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Annu.Rev. EnergyEnviron. 1993. 18:319-42
Copyright©1993by AnnualReviewsInc. All rights reserved
ECONOMIC VALUATION OF
AIR POLLUTION
ABATEMENT:
Benefits from
Health Effects
Luis A. Cifuentes
Department of Engineering and Public, Policy, Carnegie Mellon University
School of Engineering, Catholic University of Chile
&
Lester B. Lave
Graduate School of Industrial
Administration
Public Policy, Carnegie Mellon University
& Department of Engineering and
KEYWORDS:energy
economics, energy policy, mortality,
morbidity, externality
adders
CONTENTS
INTRODUCTION ..........................................
METHODS TO ESTIMATE BENEFITS ...........................
ESTIMATING THE BENEFITS OF ABATEMENTUSING THE DIRECT
METHOD ........................................
Local or National Estimates?
.................................
Estimating the Health Effects of Air Pollution ......................
Estimation of the Marginal Benefits of Pollution Abatementfor the United States
SUMMARY .............................................
319
320
322
322
323
335
338
INTRODUCTION
The environmental
effects
of energy production
and use have been studied
for more than two decades. Most studies
have focussed on identifying
and
quantifying
the effects,
without trying to ascribe a dollar value to them
(1-8). A few studies have assigned monetary values to the effects (9, 10).
Interest in the area has increased rapidly in the 1990s, due in part to concern
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about global climate change and using market mechanisms to improve
environmentalquality (11).
Economistsfinally convincedthe USCongressand regulators that effluent
fees are efficient waysto manageexternalities from environmentaldischarges
(12-17). In order to implementeffluent fees, economists have been called
uponto estimate the dollar value of these externalities (18).
Wereview the state of the art of estimation of benefit from air pollution
abatement, and propose national average estimates for the benefits of
abatementfor several air pollutants.
Economists were unprepared for the rapidity with which public service
commissionsfrom about 30 states turned to the use of "externality adders"---estimates of the social loss from having an additional ton of each
pollutant released into the environment. Since no consensus existed, Public
Utility Commissions(PUCs) have adopted bizarre estimates that bear
resemblance to the marginal benefits of abatement that they are intended
to approximate. For example, Massachusetts, NewYork, and California set
disparate externality adders, none of which is closely tied to estimates of
the economicbenefits of abatement (see for exampleRef. 19).
METHODS TO ESTIMATE
BENEFITS
Figure 1 showsthe flow from emissions to ambient concentrations to physical
effects and finally to social valuation of the effects. This frameworkassumes
that valuation is done by humans. If humansvalue wilderness and species
diversity, they have social value; animals, plants, and buildings are valued
only through humanperceptions and values. The damagesfrom air pollution
are taken to be the same as the benefits from abatement.
Environmental discharges can offend consumers because of odors, obscured visibility, and other directly perceived consequences.The discharges
can also damagehealth, materials, and agricultural and ornamental plants.
The most important damages considered in past studies have been direct
effects on the health of the populationboth morbidity (illness and disability)
and mortality (death). Amongmorbidity effects are increased incidence
asthmaattacks, cough, eye irritation, etc.
Economists have used both direct and indirect methods to estimate the
value of changes in environmentalquality. The direct or "damagefunction"
methodof estimating marginal benefits requires working through each of
these steps: (a) estimating the change in environmental quality resulting
from changes in emissions, (b) estimating the effects (damages) from
degradation in environmental quality, (c) estimating whatever change
behavior occurs because of the degraded environment, and (d) valuing the
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AIR POLLUTION ABATEMENTBENEFITS 321
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damages. Each of these steps is difficult, requiring extensive data and
analysis.
Uncertainties complicate the interpretation and use of each step and the
resulting estimates (20, 21). It is importantto give an explicit characterization
of uncertainty, both for the resulting social costs and each individual step.
Manyanalysts tend to overlook behavior change that mitigates damage.
For example, home-ownerswill not continue to plant ornamental plants that
are highly sensitive to local air pollution, and farmers will not try to grow
crops that are continually damagedby pollution. Also, by separating the
effects and pathwaysof each pollutant, interaction effects betweenpollutants
can be lost.
Several "indirect methods"have been developedto finesse the difficulties
and uncertainties of the direct method. These indirect methods focus on
market valuations or observed behavior, assumingthat consumersare aware
of environmentalquality and that their preferences are reflected in observed
market prices and behavior. Althoughthe simplicity of the indirect methods
is appealing, we question their basic assumptions, as well as the interpretations of their results. Thus, we focus on the direct methodin the rest of
this analysis. For reviews of the indirect methods, see (10, 22-24).
ESTIMATING
THE DIRECT
THE BENEFITS
METHOD
OF ABATEMENT
USING
Weconsider only the health effects on humansof sulfur oxides (SOx),
nitrogen dioxide (NO2), particles, and ozone. These health effects are the
most important.
Local or National
Estimates?
In evaluating the marginal benefits of pollution abatement, we have two
options. Wecould analyze the local effects of air pollution, and then attempt
to generalize to other sites. Unfortunately,this generalization is not straightforward: it would require analyzing several representative sites and then
averaging the results. It is not evident that the resulting estimates wouldbe
meaningful.
Alternatively, we could estimate "average" values for a state or region.
Deriving "average" values for a region results in more uncertain estimates,
because the details of topography, meteorology, and population distribution
are ignored. However,these estimates are intended to represent a broader
range of situations. Our objective is to obtain average data values that can
be used nationally as a reference. Weestimate the relationship between
emissions and ambient concentrations and the size of the population exposed
to the resulting change in ambient concentrations on a national basis.
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AIR POLLUTIONABATEMENT
BENEFITS
Estimating
the Health Effects
323
of Air Pollution
The first step is to establish that air pollution causes morbidityand mortality.
The second step is to estimate the quantitative magnitude.
Studies on the health effects of air pollution can be classified as clinical
or epidemiological.
EPIDEMIOLOGIC
STUDIES
The standard methods of epidemiology consist of
cohort- and case-controlled studies. A population-based approach can be
used wherestatistical controls are substituted for controls in data collection
in order to utilize standard demographicand public health data, e.g. Lave
& Seskin (25).
The cost of cohort studies has limited sample size, and so the studies
have focussed on investigating causality (26). One study design uses each
subject as his or her owncontrol by contrasting the incidence of symptoms
on polluted days with those on days of good air quality (27).
Most of the estimates of the concentration-response relationship come
from population-based studies [Lave & Seskin (25), Schwartz & Marcus
(28), Portney & Mullahy (29), etc]. Because these studies utilize
collected for a different purpose, they are subject to criticism. For example,
there is no measure of cigarette smokingin the studies of Lave &Seskin,
Schwartz & Marcus, and Ozkaynak & Thurston (30). Thus, these studies
are criticized for not having measuresof important variables that are known
to affect the prevalence of the health conditions being studied. In some
studies, e.g. Lave & Seskin, population data on smoking rates are used.
