P.88 

- areata) ^r.!V»"'**^V'»' •" ^ B 

REGULATORY IMPACT ANALYSIS 

INDUSTRIAL BOILER - SO2 NSPS 

FINAL 8/87 
P.89 

Contents 

Page 

ROLE OF THIS DOCUMENT vi 

FORWARD viii 

EXECUTIVE SUMMARY xi 

I. Statement of Needs and Consequences I-l 

II. Alternatives Examined II-l 

A. Introduction II-l 

B. No Further Regulation II-l 

C. Other Regulatory Approaches 11-2 

D. Market Oriented Approaches 11-2 

E. Regulatory Alternatives Within the I1-5 

Scope of Present Legislation 

III. Air Quality Data III-l 

A. Introduction III- l 

B. SO4 A1r Quality Assessment III- l 

C. SO4 Air Quality Results II1-4 

D. PM Air Quality Assessment 111-6 

E. SO2 Air Quality Assessment 111-6 

IV. Engineering Costs IV-1 

A. Introduction IV-1 

B. Analytical Framework IV-1 

V. Economic Impact Analysis V-l 

A. Introduction V-l 

B. Major Steam Users V-l 

C. Selected Industries V-2 

D. Conclusions V-3 
P.90 

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 

Appendix A A-l 
P.91 

111 

Tables 

Number Page 

1 National Cost Impacts of Regulatory xiv 

Alternatives 

2 Industrial Boiler NSPS Potential Benefit xvi 

Categories 

3 Annualized Benefits xviii 

4 Average Benefits Per Ton xix 

5 Incremental Benefits Per Ton xx 

6 Net Benefit Analysis xx 

7 Average Control Cost Per Ton and Benefit xxi 

Per ton 

8 Incremental Control Cost Per Ton and Benefit xxii 

Per Ton 

ASTRAP Matrix III- 3 

1995 Base Case Sulfate Emissions 111-5 

1995 Sulfate Emissions, LSF Alternative 111-7 

1995 Sulfate Emission, Percent Reduction II1-8 

Alternative 

ASTRAP 1995 Estimated Visibility III- 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 

VI-2 Demand Equations for Which SO2 Is VI-26,27 

A Significant Explantory Variable 

VI-3 Annualized Benefits VI-33 

VI-4 Average Benefits Per Ton, SO4 VI-34 

III-l 

111-2 

111-3 

III- 4 

111-5 

III- 6 

IV-1 

IV-2 

IV-3 

VI-1 
P.92 

IV 

Page 

VI-5 Average Benefits Par Ton, PM vi-35 

VI-6 Average Benefits Per Ton, SO2 VI-36 

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

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

VII-l Net Benefit Analysis VI1-2 

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

Per Ton 

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

Per Ton 
Number 

Figures 

P.93 

Page 

VI-1 Description of A1r Quality Scenario VI-2 

Vl-2 Basic Steps 1n Estimating Benefits VI-7 

for An Individual Study 
^94 _ 

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 1s a "major rule" because it could 

result 1n 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 1s 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.95 

vi1 

REFERENCES 

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

Executive Order 12291, the usToTftii^.j i j o ; ru e" efers tl the 

adverse economic consequences of a regulation. 
P.96 

Since proposal of the industrial-commercial-institutional steam generating 

unit New Source Performance Standard in June 1986 several changes have 

been made to the Regulatory Impact Analysis (RIA) in response to public 

comments. In addition, further analysis of the national impacts has produced 

sulfur dioxide emission reductions that bound the estimates used in the RIA 

and annualized cost estimates that are lower than the estimates used in the 

RIA. 

A. Visibility Benefit Estimates 

A study by Tolley etV al (1986) was originally used in the draft RIA as 

the basis for the visibility benefit calculations. Some concerns were raised 

regarding this study and its use as the sole basis for visibility benefits. 

Upon further analysis, use of a group of five studies was deemed to yield the 

most appropriate and reliable benefit estimates. The studies used were: 

Brookshire etV al (1979, 1980), Rowe etl al (1980), Rae (1982), Loehmann et. 

al (1981) and Tolley etVal (1986). These five studies were used as a 

composite to derive a benefit function. Further discussion of the methodology 

employed can be found in Chapter VI, C.l and Appendix A. 

B. Particulate Matter Health Benefit Estimates 

The study used 1n the draft RIA to calculate particulate mater morbidity, 

Ostro 1983, has been replaced in the final RIA with Ostro 1986. Ostro's 1986 

study makes many improvements over his earlier work. The analysis uses a 

Poisson distribution to model the health endpoints. The Polsson distribution 

is an appropriate way to characterize the small probabilities associated with 

having a work loss day, reduced activity day, or respiratory related reduced 

activity day. Ostro's concentration-response functions were estimated using 
P.97 

IX 

a fixed effects specification. This type of specification considers the 

deviation of the individual observations from the mean of their group and 

eliminates the need to control for differences across groups. Whereas the 

Ostro 1983 study only analyzed one year the 1986 study covered the period 

1976-1981. In addition, the morbidity measure used in Ostro 1986 1s limited 

to only acute respiratory conditions and is therefore a better measure of 

PM induced acute morbidity than the 1983 measure which included all acute 

conditions regardless of their cause. The 1986 study also uses fine particles 

rather than total suspended particles as the measure of exposure. Since 

the fine particles are the most damaging to health they are probably the 

most appropriate indicator of PM exposure. More Information on Ostro 1986 

and the metholology used to calculate PM benefits can be found in Chapter 

VI, C.2. 

C. Relationship of RIA to the National Impact Analysis 

The national impacts analysis has been updated since proposal to 

reflect revised energy scenarios. These scenarios incorporate new projections 

of future coal, oil, and natural gas prices. Three regulatory alternatives 

are analyzed for these energy scenarios. The same low sulfur fuel and 

percent reduction regulatory alternatives are analyzed as were in the draft 

RIA in addition to a new 0.3 pound S02/MMBtu residual oil, 1.2 pound S02/MMBtu 

coal alternative. The RIA, however, has not been revised to reflect the 

updated national impacts analysis. 

The sulfur dioxide emission reductions in the updated national impacts 

analysis bound the estimates used in the RIA. On the other hand, the low 

sulfur fuel costs in the RIA are from 2% - 92% higher than those 1n the 

updated national impacts analysis. For the percent reduction alternative, 
costs in the RIA are from 1% - 96% higher than those in the national impacts 

analysis. Considering only these factors, the net benefits detailed in 

Chapter VII of the RIA are biased downward and the regulatory alternatives 

analyzed in the RIA would yield higher net benefits if the results of the 

updated national impacts analysis were incorporated. For more detail on 

the national impacts analysis, cost estimates, and energy scenarios see 

"Revised Impacts of Alternative Surfur Dioxide New Source Performance 

Standards for Industrial Fuel-Fired Boilers", Energy and Environmental 

Analysis, Inc., revised August 1987. 
P.99 

XI 

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 fulfilling this requirement. 

It 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 arid discussed 1n 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 SO2 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 vislbii improvement 

benefits, 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.1 

XI1 

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

estimated. Other, most likely 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 million dollars to a 

positive forty-three million dollars (1983 dollars). 

II. STATEMENT OF NEED AND CONSEQUENCES 

On August 21, 1979, a priority list 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 

list identified 59 major stationary source categories that were judged to 

contribute significantly to air pollution. This list did not include 

utility boilers since new source performance standards had previously 

been developed for this source category. Fossil fuel-fired industrial 

steam generating units ranked eleventh on the priority list of sources 

for which new source performance standards would be established. Fossil 

fuel-fired 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 priority 11st 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.2 

XI 11 

(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 approaches, 

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 1s 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 A1r Act 

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

steam generating units control emissions to the level achievable by the 
P-3 . 

XIV 

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 the 

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

desulfurization (FGD) systems to achieve a percent reduction 1n 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/mi11 ion Btu) heat input from oil 

combustion and to 516 ng S02/J (1.2 lb S02/mi1 lion 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.4 

XV 

less than 258 ng SO2/J (0.6 lb S02/mi1 lion 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 A1r Pollution 

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

transport, dispersion, chemical transformation and removalof 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 
i5_ 

xvi 

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 

e 

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 1n 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.6 

XVI 1 

Table 1 

NATIONAL COST IMPACTS OF REGULATORY ALTERNATIVES1*

2 

(Millions 1983 $) 

Regulatory 

Alternative 

Baseline 

Low Sulfur Fuel3 

Percent Reduction* 

Annualized 

Costs ($/yr) 

3,396 

3,454 

3,531 

Annualized 

Control Costs ($/yr)5 

am am am 

58 

135 

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

higher than the June 1982 costs reflected 1n 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/M1ll1on Btu - 011 

1.2 lb S02/Million 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.7 

XVI1 1 

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 1s the 31 eastern state 

region. Geographic coverage for SO2 includes 113 areas where new 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 1n 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 

of 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.8 

XIX 

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 Visibility 

- Non-Local Visibility 

- Climate 

- Visibility at Parks 

- Transportation Safety 

Non-Human Biological Effects 

- Agriculture 

- Forestry 

- Fishing 

- Ecosystem 

SO 

X 

X 

X are categories not analyzed in this study. 

* are categories analyzed in this study. 

