p.1 

OAR Box 1828 

Prepped by Ollie Stewart 

Document Number: 

291) IV-A-1 

Docket Number: 

A-83-27 

Printed 11/12/200811:12:58 AM Sheet 291 of 325 
P.2 

V 

<>EPA 

United States 

Environmental Protection 

Agency 

TE-/4- J. 

Office of Air Quality 

Planning and Standards 

Research Triangle Park NC 27711 

EPA-450/3-86-0'06 

June 1986 

Air 

Regulatory Impact 

Analysis for New 

Source 

Performance 

Standards: 

IndustrialCommercialInstitutional Steam 

Generating Units of 

Greater than 100 

Million Btu/hr 

Heat Input 

1 

1 

i 
P.3 

« . 

EPA-450/3-86-006 

Regulatory Impact Analysis for New 

Source Performance Standards: 

Industrial-Commercial-lnstitutional Steam 

Generating Units of Greater than 100 

Million Btu/hr Heat Input 

U. S. ENVIRONMENTAL PROTECTION AGENCY 

Office of Air and Radiation 

Office of Air Quality Planning and Standards 

Research Triangle Park, North Carolina 27711 

June 1986 
P.4 

This report has been reviewed by the Emission Standards and Engineering Division of the Office of Air Quality Planning 

and Standards, EPA, and approved for publication. Mention of trade names or commercial products is not intended to 

constitute endorsement or recommendation of use. Copies of the report are available through the Library Services Office 

(MD-35), U.S. Environmental Protection Agency, Research Triangle Park, N.C. 27711, or from National Technical 

Information Services, 5285 Port Royal Road, Springfield, Virginia 22161. 
Contents 

P.5 

ROLE OF THIS DOCUMENT 

EXECUTIVE SUMMARY 

I. Statement of Needs and Consequences 

II. Alternatives Examined 

A. Introduction 

B. No Further Regulation 

C. Other Regulatory Approaches 

D. Market Oriented Approaches 

E. Regulatory Alternatives Within the 

Scope of Present Legislation 

III. Air Quality Data 

A. Introduction 

B. SO4 Air Quality Assessment 

C. SO4 Air Quality Results 

D. PM Air Quality Assessment 

E. SO2 Air Quality Assessment 

IV. Engineering Costs 

A. Introduction 

B. Analytical Framework 

V. Economic Impact Analysis 

A. Introduction 

B. Major Steam Users 

C. Selected Industries 

D. Conclusions 

Page 

vi 

viii 

-1 

I-l 

I-l 

I-l 

1-2 

1-2 

1-5 

II-l 

II-l 

II-l 

II-4 

II-6 

11-6 

V-1 

V-1 

V-1 

V-1 

V-1 

V-1 

V-2 

V-3 
P.6 

11 

Page 

VI. Benefit Analyis VI-1 

A. Introduction VI-1 

B. Methodology VI-2 

C. Study Selection, Application, Qualifications, VI-8 

and Plausibility Checks 

D. Benefit Analysis Estimates VI-32 

VII . Benefit-Cost Analysis VII-l 
m 

Tables 

P.7 

Number 

3 

4 

5 

6 

7 

8 

I-l 

1-2 

1-3 

;i-4 

:i-5 

1-6 

[V-1 

[V-2 

[V-3 

VI-1 

VI-2 

VI-3 

VI-4 

Page 

National Cost Impacts of Regulatory xiv 

Alternatives 

Industrial Boiler NSPS Potential Benefit xvi 

Categories 

Annualized Benefits xviii 

Average Benefits Per Ton xix 

Incremental Benefits Per Ton xx 

Net Benefit Analysis xx 

Average Control Cost Per Ton and Benefit xxi 

Per Ton 

Incremental Control Cost Per Ton and Benefit xxii 

Per Ton 

ASTRAP Matrix 111-3 

1995 Base Case Sulfate Emissions 111-5 

1995 Sulfate Emissions, LSF Alternative 111-7 

1995 Sulfate Emission, Percent Reduction 111-8 

Alternative 

ASTRAP 1995 Estimated Visibility 111-9 

Emissions Data Bases and Growth 111-10 

National Cost Impacts of Regulatory IV-4 

Alternatives 

Average Control Cost Per Ton IV-5 

Incremental Control Cost Per Ton IV-5 

Industrial Boiler NSPS Potential VI-5 

Benefit Categories 

Demand Equations for Which SO2 Is VI-26,27 

A Significant Explantory Variable 

Annualized Benefits VI-33 

Average Benefits Per Ton, SO4 V1-34 
P.8 

IV 

Page 

VI-5 Average Benefits Per Ton, PM VI-35 

VI-6 Average Benefits Per Ton, S02 VI-36 

VI-7 Average Benefits Per Ton, Total VI-37 

VI-8 Incremental Benefits Per Ton, Total VI-38 

VII-1 Net Benefit Analysis VII-2 

VI1-2 Average Control Cost Per Ton and Benefit VI1-3 

Per Ton 

VI1-3 Incremental Control Cost Per Ton and Benefit VI1-3 

Per Ton 
P.9 

Figures 

N TM ^ Page 

VI_1 Description of A1r Quality Scenario VI-2 

VI"2 Basic Steps in Estimating Benefits VI-7 

for An Individual Study 
P.10 

vi 

ROLE OF THIS DOCUMENT 

This regulatory impact analysis (RIA) has been prepared to satisfy 

Executive Order 12291 (1981) which requires preparation of an RIA for every 

"major rule." The proposed regulation is a "major rule" because it could 

result in industry-wide annualized costs, in the fifth year after the 

standards go into effect, of more than $100 million dollars. 

In compliance with the Executive Order, this study evaluates the projected consequences of alternative approaches to regulating new, modified, 

and reconstructed industrial steam generating units. It considers benefits, 

costs and economic impacts. The benefit-cost analysis portion of the RIA 

has not played any role in developing the proposed standards. 

There are several simplifying assumptions which inherently limit the 

precision of this RIA. First, whereas the air quality modeling procedures 

used are an improvement over that used in other similar studies, they 

remain subject to simplifying assumptions regarding growth rates and stack 

characteristics. Second, on the benefit analysis side, there are many 

benefit categories not covered in this analysis and in the case of the 

SO4 and PM benefits, the coverage is limited to the 31 eastern state 

region. There are other assumptions used in this study which are detailed 

in the appropriate sections of this RIA. While these assumptions are 

necessary and reasonable, they limit the precision of the analysis. 
P-11 

VI 1 

REFERENCES 

Executive Order 12291 (1981). Federal Register, Vol. 48, No. 33. In 

Executive Order 12291, the use of the words "major rule" refers to the 

adverse economic consequences of. a regulation. 
P.12 

VI11 

EXECUTIVE SUMMARY 

I. OVERVIEW 

A. Background 

New source performance standards have been proposed limiting emissions 

of sulfur dioxide and particulate matter from new, modified or reconstructed 

industrial-commercial-institutional steam generating units capable of 

combusting more than 29 MW (100 million Btu/hour) heat input. Executive 

Order 12291 states that a RIA must be performed on any regulation having 

an annual effect on the economy of $100 million or more. This RIA was 

prepared for the purpose of fulfillin g this requirement. 

I t should be noted at the outset that in conducting this analysis a 

number of analytical problems had to be overcome. Some of the analytical 

assumptions made may affect the final results. Such assumptions are 

noted in this Executive Summary and discussed in more detail in the text. 

B. Summary of Findings 

This analysis estimates the benefits and costs of two regulatory 

alternatives: 

1) standards based on the use of low sulfur fuel to reduce SO2 

emissions 

2) standards requiring a percent reduction in SOg emissions 

The cost analysis estimated all known private SO2 control costs that 

would be incurred as a result of each of these regulatory alternatives. 

The benefit analysis estimated the potential SO4 visibility improvementbenefits, SO2 related agriculture benefits, residential materials damage 

and morbidity benefits, and PM reduced morbidity and soiling benefits of 

both regulatory alternatives. Potentially large benefit categories such 
P.13 

I X 

as commercial and industrial materials damage and acid deposition, were not 

estimated. Other, most likel y smaller, benefit categories such as climate 

effects and improved transportation safety, have not been included either. 

The net benefit analysis (benefits minus costs) yielded ambiguous 

results. The estimated range of net benefits for the low sulfur fuel • 

alternative yielded positive results . The range of net benefits for the 

percent reduction alternative spanned both positive and negative net 

benefits. Annualized net benefits in the year 1990 for the low sulfur 

fuel alternative, ranged from four million dollars to sixty-two million 

dollars (1983 dollars). In 1990, the percent reduction alternative 

yielded net benefits ranging from a negative forty-two millio n dollars to a 

positive forty-three million dollars (1983 dollars). 

I I . STATEMENT OF NEED AND CONSEQUENCES 

On August 21 , 1979, a priorit y lis t for development of additional 

new source performance standards was published in accordance with Sections 

111(b)(1)(A) and 111(f)(1) of the Clean Air Act Amendments of 1977. This 

lis t identified 59 major stationary source categories that were judged to 

contribute significantl y to air pollution . This lis t did not include 

utilit y boilers since new source performance standards had previously 

been developed for thi s source category. Fossil fuel-fire d industrial 

steam generating units ranked eleventh on the priorit y lis t of sources 

for which new source performance standards would be established. Fossil 

fuel-fire d steam generating units were the highest ranked source of 

particulate matter and sulfur dioxide emissions, and the second highest 

ranked source of nitrogen oxide emissions when the priorit y lis t of 

source categories was published. 

The proposed standard could reduce emissions of sulfur dioxide from 

a typical industrial steam generating unit by between 465 Mg/Year 
P.14 

(510 tons/year) and 2,420 Mg/Year (2,670 tons/year), depending on unit 

size and type of fuel fired. 

The need for regulatory action arises from the failure of the market 

system to deal effectively with air pollution as a negative externality. 

Industrial boilers dispose of unwanted by-products by emitting them to 

the atmosphere. The societal costs associated with those emissions, in 

terms of health and welfare, are not fully paid by the emitters. The 

market place does not function effectively or efficiently when either 

total (private and social) costs and/or benefits are improperly accounted for. 

III . ALTERNATIVES EXAMINED 

Executive Order 12291 requires that the following alternatives be examined: 

a) no further regulation, 

b) other regulatory approaches, 

c) market oriented approached 

d) alternative approaches within the scope of present legislation. 

Alternative a) -- was not found to be reasonable given the Administrator's 

determination that the source category contributes significantly to air pollution 

which could reasonably be expected to endanger public health and welfare. 

Alternative b) — Reliance on BACT and LAER determinations, in lieu of 

NSPS for control of steam generating emissions, was found undesirable. 

The primary reason for this is the determination that NSPS, in practice, 

sets the "floor" for BACT and LAER determinations. In the absence of 

NSPS, the BACT and LAER control levels would likely be less stringent. 

Alternative c) -- Several market oriented approaches were considered 

including pollution taxes, charges, and permits. The Clean Air Act 

explicitly requires (Section III) that new, modified, and reconstructed 

steam generating units control emissions to the level achievable by the 
P.15 

XI 

best demonstrated technological system of continuous emission reduction, 

considering costs, nonair quality health, and environmental and energy 

impacts. This effectively precludes the use of pollution taxes and 

subsidies as alternatives to NSPS unless the exact level of taxes and 

subsidies could be established that would achieve pollution abatement 

equivalent to the level achievable by best demonstrated technology. In 

the case of permits, the number of permits and emission allowances would 

have to be correctly fixed in advance. 

Alternative d) -- A number of regulatory alternatives based on th.e 

use of low sulfur fuels to reduce SO2 emissions or the use of flue gas 

desulfurization (FGD) systems to achieve a percent reduction in SO2 

emissions were examined in developing the proposed NSPS. For purposes of 

this RIA, two alternative control levels were examined and compared to 

the regulatory baseline. 

1) Regulatory Baseline 

Defined by existing State Implementation Plans and the 

existing NSPS for large steam generating units of more than 73 

MW (250 million Btu/hour) heat input. 

2) Low Sulfur Fuel 

Based on the use of low sulfur fuel to reduce emissions to 

344 ng SO2/J (0.8 lb S02/million Btu) heat input from oil 

combustion and to 516 ng SO2/J (1.2 lb S02/million Btu) heat 

input from coal combustion. 

3) Percent Reduction 

Based on the use of FGD systems to achieve a 90 percent 

reduction in SO2 emissions from both oil and coal combustion. 

This alternative would reduce emissions from coal combustion to 
P.16 

XII 

less than 258 ng SO2/J (0.6 lb S02/million Btu) heat input and 

from oil combustion to less than 129 ng SO2/J (0.3 lb S02/million 

Btu) heat input. 

IV. AIR QUALITY DATA 

Regional air quality analysis was conducted using transfer matrices 

derived from the Advanced Statistical Trajectory Regional Air Pollution 

(ASTRAP) model. ASTRAP is a regional scale SO2 model that considers 

transport, dispersion, chemical transformation and removal of sulfur 

oxides. As used in this analysis, ASTRAP models SO2 source-receptor 

relationships in the 31 eastern state region. Sulfate reductions were 

estimated for the 31 eastern states, for both regulatory alternatives 

considered, and compared to the 1995 base case. The 1995 base case was 

used, rather than the more appropriate 1990 base case, because it was 

readily available in computer form and there is a less than 2% difference 

in total emissions between the two cases. The percent reduction 

alternative yielded the largest sulfate reductions. These estimated 

sulfate levels were used to calculate visual range improvements due to 

each regulatory alternative. 

The SO4 changes for the 31 eastern states were translated into TSP 

changes and PM benefits were calculated. No estimates of PM ambient air 

reductions due to reduction of PM emissions were included in this analysis. 

The SO2 air quality analysis was conducted primarily using the inventory 

of new industrial boilers provided by the Industrial Fuel Choice Analysis 

Model (IFCAM). SO2 reductions in 1990 were 170,000 tons for the low 

sulfur fuel alternative and 240,000 for the percent reduction alternative. 

In the 31 eastern states, for the two regulatory alternatives, SO2 reductions 
P.17 

xii i 

were 120,000 tons and 175,000 tons respectively. The tons reduced in the 

31-state region are relevant for both the SO4 and PM benefit estimates. 

V. ENGINEERING COSTS 

•National cost impacts due to the regulatory alternatives for new 

industrial fossil fuel-fired steam generating units were analyzed through 

the use of the Industrial Fuel Choice Analysis Model (IFCAM). IFCAM is 

an energy demand model developed to evaluate fuel choice decisions in the 

industrial sector. IFCAM is a highly disaggregated process engineering 

model designed to analyze factors affecting fuel choice decisions. Total 

annualized costs and control costs are presented in Table 1. 

VI. ECONOMIC IMPACT ANALYSIS 

An economic analysis was performed to determine the potential industryspecific economic impacts associated with the percent reduction regulatory 

alternative. Since this control level was the most stringent analyzed, the 

impacts from the low sulfur fuel alternative would necessarily be less severe, 

assuming the distribution of costs across affected industries are the same. 

Seven industries most likely to experience severe impacts were 

analyzed. Product prices were projected to increase from less than 0.01 

to 0.5 percent in 1990 for six of the seven industries, assuming full cost 

pass-through of increased steam costs. Cost as a percent of value added 

was projected to increase by about 0.01 to 0.9 percent in 1990 for these 

six industries, assuming full cost pass-through of increased steam costs. 

The highest increases are projected for the beet sugar refining industry 

due to the fact that the product price is low and steam costs represent an 

unusually high proportion of manufacturing costs. 
P.18 

XIV 

Table 1 

NATIONAL COST IMPACTS OF REGULATORY ALTERNATIVES1.