In time-series studies, the assumption is that the smokingrate does not
change over time. However,if people tend to smoke more when the air is
polluted, the estimated effect of air pollution will be overstated. The reverse
is true if people smokeless whenthe air is polluted.
A general problemfor almost all the studies is that the measurementfor
air pollution is that of outdoorair at a few points in the city or metropolitan
area. Since people spend less than 10%of their time outdoors (not in
vehicles), this air pollution measureneed not be closely associated with the
air they actually breathe. In cross-sectional studies (whichcontrast air quality
and health measuresacross cities), the implicit assumption is that the air
quality measurementsin each area are about equally goodin characterizing
the quality of the air people breathe. That seems a heroic assumption. For
time-series studies, the assumption is that the air pollution measures are
equally good at characterizing the quality of air breathed during each day
of the week. But this seems suspicious, especially whencontrasting weekdays and weekends. Onweekdays~more people breathe the central city air;
whereason weekends,people spend their time in different activities, such
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as sports, gardening, hiking, etc, and they may be outdoors a greater
proportion of the time.
The cohort, population, clinical, and time-series studies all have their
unique advantages and problems. With care, each can be used to measure
different effects. Cross-sectional analyses can modelboth chronic and acute
effects (31); their maindrawbackis the possibility of missing variables such
as smokingor diet. If a causal variable that is correlated with the air-pollution
variables is left out of the analysis, the estimatedeffect of air pollution will
be biased.
Time-series analysis has fewer problems with missing variables. Its
problems stem more from confounding effects of differences in weekday
and weekend moods and activities.
People may feel less tense on the
weekends,as work, commuting,and manyother activities are curtailed and
air quality is better. Asthmaattacks, heart attacks, and other morbidity are
associated with tension and activities that decrease during the weekend,as
do air pollution levels. This can obscurethe relationship betweenair pollution
and health.
CLINICAL
STUDIES
Clinical studies are conducted on a sample of volunteers
under well measured and controlled conditions. These can assess the magnitude of the effects with precision. However,their key advantage is also
their maindisadvantage whenapplied to real life, because of three points:
1. Artificial conditions: In order to produceresults that can be replicated,
the dose in a clinical study is carefully controlled. Ambientair quality in
real settings is a complexmixture that maybear little relationship to the
air quality used in the laboratory setting. There are two additional reasons
whythe clinical setting mayhave little to do with real life: (a) Clinical
studies are extremely expensive to conduct and so sample size is necessarily
small, usually about half a dozen subjects. These subjects cannot represent
the diverse mix of age, sex, ethnicity, and prior exposuresthat characterize
the general population. (b) The subjects are volunteers, almost alwayshealthy
ones. Humansubject committees are reluctant to approve an experiment
wherethere is a nontrivial chancethat the subject could be harmedor killed
by the experiment. Almost inevitably, this means that sensitive persons
cannot be subjects in the clinical study.
2. Averting behavior: People in clinical studies are subjected to very special
conditions, and they follow a protocol (for example,exercise for sometime,
rest, exercise again), despite the appearanceof symptoms.In real life, those
people likely.would avoid, or at least mitigate, the effect of air pollution:
they might rest or stop activity or even movetheir residence to a less
polluted place. This averting behavior is not captured in clinical studies,
although it maybe captured in epidemi~logical studies.
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AIR POLLUTIONABATEMENT
BENEFITS 325
3. Valuation of effects: Epidemiologicalstudies measureeffects that people
are able to perceive; thus people could conceivably put a value on such
effects. Clinical studics measurephysiological changesthat people sometimes
do not perceive; thus they could not put a value on them.
Basedon the previous discussion of epidemiological and clinical studies,
we rely on epidemiological studies to obtain the quantitative estimates.
Clinical studies are primarily importantin probing the existence and causality
of an effect.
MORTALITY
EFFECTS
OFAIRPOLLUTION
The severe episodes of air pollution
that occurred in Donora, Pennsylvania, in 1948, and in London, England,
in 1952, left no doubt about the lethal potential of air pollution. Several
epidemiological studies have reported statistically significant relationships
betweenexcess mortality and several measuresof particulate matter. To our
knowledge,only one study (32) has reported mortality effects for a pollutant
other than particulate matter or sulfur oxides (ozone). However,there
not yet enough evidence to forge an unequivocal link between ozone and
excess mortality. Therefore, we consider only particulate matter and sulfur
oxides in our analysis of mortality effects of air pollution.
The usual terminologyfor air pollution’s mortality effects is a shorthand
that is misleading to almost everyone. Rather than "deaths due to air
pollution," we should be careful to discuss "premature deaths due to air
pollution." A first metric to measurethe mortality effects of air pollution
is the reduction in "premature" deaths as air quality improves. A second
metric supplementsthe first in noting the numberof "additional life years"
due to air-quality improvements.A third metric supplementsthe first two
by measuring the numberof additional "quality-adjusted life years" gained
by improving air quality (33, 34). Since everyone dies eventually, interest
centers on premature deaths. The problem with this measure is that the
death maybe premature by only days or even minutes. Thus, it is helpful
to knowthe number of life years lost due to premature death. However,
not all life years are the same. Granting someonewith endstage emphysema
an additional year of life maynot be worth as muchas giving this person
an additional year of active, healthy life.
These metrics becomeimportant because of the nature of the epidemiological studies done to quantify air pollution’s effects. Time-series studies
relate deaths to the level of air pollution on a daily basis. Such analyses
seek to explore: Howmanypremature deaths would occur if there were an
increase of one microgram per cubic meter of fine particles? Howmuch
longer wouldthese individuals have lived if the level of fine particles had
not increased that day? If their life expectancy were a few days, the air
pollution is "harvesting" deaths that likely wouldhave occurred within days,
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absent the air pollution. The additional premature deaths uncoveredby this
day-to-day analysis maynot be important to public policy.
Twomechanismsmight be at work. In the first, people on the edge of
dying have their death advanced by a few days. In the second, the entire
population is injured, manifestated primarily by an increase in mortality that
day. If an air-pollution episode decreases everyone’s life expectancy by a
few days, it is muchmoreimportant than if it decreased the life expectancy
only of those dying during the episode.
One way to test which mechanismis at work is to examine the pattern
of deaths following the episode. If, for example, the next week shows a
dip in the mortality rate equal to the numberof excess deaths during the
episode, one might conclude that air-pollution episodes lead to harvesting.
If, instead, the mortality rate remains slightly abovenormalor declines only
to the expected level, the air-pollution episode wouldappear to be causing
large reductions in life expectancy. The point is that time-series studies
cannot be content with estimating the immediateresponse to air pollution,
since these immediate deaths might be due predominately to harvesting.
Cross-sectional studies contrast the mortality rate across urban areas,
attempting to find how many premature deaths are associated with a
difference in air quality. These studies hypothesize that differences in air
quality have persisted for manyyears. Thus, these analyses appear to be
answering the question: If someone was born, grew up, and worked in an
area with slightly worse air quality, what would be the decrease in life
expectancy?For these studies, a prematuredeath is hypothesizedto represent
manymore life years lost than does a premature death in a time-series
analysis.