NA are categories not applicable to the pollutant. 

SOj 

X 

X 

X 

X 

X 

X 

Other PM 

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 
P9 . 

XX 

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 Benefits1 

(Thousands of 1983 dollars)2 

Benefit Category 

SO4 Visibility 

PM Morbidity & Soiling4 

S02 Health 

S02 Welfare 

Materials Damage 

Agriculture 

Total 

Low 

1 

19,000 

22,000 

2,000 

26,000 

200 

69,200 

Regulatory Alternatives 

Industrial Boiler SO? 

Sulfur Fuel3 

2 3 

26,000 

25,000 

2,000 

26,000 

200 

79,200 

36,000 

27,000 

2,000 

26,000 

200 

91,200 

Percent Reduct 

1 2 

29,000 

34,000 

2,000 

40,000 

200 

105,200 

38,000 

37,000 

2,000 

40,000 

200 

117,200 

ion3 

3 

52,000 

40,000 

2,000 

40,000 

200 

134,200 

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 S04 and PM to reflect sensitivity analysis on the air quality 

modeling and economic valuation inputs. 

4 Approximately 85% of PM benefits are due to morbidity, 15% to soiling. 

X 
P.11 

XXI1 

Table 4 

Average Benefits per Ton1 

Totals (SO4. PM. and SO?) 

Regulatory B/T 

Alternative2 (1983 $) 

Low Sulfur Fuel/1 510 

Low Sulfur Fuel/2 600 

Low Sulfur Fuel/3 690 

Percent Reduction/1 540 

Percent Reduction/2 610 

Percent Reduction/3 710 

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

PM and SO?. 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 analyses on the air quality modeling and economic valuation 

inputs. 
P.12 

xxin 

Table 5 

Incremental Benefits per Ton1'

2 

Totals (S0A, PM, and SOg)' 

Percent Reduct1on/l 

Percent Reduction/2 

Percent Reduction/3 

B/T 

(1983 $) 

600 

640 

740 

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 1n geographic coverage. 

SO4 and PM only cover the 31 eastern state region. 

3 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. 

Table 6 

Net Benefit Analysis 

(thousands of 1983 dollars) 

Regulatory 

Alternative1 

Low Sulfur Fuel/1 

Low Sulfur Fuel/2 

Low Sulfur Fuel/3 

Percent Reduction/1 

Percent Reduct1on/2 

Percent Reduction/3 

Total 

Annualized 

Benefits 

69,000 

79,000 

91,000 

105,000 

117,000 

134,000 

Total 

Annualized 

Control Costs 

58,000 

58,000 

58,000 

135,000 

135,000 

135,000 

Annualized 

Net Benefits 1 

11,000 

21,000 

33,000 

-30,000 

-18,000 

-1,000 

1 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. 
PJ3, 

XXIV 

Table 7 

Average Control Cost Per Ton and Benefit Per Ton1 

(1983 $) 

Average Average 

Regulatory Alternative2 CAT B/T 

510 

600 

690 

540 

600 

710 

1 The "tons of SO? 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 S04 and PM to reflect 

sensitivity analysis on the air quality modeling and economic valuation 

inputs. 

Low Sulfur Fuel/1 

Low Sulfur Fuel/2 

Low Sulfur Fuel/3 

Percent Reduction/1 

Percent Reduction/2 

Percent Reduction/3 

340 

340 

340 

560 

560 

560 
P.M 

XXV 

Table 8 

Incremental Control Cost Per Ton and Benefit Per Ton

 l>2 

(1983 $) 

Percent Reduction/1 

Percent Reduct1on/2 

Percent Reduct1on/3 

Incremental 

C/T3 

1100 

1100 

1100 

Incremental 

B/T3 

600 

640 

740 

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

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

PM only cover 31 eastern state region. 

2 A range of benefits (1,2,3) 1s presented for SO* and PM to reflect sensitivity 

analysis on the air quality modeling and economic valuation Inputs. 

3 Percent reduction o^er low sulfur fuel. 
P.15 

XXVI 

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. 
P.16 

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 significantly 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-1nst1tut1onal 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 million Btu/hour) heat input. 

On August 21, 1979, a priority 11st 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 A1r Act Amendments of 

1977. This list identified 59 major stationary source categories that 

were judged to contribute significantly to air pollution that could 

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

performance standards had previously been developed for utility boilers 

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

units ranked eleventh on this priority 11st of sources for which new 

source performance standards would be established in the future. Fossil 

fuel-fired 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 priority list 

of source categories not regulated by NSPS was published. 
P.17 

I-2 

Fossil and nonfossil fuel-fired steam generating units are significant 

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

sulfur dioxide (SO2), and nitrogen oxides (NOx). As discussed 1n 

"Priorities for New Source Performance Standards Under the Clean A1r Act 

Amendments of 1977" (EPA-450/3-78-019), 1n the absence of the proposed 

standards, emissions from industr1al-commerc1al-inst1tut1onal steam 

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

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

total national SO2 emissions from major sources 1n 1990.. 

The expected construction of new coal-, oil-, and fossll/nonfossll 

fuel-fired steam generating units as a result of plant expansions and 

replacement of existing steam generating units 1s the principal reason 

for the large projected growth 1n emissions from this source category. 

New steam generating units with heat input capacities greater than 29 MW 

(100 million Btu/hour) are expected to have a total fossil fuel demand of 

approximately 530 million GJ (500 trillion Btu) In 1990. Many of these 

new facilities will fire coal and high sulfur oil. Combustion of wood 

and solid waste in combination with coal or oil 1s also projected to 

increase rapidly due to the lower cost of these nonfossil fuels. These 

developments could result 1n significant increases in SO2 emissions if 

standards of performance are not established for new industrial-commercialinstitutional steam generating units. 

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

wet flue gas desulfurization systems to achieve a 90 percent reduction in 

SO2 emissions and meet an emission limit of 516 ng SO2/J (1.2 lb S02/million 
P.18 

1-3 

Btu) heat Input. Coal-fired steam generating units using either fluidized 

bed combustion or lime spray drying to control SO2 emissions would be 

required to achieve an 85 percent reduction in SO2 emissions and meet an 

emission limit of 516 ng SO2/J (1.2 lb S02/mill1on Btu) heat input. Coalfired steam generaing units using an emerging technology for SO2 control 

would be required to achieve a 50 percent reduction 1n SO2 emissions and 

meet an emission limit of 258 ng SO2/J (0.6 lb S02/m1ll1on Btu) heat input. 

Steam generating units firing mixtures of coal with any other fuel (except 

oil) and having an annual capacity utilization factor for coal of less 

than 30 percent (0.30) would be required to meet an SO2 emission limit of 

516 ng SO2/J (1.2 lb S02/million Btu) heat input. 

The proposed standards would require all oil-fired industrial-commericalinstitutional steam generating units equipped with conventional wet flue gas 

desulfurization systems to achieve a 90 percent reduction in SO2 emissions 

and meet an emission limit of 344 ng SO2/J (0.8 lb S02/mill1on Btu) heat 

input. 011-flred steam generating units using either fluidized bed 

combustion or lime spray drying to control SO2 emissions would be required 

to achieve an 85 percent reduction in SO2 emissions and meet an emission 

limit of 344 ng SO2/J (0.8 lb S02/mill1on Btu) heat input. Oil-fired 

steam generating units using an emerging technology to control S02 

emissions would be required to achieve a 50 percent reduction in S02 

emissions and meet an emission limit of 172 ng SO2/J (0.4 lb S02/million 

Btu) heat input. Steam generating units firing oil and meeting an SO2 

emission limit of 86 ng SO2/J (0.2 lb S02/mi 1 Ho n Btu) or less would not be 

required to achieve a further percent reduction 1n SO2 emissions. The 
P.19 

1-4 

emission limit for steam generating units firing a mixture of coal and 

oil would be determined by proration. 

The proposed standards could reduce emissions of particulate matter 

from a typical oil-fired 1ndustr1al-commerc1al-1nst1tut1onal steam 

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

In the fifth year after this 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 S02 

because of its known adverse effects on public health and welfare. Impacts of this pollutant have been documented in the SO2 Criteria Oocument 

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

primary basis for the determination that emissions from Industrial-commercial 

institutional steam generating units will 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 will continue to contribute to local and regional air pollution. 

For these reasons the source category of 1ndustr1al-commercia1-inst1tutional 

steam generating units was selected for development of standards of 

performance. 
P.20 

1-5 

REFERENCES 

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

ProamJlI

 0mmerClal 'InSt1tUti °n a 1 Steam Cratin g Units, Draff* 
P.21 

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 all 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 million 

Btu/hour) heat Input. If only current control levels were maintained, 

S 02 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 fifth year after proposal. The Administrator has determined that 

this level of air pollution could reasonably be expected to endanger 

public health and welfare. For this reason this source category was 
P.22 

* 1 

11-2 

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) 1n 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 amount of pollution abatement that minimized 

their total cost, Including ;,ie pollution tax. Po! ion 1s abated until 

the marginal cost of abatement is equal to the poll* m tax. The regulatory agency would have to set the level of the tax ? a manner that would 
P.23 

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 1n 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 1s 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 
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, 1n the long-run, subsidies would result 1n 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 1n the form of Investment tax 

credits, would likely increase dependence on capital Intensive 

solutions. 