2 

(Millions 1983 $) 

Regulatory 

Alternative 

Baseline 

Low Sul fur Fuel3 

Percent Reduction^ 

Annualized 

Costs ($/yr) 

3,396 

3,454 

3,531 

An 

Control 

nualized 

Costs ($/yr) 5 

— 

58 

135 

1 These annualized costs are in January 1983 dollars and are therefore slightly 

higher than the June 1982 costs reflected in the Preamble. 

2 Assumed high oil penetration scenario - i.e., assumed lower oil prices than 

in the high coal penetration scenario. 

3 0.8 lb S02/Million Btu - Oil 

1.2 lb S02/Mill ion Btu - Coal 

4 90 Percent Reduction 

5 These are the control costs associated with the steam generating unit NSPS. 

They are measured as additions to the baseline costs. 
P.19 

XV 

In addition, it was concluded that a 90 percent reduction requirement 

would not impair the ability of firms to raise sufficient capital to 

construct fossil fuel-fired steam generating units. 

VII. BENEFIT ANALYSIS 

The benefit analysis quantifies some of the economic benefits attributable to health and welfare improvements of SO2 reductions. Two regulatory 

alternatives were analyzed — low sulfur fuel and percent reduction --

and compared to the regualtory baseline. Benefit coverage includes 

visibility improvement due to sulfate (SO4) reductions, morbidity reductions 

and household soiling reductions due to reduced levels of PM, and residential 

materials damage, morbidity, and agricultural yield reductions due to SO2 

reductions. Geographic coverage for SO4 and PM is the 31 eastern state 

region. Geographic coverage for SO2 includes 113 areas where rrew industrial 

boilers are projected to be built in 1990. All benefits are estimated 

for the year 1990 -- that is, they represent the benefits that would 

accrue from all boilers subject to the NSPS, that were on line in 1990. 

Just as important as the benefit categories that are covered in part or in 

total are those categories not covered at all. Table 2 lists all potential 

benefit categories for the proposed standards and indicates which ones 

are analyzed in this RIA. As can be seen, there are many categories not 

included in this analysis. Although the inclusion of these benefit 

categories would undoubtedly increase the benefit numbers, the magnitude 

«f this increase is not known. Potentially significant benefits are 

omitted from the nonhuman biological effects category (e.g., acid deposition) 

and from the SO4 health effects category. In addition, for the benefit 

categories that are included, there remains incomplete coverage. For 

example, the SO2 benefit estimates include calculations for reductions 
P.20 

XVI 

Table 2 

Industrial Boiler NSPS 

Potential Benefit Categories 

Health Effects 

- Mortality Due to Chronic Exposure 

- Mortality Due to Acute Exposure 

- Morbidity Due to Chronic Exposure 

- Morbidity Due to Acute Exposure 

Soiling and Materials Damage 

- Residential Facilities 

- Commercial, Institutional 

and Industrial Facilities 

Climate and Visibility Effects 

- Local Visibilit y 

- Non-Local Visibilit y 

- Climate 

- Visibilit y at Parks 

- Transportation Safety 

Non-Human Biological Effects 

- Agriculture 

- Forestry 

- Fishing 

- Ecosystem 

SO? 

X 

X 

SO4 Other PM 

X X 

X X 

X * 

X * 

X * 

X X 

NA 

NA 

X 

NA 

NA 

* 

X 

X 

X 

* 

* 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

NA 

NA 

NA 

NA 

X are categories not analyzed in this study. 

* are categories analyzed in this study. 

NA are categories not applicable to the pollutant. 
P.21 

xvii 

in residential materials damage, but no estimates are included for commercial, 

institutional, or industrial facilities materials damage. 

The benefit estimates are exhibited in Table 3. The benefits associated 

with the percent reduction alternative exceed the benefits associated with 

the low sulfur fuel alternative. This reflects the greater improvement in 

air quality that can be achieved when percent reduction is required. Average 

and incremental benefits per ton are displayed in Tables 4 and 5, respectively. 

The average benefits per ton are extremely similar for the regulatory alternatives. Whereas the annualized benefits for the percent reduction alternative 

are approximately 33% greater than benefits for the low sulfur fuel alternative, 

the tons of SO2 reduced under the percent reduction alternative are also 

approximately 30% greater than those under low sulfur fuel. Consequently, 

the benefit per ton estimates are almost identical. 

VIII. BENEFIT-COST ANALYSIS 

A net benefit analysis (benefits minus costs) was conducted for the 

two regulatory alternatives examined. As can be seen in Table 6, there 

are cases where the annualized net benefits are negative. Table 7 presents 

the average costs and benefits per ton and Table 8 presents the incremental 

costs and benefits per ton for the percent reduction alternative over the 

low sulfur fuel alternative. 

The results of the benefit-cost analysis depend, of course, on the 

validity and scope of the estimates of both benefits and costs associated 

with the regulatory alternatives. The wide range of variability in the 

estimated benefits is discussed in Chapter VI. Limitations also exist on 

the cost side. While all known private control costs associated with the 

regulatory alternatives have been estimated, complete coverage of all private 

and social costs is uncertain. The results of the benefit-cost analysis are 

therefore limited in scope. 
Table 3 

Annualized Benefits* 

(Thousands of 1983 dollars)2 

Benefit Category 

SO4 Visibility 

Local 

Non-Local 

PM Morbidity & Soiling 

S02 Health 

SO2 Welfare 

Materials Damage 

Agriculture 

Total 

Low 

1 

8,000 

3,000 

23,000 

2,000 

26,000 

200 

62,000 

Sulfur Fi 

2 

21,000 

11,000 

25,000 

2,000 

26 ,000 

200 

85,000 

Regulatory Alternatives 

Industrial Boiler SO? 

iel3 

3 

41,000 

25,000 

26,000 

2,000 

26,000 

200 

120,000 

Percent Reduct 

1 2 

12,000 

4,000 

35,000 

2,000 

40,000 

200 

93,000 

31,000 

15,000 

38,000 

2,000 

40,000 

200 

126,000 

ion3 

3 

61,000 

35,000 

40,000 

2,000 

40,000 

200 

178,000 

1 The benefit assessment only includes a subset of potential benefits. 

2 Benefits are for the year 1990, in 1983 dollars. 

3 A range of benefits (1,2,3) is presented for SO^ and PM to reflect sensitivity analysis on the air quality 

modeling and economic valuation inputs. 

X 

< 
P.23 

XIX 

Table 4 

Average Benefits per Ton1 

Totals (SO4. PM, and SO?) 

Regulatory B/T 

Alternative2 (1983 $) 

Low Sulfur Fuel/1 450 

Low Sulfur Fuel/2 640 

Low Sulfur Fuel/3 930 

Percent Reduction/1 470 

Percent Reduction/2 660 

Percent Reduction/3 950 

1 The "tons of SOo reduced" used to calculate B/T differ between SO* and 

PM and SO2. This reflects differences in geographic coverage. SO4 

and PM only cover 31 eastern state region. 

2 A range of benefits (1,2,3) is presented for SO4 and PM to reflect 

sensitivity analyses on the air quality modeling and economic valuation 

inputs. 
P.24 

XX 

Table 5 

Incremental Benefits per Ton1»

2 

Totals (S04, PM, and S02)' 

Percent Reduction/1 

Percent Reduction/2 

Percent Reduction/3 

B/T 

(1983 $) 

510 

690 

1000 

1 Percent reduction over low sulfur fuel. 

2 The "tons of S02 reduced" used to calculate B/T differ between SO4 

and PM and SO2. This reflects differences in geographic coverage. 

SO4 and PM only cover the" 31 eastern state region. 

A range of benefits (1,2,3) is presented for S04 and PM to reflect 

sensitivity analysis on the air quality modeling and economic valuation 

inputs.-

Table 6 

Net Benefit Analysis 

(thousands of 1983 dollars) 

Regulatory 

Alternative1 

Low Sulfur Fuel/1 

Low Sul fur Fuel/2 

Low Sul fur Fuel/3 

Percent Reduction/1 

Percent Reduction/2 

Percent Reduction/3 

Total 

Annualized 

Benefits 

62,000 

85,000 

120,000 

93,000 

126,000 

178,000 

Total 

Annualized 

Control Costs 

58,000 

58,000 

58,000 

135,000 

135,000 

135,000 

Annualized 

Net Benefits 

4,000 

27,000 

62,000 

-42,000 

-9,000 

43,000 

A range of benefits (1,2,3) is presented for SO4 and PM to reflect sensitivity 

analysis on the air quality modeling and economic valuation inputs. 
P.25 

XXI 

Table 7 

Average Control Cost Per Ton and Benefit Per Ton1 

(1983 $) 

Average Average 

Regulatory Alternative2 C/T B/T 

Low Sulfur Fuel/1 340 450 

Low Sulfur Fuel/2 340 640 

Low Sulfur Fuel/3 340 930 

Percent Reduction/1 560 470 

Percent Reduction/2 560 660 

Percent Reduction/3 560 950 

1 The "tons of SO2 reduced" used to calculate B/T differ between SO* and 

PM and SO2. This reflects differences in geographic coverage. SO4 and 

PM only cover 31 eastern state region. 

2 A range of benefits (1,2,3) is presented for SO^ and PM to reflect 

sensitivity analysis on the air quality modeling and economic valuation 

inputs. 
P.26 

XX11 

Table 8 

Incremental Control Cost Per Ton and Benefit Per Ton i»2 

(1983 $) 

Percent Reduction/1 

Percent Reduction/2 

Percent Reduction/3 

Incremental 

C/T3 

1100 

1100 

1100 

Incremental 

B/T3 

510 

690 

1000 

• The "tons of SO2 reduced" used to calculate B/T differ between SO* and 

PM and SO2. This reflects differencies in geographic coverage. SO4 and 

PM only cover 31 eastern state region. 

2 A range of benefits (1,2,3) is presented for SO4 and PM to reflect sensitivity 

analysis on the air quality modeling and economic valuation inputs. 

3 Percent reduction over low sulfur fuel. 
P.27 

x x m 

IX. CAVEATS AND QUALIFICATIONS 

Many caveats and qualifications with regard to the air quality 

modeling and benefit analysis are presented in the body of the RIA. Some 

of the more important qualifications are mentioned below along with the 

potential impacts on the results of the analysis. 

The most important qualification concerns the benefit coverage. As 

can be seen in Table 2 there are many, potentially significant categories 

omitted or only partially covered.' Thus, total benefits will actually be 

greater than those reported, and net benefits will be larger. It is 

impossible to know the magnitude of this effect with any precision. 

Geographic coverage is also limited. Since SO4 and PM calculations 

only include the 31 eastern states, potentially significant benefits from 

the western states and Canada are omitted. The inclusion of these areas 

in the benefit calculations could only increase the annualized benefits 

and net benefits. 
I-l 

I. STATEMENT OF NEEDS AND CONSEQUENCES 

The proposed standards implement Section 111 of the Clean Air Act 

and are based on the Administrator's determination that emissions from 

industrial-commercial-institutional steam generating units cause, or 

contribute significantl y to , air pollution which may reasonably be expected 

to endanger public health or welfare. The intent is to require new, 

modified, and reconstructed industrial-commercial-institutional steam 

generating units to control emissions to the level achievable by the best 

demonstrated technological system of continuous emission reduction, 

considering costs, nonair quality health, and environmental and energy 

impacts. The proposed standards apply to steam generating units capable 

of combusting more than 29 MW (100 millio n Btu/hour) heat input. 

On August 21 , 1979, a priorit y lis t for development of additional 

new source performance standards (NSPS) was published in accordance with 

Sections 111(b)(1)(A) and 111(f)(1) of the Clean Air Act Amendments of 

1977. This lis t identified 59 major stationary source categories that 

were judged to contribute significantl y to air pollution that could 

reasonably be expected to endanger public health or welfare. New source 

performance standards had previously been developed for utilit y boilers 

(see EPA 450/3-79-021). Fossil fuel-fire d industrial steam generating 

units ranked eleventh on thi s priorit y lis t of sources for which new 

source performance standards would be established in the future. Fossil 

fuel-fire d industrial steam generating units were the highest ranked 

source of particulate matter and sulfur dioxide emissions, and the second 

highest ranked source of nitrogen oxide emissions when the priorit y lis t 

of source categories not regulated by NSPS was published. 
P.29 

1-2 

Fossil and nonfossil fuel-fire d steam generating units are significant 

sources of emissions of three major pollutants: particulate matter (PM), 

sulfur dioxide (SO2), and nitrogen oxides (NOx). As discussed in 

"Prioritie s for New Source Performance Standards Under the Clean Air Act 

Amendments of 1977" (EPA-450/3-78-019), in the absence of the proposed 

standards, emissions from industrial-commercial-institutional steam 

generating units with a heat input capacity of 3 through 73 MW (10 through 

250 millio n Btu/hour) would contribute approximately 9 percent of the 

total national SO2 emissions from major sources in 1990. 

The proposed regulation would require al l coal-fired industrialcommercial-institutional steam generating units equipped with conventional 

SO2 emission reduction technologies to achieve a 90 percent reduction in 

SO2 emission and meet an emission limi t of 516 ng SO2/J (1.2 l b S02/million 

Btu) heat input. Coal-fired steam generating units using an emerging 

technology for SO2 control would be required to achieve a 50 percent 

reduction in SO2 emissions and meet an emission limi t of 258 ng SO2/J 

(0.6 l b S02/mil1 ion Btu) heat input. Steam generating units firin g 

mixtures of coal with any other fuel (except oil ) and having an annual 

capacity utilizatio n factor for coal of less than 30 percent (0.30) would 

be required to meet an SO2 emission limi t of 516 ng SO2/J (1.2 l b 

S02/million Btu) heat input. 

The proposed standards would require al l oil-fire d industrialcommercial-institutional steam generating units equipped with conventional 

SO2 emissions and meet an emission limi t of 344 ng S02/million Btu) heat 

input. Oil-fire d steam generating units using an emerging technology to 

control SO2 emissions would be required to achieve a 50 percent reduction 
P.30 

1-3 

in SO2 emissions and meet an emission limi t of 172 ng SOg/J (0.4 l b 

S02/mil 1 ion Btu) heat input. Steam generating units firin g oi l and 

meeting an S02 emission limi t of 86 ng S02/J (0.2 lb S02/million Btu) or 

less would not be required to achieve a further percent reduction in SO2 

emissions. The emission limi t for steam generating units firin g a mixture 

of coal and oi l would be determined by proration. 

The proposed standards could reduce emissions of particulate matter 

from a typical oil-fire d industrial-commercial-institutional steam 

generating unit by about 49 Mg/year (54 tons/year). 

In the fift h year after thi s NSPS becomes applicable, nationwide 

emissions of SO2 could be decreased by between 240,000 and 281,000 Mg/year 

(263,000 and 310,000 tons/year) compared with projected emission levels 

under the regulatory baseline. 

National ambient air quality standards have been established for SO2 

because of it s known adverse effects on public health and welfare. Impacts of thi s pollutant have been documented in the SO2 Criteri a Document 

prepared under Section 108 of the Clean Air Act. These effects are the 

primary basis for the determination that emissions from industrial-commercial 

institutiona l steam generating units wil l continue to be located in urban 

areas where a large population .will be exposed to the emissions. Therefore, 

the present concentration of steam generating units in industrialized 

urban areas wil l continue to contribute to local and regional air pollution . 

For these reasons the source category of industrial-commercial-institutional 

steam generating units was selected for development of standards of , 

performance. 
P.31 

1-4 

REFERENCES 

U.S. EPA (1985). Standards of Performance for New Stationary Sources, 

Industrial-Commercial-Institutional Steam Generating Units, Draft 

Preamble. 
P.32 

II-l 

II. ALTERNATIVES EXAMINED 

A. Introduction 

This section briefly presents potential alternatives to the proposed 

regulation. The E.O. requires that EPA examine regulatory alternatives 

that would mitigate or eliminate the environmental problem as described 

in the Statement of Needs and Consequences. The format of this section 

follows the requirements of E.O. 12291 that the following alternatives be 

examined: 

a) no further regulation, 

b) other regulatory approaches, 

c) market oriented approaches, 

d) alternative approaches within the scope of present legislation . 

