A Probabilistic Characterization of the Relationship between Fine

Clean Air for Europe (CAFE) estimated that PM2.5 causes 350,000 deaths ..... For example, Expert E was quite confident that fine particulate matter of...
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Environ. Sci. Technol. 2007, 41, 6598-6605

A Probabilistic Characterization of the Relationship between Fine Particulate Matter and Mortality: Elicitation of European Experts ROGER M. COOKE,† ANDREW M. WILSON,‡ JOUNI T. TUOMISTO,§ OSWALDO MORALES,† M A R K O T A I N I O , § A N D J O H N S . E V A N S * ,‡ Delft University of Technology, Delft, The Netherlands, Resources for the Future, Washington, DC, Harvard School of Public Health, Department of Environmental Health, Kuwait Public Health Project, 135 Market Street, Unit C, Portsmouth, New Hampshire 03801, and Centre for Environmental Health Risk Analysis, National Public Health Institute (KTL), Kuopio, Finland

In support of an assessment of the mortality impacts of the Kuwait Oil Fires we interviewed six European experts in epidemiology and toxicology using formal procedures for elicitation of expert judgment. While the primary focus of the elicitations was to characterize the public health impacts of the fires, the experts provided quantitative estimates of the mortality impacts of hypothetical changes in the levels of ambient fine particulate matter (PM2.5) in both the United States and Europe. Uncertainty was assessed by asking each expert to provide the 5th, 25th, 50th, 75th, and 90th percentiles of their subjective cumulative probability density function for each quantity of interest. The results suggest that many regulatory risk assessments underestimate the impacts of PM2.5 mortality; confirm that only a small fraction of the mortality impact occurs within the first few months after exposure; and indicate that it may be important to better address the differential toxicities of particles from various source classes. By providing quantitative estimates of the uncertainty in current estimates of PM2.5 mortality risks, the study facilitates structured analysis of the value of further research on PM2.5 and its impacts.

Introduction The Kuwait Oil Fires of 1991 emitted vast quantities of fine particulate matter and related gases to the atmosphere (1, 2). In support of the State of Kuwait’s environmental reparations claims, we were asked to estimate the mortality impacts of exposure to oil fire smoke. Our analysis was multifaceted and included analysis of air pollution measurements taken during the period of the fires; assessment of the atmospheric fate and transport of smoke from the fires; epidemiological analysis; and risk assessment (3). One element of the risk assessment was a formal elicitation of six * Corresponding author phone: 603-433-3956; fax: 603-433-4174; e-mail: [email protected]. † Delft University of Technology and Resources for the Future. ‡ Harvard School of Public Health. § National Public Health Institute (KTL). 6598