4) Market Oriented Approaches and Clean A1r Act Requirements. The 

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

reconstructed stationary sources such as 1ndustr1a1-commerc1a1-1nst1tut1ona1 

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 1n advance, that would achieve the same level of emission control 

as would otherwise be achieved by the best demonstrated technology. 
P.25 

11-5 

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. 011 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.26 

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. 011 does not effectively compete 

1n 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- ) . 

Oue 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 1s 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 F"uel 

This alternative 1s based on the use of low sulfur fuel to 

reduce emissions to 344 ng SO2/J (0.8 lb SOg/mllHon Btu) heat 
P.27 

11-7 

input from oil combustion and to 516 ng SO2/J (1.2 lb S02/m1llion 

Btu) heat input from coal combustion. 

3. Percent Reduction 

This alternative 1s based on the use of FGD systems to 

achieve a 90 percent reduction 1n SOg emissions from both oil and 

coal combustion. This alternative would generally reduce emissions 

from coal combustion to less than 258 ng/J (0.6 1b S02/mill1on 

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

(0.3 lb S02/mill1on Btu) heat input. 
P.28 

II-8 

REFERENCES 

Regional Forecasts of Industrial Residual Fuel 011 and Natural Gas Prices 

July 1984 Energy and Environmental Analysis, Inc. for the U.S. Environmental Protection Agency. 
P.29 

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 1s 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 A1r 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 
r 11-2 

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

geographic scale and for any pollutant is difficult and involves some 

uncertainty. Modeling of regional scale transport, dispersion, chemical 

transformation and removal of sulfur oxides 1s quite difficult 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 quality 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 this RIA, transfer matrices 

were derived from the Advanced Statistical Trajectory Regional A1r Pollution 

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

using the matrix generated SO4 concentrations. ASTRAP 1s 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. A description of the ASTRAP matrix follows in Table III-l. 

Transfer matrices assume that concentrations at a given receptor 

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

receptor A could be represented as: 

CA * TA1 *E l • TA2 * E2

 + ••• • T/g * Ej 

where Ej is the emission rate from the JT H source region and T/y is a proportionality coefficient relating region T emissions to region A concentrations. 

An array of these TAJ coefficients can be generated from running the full model 

and constitutes a transfer matrix. Transfer matrices are extremely inexpensive 

and easy to apply compared to full regional scale model runs. However, they 
P.31 

III-3 

TABLE III-l 

ASTRAP Matrix1 

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 Atlantic 

Considers low level releases as well as 

elevated releases 

None 

1976 - 1981 

1995 projected; unchanged by alternative 

1995 projected; unchanged by alternative 

1 Advanced Statistical Trajectory Regional A1r Pollution. 

2 Expressed as % of SO2 converted to sulfate per hour. 

3 Approximate daily averages. Actual rates exhibit strong diurnal variation, 
P.32 

111-4 

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 1s some "averaging out" of differences which might 

be apparent with the finer grids used 1n 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-11 near 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 1n mind. 

A more complete discussion of regional modeling and transfer matrices 

can be found in the Memorandum of Intent on Transboundary A1r 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 111-2. 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.33 

TABLE 111-2 

1995 Base Case Su 

-

STATE 

Alabama 

Arkansas 

Connecticut 

Delaware 

Florida 

Georgia 

Illinois 

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 Virginia 

Wisconsin 

(ug/m3 

lfate 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.34 

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 1s presented In Table 

III-5 along with the visibility Improvements due to the low sulfur fuel 

and percent reduction regulatory alternatives. 

0. PM Air Quality Assessment 

The air quality Information developed for the SO4 benefit assessment 

1s also used for the PM benefit assessment. Specifically, the SO4 changes 

for each state described 1n 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 1n 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 A1r Quality Assessment 

This section describes the principal procedures and assumptions used to 

calculate the S02 air quality Impacts of the two regulatory alternatives. 

The first subsection describes the development of the emissions Inventory, 
P.35 

111-7 

TABLE 111-3 

1995 Sulfate Emissions 

Low Sulfur Fuel Alternative 

(U9/m3 and % change from 1996 Base Case) 

STATE ASTRAP 

ug/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 

Illinois 5 J - .3 

Indiana STI ^T 

Iowa 2.6 - .8 

Kentucky 8.5 - .3 

Louisiana 2.5 -3.9 

Maine 3.6 - .1 

Maryland 10.9 - .2 

Massachusetts ?T5 - .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 T O - .2 

New York 7.5 - .2 

North Carolina 7.8 - .4 

Ohio 9.6 - .3 

Pennsylvania 11.3 - .2 

Rhode Island 7_JL - .2 

South Carolina O - .5 

Tennessee 6.9 - .5 

Vermont 5.1 - .2 

Virginia 9.3 - .3 

West Virginia 11.5 - .3 

Wisconsin 3.1 - .3 
P.36 

111-3 

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 

Illinois 54 - .5 

Indiana 371 - .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 4.6 -1.0 

New Hampshire 5.6 - .3 

New Jersey 10.5 - .4 

New York 7.5 - .4 

North Carolina 7.8 - .7 

Ohio 9.6 - .4 

Pennsylvania 11.3 - .4 

Rhode Island 7^0 - .4 

South Carolina BT7 - .7 

Tennessee 6.9 - .6 

Vermont 5.1 - .3 

Virginia 9.2 - .5 

West Virginia 11.5 - .4 

Wisconsin 3.1 - .7 
P.37 

111-9 

TABLE 111-5 

ASTRAP 1995 Estimated Visibility1 

(medium annual visual range in km) 

State 

Alabama 

Arkansas 

Connecticut 

Delaware 

Florida 

Georgia 

Illinois 

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 Virginia 

Wisconsin 

Baseline 

13.4 

12.6 

27.5 

24.9 

17.3 

16.9 

17.7 

16.8 

19.2 

18.7 

12.2 

35.1 

24.7 

29.3 

18.4 

21.9 

13.0 

16.7 

31.3 

25.3 

26.8 

16.8 

16.7 

19.1 

28.1 

16.8 

15.4 

31.9 

24.3 

19.6 

18.4 

LSF 

13.5 

12.7 

27.5 

24.9 

17.3 

17.0 

17.7 

16.8 

19.3 

18.7 

12.4 

35.1 

24.7 

29.3 

18.4 

21.9 

13.0 

16.8 

31.4 

25.3 

26.8 

16.8 

16.7 

19.1 

28.1 

16.8 

15.4 

31.9 

24.3 

19.6 

18.4 

Percent Reduction 

13.5 

12.7 

27.5 

24.9 

17.3 

17.0 

17.7 

16.8 

19.3 

18.7 

12.4 

35.1 

24.7 

29.3 

18.5 

21.9 

13.0 

16.8 

31.4 

25.3 

26.8 

16.9 

16.8 

19.1 

28.1 

16.8 

15.4 

31.9 

24.3 

19.6 

18.5 

1 Assumes an average nonsulfate/sulfate light extinction ratio of 1.25. 
P.38 

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 utilities from the Advanced Utility 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 III-7 shows which data base was used as the basis for the Inventory for 

different sources. 

TABLE 111-6 

Emissions Data Bases and Growth 

Source Data Base 

Type Category Age EES EEA Growth 

(MAP3S) AUSM (IFCAM) NEDS Applied? 

Point Utility Existing x x No 

No 

No 

x No 

Yes 

Area All - x Yes 

Utility 

Industrial 

boilers 

Other 

All 

Existing 

New 

Existing 

New 

«• 

am 

X 

X 

X 

X 

X 
P.39 

III-ll 

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 to 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.40 

111-12 

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

year of this Inventory Is 1978. 

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

sources other than utilities and industrial boilers. Where possible, 

utility boilers 1n the EES inventory were replaced by utility 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 utility 

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 all three cases (base case, low sulfur 

fuel, and percent reduction were deleted because their S02 emissions are 

negligible. 

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

associate each boiler with a 2-d1g1t SIC category. Within a particular 

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

This siting was accomplished 1n stages. First, the total coal and oil 

consumption (Btu's/year) 1n Industrial boilers was determined for each 

plant in the reg1on/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, if plant I's Industrial boilers 

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

would be twice as likely as plant 2 to be chosen as the site of a particular 

EEA boiler fueled by coal In the base case. 
P.41 

111-13 

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

with a maximum 1-hour S02 concentration exceeding 4500 yg/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 this 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 reg1on/SIC, 

o Utility boilers from AUSM2 with stack parameters and industrial 

steam generating unit emissions added and including retirement 

and startup years, 

o Some additional utility 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 III-7): 

0 Utility 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.42 

-I 

T 

111-14 

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

are anticipated. 

All 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-spedf1c 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. If 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 S02 

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 all the plants at which 

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

manually. An initial 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, 

this initial 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 all 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.43 

II1-15 

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 He u 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.44 

111-15 

b) A1r 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 S02 concentration at a receptor from a 

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

concentration, given that the wind direction 1s 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 utilities 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 arbitrarily allocated to those 

of the elliptical areas in proportion to their emission rates. 
P.45 

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, Illinols. 

