however,
that
the
Agency
take
a
number
of
steps
to
improve
its
benefits
analysis.
In
particular,
the
NAS
stated
that
the
Agency
should:

include
benefits
estimates
for
a
range
of
regulatory
options;

estimate
benefits
for
intervals,
such
as
every
five
years,
rather
than
a
single
year;

clearly
state
the
project
baseline
statistics
used
in
estimating
health
benefits,
including
those
for
air
emissions,
air
quality,
and
health
outcomes;
10­
4

examine
whether
implementation
of
proposed
regulations
might
cause
unintended
impacts
on
human
health
or
the
environment;

when
appropriate,
use
data
from
non­
US
studies
to
broaden
age
ranges
to
which
current
estimates
apply
and
to
include
more
types
of
relevant
health
outcomes;

begin
to
move
the
assessment
of
uncertainties
from
its
ancillary
analyses
into
its
primary
analyses
by
conducting
probabilistic,
multiple­
source
uncertainty
analyses.
This
assessment
should
be
based
on
available
data
and
expert
judgment.

Although
the
NAS
made
a
number
of
recommendations
for
improvement
in
EPA's
approach,
it
found
that
the
studies
selected
by
EPA
for
use
in
its
benefits
analysis
were
generally
reasonable
choices.
In
particular,
the
NAS
agreed
with
EPA's
decision
to
use
cohort
studies
to
derive
benefits
estimates.
It
also
concluded
that
the
Agency's
selection
of
the
American
Cancer
Society
(
ACS)
study
for
the
evaluation
of
PM­
related
premature
mortality
was
reasonable,
although
it
noted
the
publication
of
new
cohort
studies
that
should
be
evaluated
by
the
Agency.

Several
of
the
NAS
recommendations
addressed
the
issue
of
uncertainty
and
how
the
Agency
can
better
analyze
and
communicate
the
uncertainties
associated
with
its
benefits
assessments.
In
particular,
the
Committee
expressed
concern
about
the
Agency's
reliance
on
a
single
value
from
its
analysis
and
suggested
that
EPA
develop
a
probabilistic
approach
for
analyzing
the
health
benefits
of
proposed
regulatory
actions.
The
Agency
agrees
with
this
suggestion
and
is
working
to
develop
such
an
approach
for
use
in
future
rulemakings.
In
particular,
the
EPA
is
currently
in
the
process
of
developing
a
comprehensive
integrated
strategy
for
characterizing
the
impact
of
uncertainty
in
key
elements
of
the
benefits
modeling
process
(
e.
g.,
emissions
modeling,
air
quality
modeling,
health
effects
incidence
estimation,
valuation)
on
the
results
that
are
generated.
A
subset
of
this
effort,
which
is
currently
underway,
involves
an
expert
elicitation
designed
to
characterize
uncertainty
in
the
estimation
of
PM­
related
mortality
resulting
from
both
short­
term
and
longer­
term
exposure.
The
EPA
will
be
evaluating
the
results
of
this
elicitation
to
determine
its
usefulness
in
characterizing
uncertainty
in
our
estimates
of
PM­
related
mortality
benefits.
As
elements
of
this
uncertainty
analysis
strategy
are
finalized,
it
may
be
possible
to
integrate
them
into
later
iterations
of
regulatory
analyses.

In
this
RIA
at
proposal,
the
Agency
used
an
interim
approach
for
characterizing
uncertainty
that
showed
the
impact
of
several
important
alternative
assumptions
about
the
estimation
and
valuation
of
reductions
in
premature
mortality
and
chronic
bronchitis.
This
approach
provided
an
alternative
estimate
of
health
benefits
using
the
time
series
studies
in
place
of
cohort
studies,
as
well
as
alternative
valuation
methods
for
mortality
and
chronic
bronchitis
risk
reductions.
However,
reflecting
comments
from
the
SAB­
HES
as
well
as
the
NAS
panel,
rather
than
including
an
alternative
estimate
in
the
final
rule,
the
EPA
will
continue
to
investigate
the
impact
of
key
assumptions
on
mortality
and
morbidity
estimates.

The
analysis
of
benefits
of
this
NESHAP
is
conducted
in
two
phases.
For
a
portion
of
the
emission
reductions
expected
from
this
rule,
the
first
phase
of
analysis
models
the
change
in
air
quality
and
health
effects
around
specific
boiler
and
process
heater
sources.
The
benefits
resulting
from
the
changes
in
air
quality
are
then
quantified
and
monetized.
For
the
remaining
set
of
emission
reductions,
the
specific
location
of
the
emission
reduction
is
unknown
due
to
limitations
in
the
data.
Therefore,
the
second
phase
of
our
benefits
analysis
is
based
on
10­
5
benefits
transfer
of
the
modeled
changes
in
air
quality
and
health
effects
from
the
location
specific
emissions
reductions
achieved
in
phase
one
of
the
analysis.
More
specifically,
the
benefit
value
per
ton
of
emission
reduction
estimated
in
phase
one
is
transferred
and
applied
to
the
emission
reductions
in
phase
two
of
the
analysis.
Table
10­
2
summarizes
the
emissions
reductions
associated
with
the
phase
one
and
phase
two
analyses.
This
table
shows
the
emission
reduction
expected
from
two
regulatory
options
considered
for
this
rulemaking:
the
MACT
floor,
and
an
above
the
floor
regulatory
option.
Although
the
NESHAP
is
expected
to
result
in
reductions
in
emissions
of
many
HAPs
as
well
as
PM
and
SO
2,
benefits
transfer
values
are
generated
for
only
PM
and
SO
2
due
to
limitations
in
availability
of
transfer
values,
concentration­
response
functions,
or
air
quality
and
exposure
models
for
HAPs.
For
this
analysis,
we
focus
on
directly
emitted
PM,
and
SO
2
in
its
role
as
a
precursor
in
the
formation
of
ambient
particulate
matter.
Other
potential
impacts
of
PM
and
SO
2
reductions
not
quantified
in
this
analysis,
as
well
as
potential
impacts
of
HAPs
reductions
are
described
in
Chapter
9.

Table
10­
2.

Estimate
of
Emission
Reductions
for
Phases
One
and
Two
of
the
Benefit
Analysis
Regulatory
Option
Total
Emission
Reductions
(
tons/
yr)
Phase
One:
Modeled
Emission
Reductions
(
tons/
yr)
Phase
Two:
Reductions
Applied
to
Benefit
Transfer
Values
MACT
Floor:

SO
2
112,936
82,542
30,394
PM10
562,110
265,115
296,955
PM2.5
159,196
75,095
84,101
Above
MACT
Floor:

SO
2
136,733
95,361
41,372
PM10
569,229
313,947
255,282
PM2.5
171,459
94,565
76,894
The
general
term
"
benefits"
refers
to
any
and
all
outcomes
of
the
regulation
that
contribute
to
an
enhanced
level
of
social
welfare.
In
this
case,
the
term
"
benefits"
refers
to
the
dollar
value
associated
with
all
the
expected
positive
impacts
of
the
regulation,
that
is,
all
regulatory
outcomes
that
lead
to
higher
social
welfare.
If
the
benefits
are
associated
with
market
goods
and
services,
the
monetary
value
of
the
benefits
is
approximated
by
the
sum
of
the
predicted
changes
in
consumer
(
and
producer)
"
surplus."
These
"
surplus"
measures
are
standard
and
widely
accepted
measures
in
the
field
of
applied
welfare
economics,
and
reflect
the
degree
of
well­
being
enjoyed
by
people
given
different
levels
of
goods
and
prices.
If
the
benefits
are
non­
market
benefits
(
such
as
the
risk
reductions
associated
with
environmental
quality
improvements),
however,
other
methods
of
measuring
benefits
must
be
used.
In
contrast
to
market
goods,
non­
market
goods
such
as
environmental
quality
improvements
are
public
goods,
whose
benefits
are
shared
by
many
people.
The
total
value
of
such
a
good
is
the
sum
of
the
dollar
amounts
that
all
those
who
benefit
are
willing
to
pay.
10­
6
We
follow
a
"
damage­
function"
approach
in
calculating
total
benefits
of
the
modeled
changes
in
environmental
quality.
This
approach
estimates
changes
in
individual
health
and
welfare
endpoints
(
specific
effects
that
can
be
associated
with
changes
in
air
quality)
and
assigns
values
to
those
changes
assuming
independence
of
the
individual
values.
Total
benefits
are
calculated
simply
as
the
sum
of
the
values
for
all
non­
overlapping
health
and
welfare
endpoints.
This
imposes
no
overall
preference
structure,
and
does
not
account
for
potential
income
or
substitution
effects,
i.
e.
adding
a
new
endpoint
will
not
reduce
the
value
of
changes
in
other
endpoints.
The
"
damage­
function"
approach
is
the
standard
approach
for
most
cost­
benefit
analyses
of
regulations
affecting
environmental
quality,
and
it
has
been
used
in
several
recent
published
analyses
(
Banzhaf
et
al.,
2002;
Levy
et
al,
2001;
Kunzli
et
al,
2000;
Levy
et
al,
1999;
Ostro
and
Chestnut,
1998).
Time
and
resource
constraints
prevented
us
from
performing
extensive
new
research
to
measure
either
the
health
outcomes
or
their
values
for
this
analysis.
Thus,
similar
to
these
studies,
our
estimates
are
based
on
the
best
available
methods
of
benefits
transfer.
Benefits
transfer
is
the
science
and
art
of
adapting
primary
research
from
similar
contexts
to
obtain
the
most
accurate
measure
of
benefits
available
for
the
environmental
quality
change
under
analysis.

10.3.1
Methods
for
Estimating
Benefits
from
Air
Quality
Improvements
Environmental
and
health
economists
have
a
number
of
methods
for
estimating
the
economic
value
of
improvements
in
(
or
deterioration
of)
environmental
quality.
The
method
used
in
any
given
situation
depends
on
the
nature
of
the
effect
and
the
kinds
of
data,
time,
and
resources
that
are
available
for
investigation
and
analysis.
This
section
provides
an
overview
of
the
methods
we
selected
to
monetize
the
benefits
included
in
this
RIA.

We
note
at
the
outset
that
EPA
rarely
has
the
time
or
resources
to
perform
extensive
new
research
in
the
form
of
evaluating
the
response
in
human
health
effects
from
specific
changes
in
the
concentration
of
pollutants,
or
by
issuing
surveys
to
collect
data
of
individual's
willingness
to
pay
for
a
particular
rule's
given
change
in
air
quality,
which
is
needed
to
fully
measure
the
economic
benefits
of
individual
rulemakings.
As
a
result,
our
estimates
are
based
on
the
best
available
methods
of
benefit
transfer
from
epidemiological
studies
and
studies
of
the
economic
value
of
reducing
certain
health
and
welfare
effects.
Benefit
transfer
is
the
science
and
art
of
adapting
primary
benefits
research
on
concentration­
response
functions
and
measures
of
the
value
individuals
place
on
an
improvement
in
a
given
health
effect
to
the
scenarios
evaluated
for
a
particular
regulation.
Thus,
we
strive
to
obtain
the
most
accurate
measure
of
benefits
for
the
environmental
quality
change
under
analysis
given
availability
of
current,
peer
reviewed
research
and
literature.

In
general,
economists
tend
to
view
an
individual's
willingness­
to­
pay
(
WTP)
for
an
improvement
in
environmental
quality
as
the
most
complete
and
appropriate
measure
of
the
value
of
an
environmental
or
health
risk
reduction.
An
individual's
willingness­
to­
accept
(
WTA)
compensation
for
not
receiving
the
improvement
is
also
a
valid
measure.
Willingness
to
pay
and
Willingness
to
accept
are
comparable
measures
when
the
change
in
environmental
quality
is
small
and
there
are
reasonably
close
substitutes
available.
However,
WTP
is
generally
considered
to
be
a
more
readily
available
and
conservative
measure
of
benefits.
Adoption
of
WTP
as
the
measure
of
value
implies
that
the
value
of
environmental
quality
improvements
is
dependent
on
the
individual
preferences
of
the
affected
population
and
that
the
existing
distribution
of
income
(
ability
to
pay)
is
appropriate.
10­
7
For
many
goods,
WTP
can
be
observed
by
examining
actual
market
transactions.
For
example,
if
a
gallon
of
bottled
drinking
water
sells
for
one
dollar,
it
can
be
observed
that
at
least
some
persons
are
willing
to
pay
one
dollar
for
such
water.
For
goods
not
exchanged
in
the
market,
such
as
most
environmental
"
goods,"
valuation
is
not
as
straightforward.
Nevertheless,
a
value
may
be
inferred
from
observed
behavior,
such
as
sales
and
prices
of
products
that
result
in
similar
effects
or
risk
reductions,
(
e.
g.,
non­
toxic
cleaners
or
bike
helmets).
Alternatively,
surveys
may
be
used
in
an
attempt
to
directly
elicit
WTP
for
an
environmental
improvement.

One
distinction
in
environmental
benefits
estimation
is
between
"
use
values"
and
"
nonuse
values."
Although
no
general
agreement
exists
among
economists
on
a
precise
distinction
between
the
two,
the
general
nature
of
the
difference
is
clear.
Use
values
are
those
aspects
of
environmental
quality
that
affect
an
individual's
welfare
more
or
less
directly.
These
effects
include
changes
in
product
prices,
quality,
and
availability,
changes
in
the
quality
of
outdoor
recreation
and
outdoor
aesthetics,
changes
in
health
or
life
expectancy,
and
the
costs
of
actions
taken
to
avoid
negative
effects
of
environmental
quality
changes.

Non­
use
values
are
those
for
which
an
individual
is
willing
to
pay
for
reasons
that
do
not
relate
to
the
direct
use
or
enjoyment
of
any
environmental
benefit,
but
might
relate
to
existence
values
and
bequest
values.
Non­
use
values
are
not
traded,
directly
or
indirectly,
in
markets.
For
this
reason,
the
measurement
of
non­
use
values
has
proved
to
be
significantly
more
difficult
than
the
measurement
of
use
values.
The
air
quality
changes
produced
by
this
NESHAP
cause
changes
in
both
use
and
non­
use
values,
but
the
monetary
benefit
estimates
are
almost
exclusively
for
use
values.

More
frequently
than
not,
the
economic
benefits
from
environmental
quality
changes
are
not
traded
in
markets,
so
direct
measurement
techniques
can
not
be
used.
Avoided
cost
methods
are
ways
to
estimate
the
costs
of
pollution
by
using
the
expenditures
made
necessary
by
pollution
damage.
For
example,
if
buildings
must
be
cleaned
or
painted
more
frequently
as
levels
of
PM
increase,
then
the
appropriately
calculated
increment
of
these
costs
is
a
reasonable
lower
bound
estimate
(
under
most
conditions)
of
true
economic
benefits
when
PM
levels
are
reduced.
Avoided
costs
methods
are
used
to
estimate
some
of
the
health­
related
benefits
related
to
morbidity,
such
as
hospital
admissions
(
see
the
NRD
rule
and
the
IAQR
for
a
detailed
discussion
of
methods
to
value
benefit
categories).

Indirect
market
methods
can
also
be
used
to
infer
the
benefits
of
pollution
reduction.
The
most
important
application
of
this
technique
for
our
analysis
is
the
calculation
of
the
value
of
a
statistical
life
for
use
in
the
estimate
of
benefits
from
mortality
reductions.
There
exists
no
market
where
changes
in
the
probability
of
death
are
directly
exchanged.
However,
people
make
decisions
about
occupation,
precautionary
behavior,
and
other
activities
associated
with
changes
in
the
risk
of
death.
By
examining
these
risk
changes
and
the
other
characteristics
of
people's
choices,
it
is
possible
to
infer
information
about
the
monetary
values
associated
with
changes
in
mortality
risk
(
see
Section
10.4).
For
measurement
of
health
benefits,
this
analysis
captures
the
WTP
for
most
use
and
non­
use
values,
with
the
exception
of
the
value
of
avoided
hospital
admissions,
which
only
captures
the
avoided
cost
of
illness
because
no
WTP
values
were
available
in
the
published
literature.

10.3.2
Methods
for
Describing
Uncertainty
16
It
should
be
recognized
that
in
addition
to
uncertainty,
the
annual
benefit
estimates
for
the
Industrial
Boilers/
Process
Heaters
NESHAP
presented
in
this
analysis
are
also
inherently
variable,
due
to
the
truly
random
processes
that
govern
pollutant
emissions
and
ambient
air
quality
in
a
given
year.
Factors
such
as
electricity
demand
and
weather
display
constant
variability
regardless
of
our
ability
to
accurately
measure
them.
As
such,
the
estimates
of
annual
benefits
should
be
viewed
as
representative
of
the
types
of
benefits
that
will
be
realized,
rather
than
the
actual
benefits
that
would
occur
every
year.

10­
8
In
any
complex
analysis
using
estimated
parameters
and
inputs
from
numerous
models,
there
are
likely
to
be
many
sources
of
uncertainty.
16
This
analysis
is
no
exception.
As
outlined
both
in
this
and
preceding
chapters,
there
are
many
inputs
used
to
derive
the
final
estimate
of
benefits,
including
emission
inventories,
air
quality
models
(
with
their
associated
parameters
and
inputs),
epidemiological
estimates
of
concentration­
response
(
C­
R)
functions,
estimates
of
values
(
both
from
WTP
and
cost­
of­
illness
studies),
population
estimates,
income
estimates,
and
estimates
of
the
future
state
of
the
world
(
i.
e.,
regulations,
technology,
and
human
behavior).
Each
of
these
inputs
may
be
uncertain,
and
depending
on
their
location
in
the
benefits
analysis,
may
have
a
disproportionately
large
impact
on
final
estimates
of
total
benefits.
For
example,
emissions
estimates
are
used
in
the
first
stage
of
the
analysis.
As
such,
any
uncertainty
in
emissions
estimates
will
be
propagated
through
the
entire
analysis.
When
compounded
with
uncertainty
in
later
stages,
small
uncertainties
in
emission
levels
can
lead
to
much
larger
impacts
on
total
benefits.

Some
key
sources
of
uncertainty
in
each
stage
of
the
benefits
analysis
are:

°
Gaps
in
scientific
data
and
inquiry;

°
Variability
in
estimated
relationships,
such
as
C­
R
functions,
introduced
through
differences
in
study
design
and
statistical
modeling;

°
Errors
in
measurement
and
projection
for
variables
such
as
population
growth
rates;

°
Errors
due
to
mis­
specification
of
model
structures,
including
the
use
of
surrogate
variables,
such
as
using
PM
10
when
PM
2.5
is
not
available,
excluded
variables,
and
simplification
of
complex
functions;
and
°
Biases
due
to
omissions
or
other
research
limitations.

Some
of
the
key
uncertainties
in
the
benefits
analysis
are
presented
in
Table
10­
3.
Several
of
the
methods
employed
in
this
analysis
are
similar
to
the
methods
employed
in
the
Heavy
Duty
Diesel
and
Fuel
Standard
(
HDD
TSD).
Information
on
the
uncertainty
surrounding
particular
C­
R
and
valuation
functions
is
provided
in
the
HDD
TSD,
and
have
been
updated
in
the
TSD
for
the
benefits
of
the
Proposed
Non­
Road
Diesel
Engines
rule
(
NRD
rule)
(
EPA,
2003a),
and
in
the
documentation
for
the
Integrated
Air
Quality
Rule
(
IAQR)
(
EPA,
2003b).

Our
estimated
range
of
total
benefits
should
be
viewed
as
an
approximate
result
because
of
the
sources
of
uncertainty
discussed
above
(
see
Table
10­
3).
The
total
benefits
10­
9
estimate
may
understate
or
overstate
actual
benefits
of
the
rule.

In
considering
the
monetized
benefits
estimates,
the
reader
should
remain
aware
of
the
many
limitations
of
conducting
these
analyses
mentioned
throughout
this
RIA.
One
significant
limitation
of
both
the
health
and
welfare
benefits
analyses
is
the
inability
to
quantify
many
of
the
serious
effects
discussed
in
Chapter
9.

In
particular,
there
are
significant
categories
of
PM­
related
benefits
that
cannot
be
monetized
(
or
in
many
cases
even
quantified),
and
thus
they
are
not
included
in
our
accounting
of
health
and
welfare
benefits.
These
unquantified
effects
include
low
birth
weight,
changes
in
pulmonary
function,
chronic
respiratory
diseases
other
than
chronic
bronchitis,
morphological
changes,
altered
host
defense
mechanisms,
non­
fatal
cancers,
and
non­
asthma
respiratory
emergency
room
visits.
A
complete
discussion
of
PM
related
health
effects
can
be
found
in
the
PM
Criteria
Document
(
U.
S.
EPA,
1996).
In
general,
if
it
were
possible
to
monetize
these
benefits
categories,
the
benefits
estimates
presented
in
this
analysis
would
increase.
Unquantified
benefits
are
qualitatively
discussed
in
the
in
Chapter
9
and
presented
in
Table
10­
16.
The
net
effect
of
excluding
benefit
and
disbenefit
categories
from
the
estimate
of
total
benefits
depends
on
the
relative
magnitude
of
the
effects.

In
addition,
when
we
proposed
the
Industrial
Boilers
and
Process
Heaters
NESHAP
in
2003,
we
also
included
an
alternative
estimate
of
benefits
in
addition
to
a
base
estimate
that
was
intended
to
evaluate
the
impact
of
several
key
assumptions
on
the
estimated
reductions
in
premature
mortality
and
CB.
However,
reflecting
comments
from
the
SAB­
HES
as
well
as
the
NAS
panel,
we
do
not
present
an
alternative
estimate
to
reflect
uncertainty
in
our
benefit
estimate.
To
better
understand
the
scope
of
potential
uncertainties,
in
several
upcoming
analyses
EPA
will
investigate
the
impact
of
key
assumptions
on
mortality
and
morbidity
estimates
through
a
series
of
sensitivity
analyses.

The
benefits
estimates
generated
for
the
final
rule
are
subject
to
a
number
of
assumptions
and
uncertainties,
which
are
discussed
throughout
the
document.
For
example,
key
assumptions
underlying
the
primary
estimate
for
the
mortality
category
include
the
following:

(
1)
Inhalation
of
fine
particles
is
causally
associated
with
premature
death
at
concentrations
near
those
experienced
by
most
Americans
on
a
daily
basis.
Although
biological
mechanisms
for
this
effect
have
not
yet
been
definitively
established,
the
weight
of
the
available
epidemiological
evidence
supports
an
assumption
of
causality.

(
2)
All
fine
particles,
regardless
of
their
chemical
composition,
are
equally
potent
in
causing
premature
mortality.
This
is
an
important
assumption,
because
PM
produced
via
transported
precursors
emitted
from
EGUs
may
differ
significantly
from
direct
PM
released
from
automotive
engines
and
other
industrial
sources,
but
no
clear
scientific
grounds
exist
for
supporting
differential
effects
estimates
by
particle
type.

(
3)
The
C­
R
function
for
fine
particles
is
approximately
linear
within
the
range
of
ambient
concentrations
under
consideration.
Thus,
the
estimates
include
health
benefits
from
reducing
fine
particles
in
areas
with
varied
concentrations
of
PM,
including
both
regions
that
are
in
attainment
with
fine
particle
standard
and
those
that
do
not
meet
the
standard.

(
4)
The
forecasts
for
future
emissions
and
associated
air
quality
modeling
are
10­
10
valid.
Although
recognizing
the
difficulties,
assumptions,
and
inherent
uncertainties
in
the
overall
enterprise,
these
analyses
are
based
on
peer­
reviewed
scientific
literature
and
up­
to­
date
assessment
tools,
and
we
believe
the
results
are
highly
useful
in
assessing
this
proposal.
10­
11
Table
10­
3.
Primary
Sources
of
Uncertainty
in
the
Source
Benefit
Analyses
1.
Uncertainties
Associated
With
Health
Impact
Functions
S
The
value
of
the
PM
effect
estimate
in
each
impact
function.

S
Application
of
a
single
effect
estimate
to
pollutant
changes
and
populations
in
all
locations.

S
Similarity
of
future
year
effect
estimates
to
current
effect
estimates.

S
Correct
functional
form
of
each
impact
function.

S
Application
of
effect
estimates
to
changes
in
PM
outside
the
range
of
PM
concentrations
observed
in
the
study.

S
Application
of
effect
estimates
only
to
those
subpopulations
matching
the
original
study
population.

2.
Uncertainties
Associated
With
PM
Concentrations
S
Responsiveness
of
the
models
to
changes
in
precursor
emissions.

S
Projections
of
future
levels
of
precursor
emissions,
especially
ammonia
and
crustal
materials.

S
Model
chemistry
for
the
formation
of
ambient
nitrate
concentrations.

S
Use
of
separate
air
quality
models
for
ozone
and
PM
does
not
allow
for
a
fully
integrated
analysis
of
pollutants
and
their
interactions.

3.
Uncertainties
Associated
with
PM
Mortality
Risk
S
Limited
scientific
literature
supporting
a
direct
biological
mechanism
for
observed
epidemiological
evidence.

S
Direct
causal
agents
within
the
complex
mixture
of
PM
have
not
been
identified.

S
The
extent
to
which
adverse
health
effects
are
associated
with
low
level
exposures
that
occur
many
times
in
the
year
versus
peak
exposures.

S
The
extent
to
which
effects
reported
in
the
long­
term
exposure
studies
are
associated
with
historically
higher
levels
of
PM
rather
than
the
levels
occurring
during
the
period
of
study.

S
Reliability
of
the
limited
ambient
PM
2.5
monitoring
data
in
reflecting
actual
PM
2.5
exposures.

4.
Uncertainties
Associated
With
Possible
Lagged
Effects
S
The
portion
of
the
PM­
related
long­
term
exposure
mortality
effects
associated
with
changes
in
annual
PM
levels
would
occur
in
a
single
year
is
uncertain
as
well
as
the
portion
that
might
occur
in
subsequent
years.

5.
Uncertainties
Associated
With
Baseline
Incidence
Rates
S
Some
baseline
incidence
rates
are
not
location­
specific
(
e.
g.,
those
taken
from
studies)
and
may
therefore
not
accurately
represent
the
actual
location­
specific
rates.

S
Current
baseline
incidence
rates
may
not
approximate
well
baseline
incidence
rates
in
2010.

S
Projected
population
and
demographics
may
not
represent
well
future­
year
population
and
demographics.

6.
Uncertainties
Associated
With
Economic
Valuation
S
Unit
dollar
values
associated
with
health
endpoints
are
only
estimates
of
mean
WTP
and
therefore
have
uncertainty
surrounding
them.

S
Mean
WTP
(
in
constant
dollars)
for
each
type
of
risk
reduction
may
differ
from
current
estimates
due
to
differences
in
income
or
other
factors.

7.
Uncertainties
Associated
With
Aggregation
of
Monetized
Benefits
S
Health
benefits
estimates
are
limited
to
the
available
effect
estimates.
Thus,
unquantified
or
unmonetized
benefits
are
not
included.
10­
12
10.4
Phase
One
Analysis:
Modeled
Air
Quality
Change
and
Health
Effects
Resulting
from
a
Portion
of
Emission
Reductions
at
Boiler
and
Process
Heaters
Sources
In
phase
one
of
the
benefit
analysis,
we
are
able
to
link
approximately
50
percent
of
the
emission
reductions
from
this
regulation
to
specific
locations
of
boilers/
process
heaters.
This
allows
us
to
evaluate
the
change
in
air
quality
around
these
sources
and
the
resulting
effect
on
the
health
of
the
surrounding
population.
The
analysis
performed
for
the
emission
reductions
evaluated
in
phase
one
can
be
thought
of
as
having
three
parts,
including:

1.
Calculation
of
the
impact
that
our
standards
will
have
on
the
nationwide
inventories
for
PM
and
SO
2
emissions;

2.
Air
quality
modeling
to
determine
the
changes
in
ambient
concentrations
of
PM
that
will
result
from
the
changes
in
nationwide
inventories
of
directly
emitted
PM
and
precursor
pollutants;
and
3.
A
benefits
analysis
to
determine
the
changes
in
human
health,
both
in
terms
of
physical
effects
and
monetary
value,
that
result
from
the
changes
in
ambient
concentrations
of
PM.

Steps
1
and
2
are
discussed
in
previous
chapters
of
this
RIA.
For
step
3,
we
follow
the
same
general
methodology
used
in
the
benefits
analysis
of
the
HDD
rulemaking,
as
well
as
the
proposed
NRD
rule
and
the
IAQR.
EPA
also
relies
heavily
on
the
advice
of
its
independent
Science
Advisory
Board
(
SAB)
in
determining
the
health
and
welfare
effects
considered
in
the
benefits
analysis
and
in
establishing
the
most
scientifically
valid
measurement
and
valuation
techniques.

Figure
10­
1
illustrates
the
steps
necessary
to
link
the
emission
reductions
included
in
the
phase
one
analysis
with
economic
measures
of
benefits.
The
first
two
steps
involve
the
specification
and
implementation
of
the
regulation.
First,
the
specific
regulatory
options
for
reducing
air
pollution
from
industrial
boilers/
process
heaters
are
established.
In
this
chapter,
we
evaluate
the
benefits
of
two
regulatory
options:
the
MACT
floor
and
an
above
the
floor
option.
Next,
we
determine
the
changes
in
boiler
and
process
heater
control
technology
that
can
be
used
to
meet
the
level
of
emissions
reductions
specified
by
the
regulatory
options
(
see
Chapter
2).
The
changes
in
pollutant
emissions
resulting
from
the
required
changes
in
control
technology
at
boilers/
process
heaters
are
then
calculated,
along
with
predictions
of
emissions
for
other
industrial
sectors
in
the
baseline.
The
predicted
emissions
reductions
described
in
Chapter
3
are
then
used
as
inputs
to
air
quality
models
that
predict
ambient
concentrations
of
pollutants
over
time
and
space.
These
concentrations
depend
on
climatic
conditions
and
complex
chemical
interactions.
10­
13
Figure
10­
1.
Steps
in
Phase
One
of
the
Benefits
Analysis
for
the
Industrial
Boilers/
Process
Heaters
NESHAP
NESHAP
Regulatory
Options

Apply
Control
Technology
to
Affected
Sources

Estimate
Expected
Reductions
in
SO
2
and
PM
Emissions

Model
Changes
in
Ambient
Concentrations
of
PM
2.5
and
PM
10

Estimate
Expected
Changes
in
Human
Health
Outcomes

Estimate
Monetary
Value
of
Changes
in
Human
Health
Outcomes

Account
for
Income
Growth
and
Calculate
Total
Benefits
17Details
of
the
calculation
of
the
income
adjustment
factors
are
provided
in
the
IAQR
RIA
(
U.
S.
EPA,
2003b).

10­
14
Changes
in
ambient
concentrations
will
lead
to
new
levels
of
environmental
quality
in
the
U.
S.,
reflected
both
in
human
health
and
in
non­
health
welfare
effects.
For
this
analysis,
however,
we
do
not
evaluate
and
monetize
changes
in
non­
health
welfare
effects,
such
as
visibility
and
agricultural
yields.
To
generate
estimated
health
outcomes,
projected
changes
in
ambient
PM
concentrations
were
input
to
a
benefits
model,
known
as
the
Criteria
Air
Pollutant
Modeling
System
(
CAPMS),
a
customized
GIS­
based
program.
CAPMS
assigns
pollutant
concentrations
to
population
grid
cells
for
input
into
concentration­
response
functions.
CAPMS
uses
census
block
population
data
and
changes
in
pollutant
concentrations
to
estimate
changes
in
health
outcomes
for
each
grid
cell.
For
purposes
of
this
analysis,
we
assume
a
constant
proportion
of
baseline
incidence
of
the
various
health
effects
to
the
future
incidence
of
health
effects.