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European experts on air pollution epidemiology. The primary goal of the elicitation was to probabilistically characterize the number of deaths attributable to the oil fires, but in the course of the elicitation experts were asked to characterize the responses of the United States and EU (defined in this paper as the 15 member states before May 1, 2004) populations to both acute and chronic changes in levels of airborne fine particulate matter; to consider the temporal expression of the likely mortality impacts; and to assess the strength of evidence for differential toxicity of certain constituents of fine particulate matter. It is well-established that exposure to fine particulate matter leads to substantial mortality impacts. The World Health Organization global burden of disease study estimated that in the year 2000 on the order of 800,000 premature deaths in urban areas throughout the world were due to inhalable particulate matter (4, 5). Ostro and Chestnut found that roughly 80% of the $14-55 billion annual benefits attainable by adopting a 15 µg/m3 PM2.5 standard in the United States would flow from reduction of particulate matter (PM)-induced mortality (6). Clean Air for Europe (CAFE) estimated that PM2.5 causes 350,000 deaths annually in the EU, leading to a loss of life expectancy at birth of almost 9 months and economic costs on the order of several hundred billion euros (7). Similarly, the National Research Council’s 2002 review of three major U.S. EPA regulatory analyses (Heavy Duty Engine and Vehicle Standards, Prospective Analysis of the 1990 Clean Air Act Amendments, and Tier 2 Motor Vehicle Emissions Standards) concluded that the monetized benefits of reductions in PM-induced mortality were potentially enormous ($23 billion, $63 billion, and $275 billion, respectively) (8-10). The scientific support for these estimates comes from extensive literature on the epidemiology and toxicology of particulate matter, consisting of several hundred primary studies and more than a dozen reviews (11). Two study typess the daily time series study and the cohort studysare central to estimating the benefits of air pollution control. The timeseries studies examine the relationships between day-today fluctuations in air pollution and corresponding daily fluctuations in mortality. Such studies have been conducted in hundreds of large cities throughout the world. Cohort studies examine the differences in survival of individuals in cities with different levels of air pollution after correcting for differences in smoking, education, income, and other potential confounding variables. From this vast literature, two cohort studiessthe Six Cities Study and the American Cancer Society Study (and extensions/reanalyses of these studies)sprovide the coefficients at the heart of almost all recent regulatory analysis (12, 13). While the projected health impacts of PM2.5 exposure are quite large, scientists and policy analysts recognize that there are substantial uncertainties in these estimates and that these uncertainties cannot be characterized objectively (5, 6, 8). This is because many of the largest sources of uncertainty have to do with evaluation of the evidentiary support for causal interpretation of the current body of epidemiological work; assessment of the uncertainty introduced by the need to extrapolate results from one setting (e.g., the United States) to another (i.e., the EU or Kuwait), recognizing that there may be differences in the aerosol mix, the typical levels of PM, and in the health status, exposure to co-pollutants, and genetic resiliency of these various populations. Many recent regulatory analyses have addressed this issue by relying on the ACS coefficients (0.4% (all cause) or 0.6% (cardiopulmonary) per µg/m3 PM2.5) for central estimates of chronic 10.1021/es0714078 CCC: $37.00

 2007 American Chemical Society Published on Web 08/21/2007

mortality impacts and on the SCS coefficient (1.3% per µg/m3 PM2.5) for alternative (upper) estimates (5, 6, 8). In some cases lower estimates have also been made, on the assumption that the cohort studies are confounded, using coefficients from various meta-analyses of time-series studies (6). One possible approach to characterization of uncertainty, recently recommended by the National Research Council (8) and under exploration by the U.S. Environmental Protection Agency (14, 15), is to rely on formal elicitation of the opinions of experts. While the use of expert opinion in support of public policy is not yet common, there is strong evidence of increased awareness of and interest in the approach. A search of the Web of Science for “expert elicitation” yielded over 300 articles, with 28 in environmental science and 8 in public health (16). For example, in the field of climate change, Morgan and his colleagues have used expert judgment to assess likely changes in the Atlantic meridional overturning circulation and in aerosol forcing (17, 18). In the field of accident consequence analysis, the European Nuclear Commission and the U.S. Nuclear Regulatory Commission conducted a collaborative study using expert judgment to assess failure probabilities of, and health consequences from, accidental releases of radionuclides at commercial nuclear power plants (19, 20). Finally, as noted above, after conducting a pilot study (which was extensively reviewed in the late summer of 2003 and endorsed by the Health Effects Subcommittee of EPA’s Science Advisory Board), in late 2004 the U.S. EPA initiated a full-scale expert judgment study of the mortality impacts of exposure to fine particulate matter (10, 14, 15). The United Nations Compensation Commission hearings on the public health claims of Saudi Arabia, Iran, Kuwait, and other affected nations were held in September of 2004. All evidence in support of the claims needed to be submitted to the UNCC by the summer of that year. Therefore, while we were aware that the U.S. EPA had initiated a pilot study, the timing of the UNCC claims process did not allow us the luxury of waiting for their results. Furthermore, evaluation of the State of Kuwait’s claim required us to ask experts about the impacts of smoke from the oil fires (rather than the ambient mix of PM in the United States or EU) necessitated our interest in the impact of a specific pattern of smoke exposure during the 7-month period of the oil fires (on a background of perhaps 300 µg/m3 of PM10); and dictated that we evaluate the mortality impacts on the Kuwaiti national population (which is quite young and has a different ethnic makeup than the populations of the United States and EU).