Although E.O. 12291 requires that al l alternatives be examined, only the 

most promising ones need be analyzed in detail . 

B. No Further Regulation 

A decision not to further regulate steam generating units would 

result in a reliance on current control levels . The regulatory baseline 

represents the current level of control required by existing State 

implementation plans and the existing NSPS (40 CFR Part 60, Subpart D) 

applicable to steam generating units of more than 73 MW (250 millio n 

Btu/hour) heat input. I f only current control levels were maintained, 

SO2 emissions would be 240,000 to 281,000 Mg/year (263,000 and 310,000 

tons/year) greater than they would be under the proposed regulation, in 

the fift h year after proposal. The Administrator has determined that 

thi s level of air pollution could reasonably be expected to endanger 

public health and welfare. For thi s reason thi s source category was 
P.33 

II-2 

selected for development of standards of performance. This option is 

discussed in later sections of the RIA as the baseline for the evaluation 

of other regulatory alternatives. 

C. Other Regulatory Approaches 

The regulatory alternative to NSPS for controlling emissions from steam 

generating units is reliance on Best Available Control Technology (BACT) and 

Lowest Achievable Emission Requirement (LAER) in attainment and nonattainment 

areas respectively. BACT and LAER determinations are made on a case by 

case basis. Through review and analysis of current BACT and LAER levels 

it has been determined that the applicable NSPS sets a "floor," or minimum, 

on the level of control that is required. Therefore, the existence and 

stringency of the applicable NSPS has a significant influence on the 

eventual BACT or LAER determination. The importance of NSPSs to the BACT 

and LAER process takes on even greater significance in practice, given 

that the majority of BACT and LAER determinations appear to be set "by 

default" equivalent to the applicable NSPS. 

D. Market Oriented Alternatives 

There are several market oriented approaches that can be considered 

alternatives to regulating steam generating units under NSPS. These 

approaches include pollution taxes, marketable permits, and subsidies. 

1) Taxes 

This policy would require a tax on each unit of pollution emitted. 

Firms would then choose the amocmt of pollution abatement that minimized 

their total cost, including the pollution tax. Pollution is abated until 

the marginal cost of abatement is equal to the pollution tax. The regulatory agency would have to set the level of the tax in a manner that would 
II-3 

result in the desired level of air quality. While conceptually possible, 

and in terms of economic efficiency appealing, the pollution tax that 

ensures the acceptable level of air quality would have to be done on a 

case-by-case basis. 

2) Permits 

A permit system would allow a pollution source to purchase a 

permit in order to emit a specific amount of a pollutant over a specified 

period of time at a specified location. A fixed number of permits would 

be issued and auctioned off to the highest bidders. Alternatively, the 

permits could be distributed among the sources, who could then trade 

these permits as they see fit. If the number of permits and emission ' 

allowances were correctly fixed in advance, then the desired air quality 

would be achieved. Again, this may be difficult in areas with numerous 

and diverse sources. 

3) Subsidies 

A subsidy system pays sources for each unit of pollution that 

they do not emit. This can take the form of direct payments or tax 

credits. Subsidies and taxes are similar in that both increase the 

opportunity cost of polluting. Each unit of pollution emitted has attached 

to it the "cost" of the foregone subsidy. Thus, the subsidy is similar 

to a tax, except in two respects: 

(a) Administratively, there is the problem of determining the actual 

abatement at each source. There must be a determination of what 

pollution levels would have been in the absence of the subsidy, 

and this determination must be adjusted as conditions change. 

These determinations are difficult and may depend upon information 
P.35 

II-4 

from the polluters who obviously have the incentive to understate 

their intended emissions, 

(b) The long-run effects of subsidies may be quite different than 

for permits or taxes since the former increase profit levels or 

incomes for polluting industries and the latter decrease them. 

Thus, in the long-run, subsidies would result in firms entering 

the polluting industry, but permits or taxes would cause firms 

to leave. Consequently, a fixed subsidy rate would tend to 

create pollution levels beyond those that are economically 

efficient. Also, subsidies in the form of investment tax 

credits, would likely increase dependence on capital intensive 

solutions. 

4) Market Oriented Approaches and Clean Air Act Requirements. The 

Clean Air Act (Section III) explicitly requires that new, modified, and 

reconstructed stationary sources such as industrial-commercial-institutional 

steam generating units control emissions to the level achievable by the 

best demonstrated technological system of continuous emission reduction, 

considering costs, nonair quality health, and environmental and energy 

impacts. This precludes the use of pollution taxes as alternatives to 

NSPS unless the exact level of taxation could be established that would 

achieve pollution abatement equivalent to the level achievable by best 

demonstrated technology. The use of subsidies and permits are also 

rejected because of the Act requirements. In the case of permits, the 

number of permits and emission allowances would have to be correctly 

fixed in advance, that would achieve the same level of emission control 

as would otherwise be achieved by the best demonstrated technology. 
II-5 

E. Regulatory Alternatives Within the Scope of Present Legislation 

A range of regulatory alternatives has been carefully evaluated 

based on the use of low sulfur fuels to reduce SO2 emissions or the use 

of flue gas desulfurization (FGD) systems to achieve a percent reduction 

in SO2 emissions. A total of six alternative control levels were examined 

and compared to the regulatory baseline. The six regulatory alternatives 

were each analyzed under two different energy scenarios. This energy 

sensitivity analysis was performed because the magnitude of the economic, 

environmental, and energy impacts associated with various regulatory 

alternatives for new steam generating units is primarily a function of 

the type of fuel selected for each of the units. The type of fossil fuel 

selected for each new steam generating unit is a function of the projected 

prices for coal, oil, and natural gas, as well as the costs associated with 

environmental regulations. For more information on the energy prices 

used in this analysis see, "Regional Forecasts of Industrial Residual 

Fuel Oil and Natural Gas Prices," July 1984. The high oil penetration 

scenario reflects the Agency's best projection of future coal, oil, and 

natural gas prices. Oil prices are relatively low and natural gas prices 

are generally at or above the price of low sulfur residual oil. Under 

this energy price scenario residual oil and natural gas compete for the 

industrial steam generating unit energy market, with residual oil achieving 

a slightly larger share. Coal does not effectively compete in this 

market. 

In response to concerns that this energy pricing scenario might 

underestimate coal penetration in the new industrial steam generating 
P.37 

II-6 

unit energy market, an alternative energy scenario was developed to yield 

higher coal penetration. In this energy scenario, coal prices were 

assumed to remain the same as those discussed for the high oil penetration 

energy scenario. The oil prices used were higher than those used in the 

high oil penetration scenario and were also used to forecast natural gas 

prices. In this high coal penetration scenario coal and natural gas 

compete for the steam generating unit energy market with coal capturing a 

slightly larger share than natural gas. Oil does not effectively compete 

in this market due to the relatively low coal and natural gas prices. 

For a more detailed discussion of the regulatory alternatives and the 

energy scenarios see the Preamble (EPA-450/3-82- ) . 

Due to time and resource constraints, for purposes of this RIA two 

regulatory alternatives were examined. These regulatory alternatives 

were the two most viable candidates to serve as the basis for the proposed 

NSPS. Each alternative is analytically compared to the current 

regulatory baseline. Both regulatory alternatives were analyzed under the 

high oil penetration scenario. This energy scenario was chosen because 

it most accurately reflects current projections of future energy prices. 

1 . Regulatory Baseline 

The regulatory baseline is defined by existing State Implementation Plans and the existing NSPS (40 CFR, Part 60, Subpart D) 

for large steam generating units of more than 73 MW (250 million 

Btu/hour) heat input. 

2. Low Sulfur Fuel 

This alternative is based on the use of low sulfur fuel to 

reduce emissions to 344 ng SO2/J (0.8 lb S02/million Btu) heat 
P38 

II-7 

input from oil combustion and to 516 ng SO2/J (1.2 lb S02/million 

Btu) heat input from coal combustion. 

3. Percent Reduction 

This alternative is based on the use of FGD systems to 

achieve a 90 percent reduction in SO2 emissions from both oil and 

coal combustion. This alternative would generally reduce emissions 

from coal combustion to less than 258 ng/J (0.6 lb S02/miliion 

Btu) heat input and from oil combustion to less than 129 ng/J 

(0.3 lb S02/million Btu) heat input. 
P.39 

II-8 

REFERENCES 

Regional Forecasts of Industrial Residual Fuel Oil and Natural Gas Prices 

July 1984 Energy and Environmental Analysis, Inc. for the U.S. Environmental Protection Agency. 
P.40 

III-l 

III. AIR QUALITY DATA 

A. Introduction 

The estimation of economic benefits for the two regulatory 

alternatives requires the calculation of changes in population exposure 

from the baseline to each alternative. This, in term, requires knowledge 

of projected air quality changes. 

This section provides a description of the three types of air quality 

data used for the benefit analysis. The first is SO4 data used for visual 

range improvement benefits. The geographic coverage is 31 eastern states. 

The air quality changes result from industrial boiler compliance with the two 

regulatory alternatives. PM air quality data is used to estimate PM 

related morbidity risk reduction and residential soiling reduction benefits. 

The geographic coverage for PM benefits is also the 31 eastern state 

region. This second type of air quality data uses the first type of air 

quality data as an input but transforms the changes in SO4 to changes in 

TSP. The third type of air quality data is SO2 information used to 

estimate materials damage reductions, agricultural yield reductions, and 

morbidity reduction benefits. The geographic area for the SO2 ambient 

air quality data is 113 areas, spread across the country, where new 

industrial boilers are projected to be located in 1990. 

B. SO4 Air Quality Assessment 

The standards analyzed in this RIA all relate to the local scale 

impacts of sulfur oxide sources. However, it is generally recognized 

that SO2 emissions also have regional scale effects. In the atmosphere 

SO2 can be transformed into sulfates (SO4) and both can be transported 

for long distances (>300 km). As a part of the overall RIA the effect of 

SO2 emissions reductions on sulfates and visual range were modeled on a 
P.41 

III-2 

regional scale. The modeling of source-receptor relationships on any 

geographic scale and for any pollutant is difficul t and involves some 

uncertainty. Modeling of regional scale transport, dispersion, chemical 

transformation and removal of sulfur oxides is quite difficul t and involves 

a number of uncertainties. Nevertheless over the past several years a 

number of models have been developed. Although no models have been 

tested using an adequate array of air qualit y meteorology data, comparisons 

of model results with long-term data suggest that these models are now at 

a stage of development that they can be used to provide some insight into 

the magnitude and nature of air quality changes that might result from 

emission reduction scenarios. "For purposes of thi s RIA, transfer matrices 

were derived from the Advanced Statistica l Trajectory Regional Air Pollution 

(ASTRAP) model and visual range was estimated outside the model/matrix 

using the matrix generated SO4 concentrations. ASTRAP is a regional 

scale SO2 model that considers transport, dispersion, chemical transformation and removal of sulfur oxides. As used in thi s analysis, ASTRAP 

models SO2 source -receptor relationships in the 31-eastern state 

region. A description of the ASTRAP matrix follows in Table III-l . 

Transfer matrices assume that concentrations at a given receptor 

equal the sum of al l partial contributions. Thus, the concentration C at 

receptor A could be represented as: 

CA = TA1 * Ei + TA2 * E2 + .. . + TAJ * Ej 

where Ej is the emission rate from the JJH source region and TAj is a proportionalit y coefficient relating region T emissions to region A concentrations. 

An array of these TAj coefficients can be generated from running the ful l model 

and constitutes a transfer matrix. Transfer matrices are extremely inexpensive 

and easy to apply compared to ful l regional scale model runs. However, they 
P.42 

III- 3 

TABLE III- l 

ASTRAP Matrix 1 

1) 

2) 

3) 

4) 

5) 

6) 

7) 

8) 

CRITERIA 

Model Domain 

Transformation 

Rates2 

Return Flows 

Treatment of 

Emission 

Releases 

Background Factors 

Meteorology 

Western State 

Emissions 

(Outside 31 -

State Region) 

Canadian Emissions 

ASTRAP 

48 States, plus Canada 

Winter 0.53 

Spring 1.0 

Summer 2.0 

Fall 0.7 

Addresses return flows from Atlanti c 

Considers low level releases as well as 

elevated releases' 

None 

1976 - 1981 

1995 projected; unchanged by alternative 

1995 projected; unchanged by alternative 

1

 Advanced Statistica l Trajectory Regional Air Pollution . 

2

 Expressed as % of SO2 converted to sulfate per hour. 

3

 Approximate daily averages. Actual rates exhibit strong diurnal variation. 
P.43 

III-4 

also carry with them a number of limitations in addition to those inherent to 

the models themselves: 

o The matrix used employs state level source and receptor regions. 

Therefore, there is some "averaging out" of differences which might 

be apparent with the finer grids used in the models themselves. 

This may be a significant limitation in this analysis because the 

emission changes being modeled vary from source to source, 

o The models/matrices used are linear. There is substantial disagreement as to whether the processes being modeled are in fact 

linear. If non-linear processes were found then the estimates 

used here would not be accurate, 

o In modeling SO4 levels resulting from the two regulatory 

alternatives only emission changes in the eastern 31 state region 

were modeled. Western U.S. and Canadian emissions were modeled 

at their 1995 base level. This was done because the data was 

readily available for the 31 state region. 

In considering the benefits calculations and results, the reader 

should keep these limitations in mind. 

A more complete discussion of regional modeling and transfer matrices 

can be found in the Memorandum of Intent on Transboundary Air Pollution 

(1982). 

C. SO4 Air Quality Results 

The 1995 base case sulfate emissions, estimated from the ASTRAP 

matrix, for the 31 eastern states, are displayed in Table III-2. The base 

case sulfate estimates represent the estimated sulfate levels associated 

with normal growth and retirement of sources but with no change in the 
II1-5 

P.44 

1995 Base 

STATE 

Alabama 

Arkansas 

Connecticut 

Del aware 

Florida 

Georgia 

111inois 

Indiana 

Iowa 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

New Hampshire 

New Jersey 

New York 

North Carolina 

Ohio 

Pennsylvania 

Rhode Island 

South Carolina 

Tennessee 

Vermont 

Virginia 

West Vi rginia 

Wisconsin 

TABLE 111-2 

Case Su 

(pg/m3 

Ifate Estimates 

S04) 

• 

ASTRAP 

ug/m3 

5.2 

3.1 

8.2 

11.5 

4.0 

5.7 

5.5 

8.1 

2.7 

8.5 

2.6 

3.6 

10.9 

6.5 

4.5 

1.4 

3.7 

4.0 

5.6 

10.5 

7.5 

7.8 

9.6 

11.3 

7.1 

6.8 

6.9 

5.1 

9.3 

11.5 

3.1 
P.45 

111-6 

regulatory scenario. Table 111-3 represents the reduction in sulfate 

estimates due to the low sulfur fuel regulatory alternative, along 

with the percent change from the 1995 baseline. Table II1-4 represents 

the same information for the percent reduction alternative. As expected, 

both alternative control levels result in SO4 reductions, with the percent 

reduction alternative resulting in the largest reduction from the 1995 basecase. 

The estimated sulfate levels were in turn used to calculate visual 

range. This calculation uses the results from the ASTRAP model (Tables 

111-3 and 111-4) with an average nonsulfate/sulfate light extinction ratio 

of 1.25. The estimated 1995 baseline visibility is presented in Table 

111-5 along with the visibility improvements due to the low sulfur fuel 

and percent reduction regulatory alternatives. 