Studies using time-series data are numerous. Several have studied the
"Londonfogs" (28, 35-38), while others have studied NewYork (39-42),
Steubenville (43), Philadelphia (44), and Los Angeles(32, 45). Cross-sectional studies are also numerous, with manyof them following the work
by Lave &Seskin (25, 30, 46-48). Manyof these studies found a significant
relationship betweenmeasuresof particulate matter (usually Total Suspended
Particles--TSP) and sulfate with excess mortality. Based on our previous
discussion, we rely on cross-sectional studies to estimate the magnitudeof
the effects.
Weuse two cross-sectional studies to quantify the impact of air pollution on
mortality: Lave &Seskin (25) and Ozkaynak& Thurston (30). Both studies
found a significant association betweenmortality and both particulate matter
and sulfate concentrations. The data used in these studies span a period of 20
years, from 1960 to 1980. Someanalysts have concluded that the Lave &
Seskin study mayhave overestimatedthe effects of these pollutants on mortality
by a factor of two (47). Since the Ozkaynak&Thurston study generally found
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AIR POLLUTIONABATEMENT
BENEFITS 327
larger effects, our averageof the results of these twostudies can be considered
to be a reasonableupperboundof the mortality effects of these pollutants. The
USCongress directed the Environmental Protection Agency(EPA) to set
primaryambientair-quality standards that protect the health of the population
with an amplemarginof safety. For morethan 20 years, EPAhas been carrying
out this directive, relying on the most sensitive clinical and epidemiological
studies. For air quality that surpasses the primary air-quality standards, one
should expect that there will be no health effects. However,no one can show
that the standard constitutes a threshold. Thestudies on whichwe relied were
doneat levels of air quality substantially worsethan those currently prevailing.
A re-examination of the Lave & Seskin work showsthat the estimated health
effects of air pollution werenot significant whenair quality wasin compliance
with the primaryair-quality standards. Thus, in our judgment,the health effects
of a small changein air quality, whenair quality exceedsthe primary,are likely
to be very small or even zero. In particular, we hypothesize that the
concentration-responsecoefficient for air quality belowthe primaryair-quality
standard is one-tenth of that for muchworsepollution. Therefore, we use the
original mortality coefficients dividedby 10.
Particulate matter has been measuredhistorically in several ways: British
Smoke(BS), Total Suspended Particles (TSP), by the Coefficient of
(COH),Fine Particles (FP, particles less than 2.5 microns in diameter),
morerecently as PM10(particles less than 10 microns in diameter). In order
to arrive at a meaningfulestimate, we need to convert the different measures
into a commonone, PM10. To convert from TSP to PM10
, we have used
the EPAestimate (49) that PM10is between 0.5 and 0.6 of TSP, with
meanof 0.55. For fine particles (FP), we have used the estimate obtained
by Trijonis (50) using nationwide data, that gives FP = 0.30 TSP, which
results in PM~o= FP/0.55 using the previous relationship.
VALUATION
OFMORTALITY
EFFECTS
If the analysis is to estimate the dollar
benefits of pollution abatement, the decrease in premature deaths, in life
years or quality-adjusted life years lost, mustbe translated into dollars. How
much is society willing to pay to reduce the risk of a person dying
prematurely from air pollution? This question has been misstated by many
investigators to the confusion of themselves and the general public. The
usual misstatement to is ask the "dollar value of a life." The value of a
life is a moral and social question that is not related to the chancethat a
small proportion of people will have their life expectancy diminished by
exposureto air pollution.
The question is not howmuchwouldwe pay to save BabyJane. There is no
wayof knowingwhowill die prematurelydue to air pollution. Indeed, there is
no wayto identify after the fact whodied due to air pollution. This topic is
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CIFUENTES & LAVE
inherently controversial, but the misstatement has vastly increased the
confusion (52-57). Wemention the main aspects of the problem here; more
in-depth treatment can be found elsewhere(34, 58, 59).
Economists use two alternative approaches to find a dollar value for a
premature death. The first approach is based on measurementsof economic
productivity of the individual at risk, and is usually referred to as the
"humancapital" approach. It is based on two premises: that the value of
individuals to society is whatthey produce,and that productivity is accurately
measuredby earnings. Besides being ethically questionable, this approach
is not consistent with the fundamental premise of welfare economicsthat
each individual’s ownpreferences should be used to establish the economic
values used in cost-benefit analysis (60).
The second approach is based on an individual’s willingness to pay to
reduce his risk of death; it is called the "willingness to pay" approach. It
assumesthat individuals treat longevity as any other good, and that it is
possible to estimate the value they place on life expectancy by looking at
the trade-offs they madebetweenreductions in the risk of death and other
goods whose value can be measured in monetary terms. For example, some
people choose to drive small, light cars that are far more dangerous in a
crash than large, heavy cars. Somepeople accept dangerous jobs (such as
painting the steeples of churches or commercial fishing in Alaska), with
knownhigher accidental death rates, because they receive a higher wage.
Whenit is possible to estimate the increased risk and compensation from
each choice, then the individual’s willingness to pay, or the amountof
compensationhe or she requires, is revealed by these choices. This method
is theoretically correct, in contrast to measuresof earnings. Weuse it in
our estimates.
In a recent review of several willingness to pay studies, Fisher et al (61)
present a range of values from $1.6 million to $8.5 million per life. They
place more confidence in the lower bound than in the upper. Moore &
Viscusi (57) present a best estimate of $5 million using recent data from
the National Institute for OccupationalSafety. Since the analysis indicates
that the prematuredeaths tend to be concentrated amongthe elderly, society
maynot be willing to pay as muchto prevent a premature death as it would
for young workers. Thus, we regard the $4 million dollar figure in this
context as a plausible upper bound, and $1 million as a plausible lower
bound.
Tables
1 and 2 present the meanvalue for the mortality coefficient for each study,
for particulate matter and sulfate, respectively. The low and high columns
correspond to the meanestimate of the low and high scenarios for valuation
THE SOCIAL COSTS OF PREMATUREMORTALITYDUE TO AIR POLLUTION
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AIR POLLUTIONABATEMENTBENEFITS
+++
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CIFUENTES & LAVE
Table 2 Marginalbenefits of reducing SO4concentrations
Reference
Lave&Seskin, 1977(25)
Lave&Seskin, 1977(25)
Ozkaynak& Thurston, 1987
(30)
Average
Yearof data
1960
1969
1980
~
Marginaleffects
Mortality Std err
0.299
0.245
0.660
0.110
0.100
0.150
0.401
0.257
Valuationof life
Low
High
(S/life saved)
IE + 6
1E + 6
1E + 6
4E + 6
4E + 6
4E + 6
bMarginalbenefit
Low
High
299
245
660
1,196
980
2,640
401
1,605
3 of changeof SOnambient
aMarginal
effectsper 100,000people,per/xg/m
concentration
bThousands
of dollarper ,ttg/m3 of SO4,per 100,000
people.
of the effects. The average mortality coefficient was calculated as the average
of the three coefficients.
