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Table C-2 shows the calculated age-standardized lung-cancer rates by
smoking category in the two areas. The difference in lung-cancer rates
between the two areas, averaged over the smoking categories, is
approximately 74. Assuming that this difference is due totally to general
air pollution, which was mainly the result of inefficient burning of coal,
we may express these rates approximately in terms of Equation 2, with t
taking the value 55, and hence in terms of equivalent U.K. cigarettes.
These calculations estimate the effect of the additional BaP air pollution
in the urban area as the equivalent of 1.09 U.K. cigarettes. Thus, we
estimate
BaP-coal-burning at 52.5 ng/m3 = 1.09 U.K. cigarettes
or BaP-coal-burning at 48.2 ng/m3 = 1 U.K. cigarette.
Therefore, even though Stocks failed to address the issue of lifelong
smoking habits satisfactorily, his data suggest a figure for BaP-coal-
burning that is not much different from BaP-carbonization. If we use only
the data on nonsmokers in Table C-2 to estimate the effect of BaP-coal
burning, we f ind that
BaP-coal-burning at 128 ng/m3 = 1 U.K. c ;garette .
RATES IN NONSMOKERS
The study of Stocks38 has been criticized, because he obtained data
on many of the lung-cancer patients from relatives after the patients'
deaths . This would especial ly tend to exaggerate the lung-cancer rates in
the "nonsmokers." Dol 1 sugges ted that a more accurate lung-cancer
figure for nonsmokers could be obtained by combining the data on lifelong
nonsmokers from the prospective studies of Kahol9 and Hammondl3 in the
United States. The combined data (Table C-5) show a lung-cancer mortality
rate for nonsmokers roughly 45% of that found for nonsmokers in rural
North Hales by Stocks. This is the relevant comparison, because the
average BaP concentration in urban air in the United States in 1959
was roughly ~ ng/m --a figure very close to that of rural North Wales in
1954.
Dolls showed that Equation 2 provided an excellent fit to the
combined nonsmoker data from Kahn1 and Hammond (see Table C-5), and
the best fit is obtained with the equivalent number of U.K. cigarettes
~ smoked from birth) set at 0.14. If these lung cancers were due totally
to BaP-U. S. pollution, we could conclude
BaP-U.S. pollution at 6 ng/m3 = 0.14 U.K. cigarette
or BaP-U. S . pollution at 42 ng/m3 = 1 U.K. cigarette .
Thi s may be cons idered a reasonable upper 1 imit of the potency o f
BaP-U. S. pollution in nonsmokers.
C-11
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REGRES S ION STUD IES
A ~nultiple-regression analysis undertaken for the National Research
Council Subcommittee on Particulate Polycyclic Organic Matter26
attempted to "explain" the annual lung-cancer death rates (per 100,000) in
1950-1969, Y. in the 48 contenminous states of the United States by the
independent variables
X1 = cigarette sales per person over 15 yr old (1963),
in dollars,
and X2 = BaP in air, in ng/m3 (1967-1969~.
typical result obtained was
Y = 89.4 + 1.44 X1 + 7.05 X2
for white men aged 55-64. The observed average lung-cancer mortality rate
for such men for the 48 states was 140.6.
There are a number of major problems with this approach, which are
discussed at length in the report--in particular, the crudity of both the
cigarette-consumption data and the air-pollution figure for a whole
state. The regression equations also predict lung-cancer mortality rates
in the absence of smoking or air pollution that are much greater than the
observed lung-cancer incidence in nonsmokers. For example, DollS gave a
figure of 13.9 (compared with the above figure of 89.4) for the lung-
cancer mortality rate in this age group on the basis of the combined
results of Kahn 9 and Hammond. 1
Other regression studies have similar problems, leaving them useless
for quantitative risk assessment.
COMPARATIVE CARCINOGENICITY OF DIFFERENT AIR-POLLUTION MIXTURES
The available epidemiologic evidence reviewed above suggests that the
carcinogenic potencies of various air-pollution mixtures (coal
carbonization, coal-burning, and general U.S. pollution) are similar when
expressed in terms of the BaP content of the mixtures (Table C-6~. We
have no useful epidemiologic data on cases in which the major con-
tributor to air pollution has been mobile sources; to estimate the effects
of such air pollution, lie must use the results of animal-
carcinogenesis studies and short-term mutagenesis assays.
This approach was used by Harris;15 Table C-7 shows the assay
results he considered. Tables C-8 and C-9 show the relative potencies of
the various contributors to air pollution computed from the data in Table
C-7. Coke-oven extract is taken as the standard, and the results are
expressed on a constant-weight-of-extract basis in Table C-8 and ~
constant-weight-of-BaP basis in Table C-9. For example, with the SENCAR
C-12
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mouse assay, roofing-tar extract is 0.255 (0~535/2.101) times as potent as
coke-oven extract on an equal-weight basis and 0.137 [~0.255~478/889~]
times as potent as coke-oven extract on a constant-weight-of-BaP basis.
Tables C-6 and C-9 may be used together to predict the lung
carcinogenicity of exposure to spark-ignition or diesel engine exhaust.