Smith, A. E., and K. C. Brubaker (1983). Costs and A1r Quality Impacts of 

Alternative National Ambient Air Quality Standards for Particulate 

Matter - Technical Support Document, Argonne National Laboraotyr Report 

ANL/EES-TM-229. 

-J 
P.46 

IV-1 

IV. ENGINEERING COSTS 

A. Introduction 

National cost impacts on new industrial fossil fuel-fired 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 detail in "Projected Impacts of Alternative Sulfur Dioxide 

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

March 1985. IFCAM 1s an energy demand model developed to evaluate fuel 

choice decisions in the Industrial sector over a five 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 firing alternate fuels, and 

other key model parameters such as the expected size distribution of new 

industrial boilers. The model 1s 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.47 

IV-2 

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

this analysis 1s the new industrial boilers. 

A very disaggregate representation of industrial energy uses is 

incorporated in IFCAM. Energy use 1s disaggregated into nine industrial 

subsectors having different growth rates and regional dispersions. Each 

of these industrial subsectors 1s 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 1s divided among A1r Quality Control Regions 

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

model can portray the variability 1n 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 1s 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.48, 

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.49 

IV-4 

Table IV-1 

NATIONAL COST IMPACTS OF REGULATORY ALTERNATIVES1'

2 

(Millions 1983 $) 

Regulatory 

Alternative 

Annualized 

Costs ($/yr) 

Incremental 

Annualized 

Control Costs ($/yr)5 

Baseline 

Low Sulfur Fuel3 

Percent Reduction* 

3,396 

3,454 

3,531 

58 

135 

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

higher than the June 1982 costs reflected 1n the Preamble. 

2 Assumed high oil penetration scenario. 

3 0.8 lb S0?/M1llion Btu - Oil 

1.2 lb S02/Mni1on 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. 
IV-5 

P.50 

Regulatory 

Alternative 

Low Sulfur 

Percent Reduction 

Table IV-2 

Average 

Annualized Control 

Costs (thousands 

of 1983 $) 

58,000 

135,000 

Cont rol Cost Per Ton 

Tons of 

S02 Reduced 

(thousands) C/T 

170 340 

240 560 

Table IV-3 

Incremental Control Cost per Ton 

1 

Incremental Control 

Costs (thousands 

of 1983 S) 

Incremental 

Tons SO2 

Reduced (thousands) C/T 

Percent Reduction 77,000 70 1100 

1 Percent reduction over low sulfur fuel. 
P.51 

IV-6 

REFERENCES 

Projected Impacts of Alternative Sulfur Dioxide New Source Performance 

Standards for ndustrlal Fossil Fuel-F1red Boilers (March 1985) 
P.52 

V-l 

V. ECONOMIC IMPACT ANALYSIS 

A. Introduction 

A detailed analysis was undertaken to assess t'.e potential industryspecific economic impacts associated with the most stringent regulatory 

alternative—that requiring a percent reduction 1 i SO2 emissions. See 

"Projected Impacts of Alternative Sulfur Dioxide New Source Performance 

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

industry-specific impacts associated with the low sulfur fuel alternative 

would therefore be less than those discussed oelow. 

The potential industry-specific economic impacts were analyzed in two 

phases. The first phase focused on aggreg?te economic impacts for major steamusing industries and the second phase focused on selected industries that were 

considered likely 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 full 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 full 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.53 

V-2 

C. Selected Industries 

Seven industries, most likely to experience severe impacts, were 

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

utilization of their steam generating unit capacity. These industries 

were: beet sugar refining; fruit 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 1n 1990 for all except the beet sugar refining Industry, assuming 

full 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 all except the beet sugar refining industry, assuming 

full 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, this 1s due to the fact that the product price 1s 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.54 

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 a. J 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 mio s 

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.55 

V-4 

REFERENCES 

Projected Impacts of Alternative Sulfur Dioxide New Source Performance 

Standards for Industrial Fossil Fuel-F1red Boilers (March 1985). 

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

Protection Agency. 
P.56 

VI-1 

VI. BENEFIT ANALYSIS 

A. Introduction 

The economic benefits associated with the Industrial Boiler S02 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 applicable are subject to controls currently 

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

the post NSPS scenarios reflect the two regulatory alternatives discussed 

previously-low sulfur fuel and percent reduction. 

Although the NSPS are, by design, technology oriented, it 1s 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 tQ, ambient concentrations in a given area may be CQ . 

In the absence of additional controls beyond those currently 1n place, net 

growth of Industrial boilers 1n 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 1s shown by point (tj C2) 1n Figure VI-1. 

The area which represents the Improvement 1n air quality 1s the source of 

the benefit estimates. 
VI-2 

P.57 

Conctfltritioot 

c

l 

V 

C

2 

1 

^xi(ll '

C x ) 

^^s***^ 1 

*-—' 1 

f 1 1

 1 

1 1 

le 

tia« 

Figure VI-1. Description of M r 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 1s, the 

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

are applicable. In 1990. The discussion which follows 1s 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 1s precluded by project structure, 

time, and resource constraints. Therefore, estimates are based upon existing 
P.58 

VI-3 

studies which address some aspects of the health or welfare Implications 

of ambient SOg, 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 1n 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 1s 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.59 

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 1s 

presented 1n 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 contracts, 1t 1s determined that 

only some of the categories shown 1n 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 1s burned or sulfur dioxide emission controls 

are applied. These 1n turn reduce concentrations of SO2 directly 

and sulfates and particulate matter Indirectly (by reducing the 

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

S 02 emissions from oil-fired boilers, particulate matter emissions 

may also be reduced below baseline levels. Consequently, compliance 

with the Industrial Boiler NSPS may result 1n Indirect and direct 

reductions 1n PM concentrations. However, for purposes of this 

study PM benefits are only estimated for the Indirect reductions. 
VI-5 

Table VI-1 

Industrial Boiler NSPS 

P.60 

rvvcilliiai UCIICI IU dRt E 

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 and Industrial Facilities 

Climate and Visibility Effects 

- Local Visibility 

- Non-Local Visibility 

- Climate 

- Visibility at Parks 

- Transportation Safety 

Non-Human Biological Effects 

- Agriculture 

- Forestry 

- Fisheries 

- Ecosystem 

yuiICI 

S02 

X 

X 

* 

* 

* 

X 

NA 

NA 

X 

NA 

NA 

* 

X 

X 

X 

sp_4 

X 

X 

X 

X 

X 

X 

* 

* 

X 

X 

X 

X 

X 

X 

X 

Other 

PM 

X 

X 

* 

* 

* 

X 

X 

X 

X 

X 

X 

NA 

NA 

NA 

NA 

X are categories not analyzed 1n this study. 

* are categories analyzed in this study. 

NA are categories not applicable to the pollutant. 
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 1s also limited in other ways. 

The benefits are often Incomplete for those effects categories 

where benefits are measured. For example, the S02 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 1s to 

identify the magnitude of the ambient air quality Improvement 

that 1s estimated to occur 1n each area and year. This 1s the 

improvement achieved due to implementation of a particular 

standard, relative to a baseline situation reflecting controls 

already 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 S02 and 

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

year in which there 1s an air quality Improvement. 
P.62_ 

VI-7 

STEP 

1 

Identify air quality improvement 

in area i at year t 

STEP 

2 

Estimate health or welfare 

improvement in area 1 at year t 

3a 3b

 I 

STEP 

3 Estimate economic value pf the health 

or welfare improvement for 1, t 

STEP 

4 

Aggregate over 1 to obtain 

regional totals 

Figure VI-2. Basic steps in estimating benefits for an Individual study. 
P.63 

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 1s 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 1n order to complete a 

benefit-cost analysis of the various policy alternatives. The 

estimates are Incremental 1n 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 1n 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 1s organized by the 

pollutant and effect category for which benefits are estimated. 
P.64 

VI-9 

1. SO4 Related Benefits 

a) Visual Range 

1) Study Selection 

Because visibility is not directly traded in existing markets, 

benefit estimation methods require the establishment of a hypothetical 

market or identification of complementarity between visual range and 

existing markets. The former method manifests itself 1n contingent 

ranking and contingent valuation surveys eliciting w1H1ngness-to-pay 

estimates from survey respondents. The latter 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 1n 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 

et al. 1981, Rae 1982). The western visual range studies also Included 

contingent property value studies for two urban areas: the South Coastal 

Air Basin-Los Angeles (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 scenic vistas. 

To date, three eastern visibility studies have been conducted. One 

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

range Improvement 1n the Chicago area. Another evaluated the willingnessto-pay for visual range Improvement 1n the Cincinnati area (Rae, 1984). 

A third (Tolley et al. 1983) assessed the willingness-to-pay for visual 
P.65 

VI-10 

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 studies by Brookshire et al., Rae, Rowe et al., 

Loehmann et al., and Tolley et al. are chosen for this analysis. They 

cover nine cities and all use contingent valuation surveys. The nine 

cities are: Atlanta; Boston; Cincinnati (analyzed by both Tolley and 

Rae); Miami; Mobile; Washington DC; Los Angeles; San Francisco; and 

Farmington, New Mexico (analyzed by Rowe, 1980). 

2) Application 

The visual range benefit assessment Involves two sets of procedures. 

The first Involves using the annual visual range change for each state 

(Chapter 3, Table 111-5) to estimate local visual range change. 