The standard error of this average coefficient
includes the standard error of each coefficient and the standard error that
results from averaging the three coefficients. This method of averaging gives
the same weight to each study, which we believe is appropriate in this case.
A similar procedure was followed in the calculation of the average coefficients in other cases.
Although EPAsets ambient air-quality
standards for sulfur dioxide, both
clinical studies and epidemiological studies indicate that small particles,
including sulfates, have a greater effect on health at current concentrations
(25, 30, 38, 62).
MORBIDITY
EFFECTSOF AIR POLLUTIONMany researchers
have investigated
the association of air pollution and respiratory morbidity. Clinical studies
have provided a causal relationship
for most of the symptoms. We study
the effects of each pollutant separately, and try to assess the extent of the
effects of each pollutant on humans as completely as possible. We base
our assessment on a review of epidemiological studies, for the reasons
discussed before. From each study; it is possible to obtain a concentrationresponse relationship. Whenthese relationships are not linear, we linearize
them about the average ambient concentration of the pollutant in the latest
years. This assumes that there are no thresholds at current levels of air
pollution. After we have calculated the marginal increments of each effect,
we check for double counting of the effects.
As we discuss below, some
measures of morbidity may include others, so we need to subtract them
when appropriate. Once we have obtained the net marginal effects, we value
them using several contingent valuation measures. We finally aggregate
them to obtain the total marginal benefit of abatement of each ambient
pollutant.
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AIR POLLUTIONABATEMENT
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MORBIDITY
ENDPOINTS
Several endpoints have been used when studying
morbidity effects. Clinical studies tend to use very precise measures of
pulmonaryfunctions, such as Forced Vital Capacity (FVC)or Peak Expiratory Flow Rate (PEFR), and some clearly identifiable symptoms, such
eye or throat irritation, or shortness of breath. Epidemiologicalstudies have
looked at individual symptomstoo, but they have also looked at the overall
effects that such symptoms(or a combination of them) have on people.
Somemeasures have been developed to represent those effects. Restricted
Activity Days (RAD)is the most comprehensive measure, and includes days
spent in bed, days missed from work, and other days whennormal activities
are restricted due to illness. WorkLoss Days (WLD)includes days missed
from work or school. Bed Disability Days (BDD)is the most serious
the three morbidity measures, and includes days spent in bed only.
Someof these measuresare included in others, so in determining the net
marginal effects of a given pollutant, we have to subtract the included
measures when appropriate, to obtain the net effect. The presence of a
symptom,if severe enough, maylead to a RAD.Weassume that the cases
of sinusitis and asthma attacks produce a RAD,so wheneverthese measures
are considered together we subtract the asthmaand sinusitis cases from the
RADscount. Weassume that less severe symptoms, such as eye or throat
irritation, do not lead to a RAD.
PARTICULATE
MATTER
EFFECTS
Several studies of air-pollution episodes
have confirmed an association between particulate matter and morbidity
effects (63-65). They have measured mainly pulmonary function, so they
are not appropriate to use for valuation purposes. Recent epidemiological
studies have also tried to find a relationship between morbidity measures
and particulate matter (27, 66-72). Evaluating these studies requires some
care. The associations between the morbidity measures and air-quality
measuresare weak. Evenif current air-quality levels caused this morbidity,
we would expect the observed associations to be weak: The air monitors
are at sites somemiles from most of the subjects; they measureoutdoor air
quality, not the air in buildings or transport vehicles where people spend
the vast majority of their time. In addition, the morbidity measures, such
as "restricted activity days," are subjective, and no two individuals are
likely to classify a set of symptomsin precisely the same way.
Lackof statistical significance for an association, despite the large sample
sizes, meansthat association is extremely weakor there is no effect. The
weaknessof the association could be due to the irrelevance of the air-pollution measureor differences in interpretation of what constitutes a "minor
restricted activity day."
In three papers, Ostro and coworkers (68-70) found associations between
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CIFUENTES & LAVE
fine particles
(FP) and Work Loss Days (WLD), Restricted Activity
(RADs), Respiratory-related
RADs(RRADs), and Minor Restricted Activity
Days (MRADs).However, the results were generally obtained in only one
or two years, out of six years of data. Combining the estimates for the six
years (1976-1981) reveals that only the results for RADs(69) and RRADs
(70) are significant. Whittemore & Korn (27) found a significant association
of particulate matter and asthma attacks, but the magnitude of this effect
was negligible, so we do not consider it. Portney & Mullahy (71) investigated
the relationship between TSP and chronic respiratory disease, asthma, and
emphysema, but the results were not significant.
Krupnick et al (72) found
a relationship
between any symptom and coefficient
of haze (a measure of
particulate matter). However, the morbidity measure is quite general; we
can conclude only that morbidity is associated with haze in this study. After
considering these studies, we conclude that the only morbidity measure we
can use is RADs. The coefficient
for RADsis included in Table 1.
VALUATION
OF THE PHYSICALDAMAGES
In contrast to studies to estimate
the value of averted deaths, not many studies have estimated how much
people are willing to pay for a reduction in morbidity symptoms. The most
widely cited study is Loehman et al (73). Krupnick & Kopp (74) offer
review of several other studies. Table 3 shows the values we have used.
All the values from the original studies were updated to 1991 dollars using
the general consumer price index. From Ostro & Rothschild (70), we infer
that MRADsare approximately two-thirds of the RADs count. Therefore,
the valuation used for RADsis one-third of a restricted activity day plus
two-thirds of a minor restricted activity day. Since there is no measure for
a minor restricted
activity day, we used the shortness of breath symptom
from Loehman. For the restricted activity day, we use the average lost wage
for one day (75). Although it has been shown that the willingness to pay
function is not linear in the number of days for which the symptoms are
Table 3 Value of symptoms,in 1991 dollars
Symptom
Valuation(19915)
Low
High
Cough
Eyeirritation
Sinusitiscase
Asthmaattack
RAD
4.33
3.27
27.30
11.79
19.45
13.02
13.10
93.30
53.69
47.97
Reference
(73)
(74) any symptom
(74)
(74)
(73) plus our own
calculations
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AIR POLLUTIONABATEMENT
BENEFITS 333
avoided (73), we have used the values for a reduction of one day in each
symptom,since we are estimating marginal benefits.
OZONE
EFFECTSOzone is one of the main components of photochemical
air pollution of metropolitan areas. It is formedby the oxidation of nitrogen
oxides in the presence of sunlight and reactive volatile organic compounds
(VOCs). There is no doubt that, at high concentrations, ozone produces
acute effects on the respiratory tract that result in a variety of symptoms.
Clinical studies have found a significant relationship betweenozoneexposure
and several acute respiratory conditions, including cough, shortness of
breath, nose and throat irritation, and chest discomfort (76-79). Cohort
epidemiological studies have found significant impacts of ozone exposure
on pulmonaryfunctions of children, even at levels encountered in normal
ambient concentrations (80, 81). Time-series epidemiological studies have
also found a relationship between acute effects and ozone exposure (27,
29, 72, 82, 83). Only one study that we knowof, however, has found
relationship betweenozoneexposure and chronic respiratory conditions (71).