Table C-9 sugges ts that exposure to a fixed amount of BaP from a Mustang
mixture will be between 0.06 and 2.2 times as carcinogenic as such
exposure to coke-oven pollution. The different vehicles tested vary
widely in diesel-exha~st extrac t. The results shown in Table C-9 suggest
that exposure to a fixed amount of BaP from diesel exhaust will be between
O.1 and 89 times as carcinogenic as such exposure to coke-oven pollution.
If we consider the L5178Y+ assay as the assay of choice, the
predicted lifetime (age 50) lung-cancer risk associated with exposure to
air polluted by a 1-ng/m BaP source for mobile-source emission is given
in Table C-10.
OTHER CANCER SITES
Increased rates of cancer at sites other than lung were observed in
the study of British gasworkersl° and in the study of U.S. coke-oven
workers. 2
In the study of British gasworkers, an excess risk was noted for
cancer of the bladder (age-ad justed rate per 1,000 of- 0.37 vs. 0.12
expected), for cancer of the skin and scrotum (0.10 vs. 0.00), and for
cancer at all other sites combined (2.73 vs. 2.27~. Because the excess
risk of cancer of the skin and scrotum is extremely unlikely to be due to
inhalation exposure, the maximal excess rate of all cancer except lung
cancer that can be attributed to gasworks exposure is 0.71 (3.10 - 2.39~.
The comparable figure for lung cancer is 2.12 (3.61 - 1.49~. Lung cancer
therefore accounts for at least 75% (2.12/2.83) of the excess cancer
associated with this British gasworks pollution.
Similar calculations from the study of Redmond et al.32 for men
employed 5 yr or more in the most polluted area (topside) of the U.S. coke
ovens show that lung cancer accounted for at least 83t ( 17.6/21. 1) of the
excess cancer associated with U. S. coke-oven air-pollution exposure.
FOOD
The estimated daily intake of BaP in food is 160-1,600 ng (see Table
6-25~. No epidemiologic studies are available to permit one to estimate
the possible carcinogenic effect of such an intake of BaP, and recourse
must be made to animal experiments.
The experiment of Neal and Rigdon,~8 referred to in Chapter 4,
found that BaP administered to mice in their diet produced forestomach
tumors. With the extrapolation procedure used by the National Research
Council Safe Drinking Water Committee, it can be calculated that a
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daily human intake o f 47 ng of BaP would lead to a lifetime risk of 1 in
100,000. With this estimate, we may calculate that the daily intake of
160-1,600 ng of BaP translates into an estimated lifetime cancer risk of
3.4-34 in 100,000. The estimated daily intake of PAHs in food is 10 times
the intake of BaP (see Table 6-25), so one would estimate the total
lifetime cancer risk associated with exposure to BaP and other PAHs in
food at something less than 10 times these figures.
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TABLE C-1
Lung-Cancer Mortality Ratios for Smokers of High-, Medium-,
and Low-"Tar" Cigarettes$ 1960-1972a
#ITarl1
Content,
mg/cigarette
High (30)
Medium (22.5)
Low {15)
aData from Hammond et a1.14
_ _
C-15
Mortality RaLio
Males Females
1.0 1.0
0.95 0.80
0.81 0.60
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TABLE C-2
Lung-Cancer Mortality Rates of Men in Rural (North Wales)
and Urban (Liverpool) Areas, 1952-1954, by Past Smoking Habitsa
Lung-Cancer Rateb
Smoking Category Rural Urban
_
Nonsmokers 22 (2) 50 (3)
Cigarette-smokers:
App. 10 cigarettes/d . 68 (23) 168 (71)
App. 20 cigarettes/d 147 (36) 248 (140)
App. 35 cigarettes/d 317 (33) 344 (138)
aData from Stocks (p. 80~.38
bPer 100,000 per year, standardized for age. Figures in
parentheses are numbers of lung-cancer deaths.
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TABLE C-3
Lung-Cancer Mortality Rates of Men, Aged 35-74, in Japan,
by Area Pollution and Smoking Habitsa
Lung-Cancer Rateb
Low
Pollution
Smoking Category
Intermediate High
Pollution Pollution
Nonsmokers 11.5 (5) 3.8 (1) 4.9 (1)
Exsmokers 26.2 (11) 42.6 (7) 61.7 (7)
Cigarette-smokers:
1-14 cigarettes/d 10.6 (9) 14.2 (10)
23.5 (14)
15-24 cigarettes/d 14.7 (18) 19.1 (17) 27.0 (17)
25+ cigarettes/d 36.3 (19) 15.8 (4) 46.4 (9)
aReprinted from National Research Council26 (Table 17-26~; data derived
from Hitosugi.16
bPer 100,000 per year, standardized for age.
numbers of lung-cancer deaths.
C-17
Figures in parentheses are
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TABLE C-4
Smoking Habits and Lung-Cancer Mortality Rates of
Bri tish Gasworkers
Non- Ex
smokers, smokers,
OF
~0
Population
"Exposed"
gasworkers
Othe r
gasworkers
8.3 10.2
a
~0
Cont inning Smokers, %
Pipe Mixed 1-9 10-19
Lung
Canc e r
Cigarettes/d Mortality
Ratea
6.7 4.4 18.1 38.5 13.9
5.8 15.3 5.9 6.2 17.8 35.5 13.4
aPer 100, 000 per year, standardized for age.