Our
analysis
also
accounts
for
expected
growth
in
real
income
over
time.
Economic
theory
argues
that
WTP
for
most
goods
(
such
as
environmental
protection)
will
increase
if
real
incomes
increase.
The
economics
literature
suggests
that
the
severity
of
a
health
effect
is
a
primary
determinant
of
the
strength
of
the
relationship
between
changes
in
real
income
and
WTP
(
Alberini,
1997;
Miller,
2000;
Viscusi,
1993).
As
such,
we
use
different
factors
to
adjust
the
WTP
for
minor
health
effects,
severe
and
chronic
health
effects,
and
premature
mortality.
Adjustment
factors
used
to
account
for
projected
growth
in
real
income
from
1990
to
2005
are
1.03
for
minor
health
effects,
1.09
for
severe
and
chronic
health
effects,
and
1.08
for
premature
mortality17.

It
should
be
noted
that
since
proposal
of
the
Industrial
Boilers
and
Process
Heaters
NESHAP,
the
benefit
methodology
utilized
by
EPA
has
been
updated
to
reflect
the
current
science
in
air
quality
modeling
and
benefits
modeling.
Due
to
time
and
resource
constraints,
EPA
was
unable
to
complete
a
full
reassessment
of
the
benefits
analysis
from
proposal.
However,
EPA
has
carefully
considered
the
differences
in
methodology
from
proposal.
Based
on
the
IAQR
benefit
analysis
document,
we
determined
that
the
NESHAP's
analysis
from
proposal
does
not
include
additional
benefit
endpoints
(
i.
e.,
infant
mortality,
heart
attacks,
and
asthma
exacerbation),
which
would
increase
the
total
benefit
estimate
from
proposal.
The
IAQR
also
uses
a
newer
study
of
premature
mortality
due
to
PM,
which
would
increase
the
benefit
estimate
from
proposal.
The
VSL
estimate
for
premature
mortality
has
been
lowered
slightly
from
$
6
million
to
$
5.5
million
in
the
IAQR,
which
would
decrease
the
benefit
estimate
from
proposal.
Finally,
an
updated
air
quality
model
(
i.
e.,
REMSAD)
would
also
increase
our
total
benefit
estimate
in
this
analysis.
Although
the
overall
impact
on
total
benefits
is
not
determinable
without
a
full
reassessement
of
benefits,
it
is
unlikely
that
our
comparison
of
benefits
to
costs
would
reveal
a
substantially
different
conclusion
(
e.
g.,
we
still
expect
benefits
to
exceed
costs
by
a
substantial
amount).

Based
on
the
structure
of
analysis
presented
above,
Section
10.4.1
provides
a
description
of
how
we
quantify
and
value
changes
in
individual
health
effects.
Then,
in
Section
10.4.2
we
present
quantified
estimates
of
the
reductions
in
health
effects
resulting
from
phase
one
of
the
benefit
analysis.
10­
15
10.4.1
Quantifying
Individual
Health
Effect
Endpoints
We
use
the
term
"
endpoints"
to
refer
to
specific
effects
that
can
be
associated
with
changes
in
air
quality.
To
estimate
these
endpoints,
EPA
combines
changes
in
ambient
air
quality
levels
with
epidemiological
evidence
about
population
health
response
to
pollution
exposure.
The
most
significant
monetized
benefits
of
reducing
ambient
concentrations
of
PM
are
attributable
to
reductions
in
human
health
risks.
EPA's
Criteria
Document
for
PM
lists
numerous
health
effects
known
to
be
linked
to
ambient
concentrations
of
the
pollutant
(
US
EPA,
1996a).
The
previous
chapter
described
some
of
these
effects.
This
section
describes
methods
used
to
quantify
and
monetize
changes
in
the
expected
number
of
incidences
of
various
health
effects.
For
further
detail
on
the
methodology
used
to
assess
human
health
benefits
such
as
those
included
in
phase
one
of
this
analysis,
refer
to
the
HDD
RIA
and
TSD,
and
the
IAQR
benefit
analysis.

The
specific
PM
endpoints
that
are
evaluated
in
this
analysis
include:

°
Premature
mortality
°
Bronchitis
­
chronic
and
acute
°
Hospital
admissions
­
respiratory
and
cardiovascular
°
Emergency
room
visits
for
asthma
°
Asthma
attacks
°
Lower
and
upper
respiratory
illness
°
Minor
restricted
activity
days
°
Work
loss
days
As
is
discussed
previously,
this
analysis
relies
on
concentration­
response
(
C­
R)
functions
estimated
in
published
epidemiological
studies
relating
health
effects
to
ambient
air
quality.
The
specific
studies
from
which
C­
R
functions
are
drawn
are
included
in
Table
10­
4.
Because
we
rely
on
methodology
used
in
prior
benefit
analyses,
a
complete
discussion
of
the
C­
R
functions
used
for
this
analysis
and
information
about
each
endpoint
are
contained
in
the
IAQR
RIA
.

While
a
broad
range
of
serious
health
effects
have
been
associated
with
exposure
to
elevated
PM
levels
(
described
more
fully
in
the
EPA's
PM
Criteria
Document
(
US
EPA,
1996a),
we
include
only
a
subset
of
health
effects
in
this
quantified
benefit
analysis.
Health
effects
are
excluded
from
this
analysis
for
four
reasons:
(
i)
the
possibility
of
double
counting
(
such
as
hospital
admissions
for
specific
respiratory
diseases);
(
ii)
uncertainties
in
applying
effect
relationships
based
on
clinical
studies
to
the
affected
population;
(
iii)
a
lack
of
an
established
C­
R
relationship;
or
(
iv)
lack
of
resources
to
estimate
some
endpoints.

Using
the
C­
R
functions
derived
from
the
studies
cited
in
this
table,
we
apply
that
same
C­
R
relationship
to
all
locations
in
the
U.
S.
Although
the
C­
R
relationship
may
in
fact
vary
somewhat
from
one
location
to
another
(
for
example,
due
to
differences
in
population
susceptibilities
or
differences
in
the
composition
of
PM),
location­
specific
C­
R
functions
are
generally
not
available.
A
single
function
applied
everywhere
may
result
in
overestimates
of
incidence
changes
in
some
locations
and
underestimates
in
other
locations,
but
these
locationspecific
biases
will,
to
some
extent,
cancel
each
other
out
when
the
total
incidence
change
is
calculated.
It
is
not
possible
to
know
the
extent
or
direction
of
the
bias
in
the
total
incidence
change
based
on
the
general
application
of
a
single
C­
R
function
everywhere.

Recently,
the
Health
Effects
Institute
(
HEI)
reported
findings
by
investigators
at
Johns
Hopkins
University
and
others
that
have
raised
concerns
about
aspects
of
the
statistical
10­
16
methodology
used
in
a
number
of
recent
time­
series
studies
of
short­
term
exposures
to
air
pollution
and
health
effects
(
Greenbaum,
2002a).
Some
of
the
concentration­
response
functions
used
in
this
benefits
analysis
were
derived
from
such
short­
term
studies.
The
estimates
derived
from
the
long­
term
mortality
studies,
which
account
for
a
major
share
of
the
benefits
in
theanalysis,
are
not
affected.
As
discussed
in
HEI
materials
provided
to
sponsors
and
to
the
Clean
Air
Scientific
Advisory
Committee
(
Greenbaum,
2002a,
2002b),
these
investigators
found
problems
in
the
default
"
convergence
criteria"
used
in
Generalized
Additive
Models
(
GAM)
and
a
separate
issue
first
identified
by
Canadian
investigators
about
the
potential
to
underestimate
standard
errors
in
the
same
statistical
package.
1
These
and
other
investigators
have
begun
to
reanalyze
the
results
of
several
important
time
series
studies
with
alternative
approaches
that
address
these
issues
and
have
found
a
downward
revision
of
some
results.
For
example,
the
mortality
risk
estimates
for
short­
term
exposure
to
PM
10
from
NMMAPS
were
overestimated
(
the
C­
R
function
based
on
the
NMMAPS
results
used
in
this
benefits
analysis
uses
the
revised
NMMAPS
results).
2
However,
both
the
relative
magnitude
and
the
direction
of
bias
introduced
by
the
convergence
issue
is
case­
specific.
In
most
cases,
the
concentration­
response
relationship
may
be
overestimated;
in
other
cases,
it
may
be
underestimated.
The
preliminary
renalyses
of
the
mortality
and
morbidity
components
of
NMMAPS
suggest
that
analyses
reporting
the
lowest
relative
risks
appear
to
be
affected
more
greatly
by
this
error
than
studies
reporting
higher
relative
risks
(
Dominici
et
al.,
2002;
Schwartz
and
Zanobetti,
2002).

Our
examination
of
the
original
studies
used
in
this
analysis
finds
that
the
health
endpoints
that
are
potentially
affected
by
the
GAM
issues
include:
reduced
hospital
admissions
and
reduced
lower
respiratory
symptoms;
reduced
lower
respiratory
symptoms;
and
reduced
premature
mortality
due
to
short­
term
PM
10
exposures
and
reduced
premature
mortality
due
to
short­
term
PM
2.5
exposures.
While
resolution
of
these
issues
is
likely
to
take
some
time,
the
preliminary
results
from
ongoing
reanalyses
of
some
of
the
studies
used
in
our
analyses
(
Dominici
et
al,
2002;
Schwartz
and
Zanobetti,
2002;
Schwartz,
personal
communication
2002)
suggest
a
more
modest
effect
of
the
S­
plus
error
than
reported
for
the
NMMAPS
PM
10
mortality
study.
While
we
wait
for
further
clarification
from
the
scientific
community,
we
have
chosen
not
to
remove
these
results
from
the
Industrial
Boilers
and
Process
Heaters
NESHAP
benefits
estimates,
nor
have
we
elected
to
apply
any
interim
adjustment
factor
based
on
the
preliminary
reanalyses.
EPA
will
continue
to
monitor
the
progress
of
this
concern,
and
make
appropriate
adjustments
as
further
information
is
made
available.

10.4.1.1
Concentration­
Response
Functions
for
Premature
Mortality
Both
long
and
short­
term
exposures
to
ambient
levels
of
air
pollution
have
been
associated
with
increased
risk
of
premature
mortality.
The
size
of
the
mortality
risk
estimates
from
these
epidemiological
studies,
the
serious
nature
of
the
effect
itself,
and
the
high
monetary
value
ascribed
to
prolonging
life
make
mortality
risk
reduction
the
most
important
health
endpoint
quantified
in
this
analysis.
Because
of
the
importance
of
this
endpoint
and
the
considerable
uncertainty
among
economists
and
policymakers
as
to
the
appropriate
way
to
value
reductions
in
mortality
risks,
this
section
discusses
some
of
the
issues
surrounding
the
estimation
of
premature
mortality.
For
additional
discussion
on
mortality
and
issues
related
to
estimating
risk
for
other
health
effects
categories,
we
refer
readers
to
the
discussions
presented
in
the
IAQR.

Epidemiological
analyses
have
consistently
linked
air
pollution,
especially
PM,
with
excess
mortality.
Although
a
number
of
uncertainties
remain
to
be
addressed
by
continued
research
(
NRC,
1998),
a
substantial
body
of
published
scientific
literature
documents
the
correlation
between
elevated
PM
concentrations
and
increased
mortality
rates.
Community
10­
17
epidemiological
studies
that
have
used
both
short­
term
and
long­
term
exposures
and
response
have
been
used
to
estimate
PM/
mortality
relationships.
Short­
term
studies
use
a
time­
series
approach
to
relate
short­
term
(
often
day­
to­
day)
changes
in
PM
concentrations
and
changes
in
daily
mortality
rates
up
to
several
days
after
a
period
of
elevated
PM
concentrations.
Long­
term
studies
examine
the
potential
relationship
between
community­
level
PM
exposures
over
multiple
years
and
community­
level
annual
mortality
rates.
10­
18
Table
10­
4.
PM­
related
Health
Outcomes
and
Studies
Included
in
the
Analysis
Health
Outcome
Pollutant
Applied
Population
Source
of
Effect
Estimate
Source
of
Baseline
Incidence
Premature
Mortality
All­
cause
premature
mortality
from
long­
term
exposure
PM2.5
>
29
years
Krewski
et
al.,
2000
U.
S.
Centers
for
Disease
Control,
1999
Chronic
Illness
Chronic
Bronchitis
(
pooled
estimate)
PM2.5
PM10
>
26
years
>
29
years
Abbey
et
al.,
1995
Schwartz
et
al.,
1993
Abbey
et
al.,
1993
Abbey
et
al.,
1993
Adams
and
Marano,
1995
Hospital
Admissions
COPD
PM10
>
64
years
Samet
et
al.,
2000
Graves
and
Gillum,
1997
Pneumonia
PM10
>
64
years
Samet
et
al.,
2000
Graves
and
Gillum,
1997
Asthma
PM2.5
<
65
years
Sheppard
et
al.,
1999
Graves
and
Gillum,
1997
Total
Cardiovascular
PM10
>
64
years
Samet
et
al.,
2000
Graves
and
Gillum,
1997
Asthma­
Related
ER
Visits
PM10
All
ages
Schwartz
et
al.,
1993
Smith
et
al.,
1997
Graves
and
Gillum,
1997
Other
Effects
Asthma
Attacks
PM10
Asthmatics,
all
ages
Whittemore
and
Korn,
1980
Krupnick,
1988
Adams
and
Marano,
1995
Acute
Bronchitis
PM2.5
Children,
8­
12
years
Dockery
et
al.,
1996
Adams
and
Marano,
1995
Upper
Respiratory
Symptoms
PM10
Asthmatic
children,
9­
11
Pope
et
al.,
1991
Pope
et
al.,
1991
Lower
Respiratory
Symptoms
PM2.5
Children,
7­
14
years
Schwartz
et
al.,
1994
Schwartz
et
al.,
1994
Work
Loss
Days
PM2.5
Adults,
18­
65
years
Ostro,
1987
Adams
and
Marano,
1995
Minor
Restricted
Activity
Days
(
minus
asthma
attacks)
PM2.5
Adults,
18­
65
years
Ostro
and
Rothschild.,
1989
Ostro
and
Rothschild,
1989
Researchers
have
found
statistically
significant
associations
between
PM
and
premature
mortality
using
both
types
of
studies.
In
general,
the
risk
estimates
based
on
the
long­
term
exposure
studies
are
larger
than
those
derived
from
short­
term
studies.
Cohort
analyses
are
better
able
to
capture
the
full
public
health
impact
of
exposure
to
air
pollution
over
time
(
Kunzli,
2001;
NRC,
2002).
This
section
discusses
some
of
the
issues
surrounding
the
estimation
of
premature
mortality.
18The
EPA
recognizes
that
the
ACS
cohort
also
is
not
completely
representative
of
the
demographic
mix
in
the
general
population.
The
ACS
cohort
is
almost
entirely
white,
and
has
higher
income
and
education
levels
relative
to
the
general
population.
The
EPA's
approach
to
this
problem
is
to
match
populations
based
on
the
potential
for
demographic
characteristics
to
modify
the
effect
of
air
pollution
on
mortality
risk.
Thus,
for
the
various
ACS­
based
models,
we
are
careful
to
apply
the
effect
estimate
only
to
ages
matching
those
in
the
original
studies,
because
age
has
a
potentially
large
modifying
impact
on
the
effect
estimate,
especially
when
younger
individuals
are
excluded
from
the
study
population.
For
the
Lipfert
analysis,
the
applied
population
should
be
limited
to
that
matching
the
sample
used
in
the
analysis.
This
sample
was
all
male,
veterans,
and
diagnosed
hypertensive.
There
are
also
a
number
of
differences
between
the
composition
of
the
sample
and
the
general
population,
including
a
higher
percentage
of
African
Americans
(
35
percent),
and
a
much
higher
percentage
of
smokers
(
81
percent
former
smokers,
57
percent
current
smokers)
than
the
general
population
(
12
percent
African
American,
24
percent
current
smokers).
These
composition
differences
cannot
be
controlled
for,
but
should
be
recognized
as
adding
to
the
potential
extrapolation
bias.
The
EPA
recognizes
the
difficulty
in
controlling
for
composition
of
income
and
education
levels.
However,
in
or
out
criterion
such
as
age,
veteran
status,
hypertension,
race
and
sex
are
all
controllable
by
applying
filters
to
the
population
data.
The
EPA
has
traditionally
only
controlled
for
age,
because
the
ACS
study
used
only
age
as
a
screen.

10­
19
Over
a
dozen
studies
have
found
significant
associations
between
various
measures
of
long­
term
exposure
to
PM
and
elevated
rates
of
annual
mortality,
beginning
with
Lave
and
Seskin
(
1977).
Most
of
the
published
studies
found
positive
(
but
not
always
statistically
significant)
associations
with
available
PM
indices
such
as
total
suspended
particles
(
TSP).
Particles
of
different
fine
particles
components
(
i.
e.,
sulfates),
and
fine
particles,
as
well
as
exploration
of
alternative
model
specifications
sometimes
found
inconsistencies
(
e.
g.,
Lipfert,
[
1989]).
These
early
"
cross­
sectional"
studies
(
e.
g.,
Lave
and
Seskin
[
1977];
Ozkaynak
and
Thurston
[
1987])
were
criticized
for
a
number
of
methodological
limitations,
particularly
for
inadequate
control
at
the
individual
level
for
variables
that
are
potentially
important
in
causing
mortality,
such
as
wealth,
smoking,
and
diet.
More
recently,
several
long­
term
studies
have
been
published
that
use
improved
approaches
and
appear
to
be
consistent
with
the
earlier
body
of
literature.
These
new
"
prospective
cohort"
studies
reflect
a
significant
improvement
over
the
earlier
work
because
they
include
individual­
level
information
with
respect
to
health
status
and
residence.
The
most
extensive
study
and
analyses
has
been
based
on
data
from
two
prospective
cohort
groups,
often
referred
to
as
the
Harvard
"
Six­
City
Study"
(
Dockery
et
al.,
1993)
and
the
"
American
Cancer
Society
or
ACS
study"
(
Pope
et
al.,
1995);
these
studies
have
found
consistent
relationships
between
fine
particle
indicators
and
premature
mortality
across
multiple
locations
in
the
United
States.
A
third
major
data
set
comes
from
the
California
based
7th
Day
Adventist
Study
(
e.
g.,
Abbey
et
al,
1999),
which
reported
associations
between
long­
term
PM
exposure
and
mortality
in
men.
Results
from
this
cohort,
however,
have
been
inconsistent
and
the
air
quality
results
are
not
geographically
representative
of
most
of
the
United
States.
More
recently,
a
cohort
of
adult
male
veterans
diagnosed
with
hypertension
has
been
examined
(
Lipfert
et
al.,
2000).
The
characteristics
of
this
group
differ
from
the
cohorts
in
the
ACS,
Six­
Cities,
and
7th
Day
Adventist
studies
with
respect
to
income,
race,
health
status,
and
smoking
status.
Unlike
previous
long­
term
analyses,
this
study
found
some
associations
between
mortality
and
ozone
but
found
inconsistent
results
for
PM
indicators.
Because
of
the
selective
nature
of
the
population
in
the
veteran's
cohort,
which
may
have
resulted
in
estimates
of
relative
risk
that
are
biased
relative
to
a
relative
risk
for
the
general
population,
we
have
chosen
not
to
include
any
effect
estimates
from
the
Lipfert
et
al.
(
2000)
study
in
our
benefits
assessment.
18
Given
their
consistent
results
and
broad
geographic
coverage,
the
Six­
City
and
ACS
data
have
been
particularly
important
in
benefits
analyses.
The
credibility
of
these
two
studies
is
10­
20
further
enhanced
by
the
fact
that
they
were
subject
to
extensive
reexamination
and
reanalysis
by
an
independent
team
of
scientific
experts
commissioned
by
HEI
(
Krewski
et
al.,
2000).
The
final
results
of
the
reanalysis
were
then
independently
peer
reviewed
by
a
Special
Panel
of
the
HEI
Health
Review
Committee.
The
results
of
these
reanalyses
confirmed
and
expanded
those
of
the
original
investigators.
This
intensive
independent
reanalysis
effort
was
occasioned
both
by
the
importance
of
the
original
findings
as
well
as
concerns
that
the
underlying
individual
health
effects
information
has
never
been
made
publicly
available.

The
HEI
re­
examination
lends
credibility
to
the
original
studies
and
highlights
sensitivities
concerning
the
relative
impact
of
various
pollutants,
the
potential
role
of
education
in
mediating
the
association
between
pollution
and
mortality,
and
the
influence
of
spatial
correlation
modeling.
Further
confirmation
and
extension
of
the
overall
findings
using
more
recent
air
quality
and
a
longer
follow­
up
period
for
the
ACS
cohort
was
recently
published
in
the
Journal
of
the
American
Medical
Association
(
Pope
et
al.,
2002).

In
developing
and
improving
the
methods
for
estimating
and
valuing
the
potential
reductions
in
mortality
risk
over
the
years,
the
EPA
has
consulted
with
the
SAB­
HES.
That
panel
recommended
use
of
long­
term
prospective
cohort
studies
in
estimating
mortality
risk
reduction
(
EPA­
SAB­
COUNCIL­
ADV­
99­
005,
1999).
This
recommendation
has
been
confirmed
by
a
recent
report
from
the
National
Research
Council,
which
stated
that
"
it
is
essential
to
use
the
cohort
studies
in
benefits
analysis
to
capture
all
important
effects
from
air
pollution
exposure"
(
NAS,
2002,
p.
108).
More
specifically,
the
SAB
recommended
emphasis
on
the
ACS
study
because
it
includes
a
much
larger
sample
size
and
longer
exposure
interval
and
covers
more
locations
(
e.
g.,
50
cities
compared
to
the
Six
Cities
Study)
than
other
studies
of
its
kind.
As
explained
in
the
regulatory
impact
analysis
for
the
Heavy­
Duty
Engine/
Diesel
Fuel
rule
(
EPA,
2000a),
more
recent
EPA
benefits
analyses
have
relied
on
an
improved
specification
of
the
ACS
cohort
data
that
was
developed
in
the
HEI
reanalysis
(
Krewski
et
al.,
2000).
The
latest
reanalysis
of
the
ACS
cohort
data
(
Pope
et
al.,
2002),
provides
additional
refinements
to
the
analysis
of
PMrelated
mortality
by
(
a)
extending
the
follow­
up
period
for
the
ACS
study
subjects
to
16
years,
which
triples
the
size
of
the
mortality
data
set;
(
b)
substantially
increasing
exposure
data,
including
consideration
for
cohort
exposure
to
PM2.5
following
implementation
of
PM2.5
standard
in
1999;
(
c)
controlling
for
a
variety
of
personal
risk
factors
including
occupational
exposure
and
diet;
and
(
d)
using
advanced
statistical
methods
to
evaluate
specific
issues
that
can
adversely
affect
risk
estimates
including
the
possibility
of
spatial
autocorrelation
of
survival
times
in
communities
located
near
each
other.
Because
of
these
refinements,
the
SAB­
HES
recommends
using
the
Pope
et
al.
(
2002)
study
as
the
basis
for
the
primary
mortality
estimate
for
adults
and
suggests
that
alternate
estimates
of
mortality
generated
using
other
cohort
and
time
series
studies
could
be
included
as
part
of
the
sensitivity
analysis
(
SAB­
HES,
2003).
However,
as
is
discussed
above
EPA
did
not
reassess
the
benefit
analysis
presented
at
proposal
of
this
rule
to
account
for
the
new
data
of
the
Pope
et
al.
(
2002)
study.

This
analysis
also
accounts
for
a
lag
between
reductions
in
PM
2.5
concentrations
and
reductions
in
mortality
incidence.
It
is
currently
unknown
whether
there
is
a
time
lag
(
a
delay
between
changes
in
PM
exposures
and
changes
in
mortality
rates)
in
the
long­
term
PM2.5/
premature
mortality
relationship.
The
existence
of
such
a
lag
is
important
for
the
valuation
of
premature
mortality
incidences
because
economic
theory
suggests
that
benefits
occurring
in
the
future
should
be
discounted.
Although
there
is
no
specific
scientific
evidence
of
the
existence
or
structure
of
a
PM
effects
lag,
current
scientific
literature
on
adverse
health
effects,
such
as
those
associated
with
PM
(
e.
g.,
smoking­
related
disease)
and
the
difference
in
the
effect
size
between
chronic
exposure
studies
and
daily
mortality
studies
suggest
that
all
incidences
of
premature
mortality
reduction
associated
with
a
given
incremental
change
in
PM
exposure
probably
would
not
occur
in
the
same
year
as
the
exposure
reduction.
This
same
smoking­
related
19http://
www.
biostat.
jhsph.
edu/
biostat/
research/
update.
main.
htm
20Both
the
single
day
and
distributed
lag
models
are
likely
to
be
affected
to
the
same
degree
by
the
S­
Plus
convergence
issue.
As
such,
the
ratio
of
the
coefficients
from
the
models
should
not
be
affected
as
much
by
any
changes
in
the
coefficient
10­
21
literature
implies
that
lags
of
up
to
a
few
years
are
plausible.
Adopting
the
lag
structure
endorsed
by
the
SAB
(
EPA­
SAB­
COUNCIL­
ADV­
00­
001,
1999),
we
assume
a
five­
year
lag
structure,
with
25
percent
of
premature
deaths
occurring
in
the
first
year
(
in
2005),
another
25
percent
in
the
second
year,
and
16.7
percent
in
each
of
the
remaining
three
years.
The
mortality
incidences
across
the
5­
year
period
is
then
discounted
back
to
our
year
of
analysis,
2005.

For
reductions
in
direct
emissions
of
PM
10,
we
use
a
different
C­
R
function,
based
on
the
studies
of
mortality
and
shorter
term
exposures
to
PM.
Long­
term
studies
of
the
relationship
between
chronic
exposure
and
mortality
have
not
found
significant
associations
with
coarse
particles
or
total
PM
10.
As
discussed
earlier
in
this
chapter,
concerns
have
recently
been
raised
about
aspects
of
the
statistical
methodology
used
in
a
number
of
recent
time­
series
studies
of
short­
term
exposures
to
air
pollution
and
health
effects.
Due
to
the
"
S­
Plus"
issue
identified
by
the
Health
Effects
Institute,
we
use
as
the
basis
for
the
our
primary
estimate
the
revised
relative
risk
from
the
NMMAPS
study,
reported
on
the
website
of
the
Johns
Hopkins
School
of
Public
Health19.
Similar
to
the
PM
2.5
lag
adjustment
discussed
above,
we
also
include
an
adjustment
for
PM
10
to
account
for
recent
evidence
that
daily
mortality
is
associated
with
particle
levels
from
a
number
of
previous
days.
We
use
the
overall
pooled
NMMAPS
estimate
of
a
0.224
percent
increase
in
mortality
for
a
10
µ
g/
m3
increase
in
PM
10
as
the
starting
point
in
developing
our
C­
R
function.
In
a
recent
analysis,
Schwartz
(
2000)
found
that
elevated
levels
of
PM
10
on
a
given
day
can
elevate
mortality
on
a
number
of
following
days.
This
type
of
multi­
day
model
is
often
referred
to
as
a
"
distributed
lag"
model
because
it
assumes
that
mortality
following
a
PM
event
will
be
distributed
over
a
number
of
days
following
or
"
lagging"
the
PM
event5.
Because
the
NMMAPS
study
reflects
much
broader
geographic
coverage
(
90
cities)
than
the
Schwartz
study
(
10
cities),
and
the
Schwartz
study
has
not
been
reanalyzed
to
account
for
the
"
S­
Plus"
issue,
we
choose
to
apply
an
adjustment
based
on
the
Schwartz
study
to
the
NMMAPS
study
to
reflect
the
effect
of
a
distributed
lag
model.

The
distributed
lag
adjustment
factor
is
constructed
as
the
ratio
of
the
estimated
coefficient
from
the
unconstrained
distributed
lag
model
to
the
estimated
coefficient
from
the
single­
lag
model
reported
in
Schwartz
(
2000)
20.
The
unconstrained
distributed
lag
model
coefficient
estimate
is
0.0012818
and
the
single­
lag
model
coefficient
estimate
is
0.0006479.
The
ratio
of
these
estimates
is
1.9784.
This
adjustment
factor
is
then
multiplied
by
the
revised
estimated
coefficients
from
the
NMMAPS
study.
The
NMMAPS
coefficient
corresponding
to
the
0.224
percent
increase
in
mortality
risk
is
0.000224.
The
adjusted
NMMAPS
coefficent
is
then
0.000224*
1.9784
=
0.000444.

10.4.2
Valuing
Individual
Health
Effect
Endpoints
The
appropriate
economic
value
of
a
change
in
a
health
effect
depends
on
whether
the
health
effect
is
viewed
ex
ante
(
before
the
effect
has
occurred)
or
ex
post
(
after
the
effect
has
occurred).
Reductions
in
ambient
concentrations
of
air
pollution
generally
lower
the
risk
of
future
adverse
health
affects
by
a
fairly
small
amount
for
a
large
population.
The
appropriate
economic
measure
is
therefore
ex
ante
WTP
for
changes
in
risk.
However,
epidemiological
studies
generally
provide
estimates
of
the
relative
risks
of
a
particular
health
effect
avoided
due
to
a
reduction
in
air
10­
22
pollution.
A
convenient
way
to
use
this
data
in
a
consistent
framework
is
to
convert
probabilities
to
units
of
avoided
statistical
incidences.
This
measure
is
calculated
by
dividing
individual
WTP
for
a
risk
reduction
by
the
related
observed
change
in
risk.
For
example,
suppose
a
measure
is
able
to
reduce
the
risk
of
premature
mortality
from
2
in
10,000
to
1
in
10,000
(
a
reduction
of
1
in
10,000).
If
individual
WTP
for
this
risk
reduction
is
$
100,
then
the
WTP
for
an
avoided
statistical
premature
mortality
amounts
to
$
1
million
($
100/
0.0001
change
in
risk).
Using
this
approach,
the
size
of
the
affected
population
is
automatically
taken
into
account
by
the
number
of
incidences
predicted
by
epidemiological
studies
applied
to
the
relevant
population.
The
same
type
of
calculation
can
produce
values
for
statistical
incidences
of
other
health
endpoints.

For
some
health
effects,
such
as
hospital
admissions,
WTP
estimates
are
generally
not
available.
In
these
cases,
we
use
the
cost
of
treating
or
mitigating
the
effect
as
a
primary
estimate.
For
example,
for
the
valuation
of
hospital
admissions
we
use
the
avoided
medical
costs
as
an
estimate
of
the
value
of
avoiding
the
health
effects
causing
the
admission.
These
costs
of
illness
(
COI)
estimates
generally
understate
the
true
value
of
reductions
in
risk
of
a
health
effect.
They
tend
to
reflect
the
direct
expenditures
related
to
treatment
but
not
the
value
of
avoided
pain
and
suffering
from
the
health
effect.
In
the
NRD
rule
RIA
and
TSD,
and
the
IAQR,
we
describe
how
the
changes
in
health
effects
should
be
valued
and
indicate
the
value
functions
selected
to
provide
monetized
estimates
of
the
value
of
changes
in
health
effects.
Table
10­
5
below
summarizes
the
value
estimates
per
health
effect
that
we
used
in
this
analysis.
Note
that
the
unit
values
for
hospital
admissions
are
the
weighted
averages
of
the
ICD­
9
code­
specific
values
for
the
group
of
ICD­
9
codes
included
in
the
hospital
admission
categories.

