Public health and chronic low chlordecone exposures in Guadeloupe; Part 2: Health impacts, and benefits of prevention.

BACKGROUND: Inhabitants of Guadeloupe are chronically exposed to low doses of chlordecone via local food due to its past use in banana plantations. The corresponding health impacts have not been quantified. We develop a quantitative method and present the results in two articles: 1. Hazard identification, exposure-response functions, and exposure, 2. Health impacts, and benefits of a program to reduce the exposure of the population. Here is the second article. METHODS: The exposure-response functions derived in Part 1 (for liver and prostate cancer, renal dysfunction and cognitive development) are combined with the exposure data to calculate the impacts. The corresponding costs are calculated via DALY's and VOLY. A no-effect threshold is included via the marginal fraction of the collective exposure above the reference dose. The health benefits are the impacts in 2002 (before the exposure reduction program) minus the impacts in 2006 (since the program). They are compared to the costs, namely the public annual expenditures for reducing the population exposure. RESULTS: Without threshold, estimated annual cases of liver cancer, prostate cancer and renal dysfunction are respectively 5.4, 2.8, 0.10 in 2002; and 2.0, 1.0, 0.04 in 2006. Annual IQ points lost (cognitive development) are respectively: 1 173 and 1 003. The annual cost of total impacts is 38.3 Million Euros (M€) in 2002 and 23.7 M€ in 2006. Comparing the benefit of 14.6 M€ with the 3.25 M€ spent for prevention, the program appears well justified. With threshold, the costs of the impacts are lower, respectively: 26.5 M€ in 2002 and 12.8 M€ in 2006, but the benefit is not very different: 13.7 M€. CONCLUSION: This is the first study that quantified chronic non genotoxic effects of chlordecone exposures in Guadeloupe. According to our results, preventive actions should be focused on pregnant women because of the high social cost of development impairment and also because their exposures decreased less rapidly than others. Prevention effort should be sustained as long as chlordecone remains in soils. Additional toxicological and epidemiological research would also be required for health endpoints that could not be taken into account (neurotoxicity of adults, autoimmune diseases and other developmental effects).

Public health and chronic low chlordecone exposure in Guadeloupe, Part 1: hazards, exposure-response functions, and exposures.

BACKGROUND: Inhabitants of Guadeloupe are chronically exposed to low dose of chlordecone via local food. The corresponding health impacts have not been quantified. Nevertheless the public authority implemented an exposure reduction program in 2003. We develop methods for quantifying the health impacts of chlordecone and present the results in 2 articles: 1. hazard identification, exposure-response functions (ERF) and exposure in Guadeloupe, 2. Health impacts and benefits of exposure reduction. Here is the first article. METHODS: Relevant data are extracted from publications searched in Medline and Toxline. Available knowledges on mode of action and key-event hazards of chlordecone are used to identify effects of chlordecone that could occur at low dose. Then a linear ERF is derived for each possible effect. From epidemiological data, ERF is the delta relative risk (RR-1) divided by the corresponding delta exposure. From animal studies, ERF is the benchmark response (10 %) divided by the best benchmark dose modeled with BMDS2.4.0. Our goal is to obtain central values for the ERF slopes, applicable to typical human populations, rather than lower or upper bounds in the most sensitive species or sex. RESULTS: We derive ERFs for 3 possible effects at chronic low chlordecone dose: cancers, developmental impairment, and hepatotoxicity. Neurotoxicity in adults is also a possible effect at low dose but we lack quantitative data for the ERF derivation. A renal toxicity ERF is derived for comparison purpose. Two ERFs are based on epidemiological studies: prostate cancer in men aged >44y (0.0019 per µg/Lblood) and altered neurodevelopment in boys (-0.32 QIpoint per µg/Lcord-blood). Two are based on animal studies: liver cancer (2.69 per mg/kg/d), and renal dysfunction in women (0.0022 per mg/kg/d). CONCLUSION: The methodological framework developed here yields ERFs for central risk estimates for non-genotoxic effects of chemicals; it is robust with regard to models used. This framework can be used generally to derive ERFs suitable for risk assessment and for cost-benefit analysis of public health decisions.

Costs of Health Damage from Atmospheric Emissions of Toxic Metals: Part 1-Methods and Results.