C-18
3.61
1.49
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TABLE C- 5
Lung-Cancer Mortali ty in U. S . Nonsmokersa
Age, yr
35-44
45-54
55-64
65-74
75-84
Annual Mortality Rate,
per 100, 000
2.8
5.8
13.9
25.6
49.4
aReprinted with permission from Doll, 5 based
on data from Kahnl9 and Hammond.l3
C-19
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TABLE C- 6
Estimates of Lifetime (7C yr) Lung-Cancer Risk from
Exposure to BaP Source at 1 ng/m3
Study
Populat ion Risk, per 100, 000
Li f e t ime Lung-Cance r
Gasworkers 43
L iverpoo 1
North Wales
Al 1 men
Nonsmoke r s
Nonsmokers
-
S3
20
<61
C-20
Re ferenc e
Doll _ al.6310
S tocks38
DollS
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TABLE C-7
Estimates of Potency of Organic Extracts from Various Sources
of Air Pollutiona
Viral
SENCAR Trans- L5178Ye
Source Bapb Micec formationd -
.
+
Coke oven478 2. 101 0.859 0. 726 9.963
(gasworks)
Roofing tar889 0. 535 2.066 0. 311 9. 55 6
Caterpillar2 0.011 0.039 0.156 0. 049
3304 D
Oldsmobile2 O. 156 0.067 0.970 0. 764
350 D
Volkswagen26 -- 0.128 2.545 1. 012
Turbo D
Mus tang II103 0. 02 7 0. 204 0. 348 0 . 990
302 V-8 ?
catalyst
aData from Harris.15
bNanogram.s of BaP per mi 11 igram of extract .
CTumor initiation in SENCAR mice, papillomas/mouse per milligram of
extract at 27 wk.
dEnhancement of SA7 viral transformation in Syrian hamster embryo cells,
transformations per 2 x 10~ cells per nanogram of extract per milliliter.
eL5178Y mouse-lymphoma mutagenesis assay (average mutant colonies/106
survivors per microgram of extract per milliliter) without (-) and with (+)
metabolic activation.
C-21
-
OCR for page 438
30. Pike, M. C., and B. E. Henderson. Epidemiology of polycyclic hydro-
carbons: Quantifying the cancer risk from cigarette smoking and
air pollution, pp. 317-334. In H. V. Gelboin and P. O. P. Ts'o, Eds.
Polycyclic Hydrocarbons and Cancer. Vol. 3. New York: Academic
Press, 1981.
31. Raffle, P. A. B. The health of the worker. Brit. J. Indust. Med.
14:73-80, 1957.
32. Redmond, C. K., A. Ciocco, J. W. Lloyd, and H. W. Rush. Long-term
mortality study of steelworkers. VI. Mortality from malignant neo-
plasms among coke oven workers. J. Occup. Med. 14:621-629, 1972.
33. Royal College of Physicians of London. Smoking or Health. The Third
Report from the Royal College of Physicians of London. London:
Pitman Medical Publishing Co. Ltd., 1972. 128 pp.
34. Santodonato , J ., P. Howard , and D. Basu. Heal to and ecological
assessment of polyouclear aromas ic hydrocarbons . J. Environ. Pathol.
Toxicol. 5:1-364, 1981.
35. Sawicki, E. Airborne carcinogens and allied compounds. Arch. Environ.
Health 14:46-53, 1957.
36. Sawicki, E., W. C. Elbert, T. R. Hauser, F. T. Fox, and T. W. Stanley.
Benzota~pyrene content of the air of American communities. Amer. Ind.
Hyg. Assoc. J. 21:443-451, 1960.
37. Segi, M., M. Kurihara, and T. Matsuyama. Cancer Mortality for Selected
Sites in 24 Countries. No. 5 (1964-1965~. Department of Public
Health. Sendai, Japan: Tohoku University School of Medicine, 1969.
174 pp.
38. Stocks, P. Cancer in North Wales and Liverpool regions. Supplement to
British Empire Cancer Campaign Annual Report, 1957.
39. Stukonis, M. K. Cancer incidence cumulative rates. IARC Internal
Technical Report No. 78/002. Lyon, France: International Agency for
Research on Cancer, 1978.
40. U.S. Department of Health, Education, and Welfare. Office on Smoking
and Health. A Report of the Surgeon General. DHEW PubLication No.
(PHS)79-50066. Washington, D.C.: U.S. Department of Health,
Education, and Welfare, 1979. 1196 pp.
41. -~aller, R. Trends in lung cancer in London in relation to exposure to
diesel fumes, pp. 1085-1099. In HeaIth Effects of Diesel Engine
Emissions: Proceedings of an International Symposium.
EPA-600/9-80-057b. Cincinnati: U.S. Environmental Protection Agency
Office of Research and Development, 1980.