D. PM Air Quality Assessment 

The air quality information developed for the SO4 benefit assessment 

is also used for the PM benefit assessment. Specifically, the SO4 changes 

for each state described in the last section are used. The SO4 changes 

are translated into TSP changes by multiplying by 1.4 for the low estimate, 

1.5 for the middle estimate and 1.6 for the high estimate. These factors 

(Bachmann, 1985) are used to account for the weight of ammonia and water 

change in TSP weight associated with the change in SO4. No estimates of 

direct PM emission reductions for alternative standards due to SO2 controls 

such as scrubbing were calculated. Therefore no estimates of PM ambient 

air reductions due to reduction of PM emissions are included in the analysis. 

E. SO2 Air Quality Assessment 

This section describes the principal procedures and assumptions used to 

calculate the SO2 air quality impacts of the two regulatory alternatives. 

The first subsection describes the development of the emissions inventory, 
P.46 

III-7 

TABLE 111-3 

1995 Sulfate Emissions 

Low Sulfur Fuel Alternative 

(ug/m3 and % change from 1995 Base Case) 

STATE ASTRAP 

yg/m3 % Change 

Alabama 5.2 - .8 

Arkansas 3.1 -1.3 

Connecticut 8.2 - .2 

Delaware 11.5 - .2 

Florida 3.9 - .6 

Georgia 5.7 - .5 

111 inois 5_15_ - .3 

Indiana 8.1 - .2 

Iowa 2.6 - .8 

Kentucky 8.5 - .3 

Louisiana 2.5 -3.9 

Maine 3.6 - .1 

Maryland 1CL9 - .2 

Massachusetts 575 - .2 

Michigan 4.5 - .3 

Minnesota 1.4 - .3 

Mississippi 3.6 -1.6 

Missouri 4.0 - .9 

New Hampshire 5^6 - .2 

New Jersey 10.5 - .2 

New York 7.5 - .2 

North Carolina 7.8 - .4 

Ohio 9.6 - .3 

Pennsylvania 11.3 - .2 

Rhode Island IA - .2 

South Carolina 578" - .5 

Tennessee 6.9 - .5 

Vermont 5.1 - .2 

Virginia 9.3 - .3 

West Virginia 11.5 - .3 

Wisconsin 3.1 - .3 
P.47 

III-8 

TABLE 111-4 

1995 Sulfate Emissions 

Percent Reduction Alternative 

(ug/m3 and % change from 1995 Base Case) 

STATE ASTRAP pg/m3 % Change 

Alabama 5.1 -1.0 

Arkansas 3.1 -1.4 

Connecticut 8.2 - .4 

Delaware 11.5 - .4 

Florida 3.9 - .8 

Georgia 5.7 - .6 

111 inois 5_J> - .5 

Indiana 8.1 - .4 

Iowa 2.6 -1.0 

Kentucky 8.5 - .5 

Louisiana 2.5 -4.0 

Maine 3.6 - .3 

Maryland 10.9 - .4 

Massachusetts 575 - .4 

Michigan 4.4 - .6 

Minnesota 1.4 - .7 

Mississippi 3.6 -1.7 

Missouri 4.0 -1.0 

New Hampshire 5^6 - .3 

New Jersey 10.5 - .4 

New York 7.5 - .4 

North Carol ina 7.8 - .7 

Ohio 9.6 - .4 

Pennsylvania 11.3 - .4 

Rhode Island 7.0 - .4 

South Carolina §77 - .7 

Tennessee 6.9 - .6 

Vermont 5.1 - .3 

Virginia 9.2 - .5 

West Virginia 11.5 - .4 

Wisconsin 3.1 - .7 
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P.49 

111-10 

the second the determination of the study areas, and the third the modeling 

approach. 

1. Emissions Inventory 

a) Data Bases 

Four data bases were used to develop the emissions inventory: 

o A point source inventory based on MAP3S (referred to 

as the EES inventory), 

o The unit inventory of utilitie s from the Advanced Utilit y Simulation 

Model (AUSM). 

o The inventory of new industrial boilers provided by 

Energy and Environmental Analysis (EEA) based on the 

Industrial Fuel Choice Analysis Model (IFCAM), 

o The current county-level area source inventory from 

the National Emissions Data System (NEDS). 

Table 111-7 shows which data base was used as the basis for the inventory fo r 

differen t sources. 

TABLE 111-6 

Emissions Data Bases and Growth 

Source Data Base 

Type Category Age EES EEA Growth 

(MAP3S) AUSM (IFCAM) NEDS Applied? 

Point Utilit y Existing x x No 

No 

No 

x No 

Yes 

Area Al l x Yes 

Utilit y 

Industrial 

boilers 

Other 

Al l 

Existing 

New 

Existing 

New 

• -

-

X 

X 

X 

X 

X 
P.50 

I 11-11 

b) Inventory Development 

The development of the inventory can be considered as having taken 

place in a series of steps. 

Utility data was taken from of the AUSM2 unit inventory. AUSM 

contains data on individual utility boilers. Among other data, AUSM 

provides: 

o Location by state and county, 

o Plant name, 

o Startup year if unit is a planned new unit, 

o Retirement year, and 

o Fuel and fuel consumption data. 

However, AUSM did not include the stack parameters required for modeling nor 

a complete set of emissions. 

1. Stack parameters (height, temperature, diameter, volume flow) and 

industrial steam generating unit emissions were added to the AUSM utility 

data. The values used were based on information in the Utility Boiler 

Background Information Document (EPA 450/3-79-021) and EPA engineering 

judgement. Emissions were based on a model 500 MMBtu/hour boiler and were 

made proportional to capacity. It was assumed that Subpart D applied to 

utility boilers with startup dates between 1977 and 1986, inclusive, and 

that Subpart Da applied tb utility boilers with startup dates of 1987 and 

beyond. 

The MAP3S inventory was developed by Brookhaven National Laboratory 

under the MAP3S/RAINE program. The point source data in MAP3S are based 

primarily upon data taken from EPA's NEDS. Some of the NEDS data were 

revised or supplemented during the development of MAP3S (Benkovitz, 1980). 

In developing the EES inventory, missing data were defaulted and inconsistent 
P.51 

111-12 

data were changed as described in Brubaker and Smith, 1984. The nominal 

year of thi s inventory i s 1978. 

2. The EES point inventory was used as the basic data set for 

sources other than utilitie s and industrial boilers . Where possible, 

utilit y boilers in the EES inventory were replaced by utilit y boilers 

from AUSM. These matches were made based on state, county, plant name, 

and boiler size. Where matches could not be made, the EES data was 

retained. The retirement or startup year were retained with the utilit y 

boiler data based on AUSM. 

3. The EEA industrial boiler data was processed to add stack 

parameters (height, temperature, volume flow) based on information in the 

Summary of Regulatory Analysis (EPA 450/3-86-) and EPA engineering judgement. 

Costs and emissions were based on data in the EEA/IFCAM boiler file . 

Boilers burning natural gas in al l three cases (base case, low sulfur 

fuel , and percent reduction were deleted because their SO2 emissions are 

negl igible . 

4 . The EEA file s locate boilers only by federal region. They also 

associate each boiler with a 2-digi t SIC category. Within a particular 

SIC category and region, the EEA boilers were sited at existing plants. 

This sitin g was accomplished in stages. First , the total coal and oi l 

consumption (Btu's/year) in industrial boilers was determined for each 

plant in the region/SIC. Then each EEA boiler was randomly assigned to a 

specific plant with the assignment weighted by the consumption of that 

boiler' s base-case fuel type. Thus, i f plant l' s industrial boilers 

fired twice as many Btu's of coal as the boilers in plant 2, plant 1 

would be twice as likel y as plant 2 to be chosen as the sit e of a particular 

EEA boiler fueled by coal in the base case. 
111-13 

5. The sources in the EEA/MAP3S were screened to eliminate those 

with a maximum 1-hour S02 concentration exceeding 4500 pg/m3. Such large 

maximum concentrations are believed to be due to problems in the data 

base. 

6. The county-level area source emissions from NEDS were used 

without change. 

At thi s point, the inventory can be considered as consisting of the 

following: 

o New industrial boilers from EEA/IFCAM with stack parameters added 

and sited randomly by region/SIC, 

o Utilit y boilers from AUSM2 with stack parameters and industrial 

steam generating unit emissions added and including retirement 

and startup years, 

o Some additional utilit y boilers that could not be matched to AUSM 

from the EES inventory, 

o Other point sources from the EES inventory based on MAP3S with a 

1-hour SO2 impact <4500 pg/m3, and 

0 County-level area source emissions from NEDS. 

These emissions were projected to 1990 and the 113 study areas were 

identified prior to modeling. 

C. Projected Emissions 

In projecting emissions to 1990, no growth rate was applied to 

the following source categories (See Table II1-7): 

0 Utilit y boilers because growth was assumed to be represented 

adequately by the AUSM units scheduled to start-up before 1990, 

0 Industrial boilers because growth was assumed to be represented 

adequately by the boilers in the EEA/IFCAM files , and 
P.53 

111-14 

o Primary copper, lead, and zinc smelters for which no new sources 

are anticipated. 

A l l other point source growth was assumed to occur in place. Growth 

and retirement were projected on a source-by-source basis using two-digit 

SIC state-specific growth rates and two-digit SIC national-average retirement 

values (Smith and Brubaker, 1983). The projected growth and retirement 

were required to meet applicable NSPSs. I f a source's base-year emissions 

exceeded 100 T/yr, the projected growth and retirement were assumed to 

have to meet the BACT. NSPS's were taken from EPA's Cost-Effectiveness 

File (CEF) and BACT was assumed to be the average control of the SO2 

NSPS's in the CEF (97.5% removal). Area sources were grown at state-specific 

population growth rates. 

2. Determining Study Areas 

The 113 study areas were chosen to include al l the plants at which 

EEA/IFCAM boilers had been sited . The study areas were determined 

manually. An initia l attempt was made to locate each EEA/IFCAM at the 

center of a 60 km by 60 km square receptor grid with 6 receptors along 

each edge giving a total of 36 receptors and a grid spacing of 12 km, 

oriented with two edges running north-south. In many cases, however, 

thi s initia l location was modified to reduce the number of receptors 

over water and to avoid overlapping grids . The receptor grids contained 

from 24-48 receptors, had receptor spacings of 10-20 km, and had dimensions 

of from 48 to 150 km. 

The inventory associated with each grid for modeling purposes included 

the point and area sources in al l the counties within about 40-60 km of 

the outer edges of the receptor grid and thus included most of the sources 

which would have an appreciable impact within a particular receptor grid . 
P.54 

111-15 

It should be noted that a particular source, including new EEA/IFCAM 

boilers, could be included in the inventories of 3 or perhaps more study 

areas. However, no double counting occurred because there was no overlap 

of the receptor grids. 

3. Air Quality Modeling 

a) Meteorological Data 

Meteorological data specific to each of the 113 areas in the study 

was not readily available. In lieu of site-specific data, eight locations 

in the continental United States were selected so as to incorporate all 

major geographic variables that might have a large, systematic effect on 

local climate. Hourly meteorological data were obtained from the National 

Weather Service for these locations, and were processed using a modified 

version of the U.S. EPA meteorological data processing program (CRSTER) 

to produce a dataset suitable for use in air quality modeling. In order 

to run the air quality model for some given analysis area, the most 

suitable of these eight meteorological data sets was selected, based upon 

geographic similarity and proximity, and used without further modification. 

The eight locations used in this study were San Francisco, CA; Albuquerque, 

NM; Ellsworth AFB, SD; Columbus, OH; Shreveport, LA; Philadelphia, PA; 

Washington, DC; and Jacksonville, FL. 

An entire year of hourly meteorological data was available for each 

model run. In order to reduce the computing time, so that all areas 

could be handled within the scope of the program, only every fifth day 

was actually modeled. Thus, annual or seasonal extreme values may have 

been underestimated and mean values are subject to uncertainties arising 

from this sampling procedure. 
P.55 

111-16 

b) Air Quality Model 

In order to make reasonable estimates of the required air quality 

variables for each of the 113 areas without the expenditure of unreasonable 

amounts of computer time, an approximate procedure was used for the 

estimating of the contributions from the minor background point sources. 

Briefly, all "major" point sources, defined for this work as those 

with emissions exceeding 300 T/year, were modeled as point sources. The 

remaining minor point sources were treated as clusters, identified based 

on physical proximity, and replaced by an elliptical-shaped "area" 

source. 

The calculation of the 1-hour SO2 concentration at a receptor from a 

point source was done using a recently-developed expression for the mean 

concentration, given that the wind direction is only known to within 10 

degrees. The formula is based on the standard Gaussian model. The 

dispersion coefficients and plume rise values used were computed using 

USEPA-approved algorithms. 

The emission inventory actually used in a model run consisted, then, 

of 1) new and old utilitie s as points, 2) new EEA/IFCAM boilers as points, 

3) old major point sources (those with annual emissions in excess of 300 

T/year), 4) elliptical area sources (simulating the effects of minor point 

sources, i.e. , those with annual emissions less than 300 T/year) and 

5) true area sources, whose emissions were arbitraril y allocated to those 

of the elliptical areas in proportion to their emission rates. 
P.56 

111-17 

REFERENCES 

Memorandum of Intent on Transboundary Air Pollution (1982). Atmospheric 

Sciences and Analysis Work Group 2 Final Report, November 1982. 

Bachmann, John (1985). Memorandum to Tom Walton. Subject: Calculation 

of Visual Range Changes from Predicted Sulfate Changes. June 10, 1985. 

Benkovitz, C. M. (1980). Emission Inventory Progress Report, Brookhaven 

National Laboratory report BNL-51378 UC-11, New York. 

Brubaker, K. L., and A. E. Smith (1984). Air Quality Analyses in Support 

of Regulatory Impact Analysis for SO? NAAQS - Technical Notes, 

unnumbered, Argonne National Laboratory report, Argonne, Illinois . 

Smith, A. E., and K. C. Brubaker (1983). Costs and Air Quality Impacts of 

Alternative National Ambient Air Quality Standards for Particulate 

Matter - Technical Support Document, Argonne National Laboraotyr Report 

ANL/EES-TM-229. 

I 
IV-1 

IV. ENGINEERING COSTS 

A. Introduction 

National cost impacts on new industrial fossi l fuel-fire d steam 

generating units were analyzed through the use of a computer model called 

the Industrial Fuel Choice Analysis Model (IFCAM). This cost analysis is 

described in detai l in "Projected Impacts of Alternative Sulfur Dioxide 

New Source Performance Standards for Industrial Fossil Fuel-Fired Boilers," 

March 1985. IFCAM is an energy demand model developed to evaluate fuel 

choice decisions in the industrial sector over a fiv e to 15-year forecast 

horizon. IFCAM is a highly disaggregated process engineering model 

designed to analyze factors affecting fuel choice decisions in industrial 

boiler energy applications. 

IFCAM assesses the impacts of four sets of factors affecting industrial 

fuel choice: fuel prices, State and Federal energy and environmental 

policy proposals, the costs associated with firin g alternate fuels , and 

other key model parameters such as the expected size distributio n of new 

industrial boilers . The model is capable of estimating the energy, 

environmental, and cost impacts of alternative air emission regulations 

for new industrial boilers . 

B. Analytical Framework 

IFCAM focuses on boiler fuel choice decisions between coal, oil, and 

natural gas. The model determines fuel choices for boilers in each of 

the 10 Federal regions using projected industrial fuel prices and total 

fossil fuel demand that primarily have been generated by the U.S. Department 

of Energy (DOE). For purposes of this analysis, the model must distinguish 

between new industrial boilers, other process heaters, and existing 
P.58 

IV-2 

industrial boilers. Since this is a NSPS, the only category relevant to 

this analysis is the new industrial boilers. 