For a complete review of the health effects of ozone, see (84). Webase
our analysis on the following endpoints:
1. RADestimates are based on Portney & Mullahy (29). This study
based on symptomsidentified by adults nationwide over a two-week
period as part of the National Health Interview Survey (NHIS)during
1979.
2. Estimates of asthma attacks are based on Whittemore& Kom(27), based
on daily asthma-attack diaries collected by the EPAin Los Angeles,
from 1972 to 1975. The frequency of the attacks increased with oxidant
levels and particulate matter levels.
3. Eye irritation and coughdays estimates are based on Schwartzet al (83).
This is a re-analysis of the Los AngelesStudent Nurse data from Hammer
et al (82), using a new modelthat considers the time-series nature
the data. It replicated the results concerningozone.
4. Sinusitis incidence is taken from Portney &Mullahy (71). Using data
for the 1979 NHIS,they found a significant association between the
incidence of sinusitis and the average concentration of ozone during the
past five years, both for the wholepopulationand for a cohort of residents
who had lived for more than five years in the same location. A
combination of emphysema,chronic bronchitis, and asthma was found
not to be significantly associated with the concentration of ozone.
Table 4 showsthe marginal benefits of abatementof ozoneconcentrations.
To avoid double counting in the benefits, we have subtracted the sinusitis
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AIR POLLUTIONABATEMENT
BENEFITS 335
and asthma cases from the RRADs
measure. For asthma attacks, we assume
that the asthmatic population is 3%of the total population (74).
NITROGEN
DIOXIDE
EFFECTS
The literature on direct health effects of oxides
of nitrogen is less definitive. There is somesuggestion of health effects
from epidemiological studies. Harrington (85) found a relationship between
NO2exposure and acute respiratory disease in children, but the relationship
was not monotonic. Schwartz et al (83) found a relationship between eye
irritation
and NO2exposure in the same data with which Hammeret al
(82) failed previously. However,there is little indication of effects from
laboratory studies (86-88). Therefore, we disregard the direct effects
NO2on morbidity.
Estimation of the Marginal Benefits of Pollution Abatement
for the United States
After having estimated the marginal impacts of changes in average ambient
concentrations of air pollutants, we need to link those concentrations with
pollutant emissions, the point at whichregulation will be enforced.
Since we are constructing national estimates, we have analyzed the relation
between emissions and ambient concentrations by focussing on national
emissions and average national air quality. In particular, we estimated the
relationship between the ambient concentration of each pollutant and anthropogenic emissions of its precursors via linear regression analysis. The
dependent variable was EPA-estimatednational ambient concentration. The
independent variable was EPA-estimated total national emissions of the
appropriate pollutants. The data are annual for several years, dependingon
the availability of EPAestimates (89, 90). Our regressions results are shown
in Table 5. The slope of the regression line is shownin column3.
Since particulate matter has been measured historically as TSP, we had
to convert TSPconcentrations to PM~0concentrations using the relation
presented before. EPAdoes not provide sulfate concentrations, so we derived
SO4levels from the TSP concentrations as a constant fraction of those
concentrations; this estimate was regressed on SO2emissions. Weregressed
the remaining fraction of PM10concentrations (PM10 less the SO4fraction)
on TSP emissions. NO2concentrations were regressed directly on NO2
emissions. Weregressed ozone concentrations on VOCsemissions and NO2
ambient concentrations simultaneously, relating them later to NO2emissions
through the coefficient of NO2concentrations to emissions. Since the EPA
data for ozone concentrations is the average of the annual second highest
daily maximum
one-hour concentration at each monitor, and the epidemiological studies use the average of the daily maximum
one-hour concentra-
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CIFUENTES
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Table5 Regressioncoefficients for ambientconcentrationsas functionof national emissions
Pollutant concentration
3)
PM~ominusSO4(p,g/m
3)
SO,,(p.g/m
NO2(ppb)
Ozone(avg. daily max.)
(ppb)
Ozone(avg. daily max.)
(ppb)
Pollutant
emissions
TSP
(M-ton)
SO2
(M-ton)
NO2
(M-ton)
VOCs
(M-ton)
NO2
(M-ton)
Slopea
Elasticity t statistic
R2
Years of data
2.54
0.84
11.3
0.94
1976-1989
0.37
1.05
13.4
0.95
1975-1989
0.51
0.42
2.5
0.92
1979-1989
0.58
0.29
0.97
0.79
1976-1989
0.72
0.38
2.67
0.79
1976-1989
a Slopes are expressed in units of pollutant ambient concentration per million-ton of emissions of the appropriate
pollutant (for example, the units of the slope in the second line are /zg/m3 of SO4over M-ton of SO2emissions).
tions during the period of study, we scaled the coefficients according to an
estimated ratio between the two measures of 3.13.
Unfortunately, ambient concentrations of the various criteria pollutants
are highly correlated. Similarly, emissions of the relevant pollutants are
highly correlated. Thus, there is little ability to separate the effects of
emissions of each pollutant on the ambient concentrations of related pollutants, e.g. volatile organic compounds and nitrogen dioxide versus ozone.
This difficulty,
however, is small compared to problems in the quality of
emissions and ambient air-quality
data. Emissions of each pollutant are
estimated by EPAon the basis of few data, especially for the earlier years.
Ambient air quality are averages from reporting monitoring stations. However, there were few stations in the early years, and stations were not sited
with a view to getting a national average. Thus, the EPAestimates for both
dependent and independent variables must be considered to have a large
random component. Regression results are uncertain, since the EPA data
on which they are based have major uncertainties.
POPULATION
EXPOSED
The final stage to compute the marginal benefits of
emissions abatement is to determine the total population that would be
exposed to a change in ambient concentrations. For particu!ate matter and
sulfate effects, we have assumed that the population affected is the total
population of the United States living in metropolitan areas, around 193
million (91). For ozone morbidity effects, we assume that the population
affected is the adult population living in metropolitan areas, around 144
million.
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AIR POLLUTION ABATEMENTBENEFITS
337
TableIf Marginalbenefits of reducingpollutant emissions
Pollutant
emissions
TSP
TSP
TSP
SO2
VOC
NO2
Effect
Marginalabenefit
Target
Emission cMarginalbenefit
Low
High
population
coeff,b
Low
High
(K-$/Conc/100,000p) (Millionpeople) (Conc/M-ton) (199IS/Ton)
PM~omortality
PM~omorbidity
Total
SO,~mortality
Ozonemorbidity
Ozonemorbidity
118
94
472
231
193
144
2.541
2.541
401
92
92
1605
280
280
193
144
144
0.37
0.58
0.72
579
343
922
287
77
96
2315
845
3161
1146
234
290
~ Marginal benefit of abatement of ambient concentrations of the corresponding pollutant
b See Table 5
¢ Marginal benefit of emissions abatement, in dollars per ton. Lowand High correspond to the meanof the low and high
valuation scenarios.
MARGINAL
BENEFITS OF EMISSIONS ABATEMENT
Table 6 shows the calculations of the marginal benefits of emissions abatement. It should be noted
that these values include only the mortality and morbidity effects discussed
previously.