Methods The expert elicitation process comprised several steps. First, the elicitation protocol was developed and a panel of experts was selected via a peer nomination process. Second, we convened a workshop to educate the expert panel about the expert elicitation process and to foster discussion of the relevant PM-epidemiology literature. Third, individual interviews with each of six experts were conducted. Finally, the experts’ answers were analyzed, reported, and combined. Selection of Experts. Experts were selected via a twostep peer nomination process. First, a keyword search in the Web of Science database (Science Citation Index Expanded (1986-2004), Social Science Citation Index (1986-2004), and Arts & Humanities Citation Index (1986-2004)) was used to generate a list of publications relevant to the topic. The keyword search was (air pollution OR particulate matter OR fine particles OR PM2.5 OR PM10) AND (death OR mortality OR survival OR morbidity) AND (epidemiology OR human OR time-series OR cohort OR clinical). From these publications, a list of first, second, and last authors was extracted, ranked by number of appearances. The 100 top-ranking

researchers from this list (and members of the research advisory boards for CAFE (Clean Air for Europe, the air quality strategy of the EU) and AIRNET (an air pollution research and policy network, www.airnet.iras.uu.nl, funded by the European Commission)) were asked to nominate European experts who they felt would be able to thoughtfully interpret the relevant literature. The ten experts with the highest number of nominations were invited to participate and six (listed in alphabetic order) accepted: Dr. H. Ross Anderson (MD, PhD), St. George’s Hospital, University of London, England; Dr. Bert Brunekreef (PhD), University of Utrecht, Netherlands; Dr. Ken Donaldson (PhD), University of Edinburgh, Scotland; Dr. Nino Kunzli (MD, PhD), formerly at the University of Basel, Switzerland; Dr. Juha Pekkanen (MD, PhD), National Public Health Institute, Finland; and Dr. Annette Peters (PhD), GSF National Research Center for Environment and Health, Germany. To ensure confidentiality, the experts have been randomly assigned the generic titles “Expert A” through “Expert F.” Workshop and “Briefing Book”. Expert participation began with a workshop held in Kuopio, Finland in June 2004. Project staff reviewed the objectives of and methods to be used in the elicitation, provided a training exercise in quantifying uncertainty, and facilitated a discussion among the experts of key issues in the interpretation of particulate matter epidemiology. Each expert was given a copy of the protocol and some background material, including demographic, geographic, and air pollution information important for defining the exposure scenarios and populations of interest. Experts were also given a “briefing book” (on compact disc) of over 100 relevant reports and publications and were encouraged to review this information before their interviews and to refer to it freely during the elicitation. Individual Interviews. The interviews were conducted by Professor Cooke (the “normative” elicitor responsible for presenting the protocol and eliciting answers) with support from Drs. Tuomisto and Wilson (the “substantive” elicitors responsible for asking clarifying questions, challenging assumptions, and presenting information previously not considered by the expert). The individual interviews began with a review of issues related to quantification of uncertainty and a set of qualitative “warm-up” questions which asked experts to (i) qualitatively review the relevant literature, (ii) compare and contrast the available evidence with ideal evidence for quantifying PM2.5 toxicity, and (iii) consider alternative interpretations of the evidence which would lead to high and low values, before giving their final quantitative responses. The “heart” of the protocol was a series of 10 questions seeking quantitative probabilistic estimates of the impacts of various hypothetical changes in ambient levels of PM2.5. As Table 1 indicates, the protocol began with questions about the impacts of long-term changes in PM2.5 levels, then considered the impacts of single-day excursions of PM, inquired about the temporal expression of impacts, and finally asked for interpretation of current evidence on the differential toxicity of various classes of particulate matter. A typical question was of the following form: “What is your estimate of the true, but unknown, percent change in the effect window of interest, non-accidental mortality rate in the (population of interest) resulting from a (level, nature & duration of change of interest) in PM2.5 (from a population-weighted baseline concentration of relevant baseline level) throughout the (region of interest)?” Experts were asked to characterize their knowledge and uncertainty by providing the 5th, 25th, 50th, 75th, and 95th percentiles of their subjective cumulative density function for each quantity of interest. Before seeking these quantitative estimates, the elicitation team asked the expert to review the available evidence and to comment on its strengths and VOL. 41, NO. 18, 2007 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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TABLE 1. Overview of Elicitation Protocol attribute of interest topic