42. Wynder, E. L., and D. Hoffmann. Experimental tobacco carcinogenesis.
Science 162:862-871, 1968.
43. Wynder, E. L., and D. Hoffmann. Tobacco and Tobacco Smoke: Studies in
Experimental Carcinogenesis. New York: Academic Press, 1957. 730 pp.
44. Wynder, E. J~., K. Mabuchi, and E. J. Beattie. The epidemiology of
lung cancer. Recent trends. J.A.M.A. 213:2221-2228, 1970.
45. Wynder, E. T.., and S. O. Stellman. Impact of long-term filter
cigarette usage on lung and larynx cancer risk: A case-control study.
J. Natl. Cancer Ins t. 62:471-477, 1979.
C-28
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APPENDIX D
PUBLIC DECISION-MAKING WITH RESPECT TO ATMOSPHERIC
PAH SOURCES AND EMISSIONS
Lawrence J . Whi te
Among the possible justifications for public decision-making with
respect to P~\H sources and emissions would be a finding that PAHs pose an
actual or potential (and nontrivial) threat to human health. This appendix
uses the cancer-risk estimates developed in Appendix C. It assumes that
benzotaipyrene (BaP) can be used as a proxy for PAHs and that human 3
exposure to BaP in the ambient air at an average concentration of 1 ng/m
over an entire lifetime has the effect of increasing by 0.02-0.06% the risk
of dying prematurely (at or before the age of 70) because of lung cancer.
Although the appropriateness of BaP as a surrogate for PAHs in general has
been questioned, it has been so used extensively in the past, and much of
the available information refers to it as an indicator for exposure to
PAHs. The estimates of Appendix C are also based on this application. The
focus of this appendix is on the lung-cancer consequences of human exposure
to atmospheric sources of PAHs.
The rationale for public decision-making with respect to PAH emissions
from atmospheric sources is explored first, followed by discussions of the
general problems of developing the appropriate decision-making tools,
deciding on appropriate levels of control, and choosing appropriate means
of implementing the decisions. The principles developed are then applied
to PAH emissions of various sources, within the constraints of the limited
amount of information that is available. These efforts should be viewed
primarily as illustrative and approximate, because the data available are
rough and approximate. Complete analysis would require a direct linking of
the damage caused by an air pollutant to the sources of its emission. For
that, the following would be needed: data on emissions of the pollutant, a
model of the pollutant's dispersion and possible transformation or decay
during dispersion, estimates of the resulting concentrations in the ambient
air, data on human exposure to those concentrations, and a model of the
exposure dose-response relationship. Reliable estimates of the costs and
consequences of control are also needed. With respect to all these
subjects, the relevant data on PAHs are scanty and approximate, and
compromises will have to be made. Some estimates may be in error by as
much as an order of magnitude. Nevertheless, the results should be
informative and point the way toward further appropriate study.
RAT IONALE
PAH emissions from atmospheric sources are in a category of phenomena
that economists have labeled "negative externalities" or "negative
spillovers." The designations imply that people are taking actions (e.g. ,
producing coke, driving vehicles, and burning refuse) that generate, as
byproducts or as incidental consequences, uncompensated costs imposed on
D-]
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other parties, outside of a market context; i.e., the PAR emissions pro-
duced incidentally by these activities ultimately have potentially un-
favorable health consequences for others. In such situations, persons who
are motivated largely by the prospect of private gain (or, in the case of
firms, private profit) are unlikely to take corrective action. Without
incentives for corrective action, too much of the activity will occur, and
too little effort will be devoted to reducing the costs imposed on others.
An externality is an indication of a market failure;3 i.e., even an
otherwise properly functioning competitive economy will not achieve an
optimal allocation of society's resources, because of the distortion
introduced by the externality. In a private-enterprise economy, the source
of the problem created by an externality can be traced to an ill-defined
property rights (neither the emitters of PAHs nor those who are exposed
have a well-defined property right to the ambient air and its cleanness) or
to the difficulties of enforcing a property right. The latter difficulties
are usually due to the "public-goods" aspects of the phenomena; e.g.,
because an improvement in air quality in a locality will be enjoyed by all,
each individual has an incentive to let others make the necessary effort to
enforce emissions reductions, and this incentive for "free riding" leads to
too little (or no) action.
Externalities (especially those involving public-goods aspects) provide
a case for possible public intervention in a private-enterprise economy.
But whether, in practice, government intervention to correct an externality
increases or decreases societal welfare is an empirical question.
LEVELS OF CONTROL
.
Once an externality has been identified and the decision has been made
that some kind of corrective action is warranted, further decisions must be
made on the extent of corrective action (e.g., the desired degree of
reduction in PAH emissions or the amounts of PAHs that will still be
allowed to be emitted) and on the specific tools that are to- be used to
implement the desired level of control. This section addresses the former
issue, leaving the latter for the next section.
The control of an externality brings societal benefits: a reduction in
the externality costs imposed on others. In the case of PAHs, reductions
in PAR emissions that translate into reductions in human exposure to PAHs
mean the avoidance of some premature deaths (frequently termed "the saving
of lives") and the avoidance of PAH-induced illness. But the achievement
of these benefits almost always involves societal costs: individuals and
firms must be induced to change their behavior with respect to emissions,
engage in less of their desired activities, and incur costs (use real
resources) to reduce emissions.