A very disaggregate representation of industrial energy uses is 

incorporated in IFCAM. Energy use is disaggregated into nine industrial 

subsectors having different growth rates and regional dispersions. Each 

of these industrial subsectors is further divided into boiler and process 

heat applications. 

Industrial boiler energy use is disaggregated by new and existing 

boilers of different sizes and capacity utilizations rates. New and 

existing boilers are classified on the basis of the type of fuel they 

were designed to fire and whether they can be retrofitted to fire 

alternative fuels. Eight size classes are delineated for boilers. There 

are five capacity utilization rate categories for boilers. 

The final level of disaggregation incorporates regional detail. 

Industrial boiler fuel use is divided among Air Quality Control Regions 

(AQCR's). Since a large number of regions are considered by IFCAM, the 

model can portray the variability in the environmental control costs of 

using the various fuels to fire boilers located throughout the country. 

Based on the characteristics of each combustor (size, operating 

rate, pollution control requirements, etc.), capital and nonfuel operating 

costs are generated for the options of choosing oil, gas, or coal. The 

fuel type associated with the lowest after-tax present value (including 

expected fuel expenses) of the total cost of generating energy over the 

investment period is selected. As a final output, the model generates 

total costs (capital, annual operating, maintenance and fuel expenses) of 

using the selected fossil fuel to generate steam. 
P.59 

IV-3 

Table IV-1 presents the total annualized costs and control costs 

for the baseline and two regulatory alternatives examined in this RIA. 

Each alternative is analyzed using the high oil penetration energy scenario. 

The incremental control costs over baseline for the low sulfur fuel 

alternative are $58 million. For percent reduction, the incremental 

control costs over baseline are $135 million. These costs will be used 

in the following sections to analyze economic impacts and to calcualte 

net benefits. Table IV-2 presents average cost per ton data, calculated 

over the regulatory baseline and Table IV-3 presents incremental cost per 

ton data for the percent reduction alternative calculated over the low 

sulfur fuel alternative. 
P.60 

IV-4 

Table IV-1 

NATIONAL COST IMPACTS OF REGULATORY ALTERNATIVES1*

2 

(Millions 1983 $) 

Regulatory 

Alternative 

Baseline 

Low Sul fur Fuel3 

Percent Reduction* 

Annualized 

Costs ($/yr) 

3,396 

3,454 

3,531 

Annualized 

Control Costs ($/yr) 5 

— 

58 

135 

1

 These annualized costs are in January 1983 dollars and are therefore slightl y 

higher than the June 1982 costs reflected in the Preamble. 

2

 Assumed high oi l penetration scenario. 

3

 0.8 l b SOo/Million Btu - Oil 

1.2 l b S02/Million Btu - Coal 

4 90 percent reduction. 

5 These are the control costs associated with steam generating unit NSPS. 

They are measured as additions to the baseline costs. 
P.61 

IV-5 

Regulatory 

Alternative 

Low Sul fur 

Percent Reduction 

Table IV-2 

Average 

Annualized 

Costs (thousands 

of 1983 $) 

58,000 

135,000 

Control Cost Per 

Tons of 

SO2 Reduced 

(thousands) 

170 

240 

Ton 

C/T 

340 

560 

Table IV-3 

1 

Incremental Control Cost per Ton 

Incremental 

Costs (thousands 

of 1983 $) 

Incremental 

Tons SO2 

Reduced (thousands) C/T 

Percent Reduction 77,000 70 . 1100 

1

 Percent reduction over low sulfur fuel . 
P.62 

IV-6 

REFERENCES 

Projected Impacts of Alternative Sulfur Dioxide New Source Performance 

Standards for Industrial Fossil Fuel-Fired Boilers (March 1985). 

Energy and Environmental Analysis, Inc. for the U.S. Environmental 

Protection Agency. 
P.63 

V-1 

V. ECONOMIC IMPACT ANALYSIS 

A. Introduction 

A detailed analysis was undertaken to assess the potential industryspecific economic impacts associated with the most stringent regulatory 

alternative—that requiring a percent reduction in SO2 emissions. See 

"Projected Impacts of Alternative Sulfur Dioxide New Source Performance 

Standards for Industrial Fossil Fuel-Fired Boilers," March 1985. The 

industry-specific impacts associated with the low sulfur fuel alternative, 

would therefore be less than those discussed below. 

The potential industry-specific economic impacts were analyzed in two 

phases. The firs t phase focused on aggregate economic impacts for major steamusing industries and the second phase focused on selected industries that were 

considered likel y to experience the most severe economic impacts. 

B. Major Steam Users 

Potential impacts on steam costs and product prices were estimated based 

on industry-wide averages for eight large industry groups. The groups selected 

for analysis account for approximately 70 percent of domestic industrial steam 

consumption. These eight industry groups were: food; textiles ; paper; chemicals; 

petroleum refining; stone, clay and glass; iron and steel; and aluminum. 

Assuming ful l cost pass-through of increased steam costs, product 

prices in the major industry groups would increase by less than 0.03 

percent. This potential impact represents a maximum product price increase 

-because of the ful l cost pass-through assumption. In some instances, 

increased steam costs would not be completely passed through to product 

prices, and therefore, the impact on product prices would be less . 
P.64 

V-2 

C. Selected Industries 

Seven industries, most likel y to experience severe impacts, were 

selected due to the steam-intensive nature of their operation or the low . 

utilizatio n of their steam generating unit capacity. These industries 

were: beet sugar refining; frui t and vegetable canning; rubber reclaiming; 

automobile manufacturing; petroleum refining ; iron and steel manufacturing; 

and liquor distilling . 

The economic impact analysis examined potential impacts on prices, 

value added, profitability , and capital availability . This analysis was 

based on "model" plants and "model" firms representative of each industry. 

Product prices were projected to increase from less than 0.01 to 0.5 

percent in 1990 for al l except the beet sugar refining industry, assuming 

ful l cost pass-through of increased steam costs. For these same seven 

industries, value added was projected to increase by about 0.01 to 0.9 

percent in 1990 for al l except the beet sugar refining industry, assuming 

ful l cost pass-through of increased steam costs. 

For both product price and value added impacts, the highest increases 

are projected for the beet sugar refining industry. In the case of 

product prices, thi s is due to the fact that the product price is low and 

steam costs represent an unusually high proportion of manufacturing costs 

in the beet sugar refining industry, compared to the other industries 

examined. Similarly , value added impacts are higher since steam costs 

represent an unusually high proportion of the non-raw material costs of 

manufacturing the product in the beet sugar refining industry, compared 

to the other industries examined. 
P.65 

V-3 

Based on the same scenarios outlined above, but assuming "full cost 

absorption" of increased steam costs, return on assets was projected to 

decrease by 0.03 to 2.8 percentage points. Again, these potential impacts 

represent "worst case" projections of the assumption of full cost absorption 

of the increased steam costs. 

Cash flow coverage ratios and book debt/equity ratios showed 

essentially no change for any of the model firms under two different 

debt/equity financing strategies. Consequently, a percent reduction 

requirement would not impair the ability of firms to raise sufficient 

capital to construct fossil fuel-fired steam generating units. 

D. Conclusions 

The industry-specific economic impacts analysis indicates that a 

percent reduction requirement would generally increase product prices and 

value added by less than 1 percent if all steam cost increases were passed 

through to product prices. In addition, assuming absorption of all steam 

cost increases, return on assets would generally decrease by about 3 

percentage points or less. Cash flow coverage and book debt/equity ratios 

showed essentially no change. Therefore, a percent reduction requirement 

would not impose any capital availability constraints on firms. 

As mentioned earlier, a percent reduction requirement is the most 

stringent regulatory alternative considered. Consequently, the industryspecific economic impacts associated with the low sulfur fuel regulatory 

alternative would be less severe than those discussed above. 
P.66 

V-4 

REFERENCES 

Projected Impacts of Alternative Sulfur Dioxide New Source Performance 

Standards for Industrial Fossil Fuel-Fired Boilers (March 1985). 

Energy and Environmental Analysis, Inc. for the U.S. Environmental 

Protection Agency. 
P.67 

VI-1 

VI. BENEFIT ANALYSIS 

A. Introduction 

The economic benefits associated with the Industrial Boiler SO2 NSPS 

reflect the willingness to pay by individuals to be in a preferred state 

(i.e., cleaner air) as opposed to a less preferred state (i.e., dirtier air) 

of the world. In the present analysis, the less preferred state is associated 

with pre-NSPS conditions. In particular, it is assumed that industrial 

boilers for which the NSPS are appl icabie are subject to controls currently 

required by representative State Implementation Plans (SIPs). Conversely, 

the post NSPS scenarios reflect jthe two regulatory alternatives discussed 

previously-low sulfur fuel and percent reduction. 

Although the NSPS are, by design, technology oriented, it is the case 

that emissions reductions achieved translate into improvements in air 

quality. It is the reduction in concentrations associated with the NSPS 

that are the source of the economic benefits. Figure VI-1 portrays the 

situation. At time to, ambient concentrations in a given area may be Cg. 

In the absence of additional controls beyond those currently in place, net 

growth of industrial boilers in the area will lead to higher total emissions and consequently greater ambient concentrations. The point (t]_, C^) 

is an example of this possibility. If additional control programs are 

instituted, emissions will be reduced over some time path, and ambient air 

quality will improve. This is shown by point (ti C2) in Figure VI-1. 

The area which represents the improvement in air quality is the source of 

the benefit estimates. 
VI-2 

P.68 

Concentrations 

Cl + 

C A • 

C 2 + 

(t0.c0) 

^.'(t^.C-) 

tiae 

Figure VI-1. Description of Air Quality Scenario 

The purposes of this chapter are to present the analytical methodology 

and resulting benefit estimates for two of the regulatory alternatives 

being analyzed. The two alternatives are low sulfur fuel and percent 

reduction. The estimated benefits are for the year 1990. That is, the 

benefits are calculated considering all boilers on line, for which the NSPS 

are applicable, in 1990. The discussion which follows is divided into 

sections on Methodology, Study Selection, Application, Qualifications and 

Plausibility Checks, and Estimates. 

B. Methodology 

Ideally, the estimation of potential economic benefits would be 

accomplished using data, assumptions, and modeling techniques developed 

specifically for the analytic objective. In the case of the steam generating unit NSPS, the ideal approach is precluded by project structure, 

time, and resource constraints. Therefore, estimates are based upon existing 
P.69 

VI-3 

studies which address some aspects of the health or welfare implications 

of ambient SO2, SO4 and PM. This approach, which involves transformation 

and extrapolation of existing research and studies, cannot be accomplished 

in a thorough and comprehensive manner without first recognizing the many 

technical problems associated with drawing inferences from studies not 

necessarily designed for the purposes of this analysis. The problems 

stem from a variety of sources, which include limited and sometimes 

conflicting scientific information, paucity of data, and analytic techniques 

which have not always been thoroughly tested. The technical problems 

which exist result in uncertainty regarding the magnitude and precision 

of the empirical economic benefit estimates. In order to deal explicitly 

with this uncertainty, the extrapolation approach to benefit estimation 

requires: 

0 Identification and use of the best data currently available; 

0 Accomplishment of sensitivity analysis when alternative data 

or assumptions exist; 

0 Development of ranges of estimates to demonstrate the level of 

uncertainty associated with different assumptions. 

The above elements serve as the basis for the analytic strategy 

that is used to develop estimates of the benefits for the steam generating 

unit NSPS. The approach begins with a thorough literature search for 

existing studies that could possibly be used in the extrapolation process. 

The quantitative relationships which are contained in or derived from 

the best of the available studies are then used to develop the benefit, 

estimates presented in this analysis. A summary description of the 

approach used is presented in subsequent paragraphs. 
P.70 

VI-4 

1) All categories of potential benefits that might result from 

control strategies needed to meet the alternative steam generating unit SO? NSPS are identified. A review of the SO2 Criteria 

Document and other reports provided a comprehensive listing of 

possible adverse effects. A listing of effects categories is 

presented in Table VI-1 below. 

2) The existing research literature on the potential effects is 

identified, classified and reviewed. All identified studies 

are screened on the basis of several criteria, the most notable 

of which are analytic quality and potential for extrapolation of 

estimates for benefits analysis (e.g., requisite air quality 

data available). As a result of this screening analysis, and 

because of time and resource contraints, it is determined that 

only some of the categories shown in Table VI-1 can be 

estimated. Table VI-1 organizes the potential benefits by 

pollutant and effects categories. 

To comply with the steam generating unit NSPS, either 

compliance fuel is burned or sulfur dioxide emission controls 

are applied. These in turn reduce concentrations of SO2 directly 

and sulfates and particulate matter indirectly (by reducing the 

SO2 precursor). Furthermore, when scrubbers are used to reduce 

SO2 emissions from oil-fired boilers, particulate matter emissions 

may also be reduced below baseline levels. Consequently, compliance 

with the Industrial Boiler NSPS may result in indirect and direct 

reductions in PM concentrations. However, for purposes of this 

study PM benefits are only estimated for the indirect reductions. 
P.71 

VI-5 

Table VI-1 

Industrial Boiler NSPS 

Potential Benefit Categories 

Other 

SO? SOA PM 

Health Effects 

- Mortality Due to Chronic Exposure X X X 

- Mortality Due to Acute Exposure X X X 

- Morbidity Due to Chronic Exposure * X * 

- Morbidity Due to Acute Exposure * X * 

Soiling and Materials Damage 

- Residential Facilitie s 

- Commercial and Industrial Facilitie s 

Climate and Visibilit y Effects 

- Local Visibilit y 

-" Non-Local Visibilit y 

- Climate 

- Vi si bi1it y at Parks 

- Transportation Safety 

Non-Human Biological Effects 

- Agriculture 

- Forestry 

- Fishing 

- Ecosystem 

* 

X 

NA 

NA 

X 

NA 

NA 

* 

X 

X 

X 

X 

X 

* 

• 

X 

X 

X 

X 

X 

X 

X 

* 

X 

X 

X 

X 

X 

X 

NA 

NA 

NA 

NA 

X are categories not analyzed in this study. 

* are categories analyzed in this study. 

NA are categories not applicable to the pollutant. 
P.72 

VI-6 

Direct PM benefits are attributed to the particulate matter 

steam generating unit NSPS (see EPA-450/3-82-006a). 

The coverage of benefits is also limited in other ways. 

The benefits are often incomplete for those effects categories 

where benefits are measured. For example, the SO2 materials 

damage benefits only cover the residential sector. Commercial, 

industrial, and governmental facilities are omitted. Finally, 

as noted previously, there are other categories of effects 

where no benefit estimates are made. See Table VI-1. 

3) Benefits estimates are developed using the quantitative 

relationships from each individual study and the air quality 

improvements postulated for each alternative standard. These 

estimates are accomplished according to a four-step 

procedure as shown in Figure VI-2. The first step is to 

identify the magnitude of the ambient air quality improvement 

that is estimated to occur in each area and year. This is the 

improvement achieved due to implementation of a particular 

standard, relative to a baseline situation reflecting controls 

al ready in place. 

The second step involves estimating the health and welfare 

improvements that might occur as a result of the improvement in 

ambient air quality. This step makes use of the research findings 

extracted from the literature review discussed previously. These 

findings include either linear or nonlinear relationships between 

health or welfare status and ambient concentrations of SO2 and 

SO4. Note that estimates are generally required for each area and 

year in which there is an air quality improvement. 
P.73 

VI-7 

STEP 

1 

Identify air quality improvement 

in area i at year t 

STEP 

2 

Estimate health or welfare 

improvement in area i at year t 

3a 3b I 

STEP 

3 Estimate economic value of the health 

or welfare improvement for i, t 

V 

STEP 

4 

Aggregate over i to obtain 

regional totals 

Figure VI-2. Basic steps in estimating benefits for an individual study. 
P.74 

* 

VI-8 

The third step is to impute an economic value to the estimated 

changes in health and welfare status (Step 3a). For some classes 

of benefits it is possible to estimate economic values directly 

from the air quality improvement (Step 3b). The household sector 

materials benefit estimate is an example of this approach. Studies 

of this type allow direct estimates of the perceived economic value 

of environmental improvements. 