question

PM2.5 change

duration of change

nature of PM

effect window affected population

long-term impacts

Q1 In the US Q2 In the EU

-1 µg/m3 -1 µg/m3

permanent ambient permanent ambient

equilibrium equilibrium

U.S. EU

short-term impacts

Q3 In the US Q4 In the MCMA Q5 In the EU Q5 In the US

+10 µg/m3 +10 µg/m3 +10 µg/m3 +10 µg/m3

1 day 1 day 1 day 1 day

one week one week one week 3 months

U.S. MCMA EU U.S.

permanent ambient permanent ambient

n/a n/a

U.S. U.S.

permanent most toxic constituent permanent least toxic constituent

equilibrium equilibrium

U.S. U.S.

temporal expression Q7 Fraction within 1 week -1 µg/m3 Q8 Fraction within 3 months -1 µg/m3 differential toxicity

Q9 Most Toxic Q10 Least Toxic

-1 µg/m3 -1 µg/m3

weaknesses. Experts were also given basic demograhic information (e.g., population, income, education, smoking) and information on mortality (total and cause-specific) and air pollution (levels and composition) throughout the United States and the EU and in the Mexico City Metropolitan Area (MCMA). The protocol was carefully developed, reviewed to ensure that each question satisfied the “clairvoyance criterion,” pretested in a pilot study and modified accordingly, and included “seed” questions to permit calibration of judgments. The complete protocol is available as Supporting Information (see below). The questions about the temporal expression of effects were included to learn how much of the mortality impact of the Kuwait oil fires would have been expressed within weeks or months of exposure (and therefore might have been detectable through time-series studies in Kuwait) and how much of the effect would have been expected to occur later. While these are not the time periods of greatest interest in the analysis of regulatory strategies for the United States or EU, the experts’ answers provide some insight about the fraction of total mortality benefits expected to occur within the first several months after implementation of pollution controls. The discussion of differences in toxicity of various constituents of ambient PM2.5 began with a qualitative discussion of the available evidence on this subject. Each expert was asked to comment on whether specific PM2.5 constituents (e.g., ammonium sulfate, ammonium nitrate, elemental carbon/organic carbon, diesel particulate, material of crustal origin, secondary organics) were likely to be more or less toxic than the (population-weighted) ambient aerosol mixture in the United States. Finally, from this list they were asked to select one constituent which they felt was likely to be the “most toxic” constituent and one which they felt was “least toxic.” Once these were identified, each expert was asked to provide quantitative characterizations of the mortality impacts of permanent 1 µg/m3 reductions in the ambient levels of these constituents in the United States. This section of the interview culminated with two questions concerning the likely mortality impacts of smoke from the 1991 Kuwait Oil Fires. The experts’ responses to these questions about the oil fires are presented elsewhere (3) and are not considered further here. The interview ended with a set of 12 questions about “seed” or “calibration” variables. These seed questions sought estimates of the levels of pollution and health in various EU cities. The values of these variables were not known (by either the experts or the elicitors) at the time of the elicitation. By comparing the experts’ answers to these questions to the true values (which are now known) it is possible to assess their performance as probability assessors and to develop various “performance-based” combinations of their judgments. 6600

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ambient ambient ambient ambient

The interviews proved to be collegial, but rigorous, taking as long as 10 h to complete. Following the interviews, experts were asked to provide a written summary of their estimates and key points of their reasoning. Analysis, Combination, and Reporting of Results. The experts’ answers to the substantive and calibration questions were reviewed and analyzed, and are reported in two ways. First, the full set of individual opinions on each question is presented. Second, two combinations of opinionssone in which the views of all experts are given equal weight, and a second in which the results are combined using weights reflecting the experts’ performance (both informativeness and calibration) on the seed variablessare provided. The technical details supporting this approach are described by Tuomisto et al. (21).