Significant quantities of toxic metals are emitted to the air by the incineration of waste, as well as by the combustion of coal and oil. To optimize the regulations for their emissions one needs to know the cost of their damage. That requires an impact pathway analysis, with realistic dispersion models, exposure-response functions, and monetary values. In this article we explain the method and assumptions and present results for arsenic, cadmium, mercury, and lead, the most important toxic metals in terms of damage cost. We also estimate their contribution to the damage cost of waste incineration and electric power from coal for typical situations in Europe. The damage costs of As, Cd, and Pb are much higher than previous estimates because of a large number of new epidemiological studies, implying more and more serious health effects than what had been known before. New cost-benefit studies for the abatement of toxic metal emissions are advisable. The discussion of the epidemiological studies and the derivation of exposure-response functions are presented in two companion articles, one for As and Cd, the other for Hg and Pb.

Costs of Health Damage from Atmospheric Emissions of Toxic Metals: Part 2-Analysis for Mercury and Lead.

In this part of the series we explain the detailed literature review and the calculations of impacts and damage costs of mercury and lead. Methodology and general assumptions are explained in the companion article, Part 1 of this series, and the spreadsheet with the calculations is available as a supplementary file of Part 1.3 For mercury, the damage cost is 22,937 €2013 /kg if there is a no-effect threshold, 52,129 €2013 /kg if there is none; 91% is due to mortality from heart disease, the rest from loss of IQ points. For lead, the damage cost is 29,343 €2013 /kg, about 80% due to mortality and 20% due to IQ loss; there does not seem to be a no-effect threshold. These costs are per kg of emitted pollutant.

Impact of the 1990 Hong Kong legislation for restriction on sulfur content in fuel.