Howcertain are these estimates? Figure 2 shows the cumulative distribution function (cdf) of the particulate matter and sulfate marginal benefits.
The cdf was derived using the Demos modeling software (92), considering
the uncertainty of each of the steps. As it is apparent from the figures, the
estimates have substantial
uncertainty associated.
What can be done to
CumulativeProbability
1.00
0.75
0.50
0.25
-1000
J~
0
1000
TSP
2000
3000
4000
Marginal Benefits (S/Ton)
Figure2 Marginalbenefit of emissionsabatementfor particulate matterandsulfur dioxide, for
the highvaluationscenario.Mortalityeffects only.
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CIFUENTES& LAVE
reduce this uncertainty? Muchof it comesfrom the uncertainty concerning
the health effects of ambient concentrations. Continuing research in this
area should provide somewhatbetter estimates of the impact of air pollution
on humanhealth. The link between emissions and concentrations, and the
population exposed, do not add muchuncertainty in our analysis, although
this step is one that has muchvariability across different geographicareas.
For example, Rowe(93) presents exposure coefficients for the United States
that vary from 10 to 80 person-lxg/m3 of sulfate per ton of SO2emitted.
The 95%confidence interval of our exposure coefficient goes from 61 to
82 person-p~g/m3 per ton of SO2.
SUMMARY
The USEnvironmental Protection Agency, state and local environmental
agencies, and public utility commissionsseek estimates of the physical
damageand dollar valuation of damagecaused by air pollution. Both to
estimate externality adders and improveregulatory decision-making, reliable
estimates are needed.
Wehave estimated the marginal benefits of air-pollution abatement, due
to health effects, of the most importantpollutants: suspendedparticles, SO2,
NO2,and 03. For our estimation of abatement benefits we use the direct
or damagefunction approach.
Twomajor issues concern (a) whether there is a practical threshold for
air-pollution effects and (b) interpreting the effects of time-series compared
to cross-sectional studies. Proving the existence of a threshold, a level of
air pollution belowwhichthere are no significant health effects, is essentially
impossible. Even the studies with large sample sizes and relatively good
air-pollution exposure data cannot either prove or disprove the existence of
a threshold. For example, even small mischaracterizations of exposure or
omissions of confounding variables will obscure a quantitatively small
association betweenair pollutants and health.
Although time-series studies appear to have fewer problems with confounding than do cross-sectional studies, they still have problems. In
addition, existing studies of the association of daily air-pollution levels with
the daily death rate do not distinguish between"harvesting" (the advancing
by a few days or weeks a death that would have occurred anyway) and
longer-term effects. Thus, the premature deaths that time-series studies
estimate would be averted by improved air quality probably represent a
muchsmaller numberof quality life years lost than the premature deaths
estimated from cross-sectional studies. For morbidity effects, time-series
studies are appropriate, given the acute nature of the effects measured.
Given these considerations, we have reviewed the relevant literature,
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AIR POLLUTION ABATEMENT BENEFITS 339
estimating the number of premature deaths and morbidity effects associated
with decreased air quality. Since we regard these estimates as uncertain,
we have presented an explicit analysis of the uncertainty of the resulting
estimates. Since this uncertainty is great, we look to future health studies
to provide more confident estimates.
More than two decades of research has shown that air pollution levels
in many US cities in the 1960s decreased life expectancy and had other
health effects.
As the methods have improved, air quality has improved
even faster, except for ozone levels. For air-quality levels in US cities in
the 1990s, the magnitude and importance of health-related
air-pollution
effects are uncertain.
Reducing uncertainty requires (a) better measures of air-pollution
dose
(such as the use of personal monitors or having a biological measure of
cumulative exposure), (b) standardized measures of morbidity or other health
effects of concern, (c) control for other factors affecting the health measure
or randomization, and (d) large sample size to isolate possible subtle effects.
Carrying out a study with these characteristics
would be exceedingly expensive. Thus, it is unlikely that the health effects of air pollution will be
known with much more certainty in the future, unless different methods are
used.
Literature Cited
1. Sagan, L. A. 1972. Humancosts of
nuclear power.Science 177:487-93
2. Lave, L. B., Freeburg, L. C. 1973.
Healtheffects of electricity generation
fromcoal, oil andnuclear fuel. Nucl.
Safety 14:409-28
3. Sagan, L. A. 1974. Health costs associated with the mining,transport,
and combustionof coal in the steamelectric industry. Nature250:107-11
4. Hamilton,L. D. 1974. The Health and
EnvironmentalEffects of Electricity
Generation--A Preliminary Report.
Upton, NY:BrookhavenNatl. Lab.
5. Budnitz,R. J., Holdren,J. P. 1976.
Social andenvironmentalcosts of energy systems. Annu. Rev. Energy
1:553-80
6. Comar,C. L., Sagan, L. A. 1976.
Health effects of energy production
and conversion. Annu. Rev. Energy
1:581-600
7. Holdren,J. P., Morris, G., Mintzer,
I. 1980. Environmental
aspects of renewableenergy sources. Annu. Rev.
Energy5:241-91
8. Hamilton, L. D. 1984. Health and
environmental
risks of energysystems.
9.
10.
11.
12.
13.
14.
15.
16.
In Risks and Benefits of Different
EnergySystems, pp. 21-57. Vienna:
Int. At. EnergyAgency
Lave, L. B., Silverman,L. P. 1976.
Economiccosts of energy-related environmentalpollution. Annu.Rev. Energy 1:601-28
Fisher, A. C., Smith, V. K. 1982.
Economic
evaluationof energy’senvironmentalcosts with special reference
to air pollution. Annu.Rev. Energy7:
1-35
Natl. Acad. Sci. 1991. Policy Implications of GreenhouseWarming.
Washington,DC:Natl. Acad. Press
Pigou, A. C. 1920. The Economicsof
Welfare. London:Macmillan.1st ed.
Kneese,A. V., Schultze, C. L. 1975.
Pollution, Prices, and Public Policy.
Washington,DC:BrookingsInst.
Schultze, C. L. 1977. The Public Use
of Private Interest. Washington,DC:
TheBrookingsInst.
Baumol,W. J., Oates, W. E. 1988.
The Theoryof EnvironmentalPolicy.
NewYork: CambridgeUniv. Press.
2nd ed,
Stavins, R. N. 1988. Project 88:
Annual Reviews
www.annualreviews.org/aronline
340
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
CIFUENTES
& LAVE
Harnesing Market Forces to Protect
Our Environment--Initiatives for the
NewPresident. A public policy study
sponsored by Senator Timothy E.
Wirth, Colorado, and Senator John
Heinz, Pennsylvania. Washington, DC
Hahn, R. W., Hird, J. A. 1991. The
costs and benefits of regulation: Review
and synthesis. Yale J. Regul. 8:233 ff.
Dept. Publ. Util. 1992. Investigation
by the Departmentof Public Utilities
on its ownmotion as to the environmental externality values to be used
in resource cost-effectiveness test by
electric companies subject to the
Department’s jurisdiction.