Results The results of this study fall into four broad categories: (i) estimates of the impact of long-term changes in PM2.5 exposure; (ii) evaluation of the impact of short-term excursions in PM2.5 exposure; (iii) analysis of the temporal pattern of expression of impacts; and (iv) consideration of the potential impact of differential toxicity. The major findings are presented briefly below. Mortality Impacts from Long-Term Exposure. Figure 1 shows each expert’s estimates of the mortality impact of a permanent 1 µg/m3 reduction in levels of PM2.5 throughout the United States (green) or the European Union (blue). The figure provides both equal- and performance-weighted combinations of the expert’s answers, and compares these with estimates derived directly from the two studies which have been central to most recent regulatory analyses of particulate air pollution, i.e., the American Cancer Society (22) and the Six Cities (23) studies. Four features of these results are noteworthy. First, the central estimates given by all of the experts are larger than the central value derived directly from the ACS study. Second, the 95% upper estimates given by all of the experts are greater than the central value derived directly from the Six Cities study. Third, while the 5% lower estimates of two of the experts (and of both combinations) are somewhat lower than the 5% lower confidence estimate taken directly from the ACS study, no expert assigned as much as 5% probability to zero impact. Fourth, there are slight differences in the estimates given by some experts for the United States and those for the EU, but these differences are quite small in comparison to the experts’ estimates of the uncertainty inherent in either estimate. Mortality Impacts from Short-Term Excursions in Exposure. Figure 2 shows the experts’ estimates of the increase in mortality (expressed as a percent of baseline mortality) that would be expected in the week following a 1

FIGURE 1. Mortality decrease (%) following permanent 1 µg/m3 reduction in PM2.5 in the United States (green) or EU (blue).

FIGURE 2. Mortality increase (%) in week following 1 day 10 µg/m3 PM2.5 increase in the United States (green) or the EU (blue). day increase of 10 µg/m3 in PM2.5 in the United States (green) or the EU (blue). For the United States, the lowest estimate was given by Expert D who relied largely on the 14-city study by Zanobetti and Schwartz (24, 25), but also noted the quality of the NNMAPS study. Three experts (F, C, and A) derived their estimates primarily from the revised NMMAPS study (26). Expert B, who gave a somewhat higher answer, cited the recent WHO meta-analysis (27). The differences in the answers given by these five experts resulted primarily from differences in the assumptions that they made in extrapolating from the effects windows commonly reported in the published literature and the 1-week expression period referred to in our question. The highest central estimate came from Expert E, who relied on both the WHO meta-analysis and a U.S. six city study by Schwartz (28) and assumed that the increase in mortality would persist throughout the entire 1-week effect window. While Expert E’s central estimate of the effect was largest, his uncertainty distribution was also the broadest. Even so, his lower 5% confidence estimate was higher than the central estimates of all of the other experts. To extrapolate from the effect windows commonly reported to the 1-week window of interest here, experts relied on studies of the London Smog (29) and on various analyses of distributed lags (30-34). None of the six experts believed that harvesting would substantially affect this extrapolation and, accordingly, each assumed that additional deaths would occur in the latter days of the 1-week expression period. The expert’s estimates for the EU were quite similar to those for the United States, especially when viewed in context