Table
10­
5.
Unit
Values
Used
for
Economic
Valuation
of
Health
Endpoints
Health
or
Welfare
Endpoint
Estimated
Value
Per
Incidence
(
1999$)
Central
Estimate
Derivation
of
Estimates
Premature
Mortality
(
longterm
exposure)
)
$
6
million
per
statistical
life
Value
is
the
mean
of
value­
of­
statistical­
life
estimates
from
26
studies
(
5
contingent
valuation
and
21
labor
market
studies)
reviewed
for
the
Section
812
Costs
and
Benefits
of
the
Clean
Air
Act,
1990­
2010
(
US
EPA,
1999).

Chronic
Bronchitis
$
331,000
Value
is
the
mean
of
a
generated
distribution
of
WTP
to
avoid
a
case
of
pollution­
related
CB.
WTP
to
avoid
a
case
of
pollution­
related
CB
is
derived
by
adjusting
WTP
(
as
described
in
Viscusi
et
al.,
1991)
to
avoid
a
severe
case
of
CB
for
the
difference
in
severity
and
taking
into
account
the
elasticity
of
WTP
with
respect
to
severity
of
CB.

Hospital
Admissions
Chronic
Obstructive
Pulmonary
Disease
(
COPD)
(
ICD
codes
490­
492,
494­
496)
$
12,378
The
COI
estimates
are
based
on
ICD­
9
code
level
information
(
e.
g.,
average
hospital
care
costs,
average
length
of
hospital
stay,
and
weighted
share
of
total
COPD
category
illnesses)
reported
in
Elixhauser
(
1993).

Pneumonia
(
ICD
codes
480­
487)
$
14,693
The
COI
estimates
are
based
on
ICD­
9
code
level
information
(
e.
g.,
average
hospital
care
costs,
average
length
of
hospital
stay,
and
weighted
share
of
total
pneumonia
category
illnesses)
reported
in
Elixhauser
(
1993).
Table
10­
5.
Unit
Values
Used
for
Economic
Valuation
of
Health
Endpoints
Health
or
Welfare
Endpoint
Estimated
Value
Per
Incidence
(
1999$)
Central
Estimate
Derivation
of
Estimates
10­
23
Asthma
admissions
$
6,634
The
COI
estimates
are
based
on
ICD­
9
code
level
information
(
e.
g.,
average
hospital
care
costs,
average
length
of
hospital
stay,
and
weighted
share
of
total
asthma
category
illnesses)
reported
in
Elixhauser
(
1993).

All
Cardiovascular
(
ICD
codes
390­
429)
$
18,387
The
COI
estimates
are
based
on
ICD­
9
code
level
information
(
e.
g.,
average
hospital
care
costs,
average
length
of
hospital
stay,
and
weighted
share
of
total
cardiovascular
illnesses)
reported
in
Elixhauser
(
1993).

Emergency
room
visits
for
asthma
$
299
COI
estimate
based
on
data
reported
by
Smith,
et
al.
(
1997).
Table
10­
5.
Unit
Values
Used
for
Economic
Valuation
of
Health
Endpoints
Health
or
Welfare
Endpoint
Estimated
Value
Per
Incidence
(
1999$)
Central
Estimate
Derivation
of
Estimates
10­
24
Respiratory
Ailments
Not
Requiring
Hospitalization
Upper
Respiratory
Symptoms
(
URS)
$
24
Combinations
of
the
3
symptoms
for
which
WTP
estimates
are
available
that
closely
match
those
listed
by
Pope,
et
al.
result
in
7
different
"
symptom
clusters,"
each
describing
a
"
type"
of
URS.
A
dollar
value
was
derived
for
each
type
of
URS,
using
mid­
range
estimates
of
WTP
(
IEc,
1994)
to
avoid
each
symptom
in
the
cluster
and
assuming
additivity
of
WTPs.
The
dollar
value
for
URS
is
the
average
of
the
dollar
values
for
the
7
different
types
of
URS.

Lower
Respiratory
Symptoms
(
LRS)
$
15
Combinations
of
the
4
symptoms
for
which
WTP
estimates
are
available
that
closely
match
those
listed
by
Schwartz,
et
al.
result
in
11
different
"
symptom
clusters,"
each
describing
a
"
type"
of
LRS.
A
dollar
value
was
derived
for
each
type
of
LRS,
using
mid­
range
estimates
of
WTP
(
IEc,
1994)
to
avoid
each
symptom
in
the
cluster
and
assuming
additivity
of
WTPs.
The
dollar
value
for
LRS
is
the
average
of
the
dollar
values
for
the
11
different
types
of
LRS.

Acute
Bronchitis
$
57
Average
of
low
and
high
values
recommended
for
use
in
Section
812
analysis
(
Neumann,
et
al.
1994)

Restricted
Activity
and
Work
Loss
Days
Work
Loss
Days
(
WLDs)
Variable
Regionally
adjusted
median
weekly
wage
for
1990
divided
by
5
(
adjusted
to
1999$)
(
US
Bureau
of
the
Census,
1992).

Minor
Restricted
Activity
Days
(
MRADs)
$
48
Median
WTP
estimate
to
avoid
one
MRAD
from
Tolley,
et
al.
(
1986)
.
21The
choice
of
a
discount
rate,
and
its
associated
conceptual
basis,
is
a
topic
of
ongoing
discussion
within
the
federal
government.
The
EPA
adopted
a
3
percent
discount
rate
for
its
primary
estimate
in
this
case
to
reflect
reliance
on
a
"
social
rate
of
time
preference"
discounting
concept.
We
have
also
calculated
benefits
and
costs
using
a
7
percent
rate
consistent
with
an
"
opportunity
cost
of
capital"
concept
to
reflect
the
time
value
of
resources
directed
to
meet
regulatory
requirements.
In
this
case,
the
benefit
and
cost
estimates
were
not
significantly
affected
by
the
choice
of
discount
rate.
Further
discussion
of
this
topic
appears
in
the
EPA's
Guidelines
for
Preparing
Economic
Analyses
(
in
press).

10­
25
Adjustments
for
Growth
in
Real
Income
Our
analysis
also
accounts
for
expected
growth
in
real
income
over
time.
Economic
theory
argues
that
WTP
for
most
goods
(
such
as
environmental
protection)
will
increase
if
real
incomes
increase.
The
economics
literature
suggests
that
the
severity
of
a
health
effect
is
a
primary
determinant
of
the
strength
of
the
relationship
between
changes
in
real
income
and
WTP
(
Alberini,
1997;
Miller,
2000;
Viscusi,
1993).
As
such,
we
use
different
factors
to
adjust
the
WTP
for
minor
health
effects,
severe
and
chronic
health
effects,
and
premature
mortality.
Adjustment
factors
used
to
account
for
projected
growth
in
real
income
from
1990
to
2005
are
1.03
for
minor
health
effects,
1.09
for
severe
and
chronic
health
effects,
and
1.08
for
premature
mortality.

10.4.2.1
Valuation
of
Reductions
in
Premature
Mortality
Risk
We
estimate
the
monetary
benefit
of
reducing
premature
mortality
risk
using
the
"
value
of
statistical
lives
saved"
(
VSL)
approach,
which
is
a
summary
measure
for
the
value
of
small
changes
in
mortality
risk
experienced
by
a
large
number
of
people.
The
VSL
approach
applies
information
from
several
published
value­
of­
life
studies
to
determine
a
reasonable
benefit
of
preventing
premature
mortality.
The
mean
value
of
avoiding
one
statistical
death
is
estimated
to
be
$
6
million
in
1999
dollars.
This
represents
an
intermediate
value
from
a
range
of
estimates
that
appear
in
the
economics
literature,
and
it
is
a
value
the
EPA
has
used
in
rulemaking
support
analyses
and
in
the
Section
812
Reports
to
Congress.
This
estimate
is
the
mean
of
a
distribution
fitted
to
the
estimates
from
26
value­
of­
life
studies
identified
in
the
Section
812
reports
as
"
applicable
to
policy
analysis."
The
approach
and
set
of
selected
studies
mirrors
that
of
Viscusi
(
1992)
(
with
the
addition
of
two
studies),
and
uses
the
same
criteria
as
Viscusi
in
his
review
of
value­
of­
life
studies.
The
$
6
million
estimate
is
consistent
with
Viscusi's
conclusion
(
updated
to
1999$)
that
"
most
of
the
reasonable
estimates
of
the
value
of
life
are
clustered
in
the
$
3.7
to
$
8.6
million
range."
Five
of
the
26
studies
are
contingent
valuation
(
CV)
studies,
which
directly
solicit
WTP
information
from
subjects;
the
rest
are
wage­
risk
studies,
which
base
WTP
estimates
on
estimates
of
the
additional
compensation
demanded
in
the
labor
market
for
riskier
jobs,
controlling
for
other
job
and
employee
characteristics
such
as
education
and
experience.

As
indicated
in
the
previous
section
on
quantification
of
premature
mortality
benefits,
we
assume
for
this
analysis
that
some
of
the
incidences
of
premature
mortality
related
to
PM
exposures
occur
in
a
distributed
fashion
over
the
five
years
following
exposure.
To
take
this
into
account
in
the
valuation
of
reductions
in
premature
mortality,
we
apply
an
annual
three
percent
discount
rate
to
the
value
of
premature
mortality
occurring
in
future
years21.

The
economics
literature
concerning
the
appropriate
method
for
valuing
reductions
in
premature
mortality
risk
is
still
developing.
The
adoption
of
a
value
for
the
projected
reduction
in
the
risk
of
premature
mortality
is
the
subject
of
continuing
discussion
within
the
economic
and
public
policy
analysis
community.
Regardless
of
the
theoretical
economic
considerations,
the
EPA
prefers
not
to
draw
distinctions
in
the
monetary
value
assigned
to
the
lives
saved
even
if
they
differ
in
age,
health
status,
socioeconomic
status,
gender,
or
other
characteristic
of
the
adult
population.
10­
26
Following
the
advice
of
the
EEAC
of
the
SAB,
the
EPA
currently
uses
the
VSL
approach
in
calculating
the
primary
estimate
of
mortality
benefits,
because
we
believe
this
calculation
provides
the
most
reasonable
single
estimate
of
an
individual's
willingness
to
trade
off
money
for
reductions
in
mortality
risk
(
EPA­
SAB­
EEAC­
00­
013).
Although
there
are
several
differences
between
the
labor
market
studies
we
use
to
derive
a
VSL
estimate
and
the
particulate
matter
air
pollution
context
addressed
here,
those
differences
in
the
affected
populations
and
the
nature
of
the
risks
imply
both
upward
and
downward
adjustments.
In
the
absence
of
a
comprehensive
and
balanced
set
of
adjustment
factors,
the
EPA
believes
it
is
reasonable
to
continue
to
use
the
$
6
million
value
while
acknowledging
the
significant
limitations
and
uncertainties
in
the
available
literature.

Some
economists
emphasize
that
the
value
of
a
statistical
life
is
not
a
single
number
relevant
for
all
situations.
Indeed,
the
VSL
estimate
of
$
6
million
(
1999
dollars)
is
itself
the
central
tendency
of
a
number
of
estimates
of
the
VSL
for
some
rather
narrowly
defined
populations.
When
there
are
significant
differences
between
the
population
affected
by
a
particular
health
risk
and
the
populations
used
in
the
labor
market
studies,
as
is
the
case
here,
some
economists
prefer
to
adjust
the
VSL
estimate
to
reflect
those
differences.

There
is
general
agreement
that
the
value
to
an
individual
of
a
reduction
in
mortality
risk
can
vary
based
on
several
factors,
including
the
age
of
the
individual,
the
type
of
risk,
the
level
of
control
the
individual
has
over
the
risk,
the
individual's
attitudes
towards
risk,
and
the
health
status
of
the
individual.
While
the
empirical
basis
for
adjusting
the
$
6
million
VSL
for
many
of
these
factors
does
not
yet
exist,
a
thorough
discussion
of
these
factors
is
contained
in
the
benefits
TSD
for
the
nonroad
diesel
rulemaking
(
Abt
Associates,
2003).
The
EPA
recognizes
the
need
for
investigation
by
the
scientific
community
to
develop
additional
empirical
support
for
adjustments
to
VSL
for
the
factors
mentioned
above.

The
SAB­
EEAC
advised
in
their
recent
report
that
the
EPA
"
continue
to
use
a
wage­
riskbased
VSL
as
its
primary
estimate,
including
appropriate
sensitivity
analyses
to
reflect
the
uncertainty
of
these
estimates,"
and
that
"
the
only
risk
characteristic
for
which
adjustments
to
the
VSL
can
be
made
is
the
timing
of
the
risk"(
EPA­
SAB­
EEAC­
00­
013).
In
developing
our
primary
estimate
of
the
benefits
of
premature
mortality
reductions,
we
have
followed
this
advice
and
discounted
over
the
lag
period
between
exposure
and
premature
mortality.

Uncertainties
Specific
to
Premature
Mortality
Valuation.
The
economic
benefits
associated
with
premature
mortality
are
the
largest
category
of
monetized
benefits
of
the
NESHAP.
In
addition,
in
prior
analyses,
the
EPA
has
identified
valuation
of
mortality
benefits
as
the
largest
contributor
to
the
range
of
uncertainty
in
monetized
benefits
(
see
EPA
[
1999]).
Because
of
the
uncertainty
in
estimates
of
the
value
of
premature
mortality
avoidance,
it
is
important
to
adequately
characterize
and
understand
the
various
types
of
economic
approaches
available
for
mortality
valuation.
Such
an
assessment
also
requires
an
understanding
of
how
alternative
valuation
approaches
reflect
that
some
individuals
may
be
more
susceptible
to
air
pollution­
induced
mortality
or
reflect
differences
in
the
nature
of
the
risk
presented
by
air
pollution
relative
to
the
risks
studied
in
the
relevant
economics
literature.

The
health
science
literature
on
air
pollution
indicates
that
several
human
characteristics
affect
the
degree
to
which
mortality
risk
affects
an
individual.
For
example,
some
age
groups
appear
to
be
more
susceptible
to
air
pollution
than
others
(
e.
g.,
the
elderly
and
children).
Health
status
prior
to
exposure
also
affects
susceptibility.
An
ideal
benefits
estimate
of
mortality
risk
reduction
would
reflect
these
human
characteristics,
in
addition
to
an
individual's
WTP
to
improve
one's
own
chances
of
survival
plus
WTP
to
improve
other
individuals'
survival
rates.
The
ideal
measure
would
also
take
into
account
the
specific
nature
of
the
risk
reduction
10­
27
commodity
that
is
provided
to
individuals,
as
well
as
the
context
in
which
risk
is
reduced.
To
measure
this
value,
it
is
important
to
assess
how
reductions
in
air
pollution
reduce
the
risk
of
dying
from
the
time
that
reductions
take
effect
onward,
and
how
individuals
value
these
changes.
Each
individual's
survival
curve,
or
the
probability
of
surviving
beyond
a
given
age,
should
shift
as
a
result
of
an
environmental
quality
improvement.
For
example,
changing
the
current
probability
of
survival
for
an
individual
also
shifts
future
probabilities
of
that
individual's
survival.
This
probability
shift
will
differ
across
individuals
because
survival
curves
depend
on
such
characteristics
as
age,
health
state,
and
the
current
age
to
which
the
individual
is
likely
to
survive.

Although
a
survival
curve
approach
provides
a
theoretically
preferred
method
for
valuing
the
benefits
of
reduced
risk
of
premature
mortality
associated
with
reducing
air
pollution,
the
approach
requires
a
great
deal
of
data
to
implement.
The
economic
valuation
literature
does
not
yet
include
good
estimates
of
the
value
of
this
risk
reduction
commodity.
As
a
result,
in
this
study
we
value
avoided
premature
mortality
risk
using
the
VSL
approach.

Other
uncertainties
specific
to
premature
mortality
valuation
include
the
following:

Across­
study
variation:
There
is
considerable
uncertainty
as
to
whether
the
available
literature
on
VSL
provides
adequate
estimates
of
the
VSL
saved
by
air
pollution
reduction.
Although
there
is
considerable
variation
in
the
analytical
designs
and
data
used
in
the
existing
literature,
the
majority
of
the
studies
involve
the
value
of
risks
to
a
middle­
aged
working
population.
Most
of
the
studies
examine
differences
in
wages
of
risky
occupations,
using
a
wage­
hedonic
approach.
Certain
characteristics
of
both
the
population
affected
and
the
mortality
risk
facing
that
population
are
believed
to
affect
the
average
WTP
to
reduce
the
risk.
The
appropriateness
of
a
distribution
of
WTP
based
on
the
current
VSL
literature
for
valuing
the
mortality­
related
benefits
of
reductions
in
air
pollution
concentrations
therefore
depends
not
only
on
the
quality
of
the
studies
(
i.
e.,
how
well
they
measure
what
they
are
trying
to
measure),
but
also
on
the
extent
to
which
the
risks
being
valued
are
similar
and
the
extent
to
which
the
subjects
in
the
studies
are
similar
to
the
population
affected
by
changes
in
pollution
concentrations.

Level
of
risk
reduction:
The
transferability
of
estimates
of
the
VSL
from
the
wagerisk
studies
to
the
context
of
the
Interstate
Air
Quality
Rulemaking
analysis
rests
on
the
assumption
that,
within
a
reasonable
range,
WTP
for
reductions
in
mortality
risk
is
linear
in
risk
reduction.
For
example,
suppose
a
study
estimates
that
the
average
WTP
for
a
reduction
in
mortality
risk
of
1/
100,000
is
$
50,
but
that
the
actual
mortality
risk
reduction
resulting
from
a
given
pollutant
reduction
is
1/
10,000.
If
WTP
for
reductions
in
mortality
risk
is
linear
in
risk
reduction,
then
a
WTP
of
$
50
for
a
reduction
of
1/
100,000
implies
a
WTP
of
$
500
for
a
risk
reduction
of
1/
10,000
(
which
is
10
times
the
risk
reduction
valued
in
the
study).
Under
the
assumption
of
linearity,
the
estimate
of
the
VSL
does
not
depend
on
the
particular
amount
of
risk
reduction
being
valued.
This
assumption
has
been
shown
to
be
reasonable
provided
the
change
in
the
risk
being
valued
is
within
the
range
of
risks
evaluated
in
the
underlying
studies
(
Rowlatt
et
al.,
1998).

Voluntariness
of
risks
evaluated:
Although
job­
related
mortality
risks
may
differ
in
several
ways
from
air
pollution­
related
mortality
risks,
the
most
important
difference
may
be
that
job­
related
risks
are
incurred
voluntarily,
or
generally
assumed
to
be,
whereas
air
pollution­
related
risks
are
incurred
involuntarily.
Some
evidence
suggests
that
people
will
pay
more
to
reduce
involuntarily
incurred
risks
than
risks
incurred
voluntarily.
If
this
is
the
case,
WTP
estimates
based
on
wage­
risk
studies
may
10­
28
understate
WTP
to
reduce
involuntarily
incurred
air
pollution­
related
mortality
risks.

Sudden
versus
protracted
death:
A
final
important
difference
related
to
the
nature
of
the
risk
may
be
that
some
workplace
mortality
risks
tend
to
involve
sudden,
catastrophic
events,
whereas
air
pollution­
related
risks
tend
to
involve
longer
periods
of
disease
and
suffering
prior
to
death.
Some
evidence
suggests
that
WTP
to
avoid
a
risk
of
a
protracted
death
involving
prolonged
suffering
and
loss
of
dignity
and
personal
control
is
greater
than
the
WTP
to
avoid
a
risk
(
of
identical
magnitude)
of
sudden
death.
To
the
extent
that
the
mortality
risks
addressed
in
this
assessment
are
associated
with
longer
periods
of
illness
or
greater
pain
and
suffering
than
are
the
risks
addressed
in
the
valuation
literature,
the
WTP
measurements
employed
in
the
present
analysis
would
reflect
a
downward
bias.

Self­
selection
and
skill
in
avoiding
risk.
Recent
research
(
Shogren
et
al.,
2002)
suggests
that
VSL
estimates
based
on
hedonic
wage
studies
may
overstate
the
average
value
of
a
risk
reduction.
This
is
based
on
the
fact
that
the
risk­
wage
tradeoff
revealed
in
hedonic
studies
reflects
the
preferences
of
the
marginal
worker
(
i.
e.,
that
worker
who
demands
the
highest
compensation
for
his
risk
reduction).
This
worker
must
have
either
higher
risk,
lower
risk
tolerance,
or
both.
However,
the
risk
estimate
used
in
hedonic
studies
is
generally
based
on
average
risk,
so
the
VSL
may
be
upwardly
biased
because
the
wage
differential
and
risk
measures
do
not
match.

10.4.2.2
Valuation
of
Reductions
in
Chronic
Bronchitis
The
best
available
estimate
of
WTP
to
avoid
a
case
of
chronic
bronchitis
(
CB)
comes
from
Viscusi,
et
al.
(
1991).
The
Viscusi,
et
al.
study,
however,
describes
a
severe
case
of
CB
to
the
survey
respondents.
We
therefore
employ
an
estimate
of
WTP
to
avoid
a
pollution­
related
case
of
CB,
based
on
adjusting
the
Viscusi,
et
al.
(
1991)
estimate
of
the
WTP
to
avoid
a
severe
case.
This
is
done
to
account
for
the
likelihood
that
an
average
case
of
pollution­
related
CB
is
not
as
severe.
The
adjustment
is
made
by
applying
the
elasticity
of
WTP
with
respect
to
severity
reported
in
the
Krupnick
and
Cropper
(
1992)
study.
Details
of
this
adjustment
procedure
can
be
found
in
the
IAQR
and
its
supporting
documentation,
and
in
the
most
recent
Section
812
study
(
EPA
1999).

We
use
the
mean
of
a
distribution
of
WTP
estimates
as
the
central
tendency
estimate
of
WTP
to
avoid
a
pollution­
related
case
of
CB
in
this
analysis.
The
distribution
incorporates
uncertainty
from
three
sources:
(
1)
the
WTP
to
avoid
a
case
of
severe
CB,
as
described
by
Viscusi,
et
al.;
(
2)
the
severity
level
of
an
average
pollution­
related
case
of
CB
(
relative
to
that
of
the
case
described
by
Viscusi,
et
al.);
and
(
3)
the
elasticity
of
WTP
with
respect
to
severity
of
the
illness.
Based
on
assumptions
about
the
distributions
of
each
of
these
three
uncertain
components,
we
derive
a
distribution
of
WTP
to
avoid
a
pollution­
related
case
of
CB
by
statistical
uncertainty
analysis
techniques.
The
expected
value
(
i.
e.,
mean)
of
this
distribution,
which
is
about
$
331,000
(
1999$),
is
taken
as
the
central
tendency
estimate
of
WTP
to
avoid
a
PM­
related
case
of
CB.

10.4.3
Results
of
Phase
One
Analysis:
Benefits
Resulting
from
a
Portion
of
Emission
Reductions
at
a
Subset
of
Boiler
and
Process
Heater
Sources
10­
29
Applying
the
C­
R
and
valuation
functions
described
above
to
the
estimated
changes
in
PM
from
phase
one
of
our
analysis
yields
estimates
of
the
number
of
avoided
incidences
(
i.
e.
premature
mortalities,
cases,
admissions,
etc.)
and
the
associated
monetary
values
for
those
avoided
incidences.
In
Table
10­
6,
we
provide
the
results
for
the
MACT
floor
option
resulting
from
the
phase
one
analysis.
Tables
10­
7
present
the
results
for
the
above
the
MACT
floor
option
resulting
from
the
phase
one
analysis.
To
obtain
a
total
benefit
estimate,
we
aggregate
dollar
benefits
associated
with
each
of
the
health
effects
examined,
such
as
hospital
admissions,
assuming
that
none
of
the
included
health
and
welfare
effects
overlap.
All
of
the
monetary
benefits
are
in
constant
1999
dollars.

As
we
have
discussed,
not
all
known
PM­
related
health
and
welfare
effects
could
be
quantified
or
monetized.
These
unmonetized
benefits
are
indicated
in
Tables
10­
6
and
10­
7
by
place
holders,
labeled
B
1
and
B
2.
In
addition,
unmonetized
benefits
associated
with
HAP
reductions
are
indicated
by
the
placeholder
B
3.
Unquantified
reduce
incidences
of
physical
effects
are
indicated
by
U
1
and
U
2.
The
estimate
of
total
monetized
health
benefits
is
thus
equal
to
the
subset
of
monetized
PM­
related
health
benefits
plus
B
H,
the
sum
of
the
unmonetized
health
benefits.
10­
30
Table
10­
6.
Phase
One
Analysis:
Estimate
of
Annual
Benefits
Associated
with
Approximately
50%
of
the
Emission
Reductions
from
the
Industrial
Boilers/
Process
Heaters
NESHAP
(
MACT
Floor
Regulatory
Option
in
2005)
Using
Air
Quality
Modeling
&
the
CAPMS
Benefit
ModelA,
B
Endpoint
Avoided
IncidenceC
(
cases/
year)
Monetary
BenefitsD
(
millions
1999$,
adjusted
for
growth
in
real
income)

Premature
mortalityE,
F
(
long­
term
exposure,
adults
30
and
over)
­
Using
a
3%
discount
rate
1,170
$
7,325
­
Using
a
7%
discount
rate
1,170
$
6,880
Chronic
bronchitis
(
adults,
26
and
over,
WTP
valuation)
2,340
$
845
Hospital
Admissions
 
Pneumonia
(
adults,
over
64)
500
$
5
Hospital
Admissions
 
COPD
(
adults,
64
and
over)
420
$
5
Hospital
Admissions
 
Asthma
(
65
and
younger)
120
$
1
Hospital
Admissions
 
Cardiovascular
(
adults,
over
64)
1,230
$
25
Emergency
Room
Visits
for
Asthma
(
65
and
younger)
930
<$
1
Asthma
Attacks
(
asthmatics,
all
ages)
79,020
B1
Acute
bronchitis
(
children,
8­
12)
2,430
<$
1
Lower
respiratory
symptoms
(
children,
7­
14)
26,470
<$
1
Upper
respiratory
symptoms
(
asthmatic
children,
9­
11)
89,480
$
5
Work
loss
days
(
adults,
18­
65)
205,400
$
20
Minor
restricted
activity
days
(
adults,
age
18­
65)
1,011,200
$
50
Other
PM­
related
health
effectsG
U1
B2
HAP
health
effectsG
U2
B3
Total
Monetized
Health­
Related
BenefitsF
­
Using
a
3%
discount
rate
 
$
8,280+
BH
­
Using
a
7%
discount
rate
 
$
7,835+
BH
AThe
results
presented
in
this
table
are
based
on
those
SO
2
and
PM
emission
reductions
identified
for
specific
sources
included
in
the
Inventory
Database.
This
includes
approximately
50%
of
all
emission
reductions
estimated
by
the
rule.
The
location
of
all
other
emission
reductions
(
i.
e.
noninventory
reductions)
cannot
be
determined
specifically
and
hence
cannot
be
modeled
in
an
air
quality
model.
See
Section
10.5
and
Appendix
D
for
benefit
estimation
of
non­
inventory
emission
reductions.
B
The
results
presented
in
this
table
reflect
the
outcome
of
the
combination
of
PM
and
SO
2
model
runs.
See
Appendix
D
for
a
presentation
of
results
for
each
pollutant
independently.
C
Incidences
are
rounded
to
the
nearest
10
and
may
not
add
due
to
rounding.
Incidences
of
unquantified
endpoints
are
indicated
with
a
U.
D
Dollar
values
are
rounded
to
the
nearest
5
million
and
may
not
add
due
to
rounding.
The
value
of
unquantified
endpoints
are
indicated
with
a
B.
E
Note
that
the
estimated
value
for
PM­
related
premature
mortality
assumes
the
5
year
distributed
lag
structure
described
in
detail
in
the
Regulatory
Impact
Analysis
of
Heavy
Duty
Engine/
Diesel
Fuel
rule.
F
Monetized
benefits
are
presented
using
two
different
discount
rates.
Results
calculated
using
3
percent
discount
rate
are
recommended
by
EPA's
Guidelines
for
Preparing
Economic
Analyses
(
U.
S.
EPA,
2000a).
Results
calculated
using
7
percent
discount
rate
are
recommended
by
OMB
Circular
A­
94
(
OMB,
1992).
G
A
detailed
listing
of
unquantified
PM
and
HAP
related
health
effects
is
provided
in
Table
10­
17.
10­
31
Thus,
the
estimate
of
total
monetized
benefits
for
phase
one
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
benefit
analysis
associated
with
the
MACT
floor
is
approximately
$
8
billion
+
B
H
(
using
either
a
3%
or
7%
discount
rate).
The
benefits
of
phase
one
in
combination
with
the
phase
two
estimate
of
benefits
will
serve
as
the
basis
for
our
estimate
of
the
total
benefits
of
the
regulation.
For
the
Above
the
MACT
floor
option
of
this
NESHAP,
Table
10­
7
indicates
that
the
estimate
of
total
monetized
benefits
for
phase
one
of
the
analysis
is
approximately
$
10
billion
+
B
H
using
a
3%
discount
rate
(
or
approximately
$
9.5
billion
using
a
7%
discount
rate).
10­
32
Table
10­
7.
Phase
One
Analysis:
Estimate
of
Annual
Benefits
Associated
with
Approximately
50%
of
the
Emission
Reductions
from
the
Industrial
Boilers/
Process
Heaters
NESHAP
(
Above
the
MACT
Floor
Regulatory
Option
in
2005)
Using
Air
Quality
Modeling
&
the
CAPMS
Benefit
ModelA,
B
Endpoint
Avoided
IncidenceC
(
cases/
year)
Monetary
BenefitsD
(
millions
1999$,
adjusted
for
growth
in
real
income)

Premature
mortalityE,
F
(
long­
term
exposure,
adults,
30
and
over)
­
Using
a
3%
discount
rate
1,390
$
8,740
­
Using
a
7%
discount
rate
1,390
$
8,210
Chronic
bronchitis
(
adults,
26
and
over,
WTP
valuation)
2,860
$
1,030
Hospital
Admissions
 
Pneumonia
(
adults,
over
64)
610
$
10
Hospital
Admissions
 
COPD
(
adults,
64
and
over)
500
$
5
Hospital
Admissions
 
Asthma
(
65
and
younger)
140
$
1
Hospital
Admissions
 
Cardiovascular
(
adults,
over
64)
1,480
$
25
Emergency
Room
Visits
for
Asthma
(
65
and
younger)
1,140
<$
1
Asthma
Attacks
(
asthmatics,
all
ages)
97,060
B1
Acute
bronchitis
(
children,
8­
12)
2,870
<$
1
Lower
respiratory
symptoms
(
children,
7­
14)
31,290
<$
1
Upper
respiratory
symptoms
(
asthmatic
children,
9­
11)
110,370
$
5
Work
loss
days
(
adults,
18­
65)
243,870
$
25
Minor
restricted
activity
days
(
adults,
age
18­
65)
1,196,500
$
60
Other
PM­
related
health
effectsF
U1
B2
HAP
health
effectsG
U2
B3
Total
Monetized
Health­
Related
BenefitsF
­
Using
a
3%
discount
rate
 
$
9,905+
BH
­
Using
a
7%
discount
rate
 
$
9,375+
BH
AThe
results
presented
in
this
table
are
based
on
those
SO
2
and
PM
emission
reductions
identified
for
specific
sources
included
in
the
Inventory
Database.
This
includes
approximately
50%
of
all
emission
reductions
estimated
by
the
rule.
The
location
of
all
other
emission
reductions
(
i.
e.
noninventory
reductions)
cannot
be
determined
specifically
and
hence
cannot
be
modeled
in
an
air
quality
model.
See
Section
10.5
and
Appendix
D
for
benefit
estimation
of
non­
inventory
emission
reductions.
B
The
results
presented
in
this
table
reflect
the
outcome
of
the
combination
of
PM
and
SO
2
model
runs.
See
Appendix
D
for
a
presentation
of
results
for
each
pollutant
independently.
C
Incidences
are
rounded
to
the
nearest
10
and
may
not
add
due
to
rounding.
Incidences
of
unquantified
endpoints
are
indicated
with
a
U.
D
Dollar
values
are
rounded
to
the
nearest
5
million
and
may
not
add
due
to
rounding.
The
value
of
unquantified
endpoints
are
indicated
with
a
B.
E
Note
that
the
estimated
value
for
PM­
related
premature
mortality
assumes
the
5
year
distributed
lag
structure
described
in
detail
in
the
Regulatory
Impact
Analysis
of
Heavy
Duty
Engine/
Diesel
Fuel
rule.
E
Monetized
benefits
are
presented
using
two
different
discount
rates.
Results
calculated
using
3
percent
discount
rate
are
recommended
by
EPA's
Guidelines
for
Preparing
Economic
Analyses
(
U.
S.
EPA,
2000a).
Results
calculated
using
7
percent
discount
rate
are
recommended
by
OMB
Circular
A­
94
(
OMB,
1992).
F
A
detailed
listing
of
unquantified
PM
and
HAP
related
health
effects
is
provided
in
Table
10­
17.
10­
33
Transfer
Value

Benefits
Emission
Reductions
10.5
Phase
Two
Analysis:
Benefit
Transfer
Valuation
of
Remaining
Emission
Reductions
As
is
mentioned
previously,
only
a
portion
of
the
expected
emission
reductions
of
the
rule
can
be
mapped
to
specific
locations
and
hence
modeled
to
determine
the
change
in
air
quality
(
e.
g.,
change
in
ambient
PM
concentrations).
For
approximately
50%
of
the
PM
reductions
and
approximately
30%
of
the
SO
2
reductions,
the
lack
of
location­
specific
data
prevents
us
from
utilizing
the
S­
R
Matrix
to
determine
air
quality
changes
and
the
CAPMS
model
to
estimate
total
benefits.
We
can
assume,
however,
that
these
reductions
are
achieved
uniformly
throughout
the
country
because
the
location
of
boilers/
process
heaters
in
the
U.
S.
is
spread
fairly
evenly
across
all
states.
To
estimate
benefits
for
these
reductions,
we
use
the
results
of
the
air
quality
and
benefit
analysis
provided
in
phase
one
to
infer
the
average
benefit
value
per
ton
of
emission
reduction
for
each
pollutant
­
PM
and
SO
2.
The
benefit
transfer
values
for
PM
and
SO
2
are
then
applied
to
all
remaining
emission
reductions
to
approximate
total
benefits
of
phase
two
of
this
analysis.