Society's resources are scarce--in essence, society does not have
limitless resources and cannot achieve all its desired objectives
simultaneously, but must choose among them--and any level of externality
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control involves both societal benefits and societal costs; therefore,
decisions concerning levels of control should focus on levels that best use
society's scarce resources in trying to maximize societal welfare--i.e.,
society ought to aim for levels of control that provide the greatest margin
of benefits relative to costs.
Two main analytic tools have been developed that can aid decision-
makers in choosing the appropriate levels of control: cost-effectiveness
analysis and cost-benefit analysis. Cost-effectiveness analysis is the
more limited of the two. It takes, as a given, a specific societal goal
(ob jective)--~.g., a reduction in emissions by X tons of a specific
pollutant or the incurring of only up to Y dollars for the reduction of
emissions from a specific source of that pollutant. The principle of
cost-effectiveness requires a search to identify the least costly way of
achieving a reduction in pollutant emissions. If all sources of the
pollutant have equal environmental consequences, then the emission source
with the lowest marginal (incremental) cost of control should be chosen.
For example, if one source has a marginal control cost of t500/ton and
another a marginal cost of $3,000/ton, the first should be chosen over the
second. The choice of the first will mean that the achievement of emission
reduction by X tons will require less resources, or the expenditure of Y
dollars will achieve a greater reduction. The formal principle is that, in
achieving the goal, the marginal costs of control from all sources ought to
be equated. If this principle is violated, then the cost of achieving a
given level of overall control could be reduced (or the level of overall
control achieved at given costs could be increased) by increasing the
stringency of control from the low-marginal-cost sources and decreasing the
stringency of control from the high-marginal-cost sources.
Cost-effectiveness analysis can be a useful tool for improving the
efficiency of individual programs and for comparing the effectiveness of
similar programs. But cost-effectiveness analysis cannot be used to answer
the ultimate policy questions: "Should X tons or lOX tons of
pollutant-emission reduction be the appropriate societal goal?" "Should a
cost of Y dollars or 20Y dollars be incurred to achieve emission
reduction?" But cost-benefit analysis can provide an analytic basis for
making these decisions.
There are only a few primary steps in a cost-benefit analysis. The
societal benefits and societal costs should be estimated and converted into
dollar equivalents (if they are not already in dollars). An interest rate
(discount rate) must be used to convert future benefits and costs into
present-value equivalents. The projects (or alternative versions of a
project, e.g., alternative levels of stringency of required emission
reductions) with the highest margins of benefits relative to costs should
be the ones chosen. An equivalent principle is that, in choosing among
alternative versions of a project (say, alternative levels of emission
control stringency), stringency should be adjusted until the marginal
benefits of extra stringency are just equal to the marginal costs The
basic methods of cost-benefit analysis are, by now3 standard;13~3
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controversies rem2gin, however, as to the interest rate that should be used
for discounting, whether the income-distribution consequ9ences of
pro jects should be considered explicitly in the analysis,] how to
incorporate risk and uncertainty into the analysis, and how (and whether)
to place dollar values on nonmarket items and concepts.
In this last category, a frequent question that arises in the context
of cost-benefit analysis applied to projects or programs that have
mortality or morbidity consequences (e.g., many pollutant-emission control
programs) is how (and whether) to evaluate the benefits of mortality or
morbidity reduction. Claims that "a life is priceless" and that "one
cannot put a value on a life or on pain and suffering" are often heard. A
logical implication of these claims seems to be that cost-benefit analysis
is useless in such instances--that for such projects, so long as any
mortality reduction ("lives to be saved") or morbidity reduction (reduction
in "pain and suffering") can be achieved, a project or program should be
pursued (or extra stringency pursued), regardless of costs.
This approach to the benefits of reductions in mortality or morbidity
does not provide a useful guide for making societal decisions, because the
opportunities for achieving reductions in mortality and morbidity are
virtually limitless. Additional resources devoted to medical research,
medical care, accident prevention, and pollution reduction are likely to
yield reductions (albeit possibly small) in mortality and morbidity.
Society could use up its entire gross national product by devoting
ever-increasing amounts of resources to the pursuit of such reductions.
But, in fact, we do not. Through our societal decision-making processes,
at some point we desist. For example, in the wake of the Arab oil embargo
of 1973, the Congress enacted a law imposing a national highway speed limit
of 55 mph. The major goal of the legislation was to reduce American
gasoline consumption, but it was soon learned that the 55-mph speed limit
had the beneficial side effect of reducing highway mortality. There have
been no efforts to reduce the speed limit to, say, 45 mph, although such a
reduction would clearly reduce highway mortality even more. Similarly,
society does not build pedes trian underpas ses for every busy urban
intersection and does not station ambulances near those intersections,
despite the reductions in mortality and morbidity that would be achieved.
In effect, society has decided that the extra mortality and morbidity
reductions are not worth the resources (costs) that would have to be
devoted to achieving them; lines have been drawn.