In Step 4, benefits for each area are summed to obtain totals 

commensurate with the control strategy and air quality data. 

4) Total incremental benefit estimates are developed by combining or 

aggregating estimates from the appropriate effects categories. 

Total incremental benefit estimates for each of the alternative 

standards under consideration are required in order to complete a 

benefit-cost analysis of the various policy alternatives. The 

estimates are incremental in the sense they are derived from the 

air quality change associated with going from present existing SIPs 

to controls required for the alternative NSPS analyzed. 

C. Study Selection, Application, Qualifications and Plausibility Checks 

The procedures used to select studies as a basis for the benefit calculations 

are identified in this section. The procedures used for applying the selected 

studies to generate benefit estimates are also described. In addition, the 

qualifications associated with each application and the plausibility checks for 

resulting benefit estimates are discussed. The section is organized by the 

pollutant and effect category for which benefits are estimated. 
P.75 

VI-9 

1 . SO4 Related Benefits 

a) Visual Range 

1) Study Selection 

Because visibilit y is not directl y traded in existing markets, 

benefit estimation methods require the establishment of a hypothetical 

market or identificatio n of complementarity between visual range and 

existing markets. The former method manifests itsel f in contingent 

ranking and contingent valuation surveys elicitin g willingness-to-pay 

estimates from survey respondents. The latte r method generally infers a 

relationship between visual range and residential property markets or 

visual range and the cost of travel to alternative sites (e.g. , national 

parks). 

Several visual range studies have been accomplished in the western 

U.S. The contingent valuation and ranking studies generally focused on 

user and existence values at national parks (Rowe et al . 1980, Schulze 

1981, Rae 1982). The western visual range studies also included contingent 

property value studies for two urban areas: the South Coastal Air Basin 

(Brookshire, et al . 1979, 1980) and the San Francisco Bay Area 

(Loehman, et al . 1981). However, visual range baselines are vastly 

different between the eastern and western U.S., as are the vistas . 

Because studies are available for the eastern U.S. and that is 

the geographic focus of the benefit analysis, the western studies are 

not used. To date, three eastern visibilit y studies have been conducted. 

One study (Randall, et al . 1981) assessed the willingness-to-pay for 

visual range improvement in the Chicago area. Another evaluated the 

willingness-to-pay for visual range improvement in the Cincinnati area 

(Rae, 1984). A thir d (Tolley et al . 1984) assessed the willingness-to-pay 
VI-10 

for visual range improvement in each of six cities (i.e., Atlanta, 

Boston, Cincinnati, Miami, Mobile, and Washington, D.C.) as well as the 

rest of the east. All of the eastern visibility studies used contingent 

valuation or contingent ranking methods. 

The study by Tolley et al. is chosen for this analysis. It covers 

more cities and has a larger sample size than the other studies. It 

also enables an assessment of visual range changes "locally" as well as 

other parts of the east (non-local changes). 

2) Application 

The visual range benefit assessment involves two sets of procedures. 

The first involves using the visual range estimates for each of the 

31 states (Chapter 3, Table III-5) to develop estimates of "local" visual 

range change and "non-local" visual range change. The estimated annual 

visual range change for each state is used for the "local" change. 

The area weighted average visual range change for the 31 eastern states 

covered in the SO4 air quality analyses is the proxy for visual range 

changes in other parts of the east or "non-local" visual range change. 

The area weighted average visual range for the thirty-one state region 

31 

is computed by the formula V31E = Z VjAj where: 

1-1 A 3 1 E 

V31E = 31 eastern state area weighted average visual range. 

V-j = visual range for state i. 

A-j = geographic area of state i. 

^31E

 = tot.^ geographic area of the 31 states. 

The Statistical Abstract provided population estimates for 1980 and 1990 

as well as household estimates for 1980 for each of the 31 eastern 
P.77 

VI-1 1 

states. To calculate the predicted number of households for each of 

the 31 eastern states for 1990 the following steps were taken. First 

the 1980 ratio of households to population for each state was determined 

using the formula RS8Q = H^RCI where: 

PS80 

Rs8o

 = ratio of households to population in state s in 1980 

Hs80

 = numbers of households in state s in 1980 

Ps80

 = population in state s in 1980 

The number of households for 1990 and each state were then estimated 

using the formula Hsgo = Psgo Rs80 where: 

H s t = household in state s in year 1990 

pst = population in state s in year 1990 

Rs80

 = ratio of 1980 households to population in state s 

The second set of procedures entails developing visual range improvement 

valuation coefficients from the Tolley et al. study and applying them to 

the predicted visual range changes. The Tolley et al. study calculates 

the mean bids for the willingness-to-pay for a 10 mile (16.1 kilometer) 

improvement in "local" visual range and changes in the other parts of 

the east. The bids vary widely within and across the six study areas. 

The mean bid for a 10 mile improvement in "local" visual range goes from 

$3.54/year/household/kilometer in Cincinnati to $14.81/year/household/ 

kilometer in Washington, D.C. To reflect some of this variability, range 

and midpoint benefit estimates are developed. The lower estimate applies 

the Cincinnati mean bid to each of the 31 states (i.e., mean bid times 

the air quality change in each state times the population in each state) 

as a measure of the willingness-to-pay for "local" visibility changes. 

Similarly, the Washington, D.C. mean bid is applied to each state to 
VI-12 

generate the higher estimate. The mid-point estimate is derived by 

applying valuation coefficients to each of the 31 states in accordance 

with their nearness to one of the study cities . For example, the mean 

bid for Washington, D.C. i s apportioned to Virginia , Maryland, Delaware, 

etc . 

For the changes in visual range in other parts of the east a similar 

procedure is used to reflec t a range and midpoint estimate. However, 

i t was necessary to compare two types of bid information in Tolley 

et al . (1984). In that study, the exact questions asked survey respondents 

were what would you be willing-to-pay for a visual range improvement 

locall y and for a visual range improvement in the east. There is overlap in 

Jthese revealed preference bids because the "local" area is a part of the 

east. To account for thi s overlap, the "local" bid is subtracted from 

the eastern bid to yiel d the estimate of willingness-to-pay for visual 

range improvements in other parts of the east. For example, in Cincinnati, 

the mean bids derived from the Tolley et al . study are $3.54 for "local" 

and $4.57 for eastern visual range improvements. The value used in thi s 

analysis for visual range improvement in other parts of the east is 

$1.03 (i.e. , $4.57 - $3.54). The $1.03 value from Cincinnati is used to 

generate the lower benefit estimate for visual range improvements in 

other parts of the east while a value of $7.44 (i.e. , $22.25 - $14.81) 

is used to generate the higher estimate. 

An example of the procedure to calculate the low estimate for local 

benefits for the low sulfur fuel regulatory alternative is described below. 

Given the following data for Alabama: 1980 population - 3,890,000; 1980 

number of households - 1,342,000; 1990 projected population - 4,214,000, 
VI-13 

we estimate the number of households in 1990 to be 1,454,000. The low 

estimate for local benefits is the low predicted change in visual range 

(.1 km) times 1,454,000 households times $3.54 per household per kilometer 

change (1982 dollars) times the 1982 to 1983 Consumer Price Index inflato r 

(1.0311311) or $530,740. This number is the estimate of benefits in 1990 

expressed in constant 1983 dollars for local visibilit y for Alabama. 

3) Qualifications and Plausibilit y Checks 

There are certain factors which suggest that the estimates of visual 

range improvement benefits are understated. People in the west may be 

willing-to-pay for visual range improvements in the east, especially at 

the national parks. They have not been included in the benefit assessment. 

Likewise, the control strategies implemented in the 31 eastern states 

could result in visual range improvements in Canada and certain western 

states. These too are omitted from thi s analysis. Finally , a common 

result of the visual range studies conducted to date is that the 

willingness-to-pay for an additional mile of visual range diminishes as 

visual range increases. In other words people appear to be willing-to-pay 

more for the firs t mile of visual range improvement than they do for the 

second, or third . Average visual range in the eastern U.S. is about 10 

miles (16 kilometers). The Tolley et . al . study posited the willingnessto-pay for a visual range improvement of 10 miles (from a base of 10 

miles to a visual range of 20 miles). Consequently, the willingnessto-pay for that firs t mile of visual range improvement could be greater 

than our estimate which assumed a constant bid averaged over the 10 mile, 

change. 

However, there are other factors which suggest the estimates of 

visual range improvement benefits may be overstated in some respects. 
P.80 

• VI-14 

For example, the legitimacy of the benefit estimates is dependent in 

part on the ability of people to perceive the projected visual range 

improvements. The perception threshold for a change in visual range is 

two to five percent for a single visibility event (EPA Report to Congress, 

1979). Depending on the variance of visual range improvements through 

the year, the perception factor could influence the benefit estimate. 

For purposes of this analysis, no threshold was imposed on visibility 

perception. 

The estimates of willingness to pay for non-local changes are based 

on an extrapolation of the difference between local and eastern bids per 

mile change in visual range for a ten mile change and applied to an average 

change in visual range for the thirty-one states. This extrapolation 

presumes that the spatial distribution of visual range changes is unimportant and that the average change is what is valued in the bids. This 

assumption is open to question and less confidence should be placed in 

non-local benefit estimates than in the local benefit estimates. 

Other qualifications to the visual range benefit estimates include 

concern about extrapolating the contingent valuation results from six 

cities to other areas of the east. This extrapolation includes urban to 

rural extrapolation which may be questionable. 

Attempts to assess the plausibility of the benefit estimates are 

limited. A presurvey study in Cincinnati (Rae, 1984) resulted in mean 

bid estimates similar to those developed by Tolley et. al. However, due 

to possible information bias problems, the final survey by Rae in Cincinnati 

yielded mean bid estimates which are much higher than the one used in 

this study. 
P.81 

VI-15 

2. PM 

The PM benefits developed in this analysis are derived from willingness-to-pay estimates in the form of dollars/pg/m3

 reduction in TSP. These 

estimates in turn are derived from earlier Agency directed studies, including 

the PM NAAQS RIA. In this section the study selection, application, 

qualification and plausibility check procedures used in the PM NAAQS work 

are briefly summarized. In addition the procedures, qualifications, and 

plausibility of using those studies to develop estimates of PM benefits 

associated with the steam generating unit NSPS are described. 

a) Chronic Morbidity 

1) Study Selection 

The epidemiological studies amenable for benefit analysis in this 

category include the Ferris et al. (1962, 1973, and 1976) and Crocker 

et. al. (1979) research. The longitutional studies by Ferris et al. 

(1962, 1973, and 1976) in Berlin, New Hampshire were classified by 

the criteria document and staff paper as useful for quantitative 

purposes in PM standard setting. The cross-sectional study by Crocker 

et al., although analytically appealing from a benefit analysis 

perspective, was viewed as not quantitative for purposes of standard 

setting during the development of the SO2 Criteria Document. The Crocker 

study yields higher benefit estimates. However, the Ferris et al. 

study is adopted for purposes of estimating PM benefits associated 

with the SO2 NSPS. 

2) Application 

In the PM NAAQS study, air quality concentration thresholds are 

imposed to avoid going outside the TSP concentration range used by 
P.82 

VI-16 

Ferris et al . in estimating the concentration response relationship. 

The health end point used by Ferris et al . is incidence of chronic 

respiratory disease. After applying the Ferris et al . concentrationresponse relationship, the Health Interview Survey i s used to establish 

a relationship between the change in chronic respiratory disease incidence 

and work loss or restricted activit y days. The geographic unit of 

analysis is the county. The valuation of chronic respiratory disease 

damages included an assessment of los t productivity (i.e. , foregone 

average dail y wage), and increased medical care service charges (i.e. , 

direc t medical expenditures). Of course, the benefit of decreased PM 

concentrations are evaluated as the reduction in the aforementioned 

damages. Benefits are not calculated for reductions in pain and 

suffering prior and subsequent to the receipt of medical care services. 

The average per capita benefit per pg/m3 reduction in annual TSP for 

the counties used in the PM NAAQS analysis ranged from $0.12 to $0.18 

for direc t medical expenditures, $0.15 to $0.21 for reduced work loss 

days per employed worker, and $0.33 to $0.49 per capita reduction in 

reduced activit y days. 

3) Qualifications and Plausibilit y Checks 

Applying a study based on a small area in New Hampshire to estimate 

benefits in 31 eastern states is not without uncertainty. However, the 

fact that the study is judged to be quantitative for purposes of 

standard setting does suggest some underlying credibilit y in the 

benefit estimates. Even so, the benefit estimates for thi s PM category 

are limited . For example, no valuation factor i s applied to the 

residual pain and suffering category. 
VI-17 

b) Acute Morbidity 

1) Study Selection 

The acute morbidity studies amenable for benefit analysis include 

the Samet et. al (1981) longitudinal epidemiological study in Steubenville, Ohio and the cross sectional microepidemiological study by 

Ostro (1983). The Samet et.al. study focused on the relationship of 

emergency room visits to acute respiratory disease. The study was 

classified by the PM staff paper as useful for determining concentration-response relationships in the standard setting. The Ostro study 

focused on broader health end points which related work loss and 

restricted activity days due to respiratory disease to TSP concentrations. The Ostro study was not available in time for inclusion in 

the PM Criteria Document or Staff Paper; but like some other studies 

published later was regarded highly enough that the Administrator 

asked for public comment (PM NAAQS Proposal Preamble) on using the 

study in standard setting. 

The Ostro study provides a more complete geographic and health 

end point assessment than the Samet et. al. study and estimates work 

loss and restricted activity days directly. Hence, it is selected 

for use in estimating PM benefits associated with the steam generating 

unit NSPS. 

2) Application 

Like the chronic morbidity benefits, the geographic unit of analysis 

is the county. Similarly , the damage categories are los t productivity , 

reduced non-work day activities , and increased medical care service charges. 

Furthermore, benefits are not calculated for reduction in pain and suffering 

prior and subsequent to the receipt of medical care services. 
P.84 

VI-18 

3) Qualifications 

Like all epidemiological studies, there is the question of inferring 

causality from the statistically significant relationship. However, unlike 

many other epidemiological studies, Ostro has relatively better control 

for potentially confounding factors although some such as other pollutants 

are omitted. Ostro uses annual average TSP concentrations as the measure 

for exposure for the two-week period for which acute illness is examined. 

The estimated decrease in work loss days due to respiratory causes for a 

10 pg/m3 decrease in TSP is 3.6%. The estimated decrease in restricted 

activities days due to respiratory causes is about 6.7% for a 10 pg/m3 

decrease in TSP. 

c) Household Soiling 

1) Study Selection 

The studies available for benefit assessment include the two Philadelphia studies by Watson-Jaksch and Cummings et al . (1981) and the 24 

SMSA longitudinal study by Mathtech (1982). The firs t two studies are 

developed from a soiling survey (Booze, Allen, Hamilton 1970) designed 

to determine out-of-pocket cost for air pollution induced soiling. 

Watson-Jaksch (1978) analyzed the survey results and found that although 

cleaning expenditures did not change a welfare loss could also be incurred. 

Cummings et al (1981) analyzed the survey and found that by imputing a 

value for the time of the do-it-yourself cleaning activities , which varied 

with pollution levels, welfare losses could also be incurred. 