of their estimates of the uncertainty surrounding either effect. To derive their answers for the EU, experts relied primarily upon the WHO meta-analysis (27), the APHEA time-series study (35), and meta-analysis results reported by Stieb et al. (36, 37). Almost all of the experts gave similar characterizations of the uncertainty in their EU and U.S. effect estimates, despite small reservations about differences between the exposure measure used in these studies (black smoke in the European APHEA study and PM2.5 in the U.S. NMMAPS study). Their central estimates for Mexico City (not shown) were typically substantially largersby 30% (experts B and C) and by factors of almost 4 (expert F), almost 6 (expert D), and more than 7 (expert A)sthan those for the United States or EU. Only one expert (E) gave the same central estimate for all three exposure settings. These larger values for Mexico were driven largely by results from time-series studies conducted in Mexico City (38-40) which reported significantly higher effect estimates than similar U.S. and EU studies. One additional difference was the greater breadth of the uncertainty distributions given for Mexico City. Temporal Expression of Impacts. Figure 3 shows the experts’ estimates of the fraction of the total mortality impact likely to be expressed within one week (top panel) and 3 months (bottom panel) of the exposure reduction. In the course of the elicitation, each expert noted the paucity of information directly addressing the temporal expression of mortality impacts, though all agreed about its importance. Experts drew variously from their knowledge of published literature on air pollution episode studies (such VOL. 41, NO. 18, 2007 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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FIGURE 3. Temporal expression of impact (fraction of effect expressed) within one week (top panel) and within 3 months (bottom panel) as the London Smog, the Asian haze, and the Meuse and Donora events), from results of smoking cessation studies, and from findings of intervention studies such as those by Clancy et al. (41). Uncertainty bands are generally quite large for the experts’ estimates, reflecting low confidence in the literature base to support quantitative answers. Despite this uncertainty, two general approaches emerged. These differed primarily in the size of the impact anticipated in the first week after the reduction in exposure. Four experts (C, D, E, and F) gave very low estimates (all less than 10% of the equilibrium effect) of the fraction of the mortality impact expected in this first week. The other two experts (A and B) gave substantially higher estimates (25% and 50%, respectively) of the impact anticipated during this period. When asked how much of the impact would occur within 3 months of the exposure reduction, most experts (A, C, D and F) gave central estimates in the range of 20-30% of the equilibrium impact, while expert E’s central estimate was 12% and expert B’s central estimate was 60%. This expert to expert variability is small in comparison with the width of 6602

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most of the experts’ confidence intervals. An equal weight combination of expert opinion yields a median estimate of 29%, and 5% and 95% confidence intervals of 11% and 54%, respectively. Clearly this expert group believes that most of the mortality impact of a permanent reduction in PM2.5 levels will occur more than 3 months after the reduction in exposure. An informal poll suggested substantial uncertainty and disagreement about how long it might take for the new equilibrium to be achieved; answers ranged from as little as 1 year to as many as 20 years. Differential Toxicity. Figure 4 shows the experts’ estimates of the impact of unit reductions in ambient concentrations of the “most toxic” and “least toxic” constituents of PM2.5 and compares these with their estimates of the impact of similar reductions in ambient PM2.5. All of the experts identified combustion particles (variously referred to as “elemental and organic carbon” (Experts A, B, E and F); “diesel PM2.5” (Expert C); and “traffic PM2.5” (Expert D)) as most toxic and gave central estimates of the “differential

FIGURE 4. Mortality impact of a permanent 1 µg/m3 change in either the “most toxic” constituent of PM2.5 (dark red, Question 9), the “least toxic”constituent of PM2.5 (dark green, Question 10) or the U.S. ambient mix of PM2.5 (dark yellow, Question 1). toxicity” ranging from 1 to 4. However, they gave quite large confidence intervals for the differential toxicity of this “most toxic” constituent, suggesting not only that they were quite unsure about the “differential toxicity” of combustion particles, but acknowledging that these particles might be no more toxic than the ambient mix. These large uncertainties reflect the paucity of direct evidence about the mortality impacts of chronic exposure to combustion particles. To answer these questions experts had to extrapolate results from short-term time-series epidemiology and animal toxicology studies. There was less agreement concerning the least toxic constituent, although there were no situations where one expert identified as least toxic a component that another expert believed to be more toxic than the ambient mixture. Experts A and D specified ammonium sulfates as least toxic. Expert B felt that ammonium sulfates or ammonium nitrates were equally likely to be least toxic. Expert C chose ammonium nitrate, and Experts E and F believed PM2.5 from crustal sources were likely to be least toxic. There were also substantial differences in the stated confidence intervals for the toxicity of the “least toxic constituent.” For example, Expert E was quite confident that fine particulate matter of crustal origin was benignsassigning his 95% upper estimate of its toxicity as 1/25th of his median estimate of the toxicity of the ambient mix. Expert C had a similar view about the toxicity of ammonium nitrates. In contrast, Experts A, B, and D, who all chose ammonium sulfate and assigned median estimates of its toxicity below 1/4th of the toxicity of the ambient mix, all expressed some uncertainty about this beliefsgiving 95% upper estimates of its toxicity 1/3rd, 5/6th, and 100% of their median estimates for the ambient mix. Expert F identified specific constituents as most and least toxic, but gave identical quantitative distributions for the “most toxic” constituent, the “least toxic” constituent, and the ambient mix, arguing that too little information was available to support meaningful quantitative distinctions.