Drawing these lines has been a largely implicit process; drawing them
explicitly apparently makes many people uneasy. They are reluctant to put
a value on mortality or morbidity reductions. But a society that wishes to
achieve the best that it can from its scarce resources must understand the
uses to which those resources are put and the tradeoffs (the "opportunity
costs") involved. A society may well have multiple goals. Nevertheless,
an understanding of the tradeoffs is important in pursuing them; and the
use of explicit values for mortality and morbidity reductions is necessary
for that understanding. Furthermore, the logic of cost-effectiveness
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argues for the consistency of these values across projects; otherwise,
societal resources are allocated in an ineffective way, as apparently has
been the case for actual projects and programs involving mortality and
morbidity reductions.
A good case can be made, then, for using explicit values for mortality
and morbidity reductions. There are a number of candidates for
establishing the value of mortality reduction (or, alternatively, "the
value of a lifers:
· The expected discounted future earnings of a person.
o The life insurance held by a person.
· The average (or some other summary measure) of the implicit
values yielded by other, recent projects or programs involving mortality
reduction.
o Compensation awarded in trials involving premature deaths.
O Estimates of the value that people, in their day-to-day
behavior, place on incurring or avoiding risks of premature death.
For the purposes of deciding on the appropriate levels of pollution
control, Bailey and Freemanl6 (Chapter 4) have reviewed and criticized
these measures. The last measure (risk valuation) is most consistent with
the market valuations that are the other components of cost-effectiveness
and cost-benefit analyses. An important point here is that pollution-
reduction programs (and accident-reduction programs) do not have a knowable
effect on specific persons' lives; they do not involve before-the-fact
specific deaths. Instead, if they are effective at all, they reduce the
probabilities or risks of the premature death of exposed persons. After
the fact, this reduction in risk must mean a reduction in premature deaths;
but before the fact, the programs can be evaluated only in terms of risk.
Because the affected persons benefit from the reduction in risk and
because virtually all people expose themselves to risks in their day-to-day
behavior (whether they acknowledge it or not), the benefit o f the risk
reduction should be roughly comparable with the value of the risks that
they incur or avoid ~ at the margin) in their day-to-day behavior. In
essence, if they are asked, "What would you be willing to pay in return for
a reduction in risk?" or "What would you need to receive to compensate you
for an increase in risk?" their responses should be roughly consistent with
their private behavior. In a market economy, the prices of goods and
services reflect (at the margin) a willingness to pay for those goods and
services. Public projects, to maximize the societal value that can be
achieved from society's resources, should also use willingness-to-pay
measures for valuation purposes wherever possible. Accordingly, the
risk-valuation approach is consistent for assessing pollution-reduction
programs.
There are no specific markets in the private sector where one could
directly observe a person's willingness to pay for risk reduction. But
people do choose to incur or avoid risk, gaining or giving up other things
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in return, in most aspects of their lives: They choose jobs that have
higher or lower risks of accidental death or injury, in return for explicit
or indirect wage premiums; they choose to use or not to use seatbelts
in automobiles, trading off time and convenience against reduced risk of
death or injury in the event of a crash;4 they choose to live in
neighborhoods with higher or lower air-pol lutant concentrat ions, trading
off housing costs against the extra risks of mortality or morbidity from
the pollutants;30 and so on. Economists have been able to provide models
of individual behavior and, with actual data and econometric estimation
techniques, estimate the implicit value that people have placed on the
risks that they have incurred or avoided. For example, to estimate the
wage premium that accompanies extra risk, a researcher could collect a
sample of wage rates for various occupat ions, the ac tuarial data on
accidental deaths for those occupations, and data on the various influences
on wage rates (e.g., degree of unionization, amount of education, extent of
experience). The econometric techniques allow the researcher to control
for the other influences and thus to infer the implicit wage premium that
accompanies extra risk.
Placing a value on reducing the risk of death is very difficult and
controversial. Different values can be assigned. However, the values
discussed here fairly represent the research that has been done in this
field, and they provide a useful re ference guide for decision-making with
regard to pollution control.
Studies of the value of risk do not yield identical estimates, but, as
Bailey showed, they can be grouped (after appropriate adjustments and
corrections) into a range of $170-715 (in 1978 dollars) in annual payment
per 0.O31 (i.e., 0.1%) additional annual risk of death. ~ study by
Portney O yielded an additional estimate that is in the middle of this
range. Freemanl6 argued that the most likely value is $1,000 (in 1978
dollars) per 0.001 additional risk. This same figure was used in the NRC
study (pp. 744-245) of the costs of removing chloroform and other
trihalomethanes from drinking water.2
Some problems of using these studies and the estimates they yield for
evaluating public pollution-control programs should be noted. First, as
with the use of any econometric model, one needs to be satisfied that the
model has been properly specified and all important influences properly
accounted for. Second, the models assume that the persons involved were
aware of the risks they were incurring or avoiding. Third, use of the
models' estimates for public-policy purposes assumes that the persons in
the sample (and hence the estimates of the value of risk) are typical of
the general population. If a wage study included only or mostly high-risk
occupations, the resulting estimate of the value of risk might be an
underestimate of the value that applies to most of the population, since
persons with less fear of risk would likely gravitate toward high-risk
occupations or housing locations--i.e., self-selection might bias the
results. Fourth, people may feel differently about (value differently)
risks over which they have more control (e.g., job choice) and risks over
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which they have less control (e.g., the general level of pollution in the
air they breathe). Finally, even if the models' estimates are representa-
tive of the general population's valuation of risk, individual persons will
have different values of risk and hence different perceptions of, say, the
concentrations for which a pollution-control program should aim. Within a
locality, however, all persons will have to be exposed to roughly the same
po 11utant concentra ~ ions .