The Mathtech study (1982) is referenced later in the SO2 section on 

materials damage. As wil l be indicated there, the approach incorporates a 

physical damage function indirectly in the structure of an economic demand 
P.85 

VI-19 

and supply model. Within that framework, household behavior in terms of 

soiling perception, cleaning activity, and expenditures to maintain a 

given degree of cleanliness is estimated econometrically. Prices, environmental variables, and sociodemographic characteristics are inputs to the 

model. 

The Mathtech model is chosen because it is based on more recent 

data, has broader geographic coverage, and uses the theoretically correct 

measure of benefits, willingness-to-pay. 

2) Application 

To apply the model in the PM NAAQS (Mathtech, 1983) analysis, values 

of prices, environmental variables, and socio-demographic characteristics 

for 491 counties are put into the estimated model at the county level. 

The benefits are determined by changing the value of the environmental 

variable (i.e., TSP) to reflect alternative SO2 NSPS or conditions 

with and without TSP air quality improvements. 

3) Qualification and Plausibility 

The Mathtech model was peer reviewed in a public forum and a panel of 

experts found the model and empirical methods to be sound (Mathtech, 1982). 

The predicted level of benefits was judged to be reasonable as a percent 

of household income and relative to previously developed estimates. The 

model is also referenced in the Criteria Document. However, the framework 

of the Mathtech household model does not capture soiling related benefits 

such as the time cost incurred for the do-it-yourselfers or the residential 

location decision. The Mathtech model is limited in other ways. .For 

example, the level of detail for the data inputs of the econometric estimation could have been more refined in the absence of the disclosure 
P.86 

VI-20 

restrictions on the Consumer Expenditure Survey. Application of a model 

based on 24 SMSAs to 491 counties is not without analytic uncertainty, 

d) Extrapolation 

1) Method 

The studies selected for estimating PM benefits associated with reductions in chronic morbidity, acute morbidity, and household soiling were 

used in a related PM generic NSPS study (Mathtech 1984). Rather than 

applying these same studies at a micro level, average benefits estimated 

for this PM generic NSPS study are extrapolated to the PM changes associated 

with the two regulatory alternatives. Of the counties covered in the related PM generic NSPS study 491 are in the 31 eastern states addressed in 

this analysis. The baseline for the PM generic NSPS analysis is current 

PM SIP levels. Projected air quality is with and without 16 currently 

promulgated PM NSPSs. The chronic and acute morbidity and household 

soiling benefits accruing in the year 1990, to the population projected to 

reside in those 491 counties, are calculated for purposes of this analysis. 

For each county, the estimated benefits are divided by population to yield 

a benefit/person figure. This, in turn, is divided by the annual change 

in air quality to yield a benefit/percent pg/m3 reduction TSP figure. 

These figures are summed and divided by the number of counties (i.e. 491) 

to give the $/person/pg/m3 reduction TSP estimate used in this analysis. 

2) Qualifications and Plausibility Checks 

To the extent the air quality scenario in the PM generic NSPS 

analysis is different from that projected in the SO2 NSPS, analysis 

* For example, controlling SO2 emissions results in lower fine particle (i.e., 

£2. 5 um) levels, while NSPS controls for PM emissions result in lower 

concentrations of other particle sizes in addition to fine. 
P.87 

VI-21 

biases of an unknown direction will result. Furthermore, population 

differences between the 31 eastern states and the 491 counties forming 

the basis of this analysis could also impart biases of an unknown 

direction. 

3. SO2 Benefit Assessment 

For purposes of this analysis, the scope of coverage of SO2 benefits 

includes materials damage (household sector), acute and chronic morbidity, 

and agriculture benefits (soybeans, wheat, and oats), 

a) Materials Damage 

1) Study Selection 

There are two elements that are important in selecting models 

that consider materials damage. First, one must evaluate the validity 

of statistical relationships between measures of physical damage (e.g., 

corrosion rates) for a given material and plausible explanatory factors 

such as SO2 concentrations and relative humidity. Second, one must 

consider the soundness of the procedures used to impart economic value 

to the physical damage that is caused. 

The first topic requires a review and critique of the literature on 

physical damage functions. These functions have been reviewed in the 

Criteria Document and the general consensus is that fairly reliable damage 

functions have been developed for ferrous metals and zinc. However, currently available damage functions for exterior paints, stone, masonary, 

concrete, textile, leather, and paper are considered not to be as well 

specified. 

There are three general approaches that have been used to value 

physical damage. Two of the approaches use the physical damage functions 

directly. These approaches have been classified as the value of lost 
P.88 

VI-22 

material method and the cost of ameliorative/preventive action method. 

Examples of the first approach include Salmon (1970) and SRI (1981). 

Examples of the second valuation approach include Fink et al. (1971) and 

TRC (1981). The third approach does not rely on physical damage functions 

directly. Instead, economic demand and supply surveys are estimated as 

factors (Mathtech, 1982). Note however, that the physical damage 

functions can provide supporting information on the types of behavioral 

responses implied by the economic analysis. 

A prime concern in selecting benefit models for valuing material 

damage is the data requirements. Both valuation methods that rely 

explicitly on physical damage functions require information on materials 

inventory, exposure and distribution. These data are most likely 

available only with significant approximation and are most certainly 

available with any degree of accuracy only for selected cities where 

materials surveys have been conducted. It is principally for this 

reason that the calculation of benefits from reduced materials damage 

is limited to the demand/supply model as estimated by Mathtech. 

Although the data used in the Mathtech analysis are limited in some 

respects and interpretations of some of the implied behavioral 

responses have been questioned, the theoretical and empirical methods 

have been judged by several groups to be sound. The Mathtech model 

is an economic demand model which describes relationships between SO2 

and various goods and services that may be purchased by a consumer. 

Thus, the concentration-response function relates SO2 directly to 

economic parameters; there is no intermediate calculation of physical 

damage. In addition to reduced data requirements, the Mathtech model 
P.89 

VI-23 

of materials damage in the household sector has other positive attributes 

that are not shared by the other valuation approaches. The method of 

benefit calculation is based on willingness to pay which is the theoretically correct procedure for measuring welfare change. Also, the 

Mathtech model permits consideration of substitution possibilities. 

2) Application 

Demand equations are estimated for seven commodity groups: food, 

shelter, household operations, home furnishings, clothing, transportation, 

and personal care. Two additional plausible demand categories, property 

expenditures and recreation are not included because of data problems. 

For each of the seven commodity groups, from 2 to 5 goods are separately 

identified and demand equations are also estimated for each of these goods. 

For example, separate equations are estimated for household textiles, 

furniture, appliances, and houseware in the home furnishings commodity 

group. In all, 21 demand equations for goods are estimated. 

Data for the original estimation of the household sector model were 

obtained from several sources. The expenditure data for individual goods 

and specific SMSA's are taken from the U.S. Bureau of Labor Statistics, 

Consumer Expenditure Survey (1978). Retail price data for the same 

SMSA's and goods are also from a Bureau of Labor Statistics publication 

(1973). Air quality data are developed from data maintained by EPA on 

the SAROAD data base. The data base that is constructed covers 24 

SMSA's with budget and environmental data representative of conditions 

in 1972 and 1973. It is assumed that the preferences revealed in the 

1972-73 data can be applied to the time period and areas considered in 

the case study analysis. That is, consumer preferences and relative 

prices remain unchanged. 
P.90 

VI-24 

The procedures used to develop estimates of benefits are quite complex, involving simultaneous evaluation of systems of demand equations. 

The major steps of the calculation routine are highlighted below. 

The first step involves aggregation of market data to form price and 

quantity indices for the 21 goods for which separate demand equations are 

to be estimated. 

Second, the 21 goods are grouped into seven commodity groups. The 

seven commodity groups are consistent with the major divisions defined by 

the Bureau of Labor Statistics for household budget allocations. 

As noted earlier, each .'Of the seven commodity groups contains from 2 

to 5 goods. The third step thus involves the simultaneous estimation of 

demand equations for each good in a given commodity group. It is at this 

stage that the SO2 variables are entered to determine whether they are 

relevant explanatory variables. In addition, several socioeconomic variables are also considered to determine whether they help explain the variation in demand. 

The econometric modeling of the goods demand equations indicated that 

S02 is a significant explanatory variable in three of the equations: home 

repair activities; textiles excluding clothing; and transportation services. These equations are reproduced in Table VI-2. The measure of SO2 

found to be most robust is the 24-hour second high for the monitor recording the maximum 24-hour second high concentration among all receptors.* 

* Additional work is underway to estimate the demand equations using annual 

average values for the pollutant variables and to test specifically for 

non linearities in the pollution effects on demand. 
VI-25 

Table VI-2 

DEMAND EQUATIONS FOR WHICH SOj IS A SIGNIFICANT EXPLANATORY VARIABLE 

P.91 

1. Hoas Repair 

X

l " 0.23288 + 0.767 • (-33.314 • 0.03286 • SO,) • Z. 

- 0.232SS • (-133.27 + 0.11979 • TSP) • Zj 

vhsrs Xj - ths shsxs of hoas xspair sxpsnditnrss rslstirs to all 

szpsaditurss for shsltsr. 

Zj - ths ratio of ths hoas rspair pries iadss to shsltsr 

sxpsnditnrss. 

Zj - ths rstio of ths utility pries indsx to shsltsr 

szpsaditnxss. 

SOj • ths 24 hoar sseoad high asasnrs of SOj for ths aoaitor 

rseordiag ths aaziaaa Ttias of this Taxiabls within ths 

eaas study araa. 

TSP • ths 24 hoax sseoad high asaaaxs of Totsl Saspsadsd Partiealatss fox ths aoaitox rseordiag ths aaziaaa Talus of 

this rsriabls vithia ths eass study arss. This Tilas is 

dsfsaltsd to ths currant priaary NAAQS. 

2. Tsztilss szeludiag elothiag 

X~ - 0.106436 + 0.89334 • (3.23302 + 0.020286 • SO.) • Z, 

- 0.106436 • ((-21.3796 - 37.8934 • FAMSZ > 55.373 * 

REGION) • Z4 + (-50.0434 • 10.3395 • FAMSZ + 2.4711 • 

REGION) • ZPS - 7.33839 • Z6) 

whsrs lm " ths shsrs of tsztils tzpsaditurss relatiTs to all 

szpsaditurss for hoas furnishings. 

Z. • ths ratio of ths tsztils pries indsz to hoas furnishing 

szpsndituzss. 

Zj - ths rsti o of ths furniturs pries indsz to hoas 

furaishiag szpsaditurss. 

2aj • ths ratio of ths spplisaes pries indsz to hoas 

furaishiag szpsaditurss. 
P.92 

VI-26 

Table VI-2 (continued) 

DEMAND EQUATIONS FOR WHICH SOj IS A SIGNIFICANT EXPLANATORY VARIABLE 

Z

6 

so2 

FAMSZ 

REGION 

a 

a 

a 

" 

ths ratio of ths hoassvsrss pries iadsz to hoas 

furaishiag szpsaditurss. 

ths 24 hoar sseoad high asaaars of SOj for ths aoaitor 

rseordiag ths aaziaaa Talus of this rariabls withia ths 

eass study arsa. 

faaily aizs. 

dua ay Tsriabls for loeatioa of eaas stady arsa 

(1-Northsaet or Nozth Csatral* 0>othsrviss). 

3. Traasporatioa Ssrricss 

X

3 

whsrs Xj 

h 

H 

• 

a 

a 

m 

0.53466 + 0.46334 • (-675.609 + 37.1853 • SO.) • Z. 

- 0.53466 • (-377.413 • 28.3191 • TEMP) • Zg 

ths shars of gaaolias szpsaditarss rslstir s to sl l 

szpsaditurss for txaaapoxtatioa. 

ths xstio of ths gaaolias pxies iadsz to sll 

txsaspoxtatioa szpsaditnxss. 

ths xatio of ths pxies iadsz fox ths "other" 

txaaapoxtatioa dsasad eatsgoxy to sll transportation 

sxpsnditnrss. 

SOj • ths 24 hoax sseoad high asasaxs of SOj for ths aonitor 

rseordiag ths aaziaaa rains of this variable within ths 

esss study srsa. 

TEMP - arsrsgs aaaaal tsapsratars ia dsgrsss Cslsius. 
P.93 

VI-27 

It is important to note that these equations are estimated as part of 

a system of demand equations, and by themselves do not lead directly to a 

measure of benefits for reductions in SO2. In fact, a series of steps is 

required before benefits can be ascertained. 

Given the demand equations for goods, the next step involves using 

these equations to define price and quantity indices for the commodity 

category in which they have been placed. Note, in particular, that the 

price index for a commodity will be sensitive to the level of SO2 that is 

used to evaluate the goods demand equations. Since demand for only three 

goods is found to be associated with SO2, only three of the commodity price 

indices will be dependent on SO2. However, since the seven commodity 

groups also form a demand system, the SO2 variable indirectly plays a role 

in the overall budget allocation across commodities. 

With aggregate price and quantity indices defined for the commodities 

the next step involves the simultaneous estimation of the commodity demand 

functions. With the parameters of the commodity demand functions identified, it is now possible to calculate benefits. The goal is to use the 

commodity demand functions to define an expenditure function that is a 

function of SO2. This is accomplished in the following way. 

First, the parameters of the system of commodity demand functions are 

used to define a compensated commodity demand system. The compensated 

curves result from a consumer optimization problem in which the consumer 

minimizes expenditures subject to a constant level of utility. The expenditure function is then formed as the inner product of the commodity 

compensated demand function and the associated price index for all seven 
P.94 

VI-28 

commodities. This procedure is performed with SO2 first at baseline 

(pre-control) levels and then at the two post-control levels - low 

sulfur fuel and percent reduction. The difference between the two 

expenditure functions is a measure of the compensating variation, a 

welfare measure that is consistent with the correct concept of a 

benefits measure: willingness to pay. 

3) Qualification and Plausibility Checks 

Using modeled air quality receptors rather than monitored data as 

was used in the original study may bias the benefit estimate upward. 

Only residential material damage is estimated. Because of the pollution 

index used in the underlying study (24-hour second high for an SMSA) 

and the geographic unit of the underlying study (SMSAs), the impact of 

applying these coefficients to a different area (a rectangular grid 

around an industrial boiler) is unclear. For the 113 study areas analyzed 

benefits calculated on a per-household basis range from 0 to $15.55 

per year for both the low sulfur fuel and percent reduction regulatory 

alternatives. This range reflects the population distribution among 

113 study areas, 

b) Morbidity 

1) Study Selection 

A large number of studies were reviewed to identify sources for 

benefit functions relating SO2 to morbidity. Based on the type of 

exposure, the studies can be divided into three categories: 

Short-term (1-hour), 

Daily (24-hour) 
VI-29 

Short-term Exposure 

For the short-term exposure category, clinica l studies are 

utilized . In the relevant range of SO2, the major effects occur in 

asthmatics. Studies of thi s group examine effects on both lung function 

changes are difficul t to value. There are no estimates of willingness 

to pay for these changes or of the accompanying medical costs. Therefore, 

the analysis considers only effects on symptoms. 

The ful l range of clinica l studies of effects of SO2 on symptom 

prevalence is utilized . The lower-bound estimate is based on the 

pooled results of eight studies. The upper-bound estimate is based on 

work of Kirkpatrick et al . (1982). 

Daily Exposure 

No microepidemiology studies were found to be directl y usable for 

estimating effects of dail y exposure. Among the limitations of the 

studies were failur e to derive quantitative concentration-response 

functions and lack of control of confounding factors . 

Several macroepidemiology studies examine the relationship between 

SO2 and the number of emergency room visit s in an area using timeseries regression analysis. The studies of Mazumdar and Sussman (1981) 

and Graves et al . (1980) were selected to develop a range of benefit estimates. 