Discussion Despite the great progress that has been achieved in the control of air pollution, much remains to be done. Recent WHO estimates of the global burden of disease attribute 800,000 deaths each year to ambient particulate matter exposure. The economic costs of mortality due to PM exposure in the EU have been estimated to be on the order of hundreds of billions of euros annually. In the United States, the benefits of adopting a 15 µg/m3 PM2.5 standard are thought to be in the range of $14-55 billion US$. Regulators on both continents are exploring ways to reduce this burden. Efforts to quantify and compare the benefits and costs of alternative regulatory strategies for reducing PM exposure

rely primarily on the results from two epidemiological studies, the ACS and the SCS, and on various extensions and reanalyses of the data from these studies. While these studies are quite well done, and have withstood extensive critical review, there are several questions which arise in the application of results from these studies to estimate the benefits of air pollution regulation. These include the following: whether the studies reflect causal associations, or merely statistical associations, between PM exposure and mortality; how much weight to place on the results of each study given the more than 3-fold difference in the central effect estimates from the two studies; how to characterize the uncertainty in effect estimates, recognizing the parameter uncertainty in each estimate, the difference between the two central estimates, and the epistemic uncertainty due to concerns about confounding, effect modification, and exposure misclassification; whether, and if so how, to account for any differential toxicity of various constituents of the ambient PM mix (e.g., ammonium sulfate, ammonium nitrate, elemental and organic carbon, and crustal material); how to characterize the temporal pattern of expression of mortality impacts (i.e., the lag structure); and how to account for the impacts of nonlinearities or thresholds in the exposure-response relationship. Many regulatory analyses conducted in the late 1990s and early 2000s addressed these questions by (i) assuming that the relationships were causal; (ii) using the ACS coefficient as the central estimate of effect; (iii) using the SCS coefficient as an upper bound on effect; (iv) relying on coefficients from time-series studies as a lower bound; (v) implicitly treating all constituents of PM as equally toxic; and (vi) assuming that effects occur in the same year as exposure changes or specifying a fixed lag structure (25% in years 1 and 2, 16% in years 3, 4, and 5). Our study was conducted in support of an analysis of the mortality impacts of the Kuwait oil fires, but the protocol addressed many questions that are central to regulatory analysis. These experts expressed a high degree of confidence that the ACS and SCS cohort studies reflect causal relationships between air pollution and mortality. No expert assigned as much as 5% probability to the proposition that a 1 µg/m3 permanent reduction in ambient levels of PM2.5 in the United States or EU would have no effect on mortality. All of these experts gave central estimates of the mortality benefits associated with a 1 µg/m3 permanent reduction in PM2.5 levels that are at least as large as the central estimate derived directly from the ACS study. The equal-weighted combination of their central estimates is about twice as large as the comparable value from the ACS study. The performance-weighted combination is about 30% larger than the ACS result. Many regulatory benefits assessments have relied VOL. 41, NO. 18, 2007 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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on the ACS result and thus may have underestimated the mortality benefits of improvements in air quality. They believe that reasonable upper estimates of the health benefits associated with a permanent 1 µg/m3 reduction in PM2.5 should be at least as large as the central estimate from the Six Cities Study. The experts identified potential exposure misclassification in the cohort studies as the primary factor underlying their adjustment of upper estimates. Many recent regulatory analyses have relied on the central estimates from the Six Cities Study as an upper estimate of effect and therefore may have underestimated the uncertainty inherent in effect estimates derived from these studies. These experts all identify primary combustion particles (i.e., elemental and organic carbon, traffic particles, or diesel particles) as the “most toxic” constituent of the ambient PM mixture; and give central estimates of the relative toxicity of combustion particles that are 1-4 times as large as those for the ambient PM mixture; but acknowledge the limitations of available data and the large uncertainty in their answers, evident in uncertainty intervals large enough to accommodate the possibility that the constituent that they have identified as “most toxic” is in fact no more toxic than the ambient mix. While they are all certain that some constituents are far less toxic than the ambient mix; they offer various candidate substances (i.e., ammonium sulfate, ammonium nitrate, or crustal matter) as the “least toxic” constituent. These results are important because they suggest that central estimates of the benefits of programs to reduce emissions of “combustion particles” may be low; that estimates of the benefits of control of sulfates, nitrates, and fine crustal PM may be high; and, perhaps more importantly, that the further research on the question of differential toxicity might be of great value. They express considerable uncertainty about the temporal pattern of expression of mortality impacts; but in the main (4 of 6 experts) suggest that only 20-30% of the eventual impact of a permanent reduction in PM2.5 is likely to be expressed within 3 months of the change in air pollution. This work provides one characterization of current understanding of the health benefits likely to flow from further reduction in ambient levels of fine particulate matter. The characterization is quantitative, probabilistic, and based on structured elicitation of the judgment of six eminent European scientists identified by their peers as among the best qualified to interpret the relevant literature. The opinions of these scientists were elicited using approaches designed to minimize the influences of the many well-known heuristics and biases which may affect judgment. The results of the individual elicitations are presented along with two combinations of judgmentsone which weights all experts equally and a second which gives greater weight to those experts who performed well on calibration questions. While the quantitative estimates may be of some interest to those responsible for regulation of PM2.5, the utility of the approach may be of more interest to others. Characterizations of the state of knowledge, and uncertainty, about mortality impacts of PM exposure are important not only for regulation but also pave the way for analysis of the value of information and inform future research investment decisions. The value of the approach is in its transparency. Experts views are elicited and presented individually. The potential for artificial consensus present in traditional consensus reports from expert panels is minimized. Any combination of results is done in an explicit way. Uncertainties are completely articulated and quantified. It should be recognized that the results presented here reflect the views of one set of six European experts elicited more than 2 years ago. These results must be compared with the results from the EPA/IEc elicitation of American experts. The strengths and weaknesses of both efforts, and of structured elicitation of expert judgment itself, should be 6604