The last problem is an unresolvable dilemma that is inherent in the
public-goods aspects of most pollution prowlers, which cause them to be the
proper concern of nonindividualistic, government action in the first
place. This dilemma is present for all public goods (e.g. , national
defense and local police protection) that people consume generally
automatically and equally as part of a community. As Samuelson31 has
demonstrated, the proper procedure for deciding on the appropriate level of
a public-goods project is to sum the valuations of all affected persons and
extend the project to the point at which the sum of the marginal valuations
(benefits) equals the marginal cost of the extension--exactly the criterion
stated in the discussion of cost-benefit analysis.
Despite the possible problems, the range of estimates yielded by the
risk-valuation studies does appear to be reasonable when compared with the
income of a typical family and the safety-related expenditures it would
find worthwhile.
One aspect of the risk-valuation estimates is worth emphasizing. If
one finds that people appear to be willing to pay $500 her year each to
avoid a 0.001 risk of death in a given year, the proper use of this
estimate is as follows: Suppose a government pollution-control program can
reduce the risk of death in a community of 1 million by a factor of 0.001.
Then, because each person, on average, should be willing to value this
improvement at about $500 per year, the 1 million people in the community
should be willing to pay about $500 million per year for these benefits,
and this aggregate value could be compared with the anticipated cost of the
program. In essence, the aggregate cost of the benefit is estimated by
multiplying the typical person's valuation of the risk reduction by the
number of persons involved (reduction in risk per person).
In contrast, the value of risk is sometimes extrapolated to a value of
avoiding (or, in reality, delaying) a death or "the value of [extending] a
life" ; i. e., the $500 per 0.001 risk would be extrapolated to $500,000 as
the value of avoiding a death. It is true that, if the government
implements the hypothetical program just mentioned, there will be 1,000
fewer deaths per year; and, because the program was valued at $500 mill ion
per year, this implies a value of $500, 000 per avoided death. Furtl~er-
more, for some purposes, it is sometimes convenient to speak or write in
terms of "the value of a life" (or the value of a statistical life). But
.
there is nothing in tone statistical or conceptual procedures that leads to
the conclusion that any person would, could, or should pay $500,000 to
avoid a certain death. Rather, before the fact, the government pro ject
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promises a change in risk, not a change in the certainty of death for any
person. People behave toward and implicitly value risk in their everyday
life, so risk valuation is the consistent conceptual procedure to use.
The discussion thus far has focused entirely on valuing mortality
changes. In principle, the same procedures could be applied to valuing
changes in morbidity--i.e, willingness-to-pay measures could be inferred
from persons' behavior. There do not appear to be any studies that have
tried to generate such estimates. Instead, estimates of the medical costs
and lost productivity related to illness and accidents are usually used to
estimate these societal costs (and hence the societal benefits from their
reduction). These estimates may not be too far away from what the
appropriate willingness-to-pay measures, if they existed, would indicate,
except that the former probably underestimate the latter by excluding the
value of avoiding pain and suffering.
Finally3 the limitations of cost-effectiveness and cost-benefit
analysis must be acknowledged. Knowledge about costs and benefits is never
perfect; in some cases, it may be quite imperfect. Risks and uncertainties
often pervade analyses. Society has multiple goals. But, in the end,
society's resources have to be allocated, and those resources are scarce
and have alternative uses. Cost-effectiveness and cost-benefit analysis,
imperfect though they may be, can be aids to effective societal decisions
making.
IMPLEMENTATION
-
Regardless of the target level of control desired, a number of choices
with respect to the implementation of an emission-control program are
possible. A useful dichotomy is provided by the division between fiat
methods (frequently called "command and control") and methods that rely on
the use of economic incentives.
At one extreme, after a desired reduction in emissions (or a desired
level of remaining emissions) has been ascertained, a central regulatory
control agency can attempt to specify to each emitter (or class of
emitters) the reduction or allowable emissions that will be required. If
the agency wished to minimize the societal cost of achieving the emission
reduction, it would try to have complete information about the total and
marginal cost schedules for each of the various emitters and allocate
reduction or emission appropriately, following the precepts of cost-
effectiveness analysis.
At the other extreme, the agency could set an effluent fee that would
require an emitter to pay a specified amount per unit of the pollutant that
was emitted. In the presence of rising marginal costs of control ~ emitters
would find it worthwhile to reduce emissions to the point at which the
marginal cost per unit of pollutant reduction was equal to the effluent
fee. The same knowledge of cost schedules assumed above would allow the
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agency to set an effluent fee that would achieve the same reductions as
those achieved by the fiat method.