The second set of procedures entails developing a visual range 

improvement valuation coefficient from the five studies discussed above 

and applying it to the predicted visual range changes. A H of the studies 

used personal Interviews 1n which subjects were shown photographs of 

different levels of visibility and were asked to estimate how much they 

would be willing to pay each month to have one level rather than another. 

In some cases, subjects were asked to give separate values for concerns 

related to health effects of air pollution versus the visual aesthetic 

effects. In other cases, subjects were asked to consider only the visual 

aesthetic effects of air pollution. Most of the studies asked about two 

or more different changes 1n visual range. In most cases, the subjects 

were told that the payment would be 1n the form of different monthly 

utility bills. 
P.66 

VI-11 

The bids vary widely within and across the nine cities - ranging 

from $1.66/year/household/kilometer in Farmington (Rowe et. al.) to 

$80.66/ year/household/ kilometer in Cincinnati (Rae). The average annual 

household values from each of the studies for each hypothesized change in 

visual range were compiled to estimate a benefits equation. This equation 

suggests that the bids from the surveys can be expected to be a function 

of the change 1n visual range considered and of the base level and new 

level of visual range hypothesized. The variables and data set used in 

this analysis can be found in Appendix A. 

3) Qualifications and Plausibility Checks 

There are certain factors which suggest that the estimates of visual 

range improvement benefits are understated. No attempt has been made 

in this RIA to quantify option or existence values. People In the west 

may be w11ling-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 may 

result in visual range improvements 1n Canada and certain western states 

bordering the 31 eastern states. These too are omitted from this analysis. 

However, there are other factors which suggest the estimates of 

visual range Improvement benefits may be overstated 1n some respects. For 

example, the legitimacy of the benefit estimates 1s dependent in part on 

the ability of people to perceive the projected visual range improvements. 

The perception threshold for a change 1n visual range 1s two to five 

percent for a single visibility event. Depending on the variance of 

visual range improvements through the year, the perception factor could 

influence the benefit estimate. 
P.67 

VI-12 

Other qualifications to the visual range benefit estimates include 

concern about extrapolating the contingent valuation results from nine 

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

to rural extrapolation which may be questionable. These estimates reflect 

the average estimates obtained to date In contingent valuation studies 

concerning values to residents of visibility 1n urban areas. As such, the 

range of the data should be kept In mind. For example, the smallest 

change in average visual range considered in any of the studies was about 

1 mile, while the average change was about 5 miles and most of the changes 

were 20 miles or less. The equation would therefore be less reliable for 

predicting values for changes in average visual range of less than 1 mile 

or greater than 20 miles. The base level of visual range 1s also Important. 

The average in these studies was about 15 miles, with most of them falling 

between 7 and 19 miles. The equation would be less reliable for areas 

where the current average visual range Is less than 7 or more than 19 

miles. 

2. PM 

The PM benefits developed in this analysis are derived from willingnessto-pay estimates in the form of dollars/pg/m3 reduction 1n 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. 
P.68 

VI-13 

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 

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 1s used to establish 

a relationship between the change in chronic respiratory disease incidence 

and work loss or restricted activity days. The geographic unit of 

analysis 1s the county. The valuation of chronic respiratory disease 

damages Included an assessment of lost productivity (I.e., foregone 

average daily wage), and Increased medical care service charges (I.e., 

direct medical expenditures). Of course, the benefit of decreased PM 
P.69 

VI-14 

concentrations are evaluated as the reduction 1n 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 1n annual TSP for 

the counties used 1n the PM NAAQS analysis ranged from $0.12 to $0.18 

for direct medical expenditures, $0.15 to $0.21 for reduced work loss 

days per employed worker, and $0.33 to $0.49 per capita reduction 1n 

reduced activity days. 

3) Qualifications and Plausibility Checks 

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

benefits In 31 eastern states 1s not without uncertainty. However, the 

fact that the study 1s judged to be quantitative for purposes of 

standard setting does suggest some underlying credibility in the 

benefit estimates. Even so, the benefit estimates for this PM category 

are limited. For example, no valuation factor 1s applied to the 

residual pain and suffering category, 

b) Acute Morbidity 

1) Study Selection 

The acute morbidity studies amenable for benefit analysis Include 

the Samet et. al (1981) longitudinal epidemiological study 1n Steubenvilie, Ohio and the cross sectional mlcroepldemlological study by 

Ostro (1986). 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 
P.70 

VI-15 

restricted activity days due to respiratory disease to fine particle 

concentrations. The PM Staff Paper states that this study provides 

strong qualitative support for a relationship between current PM levels 

and restricted activities 1n adults. 

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 1s selected 

for use in estimating PM benefits associated with the steam generating 

unit NSPS. 

2) Application 

Ostro (1986) analyzed six years of Individual data from 

the National Center for Health Statistics Health Interview Survey (HIS) 

to examine the relationship between air pollution and morbidity. Ostro's 

sample included all adults age 18 to 65 from 49 metropolitan areas for 

which pollution data and HIS sample data exist. The sample contained 

approximately 12,000 adults for each of the six years from 1976 through 

1981. 

Three measures of morbidity were used 1n the analysis: days of lost 

work (WLD), days of restricted activity (RAD) and days of respiratoryrelated restricted activity (RRAD). Information on these morbidity 

measures was obtained In response to a survey question asking the 

individual how many days, 1n the previous two weeks did Illness prevent 

him (her) from working or participating 1n his (her) usual activities. 

The concentration-response functions estimated by Ostro regressed 

a measure of the individual's acute WLD, RAD, or RRAD against a measure 

of PM and his/her personal, economic, and other characteristics. The 
P.71 

VI-16 

measure of PM was a two-week average lagged to represent the two-week 

exposure period before the period under consideration by the HIS. In 

addition to the PM measure, the variables Included the Individual's age, 

sex, race, education, family Income, marital status, existence of a chronic 

condition, quarter of the survey, and average two-week minimum temperature. 

The concentration-response functions that Included WLD as the dependent 

variable also controlled for paid sick leave and whether the Individual 

worked in a blue or white collar job. In addition to the basic set of 

variables, the RAD and RRAD concentration-response functions Included a 

variable reflecting whether or not the Individual was working. Benefits 

are not calculated for reduction 1n pain and suffering prior and subsequent 

to the receipt of medical care services. 

3) Qualifications 

Like all epidemiological studies, there 1s the question of Inferring 

causality from the statistically significant relationship. Unlike many 

epidemiological studies, Ostro has relatively better control for potentially 

confounding factors. Ostro uses a lagged two-week average fine particle 

concentration as the measure of exposure for the two-week period for 

which acute Illness is examined. This two-week lag resulted 1n the 

strongest regression. Alternative lag structures (I.e., 0 to 3 periods) 

were examined but they were either not significant of less significant 

than the two-week lag. Results from Steubenvllle, Spengler (1986) 

and the Netherlands, Dassen (1986) which show an extended depression In 

lung function following § single episode provide additional support for 

a two-week lag. 

The third significant feature of the Ostro study 1s the use of 

fine particle data. Current evidence suggests that small particles (i.e., 
P.72 

VI-17 

less than 10.0 microns), rather than total suspended particulates (TSP), 

have an adverse impact on health. Ostro used data on particles less than 

2.5 microns [i.e., fine particles (FP)] as an index of exposure to smaller 

particles. Because data on FP were not routinely collected during the 

1976 through 1981 time period, Ostro estimated FP concentrations using 

equations developed by TMjonis (1982, 1983) and airport visibility data. 

Two comments can be raised with respect to the fine particle air 

quality data used by Ostro. First, estimated rather than actual FP concentrations, were used by Ostro. Although several quality control features 

were undertaken to assure that the estimates of FP were reliable, the 

reliability of the Trijonis equation Itself was never examined by Ostro. 

Second, the two-week average of FP used by Ostro corresponds to the 

two-week period before the recall period considered 1n the HIS. 

c) Household Soiling 

1) Study Selection 

The studies available for benefit assessment Include the two Philadelphia studies by Watson-Jaksch and Cummlngs et al. (1981) and the 24 

SMSA longitudinal study by Mathtech (1982). The first 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. 
P.73 

VI-18 

The Mathtech study (1982) 1s referenced later 1n the SO2 section on 

materials damage. As will be indicated there, the approach Incorporates a 

physical damage function indirectly 1n the structure of an economic demand 

and supply model. Within that framework, household behavior 1n terms of 

soiling perception, cleaning activity, and expenditures to maintain a 

given degree of cleanliness Is estimated econometrlcally. Prices, environmental variables, and sociodemographic characteristics are Inputs to the 

mode 1. 

The Mathtech model is chosen because It 1s based on more recent 

data, has broader geographic coverage, and uses the theoretically correct 

measure of benefits, w1l11ngness-to-pay. 

2) Application 

To apply the model in the PM NAAQS (Mathtech, 1983) analysis, values 

of prices, environmental variables, and sodo-demographlc 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 S02 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 1s also referenced 1n 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 
P.74 

VI-19 

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 

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 1n 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 1n 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, 1n turn, is divided by the annual change 

in air quality to yield a benefit/percent pg/ra3 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 1n 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 
P-75 

VI-20 

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 (residential 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 1s caused. 

The first topic requires a review and critique of the literature on 

physical damage functions. These functions have been reviewed 1n 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. 