Before
determining
the
benefit
value
to
transfer
to
these
reductions,
one
consideration
must
first
be
made.
The
total
benefits
that
result
from
the
air
quality
analysis
of
phase
one
is
due
to
the
combination
of
both
direct
PM
reductions
and
SO
2
reductions
that
transform
into
secondary
PM.
Without
knowledge
of
the
percent
of
the
total
benefits
in
phase
one
that
can
be
attributed
to
direct
PM
versus
the
percent
of
phase
one
benefits
attributed
to
SO
2,
we
cannot
accurately
assign
the
monetized
benefits
to
the
tons
reduced
of
each
pollutant.
To
correctly
apportion
the
total
benefit
value
from
phase
one
to
the
respective
PM
and
SO
2
reductions,
we
performed
two
additional
S­
R
Matrix
model
runs
of
the
reductions
valued
in
phase
one;
one
evaluation
of
the
benefits
of
the
PM
reductions
alone
(
holding
SO
2
unchanged),
and
one
run
of
the
benefits
of
the
SO
2
reductions
alone
(
holding
PM
reductions
unchanged).
This
allows
us
to
determine
the
appropriate
benefit
transfer
value
for
each
individual
pollutant.
Because
the
combined
effect
of
reducing
both
PM
and
SO
2
simultaneously
at
one
location
would
result
in
a
larger
change
in
the
concentration
of
PM,
it
can
be
expected
that
the
air
quality
analyses
of
each
pollutant
alone
will
result
in
lower
changes
in
concentrations
and
hence
lower
calculated
benefits.
The
air
quality
and
benefit
assessment
of
the
individual
pollutants
are
again
performed
for
each
regulatory
option:
the
MACT
floor,
and
the
above
the
MACT
floor
option.
The
detailed
results
of
the
additional
air
quality
and
benefit
model
runs
are
reported
in
Appendix
D.

These
data,
along
with
the
set
of
C­
R
and
valuation
functions
contained
in
CAPMS,
constitute
the
input
set
for
the
benefits
transfer
value
function.
The
benefits
transfer
function
for
each
pollutant
is
specified
as:

The
numerator
in
the
transfer
value
formula
is
total
monetary
benefits,
which
is
determined
by
applying
the
same
economic
valuation
functions
specified
in
Table
10­
5
to
changes
in
incidences
of
human
health
endpoints
resulting
from
the
air
quality
modeling
of
each
pollutant
separately.
In
Appendix
D,
we
show
the
calculated
benefit
transfer
value
of
the
total
monetized
benefits
of
PM
alone
and
SO
2
alone
and
also
for
each
individual
endpoint
included
in
this
analysis.

A
similar
calculation
is
also
done
for
the
number
of
incidences
associated
with
each
endpoint.
From
the
air
quality
assessments
of
PM
and
SO
2
alone,
we
divide
total
incidences
of
an
endpoint
by
the
total
emission
reductions
included
in
the
air
quality
scenario.
Therefore,
we
determine
a
measure
of
the
number
of
incidences
of
each
health
effect
that
can
result
from
a
ton
10­
34
of
pollutant
reductions
(
for
example,
0.10
fewer
asthma
cases
per
ton
reduced).
This
allows
us
to
transfer
the
incidence
per
ton
reduced
to
the
remaining
set
of
emission
reductions
of
the
phase
two
analysis.

Note
that
for
both
dollar
and
incidence
per
ton
estimates,
we
assume
that
each
ton
of
pollutant
has
the
same
impact,
so
that
subnational
applications
are
inappropriate
as
the
national
application
requires
assuming
populations
are
uniformly
distributed
throughout
the
U.
S.

Once
all
transfer
values
are
determined
for
each
endpoint
and
total
benefits,
we
apply
them
to
the
set
of
phase
two
emission
reductions.
Finally,
we
combine
our
phase
two
estimates
of
benefits
with
the
phase
one
calculated
benefits
to
provide
an
estimate
of
total
benefits
for
each
endpoint
and
determine
the
total
monetized
benefits
associated
with
the
rule.

Sections
10.5.1
and
10.5.2
provide
further
detail
on
the
transfer
values
obtained
for
SO
2
and
PM
in
this
analysis.

10.5.1
SO
2
Benefits
Transfer
Values
Using
the
results
of
the
air
quality
analysis
of
SO
2
reductions
alone
(
holding
PM
unchanged)
from
phase
one,
we
can
extract
information
on
the
total
number
of
incidences
and
total
benefit
value
of
each
endpoint
to
estimate
the
SO
2
benefit
transfer
values.
As
an
example
of
the
calculation
consider
the
following:
the
total
SO
2
emission
reductions
applied
in
the
S­
R
matrix
analysis
for
phase
one
of
this
analysis
are
82,542
tons.
Under
the
MACT
floor,
the
analysis
yields
approximately
240
fewer
premature
deaths
at
a
total
value
of
$
1.5
billion
(
see
Appendix
D
for
details).
Therefore,
the
benefit
transfer
value
to
apply
to
SO
2
emission
reductions
in
the
phase
two
analysis
associated
with
the
mortality
endpoint
would
on
average
be
$
18,385
per
ton
reduced.
This
procedure
is
repeated
for
each
endpoint
and
for
the
total
benefits
estimate
associated
with
SO
2
reductions
alone.
Further,
based
on
these
results
it
can
be
estimated
that
SO
2
reductions
from
the
MACT
floor
on
average
result
in
0.003
fewer
incidences
of
mortality
per
ton
reduced
(
240
incidences/
82,542
tons).

The
following
tables
present
the
incidence
and
benefits
data
necessary
to
calculate
the
benefits
transfer
values
for
SO
2.
Table
10­
8
present
the
benefit
transfer
values
for
the
MACT
floor
option,
while
Table
10­
9
presents
benefit
transfer
values
associated
with
the
Above
the
MACT
floor
option.
The
benefits
transfer
values
for
SO
2
emission
reductions
are
reported
in
1999
dollars.
Differences
in
benefit/
ton
estimates
between
the
MACT
floor
option
and
the
above
the
floor
option
may
be
due
to
differences
in
the
location
of
emission
reductions
and
other
factors.
In
particular,
while
PM
reductions
from
process
heaters
are
not
expected
to
accrue
at
the
MACT
floor
level
of
control,
approximately
18,300
tons
are
estimate
for
the
above
the
floor
option.
The
Inventory
Database
provides
information
on
the
location
of
the
majority
of
process
heaters
and
thus
we
can
apply
a
large
percentage
of
these
reductions
directly
into
the
air
quality
and
benefit
analysis.
In
addition,
the
process
heaters
affected
by
this
proposal
are
largely
found
at
large
facilities
located
near
large
cities,
thus
the
changes
in
air
quality
are
applied
to
the
populated
areas
around
the
cities.
10­
35
Table
10­
8.
SO2
Benefit
Transfer
Values
Based
on
Data
From
Phase
One
Analysis
MACT
Floor
Regulatory
OptionA
Endpoint
Avoided
IncidenceB
(
cases/
year)
Incidence
Per
Ton
ReducedC
Monetary
BenefitsD
(
millions
1999$,
adjusted
for
growth
in
real
income)
Total
Benefit
Per
Ton
ReducedC
($/
ton)

Premature
mortalityE
(
long­
term
exposure,
adults
30
and
over)
­
Using
a
3%
discount
rate
240
0.0029
$
1,520
$
18,385
­
Using
a
7%
discount
rate
240
0.0029
$
1,425
$
17,270
Chronic
bronchitis
(
adults,
26
and
over,
WTP
valuation)
320
0.0039
$
115
$
1,400
Hospital
Admissions
 
Pneumonia
(
adults,
over
64)
60
0.0008
$
1
$
10
Hospital
Admissions
 
COPD
(
adults,
64
and
over)
50
0.0006
$
1
$
5
Hospital
Admissions
 
Asthma
(
65
and
younger)
20
0.0003
<$
1
<$
5
Hospital
Admissions
 
Cardiovascular
(
adults,
over
64)
150
0.0018
$
5
$
30
Emergency
Room
Visits
for
Asthma
(
65
and
younger)
130
0.0016
<$
1
<$
1
Asthma
Attacks
(
asthmatics,
all
ages)
11,120
0.1347
B
1
B
1
Acute
bronchitis
(
children,
8­
12)
490
0.0059
<$
1
<$
1
Lower
respiratory
symptoms
(
children,
7­
14)
5,330
0.0645
<$
1
$
1
Upper
respiratory
symptoms
(
asthmatic
children,
9­
11)
12,980
0.1572
<$
1
$
5
Work
loss
days
(
adults,
18­
65)
42,611
0.5162
$
5
$
55
Minor
restricted
activity
days
(
adults,
age
18­
65)
214,592
2.5998
$
10
$
130
Other
PM­
related
health
effectsF
U
1
­­­­­
B
2
B
2
HAP­
related
health
effectsF
U
2
­­­­­
B
3
B
3
Total
Benefits
of
SO2­
Related
ReductionsE
­
Using
a
3%
discount
rate
 
­
­­­­
$
1,650
$
20,030+
B
H
­
Using
a
7%
discount
rate
C
­­­­­
$
1,560
$
18,910+
B
H
A
Results
of
the
phase
one
benefit
analysis
of
SO
2
emission
reductions
are
presented
in
Appendix
D,
and
replicated
in
columns
2
and
4
of
this
table.
B
Incidences
are
rounded
to
the
nearest
10
and
may
not
add
due
to
rounding.
Incidences
of
unquantified
endpoints
are
indicated
with
a
U.
C
Total
SO
2
emission
reductions
included
in
the
phase
one
analysis
and
applied
to
derive
the
benefit
transfer
values
of
this
table
are
82,542
tons.
D
Dollar
values
are
rounded
to
the
nearest
5
million
and
may
not
add
due
to
rounding.
The
value
of
unquantified
endpoints
are
indicated
with
a
B.
E
Monetized
benefits
are
presented
using
two
different
discount
rates.
Results
calculated
using
3
percent
discount
rate
are
recommended
by
EPA's
Guidelines
for
Preparing
Economic
Analyses
(
U.
S.
EPA,
2000a).
Results
calculated
using
7
percent
discount
rate
are
recommended
by
OMB
Circular
A­
94
(
OMB,
1992).

Table
10­
9.
SO2
Benefit
Transfer
Values
Based
on
Data
From
Phase
One
Analysis
Above
the
MACT
Floor
Regulatory
OptionA
10­
36
Endpoint
Avoided
IncidenceB
(
cases/
year)
Incidence
Per
Ton
ReducedC
Monetary
BenefitsD
(
millions
1999$,
adjusted
for
growth
in
real
income)
Total
Benefit
Per
Ton
ReducedC
($/
ton)

Premature
mortality
(
long­
term
exposure,
adults,
30
and
over)
­
Using
a
3%
discount
rate
310
0.0032
$
1,935
$
20,305
­
Using
a
7%
discount
rate
310
0.0032
$
1,820
$
19,070
Chronic
bronchitis
(
adults,
26
and
over,
WTP
valuation)
400
0.0042
$
145
$
1,500
Hospital
Admissions
 
Pneumonia
(
adults,
over
64)
70
0.0007
$
1
$
10
Hospital
Admissions
 
COPD
(
adults,
64
and
over)
60
0.0006
$
1
$
10
Hospital
Admissions
 
Asthma
(
65
and
younger)
30
0.0003
<$
1
<$
5
Hospital
Admissions
 
Cardiovascular
(
adults,
over
64)
170
0.0018
$
5
$
35
Emergency
Room
Visits
for
Asthma
(
65
and
younger)
150
0.0015
<$
1
<$
1
Asthma
Attacks
(
asthmatics,
all
ages)
12,250
0.1284
B
1
B
1
Acute
bronchitis
(
children,
8­
12)
660
0.0069
<$
1
<$
1
Lower
respiratory
symptoms
(
children,
7­
14)
7,170
0.0752
<$
1
$
1
Upper
respiratory
symptoms
(
asthmatic
children,
9­
11)
14,160
0.1485
<$
1
$
5
Work
loss
days
(
adults,
18­
65)
54,980
0.5765
$
5
$
60
Minor
restricted
activity
days
(
adults,
age
18­
65)
279,760
2.9337
$
15
$
145
Other
PM­
related
health
effects
U
1
­­­­­
B
2
B
2
HAP­
related
health
effects
U
2
­­­­­
B
3
B
3
Total
Benefits
of
SO2­
Related
Reductions
­
Using
a
3%
discount
rate
C
­­­­­
$
2,105
$
22,070+
B
H
­
Using
a
7%
discount
rate
 
­
­­­­
$
1,990
$
20,840+
B
H
A
Results
of
the
phase
one
benefit
analysis
of
SO
2
emission
reductions
are
presented
in
Appendix
D,
and
replicated
in
columns
2
and
4
of
this
table.
B
Incidences
are
rounded
to
the
nearest
10
and
may
not
add
due
to
rounding.
Incidences
of
unquantified
endpoints
are
indicated
with
a
U.
C
Total
SO
2
emission
reductions
included
in
the
phase
one
analysis
and
applied
to
derive
the
benefit
transfer
values
of
this
table
are
95,361
tons.
D
Dollar
values
are
rounded
to
the
nearest
5
million
and
may
not
add
due
to
rounding.
The
value
of
unquantified
endpoints
are
indicated
with
a
B.
10.5.2
PM
Benefits
Transfer
Values
The
transfer
values
for
PM
are
developed
using
the
same
basic
approach
as
for
the
SO2
reductions.
However,
the
PM
benefits
analysis
conducted
for
this
RIA
includes
health
benefits
associated
with
reductions
in
both
PM
2.5
and
PM
10.
Therefore,
the
benefit
transfer
values
for
endpoints
associated
with
PM
2.5
alone
will
be
established
using
an
estimate
of
the
portion
of
total
PM
reductions
that
are
likely
to
be
PM
2.5.
Likewise
the
benefit
endpoints
associated
with
PM
10
alone
require
an
estimate
of
PM
10
emission
reductions
to
derive
the
benefit
transfer
value
for
such
endpoints.
Fortunately,
the
S­
R
Matrix
model
has
a
component
that
can
approximate
PM
2.5
emissions
from
a
total
change
in
PM.
Based
on
this
approximation,
of
the
265,155
tons
of
PM
10
emission
reductions
included
in
the
air
quality
analysis
of
the
MACT
floor
from
phase
one,
22
Reductions
in
PM2.5
are
derived
as
a
function
of
the
estimated
PM10
reductions.
The
S­
R
matrix
model
contains
coefficients
that
relate
reductions
in
both
directly
emitted
PM10
and
directly
emitted
PM2.5.
At
the
time
the
S­
R
matrix
was
being
developed
in
the
early
1990s,
a
nationwide
inventory
of
directly
emitted
PM2.5
emissions
was
not
available,
so
the
author
developed
a
method
for
crudely
estimating
PM2.5
emissions
from
PM10
emissions.
The
air
quality
changes
predicted
by
the
model
for
direct
PM2.5
were
then
developed
from
these
crude
emissions
estimates.
A
full
discussion
of
the
derivation
of
PM2.5
estimates
is
provided
in
E.
H.
Pechan
(
1994
and
1996),
and
Latimer
and
Associates(
1996).
The
PM
Calculator
Tool
can
also
be
found
on
the
Internet
at
www.
epa.
gov/
chief/
software/
pmcalc/
index.
html.

10­
37
approximately
75,095
tons
are
PM
2.5.22
The
endpoints
associated
with
PM
2.5
are
long­
term
mortality,
minor
restricted
activity
days
(
MRAD),
and
acute
respiratory
symptoms.
All
other
endpoints
are
associated
with
PM
10
reductions.
For
the
MACT
floor
option,
Tables
10­
9
present
the
total
incidence
and
benefits
data
for
each
endpoint
from
the
phase
one
analysis
,
and
the
calculated
the
benefits
transfer
values
for
PM
that
are
to
be
applied
for
the
phase
two
analysis.
Table
10­
10
present
similar
data
for
the
above
the
MACT
floor
regulatory
option.
10­
38
Table
10­
10.
PM
Benefit
Transfer
Values
Based
on
Data
From
Phase
One
Analysis
MACT
Floor
Regulatory
OptionA
Endpoint
Avoided
IncidenceB
(
cases/
year)
Incidence
Per
Ton
ReducedC
Monetary
BenefitsD
(
millions
1999$,
adjusted
for
growth
in
real
income)
Total
Benefit
Per
Ton
ReducedC
($/
ton)

Premature
mortality
(
long­
term,
adults,
30
and
over)
­
Using
a
3%
discount
rate
900
0.01202
$
5,675
$
75,595
­
Using
a
7%
discount
rate
900
0.01202
$
5,330
$
71,005
Chronic
bronchitis
(
adults,
26
and
over,
WTP
valuation)
2,360
0.0089
$
850
$
3,195
Hospital
Admissions
 
Pneumonia
(
adults,
over
64)
510
0.0019
$
10
$
30
Hospital
Admissions
 
COPD
(
adults,
64
and
over)
420
0.0016
$
5
$
20
Hospital
Admissions
 
Asthma
(
65
and
younger)
90
0.0012
$
1
$
10
Hospital
Admissions
 
Cardiovascular
(
adults,
over
64)
1,230
0.0046
$
25
$
85
Emergency
Room
Visits
for
Asthma
(
65
and
younger)
950
0.0036
<$
1
$
1
Asthma
Attacks
(
asthmatics,
all
ages)
80,700
0.3043
B
1
B
1
Acute
bronchitis
(
children,
8­
12)
1,870
0.0248
<$
1
$
1
Lower
respiratory
symptoms
(
children,
7­
14)
20,370
0.2712
<$
1
$
5
Upper
respiratory
symptoms
(
asthmatic
children,
9­
11)
91,620
0.3455
$
5
$
10
Work
loss
days
(
adults,
18­
65)
158,560
2.1115
$
20
$
225
Minor
restricted
activity
days
(
adults,
age
18­
65)
760,870
10.132
$
40
$
500
Other
PM­
related
health
effects
U
1
­­­­­
B
2
B
2
HAP­
related
health
effects
U
2
­­­­­
B
3
B
3
Total
Benefits
of
PM­
Related
Reductions
­
Using
a
3%
discount
rate)
 
­
­­­­
$
6,620
$
88,120+
B
H
­
Using
a
7%
discount
rate
 
­
­­­­
$
6,275
$
83,530+
B
H
A
Results
of
the
phase
one
benefit
analysis
of
PM
emission
reductions
are
presented
in
Appendix
D,
and
replicated
in
columns
2
and
4
of
this
table.
B
Incidences
are
rounded
to
the
nearest
10
and
may
not
add
due
to
rounding.
Incidences
of
unquantified
endpoints
are
indicated
with
a
U.
C
Total
PM
10
and
PM
2.5
emission
reductions
included
in
the
phase
one
analysis
and
applied
to
derive
the
benefit
transfer
values
of
this
table
are
265,155
tons
and
75,095
tons,
respectively.
D
Dollar
values
are
rounded
to
the
nearest
5
million
and
may
not
add
due
to
rounding.
The
value
of
unquantified
endpoints
are
indicated
with
a
B.
10­
39
Table
10­
11.
PM
Benefit
Transfer
Values
Based
on
Data
From
Phase
One
Analysis
Above
the
MACT
Floor
Regulatory
OptionA
Endpoint
Avoided
IncidenceB
(
cases/
year)
Incidence
Per
Ton
ReducedC
Monetary
BenefitsD
(
millions
1999$,
adjusted
for
growth
in
real
income)
Total
Benefit
Per
Ton
ReducedC
Premature
mortality
(
long­
term
exposure,
adults,
30
and
over)
­
Using
a
3%
discount
rate
1,090
0.0115
$
6,835
$
72,290
­
Using
a
7%
discount
rate
1,090
0.0115
$
6,420
$
67,900
Chronic
bronchitis
(
adults,
26
and
over,
WTP
valuation)
2,680
0.0085
$
965
$
3,070
Hospital
Admissions
 
Pneumonia
(
adults,
over
64)
570
0.0018
$
10
$
30
Hospital
Admissions
 
COPD
(
adults,
64
and
over)
470
0.0015
$
5
$
20
Hospital
Admissions
 
Asthma
(
65
and
younger)
110
0.0012
$
1
$
10
Hospital
Admissions
 
Cardiovascular
(
adults,
over
64)
1,390
0.0044
$
25
$
80
Emergency
Room
Visits
for
Asthma
(
65
and
younger)
1,070
0.0034
<$
1
$
1
Asthma
Attacks
(
asthmatics,
all
ages)
90,940
0.2897
B
1
B
1
Acute
bronchitis
(
children,
8­
12)
2,230
0.0236
<$
1
$
1
Lower
respiratory
symptoms
(
children,
7­
14)
24,330
0.2572
<$
1
$
5
Upper
respiratory
symptoms
(
asthmatic
children,
9­
11)
103,400
0.3294
$
5
$
10
Work
loss
days
(
adults,
18­
65)
190,370
2.0131
$
20
$
215
Minor
restricted
activity
days
(
adults,
age
18­
65)
918,650
9.7144
$
45
$
485
Other
PM­
related
health
effects
U
1
­­­­­
B
2
B
2
HAP­
related
health
effects
U
2
­­­­­
B
3
B
3
Total
Benefits
of
PM­
Related
Reductions
­
Using
a
3%
discount
rate
C
­­­­­
$
7,910
$
83,645+
B
H
­
Using
a
7%
discount
rate
 
­
­­­­
$
7,495
$
79,255+
B
H
A
Results
of
the
phase
one
benefit
analysis
of
PM
emission
reductions
are
presented
in
Appendix
D,
and
replicated
in
columns
2
and
4
of
this
table.
B
Incidences
are
rounded
to
the
nearest
10
and
may
not
add
due
to
rounding.
Incidences
of
unquantified
endpoints
are
indicated
with
a
U.
C
Total
PM
10
and
PM
2.5
emission
reductions
included
in
the
phase
one
analysis
and
applied
to
derive
the
benefit
transfer
values
of
this
table
are
313,947
tons
and
94,565
tons,
respectively.
D
Dollar
values
are
rounded
to
the
nearest
5
million
and
may
not
add
due
to
rounding.
The
value
of
unquantified
endpoints
are
indicated
with
a
B.
10­
40
10.5.3
Application
of
Benefits
Transfer
Values
to
Phase
Two
Emission
Reductions
Emission
reductions
included
in
phase
two
of
our
benefit
analysis
are
summarized
in
Table
10­
2.
These
reductions
will
be
applied
to
the
benefit
transfer
values
developed
in
the
previous
section.
These
emission
reductions
are
derived
by
simply
subtracting
the
emission
reductions
including
in
the
phase
one
analysis
from
the
total
emission
reductions
anticipated
from
this
NESHAP.

Thus,
in
the
final
step
of
the
phase
two
analysis,
the
transfer
values
calculated
in
section
10.5.3
are
multiplied
by
the
emission
reductions
associated
with
the
phase
two
analysis.
Appendix
D
provides
tables
showing
the
benefit
estimation
for
each
pollutant
(
PM
and
SO
2)
separately.
In
the
tables
below,
we
combine
the
total
SO
2
benefits
of
phase
two
with
the
total
PM
benefits
of
phase
two
from
Appendix
D
to
provide
a
summary
of
total
benefits
associated
with
phase
two
of
this
analysis
for
each
regulatory
option
analyzed.
10­
41
Table
10­
12.
Phase
Two
Analysis:
Annual
Health
Benefits
Associated
with
Non­
Inventory
Emission
Reductions
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
­
MACT
Floor
Regulatory
Option
in
2005,
Using
Benefit
Transfer
ValuesA
Endpoint
Avoided
IncidenceB
(
cases/
year)
Monetary
BenefitsC
(
millions
1999$,
adjusted
for
growth
in
real
income)

Premature
mortalityD
(
long­
term
exposure,
adults,
30
and
over)
­
Using
a
3%
discount
rate
1,100
$
6,920
­
Using
a
7%
discount
rate
1,110
$
6,495
Chronic
bronchitis
(
adults,
26
and
over,
WTP
valuation)
2,760
$
990
Hospital
Admissions
 
Pneumonia
(
adults,
over
64)
590
$
10
Hospital
Admissions
 
COPD
(
adults,
64
and
over)
490
$
5
Hospital
Admissions
 
Asthma
(
65
and
younger)
110
$
1
Hospital
Admissions
 
Cardiovascular
(
adults,
over
64)
1,430
$
25
Emergency
Room
Visits
for
Asthma
(
65
and
younger)
1,110
<$
1
Asthma
Attacks
(
asthmatics,
all
ages)
94,470
B
1
Acute
bronchitis
(
children,
8­
12)
2,270
<$
1
Lower
respiratory
symptoms
(
children,
7­
14)
24,770
<$
1
Upper
respiratory
symptoms
(
asthmatic
children,
10­
11)
107,380
<$
5
Work
loss
days
(
adults,
18­
65)
193,270
$
20
Minor
restricted
activity
days
(
adults,
age
18­
65)
931,140
$
45
Other
PM­
related
health
effectsE
U
1
B
2
HAP­
related
health
effectsE
U
2
B
3
Total
Monetized
Health­
Related
Benefits
­
Using
a
3%
discount
rate
 
$
8,020+
BH
­
Using
a
7%
discount
rate
 
$
7,600+
BH
A
The
results
presented
in
this
table
reflect
the
outcome
of
the
combination
of
PM
and
SO
2
benefit
estimates
from
the
application
of
benefit
transfer
values
applied
in
the
phase
two
analysis.
See
Appendix
D
for
a
presentation
of
results
for
each
pollutant
independently.
B
Incidences
are
rounded
to
the
nearest
10
and
may
not
add
due
to
rounding.
Incidences
of
unquantified
endpoints
are
indicated
with
a
U.
C
Dollar
values
are
rounded
to
the
nearest
5
million
and
may
not
add
due
to
rounding.
The
value
of
unquantified
endpoints
are
indicated
with
a
B.
D
Note
that
the
estimated
value
for
PM­
related
premature
mortality
assumes
the
5
year
distributed
lag
structure
described
in
detail
in
the
Regulatory
Impact
Analysis
of
Heavy
Duty
Engine/
Diesel
Fuel
rule.
E
A
detailed
listing
of
unquantified
PM
and
HAP
related
health
effects
is
provided
in
Table
10­
16.
10­
42
Table
10­
13.
Phase
Two
Analysis:
Annual
Health
Benefits
Associated
with
Non­
Inventory
Emission
Reductions
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
­
Above
the
MACT
Floor
Regulatory
Option
in
2005,
Using
Benefit
Transfer
ValuesA
Endpoint
Avoided
IncidenceB
(
cases/
year)
Monetary
BenefitsC
(
millions
1999$,
adjusted
for
growth
in
real
income)

Premature
mortalityD
(
long­
term
exposure,
adults,
30
and
over)
­
Using
a
3%
discount
rate
1,020
$
6,400
­
Using
a
7%
discount
rate
1,020
$
6,010
Chronic
bronchitis
(
adults,
26
and
over,
WTP
valuation)
2,350
$
850
Hospital
Admissions
 
Pneumonia
(
adults,
over
64)
500
$
10
Hospital
Admissions
 
COPD
(
adults,
64
and
over)
410
$
5
Hospital
Admissions
 
Asthma
(
65
and
younger)
100
$
1
Hospital
Admissions
 
Cardiovascular
(
adults,
over
64)
1,200
$
20
Emergency
Room
Visits
for
Asthma
(
65
and
younger)
930
<$
1
Asthma
Attacks
(
asthmatics,
all
ages)
79,260
B
1
Acute
bronchitis
(
children,
8­
12)
2,100
<$
1
Lower
respiratory
symptoms
(
children,
7­
14)
22,890
<$
1
Upper
respiratory
symptoms
(
asthmatic
children,
10­
11)
90,220
<$
5
Work
loss
days
(
adults,
18­
65)
178,650
$
20
Minor
restricted
activity
days
(
adults,
age
18­
65)
868,360
$
45
Other
PM­
related
health
effectsE
U
1
B
2
HAP­
related
health
effectsE
U
2
B
3
Total
Monetized
Health­
Related
Benefits
­
Using
a
3%
discount
rate
 
$
7,350+
BH
­
Using
a
7%
discount
rate
 
$
6,960+
BH
A
The
results
presented
in
this
table
reflect
the
outcome
of
the
combination
of
PM
and
SO
2
benefit
estimates
from
the
application
of
benefit
transfer
values
applied
in
the
phase
two
analysis.
See
Appendix
D
for
a
presentation
of
results
for
each
pollutant
independently.
B
Incidences
are
rounded
to
the
nearest
10
and
may
not
add
due
to
rounding.
Incidences
of
unquantified
endpoints
are
indicated
with
a
U.
C
Dollar
values
are
rounded
to
the
nearest
5
million
and
may
not
add
due
to
rounding.
The
value
of
unquantified
endpoints
are
indicated
with
a
B.
D
Note
that
the
estimated
value
for
PM­
related
premature
mortality
assumes
the
5
year
distributed
lag
structure
described
in
detail
in
the
Regulatory
Impact
Analysis
of
Heavy
Duty
Engine/
Diesel
Fuel
rule.
E
A
detailed
listing
of
unquantified
PM
and
HAP
related
health
effects
is
provided
in
Table
10­
16.
10­
43
10.6
Total
Benefits
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
Given
the
estimates
of
benefits
from
phases
one
and
two
of
this
analysis,
this
section
combines
those
results
to
present
the
estimate
of
total
benefits
of
the
NESHAP.
To
obtain
this
estimate,
we
aggregate
dollar
benefits
associated
with
each
of
the
effects
examined,
such
as
hospital
admissions,
into
a
total
benefits
estimate
assuming
that
none
of
the
included
health
and
welfare
effects
overlap.
The
benefits
associated
with
the
health
and
welfare
effects
is
the
sum
of
the
separate
effects
estimates.
Total
monetized
benefits
associated
with
the
MACT
floor
regulatory
option
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
are
listed
in
Table
10­
14,
along
with
a
breakdown
of
benefits
by
endpoint.
Table
10­
15
provides
total
annual
benefits
of
the
above
the
MACT
floor
option.