As the previous paragraphs indicated, under conditions of complete
certainty, the two methods can achieve the same outcome. But knowledge
about the costs of control is rarely complete. With incomplete knowledge,
the control agency is likely to make socially costly mistakes by improperly
assigning excessive emission reductions to emitters with high marginal
costs of control. The effluent-fee system has an important advantage in
this respect, in that it allows the high-cost and low-cost emitters to sort
themselves out and achieve the lowest overall cost of control through their
own behavior. Incomplete knowledge of costs may also lead to effluent-fee
schedules that are too high or too low, with consequent emission reductions
that are off target. But the schedules can be readjusted by continuing to
observe emissions; incorrect assignments under the fiat method may never be
corrected, because correct cost-information is not automatically revealed.
An alleged advantage of the fiat method is its apparent certainty of
outcome. Emitters will be told to reduce their emissions by a specified
amount, and that reduction "will" be achieved. The effluent-fee method
appears to be more indirect; one has to rely on the cost-reduction
consciousness of firms and individuals to recognize that reducing emissions
(up to a point) is less costly than paying effluent fees. But experience
with pollution-control programs has shown that even the expected certainty
of the fiat method often does not materialize.27~44 Many emission-
control programs are intended to be "technology-forcing"; they try to set
emission standards that are beyond the economical range of current
technology, thus attempting to force the development of advanced
technology. The ostensible sanctions for failure to meet emission
standards are usually severe fines or closure of offending companies. But
if the technology appears not to be available, the sanctions are not
credible or enforceable. Furthermore, regulators may have difficulty in
ascertaining whether the necessary technology is or is not available or
economical or whether a good-faith effort has been made to develop the
needed technology.
As a consequence of these uncertainties, the emitters (especially in an
industry with a relatively small number of large firms) have an incentive
to slow down their own technology development. Thus, the apparent
certainty of success of the fiat programs is not necessarily reflected in
actual practice, as the delays in the implementation of many
pollution-control programs have revealed.
Even if the sanctions behind them are thought to be credible, fiat
methods can lead to the development of inefficient techniques.
Technologies that are low in cost but that may fall short of the standards
are unlikely to be pursued; technologies that can, at low cost, reduce
emissions beyond the point set by the standards will be pursued only to the
point set by the standards; technologies that are expected to be low in
cost but have an uncertain likelihood of probability of success will be
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discarded in favor of high-cost, more certain technologies. An effluent-
fee system would not have these inefficiency properties.
Another method of control that retains most of the incentive properties
of effluent fees, but also has some of the possible quantitative certainty
of a fiat system, is a system of marketable emission permits.! Under
this system, the central regulatory agency sets a target of maximal total
emissions of a given pollutant. It then creates a set of permits equal to
this total . The permits are, in essence, a property right in a given
amount of emissions. No one is allowed to emit without a permit; thus,
each emitter must control emissions down to the point for which permits
have been received. The agency could auction off the permits to the
highest bidder (thus lodging the property right in clean air initially with
the government) ~ or it could initially assign the permits among emitters'
or even among the population generally, in some manner (thus initially
ass igning the property rights in the manner chosen) . If the permits are
auctioned or can be traded, emitters will again sort themselves into an
efficient, least-cost pattern, with low-cost emitters choosing to control
emissions more and buying relatively fewer permits and high-cost emitters
doing the opposite.
It is clear that, with appropriately chosen targets (costs and
emissions), an effluent-fee system and a marketable-permit system can
achieve the same outcome with comparable incentive effects. One difference
between them is that the effluent-fee system always implicitly lodges the
property right with the government, whereas the marketable-permit system
may lodge the property right with the government (if the auction method is
used) or in the private sector (if some assignment scheme is used).
Another difference is in the identity of the group that bears the risk in
the event O2f uncertainty about or variation in emitters' marginal-cost
schedules.3 In an effluent-fee system, variation in marginal-cost
schedules will mean that variation can be expected in the quantities of
emissions; thus, the risk is borne by those who are exposed to the
emissions. In a marketable-permit system, variation in marginal-cost
schedules will mean variation in the prices paid for the permits; the risk
is borne by the emitters. The choice between the two systems on these
grounds should be determined by examining the societal cos ts of lodging the
risk with one group or the other. If, for example, the health consequences
of small variations in emissions could be severe, a marketable-permit
scheme would be preferred; if, however, the health consequences of small
variations in emissions are not severe and the price variance of permits
would cause firms to take relatively costly offsetting actions, the
effluent-fee system would be preferred.
Even within the context of a fiat system, there are measures that
increase the scope of economic incentives and efficiency. For stationary-
source emissions, a "bubble" strategy that allows individual firms to trade
off pollutant emission from different sources (e.g., different smokestacks)
at the same geographic location provides the possibility of reducing the
cost of controlling emission by a given amount.23 ~ 25 In essence, an
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Representative terms from entire chapter:
coke oven