* For example, controlling SO? emissions results 1n lower fine particle (I.e., 

<_ 2.5 um) levels, while NSPS controls for PM emissions result 1n lower 

concentrations of other particle sizes In addition to fine. 
P.76 , 

VI-21 

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 

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 1n selecting benefit models for valuing material 

damage 1s 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 1s 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 

1s an economic demand model which describes relationships between SO2 

and various goods and services that may be purchased by a consumer. 
P.77 

VI-22 

Thus, the concentration-response function relates SO2 directly to 

economic parameters; there 1s no intermediate calculation of physical 

damage. In addition to reduced data requirements, the Mathtech model 

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 1s 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 1n 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 SAROAO data base. The data base that 1s constructed covers 24 

SMSA's with budget and environmental data representative of conditions 
P.78 

VI-23 

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. 

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 1s at this 

stage that the S02 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 
P.79 

n 

VI-24 

recording the maximum 24-hour second high concentration among all receptors.* 

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 1n 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, 1n particular, that the 

price Index for a commodity will be sensitive to the level of S02 that 1s 

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 S02 . However, since the seven commodity 

groups also form a demand system, the S02 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, 1t 1s now possible to calculate benefits. The goal 1s to use the 

commodity demand functions to define an expenditure function that 1s a 

function of S02 . This 1s accomplished 1n 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 

* Additional work 1s 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. 
P.80 

VI-25 

Table VI-2 

DEMAND EQUATIONS FOI TOCH SOj IS A SIGNIFICANT EXPLANATOII VAIZABLZ 

1. Home la pair 

I. - 0.23211 ii 0.767 • (-33.314 + 0.032S4 • SO.) • Z. 

- 0.23211 • (-153.27 • 0.11979 • TSP) • Zj 

vkore Xj - tke skeze of koae repair ezpeaditerea relative te all 

ozpeaditeree for skelter. 

Zj - tke ratio ef tke koae repair priee iadez to skelter 

ezpeaditares. 

.ma - tke ratio of tke etilit y priee izdez to skelter 

ezpeaditares. 

SOj " tke 24 koar seeoad kigk aeaaere of SOj *•* tke aoaitor 

roeerdiag tke aaziaaa valae of tkis variable vitkia tke 

ease stadj area. 

TSF • tke 24 koaz seeoad kigk aeasaze ef Total Saspeaded Partiealate s for tke aoaitor reeordiaz tke aaziaaa rales of 

tkis Taziable vitkia tke ease a tody area. Tkis velee ia 

defsalted to tke earreat priaary NAAQS. 

2. Teztiles axeladles elotkiag 

vkore 

- 0.10445* • 0.I9SS4 • (3.23302 * 0.0202S4 • SO.) • Z. 

- 0.104454 • ((-21.5794 - 37.S934 • FAMSZ • 55.375 • 

USI0H) * la * (-50.0434 • 10.3395 • FAMSZ * 2.4711 • 

EJSION) • Z?5 - 7.33139 • Z() 

» tke skare of teztil e ezpeaditares relative to all 

ezpeaditares for koae faraiakiazs. 

• tke ratio of tke teztil e priee iadez te koae faraiakiaz 

ezpeaditases. 

• tke ratio of tke faraitare priee iadez to koae 

faraiakiaz ezpeaditares. 

• tke ratio of tke sppiiaaee priee iadez to koae 

faraiskiaz ezpeaditares. 
P.81 

VI-26 

Table VI-2 (continued) 

DEMAND EQUATIONS FOE 1110 1 SOj IS A SIGNIFICANT EXPLANATOBT VA1IABLE 

Z

4 

» 2 

FAMSZ 

UBION 

• 

• 

• 

• 

tke ratio of tke koasevaroa priee iadez to koae 

feraiskiat ezpeaditares. 

tke 24 hoar seeoad kigk aeasare ef SOj for tke aoaitor 

record lag tke aaziaaa valae of tkis variable vitkia tke 

eaae stady erea. 

family size. 

daaay variable for loeatioa of ease stady area 

(1-NerUeaat or Nortk Ceatral. O»otkervise). 

3. Treasporatioa Services 

X

3 

vkore Xj 

h 

h 

» 2 

TEMP 

-

• 

-

• 

• 

-

0.53444 • 0.44534 • (-475.409 • 37.1453 • SO.) • Z-

- 0.53444 • (-377.413 • 28.3191 • TEMP) • Z, 

tke skare of gasoliao ezpeaditaree relative to all 

ezpeaditares for trsasportatioa. 

tke ratio of tke gasoliao priee iadez to all 

trsasportatioa ezpeaditares. 

tke ratio of tke prise iadez for tke "othar* 

traasportatioa deaaad category to all trsasportatioa 

ezpeaditaree. 

tke 24 koar seeoad kigk aeasare ef SOj for tke aoaitor 

reeordiag tke aaziaaa valae of tkie varisble vitkia tke 

case stady area. 

average aaaaal teaperstare ia degrees Celsios. 
P.82 

VI-27 

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 

commodities. This procedure 1s 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 1s 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: 
P.83 

VI-28 

Short-term (1-hour), 

Dally (24-hour) 

Short-term Exposure 

For the short-term exposure category, clinical studies are 

utilized. In the relevant range of SO2, the major effects occur 1n 

asthmatics. Studies of this group examine effects on both lung function 

changes are difficult 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 full range of clinical studies of effects of SO2 on symptom 

prevalence Is utilized. The lower-bound estimate 1s based on the 

pooled results of eight studies. The upper-bound estimate 1s based on 

work of Kirkpatrick et al. (1982). 

Daily Exposure 

No mlcroepldemlology studies were found to be directly usable for 

estimating effects of dally exposure. Among the limitations of the 

studies were failure to derive quantitative concentration-response 

functions and lack of control of confounding factors. 

Several macroepldemlology studies examine the relationship between 

SO2 and the number of emergency room visits 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 1s used. The 

maximum estimate for each day's symptoms Is $25 based on unpublished work 

by Dickie and Gerking and Tolley and Babcock. 
P.84 

VI-29 

3) Qualifications and Plausibility Checks 

To estimate the benefits using clinical studies, assumptions about 

activity levels ire 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 arbltary 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 1s 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 1n 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; 
P.85 

VI-30 

and plausible and quantifiable results which can be used to develop 

concentration response functions. 

Application of these criteria yielded a very limited number of studies 

for each crop. The major study used for soybeans 1s from Sprugel et al. 

(1980). For oats and wheat, the principal source 1s a series of reports by 

Guderlan 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 1s applies. The estimate 1s 

restricted to air quality changes within the underlying study range. Zero 

1s 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 1s 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 1n 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.86 

VI-31 

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 11 I-B and VI-C, respectively. The 

benefit categories estimated include: increased local visibility due to 

SO4 reductions, reduced chronic and acute morbidity and reduced residential 

soiling due to PM reductions, reduced morbidity, materials damage, and 

increased agricultural yield 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 1s required. 

Tables VI-4 - VI-6 report the average benefits per ton of SO2 reduced 

from all 113 areas where new industrial boilers were placed. For SO4 and 

PM, only the tons reduced from the 31 eastern states are considered. 

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 - 34% 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 Benefits1 

(Thousands of 1983 dollars)2 

Benefit Category 

S04 Visibility 

PM Morbidity ft Soiling4 

S02 Morbidity Health 

S02 Welfare 

Materials Damage 

Agriculture 

Total 

Low 

1 

19,000 

22,000 

2,000 

26,000 

200 

69,200 

Regulatory Alternatives3 

Industrial Boiler S02 

Sulfur Fuel 

2 

26,000 

25,000 

2,000 

26,000 

200 

79,200 

3 

36,000 

27,000 

2,000 

26,000 

200 

91.200 

Percent Reduct 

1 

29,000 

34,000 

2,000 

40,000 

200 

105,200 

2 

38,000 

37,000 

2.000 

40,000 

200 

117,200 

ion 

3 

52,000 

40,000 

2,000 

40,000 

200 

134,200 

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 S04 and PM to reflect sensitivity 

analysis on the air quality modeling and economic valuation inputs. 

4 Approximately 85% of PN benefits are due to morbidity, 15% to soiling. 

1 

imJ 
VI-33 

P.88 

SO4 (Total Visibili 

Regulatory1 

Alternative 

Low Sulfur Fuel/1 

Low Sulfur Fuel/2 

Low Sulfur Fuel/3 

Percent Reduction/1 

Percent Reduction/2 

Percent Reduction/3 

Table VI-4 

Average Benefits 

M 

per Ton 

Annualized 

Benefits 

(thousands of 1983$) 

19,000 

26,000 

36,000 

29,000 

38,000 

52,000 

Tons S02

2 

Reduced 

(thousands) 

120 

120 

120 

175 

175 

175 

-

B/T 

160 

220 

300 

170 

220 

300 

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-34 

P.89 

Particulate Matter 

Regulatory1 

Alternative 

Low Sulfur Fuel/1 

Low Sulfur Fuel/2 

Low Sulfur Fuel/3 

Percent Reduction/1 

Percent Reduct1on/2 

Percent Reduct1on/3 

Table VI-5 

Average Benefits per Ton 

Annualized 

Benefits 

(thousands of 1983$) 

22,000 

25,000 

26,000 

34,000 

37,000 

40,000 

Tons S02

2 

Reduced 

(thousands) 

120 

120 

120 

175 

175 

175 

B/T 

180 

210 

220 

190 

210 

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.90 

SO 

VI-35 

Table VI-6 

Average Benefits per Ton 

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 all 113 areas analyzed. 
P.91 

VI-36 

Table VI-7 

Average Benefits per Ton 

Totals (SOa, PM, and SO?) 