Again,
note
that
the
value
of
endpoints
known
to
be
affected
by
PM
that
we
are
not
able
to
monetize
are
assigned
a
placeholder
value
(
e.
g.,
B
1,
B
2,
etc.).
Unquantified
physical
effects
are
indicated
by
a
U.
The
estimate
of
total
benefits
is
thus
the
sum
of
the
monetized
benefits
and
a
constant,
B,
equal
to
the
sum
of
the
unmonetized
benefits,
B
1+
B
2+...+
B
n.

A
comparison
of
the
incidence
column
to
the
monetary
benefits
column
reveals
that
there
is
not
always
a
close
correspondence
between
the
number
of
incidences
avoided
for
a
given
endpoint
and
the
monetary
value
associated
with
that
endpoint.
For
example,
under
the
MACT
floor
option
there
are
over
75
times
more
asthma
attacks
than
premature
mortalities,
yet
these
asthma
attacks
account
for
only
a
very
small
fraction
of
total
monetized
benefits.
This
reflects
the
fact
that
many
of
the
less
severe
health
effects,
while
more
common,
are
valued
at
a
lower
level
than
the
more
severe
health
effects.
Also,
some
effects,
such
as
asthma
attacks,
are
valued
using
a
proxy
measure
of
WTP.
As
such
the
true
value
of
these
effects
may
be
higher
than
that
reported
in
Table
10­
14
and
Table
10­
15.

The
estimate
of
total
monetized
benefits
for
the
MACT
floor
is
$
16.3
billion
when
using
a
3
percent
discount
rate
(
or
$
15.4
billion
when
using
a
7
percent
discount
rate).
Of
this
total,
$
14.2
billion
(
or
$
13.4
billion)
are
the
benefits
of
reduced
premature
mortality
risk
from
PM
exposure.
Total
monetized
benefits
are
dominated
by
the
benefits
of
reduced
mortality
risk,
accounting
for
87
percent
of
total
monetized
benefits,
followed
by
chronic
bronchitis
totaling
$
1.8
billion,
which
represents
11
percent
of
the
total.
Following
chronic
bronchitis,
minor
restricted
activity
days
(
MRADs)
is
the
next
largest
quantified
benefit
category
totaling
$
100
million,
and
it
also
presents
the
category
with
the
largest
number
of
incidences
at
1,942,340
per
year.
MRADs
in
combination
with
lost
work
days
and
avoided
hospital
admissions
from
cardiovascular­
related
illness
account
for
$
140
million
of
total
benefits.
For
the
asthma­
related
endpoints,
we
note
that
the
MACT
floor
will
result
in
approximately
173,000
fewer
asthma
attacks,
more
than
2,000
fewer
visits
to
the
emergency
room
of
hospitals
for
asthma,
and
200
fewer
hospital
admissions
for
asthma­
related
effects.

Total
annual
benefits
of
the
above
the
MACT
floor
regulatory
option
are
$
17.2
billion
under
when
using
a
3
percent
discount
rate
(
or
$
16.3
billion
when
using
a
7
percent
discount
rate).
Similar
to
the
MACT
floor
results,
the
mortality
endpoint
accounts
for
the
majority
of
benefits
at
$
15.1
billion
(
or
$
14.2
billion),
followed
by
chronic
bronchitis
at
$
1.9
billion.
MRADs
account
for
$
100
million
in
benefits
and
2,064,854
fewer
incidences.
The
monetized
benefits
of
MRADs
combined
with
lost
work
days
and
cardiovascular­
related
hospital
admissions
account
for
$
180
million
of
benefits.
For
the
asthma­
related
endpoints,
we
note
that
the
above
the
MACT
floor
option
will
result
in
approximately
82,000
fewer
asthma
attacks,
more
than
2,000
fewer
visits
to
the
emergency
room
of
hospitals
for
asthma,
and
about
240
fewer
hospital
admissions
for
asthma­
related
effects.
10­
44
10­
45
Table
10­
14.
Total
Annual
Benefits
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
A
MACT
Floor
Regulatory
Option
Endpoint
Avoided
IncidenceB
(
cases/
year)
Monetary
BenefitsC
(
millions
1999$,
adjusted
for
growth
in
real
income)

Premature
mortalityD
(
long­
term
exposure,
adults,
30
and
over)
­
Using
a
3%
discount
rate
2,270
$
14,240
­
Using
a
7%
discount
rate
2,270
$
13,375
Chronic
bronchitis
(
adults,
26
and
over,
WTP
valuation)
5,100
$
1,835
Hospital
Admissions
 
Pneumonia
(
adults,
over
64)
1,100
$
15
Hospital
Admissions
 
COPD
(
adults,
64
and
over)
900
$
10
Hospital
Admissions
 
Asthma
(
65
and
younger)
230
<$
5
Hospital
Admissions
 
Cardiovascular
(
adults,
over
64)
2,660
$
50
Emergency
Room
Visits
for
Asthma
(
65
and
younger)
2,040
<$
1
Asthma
Attacks
(
asthmatics,
all
ages)
173,490
B1
Acute
bronchitis
(
children,
8­
12)
4,700
<$
1
Lower
respiratory
symptoms
(
children,
7­
14)
51,240
$
1
Upper
respiratory
symptoms
(
asthmatic
children,
10­
11)
196,860
$
5
Work
loss
days
(
adults,
18­
65)
398,670
$
40
Minor
restricted
activity
days
(
adults,
age
18­
65)
1,942,340
$
100
Other
PM­
related
health
effectsE
U1
B2
HAP­
related
health
effectsE
U2
B3
Total
Monetized
Health­
Related
BenefitsF
­
Using
a
3%
discount
rate
C
$
16,300+
B
H
­
Using
a
7%
discount
rate
C
$
15,430+
B
H
A
The
results
presented
in
this
table
include
all
emission
reductions
including
those
identified
for
specific
sources
included
in
the
Inventory
Database
included
in
the
Phase
One
analysis
and
the
remaining
reductions
not
included
in
the
Inventory
Database
included
in
the
Phase
Two
analysis
B
Incidences
are
rounded
to
the
nearest
10
and
may
not
add
due
to
rounding.
Incidences
of
unquantified
endpoints
are
indicated
with
a
U.
C
Dollar
values
are
rounded
to
the
nearest
5
million
and
may
not
add
due
to
rounding.
The
value
of
unquantified
endpoints
are
indicated
with
a
B.
D
The
estimated
value
for
PM­
related
premature
mortality
assumes
a
5­
year
distributed
lag
structure
and
discounted
at
a
3%
rate,
which
is
described
in
the
IAQR
benefit
anlaysis.
E
A
detailed
listing
of
unquantified
PM
and
HAP
related
health
effects
is
provided
in
Table
10­
16.
10­
46
Table
10­
15.
Total
Annual
Benefits
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
A
Above
the
MACT
Floor
Regulatory
Option
Endpoint
Avoided
IncidenceB
(
cases/
year)
Monetary
BenefitsC
(
millions
1999$,
adjusted
for
growth
in
real
income)

Premature
mortalityD
(
long­
term
exposure,
adults,
30
and
over)
­
Using
a
3%
discount
rate
2,410
$
15,135
­
Using
a
7%
discount
rate
2,410
$
14,220
Chronic
bronchitis
(
adults,
26
and
over,
WTP
valuation)
5,220
$
1,875
Hospital
Admissions
 
Pneumonia
(
adults,
over
64)
1,110
$
15
Hospital
Admissions
 
COPD
(
adults,
64
and
over)
910
$
10
Hospital
Admissions
 
Asthma
(
65
and
younger)
240
<$
5
Hospital
Admissions
 
Cardiovascular
(
adults,
over
64)
2,680
$
50
Emergency
Room
Visits
for
Asthma
(
65
and
younger)
2,080
<$
1
Asthma
Attacks
(
asthmatics,
all
ages)
82,130
B
1
Acute
bronchitis
(
children,
8­
12)
4,970
<$
1
Lower
respiratory
symptoms
(
children,
7­
14)
54,190
$
1
Upper
respiratory
symptoms
(
asthmatic
children,
10­
11)
200,590
$
5
Work
loss
days
(
adults,
18­
65)
275,710
$
30
Minor
restricted
activity
days
(
adults,
age
18­
65)
2,064,850
$
100
Other
PM­
related
health
effectsE
U
1
B
2
HAP­
related
health
effectsE
U
2
B
3
Total
Monetized
Health­
Related
Benefits
­
Using
a
3%
discount
rate
 
$
17,230+
BH
­
Using
a
7%
discount
rate
 
$
16,310+
BH
A
The
results
presented
in
this
table
include
all
emission
reductions
including
those
identified
for
specific
sources
included
in
the
Inventory
Database
and
the
remaining
reductions
not
included
in
the
Inventory
Database.
B
Incidences
are
rounded
to
the
nearest
10
and
may
not
add
due
to
rounding.
Incidences
of
unquantified
endpoints
are
indicated
with
a
U.
C
Dollar
values
are
rounded
to
the
nearest
5
million
and
may
not
add
due
to
rounding.
The
value
of
unquantified
endpoints
are
indicated
with
a
B.
D
The
estimated
value
for
PM­
related
premature
mortality
assumes
a
5­
year
distributed
lag
structure
and
discounted
at
a
3%
rate,
which
is
described
in
the
IAQR
benefit
anlaysis.
E
A
detailed
listing
of
unquantified
PM
and
HAP
related
health
effects
is
provided
in
Table
10­
16.
10­
47
10.7
Limitations
of
the
Analysis
10.7.1
Uncertainties
and
Assumptions
Significant
uncertainties
and
potential
biases
are
inherent
in
any
benefits
analysis
based
on
benefits
transfer
techniques.
This
analysis
uses
two
forms
of
benefit
transfer,
(
1)
the
transfer
of
dose­
response
functions
and
valuation
estimates
from
published
articles,
and
(
2)
the
transfer
of
value
per
ton
reduced
from
the
monetized
estimate
in
the
phase
one
analysis.
The
degree
of
uncertainty
and
bias
depends
on
how
divergent
the
reality
of
the
policy
situation
is
from
the
state
of
the
world
assumed
in
the
benefits
transfer
approaches.

For
this
analysis,
several
key
assumptions
may
lead
to
over
or
underestimation
of
benefits.
Table
10­
8
lists
these
assumptions,
and
where
possible
indicate
the
expected
direction
of
the
bias.
This
is
by
no
means
an
exhaustive
list,
but
captures
what
we
have
identified
as
key
assumptions.
In
addition
to
these
uncertainties
and
biases,
there
are
uncertainties
and
biases
embedded
in
the
original
benefits
analyses
from
which
the
transfer
values
were
generated.
Some
of
these
potential
biases
and
assumptions
are
discussed
in
the
preceding
sections.
For
a
full
discussion
of
these
uncertainties,
see
the
RIA
for
the
Heavy
Duty
Engine/
Diesel
Fuel
rule,
as
well
as
the
Section
812
report
to
congress
on
the
Benefits
and
Costs
of
the
Clean
Air
Act
1999
to
2010.
10­
48
Table
10­
16.
Significant
Uncertainties
and
Biases
Associated
with
the
Industrial
Boilers/
Process
Heaters
Benefit
Analysis
Assumption
Direction
of
BiasA
Omission
of
HAP
effects,
and
PM
effects
associated
with
visibility
and
materials
damage
benefit
categories
Downward
Estimated
emission
reductions
accurately
reflect
conditions
in
2005
Unknown
Future
meteorology
well­
represented
by
modeled
meteorology
Unknown
Benefits
from
source
studies
do
not
include
all
benefits
and
disbenefits
Unknown
Population,
demographics,
exposures,
and
air
quality
included
in
phase
one
analysis
is
representative
for
the
transfer
to
the
phase
two
analysis
Unknown
Linear
extrapolation
of
future
populations
Unknown
Accuracy
of
S­
R
Matrix
representativeness
of
secondary
PM
formation
chemistry
Unknown
A
A
downward
bias
is
an
indicator
that
total
benefits
are
underestimated.
An
upward
bias
is
an
indicator
that
total
benefits
are
overestimated.
In
several
cases,
the
direction
of
the
bias
is
unknown
and
can
potential
be
an
underestimate
or
an
overestimate
of
total
benefits.

10.7.2
Unquantified
Effects
In
addition
to
the
monetized
benefits
presented
in
the
above
tables,
it
is
important
to
recognize
that
many
benefit
categories
associated
with
HAP,
SO
2,
and
PM
reductions
are
not
quantified
or
monetized
for
this
analysis.
With
respect
to
the
benefits
of
reducing
exposure
to
HAPs,
EPA
has
developed
a
rudimentary
risk
analysis
focusing
only
on
cancer
risks.
As
discussed
above,
this
analysis
suggests
that
the
rule
would
reduce
cancer
incidence
by
roughly
tens
of
cases
per
year
if
it
were
implemented
at
all
affected
boiler
and
process
heater
facilities.
Placing
a
value
on
these
impacts
would
increase
the
economic
benefits
of
the
rule.
This
analysis
carries
significant
assumptions,
uncertainties,
and
limitations.
EPA
is
working
with
the
SAB
to
develop
better
methods
for
analyzing
the
cancer
and
non­
cancer
benefits
of
HAP
reductions.
EPA
will
include
a
monetized
estimate
of
the
benefits
of
reducing
HAP
emissions
with
the
analysis
for
the
final
rule
if
it
is
able
to
develop
better
methods
before
promulgation
of
this
rule.
Other
potentially
important
unquantified
benefit
categories
are
listed
in
Table
10­
17.
For
a
more
complete
discussion
of
unquantified
benefits
and
disbenefits,
see
the
RIA
for
the
Heavy
Duty
Engine/
Diesel
Fuel
rule.
10­
49
Table
10­
17.
Unquantified
Benefit
Categories
Unquantified
Benefit
Categories
Associated
with
HAPs
Unquantified
Benefit
Categories
Associated
with
PM
Health
Categories
Airway
responsiveness
Pulmonary
inflammation
Increased
susceptibility
to
respiratory
infection
Acute
inflammation
and
respiratory
cell
damage
Chronic
respiratory
damage/
Premature
aging
of
lungs
Emergency
room
visits
for
asthma
Changes
in
pulmonary
function
Morphological
changes
Altered
host
defense
mechanisms
Other
chronic
respiratory
disease
Emergency
room
visits
for
asthma
Emergency
room
visits
for
nonasthma
respiratory
and
cardiovascular
causes
Lower
and
upper
respiratory
symptoms
Acute
bronchitis
Shortness
of
breath
Increased
school
absence
rates
Welfare
Categories
Ecosystem
and
vegetation
effects
Damage
to
urban
ornamentals
(
e.
g.,
grass,
flowers,
shrubs,
and
trees
in
urban
areas)
Commercial
field
crops
Fruit
and
vegetable
crops
Reduced
yields
of
tree
seedlings,
commercial
and
non­
commercial
forests
Damage
to
ecosystems
Materials
damage
Materials
damage
Damage
to
ecosystems
(
e.
g.,
acid
sulfate
deposition)
Nitrates
in
drinking
water
Visibility
in
recreational
and
residential
areas
10­
50
10.8
Benefit­
Cost
Comparison
This
Regulatory
Impact
Analysis
(
RIA)
provides
cost,
economic
impact,
and
benefit
estimates
that
are
potentially
useful
for
evaluating
regulatory
alternatives
for
the
industrial
boilers
and
process
heaters
rule.
Benefit­
cost
analysis
provides
a
systematic
framework
for
assessing
and
comparing
such
alternatives.
According
to
economic
theory,
the
efficient
alternative
maximizes
net
benefits
to
society
(
i.
e.,
social
benefits
minus
social
costs).
However,
there
are
practical
limitations
for
the
comparison
of
benefits
to
costs
in
this
analysis.
In
particular,
the
inability
to
quantify
the
primary
HAP
related
benefits
of
the
rule,
as
well
as
the
inability
to
quantify
the
disbenefits
of
increased
electricity
generation
related
emissions
introduces
biases
into
our
estimate
of
benefits
that
make
comparison
with
costs
less
meaningful.
Executive
Order
12866
clearly
indicates
that
unquantifiable
or
nonmonetizable
categories
of
both
costs
and
benefits
should
not
be
ignored.
There
are
many
important
unquantified
and
unmonetized
costs
and
benefits
associated
with
reductions
in
PM
10
and
PM
2.5
emissions,
including
many
health
and
welfare
effects.
Potential
PM
benefit
categories
that
have
not
been
quantified
and
monetized
are
listed
in
Table
10­
18
of
this
chapter.
It
is
also
important
to
recall
that
this
analysis
is
only
of
the
monetizable
benefits
associated
with
PM
10
and
PM
2.5
reductions.
The
rule
is
designed
to
reduce
HAP
emissions.
By
achieving
these
HAP
reductions,
the
rule
reduces
the
risks
associated
with
exposures
to
those
chemicals,
including
the
risk
of
fatal
cancers.
It
is
likely
the
monetized
benefit
estimates
presented
in
this
chapter
are
expected
to
underestimate
total
benefits
of
the
rule.

In
addition
to
categories
that
cannot
be
included
in
the
calculated
net
benefits,
there
are
also
practical
limitations
for
the
comparison
of
benefits
to
costs
in
this
analysis,
which
have
been
discussed
throughout
this
chapter.
Several
specific
limitations
deserve
to
be
mentioned
again
here:

The
state
of
atmospheric
modeling
is
not
sufficiently
advanced
to
provide
a
workable
"
one
atmosphere"
model
capable
of
characterizing
ground­
level
pollutant
exposure
for
all
pollutants
of
interest
(
e.
g.,
ozone,
particulate
matter,
carbon
monoxide,
nitrogen
deposition,
etc).
Therefore,
the
EPA
must
employ
several
different
pollutant
models
to
characterize
the
effects
of
alternative
policies
on
relevant
pollutants.
Also,
not
all
atmospheric
models
have
been
widely
validated
against
actual
ambient
data.
In
particular,
since
a
broad­
scale
monitoring
network
is
in
the
early
stages
of
development
for
fine
particulate
matter
(
PM
2.5),
atmospheric
models
designed
to
capture
the
effects
of
alternative
policies
on
PM
2.5
are
not
fully
validated.
Additionally,
significant
shortcomings
exist
in
the
data
that
are
available
to
perform
these
analyses.
While
containing
identifiable
shortcomings
and
uncertainties,
EPA
believes
the
models
and
assumptions
used
in
the
analysis
are
reasonable
based
on
the
available
data
and
evidence.

Qualitative
and
more
detailed
discussions
of
the
above
and
other
uncertainties
and
limitations
are
included
in
detail
in
earlier
sections.
In
particular,
the
fact
that
only
half
of
the
sources
expected
to
be
affected
by
this
rule
are
actually
covered
in
these
analysis
contributes
to
the
uncertainty
of
the
benefits
estimates
(
as
well
those
of
the
costs
and
economic
impacts,
as
well).
Data
limitations
prevent
an
overall
quantitative
estimate
of
the
uncertainty
associated
with
final
estimates.
Nevertheless,
the
reader
should
keep
all
of
these
uncertainties
and
limitations
in
mind
when
reviewing
and
interpreting
the
results.

°
The
PM
benefit
estimates
do
not
include
the
monetary
value
of
several
known
PMrelated
welfare
effects,
including
recreational
and
residential
visibility,
household
soiling,
and
materials
damage.
10­
51
Nonetheless,
if
one
is
mindful
of
these
limitations,
the
relative
magnitude
of
the
benefitcost
comparison
presented
here
can
be
useful
information.
Thus,
this
section
summarizes
the
benefit
and
cost
estimates
that
are
potentially
useful
for
evaluating
the
efficiency
of
the
Industrial
Boilers
and
Process
Heaters
rule.

The
estimated
social
cost
of
implementing
the
NESHAP
at
the
MACT
floor
is
approximately
$
837
million
(
1999$)
in
third
year
after
issuance
of
this
rule.
The
monetized
benefits
of
the
MACT
floor
are
$
16.3
billion
when
using
a
3
percent
discount
rate
(
or
approximately
$
15.4
billion
when
using
a
7
percent
discount
rate).
Keeping
in
mind
that
no
primary
HAP­
related
benefits
are
quantified,
comparison
with
costs
indicates
that
our
estimate
of
monetized
benefits
of
ancillary
PM
10
and
SO
2
reductions
alone
exceed
the
compliance
costs
by
nearly
a
factor
of
20.

For
the
above
the
floor
option
(
also
called
"
Option
1A"
in
this
RIA),
the
estimated
social
cost
is
$
1.9
billion
(
1999$)
in
third
year
after
issuance
of
this
rule.
The
monetized
benefits
of
the
above
the
floor
option
are
$
17.2
billion
when
using
a
3
percent
discount
rate
(
or
approximately
$
16.3
billion
when
using
a
7
percent
discount
rate).
Thus,
our
estimate
of
benefits
of
the
above
the
floor
option
exceed
the
costs
by
a
factor
of
8.

It
is
also
useful
to
consider
the
incremental
costs
and
benefits
of
moving
from
the
MACT
floor
to
the
above
the
floor
option.
The
incremental
net
benefits
of
going
to
the
above
the
floor
option
from
the
NESHAP
(
the
MACT
floor
alternative)
is
­$
160
million
(
using
a
3
percent
discount
rate).
Hence,
the
final
rule
can
be
considered
a
more
efficient
alternative
to
society
than
the
above
the
floor
option
from
the
standpoint
of
maximizing
net
benefits.
Note
that
while
monetized
benefits
of
PM
10
and
SO
2
reductions
are
large
in
this
instance,
they
account
for
only
a
portion
of
the
benefits
of
this
rule.
Notable
omissions
include
all
benefits
of
HAPs
and
VOC
reductions,
including
reduced
cancer
incidences,
central
nervous
system
and
cardiovascular
system
effects,
and
ozone
related
benefits.
It
is
also
important
to
note
that
not
all
benefits
of
PM
10
reductions
have
been
monetized.
Categories
which
have
contributed
significantly
to
monetized
benefits
in
past
analyses
(
see
the
Heavy
Duty
Engine/
Diesel
Fuel
RIA)
include
recreational
and
residential
visibility
and
household
soiling.
Table
10­
17
lists
known
unquantified
benefits
associated
with
PM
and
HAP
reductions.
Table
10­
18
summarizes
the
costs,
benefits,
and
net
benefits
for
the
rule
and
the
above
the
floor
option,
and
shows
a
comparison
of
the
two
options.

We
did
not
attempt
to
estimate
welfare
benefits
associated
with
PM
reductions
for
this
rule
because
of
the
difficulty
in
developing
acceptable
benefit
transfer
values
for
these
effects.
The
SAB
has
recently
reviewed
existing
studies
valuing
improvements
in
residential
visibility
and
reductions
in
household
soiling
and
advised
that
these
studies
do
not
provide
an
adequate
basis
for
valuing
these
effects
in
cost­
benefit
analyses
(
EPA­
SAB­
COUNCIL­
ADV­
00­
002,
1999;
EPA­
SAB­
Council­
ADV­
003,
1998).
Reliable
methods
do
exist
for
valuing
visibility
improvements
in
Federal
Class
I
areas,
however,
the
benefits
transfer
method
outlined
above
does
not
allow
for
predictions
of
changes
in
visibility
at
specific
Class
I
areas.
These
predictions
are
necessary
to
estimate
Class
I
area
visibility
benefits.
As
such
we
have
left
this
potentially
important
endpoint
unquantified
for
this
analysis.
Given
the
proximity
of
some
sources
to
national
parks
in
the
Northwest
(
Mt.
Ranier,
Olympic,
and
Crater
Lake),
Northern
Rockies
(
Glacier),
and
Maine
(
Acadia),
these
omitted
benefits
may
be
significant.

As
we
characterize
the
comparison
of
benefits
to
costs,
it
should
be
recognized
that
the
Agency
believes
its
risk­
based
approach
to
regulating
HCl
and
Mn
emissions
from
industrial
boilers
will
reduce
the
cost
impact
of
this
final
MACT
standard
while
still
achieving
substantial
reduction
in
HCl
and
Mn
exposure
by
affected
populations.
In
offering
this
approach,
the
10­
52
Agency
recognizes
that
there
may
be
foregone
benefits
associated
in
excess
of
the
resulting
reduction
in
costs.
As
is
discussed
in
earlier
in
the
RIA,
the
Agency
is
not
able
to
quantify
the
benefits
of
HAP
reductions.
However,
the
reduction
in
HCl
and
Mn
benefits
are
not
anticipated
to
be
substantial
based
on
the
description
of
potential
effects
described
in
Chapter
9
of
this
RIA.
The
acid
gas
scrubbers
installed
by
industrial
boilers
not
only
reduce
HCl
emissions
but
also
sulfur
dioxide
(
SO
2)
emissions
simultaneously.
Reduction
of
SO
2
emissions
can
provide
large
monetized
benefits
since
it
is
a
precursor
of
fine
particulate
matter
(
PM
2.5),
a
pollutant
associated
with
a
high
degree
of
premature
mortality
in
exposed
populations.
The
fabric
filters
installed
by
industrial
boilers
not
only
reduce
Mn
emissions
but
also
PM
emissions
simultaneously.
Reduction
of
directly
emitted
coarse
particulate
matter
(
PM
10)
emissions
can
also
provide
large
monetized
benefits
as
well.
While
there
may
be
foregone
benefits
in
excess
of
the
cost
reduction,
it
should
be
recognized
that
the
estimated
monetized
benefits
from
implementation
of
the
final
rule
including
this
risk­
based
approach
are
still
much
larger
than
the
costs
($
14.5
billion
versus
$
690
million,
or
greater
by
a
factor
of
21).
In
addition,
it
should
be
recognized
that
the
reductions
not
achieved
due
to
industrial
boilers
taking
advantage
of
the
risk­
based
approach
could
be
obtained
in
a
more
efficient
manner
through
other
regulatory
programs
to
reduce
PM.
More
information
on
comparing
the
benefits
of
this
rule
to
its
costs
can
be
found
earlier
in
this
RIA
chapter.

The
Agency
recognizes
that
many
States
will
want
to
reduce
SO
2
and
PM
emissions
from
current
levels
in
order
to
meet
requirements
associated
with
the
proposed
Interstate
Air
Quality
Rule
(
IAQR)
and
PM
National
Ambient
Air
Quality
Standards
(
NAAQS).
It
may
be
necessary
for
States
to
require
reductions
of
SO
2
in
higher
amounts
than
can
be
obtained
from
the
venturi
scrubbers
or
PM
reductions
from
fabric
filters
that
would
be
required
to
meet
this
final
MACT
standard.
The
Agency
understands
that
it
would
be
difficult
for
States
to
justify
requiring
industrial
boilers
to
dismantle
scrubbers
and
fabric
filters
installed
to
comply
with
the
MACT
standard
in
order
to
install
more
expensive
ones
that
meet
potentially
more
stringent
SO
2
and
PM
control
requirements
associated
with
implementation
of
the
IAQR
and
PM
NAAQS.
The
Agency
will
work
carefully
with
States
to
help
them
minimize
the
potential
"
stranded
investment"
by
industrial
boiler
owners
in
venturi
scrubbers
that
may
result
as
State
agencies
develop
SIPs
to
meet
the
IAQR
and
PM
NAAQS.
10­
53
Table
10­
18.
Annual
Net
Benefits
of
the
Industrial
Boilers
and
Process
Heaters
NESHAP
in
2005
MACT
Floor
(
Million
1999$)
Above
the
MACT
Floor
(
Million
1999$)

Social
CostsB
$
837
$
1,923
Social
BenefitsB,
C,
D:

HAP­
related
health
and
welfare
benefits
Not
monetized
Not
monetized
PM­
related
welfare
benefits
Not
monetized
Not
monetized
SO2­
and
PM­
related
health
benefits:

­
Using
3%
Discount
Rate
­
Using
7%
Discount
Rate
$
16,300
+
B
$
15,430
+
B
$
17,230
+
B
$
16,310
+
B
Net
Benefits
(
Benefits
­
Costs)
C,
D:

­
Using
3%
Discount
Rate
­
Using
7%
Discount
Rate
$
15,465
$
14,595
$
15,305
+
B
$
14,385
+
B
A
All
costs
and
benefits
are
rounded
to
the
nearest
$
5
million.
Thus,
figures
presented
in
this
table
may
not
exactly
equal
benefit
and
cost
numbers
presented
in
earlier
sections
of
the
chapter.
B
Note
that
costs
are
the
total
costs
of
reducing
all
pollutants,
including
HAPs
as
well
as
SO
2
and
PM
10.
Benefits
in
this
table
are
associated
only
with
PM
and
SO
2
reductions.
C
Not
all
possible
benefits
or
disbenefits
are
quantified
and
monetized
in
this
analysis.
Potential
benefit
categories
that
have
not
been
quantified
and
monetized
are
listed
in
Table
8­
13.
B
is
the
sum
of
all
unquantified
benefits
and
disbenefits.
D
Monetized
benefits
are
presented
using
two
different
discount
rates.
Results
calculated
using
3
percent
discount
rate
are
recommended
by
EPA's
Guidelines
for
Preparing
Economic
Analyses
(
U.
S.
EPA,
2000a).
Results
calculated
using
7
percent
discount
rate
are
recommended
by
OMB
Circular
A­
94
(
OMB,
1992).
10­
54
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58
APPENDIX
A:
ECONOMIC
MODEL
OF
MARKETS
AFFECTED
BY
THE
BOILERS
AND
PROCESS
HEATERS
MACT
The
primary
purpose
of
the
EIA
for
the
final
rule
is
to
describe
and
quantify
the
economic
impacts
associated
with
the
rule.
The
Agency
used
a
basic
framework
that
is
consistent
with
economic
theory
and
the
analyses
performed
for
other
rules
to
develop
estimates
of
these
impacts.
This
approach
employs
standard
microeconomic
concepts
to
model
behavioral
responses
expected
to
occur
with
regulation.
This
appendix
describes
the
spreadsheet
model
in
more
detail
and
discusses
how
the
Agency

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

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

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

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

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

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

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

Supply
and
Demand
Elasticities
 
The
supply
and
demand
elasticity
values
used
in
the
market
model
are
reported
in
Table
5­
2
of
this
report.
Given
the
uncertainties
regarding
these
parameters,
EPA
also
conducted
several
sensitivity
analyses
and
report
these
results
in
Appendix
B.
A.
2
Multi­
Market
Model
The
model
includes
four
energy
markets
(
coal,
electricity,
natural
gas,
and
petroleum)
and
24
goods
and
service
markets.
The
following
sections
describe
model
equations
the
Agency
developed
to
characterize
these
markets
and
estimate
welfare
changes
resulting
from
the
rule.