2) Application 

For the clinical studies a minimum estimate of zero is used. The 

maximum estimate for each day's symptoms is $25 based on unpublished work 

by Dickie and Gerking and Tolley and Babcock. 

3) Qualifications and Plausibility Checks 

To estimate the benefits using clinical studies, assumptions about 
P.96 

VI-30 

activity levels are derived form the original PM exposure analysis. Doing 

this implicitly assumed the same activity patterns for asthmatics as the 

rest of the population. Inhaled dose is estimated using an assumed 

ventilation rate of 40 liters per minute and a peak concentration of twice 

the hourly concentration. The symptom valuation is an arbitary escalation 

of a study valuing similar symptoms for the general population rather than 

for asthmatics, 

c) Agriculture 

1) Study Selection 

The selection of crops for analysis is governed by the following 

criteria: 

o Crop sensitivity to exposure to SO2; 

0 Information availability for the formulation of a 

dose-response function; and 

0 Significant economic value of the crop. 

Based on application of these criteria, soybeans, wheat, and oats are selected. 

For calculation of benefits, the parameters which define the response 

of a crop to SO2 should reflect its economic value. Yield can be given a value 

in economic terms. While foliar and yield effects may occur together and may, 

in some instances, be highly correlated, yield response cannot generally be 

accurately extrapolated from observed foliar effects of variations in SO2. 

Therefore, study selection is limited to studies of yield effects. The 

additional criteria for study selection are: study focus is on ambient SO2 

exposure and other ambient environmental factors; control for the impact of 

other confounding environmental conditions on the concentration relationship; 

and plausible and quantifiable results which can be used to develop 

concentration response functions. 
VI-31 

Application of these criteria yielded a very limited number of studies 

for each crop. The major study used for soybeans is from Sprugel et al . 

(1980). For oats and wheat, the principal source is a series of reports by 

Guderian and Stratmann (1962 and 1968). 

2) Application 

Average air quality for each receptor area for the same part of the 

growing season as the underlying study uses is applies. The estimate is 

restricted to air quality changes within the underlying study range. Zero 

is used as the minimum estimate. The maximum estimate applies the dose 

response function of the study varietal to all of that crop. One-half the 

maximum estimate is used for the middle estimate. 

3) Qualifications and Plausibility Checks 

The analysis values yield changes at recent state market prices. No 

attempt is made to adjust for price changes that might result from nationwide 

yield changes. No changes in cropping patterns are factored into the 

analysis. No attempt is made to value contributions to yield for sulfur 

deficient soils. 

The yield functions only consider average sulfate concentrations for 

the growing seasons. This ignores impacts of the time pattern of exposure 

(e.g. size and timing of peaks), the impact of other pollutants, and 

interactions with other determinants of yield such as temperature, light, 

soil, and agricultural practice. 

The choice of functional form for the yield function was necessarily 

made with a very limited set of data points. The yield changes are sensitive 

to the functional form. 
P.98 

VI-32 

D. Benefit Analysis Estimates 

The benefit estimates are exhibited in Table VI-3. Ranges are presented 

for SO4 and PM estimates to reflect the uncertainty concerning air quality 

and economic valuation, as discussed in III-B and VI-C, respectively. The 

benefit categories estimated include increased local and non-local visibility 

due to SO4 reductions, reduced chronic and acute morbidity, and reduced 

household (residential) soiling due to PM reductions, and decreased household 

sector materials damage due to SO2 reductions. The SO4 and PM benefit 

estimates are for the 31 eastern state region, while the SO2 benefit estimates 

are nationwide. The benefits associated with the percent reduction regulatory 

alternative exceed the benefits associated with the low sulfur fuel alternative. 

This reflects the greater improvement in air quality that can be achieved 

when percent reduction is required. 

Tables VI-4 - VI-6 report the average benefits per ton of SO2 reduced. 

For SO4 and PM, only the tons reduced from the 31 eastern states are considered. 

For SO2, tons reduced from all 113 areas where new industrial boilers were 

placed, are calculated. 

The benefits per ton are extremely similar for both low sulfur fuel 

and percent reduction, as can be seen in Table VI-7. The annualized 

benefits and the tons of SO2 reduced for the percent reduction alternative 

are approximately 30 - 33% greater than those for the low sulfur fuel 

alternative. Consequently, the benefit per tons estimates are almost 

identical. Table VI-8 presents incremental benefits per ton of percent 

reduction over the low sulfur fuel alternative. 
Table VI-3 

Annualized Benefits* 

(Thousands of 1983 dollars)2 

Benefit Category 

S04 Visibility 

Local 

Non-Local 

PM Morbidity & Soiling 

SO2 Health 

SO2 Welfare 

Materials Damage 

Agriculture 

Total 

Low 

1 

8,000 

3,000 

23,000 

2,000 

26,000 

200 

62,000 

Regulatory ATternat 

Industrial Boiler 

Sulfur F 

2 

21,000 

11,000 

25,000 

2,000 

26,000 

200 

85,000 

uel 

3 

41,000 

25,000 

26,000 

2,000 

26,000 

200 

120,000 

ives3 

S02 

Percent Reduct 

1 

12,000 

4,000 

35,000 

2,000 

40,000 

200 

93,000 

2 

31,000 

15,000 

38,000 

2,000 

40,000 

200 

126,000 

ion 

3 

61,000 

35,000 

40,000 

2,000 

40,000 

200 

178,000 

j 

1 The benefit assessment only includes a subset of potential benefits. 

2 Benefits are for the year 1990, in 1983 dollars. 

A range of benefits (1,2,3) is presented for SO4 and PM to reflect sensitivity 

analysis on the air quality modeling and economic valuation inputs. 

1 

CJ 

CJ 
P.100 

VI-34 

Table VI-4 

Average Benefits per Ton 

SO4 (Total Visibil i 

Regulatory1 

Alternative 

Low Sulfur Fuel/1 

Low Sul fur Fuel/2 

Low Sul fur Fuel/3 

Percent Reduction/1 

Percent Reduction/2 

Percent Reduction/3 

ty) 

(thou 

Annualized 

Benefits 

sands of 1983$) 

11,000 

32,000 

66,000 

16,000 

46,000 

96,000 

Tons S02

2 

Reduced 

(thousands) 

120 

120 

120 

175 

175 

175 

B/T 

90 

270 

550 

90 

260 

550 

1

 A range of benefits (1,2,3) is presented for S04 to reflect sensitivity 

analysis on the air quality modeling and economic valuation inputs. 

2 Tons reduced calculated only for 31 eastern state region. 
VI-35 

p.i 

Particulate Matter 

Regulatory1 

Alternative 

Low Sui fur Fuel/1 

Low Sulfur Fuel/2 

Low Sui fur Fuel/3 

Percent Reduction/1 

Percent Reduction/2 

Percent Reduction/3 

Table VI-5 

Average Benefits per Ton 

Annualized 

Benefits 

(thousands of 1983$) 

23,000 

25,000 

26,000 

35,000 

38,000 

40,000 

Tons S02

2 

Reduced 

(thousands) 

120 

120 

120 

175 

175 

175 

B/T 

190 

210 

220 

200 

220 

230 

1

 A range of benefits (1,2,3) is presented for PM to reflect sensitivity 

analysis on the air quality modeling and economic valuation inputs. 

2 Tons reduced calculated only for 31 eastern state region. 
P.2 

VI-36 

Table VI-6 

Average Benefits per Ton 

SO; 

Annualized Tons SO-?1 

Regulatory Benefits Reduced 

Alternative (thousands of 1983$) (thousands) B/T 

Low Sulfur Fuel 28,000 170 170 

Percent Reduction 42,000 240 180 

1 Tons reduced calculated for al l 113 areas analyzed. 
-EA_ 

VI-37 

Table VI-7 

Average Benefits per Ton 

Totals (SOA, PM, and SO?) 

Regulatory1 B/T 

Alternative (1983 $) 

Low Sulfur Fuel/1 450 

Low Sulfur Fuel/2 640 

Low Sulfur Fuel/3 930 

Percent Reduction/1 470 

Percent Reduction/2 660 

Percent Reduction/3 950 

1 A range of benefits (1,2,3) is presented for S0d and PM to reflect 

sensitivity analysis on the air quality modeling and economic 

valuation inputs. 

Table VI-8 

Incremental Benefits per Ton1 

Totals (S04, PM, and S0 2 )

2 

B/T 

(1983 $) 

Percent Reduction/1 510 

Percent Reduction/2 690 

Percent Reduction/3 1000 

1 Percent reduction over low sulfur fuel. 

2 A range of benefits (1,2,3) is presented for S04 and PM to reflect 

sensitivity analysis on the air quality modeling and economic valuation 

inputs. 
P.4 

VI-38 

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P.5 

VI-39 

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G.D. Labovich (1985). Benefit-Cost Analysis of Selected New Source 

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Mathtech, Inc., (1983). Benefit and Net Benefit Analysis of Alternative 

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Mazumdar, S. and Sussman, N., (1981). Relationships of air pollution to 

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^ 

VI-40 

Rae, D., (1982). "The Value to Visitors of Improving Visibility at Mesa 

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P.7 

VI-41 

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VII-1 

VII. BENEFIT-COST ANALYSIS 

This chapter compares the cost of control for the alternative regulations 

to the benefits estimated for SO4, PM, and SO2. Table VII-1 presents the results of the net benefit analysis (benefits minus costs). Table VI1-2 and 

Table VI1-3 present a comparison of average and incremental benefit per ton 

and cost per ton estimates, respectively. 

As can be seen by examining Table VII-1, there are cases where the 

annualized net benefits are negative. In drawing any conclusions from this 

table, the reader should keep several factors in mind. Foremost, there are 

many benefit categories not included in this analysis. Table VI-1, page 

VI-5 lists all potential benefit categories for the proposed standards and 

indicates which ones are analyzed in this RIA. Of the benefit categories 

that are included, there remains incomplete coverage. For example, the SO2 

benefit estimates only include calculations for reductions in residential 

materials damage. No calculations are included for commercial or industrial 

facilities. Potentially significant benefits are not included from the 

non-human biological effects category (e.g., acid deposition) and from the 

SO4 mortality category. 

In addition, geographic coverage is limited. The SO4 and PM benefit 

calculations only include the 31 eastern states. Potentially significant 

benefits from the western states and from Canada are not included. 

Another important consideration is that the RIA compares a range of 

benefit estimates to a single cost estimate. This inherently implies a 

greater confidence level in the cost estimate than may be justified. If 

costs were also presented as a range of estimates, to reflect uncertainties 

in the underlying assumptions, the comparison of benefits and costs would be 

more valid. 
VI1-2 

Tabl e VII- 1 

Net Benefit Analysis 

(thousands of 1983 dollars) 

P.9 

Regulatory1 

Alternative 

Low Sulfur Fuel/1 

Low Sulfur Fuel/2 

Low Sulfur Fuel/3 

Precent Reduction/1 

Percent Reduction/2 

Percent Reduction/3 

Total 

Annualized 

Benefits 

62,000 

85,000 

120,000 

93,000, 

126,000 

178,000 

Total 

Annualized 

Control Costs 

58,000 

58,000 

58,000 

135,000 

135,000 

135,000 

Annualized 

Net Benefits 

4,000 

27,000 

62,000 

-42,000 

- 9,000 

43,000 

1 A range of benefits (1,2,3) is presented for SO4 and PM to reflect 

senstivity analysi on the air quality modeling and economic valuation 

inputs. 
P.10 

VII- 3 

Table VI1-2 

Average Control Cost Per Ton and Benefit Per Ton 

(1983 $) 

Average Average 

Regulatory Alternative1 C/T B/T 

Low Sulfur Fuel/1 340 450 

Low Sulfur Fuel/2 340 640 

Low Sulfur Fuel/3 340 930 

Percent Reduction/1 560 470 

Percent Reduction/2 560 660 

Percent Reduction/3 560 950 

1 A range of benefits (1,2,3) is presented for S04 and PM to reflect 

sensitivity analysis on the air quality modeling and economic valuation 

inputs. 

Table VII-3 

Incremental Control Cost Per Ton and Benefit Per Ton1 

(1983 $) 

Percent Reduction/1 

Percent Reduction/2 

Percent Reduction/3 

Incremental2 

C/T 

1100 

1100 

1100 

Incremental 2 

B/T 

510 

690 

1000 

1 A range of benefits (1,2,3) is presented for S04 and PM to reflect 

sensitivity analysis on the air quality modeling and economic valuation 

inputs. 

2 Percent reduction over low sulfur fuel. 
p.11 

VII-4 

Due to the limited benefit coverage and geographic/temporal scope 

of this RIA, it is impossible to draw sound conclusions as to whether 

the proposed standards will lead to a welfare improvement for society 

relative to the baseline situation. This RIA has not been designed or 

intended to portray a complete picture of all potential benefits. No 

attempt has been made to quantitatively calculate all benefit categories. 

Thus, total benefits will actually be greater than those reported, and net 

benefits will be larger. While the direction of change in the benefit 

calculation, due to the addition of new benefit categories is known, the 

magnitude of the increase is unknown. 
P.12 

TECHNICAL REPORT DATA 

(Please read Instructions on the reverse before completing) 

1. REPORT NO. 

EPA 450/3-86-006 

3. RECIPIENT'S ACCESSION NO. 

4. TITLE ANO SUBTITLE Regulatory Impact Analysis for New 

Source Performance Standards: Industrial-CommercialInstitutional Steam Generating Units of Greater Than 

100 Million Btu/hr Heat Input 

5. REPORT DATE 

June 1986 

6. PERFORMING ORGANIZATION COOE 

7. AUTHOR(S) 8. PERFORMING ORGANIZATION REPORT NO. 

9. PERFORMING ORGANIZATION NAME ANO ADDRESS 

Office of Air Quality Planning and Standards 

U.S. Environmental Protection Agency 

Research Triangle Park, N.C. 27711 

10. PROGRAM ELEMENT NO. 

11. CONTRACT/GRANT NO. 

12. SPONSORING AGENCY NAME AND ADDRESS 

DAA for Air Quality Planning and Standards 

Office of Air and Radiation 

U.S. Environmental Protection Agency 

Research Triangle Park, N.C. 27711 

13. TYPE OF REPORT AND PERIOD COVERED 

Draft 

14. SPONSORING AGENCY CODE 

EPA/200/04 

15. SUPPLEMENTARY NOTES 

16. ABSTRACT 

New source performance standards limiting emissions of sulfur dioxide (SO.) have been 

proposed for new industrial-commercial-institutional steam generating units with heat 

input capacities above 100 million Btu/hour. Executive Order 12291 states that a 

regulatory impact analysis (RIA) must be performed on any regulation having an annual 

effect on the economy of $100 million or more. This RIA was prepared to fulfill this 

requirement. 

The analysis estimates the benefits and costs of two regulatory alternatives: low 

sulfur fuel-based standards and standards requiring a percent reduction in SO. 

emissions. This document describes the methodology used in estimating the benefits 

and presents the results of the analysis. 

17. KEY WORDS AND DOCUMENT ANALYSIS 

DESCRIPTORS b.lDENTIFIERS/OPEN ENDED TERMS c. COSATi licld/Group 

Air pollution 

Standards of performance 

Steam generating units 

Industrial boilers 

Major rule 

Benefits analysis 

Air pollution control 

SO. benefits 

13B 

18. DISTRIBUTION STATEMENT 

Release unlimited 

19. SECURITY CLASS (This Report! 

Unclassified 

2 1 . NO. OF PAGES 

108 

20. SECURITY CLASS (This page) 22. PRICE 

Unr-lass-tf-fp H 

EPA Form 2220-1 (Rev. 4-77) PREVIOU S EDITIO N IS OBSOLET E