Regulatory1 B/T 

Alternative (1983 $) 

Low Sulfur Fuel/1 510 

Low Sulfur Fuel/2 600 

Low Sulfur Fuel/3 690 

Percent Reduction/1 540 

Percent Reduct1on/2 610 

Percent Reduction/3 710 

1 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. 

Table VI-8 

Incremental Benefits per Ton1 

Totals (S04, PM, and SO?)2 

B/T 

(1983 $) 

Percent Reduct1on/l 600 

Percent Reduction/2 640 

Percent Reduction/3 740 

1 Percent reduction over low sulfur fuel. 

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. 
VI-37 

References 

Bachmann, J. Memorandum to Tom Walton, "Estimate of Sulfate/Fine Mass 

Relationship," 1985. 

Brookshire, D., d'Arge, R., Schulze, W., and Thayer, M., (1979). Experiences 

1n Valuing Non-Market Goods: Alternative Benefit Measures of Air 

Pollution 1n the South Coast A1r Basin of Southern California, 

EPA-600/6-79-0016. 

Brookshire, D., Thayer, M., Schulze, W., and d'Arge, R., (1980). "Valuing 

Public Goods: A Comparison of Survey and Hedonic Approaches," Resource 

and Environmental Economic Laboratory, University of Wyoming, later 

published in American Economic Review, 72 (March). 

Crocker, T.D., Schulze, W., Ben-David, S. and Kneese, A., (1979). "Methods 

Development for Assessing A1r Pollution Control Benefits," Vol. I, 

Economics of A1r Pollution Epidemiology, EPA-600/5-79-001a, U.S. 

Environmental Protection Agency, Washington, O.C. 

Cummings, R., Burness, H. and Norton, R. Methods Development for Environmental 

Control Benefits Assessment, Volume V: Measuring Household Soiling 

Damages from Suspended Air Particulates, A Methodological Inquiry. Draft 

Report, January 1981. 

Dassen, W., Brunekreef, B., Hoek, G., Hofschreuder, P., Staatsen, B., de Grout, 

H., Schouten, E., Biersteker, K. (1986). Decline 1n Children's Pulmonary 

Function During an A1r Pollution Episode. J. A1r Pollution Control 

Association (in press). 

Dickie, M. and Gerking, S. Written correspondence to Allen Basala, "Willingness 

to Pay to Avoid Symptoms," 1980. 

Ferris, B.G., Jr., Higgins, I., Higgins, M.W. and Peters, J.M., (1973). Chronic 

Non-Specific Respiratory Disease In Berlin, New Hampshire, 1961-1967: 

A Follow-up Study. American Review of Respiratory Disease, 107-110-122. 

Ferris, G.B., Jr. and Anderson, D.O., (1962). Prevalence of Chronic Respiratory 

Disease 1n a New Hampshire Town. American Review of Respiratory Disease, 

86:165-177. 

F1nk, F.W., Buttner, F.H., and Boyd W.K., (1971). Technical-Economic 

Evaluation of Air Pollution Corrosion Costs on Metals 1n the U.S. 

APTD-0654. U.S. Environmental Protection Agency, Research Triangle 

Park, N.C. 

Graves, P.E., Krumm R.J., and Vlolette, D.M., (1980). Estimating the Benefits 

of Improved A1r Quality. Report for Meeting of Benefit Methodology Panel, 

National Commission on Air Quality, December. 
P.93 

VI-38 

Guderian, R. and Stratman, H., (1962). Field Experiments to Determine the 

Effects of SO2 on Vegetation - Part I: Survey of Method and Evaluation 

of Results. Research Reports by the State of North Rhine-Westphalia, 

No. 1920. West German Press, Cologne and Opladen. 

Hobart, J.M., R.L. Horst, Jr., K.M. Brennan, E.H. Manuel, Jr., et al. 

(1984). Benefit Analysis of National A1r Quality Standards for Sulfur 

Dioxide. Report by Mathtech, Inc. for EPA, Office of A1r Quality 

Planning and Standards, Research Triangle Park, NC, December. 

Horst, R.L., J.M. Hobart, E.H. Manuel, Jr., K.M. Brennan, M.C. Duff, and 

G.D. Labovlch (1985). Benefit-Cost Analysis of Selected New Source 

Performance Standards for Particulate Matter. Report prepared by 

Mathtech, Inc. for the Environmental Protection Agency under Contract 

No. 68-02-3553, July. 

Kirkpatrick, M.B., Sheppard, D., Nadel, J.A., and Boushey, H.A., (1982). 

Effect of Oronasal Breathing Route on Sulfur Dioxide-Induced Bronchoconstriction in Excercislng Asthmatic Subjects. American Review 

of Respiratory Diseases, 125:627-631. 

Loehman, E., Boldt, D., and Chaikin, K., (1981). Measuring the Benefits of Air 

Quality Improvements in the San Francisco Bay Area, SRI 8962. 

Manuel, E.H., Jr., R.L. Horst, Jr., K.M. Brennan, et al. (1982).. Benefits 

Analysis of Alternative Secondary National Ambient A1r Quality Standards for Sulfur Dioxides and Total Suspended Particulates, Volume II. 

Final report by Mathtech, Inc. for EPA, Office of A1r Quality Planning 

and Standards, Research Triangle Park, North Carolina, May. 

Mathtech, Inc., (1982). Benefits Analysis of Alternative Secondary National 

Ambient Air Quality Standards for Sulfur Dioxide and Total Suspended 

Particulates. Final report prepared for U.S. Environmental Protection 

Agency under Contract No. 68-02-3392. Research Triangle Park, N.C. 

Mathtech, Inc., (1983). Benefit and Net Benefit Analysis of Alternative 

National Ambient Air Quality Standards for Particulate Matter. Prepared 

for the U.S. Environmental Protection Agency, Office of A1r Quality 

Planning and Standards under Contract No. 68-02-3826. 

Mathtech, Inc., (1984). Benefit Cost Analysis of Selected New Source 

Performance Standards for Particulate Matter. Draft Final Report 

Proposed for U.S. Environmental Protection Agency, Office of A1r Quality 

Planning and Standards under Contract No. 68-02-3553, Resarch Triangle 

Park, N.C. 

Mazumdar, S. and Sussman, N., (1981). Relationships of air pollution to 

health: results from the Pittsburgh study. Proceedings of the 74th 

Annual Meeting, Air Pollution Control Association, Philadelphia, Pa, 

June 21-12. 1981. 
P.94 

VI-39 

Ostro, B. The Effects of Air Pollution on Work Loss and Morbidity, Journal 

of Environmental Economics and Management 10:71-78. December 1983. 

Rae, D., (1982). "The Value to Visitors of Improving Visibility at Mesa 

Verde and Great Smokey National Parks," a paper presented at a National 

Park Service Conference, Keystone Colorado, May, later published in 

Robert Rowe and Lauraine Chestnut, eds., Managing Air Quality and Scenic 

Resources at National Parks and Wilderness Areas, Westview Press, Boulder, 

Colorado, 1983. 

Rae, D., Charles River Associates, (1984). Benefits of Visual A1r Quality In 

Cincinnati Results of a Contingent Ranking Survey, draft report, 

Electric Power Research Institute, Project #1742. 

Randall, A., Hoehn, J., and Tolley, G. "The Structure of Contingent Markets: 

Results of a Recent Experiment," a paper presented at the American 

Economic Association Meetings, December 1981. 

Rowe, R.D., d'Arge, R., and Brookshire, D., (1980). An experiment on the economic 

value of visibility. Journal of environmental economics and management 

7:1-19. 

Salman, A. Systems Analysis of the Effect of A1r Pollution on Materials, 

Final Report for the National Air Pollution Control Association under 

Contract No. CPA-22-69-113. January 1970. 

Samet, J.M., Speizer, F.E., Bishop, Y., Spengler, J.D., and Ferris, Jr., B.G., 

(1981). The relationship between air pollution and emergency room 

visits in an Industrial community. J. A1r Pollut. Control Assoc. 

31:236-240. 

Schulze, W.D., Brookshire, D.S., Walther, E., and Kelley, K., (1981). Methods 

development for environmental control benefits assessment. Vol. X: 

The benefits of preserving visibility in the national parklands of the 

Southwest. Washington, D.C : U.S. Environmental Protection Agency, 

Office of Research and Development. 

Sprugel, D.G., Miller, J.E., Muller, R.N., Smith, H.J., and Xerikos, P.B., 

(1980). Sulfur Dioxide Effects on Yield and Seed Quality in FieldGrown Soybeans. Phytopathology, 70:1129-1133. 

SRI, Inc. An Estimate of the Non-Health Benefits of Meeting the Secondary 

National Ambient A1r Quality Standards. Prepared for the National 

Commission on Air Quality, January 1981. 