INTRODUCTION: After the implementation of a regulation restricting sulfur to 0.5% by weight in fuel on July 1, 1990, in Hong Kong, sulfur dioxide (SO2*) levels fell by 45% on average and as much as 80% in the most polluted districts (Hedley et al. 2002). In addition, a reduction of respiratory symptoms and an improvement in bronchial hyperresponsiveness in children were observed (Peters et al. 1996; Wong et al. 1998). A recent time-series study (Hedley et al. 2002) found an immediate reduction in mortality during the cool season at six months after the intervention, followed by an increase in cool-season mortality in the second and third years, suggesting that the reduction in pollution was associated with a delay in mortality. Proportional changes in mortality trends between the 5-year periods before and after the intervention were measured as relative risks and used to assess gains in life expectancy using the life table method (Hedley et al. 2002). To further explore the relation between changes in pollution-related mortality before and after the intervention, our study had three objectives: (1) to evaluate the short-term effects on mortality of changes in the pollutant mix after the Hong Kong sulfur intervention, particularly with changes in the particulate matter (PM) chemical species; (2) to improve the methodology for assessment of the health impact in terms of changes in life expectancy using linear regression models; and (3) to develop an approach for analyzing changes in life expectancy from Poisson regression models. A fourth overarching objective was to determine the relation between short- and long-term benefits due to an improvement in air quality. METHODS: For an assessment of the short-term effects on mortality due to changes in the pollutant mix, we developed Poisson regression Core Models with natural spline smoothers to control for long-term and seasonal confounding variations in the mortality counts and with covariates to adjust for temperature (T) and relative humidity (RH). We assessed the adequacy of the Core Models by evaluating the results against the Akaike Information Criterion, which stipulates that, at a minimum, partial autocorrelation plots should be between -0.1 and 0.1, and by examining the residual plots to make sure they were free from patterns. We assessed the effects for gaseous pollutants (NO2, SO2, and O3), PM with an aerodynamic diameter < or = 10 microm (PM10), and its chemical species (aluminum [Al], iron [Fe], manganese [Mn], nickel [Ni], vanadium [V], lead [Pb], and zinc [Zn]) using the Core Models, which were developed for the periods 5 years (or 2 years in the case of the sensitivity analysis) before and 5 years after the intervention, as well as in the10-year (or 7-year in the case of the sensitivity analysis) period pre- and post-intervention. We also included an indicator to separate the pre- and post-intervention periods, as well as the product of the indicator with an air pollution concentration variable. The health outcomes were mortality for all natural causes and for cardiovascular and respiratory causes, at all ages and in the 65 years or older age group. To assess the short- and long-term effects, we developed two methods: one using linear regression models reflecting the age-standardized mortality rate D(j) at day j, divided by a reference D(ref); and the other using Poisson regression models with daily mortality counts as the outcome variables. We also used both models to evaluate the relation between outcome variables and daily air pollution concentrations in the current day up to all previous days in the past 3 to 4 years. In the linear regression approach, we adjusted the data for temperature and relative humidity. We then removed season as a potential confounder, or deseasonalized them, by calculating a standard seasonal mortality rate profile, normalized to an annual average of unity, and dividing the mortality rates by this profile. Finally, to correct for long-term trends, we calculated a reference mortality rate D(ref)(j) as a moving average of the corrected and deseasonalized D(j) over the observation window. Then we regressed the outcome variable D(j)/D(ref) on an entire exposure sequence {c(i)} with lags up to 4 years in order to obtain impact coefficient f(i) from the regression model shown below: deltaD(j)/D (ref) = i(max)sigma f(i) c(j - i)(i = 0). The change in life expectancy (LE) for a change of units (deltac) in the concentration of pollutants on T(day)--representing the short interval (i.e., a day)--was calculated from the following equation (deltaL(pop) = average loss in life expectancy of an entire population): deltaL(pop) = -deltac T(day) infinity sigma (j = 0) infinity sigma f(i) (i = 0). In the Poisson regression approach, we fitted a distributed-lag model for exposure to previous days of up to 4 years in order to obtain the cumulative lag effect sigma beta(i). We fit the linear regression model of log(LE*/LE) = gamma(SMR - 1) + alpha to estimate the parameter gamma by gamma, where LE* and LE are life expectancy for an exposed and an unexposed population, respectively, and SMR represents the standardized mortality ratio. The life expectancy change per Ac increase in concentration is LE {exp[gamma delta c(sigma beta(i))]-1}. RESULTS: In our assessment of the changes in pollutant levels, the mean levels of SO2, Ni, and V showed a statistically significant decline, particularly in industrial areas. Ni and V showed the greatest impact on mortality, especially for respiratory diseases in the 5-year pre-intervention period for both the all-ages and 65+ groups among all chemical species. There were decreases in excess risks associated with Ni and V after the intervention, but they were nonsignificant. Using the linear regression approach, with a window of 1095 days (3 years), the losses in life expectancy with a 10-microg/m3 increase in concentrations, using two methods of estimation (one with adjustment for temperature and RH before the regression against pollutants, the other with adjustment for temperature and RH within the regression against pollutants), were 19.2 days (95% CI, 12.5 to 25.9) and 31.4 days (95% CI, 25.6 to 37.2) for PM10; and 19.7 days (95% CI, 15.2 to 24.2) and 12.8 days (95% CI, 8.9 to 16.8) for SO2. The losses in life expectancy in the current study were smaller than the ones implied by Elliott and colleagues (2007) and Pope and colleagues (2002) as expected since the observation window in our study was only 3 years whereas these other studies had windows of 16 years. In particular, the coefficients used by Elliott and colleagues (2007) for windows of 12 and 16 years were non-zero, which suggests that our window of at most 3 years cannot capture the full life expectancy loss and the effects were most likely underestimated. Using the Poisson regression approach, with a window of 1461 days (4 years), we found that a 10-microg/m3 increase in concentration of PM10 was associated with a change in life expectancy of -69 days (95% CI, -140 to 1) and a change of -133 days (95% CI, -172 to -94) for the same increase in SO2. The effect estimates varied as expected according to most variations in the sensitivity analysis model, specifically in terms of the Core Model definition, exposure windows, constraint of the lag effect pattern, and adjustment for smoking prevalence or socioeconomic status. CONCLUSIONS: Our results on the excess risks of mortality showed exposure to chemical species to be a health hazard. However, the statistical power was not sufficient to detect the differences between the pre- and post-intervention periods in Hong Kong due to the data limitations (specifically, the chemical species data were available only once every 6 days, and data were not available from some monitoring stations). Further work is needed to develop methods for maximizing the information from the data in order to assess any changes in effects due to the intervention. With complete daily air pollution and mortality data over a long period, time-series analysis methods can be applied to assess the short- and long-term effects of air pollution, in terms of changes in life expectancy. Further work is warranted to assess the duration and pattern of the health effects from an air pollution pulse (i.e., an episode of a rapid rise in air pollution) so as to determine an appropriate length and constraint on the distributed-lag assessment model.

How to determine life expectancy change of air pollution mortality: a time series study.