Report
D.P.U. 91-131. Commonw.Mass.
Chernick, P., Caverhill, E. 1991.
Methods of valuing environmental externalities. Electr. J. 4:46-53
Krupnick, A. J., Portney, P. R. 1991.
Controlling urban air-pollution: Abenefit cost assesment. Science 252:52~27
Hall, J. V., Wirier, A. M., Kleinman,
M. T., Lurmann, F. W., Brajer, V.,
Colome, S. D. 1992. Valuing the
health benefits of clean air. Science
255:812-17
Pearce, D. W., Markandya, A. 1989.
Environmental Policy Benefits: Monetary Valuation. Washington, DC:
OECDPubl./Inf. Cent.
Mitchell, R. C., Carson, R. T. 1989.
Using Surveys to Value Public Goods:
The Contingent Valuation Method.
Washington, DC: Resourc. Future
Braden, J. B., Kolstad, C. D. 1991.
Measuring the Demandfor Environmental Quality. Amsterdam: North
Holland
Lave, L. B., Seskin, E. P. 1977. Air
Pollution and HumanHealth. Baltimore, Md: Johns Hopkins Univ. Press
Fen-is, B. G., Anderson, D. O. 1962.
The prevalence of chronic respiratory
disease in a NewHampshire town.
Am. Rev. Respir. Dis. 86:165 ft.
Whittemore, A. S., Korn, E. L. 1980.
Asthmaand air pollution in the Los
Angeles area. Am. J. Pub. Health
70:687-96
Schwartz, J., Marcus, A. 1990. Mortality and air pollution in London:A
time series analysis. Am. J. Epidemiol.
131:185-94
Portney, P., Mullahy, J. 1986. Urban
air quality and acute respiratory illness.
J. Urb. Econ. 20:21-38
Ozkaynak, H., Thurston, G. D. 1987.
Associations between 1980 U.S. mortality rates and alternative measuresof
airborne particle concentration. Risk
Anal. 7:449-61
31. Evans, J. S., Kinney, P. L., Koehler,
J. L., Cooper, D. W. 1984. The
relationship between cross-sectional
and time series studies. J. Air Pollut.
Control Assoc. 34:551-53
32. Kinney, P. L., Ozkaynak, H. 1991.
Associations of daily mortality and air
pollution in Los Angeles County. Environ. Res. 54:99-120
33. Zeckhauser, R., Shepard, D. S. 1976.
Where now for saving lives? Law.
Contemp. Probl. 39:545
34. Zeckhauser, R., Shepard, D. S. 1984.
Principles for saving and valuing lives.
In Technological Risk Assesment, ed.
P. F. Ricci, L. A. Sagan, C. G.
Whipple, pp. 133-68. The Hague:
Matinus Nijhoff
35. Cummings,B. T., Walker, R. E. 1967.
Observations from a ten-year study of
pollution at a site in the City of
London. Atmos. Environ. 1:49-68
36. Mazumdar, S., Schimmel, H., Higgins, I. T. T. 1982. Relation of daily
mortality to air pollution: Ananalysis
of 14 London winters 1958/59-1971/
72. Arch. Environ. Health 37:213-20
37. Ostro, B. D. 1984. A search for a
threshold in the relationship of air
pollution to mortality: A reanalysis of
data on London winters. Environ.
Health Perspect. 58:397-99
38. Thurston, G. D., Ito, K., Lippmann,
M., Hayes, C. 1989. Re-examination
of London, England mortality in relation to exposure to acidic aerosols
during 1963-1972 winters. Environ.
Health Perspect. 79:73-82
39. Glasser, M., Greenburg, L, 1971. Air
pollution and mortality and weather,
NewYork City 1960-1964. Arch. Environ. Health 22:334 ff.
40. Schimmel, H., Greenburg, L. 1972.
A study on the relationship of pollution
to mortality, NewYork City 19631968. J. Air Pollut. Control Assoc.
22:607 ff.
41. Buechley, R. W., Riggan, W. B.,
Hasselblad, V., Van Bruggen, J. B.
1973. SO2levels and perturbations in
mortality. A study in NewYork-New
Jersey metropolis. Arch. Environ.
Health 27:134 ff.
42. Schimmel, H., Murawski, T. J. 1976.
The relation of air pollution to mortality. J. Occup. Med. 18:316 ff.
43. Schwartz, J., Dockery, D. W. 1992.
Particulate air pollution and daily mortality in Steubenville, Ohio. Am. J.
Epidemiol. 135:12-25
44. Schwartz, J., Dockery, D. W. 1992.
Increased mortality in Philadelphia associated with daily air pollution con-
Annual Reviews
www.annualreviews.org/aronline
AIR POLLUTION
centrations. Am. Rev. Respir. Dis.
145:600-4
45. Shumway, R. H., Azari, A. S.,
Pawitan, Y. 1988. Modeling mortality
fluctuations in Los Angelesas I~tnctions
of pollution and weather effects. Environ. Res. 45:224-41
46. Chappie, M., Lave, L. B. 1982.
The health effects of air pollution:
A reanalysis. J. Urb. Econ. 12:34676
47. Evans, J. S., Tosteson, T., Kinney,
P. L. 1984. Cross-sectional mortality
studies and air pollution risk assesment.
Environ. Int. 10:55-83
48. Lipfert, F. W. 1984. Air pollution and
mortality: Specifications searches using
SMSA-baseddata. J. Environ. Econ.
Manage. 1 l:208-43
49. US Environ. Protect. Agency. 1982.
Review of the National Ambient Air
Quality Standard for Particulate Matter: Assesmentof Scientific and Technical Information’. Research Triangle
Park, NC
50. Trijonis, J. 1983. Development and
application of methodsfor estimating
inhalable and fine particles concentrations for HI-Vol data. Atmos. Environ.
17:999-1008
51. Deleted in proof
52. Mishan,E. J. 1971. Evaluation of life
and limb: A theoretical approach. J.
Polit. Econ. 79:687-705
53. Broome, J. 1978. Trying to value a
life. J. Public Econ. 9:91-100
54. Broome, J. 1985. The economic value
of life. Economica52:281-94
55. Jones-Lee, M. W., Hammerton, M.,
Philips, P. R. 1985. The value of
safety: Results from a national sample
survey. Econ. J. March:48-72
56. Garen, J. E. 1988. Compensating
wagedifferentials and the endogeneity
of job riskiness. Rev. Econ. Stat.
70:9-16
57. Moore, M. J., Viscusi, W. K. 1988.
Doubling the estimated value of life:
Results using newoccupational fatality
data. J. Policy Anal. Manage.7:47690
58. Kahn, S. 1986. Economicestimates of
the value of life. IEEE Tech. Soc.
Mag. 5:24-31
59. Viscusi, W. K. 1991. Strategic and
ethical issues in the valuation of life.
In Strategy and Choice, ed. R. J.
Zeckhauser, pp. 359-87. Cambridge,
Mass: M1TPress
60. Cropper, M. L., Freeman, A. M. III.
1991. Environmentalhealth effects. In
Measuring the Demandfor Environmental Quality, ed. J. B. Braden, C.