Tolley, G., Randall, A., Blooaquist, G., Fabian, R., Flshelson, G., Frankel, 

A., Hoehn, J., Krumm, R., Mensah, E., and Smith, T., (1986). Establishing 

and Valuing the Effects of Improved Visibility in Eastern United States, 

Office of Research and Development, Environmental Protection Agency. 

Tolley, G. and Babcock, C , (1986). Draft - Valuation of Reductions in 

Human Health Symptoms and Risks. USEPA Grant No. CR-811053-01-0. 

_J 
P.95 

VI-40 

TRC (1981). Benefit Model for Pollution Effects on Material. Final report 

prepared for U.S. Environmental Protection Agency under Contract No. 

68-02-3447. Research Triangle Park, N.C. 27711. 

U.S. Bureau of Labor Statistics (1973). Average Retail Prices of Selected 

Commodities 4 Services. U.S. Government Printing Office, Washington, DC, 

U.S. Bureau of Labor Statistics (1978). Consumer Expenditure Survey: 

Integrated Diary and Interview Survey Data, 1972-73. Bulletin 1992, 

U.S. Government Printing Office, Washington, D.C. 

U.S. Environmental Protection Agency, Office of A1r Quality Planning and 

Standards. Protecting Visibility, An EPA Report to Congress. EPA450/5-79-008. October 1979. 

U.S. Environmental Protection Agency, Office of Air Quality Planning and 

Standards. Review of the National Ambient A1r Quality Standards for 

Sulfur Oxides: Assessment of Scientific and Technical Information, 

OAQPS Staff paper. November 1982. 

Watson, W.D., Jr., and Jaksch, J.A., (1978). Household cleaning costs and 

air pollution. Presented at the 71st Annual Meeting, A1r Pollution 

Control Association, Houston, Texas, June 25-30. Paper No. 78-52.3. 
VI I-l 

VII. BENEFIT-COST ANALYSIS 

This chapter compares the cost of control for the alternative regulations 

to the bene s 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 VII-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 S02 

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., ad d deposition) and from the 

SO4 health categories. 

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 1n 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. 
VII-2 

Table VII-1 

Net Benef't Analysis 

(thousands of 1983 dollars) 

P.97 

Regulatory1 

Alternative 

Low Sulfur Fuel/1 

Low Sulfur Fuel/2 

Low Sulfur Fuel/3 

Precent Reduct1on/l 

Percent Reduct1on/2 

Percent Reduction/3 

Total 

Annual 1 zee 

Benefits 

69,000 

79,000 

91.0C0 

105,000 

117,000 

134,000 

Total 

Annualized 

Control Costs 

58,000 

58,000 

58,000 

135,000 

135,000 

135,000 

Annualized 

Net Benefits 

11,000 

21,000 

33,000 

-30,000 

-18,000 

- 1,000 

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

senstivity analysis on the air quality modeling and economic valuation 

inputs. 
P.98 

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/1 340 510 

Low Sulfur Fuel/2 340 600 

Low Sulfur Fuel/3 340 690 

Percent Reduction/1 560 540 

Percent Reduction/2 560 610 

Percent Reduction/3 560 710 

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 Reduct1on/l 

Percent Reduction/2 

Percent Reduction/3 

Incremental 

C/T 

1100 

1100 

1100 

Incremental 

B/T 

600 

640 

740 

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

sensitivity analysis on the air quality modeling and economic valuation 

inputs. 

2 Percent reduction over low sulfur fuel. 
P.99 

VII-4 

Due to the limited benefit coverage and geographic/temporal scope 

of this RIA, it 1s 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. 
Appendix A 

The purpose of this appendix 1s to provide more information on the 

procedure for calculating SO4 visibility benefits. The SO4 benefits 

estimated in Chapter VI and VII are associated with visual range improvement 

due to decreases in SO4 concentrations form compliance with alternative 

regulations. The visibility numbers used for each state can be found in 

Table II1-5. These numbers represent annual average visual range estimates 

for each state. 

The estimation of visibility benefits uses information on wlllingnes 

to pay on a household basis. The visibility valuation data 1s used 

together with the visual range Improvements to generate the benefits of 

visual range improvements for the 31 eastern states. The visibility 

valuation data represents the annual willingness to pay of the mean 

household for a one kilometer improvement in visual range. The average 

annual household values from each of the studies (Brookshlre, et al. 1979, 

Rowe et al. 1980, Rae 1983, Loehmann et al. 1981, To1 ley et al. 1986) for 

each hypothesized change 1n visual range were compiled to estimate Equation 

A.l. 

Benefits * [(b/a) (VR2-VR1) + (c/a) (VR22-VRl2)] f(x) A.l 

This equation suggests that the bids from the surveys can be expected to 

be a function of the change 1n visual range considered and of the base 

level (VRl) and new level (VR2) of visual range hypothesized. The function 

f(x) was presumed to be held constant across the different studies. The 

variables used In this analysis are defined in Table A.l and the entire 

data set used can be found in Table A.2. 
_EJ 

A-2 

TABLE A.l 

VARIABLES USED IN ANALYSIS OF RESULTS FROM CONTINGENT VALUATION STUDIES 

Varlaala Oaacrlpcloa M«a_ 

CITT 

BID 

V U 

912 

DVB 

POMXIJ 

DIfSO 

pncmr 

LOOUT 

BANC 

DIST 

VIST 

Clclta vhare tha aaans vara teelaattd—tattrad 

saparately If aera than eaa city covered la ana 

ftudy. Value codas aa follows (dace of Surrey)t 

1 • Chicago - Tolley ae al. (1981) 

2 • Atlanta - Tolley et al. (1982) 

3 - Boston - Tolley at al. (1982) 

4 • Cincinnati - Tolley at al. (1982) 

3 - Nlaal - Tollay at al. (1982) 

• - Nobila - Tolley tt al. (1982) 

7 - Vashlngton DC - Tollay at al. (1982) 

* I • Los Angtlts - Brookshlrt tt al. (1978) 

9 • San Francisco - Loahaan at al. (1980) 

10 • Cincinnati - Raa at al. (1982) 

11 • Partington, Nav Naxleo • lovt at al. (1977) 

• 

Annual vllllngnaflt to pay par household la 1984 

dollars. Hid points of ranges vara used for Baa 

study. Format C2 (payaant card vith prlvaca and 

public goods) vaa used far Tollay ac al. pracaat. 

Visual range In alios chat vaa tha praauaad 

starting palnc far tha hypothaalsad chaaga 

Visual raaga la alias chat vaa tha hypothesised aav 

leval 

Chaaga la visual ranga hypothaalsad (VTL2 - VII) 

IXB/091 

((VI2)2 - <7I1>2) 

0V1/VB 

L0G(VB2/VU) 

1 • contingent ranking atthod vaa ustd. 

1 • visual raaga vaa presented aa a distribution of 

strraral lavala, aat a siagla avaraga value. 

1 • study vaa a prataat far a largtr effort. 

1 • study conducted la tha Vttttrn U.S. 

100.47 

14.98 

19.48 

4.50 

29.64 

-4.74 

.82 

.34 

.17 

.17 

.19 

.19 
P.3 

A-3 

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_FM_ 

A-4 

Four dummy variables were defined for study characteristics that might 

influence the value estimate. These are: RANK, DIST, PRETEST, and WEST 

and are defined in Table A.l. 

Table A.3 shows the OLS estimates of Equation A.l. Both DVR and DIFSQ 

are significant. The negative coefficient for DIFSQ combined with the 

positive coefficient for DVR indicates that over the range of visibility 

considered in these studies, the value Increases with bigger changes in 

visual range, but at a decreasing rate. 

An example of the procedure calculating the middle estimate benefits 

for the percent reduction alternative 1s 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; 2000 projected population 

- 4,415,000, we estimate the 1997 Alabama population to be 4,353,714 people 

and the number of households in 1997 to be 1,501,988. The middle estimate 

for benefits 1s Equation A.l. [(19.74) (13.5-13.4)-(.17)(13.52-13.42)] 

times 1,501,988 households times 1.047 (1982 to 1984 Consumer Price Index 

inflator) or $2,385,134. This number 1s the estimate of visibility benefits, 

In Alabama, In 1997, expressed 1n constant January 1984 dollars. 

Visibility benefits are aggregated across time by discounting 

back to January 1984 with a 10% real discount rate. The discount formula 

for year n 1s 1 . Therefore, the Alabama 1997 local 

(1 • .l)""" 8 4 

1 13 

visibility benefits become $2,385,134* ( O ) - $690,888. These 

discounted values for the years 1990 through 2000 are added to reach an 

estimate for each state and the totals for each of the thirty-one states 

are added to give the thirty-one state total. 
P.5 

A-5 

TABLE A.3 

REGRESSION ESTIMATES OF EQUATION A.l FOR ALL CONTINGENT VALUATION STUDIES 

WITH DUMMY VARIABLES FOR DIFFERENCES IN STUDIES 

Variable Coefficient t-statistic 

DVR 19.74 5.62 

DIFSQ -.17 -3.11 

RANK 268.15 3.28 

DIST -98.41 -1.14 

PRETEST -5.23 -.10 

WEST -6.39 -.09 

N2 • 36 

R = .77 

F = 16.33