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carefully discussed in an effort to ensure that the results are properly used in support of policy analysis. We are now working with the EPA/IEc team to produce a careful synthesis of the results from these two elicitations; make recommendations for their use in policy; and suggest improvements in the approaches used in future efforts of this kind. Preliminary comparisons indicate that the results from these two independent efforts to assess expert opinions about mortality from PM2.5 exposure are quite similar.

Acknowledgments We most sincerely thank the European epidemiologists and toxicologists who provided the knowledge and expert judgments upon which this analysis depends. Without their willingness to participate, their energy and commitment to the project, this work would have not been possible. This work was conducted under the auspices of the United Nations Compensation Commission through a contract with Kuwait’s Public Authority for Assessment of Compensation for Damage Resulting from the Iraqi Aggression. We thank the experts both in Europe and in Mexico, upon whose knowledge this elicitation depends, for their time, energy, and enthusiasm. We are grateful for the advice and encouragement of Dr. Wajih Sawaya of the Kuwait Institute for Scientific Research and Professor Zoran Radovanovic of Kuwait University. The work was also funded by the Academy of Finland (Grant 53307) and the National Technology Agency of Finland (Tekes) (Grants 40715/01, 616/31/02).

Supporting Information Available The complete elicitation protocol. This material is available free of charge via the Internet at http://pubs.acs.org.

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Received for review June 12, 2007. Accepted July 10, 2007. ES0714078

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