A.
1.1
Supply
Side
Modeling
EPA
estimated
the
change
in
quantity
supplied
as
follows:
A­
1
 
qS

q
0
S

S

 
p

c

n

j

1
 
j 
p
j
p
0
(
A.
1)

 
PS

q
1

(
 
p

c

n

j

1
 
j 
p
j)

0.5

 
q

(
 
p

c

n

j

1
 
j 
p
j)
(
A.
2)

Q
Dj

n

i

1
q
Dji
,
(
A.
3)

 
q
D
j

q
0
D
j

 
D
j

 
p
j
p
j0
(
A.
4)

BTU
ji1

BTU
ji
q
i0

FSW

q
i1
(
A.
5)
where
is
the
baseline
quantity,
is
the
domestic
supply
elasticity,
the
term
q
S
0

S
 
p

c

n

j

1
 
j 
p
j
is
the
change
in
the
producer's
net
price,
and
p
0
is
the
baseline
price.
The
change
in
net
price
is
composed
of
the
change
in
baseline
price
resulting
from
the
regulation,
the
direct
shift
in
the
supply
function
resulting
from
compliance
costs,
and
the
indirect
shift
in
the
supply
function
resulting
from
changes
in
input
prices
in
energy
market
(
j).
The
fuel
share
is
allowed
to
vary
using
a
fuel
switching
rule
relying
on
cross­
price
elasticities
of
demand
between
energy
sources.

A.
1.1.2
Producer
Welfare
Measurement
EPA
approximated
the
change
in
producer
surplus
with
the
following
equation:
Increased
control
costs,
higher
energy
input
costs,
and
output
declines
have
a
negative
effect
on
domestic
producer
surplus.
However,
these
losses
are
mitigated
to
some
degree
as
a
result
of
higher
market
prices.
A.
1.2
Energy
Demand
Side
Modeling
Market
demand
in
the
energy
markets
is
expressed
as
the
sum
of
the
energy,
residential,
agriculture,
manufacturing,
mining,
commercial,
and
transportation
sectors:

where
j
indexes
the
energy
market
and
i
indexes
the
consuming
sector.
The
change
in
residential
quantity
demanded
of
energy
market
j
can
be
approximated
as
follows:

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

where
BTU
is
demand
for
energy
market
j
from
sector
i,
q
is
sector
i's
output,
and
FSW
is
a
factor
generated
by
the
fuel
switching
algorithm.
The
subscripts
0
and
1
represent
baseline
and
with
regulation
A­
2
 
q
D
i

q
0
D
i

 
D
i

 
p
i
p
i0
(
A.
6)

 
CS


q
1

 
p

0.5

 
q

 
p
(
A.
7)
conditions,
respectively.
A.
1.3
Agriculture,
Manufacturing,
Mining,
Commercial,
and
Transportation
Demand
Side
Modeling
The
change
in
quantity
demanded
in
these
markets
can
be
approximated
as
follows:

where
is
baseline
output,
 D
is
the
demand
elasticity
of
the
respective
market
(
i)
and
( 
p
i)
is
the
q
Di
0
change
in
the
market
price.
The
change
in
consumer
surplus
in
markets
is
approximated
as
follows:
As
shown,
higher
market
prices
and
reduced
consumption
lead
to
welfare
losses
for
consumers.

A.
2
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.
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:
1.
Impose
the
control
costs
on
affected
supply
segments,
thereby
affecting
their
supply
decisions.

2.
Recalculate
the
market
supply
in
each
market.
Excess
demand
currently
exists.

3.
Determine
the
new
prices
via
a
price
revision
rule.

4.
Recalculate
market
supply
with
new
prices,
accounting
for
fuel
switching
choices
associated
with
new
energy
prices.

5.
Compute
market
demand
in
each
market.

6.
Compare
supply
and
demand
in
each
markets.
If
equilibrium
conditions
are
not
satisfied,
go
to
Step
3,
resulting
in
a
new
set
of
market
prices.
Repeat
until
equilibrium
conditions
are
satisfied
(
i.
e.,
the
ratio
of
supply
to
demand
is
arbitrarily
close
to
one).
B­
3
APPENDIX
B
ASSUMPTIONS
AND
SENSITIVITY
ANALYSIS
In
developing
the
economic
model
to
estimate
the
impacts
of
the
industrial/
commercial/
institutional
boilers
and
process
heaters
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
goods
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:
Market
Supply
and
Demand
Elasticity
Uncertainty
Explanation:
The
goods
and
service
markets
are
modeled
at
the
two
or
three­
digit
NAICS
code
level
to
operationalize
the
economic
model.
Because
of
the
high
level
of
aggregation,
only
limited
data
on
elasticities
of
supply
and
demand
estimates
are
available.
However,
these
elasticities
strongly
influence
the
distribution
of
economic
impacts
between
producers
and
consumers.
Sensitivity
Analysis:
Tables
B­
1a
and
Table
B­
1b
show
how
the
economic
impact
estimates
vary
as
the
supply
and
demand
elasticities
for
goods
and
services
change
by
25
percent.
B­
4
Assumption:
Cross­
price
elasticities
of
demand
for
fuels
are
based
on
2015
NEMS
projections.
Explanation:
Cross­
and
own­
price
elasticities
of
demand
from
NEMS
were
used
to
capture
fuel
switching
in
the
manufacturing
sectors
in
the
economic
model.
As
shown
in
Table
5­
2,
allowing
manufacturers
to
switch
fuels
in
response
to
changes
in
relative
energy
prices
decreases
the
change
in
social
welfare
by
approximately
10
percent.
However,
the
NEMS
projection
reflects
aggregate
behavioral
responses
in
the
year
2015.
Because
this
is
a
longer
window
of
analysis
compared
to
the
baseline
year
2005,
this
analysis
may
overestimate
firms'
ability
to
switch
fuels
in
the
short
run.

Sensitivity
Analysis:
Table
B­
2
shows
how
the
economic
impact
estimates
vary
as
the
own­
and
crossprice
elasticities
used
in
the
EIA
are
reduced
by
50
percent
and
75
percent.
Table
B­
1a.
Sensitivity
Analysis:
Supply
and
Demand
Elasticities
in
the
Goods
and
Services
Markets
Change
Supply
Demand
Constant
25%
Decrease
Elasticities
Reported
in
Section
6
25%
Increase
Change
in
consumer
surplus
 
367.8
 
414.3
 
450.5
Change
in
producer
surplus
 
495.2
 
448.7
 
412.4
Change
in
social
welfare
 
862.9
 
862.9
 
862.9
Table
B­
1b.
Sensitivity
Analysis:
Supply
and
Demand
Elasticities
in
the
Goods
and
Services
Markets
Supply
Constant
Demand
Change
25%
Decrease
Elasticities
Reported
in
Section
6
25%
Increase
Change
in
consumer
surplus
 
462.7
 
414.3
 
364.4
Change
in
producer
surplus
 
400.2
 
448.7
 
498.5
Change
in
social
welfare
 
862.9
 
862.9
 
862.9
B­
1
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:
The
elasticity
of
supply
in
the
electricity
market
for
existing
sources
is
approximately
0.75.
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
3
shows
how
the
economic
impact
estimates
vary
as
the
elasticity
of
supply
in
the
electricity
markets
varies.
Table
B­
2.
Sensitivity
Analysis:
Own­
and
Cross­
Price
Elasticities
Used
to
Model
Fuel
Switching
Fuel
Price
Elasticities
Presented
in
Table
5­
2
Reduced
by
50
Percent
Reduced
by
75
Percent
Change
in
consumer
surplus
 
414.3
 
414.6
 
414.9
Change
in
producer
surplus
 
448.7
 
448.4
 
448.0
Change
in
social
welfare
 
862.9
 
862.9
 
862.9
Table
B­
3.
Sensitivity
Analysis:
Elasticity
of
Supply
in
the
Electricity
Markets
ES
=
0.5
ES
=
0.75
ES
=
1.0
Change
in
consumer
surplus
 
405.0
 
414.3
 
419.6
Change
in
producer
surplus
 
457.9
 
448.7
 
443.4
Change
in
social
welfare
 
862.9
 
862.9
 
862.9
C­
2
Appendix
C
Air
Quality
Changes
for
the
Above­
the­
Floor
Option
(
Option
1A)

Table
C­
1
summarizes
the
baseline
PM
10,
PM
2.5,
and
SO
2
emissions
and
emission
reductions
nationwide
for
the
MACT
floor
option.
The
air
quality
analysis
presumes
no
change
in
volatile
organic
compound
(
VOC),
nitrogen
oxides
(
NOx),
carbon
monoxide
(
CO),
and
ammonia
(
NH
3)
emissions.
Hence,
the
baseline
emissions
for
these
pollutants
are
not
shown
in
this
table.
For
these
baseline
emissions,
refer
to
Pechan,
2001.

Table
C­
1.
Summary
of
Nationwide
Baseline
Emissions
and
Emission
Reductionsa
for
the
MACT
floor
(
in
tons/
year),
Existing
Units
Onlyb,
c
in
2005
Pollutant
Source
Type
1996
Baseline
Emissions
(
tons/
year)
Unknow
n
Affected
Units
Option
1A
Emission
Reductions
Known
Unknown
Total
Affected
Affected
Affected
Units
Units
Units
SO
2
Point
3,745,790
30,394
95,361
41,372
136,733
Area
1,397,425
Motor
Vehicle
302,938
Nonroad
840,167
PM
10
Point
1,167,995
298,109
313,947
255,282
569,229
C­
3
Area
30,771,607
Motor
Vehicle
294,764
Nonroad
463,579
PM
2.5
Point
576,022
84,125
94,565
76,894
171,459
Area
6,675,777
Motor
Vehicle
230,684
Nonroad
410,334
As
mentioned
in
Chapter
8
of
this
RIA,
we
conducted
no
air
quality
modeling
for
the
HAP
or
the
mercury
emission
reductions
that
occur
from
the
potential
implementation
of
Option
1A.
These
emission
reductions
are
listed
in
Table
C­
2.
For
a
description
of
how
HAP
emissions
and
emission
factors
are
estimated
for
this
rule,
refer
to
the
emission
factors/
emissions
estimates
memo
in
the
public
docket
(
ERG,
2002).

Table
C­
2.
HAP
Emission
Reductions
for
Option
1A,
2005
Existing
Sources
Only
Pollutant
Emission
Reductions
(
tons/
year)

Option
1A
HCl
40,406
Pb
105
Hg
2.2
Non­
mercury
metalsa
1,135
Selected
inorganicsb
18,250
Total
HAP
reductions
59,190
aNon­
mercury
metals
include:
arsenic,
beryllium,
cadmium,
chromium,
manganese,
and
nickel.
bSelected
inorganics
include:
chlorine,
hydrofluoric
acid,
and
phosphorus.

Table
C­
3
provides
a
summary
of
the
predicted
ambient
PM
10
and
PM
2.5
concentrations
from
the
S­
R
matrix
for
the
2005
baseline
and
changes
associated
with
Option
1A,
the
above­
the­
MACT
floor
examined
in
this
RIA.
The
results
indicate
that
the
predicted
change
in
PM
concentrations
is
composed
almost
entirely
of
reductions
in
fine
particulates
(
PM
2.5)
with
little
or
no
reduction
in
coarse
particles
(
PM
10
less
PM
2.5).
Therefore,
the
observed
changes
in
PM
10
are
composed
primarily
of
changes
in
PM
2.5.
These
results
are
quite
similar
to
those
for
the
final
rule
C­
1
(
MACT
floor
option).
In
addition
to
the
standard
frequency
statistics
(
e.
g.,
minimum,
maximum,
average,
median),
Table
C­
3
provides
the
population­
weighted
average
which
better
reflects
the
baseline
levels
and
predicted
changes
for
more
populated
areas
of
the
nation.
This
measure,
therefore,
will
better
reflect
the
potential
benefits
of
these
predicted
changes
through
exposure
changes
to
these
populations.
As
shown,
the
average
annual
mean
concentrations
of
PM
2.5
across
all
U.
S.
grid­
cells
declines
by
roughly
0.9
percent,
or
0.10

g/
m3.
The
population­
weighted
average
mean
concentration
declined
by
0.9
percent,
or
0.12

g/
m3,
which
is
slightly
larger
in
absolute
terms
than
the
spatial
average.
This
indicates
that
the
above­
the­
floor
option
generates
slightly
greater
absolute
air
quality
improvements
in
more
populated,
urban
areas
than
in
less
populated,
rural
areas.

Table
C­
3.
Summary
of
2005
Base
Case
PM
Air
Quality
and
Changes
Due
to
MACT
Above­
the­
Floor
Option:
Industrial
Boiler/
Process
Heater
Source
Categories
Statistic
2005
Baseline
Changea
Percent
Change
PM
10
Minimum
Annual
Mean
(

g/
m3)
b
6.09
­
0.08
­
1.3%

Maximum
Annual
Mean
(

g/
m3)
b
69.30
­
0.03
­
0.1%

Average
Annual
Mean
(

g/
m3)
22.68
­
0.36
­
1.6%

Median
Annual
Mean
(

g/
m3)
21.84
­
0.43
­
1.9%

Population­
Weighted
Average
Annual
Mean
(

g/
m3)
c
28.79
­
0.38
­
1.3%

PM
2.5
Minimum
Annual
Mean
(

g/
m3)
b
0.74
­
0.01
0.0%

Maximum
Annual
Mean
(

g/
m3)
b
30.35
­
0.77
­
2.5%

Average
Annual
Mean
(

g/
m3)
11.15
­
0.10
­
0.9%

Median
Annual
Mean
(

g/
m3)
11.11
­
0.13
­
1.2%

Population­
Weighted
Average
Annual
Mean
(

g/
m3)
c
13.50
­
0.12
­
0.9%

aThe
change
is
defined
as
the
control
case
value
minus
the
baseline
value.
b
The
baseline
minimum
(
maximum)
is
the
value
for
the
populated
county
with
the
lowest
(
highest)
annual
average.
The
change
relative
to
the
baseline
is
the
observed
change
for
the
populated
county
with
the
lowest
(
highest)
annual
average
in
the
baseline.
c
Calculated
by
summing
the
product
of
the
projected
2005
county
population
and
the
estimated
2005
PM
concentration
for
that
county,
and
then
dividing
by
the
total
population
in
the
48
contiguous
States.

Table
C­
4
provides
information
on
the
2005
populations
that
will
experience
improved
PM
air
quality
under
the
above­
the­
floor
option.
There
are
also
fairly
significant
populations
that
live
in
areas
with
meaningful
reductions
in
annual
mean
PM
2.5
concentrations
resulting
from
the
above­
the­
floor
option,
though
the
increment
of
reduction
between
the
above­
the­
floor
option
and
the
MACT
floor
option
is
quite
small.
As
shown,
about
1
percent
of
the
2005
continental
U.
S.
population
are
predicted
to
experience
reductions
of
greater
than
1

g/
m3.
Furthermore,
about
4
percent
of
the
2005
U.
S.
population
will
benefit
from
reductions
in
annual
mean
PM
2.5
C­
2
concentrations
of
greater
than
0.5

g/
m3
and
about
38
percent
will
live
in
areas
with
reductions
of
greater
than
0.1

g/
m3.

Table
C­
4.
Distribution
of
PM2.5
Air
Quality
Improvements
Over
2005
Population
Due
to
MACT
Above­
the­
Floor
Option:
Industrial
Boiler/
Process
Heater
Source
Categories
2005
Population
Change
in
Annual
Mean
PM
2.5
Concentrations
(

g/
m3)
Number
(
millions)
Percent
(%)

 
PM
2.5
Conc
=
0
34.3
12.1%

0
>
 
PM
2.5
Conc

0.05
86.4
30.5%

0.05
>
 
PM
2.5
Conc

0.1
56.5
19.9%

0.1
>
 
PM
2.5
Conc

0.25
77.2
27.3%

0.25
>
 
PM
2.5
Conc

0.5
18.1
6.4%

0.5
>
 
PM
2.5
Conc

1.0
8.6
3.0%

1.0
>
 
PM
2.5
Conc

2.0
2.0
0.7%

 
PM
2.5
Conc
>
2.0
0.2
0.1%
a
The
change
is
defined
as
the
control
case
value
minus
the
baseline
value.
C­
3
Table
C­
5.
Summary
of
Absolute
and
Relative
Changes
in
PM
Air
Quality
Due
to
MACT
Above­
the­
Floor
Option:
Industrial
Boiler/
Process
Heater
Source
Categories
Statistic
PM
10
Annual
Mean
PM
2.5
Annual
Mean
Absolute
Change
from
2005
Baseline
(

g/
m3)
a
Minimum
0.00
0.00
Maximum
­
19.20
­
6.09
Average
­
0.36
­
0.10
Median
­
0.20
­
0.07
Population­
Weighted
Average
c
­
0.38
­
0.12
Relative
Change
from
2005
Baseline
(%)
b
Minimum
0.00%
0.00%

Maximum
­
58.34%
­
38.47%

Average
­
1.52%
­
0.85%

Median
­
0.94%
­
0.65%

Population­
Weighted
Average
c
­
1.46%
­
0.87%

a
The
absolute
change
is
defined
as
the
control
case
value
minus
the
baseline
value
for
each
county.

b
The
relative
change
is
defined
as
the
absolute
change
divided
by
the
baseline
value,
or
the
percentage
change,
for
each
county.
The
information
reported
in
this
section
does
not
necessarily
reflect
the
same
county
as
is
portrayed
in
the
absolute
change
section.

c
Calculated
by
summing
the
product
of
the
projected
2005
county
population
and
the
estimated
2005
county
PM
absolute/
relative
measure
of
change,
and
then
dividing
by
the
total
population
in
the
48
contiguous
states.

Table
C­
5
provides
additional
insights
on
the
changes
in
PM
air
quality
resulting
from
the
above­
the­
floor
option.
The
information
presented
previously
in
Table
8­
6
illustrated
the
absolute
and
relative
changes
for
different
points
along
the
distribution
of
baseline
2005
PM
concentration
levels,
e.
g.,
the
change
reflects
the
lowering
of
the
minimum
predicted
baseline
concentration
rather
than
the
minimum
predicted
change
for
2005.
The
latter
is
the
focus
of
Table
C­
5
as
it
presents
the
distribution
of
predicted
changes
in
both
absolute
terms
(
i.
e.,

g/
m3)
and
relative
terms
(
i.
e.,
percent)
across
individual
grid­
cells.
Therefore,
it
provide
more
information
on
the
range
of
predicted
changes
that
as
shown,
the
absolute
reduction
in
annual
mean
PM
10
concentration
ranged
from
a
low
of
0.00

g/
m3
to
a
high
of
19.20

g/
m3,
while
the
relative
reduction
ranged
from
a
low
of
0.0
percent
to
a
high
of
58.5
percent.
Alternatively,
for
mean
PM
2.5,
the
absolute
reduction
ranged
from
0.00
to
6.09

g/
m3,
while
the
relative
reduction
ranged
from
0.0
to
38.5
percent.
C­
4
Comparison
of
Air
Quality
Changes
for
the
MACT
Floor
and
Above
The
Floor
Options
The
increment
in
air
quality
improvements
between
the
above
the
floor
option
and
the
MACT
floor
option
(
the
final
rule)
in
2005
is
quite
small
as
seen
in
a
comparison
between
the
results
for
each
option.
There
is
only
a
0.01

g/
m3
decrease
in
nationwide
average
annual
mean
PM
2.5
concentration
for
the
above­
the­
floor
option
compared
to
the
MACT
floor
option,
and
a
0.04

g/
m3
decrease
in
average
annual
mean
PM
10
concentration.
In
addition,
the
differences
in
the
nationwide
population­
weighted
average
annual
mean
are
0.02

g/
m3
for
PM
2.5
and
0.05

g/
m3
for
PM
10
concentrations.
Hence,
the
difference
in
air
quality
improvement
between
the
options
is
small.
The
improvements
in
air
quality
is
one
possible
component
of
choosing
between
a
MACT
floor
option
and
an
above
the
floor
option.

Visibility
Improvements
Table
C­
6
provides
the
distribution
of
visibility
improvements
across
the
2005
U.
S.
population
resulting
from
the
above­
the­
floor
MACT
option.
The
majority
of
the
2005
U.
S.
population
live
in
areas
with
predicted
improvement
in
annual
average
visibility
of
between
0
to
0.1
deciviews.
As
shown,
5
percent
of
the
2005
U.
S.
population
are
predicted
to
experience
improved
annual
average
visibility
of
greater
than
0.25
deciviews.
Furthermore,
just
over
80
percent
of
the
2005
U.
S.
population
will
benefit
from
an
improvement
in
visibility,
i.
e.,
change
in
deciview
greater
than
zero.

Table
C­
6.
Distribution
of
Populations
Experiencing
Visibility
Improvements
in
2005
Due
to
MACT
Above­
the­
Floor
Option:
Industrial
Boiler/
Process
Heater
Source
Categories
2005
Population
Improvements
in
Visibility
a
(
annual
average
deciviews)
Number
(
millions)
Percent
(%)

 
Deciview
=
0
50.2
17.7%

0
>
 
Deciview

0.05
152.5
53.9%

0.05
>
 
Deciview

0.1
55.8
19.7%

0.1
>
 
Deciview

0.15
10.5
3.7%

0.15
>
 
Deciview

0.25
10.2
3.6%

0.25
>
 
Deciview

0.5
2.8
1.0%

 
Deciview
>
0.5
1.1
0.4%

aThe
change
is
defined
as
the
MACT
Above­
the­
Floor
control
case
deciview
level
minus
the
base
case
deciview
level.

Residential
Visibility
For
the
above­
the­
floor
option,
the
air
quality
modeling
results
predict
slightly
greater
improvements
in
visibility
through
the
country
than
for
the
MACT
floor
option.
In
Table
C­
7,
we
summarize
residential
visibility
improvements
across
the
Eastern
and
Western
U.
S.
in
2005
that
result
C­
5
from
the
above­
the­
floor
MACT
option.
The
baseline
annual
average
visibility
for
all
U.
S.
counties
in
the
contiguous
48
States
is
14.8
deciviews.
The
mean
improvement
across
these
U.
S.
counties
is
0.05
deciviews,
or
almost
0.2
percent.
In
urban
areas
with
a
population
of
250,000
or
more
(
i.
e.,
819
out
of
3,080
counties),
the
mean
improvement
in
annual
visibility
was
0.06
deciviews
and
ranged
from
0.01
to
0.98
deciviews.
In
rural
areas
(
i.
e.,
2,261
counties),
the
mean
improvement
in
visibility
was
0.05
deciviews
in
2005
and
ranged
from
0.01
to
0.52
deciviews.

On
average,
the
Eastern
U.
S.
experienced
larger
absolute
and
relative
improvements
in
visibility
than
the
Western
U.
S.
from
the
industrial
boilers
and
process
heaters
reductions.
In
Eastern
U.
S.,
the
mean
improvement
was
0.06
deciviews
from
an
average
baseline
of
22
deciviews.
Western
counties
experienced
a
mean
improvement
of
0.01
deciviews
from
an
average
baseline
of
17.82
deciviews
projected
in
2005.
Overall,
the
data
suggest
that
the
rule
provides
slight
improvements
in
visibility
for
2005.

Table
C­
7.
Summary
of
2005
Baseline
Visibility
and
Changes
by
Region
Due
to
MACT
Above­
the­
Floor
Option:
Residential(
Annual
Average
Deciviews)

Regionsa
2005
Baseline
Changeb
Percent
Change
Eastern
U.
S.
22.00
­
0.06
­
0.2%

Urban
22.95
­
0.07
­
0.3%

Rural
21.62
­
0.06
­
0.2%

Western
U.
S.
17.82
­
0.01
­
0.1%

Urban
19.19
­
0.01
­
0.1%

Rural
17.55
­
0.01
­
0.1%

National,
all
counties
21.19
­
0.05
­
0.2%

Urban
22.49
­
0.06
­
0.3%

Rural
20.72
­
0.04
­
0.2%
a
Eastern
and
Western
regions
are
separated
by
100
degrees
West
longitude.
Background
visibility
conditions
differ
by
region.
b
An
improvement
in
visibility
is
a
decrease
in
deciview
value.
The
change
is
defined
as
the
MACT
Above­
the­
Floor
control
case
deciview
level
minus
the
baseline
deciview
level
Recreational
Visibility
In
Table
C­
8,
we
summarize
recreational
visibility
improvements
resulting
from
the
Above­
the­
Floor
MACT
option
in
2005
for
Federal
Class
I
areas
by
region.
These
recreational
visibility
regions
are
the
same
ones
as
those
in
Figure
8­
1
in
Chapter
8
of
the
RIA.
As
shown,
the
national
improvement
in
visibility
for
these
areas
is
0.3
percent,
or
0.05
deciviews.
Predicted
relative
visibility
improvements
are
the
largest
in
the
Southeast
(
0.3%)
and
Northeast/
Midwest
(
0.2%).
These
improvements
are
only
slightly
greater
than
those
estimated
for
the
MACT
floor
option.
California
was
predicted
to
have
no
visibility
improvements
in
Class
I
areas
within
that
state.
C­
6
Table
C­
8.
Summary
of
2005
Baseline
Visibility
and
Changes
by
Region
Due
to
MACT
Above­
the­
Floor
Option:
Recreational
(
Annual
Average
Deciviews)

Class
I
Visibility
Regionsa
2005
Baseline
Changeb
Percent
Change
Southeast
21.49
­
0.07
­
0.3%

Southwest
17.18
­
0.01
­
0.1%

California
19.86
0.00
0.0%

Northeast/
Midwest
20.64
­
0.06
­
0.2%

Rocky
Mountain
17.29
­
0.02
­
0.1%

Northwest
20.62
­
0.03
­
0.1%

National
Average
(
unweighted)
19.17
­
0.05
­
0.3%

a
Regions
are
pictured
in
Figure
8­
1
and
are
defined
in
the
technical
support
document
for
the
air
quality
analysis.
b
An
improvement
in
visibility
is
a
decrease
in
deciview
value.
The
change
is
defined
as
the
MACT
Above­
the­
Floor
control
case
deciview
level
minus
the
baseline
deciview
level.
C­
7
APPENDIX
D:
Derivation
of
Quantified
Benefits
C­
8
Appendix
D:
Derivation
of
Quantified
Benefits
As
Chapter
10
of
this
RIA
explains,
the
benefit
analysis
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
entails
two
phases
of
analysis.
These
results
reflect
the
use
of
two
different
discount
rates
to
value
reduced
incidences
of
mortality;
a
3%
rate
which
is
recommended
by
EPA's
Guidelines
for
Preparing
Economic
Analyses
(
US
EPA,
2000a),
and
7%
which
is
recommended
by
OMB
Circular
A­
94
(
OMB,
1992).
In
phase
one,
we
modeled
approximately
50
percent
of
the
estimated
emission
reductions
of
SO2
and
PM
in
an
air
quality
model
(
the
SR
Matrix)
and
a
benefit
valuation
model
(
the
CAPMS
model).
This
appendix
provides
tables
that
detail
the
steps
necessary
to
derive
the
total
benefits
of
the
NESHAP.

Tables
D­
1
to
D­
4
show
the
benefits
estimation
for
the
MACT
floor.
Table
D­
1(
a)
shows
the
results
of
the
phase
one
analysis
when
we
modeled
SO2
emission
reductions
alone.
Given
a
total
benefit
estimate
of
$
1.7
billion
from
the
assessment
of
benefits
for
85,542
tons
of
SO2
reduced
out
of
a
total
estimated
reduction
of
112,936
tons,
we
then
calculate
a
coefficient
for
each
benefit
endpoint
to
derive
benefit
transfer
values
for
(
1)
incidence
per
ton
reduced,
and
(
2)
benefit
per
ton
reduced.

Table
D­
1(
b)
shows
the
results
of
phase
two
of
the
analysis
associated
with
SO2
reductions.
Using
the
benefit
transfer
values
for
incidence
and
value,
we
calculate
the
approximate
benefits
of
the
remaining
30,394
tons
of
SO2
out
of
the
total
112,936
tons.
Multiplying
the
total
benefit
per
ton
from
Table
D­
1(
a)
of
$
20,028
to
the
30,394
tons
SO2
yields
total
benefits
of
the
phase
two
analysis
for
SO2
of
$
609
million.

Tables
D­
2(
a)
and
D­
2(
b)
present
results
of
the
phase
one
and
phase
two
analysis
for
the
expected
562,110
tons
of
PM
reduced
due
to
the
MACT
Floor
regulatory
option
of
the
NESHAP.
The
phase
one
analysis
of
PM
reductions
(
Table
D­
2(
a))
results
in
total
benefits
of
$
6.6
billion
for
265,155
tons
of
PM10
and
75,095
tons
of
PM2.5.
The
resulting
total
benefit
transfer
value
is
$
88,118
per
ton
of
PM.
Applying
the
benefit
transfer
values
to
the
remaining
296,955
tons
of
PM
results
in
total
phase
two
benefits
of
approximately
$
7.4
billion.

Tables
D­
3(
a)
and
D­
3(
b)
show
the
summary
of
results
of
the
phase
one
and
phase
two
analysis
for
the
combination
of
SO2
and
PM
reductions.
Then
Table
D­
4
aggregates
the
results
of
the
two
phases
for
all
pollutant
reductions
to
provided
an
estimate
of
the
total
benefits
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
under
the
MACT
Floor
regulatory
option
in
2005
equal
to
$
16.3
billion.

Tables
D­
5
to
D­
8
show
the
estimate
of
benefits
for
the
above
the
MACT
floor
regulatory
option.
Table
D­
5(
a)
shows
the
results
of
the
phase
one
analysis
when
we
modeled
SO2
emission
reductions
alone.
Given
a
total
benefit
estimate
of
$
2.1
billion
from
the
assessment
of
benefits
of
95,361
tons
of
SO2
reduced
out
of
a
total
estimated
reduction
of
136,733
tons,
we
then
calculate
a
coefficient
for
each
benefit
endpoint
to
derive
benefit
transfer
values
for
(
1)
incidence
per
ton
reduced,
and
(
2)
benefit
per
ton
reduced.