61.
62.
63.
64.
65.
66.
67.
68.
69.
70.
71.
72.
ABATEMENT BENEFITS
341
D. Kolstad, pp. 165-211. Amsterdam:
North Holland
Fisher, A., Chestnut, L. G., Violette,
D. M. 1989. The value of reducing
risks of death: A note on newevidence.
J. Policy Anal. Manage. 8:88-100
Dockery, D. W., Schwartz, J., Spengler, J. D. 1992. Air pollution and daily
mortality: Associations with particulates and acid aerosols. Environ. Res.
59:362-73
Brunekreef, B., Lumens, M., Hock,
G., Hofschreuder, P., Fischer, P.,
Biersteker, K. 1989. Pulmonaryfunction changes associated with an air
pollution episode in January 1987. J.
Air Pollut. Control Assoc. 39:1444-47
Dassen, W., Bmnekreef, B., Hoek,
G., Hofschreuder, P., Staatsen, B., et
al. 1986. Decline in children’s pulmonary function during an air pollution
episode. J. Air Pollut. Control Assoc.
36:1223-27
Dockery, D. W., Ware, J. H., Ferris,
B. G. Jr., Speizer, F. E., Cook, N.
R. 1982. Changein pulmonaryfunction
in children associated with air pollution
episodes. J, Air Pollut. Control Assoc.
32:937-42
Ware, J. H., Ferris, B. G. Jr., Dockcry, D. W., Spengler, J. D., Stram,
D. O., Speizer, F. E. 1986. Effects
of ambient sulfur oxides and suspended
particles on respiratory health of preadolescent children. Am. Rev. Respir.
Dis. 133:834-42
Dockery, D. W., Speizer, F. E.,
Stram, D. O., Ware, J. H., Spengler,
J. D., Fen’is, B, G. Jr. 1989. Effects
of inhalable particles on respiratory
health of children. Am. Rev. Respir.
Dis. 139:587-94
Ostro, B. D. 1983. The effects of air
pollution on work loss and morbidity.
J. Environ. Econ. Manage. 10:37182
Ostro, B. D. 1987. Air pollution and
morbidity revisited: A specification
test. J. Environ. Econ. Manage.14:8798
Ostro, B. D., Rothschild, S. 1989.
Air pollution and acute respiratory
morbidity: An observational study of
multiple pollutants. Environ. Res.
50:238-47
Portney, P., Mullahy, J. 1990. Urban
air quality and chronic respiratory disease. Reg. Sci. Urb. Econ. 20:407-18
Krupnick, A., Harrington, W., Ostro,
B. 1990. Ambient ozone and acute
health effects: Evidence from daily
data. J. Environ. Econ. Manage.18:118
Annual Reviews
www.annualreviews.org/aronline
342
CIFUENTES
& LAVE
73. Loehman,E. T., Berg, S. V., Arroyo,
A. A., Hedinger, R. A., Schwartz, J.
M., et al. 1979. Distributional analysis
of regional benefits and cost of air
quality. J. Environ. Econ. Manage.
6:222--43
74. Krupnick, A. J., Kopp, R. J. 1988.
The Health and Agricultural Benefits
of Reductions in Ambient Ozone in the
United States. Report QE88-10.Washington, DC: Resourc. Future
75. Table C4: Establishment data, Earnings, Not seasonally adjusted. 1992.
Employ. Earn. 39:156
76. McDonnell, W. F., Horstman, D. H.,
Hazucha, M., Seal, E. Jr., Haak, E.
D., et al. 1983. Pulmonaryeffects of
ozone exposure during exercise: Dose
responsecharacteristics. J. Appl. Physiol. 54:1345-52
77. Kulle, T. J., Sauder, L. R., Hebel,
J. R., Chatam, M. D. 1985. Ozone
response relationships in healthy nonsmokers. Am. Rev. Respir. Dis. 132:
36-41
78. Horstman, D. D., Folinsbee, L. J.,
lves, P. J., Abdul-Salaam, S., McDonnell, W. F. 1990. Ozone concentration
and pulmonary response
relationships for 6.6 hour exposures
with five hours of moderate exercise
to 0.08, 0.10 and 0.12 ppm. Am. Rev.
Respir. Dis. 142:1158-63
79. McDonnell, W. F., Kehrl, H. R.,
AbduI-Salaam, S. 1991. Respiratory
response of humans exposed to low
levels of ozone for 6.6 hours. Arch.
Environ. Health 46:145-50
80. Spektor, D. M., Lippmann, M., Lioy,
P. J., Thurston, G. D., Citak, K., ct
al. 1988. Effects of ambient ozone on
respiratory function in active, normal
children. Am. Rev. Respir. Dis. 137:
313-20
81. Spektor, D. M., Thurston, G. D.,
Mao, J., He, D., Hayes, C., Lippmann, M. 1991. Effects of single- and
multiday ozone exposures on respiratory function in active normalchildren.
Environ. Res. 55:107-22
82. Hammer,D. I., Hasselblad, V., Portnoy, B., Wehrle, P. F. 1974. Los
Angeles student nurse study. Arch.
Environ. Health 28:255-60
83. Schwartz, J., Hasselblad, V., Pitcher,
P. 1988. Air pollution and morbidity:
A further analysis on the Los Angeles
student nurses data. J. Air Pollut.
Control Assoc. 38:158-62
84. Lippmann, M. 1989. Health effects of
ozone: Acritical review. J. Air Pollut.
Control Assoc. 39:672-95
85. Harrington, W., Krupnick, A. J. 1985.
Short term nitrogen dioxide exposure
and acute respiratory disease in children. J. Air Pollut. Control Assoc.
35:1061-67
86. Morrow, P. E., Utell, M. J. 1989.
Responses ~f Susceptible
Subpopulations to Nitrogen Dioxide. Report 23. Health Effects Inst.
87. Off. Air Qual. Plann. Stand. 1987.
Review of the National Ambient Air
Quality Standards for Ozone. Preliminary Assesmentof Scientific and Technical Information. USEnviron. Protect.
Agency
88. Utell, M. J., Frampton, M. W., Roberts, N. J., Finkelstein, J. N., Cox,
C., Morrow, P. E. 1991. Mechanisms
of Nitrogen Dio~ide Toxicity in Humans. Report 43. Health Effects Inst.
89. Counc. Environ. Qual. 1992. Environmental Quality: 22nd Annual Report.
90. US Environ. Protect. Agency. 1991.
National Air Quality and Emissions
Trends Report 1990. Report EPA450/4-91-023.
91. US Census Bur. 1991. Statistical
Abstract of the U.S. Washington,
DC
92. Morgan, M. G., Henrion, M. 1990.
Uncertainty: A Guide to Dealing with
Uncertainty in Quantitative Risk and
Policy Analysis. Cambridge: Cambridge Univ. Press
93. Rowe, M. D. 1980. Human exposure
to sulfates from coal-fired power
plants. J. Air Pollut. Control Assoc.
30:682-83