Table
D­
5(
b)
shows
the
results
of
phase
two
of
the
analysis
associated
with
SO2
reductions.
Using
the
benefit
transfer
values
for
incidence
and
value,
we
calculate
the
approximate
benefits
of
the
remaining
41,372
tons
of
SO2
out
of
the
total
136,733
tons.
Multiplying
the
total
benefit
per
ton
from
Table
D­
5(
a)
of
$
22,071
to
the
41,372
tons
SO2
yields
total
benefits
of
the
phase
two
analysis
for
SO2
of
$
913
million.

Tables
D­
6(
a)
and
D­
6(
b)
present
results
of
the
phase
one
and
phase
two
analysis
for
C­
9
the
expected
569,229
tons
of
PM
reduced
due
to
the
above
the
MACT
floor
regulatory
option
of
the
NESHAP.
The
phase
one
analysis
of
PM
reductions
(
Table
D­
6(
a))
results
in
total
benefits
of
$
7.9
billion
for
313,947
tons
of
PM10
and
94,565
tons
of
PM2.5.
The
resulting
total
benefit
transfer
value
is
$
83,647
per
ton
of
PM.
Applying
the
benefit
transfer
values
to
the
remaining
255,282
tons
of
PM
results
in
total
phase
two
benefits
of
approximately
$
6.4
billion.

Tables
D­
7(
a)
and
D­
7(
b)
show
the
summary
of
results
of
the
phase
one
and
phase
two
analysis
for
the
combination
of
SO2
and
PM
reductions.
Then
Table
D­
8
aggregates
the
results
of
the
two
phases
for
all
pollutant
reductions
to
provided
an
estimate
of
the
total
benefits
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
under
the
above
MACT
floor
regulatory
option
in
2005
equal
to
$
17.2
billion.
C­
10
Avoided
Incidence
(
cases/
year)
Monetary
Benefits
(
millions
1999$)
Income
Adjustment
Adjusted
Benefits
Incidence/
ton
$/
ton
Endpoint
Reference
Mean
Simple
Mean
Factor
(
millions
1999$)
(
1999$)

MORTALITY
Ages
30+,
Mean,
Discount
Rate
=
3%
Krewski
et
al.
(
2000)
241
$
1,405
1.0805
$
1,518
0.00292461
$
18,385.89
Ages
30+,
Mean,
Discount
Rate
=
7%
Krewski
et
al.
(
2000)
241
$
1,319
1.0805
$
1,425
0.00292461
$
17,269.44
CHRONIC
ILLNESS
Chronic
Bronchitis
Schwartz,
1993
321
$
106
1.0911
$
115
0.00388893
$
1,397.96
HOSPITALIZATION
COPD­
Related
Samet
et
al.
(
2000)
51
$
1
1.0000
$
1
0.00061787
$
7.65
Pneumonia­
Related
Samet
et
al.
(
2000)
62
$
1
1.0000
$
1
0.00075113
$
11.04
Asthma­
Related
Sheppard
et
al.
(
1999)
24
$
0
1.0000
$
0
0.00029076
$
1.99
Cardiovascular­
Related
Samet
et
al.
(
2000)
149
$
3
1.0000
$
3
0.00180514
$
33.19
Asthma­
Related
ER
Visits
Schwartz
et
al.
(
1993)
134
$
0.0
1.0000
$
0.0
0.00162342
$
0.48
MINOR
ILLNESS
Acute
Bronchitis
Dockery
et
al.
(
1996)
490
$
0.0
1.0275
$
0.0
0.00593637
$
0.35
Upper
Respiratory
Symptoms
Pope
et
al.
(
1991)
12,976
$
0.3
1.0275
$
0.3
0.15720022
$
3.91
Lower
Respiratory
Symptoms
Schwartz
et
al.
(
1994)
5,327
$
0
1.0275
$
0
0.06453591
$
1.01
Asthma
Attacks
Whittemore
and
Korn
(
1980)
11,120
B
1.0275
B
0.13471911
B
Work
Loss
Days
Ostro
(
1987)
42,611
$
5
1.0000
$
5
0.51623645
$
54.72
MRAD
­
Adjusted
Ostro
and
Rothschild
(
1989)
214,592
$
10
1.0275
$
11
2.59979181
$
129.42
WELFARE
EFFECTS
Visibility
Recreational
Direct
Economic
Valuation
$
0
1.1908
$
0
$
0.00
Total
Base
PM­
Related
Benefits,
Discount
Rate
=
3%
$
1,530
$
1,653
$
20,027.62
Total
Base
PM­
Related
Benefits,
Discount
Rate
=
7%
$
1,445
$
1,561
$
18,911.17
NOTE:
Emission
Reduction
Summary
(
Converted
from
Mg
to
Tons)

SO2
Emission
Reductions
modeled
in
SR
Matrix
&
CAPMS
82542
Total
SO2
Emission
Reductions
from
all
sources
(
MACT
floor)
112936
SO2
reductions
applied
to
benefit
transfer
values
30394
Table
D­
1(
a).
Base
Estimate:
Results
of
Air
Quality
and
Benefit
Analyses
for
the
Phase
One
Analysis
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
Transfer
Values
National
Benefit­

MACT
Floor
in
2005
(
SO2
reductions
only)
D­
1
Avoided
Incidence
(
cases/
year)
Monetary
Benefits
(
millions
1999$)
Income
Adjustment
Adjusted
Benefits
Endpoint
Reference
Mean
Simple
Mean
Factor
(
millions
1999$)

MORTALITY
Ages
30+,
Mean,
Discount
Rate
=
3%
Krewski
et
al.
(
2000)
89
$
517
1.0805
$
559
Ages
30+,
Mean,
Discount
Rate
=
7%
Krewski
et
al.
(
2000)
89
$
486
1.0805
$
525
CHRONIC
ILLNESS
Chronic
Bronchitis
Schwartz,
1993
118
$
39
1.0911
$
42
HOSPITALIZATION
COPD­
Related
Samet
et
al.
(
2000)
19
$
0
1.0000
$
0
Pneumonia­
Related
Samet
et
al.
(
2000)
23
$
0
1.0000
$
0
Asthma­
Related
Sheppard
et
al.
(
1999)
9
$
0
1.0000
$
0
Cardiovascular­
Related
Samet
et
al.
(
2000)
55
$
1
1.0000
$
1
Asthma­
Related
ER
Visits
Schwartz
et
al.
(
1993)
49
$
0.0
1.0000
$
0.0
MINOR
ILLNESS
Acute
Bronchitis
Dockery
et
al.
(
1996)
180
$
0.0
1.0275
$
0.0
Upper
Respiratory
Symptoms
Pope
et
al.
(
1991)
4,778
$
0.1
1.0275
$
0.1
Lower
Respiratory
Symptoms
Schwartz
et
al.
(
1994)
1,962
$
0
1.0275
$
0
Asthma
Attacks
Whittemore
and
Korn
(
1980)
4,095
B
1.0275
B
Work
Loss
Days
Ostro
(
1987)
15,690
$
2
1.0000
$
2
MRAD
­
Adjusted
Ostro
and
Rothschild
(
1989)
79,018
$
4
1.0275
$
4
WELFARE
EFFECTS
Visibility
Recreational
Direct
Economic
Valuation
$
0
1.1908
$
0
Total
Base
PM­
Related
Benefits,
Discount
Rate
=
3%
$
563
$
609
Total
Base
PM­
Related
Benefits,
Discount
Rate
=
7%
$
532
$
575
MACT
Floor
in
2005
(
SO2
reductions
only)

Table
D­
1(
b).
Base
Estimate:
Results
of
Benefit
Transfer
Application
for
the
Phase
Two
Analysis
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
D­
2
Avoided
Incidence
(
cases/
year)
Monetary
Benefits
(
millions
1999$)
Income
Adjustment
Adjusted
Benefits
Incidence/
ton
$/
ton
Endpoint
Reference
Mean
Simple
Mean
Factor
(
1999$)

MORTALITY
Ages
30+,
Mean,
Discount
Rate
=
3%
Krewski
et
al.
(
2000)
903
$
5,254
1.0805
$
5,677
0.01202477
$
75,594.95
Ages
30+,
Mean,
Discount
Rate
=
7%
Krewski
et
al.
(
2000)
903
$
4,935
1.0805
$
5,332
0.01202477
$
71,004.58
CHRONIC
ILLNESS
Chronic
Bronchitis
Schwartz,
1993
2,356
$
776
1.0911
$
847
0.00888537
$
3,194.03
HOSPITALIZATION
COPD­
Related
Samet
et
al.
(
2000)
417
$
5
1.0000
$
5
0.00157267
$
19.47
Pneumonia­
Related
Samet
et
al.
(
2000)
509
$
7
1.0000
$
7
0.00191963
$
28.21
Asthma­
Related
Sheppard
et
al.
(
1999)
90
$
1
1.0000
$
1
0.00119848
$
8.21
Cardiovascular­
Related
Samet
et
al.
(
2000)
1,229
$
23
1.0000
$
23
0.00463502
$
85.22
Asthma­
Related
ER
Visits
Schwartz
et
al.
(
1993)
949
$
0.3
1.0000
$
0.3
0.00357904
$
1.07
MINOR
ILLNESS
Acute
Bronchitis
Dockery
et
al.
(
1996)
1,866
$
0.1
1.0275
$
0.1
0.02484853
$
1.46
Upper
Respiratory
Symptoms
Pope
et
al.
(
1991)
91,618
$
2.2
1.0275
$
2.3
0.34552721
$
8.60
Lower
Respiratory
Symptoms
Schwartz
et
al.
(
1994)
20,369
$
0
1.0275
$
0
0.27124181
$
4.26
Asthma
Attacks
Whittemore
and
Korn
(
1980)
80,696
B
1.0275
B
0.30433468
B
Work
Loss
Days
Ostro
(
1987)
158,563
$
17
1.0000
$
17
2.11150235
$
223.82
MRAD
­
Adjusted
Ostro
and
Rothschild
(
1989)
760,866
$
37
1.0275
$
38
10.13204793
$
504.40
WELFARE
EFFECTS
Visibility
Recreational
Direct
Economic
Valuation
$
0
1.1908
$
0
$
0.00
Total
Base
PM­
Related
Benefits,
Discount
Rate
=
3%
$
6,123
$
6,617
$
88,118.38
Total
Base
PM­
Related
Benefits,
Discount
Rate
=
7%
$
5,803
$
6,273
$
83,528.02
NOTE:
Emission
Reduction
Summary
(
Converted
from
Mg
to
Tons)

Industrial
Boiler
PM
Reductions
modeled
in
SR
Matrix
&
CAPMS
265155
Process
Heater
PM
Reductions
modeled
in
SR
Matrix
&
CAPMS
0
Total
PM10
Reductions
modeled
in
Phase
One
265155
Total
PM2.5
Reductions
modeled
in
Phase
One
75095
Total
PM
Reductions
from
All
Sources
(
MACT
floor)
562110
PM10
reductions
applied
to
benefit
transfer
values
296955
Non­
Inventory
PM2.5
reductions
applied
to
benefit
transfer
values
84101
Table
D­
2(
a).
Base
Estimate:
Results
of
Air
Quality
and
Benefit
Analyses
for
the
Phase
One
Analysis
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
Transfer
Values
National
Benefit­

MACT
Floor
in
2005
(
PM
reductions
only)
D­
3
Avoided
Incidence
(
cases/
year)
Monetary
Benefits
(
millions
1999$)
Income
Adjustment
Adjusted
Benefits
Endpoint
Reference
Mean
Factor
MORTALITY
Ages
30+,
Mean,
Discount
Rate
=
3%
Krewski
et
al.
(
2000)
1,011
$
5,884
1.0805
$
6,358
Ages
30+,
Mean,
Discount
Rate
=
7%
Krewski
et
al.
(
2000)
1,011
$
5,527
1.0805
$
5,972
CHRONIC
ILLNESS
Chronic
Bronchitis
Schwartz,
1993
2,639
$
869
1.0911
$
948
HOSPITALIZATION
COPD­
Related
Samet
et
al.
(
2000)
467
$
6
1.0000
$
6
Pneumonia­
Related
Samet
et
al.
(
2000)
570
$
8
1.0000
$
8
Asthma­
Related
Sheppard
et
al.
(
1999)
101
$
1
1.0000
$
1
Cardiovascular­
Related
Samet
et
al.
(
2000)
1,376
$
25
1.0000
$
25
Asthma­
Related
ER
Visits
Schwartz
et
al.
(
1993)
1,063
$
0.3
1.0000
$
0.3
MINOR
ILLNESS
Acute
Bronchitis
Dockery
et
al.
(
1996)
2,090
$
0.1
1.0275
$
0.1
Upper
Respiratory
Symptoms
Pope
et
al.
(
1991)
102,606
$
2.5
1.0275
$
2.6
Lower
Respiratory
Symptoms
Schwartz
et
al.
(
1994)
22,812
$
0
1.0275
$
0
Asthma
Attacks
Whittemore
and
Korn
(
1980)
90,374
B
1.0275
B
Work
Loss
Days
Ostro
(
1987)
177,580
$
19
1.0000
$
19
MRAD
­
Adjusted
Ostro
and
Rothschild
(
1989)
852,117
$
41
1.0275
$
42
WELFARE
EFFECTS
Visibility
Recreational
Direct
Economic
Valuation
$
0
1.1908
$
0
Total
Base
PM­
Related
Benefits,
Discount
Rate
=
3%
$
6,857
$
7,411
Total
Base
PM­
Related
Benefits,
Discount
Rate
=
7%
$
6,499
$
7,025
Table
D­
2(
b).
Base
Estimate:
Results
of
Benefit
Transfer
Application
for
the
Phase
Two
Analysis
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
MACT
Floor
in
2005
(
PM
reductions
only)
D­
4
Avoided
Incidence
(
cases/
year)
Monetary
Benefits
(
millions
1999$)
Income
Adjustment
Adjusted
Benefits
Endpoint
Reference
Mean
Simple
Mean
Factor
MORTALITY
Ages
30+,
Mean,
Discount
Rate
=
3%
Krewski
et
al.
(
2000)
1,165
$
6,778
1.0805
$
7,324
Ages
30+,
Mean,
Discount
Rate
=
7%
Krewski
et
al.
(
2000)
1,165
$
6,367
1.0805
$
6,879
CHRONIC
ILLNESS
Chronic
Bronchitis
Schwartz,
1993
2,344
$
772
1.0911
$
843
HOSPITALIZATION
COPD­
Related
Samet
et
al.
(
2000)
415
$
5
1.0000
$
5
Pneumonia­
Related
Samet
et
al.
(
2000)
507
$
7
1.0000
$
7
Asthma­
Related
Sheppard
et
al.
(
1999)
117
$
1
1.0000
$
1
Cardiovascular­
Related
Samet
et
al.
(
2000)
1,225
$
23
1.0000
$
23
Asthma­
Related
ER
Visits
Schwartz
et
al.
(
1993)
925
$
0.3
1.0000
$
0.3
MINOR
ILLNESS
Acute
Bronchitis
Dockery
et
al.
(
1996)
2,425
$
0.1
1.0275
$
0.1
Upper
Respiratory
Symptoms
Pope
et
al.
(
1991)
89,477
$
2.2
1.0275
$
2.2
Lower
Respiratory
Symptoms
Schwartz
et
al.
(
1994)
26,465
$
0
1.0275
$
0
Asthma
Attacks
Whittemore
and
Korn
(
1980)
79,018
B
1.0275
B
Work
Loss
Days
Ostro
(
1987)
205,400
$
22
1.0000
$
22
MRAD
­
Adjusted
Ostro
and
Rothschild
(
1989)
1,011,204
$
49
1.0275
$
50
WELFARE
EFFECTS
Visibility
Recreational
Direct
Economic
Valuation
$
0
1.1908
$
0
Total
Base
PM­
Related
Benefits,
Discount
Rate
=
3%
$
7,660
$
8,278
Total
Base
PM­
Related
Benefits,
Discount
Rate
=
7%
$
7,249
$
7,833
Table
D­
3(
a).
Base
Estimate:
Results
of
Air
Quality
and
Benefit
Analyses
for
the
Phase
One
Analysis
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
MACT
Floor
in
2005
(
PM
and
SO2
reductions
modeled
together)
D­
5
Avoided
Incidence
(
cases/
year)
Monetary
Benefits
(
millions
1999$)
Income
Adjustment
Adjusted
Benefits
Endpoint
Reference
Mean
Factor
(
millions
1999$)

MORTALITY
Ages
30+,
Mean,
Discount
Rate
=
3%
Krewski
et
al.
(
2000)
1,100
$
6,401
1.0805
$
6,916
Ages
30+,
Mean,
Discount
Rate
=
7%
Krewski
et
al.
(
2000)
1,100
$
6,012
1.0805
$
6,496
CHRONIC
ILLNESS
Chronic
Bronchitis
Schwartz,
1993
2,757
$
908
1.0911
$
991
HOSPITALIZATION
COPD­
Related
Samet
et
al.
(
2000)
486
$
6
1.0000
$
6
Pneumonia­
Related
Samet
et
al.
(
2000)
593
$
9
1.0000
$
9
Asthma­
Related
Sheppard
et
al.
(
1999)
110
$
1
1.0000
$
1
Cardiovascular­
Related
Samet
et
al.
(
2000)
1,431
$
26
1.0000
$
26
Asthma­
Related
ER
Visits
Schwartz
et
al.
(
1993)
1,112
$
0.3
1.0000
$
0.3
MINOR
ILLNESS
Acute
Bronchitis
Dockery
et
al.
(
1996)
2,270
$
0.1
1.0275
$
0.1
Upper
Respiratory
Symptoms
Pope
et
al.
(
1991)
107,384
$
2.6
1.0275
$
2.7
Lower
Respiratory
Symptoms
Schwartz
et
al.
(
1994)
24,773
$
0
1.0275
$
0
Asthma
Attacks
Whittemore
and
Korn
(
1980)
94,468
B
1.0275
B
Work
Loss
Days
Ostro
(
1987)
193,270
$
20
1.0000
$
20
MRAD
­
Adjusted
Ostro
and
Rothschild
(
1989)
931,135
$
45
1.0275
$
46
WELFARE
EFFECTS
Visibility
Recreational
Direct
Economic
Valuation
$
0
1.1908
$
0
Total
Base
PM­
Related
Benefits,
Discount
Rate
=
3%
$
7,420
$
8,020
Total
Base
PM­
Related
Benefits,
Discount
Rate
=
7%
$
7,032
$
7,600
NOTE:
Results
of
this
table
are
based
on
the
addition
of
incidences
and
monetary
values
from
Tables
D­
1(
b)
and
D­
2(
b).

Table
D­
3(
b).
Base
Estimate:
Results
of
Benefit
Transfer
Application
for
the
Phase
Two
Analysis
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
MACT
Floor
in
2005
(
PM
and
SO2
reductions)
D­
6
Avoided
Incidence
(
cases/
year)
Monetary
Benefits
(
millions
1999$)
Income
Adjustment
Adjusted
Benefits
Endpoint
Reference
Mean
Factor
(
millions
1999$)

MORTALITY
Ages
30+,
Mean,
Discount
Rate
=
3%
Krewski
et
al.
(
2000)
2,265
$
13,179
1.0805
$
14,240
Ages
30+,
Mean,
Discount
Rate
=
7%
Krewski
et
al.
(
2000)
2,265
$
12,379
1.0805
$
13,376
CHRONIC
ILLNESS
Chronic
Bronchitis
Schwartz,
1993
5,101
$
1,680
1.0911
$
1,834
HOSPITALIZATION
COPD­
Related
Samet
et
al.
(
2000)
901
$
11
1.0000
$
11
Pneumonia­
Related
Samet
et
al.
(
2000)
1,100
$
16
1.0000
$
16
Asthma­
Related
Sheppard
et
al.
(
1999)
227
$
2
1.0000
$
2
Cardiovascular­
Related
Samet
et
al.
(
2000)
2,656
$
49
1.0000
$
49
Asthma­
Related
ER
Visits
Schwartz
et
al.
(
1993)
2,037
$
0.6
1.0000
$
0.6
MINOR
ILLNESS
Acute
Bronchitis
Dockery
et
al.
(
1996)
4,695
$
0.3
1.0275
$
0.3
Upper
Respiratory
Symptoms
Pope
et
al.
(
1991)
196,861
$
4.8
1.0275
$
4.9
Lower
Respiratory
Symptoms
Schwartz
et
al.
(
1994)
51,238
$
1
1.0275
$
1
Asthma
Attacks
Whittemore
and
Korn
(
1980)
173,486
B
1.0275
B
Work
Loss
Days
Ostro
(
1987)
398,671
$
42
1.0000
$
42
MRAD
­
Adjusted
Ostro
and
Rothschild
(
1989)
1,942,339
$
94
1.0275
$
97
WELFARE
EFFECTS
Visibility
Recreational
Direct
Economic
Valuation
$
0
1.1908
$
0
Total
Base
PM­
Related
Benefits,
Discount
Rate
=
3%
$
15,080
$
16,297
Total
Base
PM­
Related
Benefits,
Discount
Rate
=
7%
$
14,280
$
15,432
NOTE:
Results
of
this
table
are
based
on
the
addition
of
results
from
Tables
D­
3(
a)
and
D­
3(
b).

Table
D­
4.
Base
Estimate:
Total
Benefits
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
­
MACT
Floor
in
2005
(
Combined
Estimates
of
Reduced
Incidences
and
Monetized
Benefits
from
Phase
One
and
Two
Analyses)
D­
7
Avoided
Incidence
(
cases/
year)
Monetary
Benefits
(
millions
1999$)
Income
Adjustment
Adjusted
Benefits
Incidence/
ton
$/
ton
Endpoint
Reference
Mean
Simple
Mean
Factor
(
millions
1999$)
(
1999$)

MORTALITY
Ages
30+,
Mean,
Discount
Rate
=
3%
Krewski
et
al.
(
2000)
308
$
1,792
1.0805
$
1,936
0.00322983
$
20,304.67
Ages
30+,
Mean,
Discount
Rate
=
7%
Krewski
et
al.
(
2000)
308
$
1,683
1.0805
$
1,819
0.00322983
$
19,071.71
CHRONIC
ILLNESS
Chronic
Bronchitis
Schwartz,
1993
398
$
131
1.0911
$
143
0.00417361
$
1,500.29
HOSPITALIZATION
COPD­
Related
Samet
et
al.
(
2000)
58
$
1
1.0000
$
1
0.00060822
$
7.53
Pneumonia­
Related
Samet
et
al.
(
2000)
71
$
1
1.0000
$
1
0.00074454
$
10.94
Asthma­
Related
Sheppard
et
al.
(
1999)
31
$
0
1.0000
$
0
0.00032508
$
2.23
Cardiovascular­
Related
Samet
et
al.
(
2000)
170
$
3
1.0000
$
3
0.00178270
$
32.78
Asthma­
Related
ER
Visits
Schwartz
et
al.
(
1993)
147
$
0.0
1.0000
$
0.0
0.00154151
$
0.46
MINOR
ILLNESS
Acute
Bronchitis
Dockery
et
al.
(
1996)
657
$
0.0
1.0275
$
0.0
0.00688919
$
0.41
Upper
Respiratory
Symptoms
Pope
et
al.
(
1991)
14,162
$
0.3
1.0275
$
0.4
0.14851322
$
3.70
Lower
Respiratory
Symptoms
Schwartz
et
al.
(
1994)
7,174
$
0
1.0275
$
0
0.07523289
$
1.18
Asthma
Attacks
Whittemore
and
Korn
(
1980)
12,248
B
1.0275
B
0.12844191
B
Work
Loss
Days
Ostro
(
1987)
54,979
$
6
1.0000
$
6
0.57653799
$
61.11
MRAD
­
Adjusted
Ostro
and
Rothschild
(
1989)
279,759
$
14
1.0275
$
14
2.93367993
$
146.05
WELFARE
EFFECTS
Visibility
Recreational
Direct
Economic
Valuation
$
0
1.1908
$
0
$
0.00
Total
Base
PM­
Related
Benefits,
Discount
Rate
=
3%
$
1,948
$
2,105
$
22,071.34
Total
Base
PM­
Related
Benefits,
Discount
Rate
=
7%
$
1,839
$
1,987
$
20,838.38
NOTE:
Emission
Reduction
Summary
(
Converted
from
Mg
to
Tons)

SO2
Emission
Reductions
modeled
in
SR
Matrix
&
CAPMS
95361
Total
SO2
Reductions
from
all
sources
(
Above
MACT
Floor)
136733.3
SO2
reductions
applied
to
benefit
transfer
values
41372.3
Table
D­
5(
a).
Base
Estimate:
Results
of
Air
Quality
and
Benefit
Analyses
for
the
Phase
One
Analysis
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
Transfer
Values
National
Benefit­

Above
the
MACT
Floor
in
2005
(
SO2
reductions
only)
D­
8
Avoided
Incidence
(
cases/
year)
Monetary
Benefits
(
millions
1999$)
Income
Adjustment
Adjusted
Benefits
Endpoint
Reference
Mean
Simple
Mean
Factor
(
millions
1999$)

MORTALITY
Ages
30+,
Mean,
Discount
Rate
=
3%
Krewski
et
al.
(
2000)
134
$
777
1.0805
$
840
Ages
30+,
Mean,
Discount
Rate
=
7%
Krewski
et
al.
(
2000)
134
$
730
1.0805
$
789
CHRONIC
ILLNESS
Chronic
Bronchitis
Schwartz,
1993
173
$
57
1.0911
$
62
HOSPITALIZATION
COPD­
Related
Samet
et
al.
(
2000)
25
$
0
1.0000
$
0
Pneumonia­
Related
Samet
et
al.
(
2000)
31
$
0
1.0000
$
0
Asthma­
Related
Sheppard
et
al.
(
1999)
13
$
0
1.0000
$
0
Cardiovascular­
Related
Samet
et
al.
(
2000)
74
$
1
1.0000
$
1
Asthma­
Related
ER
Visits
Schwartz
et
al.
(
1993)
64
$
0.0
1.0000
$
0.0
MINOR
ILLNESS
Acute
Bronchitis
Dockery
et
al.
(
1996)
285
$
0.0
1.0275
$
0.0
Upper
Respiratory
Symptoms
Pope
et
al.
(
1991)
6,144
$
0.1
1.0275
$
0.2
Lower
Respiratory
Symptoms
Schwartz
et
al.
(
1994)
3,113
$
0
1.0275
$
0
Asthma
Attacks
Whittemore
and
Korn
(
1980)
5,314
B
1.0275
B
Work
Loss
Days
Ostro
(
1987)
23,853
$
3
1.0000
$
3
MRAD
­
Adjusted
Ostro
and
Rothschild
(
1989)
121,373
$
6
1.0275
$
6
WELFARE
EFFECTS
Visibility
Recreational
Direct
Economic
Valuation
$
0
1.1908
$
0
Total
Base
PM­
Related
Benefits,
Discount
Rate
=
3%
$
845
$
913
Total
Base
PM­
Related
Benefits,
Discount
Rate
=
7%
$
798
$
862
Above
the
MACT
Floor
in
2005
(
SO2
reductions
only)

Table
D­
5(
b).
Base
Estimate:
Results
of
Benefit
Transfer
Application
for
the
Phase
Two
Analysis
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
D­
9
Avoided
Incidence
(
cases/
year)
Monetary
Benefits
(
millions
1999$)
Income
Adjustment
Adjusted
Benefits
Incidence/
ton
$/
ton
Endpoint
Reference
Mean
Simple
Mean
Factor
(
1999$)

MORTALITY
Ages
30+,
Mean,
Discount
Rate
=
3%
Krewski
et
al.
(
2000)
1,087
$
6,327
1.0805
$
6,836
0.01149862
$
72,287.27
Ages
30+,
Mean,
Discount
Rate
=
7%
Krewski
et
al.
(
2000)
1,087
$
5,942
1.0805
$
6,421
0.01149862
$
67,897.76
CHRONIC
ILLNESS
Chronic
Bronchitis
Schwartz,
1993
2,683
$
884
1.0911
$
964
0.00854575
$
3,071.95
HOSPITALIZATION
COPD­
Related
Samet
et
al.
(
2000)
470
$
6
1.0000
$
6
0.00149707
$
18.53
Pneumonia­
Related
Samet
et
al.
(
2000)
573
$
8
1.0000
$
8
0.00182515
$
26.82
Asthma­
Related
Sheppard
et
al.
(
1999)
109
$
1
1.0000
$
1
0.00115265
$
7.89
Cardiovascular­
Related
Samet
et
al.
(
2000)
1,385
$
25
1.0000
$
25
0.00441157
$
81.12
Asthma­
Related
ER
Visits
Schwartz
et
al.
(
1993)
1070
$
0.3
1.0000
$
0.3
0.00340822
$
1.02
MINOR
ILLNESS
Acute
Bronchitis
Dockery
et
al.
(
1996)
2,230
$
0.1
1.0275
$
0.1
0.02358633
$
1.39
Upper
Respiratory
Symptoms
Pope
et
al.
(
1991)
103,400
$
2.5
1.0275
$
2.6
0.32935392
$
8.20
Lower
Respiratory
Symptoms
Schwartz
et
al.
(
1994)
24,325
$
0
1.0275
$
0
0.25722847
$
4.04
Asthma
Attacks
Whittemore
and
Korn
(
1980)
90,940
B
1.0275
B
0.28966831
B
Work
Loss
Days
Ostro
(
1987)
190,370
$
20
1.0000
$
20
2.01311570
$
213.39
MRAD
­
Adjusted
Ostro
and
Rothschild
(
1989)
918,645
$
45
1.0275
$
46
9.71442399
$
483.61
WELFARE
EFFECTS
Visibility
Recreational
Direct
Economic
Valuation
$
0
1.1908
$
0
$
0.00
Total
Base
PM­
Related
Benefits,
Discount
Rate
=
3%
$
7,319
$
7,910
$
83,646.62
Total
Base
PM­
Related
Benefits,
Discount
Rate
=
7%
$
6,935
$
7,495
$
79,257.11
NOTE:
Emission
Reduction
Summary
(
Converted
from
Mg
to
Tons)

Industrial
Boiler
PM
Reductions
modeled
in
SR
Matrix
&
CAPMS
295645
Process
Heater
PM
Reductions
modeled
in
SR
Matrix
&
CAPMS
18302
Total
PM10
Reductions
modeled
313947
Total
PM2.5
Reductions
modeled
94565
Total
PM
Reductions
from
All
Sources
(
Above
MACT
Floor)
569229.1
PM10
reductions
applied
to
benefit
transfer
values
255282.1
PM2.5
reductions
applied
to
benefit
transfer
values
76894
Table
D­
6(
a).
Base
Estimate:
Results
of
Air
Quality
and
Benefit
Analyses
for
the
Phase
One
Analysis
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
Transfer
Values
National
Benefit­

Above
the
MACT
Floor
in
2005
(
PM
reductions
only)
D­
10
Avoided
Incidence
(
cases/
year)
Monetary
Benefits
(
millions
1999$)
Income
Adjustment
Adjusted
Benefits
Endpoint
Reference
Mean
Factor
MORTALITY
Ages
30+,
Mean,
Discount
Rate
=
3%
Krewski
et
al.
(
2000)
884
$
5,144
1.0805
$
5,558
Ages
30+,
Mean,
Discount
Rate
=
7%
Krewski
et
al.
(
2000)
884
$
4,832
1.0805
$
5,221
CHRONIC
ILLNESS
Chronic
Bronchitis
Schwartz,
1993
2,182
$
719
1.0911
$
784
HOSPITALIZATION
COPD­
Related
Samet
et
al.
(
2000)
382
$
5
1.0000
$
5
Pneumonia­
Related
Samet
et
al.
(
2000)
466
$
7
1.0000
$
7
Asthma­
Related
Sheppard
et
al.
(
1999)
89
$
1
1.0000
$
1
Cardiovascular­
Related
Samet
et
al.
(
2000)
1,126
$
21
1.0000
$
21
Asthma­
Related
ER
Visits
Schwartz
et
al.
(
1993)
870
$
0.3
1.0000
$
0.3
MINOR
ILLNESS
Acute
Bronchitis
Dockery
et
al.
(
1996)
1,814
$
0.1
1.0275
$
0.1
Upper
Respiratory
Symptoms
Pope
et
al.
(
1991)
84,078
$
2.0
1.0275
$
2.1
Lower
Respiratory
Symptoms
Schwartz
et
al.
(
1994)
19,779
$
0
1.0275
$
0
Asthma
Attacks
Whittemore
and
Korn
(
1980)
73,947
B
1.0275
B
Work
Loss
Days
Ostro
(
1987)
154,797
$
16
1.0000
$
16
MRAD
­
Adjusted
Ostro
and
Rothschild
(
1989)
746,984
$
36
1.0275
$
37
WELFARE
EFFECTS
Visibility
Recreational
Direct
Economic
Valuation
$
0
1.1908
$
0
Total
Base
PM­
Related
Benefits,
Discount
Rate
=
3%
$
5,951
$
6,432
Total
Base
PM­
Related
Benefits,
Discount
Rate
=
7%
$
5,639
$
6,094
Table
D­
6(
b).
Base
Estimate:
Results
of
Benefit
Transfer
Application
for
the
Phase
Two
Analysis
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
Above
the
MACT
Floor
in
2005
(
PM
reductions
only)
D­
11
Avoided
Incidence
(
cases/
year)
Monetary
Benefits
(
millions
1999$)
Income
Adjustment
Adjusted
Benefits
Endpoint
Reference
Mean
Simple
Mean
Factor
MORTALITY
Ages
30+,
Mean,
Discount
Rate
=
3%
Krewski
et
al.
(
2000)
1,390
$
8,086
1.0805
$
8,737
Ages
30+,
Mean,
Discount
Rate
=
7%
Krewski
et
al.
(
2000)
1,390
$
7,595
1.0805
$
8,207
CHRONIC
ILLNESS
Chronic
Bronchitis
Schwartz,
1993
2,864
$
944
1.0911
$
1,029
HOSPITALIZATION
COPD­
Related
Samet
et
al.
(
2000)
502
$
6
1.0000
$
6
Pneumonia­
Related
Samet
et
al.
(
2000)
613
$
9
1.0000
$
9
Asthma­
Related
Sheppard
et
al.
(
1999)
139
$
1
1.0000
$
1
Cardiovascular­
Related
Samet
et
al.
(
2000)
1,480
$
27
1.0000
$
27
Asthma­
Related
ER
Visits
Schwartz
et
al.
(
1993)
1142
$
0.3
1.0000
$
0.3
MINOR
ILLNESS
Acute
Bronchitis
Dockery
et
al.
(
1996)
2,869
$
0.2
1.0275
$
0.2
Upper
Respiratory
Symptoms
Pope
et
al.
(
1991)
110,367
$
2.7
1.0275
$
2.7
Lower
Respiratory
Symptoms
Schwartz
et
al.
(
1994)
31,293
$
0
1.0275
$
0
Asthma
Attacks
Whittemore
and
Korn
(
1980)
97,058
$
4
1.0275
$
4
Work
Loss
Days
Ostro
(
1987)
243,866
$
26
1.0000
$
26
MRAD
­
Adjusted
Ostro
and
Rothschild
(
1989)
1,196,497
$
58
1.0275
$
60
WELFARE
EFFECTS
Visibility
Recreational
Direct
Economic
Valuation
$
0
1.1908
$
0
Total
Base
PM­
Related
Benefits,
Discount
Rate
=
3%
$
9,165
$
9,904
Total
Base
PM­
Related
Benefits,
Discount
Rate
=
7%
$
8,674
$
9,373
Table
D­
7(
a).
Base
Estimate:
Results
of
Air
Quality
and
Benefit
Analyses
for
the
Phase
One
Analysis
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
Above
the
MACT
Floor
in
2005
(
PM
and
SO2
reductions
modeled
together)
D­
12
Avoided
Incidence
(
cases/
year)
Monetary
Benefits
(
millions
1999$)
Income
Adjustment
Adjusted
Benefits
Endpoint
Reference
Mean
Factor
(
millions
1999$)

MORTALITY
Ages
30+,
Mean,
Discount
Rate
=
3%
Krewski
et
al.
(
2000)
1,018
$
5,922
1.0805
$
6,399
Ages
30+,
Mean,
Discount
Rate
=
7%
Krewski
et
al.
(
2000)
1,018
$
5,562
1.0805
$
6,010
CHRONIC
ILLNESS
Chronic
Bronchitis
Schwartz,
1993
2,354
$
776
1.0911
$
846
HOSPITALIZATION
COPD­
Related
Samet
et
al.
(
2000)
407
$
5
1.0000
$
5
Pneumonia­
Related
Samet
et
al.
(
2000)
497
$
7
1.0000
$
7
Asthma­
Related
Sheppard
et
al.
(
1999)
102
$
1
1.0000
$
1
Cardiovascular­
Related
Samet
et
al.
(
2000)
1,200
$
22
1.0000
$
22
Asthma­
Related
ER
Visits
Schwartz
et
al.
(
1993)
934
$
0.3
1.0000
$
0.3
MINOR
ILLNESS
Acute
Bronchitis
Dockery
et
al.
(
1996)
2,099
$
0.1
1.0275
$
0.1
Upper
Respiratory
Symptoms
Pope
et
al.
(
1991)
90,222
$
2.2
1.0275
$
2.2
Lower
Respiratory
Symptoms
Schwartz
et
al.
(
1994)
22,892
$
0
1.0275
$
0
Asthma
Attacks
Whittemore
and
Korn
(
1980)
79,261
$
3
1.0275
$
3
Work
Loss
Days
Ostro
(
1987)
178,650
$
19
1.0000
$
19
MRAD
­
Adjusted
Ostro
and
Rothschild
(
1989)
868,357
$
42
1.0275
$
43
WELFARE
EFFECTS
Visibility
Recreational
Direct
Economic
Valuation
$
0
1.1908
$
0
Total
Base
PM­
Related
Benefits,
Discount
Rate
=
3%
$
6,800
$
7,348
Total
Base
PM­
Related
Benefits,
Discount
Rate
=
7%
$
6,440
$
6,960
NOTE:
Results
of
this
table
are
based
on
the
addition
of
incidences
and
monetary
values
from
Tables
D­
5(
b)
and
D­
6(
b).

Table
D­
7(
b).
Base
Estimate:
Results
of
Benefit
Transfer
Application
for
the
Phase
Two
Analysis
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
Above
the
MACT
Floor
in
2005
(
PM
and
SO2
reductions)
D­
13
Avoided
Incidence
(
cases/
year)
Monetary
Benefits
(
millions
1999$)
Income
Adjustment
Adjusted
Benefits
Endpoint
Reference
Mean
Factor
(
millions
1999$)

MORTALITY
Ages
30+,
Mean,
Discount
Rate
=
3%
Krewski
et
al.
(
2000)
2,408
$
14,008
1.0805
$
15,136
Ages
30+,
Mean,
Discount
Rate
=
7%
Krewski
et
al.
(
2000)
2,408
$
13,158
1.0805
$
14,217
CHRONIC
ILLNESS
Chronic
Bronchitis
Schwartz,
1993
5,218
$
1,719
1.0911
$
1,876
HOSPITALIZATION
COPD­
Related
Samet
et
al.
(
2000)
909
$
11
1.0000
$
11
Pneumonia­
Related
Samet
et
al.
(
2000)
1,110
$
16
1.0000
$
16
Asthma­
Related
Sheppard
et
al.
(
1999)
241
$
2
1.0000
$
2
Cardiovascular­
Related
Samet
et
al.
(
2000)
2,680
$
49
1.0000
$
49
Asthma­
Related
ER
Visits
Schwartz
et
al.
(
1993)
2,076
$
0.6
1.0000
$
0.6
MINOR
ILLNESS
Acute
Bronchitis
Dockery
et
al.
(
1996)
4,968
$
0.3
1.0275
$
0.3
Upper
Respiratory
Symptoms
Pope
et
al.
(
1991)
200,589
$
4.9
1.0275
$
5.0
Lower
Respiratory
Symptoms
Schwartz
et
al.
(
1994)
54,185
$
1
1.0275
$
1
Asthma
Attacks
Whittemore
and
Korn
(
1980)
82,130
B
1.0275
B
Work
Loss
Days
Ostro
(
1987)
275,708
$
29
1.0000
$
29
MRAD
­
Adjusted
Ostro
and
Rothschild
(
1989)
2,064,854
$
100
1.0275
$
103
WELFARE
EFFECTS
Visibility
Recreational
Direct
Economic
Valuation
$
0
1.1908
$
0
Total
Base
PM­
Related
Benefits,
Discount
Rate
=
3%
$
15,942
$
17,229
Total
Base
PM­
Related
Benefits,
Discount
Rate
=
7%
$
15,091
$
16,310
NOTE:
Results
of
this
table
are
based
on
the
addition
of
results
from
Tables
D­
7(
a)
and
D­
7(
b).

Table
D­
8.
Base
Estimate:
Total
Benefits
of
the
Industrial
Boilers/
Process
Heaters
NESHAP
­
Above
the
MACT
Floor
in
2005
(
Combined
Estimates
of
Reduced
Incidences
and
Monetized
Benefits
from
Phase
One
and
Two
Analyses)
E­
1
Appendix
E.
Impacts
Based
on
Low­
Risk
Threshold
Cutoffs
for
Hydrochloric
Acid
(
HCl)
and
Manganese
(
Mn)

Background
Among
the
alternatives
to
compliance
with
the
final
rule
are
health­
based
threshold
cutoffs
for
different
pollutants.
As
an
alternative
to
the
requirement
for
each
large
solid
fuel­
fired
boiler
to
demonstrate
compliance
with
the
HCl
emission
limit
in
the
final
rule,
you
may
demonstrate
compliance
with
a
health­
based
HCl
equivalent
allowable
emission
limit.
In
lieu
of
complying
with
the
emission
standard
for
total
selected
metals
(
TSM)
in
the
final
rule
based
on
the
sum
of
emissions
for
the
eight
selected
metals,
you
may
demonstrate
eligibility
for
complying
with
the
TSM
standard
based
on
excluding
manganese
emissions
from
the
summation
of
TSM
emissions
for
the
affected
source
unit(
s).

Emission
Reductions
Nationwide
emissions
of
selected
HAP
(
i.
e.,
HCl,
hydrogen
fluoride,
lead,
and
nickel)
will
be
reduced
by
58,500
tpy
for
existing
units
and
73
tpy
for
new
units.
Depending
on
the
number
of
facilities
demonstrating
eligibility
for
the
health­
based
compliance
alternatives,
the
total
HAP
reduction
for
existing
units
could
be
50,600
tpy.
Emissions
of
HCl
will
be
reduced
by
42,000
tpy
for
existing
units
and
72
tpy
for
new
units.
Depending
on
the
number
of
facilities
demonstrating
eligibility
for
the
health­
based
compliance
alternatives,
the
total
HCl
emissions
reduction
for
existing
units
could
be
36,400
tpy.
Emissions
of
mercury
will
be
reduced
by
1.9
tpy
for
existing
units
and
0.006
tpy
for
new
units.
Emissions
of
PM
will
be
reduced
by
565,000
tpy
for
existing
units
and
480
tpy
for
new
units.
Depending
on
the
number
of
facilities
demonstrating
eligibility
for
the
healthbased
compliance
alternatives,
the
total
PM
emissions
reduction
for
existing
units
could
be
547,000
tpy.
Emissions
of
total
selected
nonmercury
metals
(
i.
e.,
arsenic,
beryllium,
cadmium,
chromium,
lead,
manganese,
nickel,
and
selenium)
will
be
reduced
by
1,100
tpy
for
existing
units
and
will
be
reduced
by
1.4
tpy
for
new
units.
Depending
on
the
number
of
facilities
demonstrating
eligibility
for
the
health­
based
compliance
alternatives,
the
total
nonmercury
metals
emissions
reduction
for
existing
units
could
fall
to
be
950
tpy.
In
addition,
emissions
of
sulfur
dioxide
are
established
to
be
reduced
by
113,000
tpy
for
existing
sources
and
110
tpy
for
new
sources.
Depending
on
the
number
of
facilities
demonstrating
eligibility
for
the
health­
based
compliance
alternatives,
the
total
sulfur
dioxide
emissions
reduction
for
existing
units
could
fall
to
be
49,000
tpy.
A
discussion
of
the
methodology
used
to
estimate
emissions
and
emissions
reductions
is
presented
in
"
Estimation
of
Baseline
Emissions
and
Emissions
Reductions
for
Industrial,
Commercial,
and
Institutional
Boilers
and
Process
Heaters"
in
the
docket.
To
estimate
the
potential
impacts
of
the
health­
based
compliance
alternatives,
we
performed
a
preliminary
"
rough"
assessment
of
the
large
solid
fuel
subcategory
to
determine
the
extent
to
which
facilities
might
become
eligible
for
the
health­
based
compliance
alternatives.
Based
on
the
results
of
this
rough
assessment,
448
coal­
fired
boilers
could
potentially
be
eligible
for
the
HCl
compliance
alternative
and
386
biomass­
fired
boilers
could
be
potentially
eligible
for
the
TSM
compliance
alternative.

Wastewater
and
Solid
Waste
impacts
The
EPA
estimates
the
additional
water
usage
that
would
result
from
the
MACT
floor
level
of
control
to
be
110
million
gallons
per
year
for
existing
sources
and
0.6
million
gallons
per
year
for
new
sources.
In
addition
to
the
increased
water
usage,
an
additional
3.7
million
gallons
per
year
of
wastewater
will
be
produced
for
existing
sources
and
0.6
million
gallons
per
year
for
new
sources.
The
costs
of
treating
the
additional
wastewater
are
$
18,000
for
existing
sources
and
$
2,300
for
new
sources,
in
advance
of
any
facility
demonstrating
eligibility
for
the
health­
based
compliance
alternatives.
These
costs
are
accounted
for
in
the
control
costs
estimates.
The
EPA
estimates
the
additional
solid
waste
that
would
result
from
the
MACT
floor
level
of
control
to
be
102,000
tpy
for
existing
sources
and
1
tpy
for
new
sources.
The
estimated
costs
of
handling
the
additional
solid
waste
generated
are
$
1.5
million
for
existing
sources
and
$
17,000
for
new
sources,
in
advance
of
any
facility
demonstrating
eligibility
for
the
health­
based
compliance
alternatives.
These
costs
are
also
accounted
for
in
the
control
costs
estimates.
A
discussion
of
the
methodology
used
to
estimate
impacts
is
presented
in
"
Estimation
of
Impacts
for
Industrial,
Commercial,
and
Institutional
Boilers
and
Process
Heaters
NESHAP"
in
the
docket.

Energy
Impact
from
Additional
Control
Equipment
E­
2
The
EPA
expects
an
increase
of
approximately
1,130
million
kilowatt
hours
(
kWh)
in
national
annual
energy
usage
as
a
result
of
the
final
rule,
in
advance
of
any
facility
demonstrating
eligibility
for
the
health­
based
compliance
alternatives.
Of
this
amount,
1,120
million
kWh
is
estimated
from
existing
sources
and
13
million
kWh
is
estimated
from
new
sources.
The
increase
results
from
the
electricity
required
to
operate
control
devices
installed
to
meet
the
final
rule,
such
as
wet
scrubbers
and
fabric
filters.

Compliance
Costs
To
estimate
the
national
cost
impacts
of
the
final
rule
for
existing
sources,
EPA
developed
several
model
boilers
and
process
heaters
and
determined
the
cost
of
control
equipment
for
these
model
boilers.
The
EPA
assigned
a
model
boiler
or
heater
to
each
existing
unit
in
the
database
based
on
the
fuel,
size,
design,
and
current
controls.
The
analysis
considered
all
air
pollution
control
equipment
currently
in
operation
at
existing
boilers
and
process
heaters.
Model
costs
were
then
assigned
to
all
existing
units
that
could
not
otherwise
meet
the
proposed
emission
limits.
The
resulting
total
national
cost
impact
of
the
final
rule
is
$
1,790
million
in
capital
expenditures
and
$
860
million
per
year
in
total
annual
costs.
Depending
on
the
number
of
facilities
demonstrating
eligibility
for
the
health­
based
compliance
alternatives,
these
costs
could
fall
to
be
$
1,440
million
in
capital
expenditures
and
$
690
million
per
year
in
total
annual
costs.
The
total
capital
and
annual
costs
include
costs
for
testing,
monitoring,
and
recordkeeping
and
reporting.
Costs
include
testing
and
monitoring
costs,
but
not
recordkeeping
and
reporting
costs.
Using
Department
of
Energy
projections
on
fuel
expenditures,
EPA
estimated
the
number
of
additional
boilers
that
could
be
potentially
constructed.
The
resulting
total
national
cost
impact
of
the
final
rule
in
the
5th
year
is
$
58
million
in
capital
expenditures
and
$
18.6
million
per
year
in
total
annual
costs,
in
advance
of
any
facility
demonstrating
eligibility
for
the
healthbased
provisions.
Costs
are
mainly
for
testing
and
monitoring.
A
discussion
of
the
methodology
used
to
estimate
cost
impacts
is
presented
in
"
Methodology
and
Results
of
Estimating
the
Cost
of
Complying
with
the
Industrial,
Commercial,
and
Institutional
Boiler
and
Process
Heater
NESHAP"
in
the
docket.

Economic
Impacts
The
economic
impact
analysis
shows
that
the
expected
price
increase
for
output
in
the
40
affected
industries
would
be
no
more
than
0.04
percent
as
a
result
of
the
final
rule
for
industrial
boilers
and
process
heaters.
The
expected
change
in
production
of
affected
output
is
a
reduction
of
only
0.03
percent
or
less
in
the
same
industries.
In
addition,
impacts
to
affected
energy
markets
show
that
prices
of
petroleum,
natural
gas,
electricity
and
coal
should
increase
by
no
more
than
0.05
percent
as
a
result
of
implementation
of
the
final
rule,
and
output
of
these
types
of
energy
should
decrease
by
no
more
than
0.01
percent.
These
impacts
are
generated
in
advance
of
any
facility
demonstrating
eligibility
for
the
health­
based
compliance
alternatives.
Depending
on
the
number
of
affected
facilities
demonstrating
eligibility
for
the
health­
based
compliance
alternatives,
these
impacts
on
product
prices
could
fall
to
a
0.03
percent
increase,
and
a
decrease
in
output
of
the
energy
types
mentioned
previously
of
less
than
0.01
percent.
Therefore,
it
is
likely
that
there
is
no
adverse
impact
expected
to
occur
for
those
industries
that
produce
output
affected
by
the
final
rule,
such
as
lumber
and
wood
products,
chemical
manufacturers,
petroleum
refining,
and
furniture
manufacturing.

Small
Entity
Impacts
After
considering
the
economic
impact
of
the
final
rule
on
small
entities,
we
have
determined
that
the
final
rule
will
not
have
a
significant
economic
impact
on
a
substantial
number
of
small
entities.
Based
on
SBA
size
definitions
for
the
affected
industries
and
reported
sales
and
employment
data,
EPA
identified
185
of
the
576
entities,
or
32
percent,
owning
affected
facilities
as
small
entities.
Although
small
entities
represent
32
percent
of
the
entities
within
the
source
category,
they
are
expected
to
incur
only
4
percent
of
the
total
compliance
costs
of
$
862.7
million
(
1999
dollars).
There
are
only
ten
small
entities
with
compliance
costs
equal
to
or
greater
than
3
percent
of
their
sales.
In
addition,
there
are
only
24
small
entities
with
cost­
to­
sales
ratios
between
1
and
3
percent.
An
economic
impact
analysis
was
performed
to
estimate
the
changes
in
product
price
and
production
quantities
for
the
final
rule.
As
mentioned
in
the
summary
of
economic
impacts
earlier
in
this
preamble,
the
estimated
changes
in
prices
and
output
for
affected
entities
is
no
more
than
0.05
percent.
For
more
information,
consult
the
docket
for
the
final
rule.
It
should
be
noted
that
these
small
entity
impacts
are
in
advance
of
any
facility
demonstrating
eligibility
for
the
healthbased
compliance
alternatives.
Depending
on
the
number
of
affected
facilities
demonstrating
eligibility
for
the
health­
based
compliance
alternatives,
the
estimated
small
entity
impacts
fall
to
eight
small
entities
with
compliance
costs
equal
to
or
greater
than
3
percent
of
their
sales,
and
14
small
entities
with
compliance
costs
between
1
and
3
percent
of
their
sales.
The
final
rule
will
not
have
a
significant
economic
impact
on
a
substantial
number
of
small
entities
as
a
result
of
several
E­
3
decisions
EPA
made
regarding
the
development
of
the
rule,
which
resulted
in
limiting
the
impact
of
the
rule
on
small
entities.
First,
as
mentioned
earlier
in
this
preamble,
EPA
identified
small
units
(
heat
input
of
10
MMBtu/
hr
or
less)
and
limited
use
boilers
(
operate
less
than
10
percent
of
the
time)
as
separate
subcategories
different
from
large
units.
Many
small
and
limited
use
units
are
located
at
small
entities.
As
also
discussed
earlier,
the
results
of
the
MACT
floor
analysis
for
these
subcategories
of
existing
sources
was
that
no
MACT
floor
could
be
identified
except
for
the
limited
use
solid
fuel
subcategory,
which
is
less
stringent
than
the
MACT
floor
for
large
units.
Furthermore,
the
results
of
the
beyond­
the­
floor
analysis
for
these
subcategories
indicated
that
the
costs
would
be
too
high
to
consider
them
feasible
options.
Consequently,
the
final
rule
contains
no
emission
limitations
for
any
of
the
existing
small
and
limited
use
subcategories
except
the
existing
limited
use
solid
fuel
subcategory.
In
addition,
the
alternative
metals
emission
limit
resulted
in
minimizing
the
impacts
on
small
entities
since
some
of
the
potential
entities
burning
a
fuel
containing
very
little
metals
are
small
entities.

Social
Costs
and
Benefits
The
regulatory
impact
analysis
prepared
for
the
final
rule
including
the
EPA's
assessment
of
costs
and
benefits,
is
detailed
in
the
"
Regulatory
Impact
Analysis
for
the
Industrial
Boilers
and
Process
Heaters
MACT"
in
the
docket.
Based
on
estimated
compliance
costs
associated
with
the
final
rule
and
the
predicted
change
in
prices
and
production
in
the
affected
industries,
the
estimated
social
costs
of
the
final
rule
are
$
863
million
(
1999
dollars).
Depending
on
the
number
of
affected
facilities
demonstrating
eligibility
for
the
health­
based
compliance
alternatives,
these
annualized
social
costs
could
fall
to
$
746
million.
It
is
estimated
that
5
years
after
implementation
of
the
final
rule,
HAP
will
be
reduced
by
58,500
tpy
due
to
reductions
in
arsenic,
beryllium,
dioxin,
hydrochloric
acid,
and
several
other
HAP
from
industrial
boilers
and
process
heaters.
Studies
have
determined
a
relationship
between
exposure
to
these
HAP
and
the
onset
of
cancer,
however,
there
are
some
questions
remaining
on
how
cancers
that
may
result
from
exposure
to
these
HAP
can
be
quantified
in
terms
of
dollars.
Therefore,
the
EPA
is
unable
to
provide
a
monetized
estimate
of
the
benefits
of
the
HAP
reduced
by
the
final
rule
at
this
time.
However,
there
are
significant
reductions
in
PM
and
in
SO2
that
occur.
Reductions
of
560,000
tons
of
PM
with
a
diameter
of
less
than
or
equal
to
10
micrometers
(
PM10),
159,000
tons
of
PM
with
a
diameter
of
less
than
or
equal
to
2.5
micrometers
(
PM2.5),
and
112,000
tons
of
SO2
are
expected
to
occur.
These
reductions
occur
from
existing
sources
in
operation
5
years
after
the
implementation
of
the
regulation
and
are
expected
to
continue
throughout
the
life
of
the
affected
sources.
The
major
health
effect
that
results
from
these
PM
and
SO2
emissions
reductions
is
a
reduction
in
premature
mortality.
Other
health
effects
that
occur
are
reductions
in
chronic
bronchitis,
asthma
attacks,
and
work­
lost
days
(
i.
e.,
days
when
employees
are
unable
to
work).
While
we
are
unable
to
monetize
the
benefits
associated
with
the
HAP
emissions
reductions,
we
are
able
to
monetize
the
benefits
associated
with
the
PM
and
SO2
emissions
reductions.
For
SO2
and
PM,
we
estimated
the
benefits
associated
with
health
effects
of
PM,
but
were
unable
to
quantify
all
categories
of
benefits
(
particularly
those
associated
with
ecosystem
and
environmental
effects).
Unquantified
benefits
are
noted
with
"
B"
in
the
estimates
presented
below.
Our
primary
estimate
of
the
monetized
benefits
in
2005
associated
with
the
implementation
of
the
proposed
alternative
is
$
16.3
billion
+
B
(
1999
dollars).
This
estimate
is
about
$
15.3
billion
+
B
(
1999
dollars)
higher
than
the
estimated
social
costs
shown
earlier
in
this
section.
These
benefit
estimates
are
in
advance
of
any
facility
demonstrating
eligibility
for
the
health­
based
compliance
alternatives.
Depending
on
the
number
of
affected
facilities
demonstrating
eligibility
for
the
health­
based
compliance
alternatives,
the
benefit
estimate
presuming
the
health­
based
compliance
alternatives
is
$
14.5
billion
+
B,
which
is
$
1.7
billion
lower
than
the
estimate
for
the
final
rule.
This
estimate
is
$
13.8
billion
+
B
higher
than
the
estimated
social
costs
presuming
the
health­
based
compliance
alternatives.
The
general
approach
to
calculating
monetized
benefits
is
discussed
in
more
detail
earlier
in
this
preamble.
For
more
detailed
information
on
the
benefits
estimated
for
the
final
rule,
refer
to
the
RIA
in
the
docket.

Energy
Impact
Analysis
As
mentioned
in
the
economic
impact
analysis,
the
reduction
in
petroleum
product
output,
which
includes
reductions
in
fuel
production,
is
estimated
at
only
0.001
percent,
or
about
68
barrels
per
day
based
on
2000
U.
S.
fuel
production
nationwide.
That
is
a
minimal
reduction
in
nationwide
petroleum
product
output.
The
reduction
in
coal
production
is
estimated
at
only
0.014
percent,
or
about
3.5
million
tpy
(
or
less
than
1,000
tons
per
day)
based
on
2000
U.
S.
coal
production
nationwide.
The
combination
of
the
increase
in
electricity
usage
estimated
with
the
effect
of
the
increased
price
of
affected
output
yields
an
increase
in
electricity
output
estimated
at
only
0.012
percent,
or
about
0.72
billion
kilowatt­
hours
per
year
based
on
2000
U.
S.
electricity
production
nationwide.
All
energy
price
changes
estimated
show
no
increase
in
price
more
than
0.05
percent
nationwide,
and
a
similar
result
occurs
for
energy
distribution
costs.
We
also
expect
that
there
will
be
no
discernable
impact
on
the
import
of
foreign
energy
supplies,
and
no
other
adverse
outcomes
are
expected
to
occur
with
regards
to
energy
supplies.
All
of
the
results
presented
above
account
for
the
pass
through
of
costs
to
consumers,
as
well
as
the
cost
impact
to
producers.
For
more
information
on
the
estimated
energy
effects,
please
refer
to
the
economic
impact
analysis
for
the
final
rule.
Depending
on
the
number
of
affected
facilities
demonstrating
eligibility
for
the
health­
based
compliance
alternatives,
the
reduction
in
petroleum
product
output,
which
includes
reductions
in
fuel
production,
could
fall
to
65
barrels
per
day,
or
only
0.001
percent.
The
reduction
in
coal
production
could
fall
to
only
0.010
percent,
or
about
2.5
million
tpy
based
on
2000
U.
S.
coal
E­
4
production
nationwide.
The
combination
of
the
increase
in
electricity
usage
estimated
with
the
effect
of
the
increased
price
of
affected
output
could
yield
an
increase
in
electricity
output
that
could
be
only
0.0067
percent,
or
about
0.40
billion
kilowatt­
hours
per
year
based
on
2000
U.
S.
electricity
production
nationwide.
All
energy
price
changes
estimated
could
now
fall
to
increases
of
no
more
than
0.04
percent
nationwide,
and
a
similar
result
occurs
for
energy
distribution
costs.
There
should
be
no
discernable
impact
on
import
of
foreign
energy
supplies,
and
no
other
adverse
outcomes
are
expected
to
occur
with
regards
to
energy
supplies.
All
of
the
results
presented
with
presumption
of
the
health­
based
compliance
alternatives
also
account
for
the
pass
through
of
costs
to
consumers
as
well
as
the
cost
impact
to
producers.
TECHNICAL
REPORT
DATA
(
Please
read
Instructions
on
reverse
before
completing)

1.
REPORT
NO.

EPA­
452­
R­
04­
002
2.
3.
RECIPIENT'S
ACCESSION
NO.

4.
TITLE
AND
SUBTITLE
Regulatory
Impact
Analysis
for
the
Industrial
Boilers
and
Process
Heaters
NESHAP
5.
REPORT
DATE
February
2004
6.
PERFORMING
ORGANIZATION
CODE
7.
AUTHOR(
S)
8.
PERFORMING
ORGANIZATION
REPORT
NO.

9.
PERFORMING
ORGANIZATION
NAME
AND
ADDRESS
U.
S.
OAQPS
10.
PROGRAM
ELEMENT
NO.

11.
CONTRACT/
GRANT
NO.

12.
SPONSORING
AGENCY
NAME
AND
ADDRESS
Office
of
Air
Quality
Planning
and
Standards
Air
Quality
Strategies
and
Standards
Division
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
includes
benefits,
costs,
and
economic
impacts
for
the
final
Industrial
Boilers
and
Process
Heaters
NESHAP,
which
is
a
MACT
standard.
The
benefits
of
the
rule
are
well
in
excess
of
the
social
costs
($
16.3
billion
compared
to
$
863
million).

17.
KEY
WORDS
AND
DOCUMENT
ANALYSIS
a.
DESCRIPTORS
b.
IDENTIFIERS/
OPEN
ENDED
TERMS
c.
COSATI
Field/
Group
Air
Pollution
control,
Economic
Impacts,
Benefits,
Costs
18.
DISTRIBUTION
STATEMENT
Release
Unlimited
19.
SECURITY
CLASS
(
Report)

Unclassified
21.
NO.
OF
PAGES
310
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
04­
002
Environmental
Protection
Air
Quality
Strategies
and
Standards
Division
February
2004
Agency
Research
Triangle
Park,
NC
Postal
information
in
this
section
where
appropriate.