BACKGROUND: Information on life expectancy (LE) change is of great concern for policy makers, as evidenced by discussions of the "harvesting" (or "mortality displacement") issue, i.e. how large an LE loss corresponds to the mortality results of time series (TS) studies. Whereas loss of LE attributable to chronic air pollution exposure can be determined from cohort studies, using life table methods, conventional TS studies have identified only deaths due to acute exposure, during the immediate past (typically the preceding one to five days), and they provide no information about the LE loss per death. METHODS: We show how to obtain information on population-average LE loss by extending the observation window (largest "lag") of TS to include a sufficient number of "impact coefficients" for past exposures ("lags"). We test several methods for determining these coefficients. Once all of the coefficients have been determined, the LE change is calculated as time integral of the relative risk change after a permanent step change in exposure. RESULTS: The method is illustrated with results for daily data of non-accidental mortality from Hong Kong for 1985 - 2005, regressed against PM10 and SO2 with observation windows up to 5 years. The majority of the coefficients is statistically significant. The magnitude of the SO2 coefficients is comparable to those for PM10. But a window of 5 years is not sufficient and the results for LE change are only a lower bound; it is consistent with what is implied by other studies of long term impacts. CONCLUSIONS: A TS analysis can determine the LE loss, but if the observation window is shorter than the relevant exposures one obtains only a lower bound.

Improving health through policies that promote active travel: a review of evidence to support integrated health impact assessment.

BACKGROUND: Substantial policy changes to control obesity, limit chronic disease, and reduce air pollution emissions, including greenhouse gasses, have been recommended. Transportation and planning policies that promote active travel by walking and cycling can contribute to these goals, potentially yielding further co-benefits. Little is known, however, about the interconnections among effects of policies considered, including potential unintended consequences. OBJECTIVES AND METHODS: We review available literature regarding health impacts from policies that encourage active travel in the context of developing health impact assessment (HIA) models to help decision-makers propose better solutions for healthy environments. We identify important components of HIA models of modal shifts in active travel in response to transport policies and interventions. RESULTS AND DISCUSSION: Policies that increase active travel are likely to generate large individual health benefits through increases in physical activity for active travelers. Smaller, but population-wide benefits could accrue through reductions in air and noise pollution. Depending on conditions of policy implementations, risk tradeoffs are possible for some individuals who shift to active travel and consequently increase inhalation of air pollutants and exposure to traffic injuries. Well-designed policies may enhance health benefits through indirect outcomes such as improved social capital and diet, but these synergies are not sufficiently well understood to allow quantification at this time. CONCLUSION: Evaluating impacts of active travel policies is highly complex; however, many associations can be quantified. Identifying health-maximizing policies and conditions requires integrated HIAs.

Estimation of incidence and social cost of colon cancer due to nitrate in drinking water in the EU: a tentative cost-benefit assessment.

BACKGROUND: Presently, health costs associated with nitrate in drinking water are uncertain and not quantified. This limits proper evaluation of current policies and measures for solving or preventing nitrate pollution of drinking water resources. The cost for society associated with nitrate is also relevant for integrated assessment of EU nitrogen policies taking a perspective of welfare optimization. The overarching question is at which nitrogen mitigation level the social cost of measures, including their consequence for availability of food and energy, matches the social benefit of these measures for human health and biodiversity. METHODS: Epidemiological studies suggest colon cancer to be possibly associated with nitrate in drinking water. In this study risk increase for colon cancer is based on a case-control study for Iowa, which is extrapolated to assess the social cost for 11 EU member states by using data on cancer incidence, nitrogen leaching and drinking water supply in the EU. Health costs are provisionally compared with nitrate mitigation costs and social benefits of fertilizer use. RESULTS: For above median meat consumption the risk of colon cancer doubles when exposed to drinking water exceeding 25 mg/L of nitrate (NO3) for more than ten years. We estimate the associated increase of incidence of colon cancer from nitrate contamination of groundwater based drinking water in EU11 at 3%. This corresponds to a population-averaged health loss of 2.9 euro per capita or 0.7 euro per kg of nitrate-N leaching from fertilizer. CONCLUSIONS: Our cost estimates indicate that current measures to prevent exceedance of 50 mg/L NO3 are probably beneficial for society and that a stricter nitrate limit and additional measures may be justified. The present assessment of social cost is uncertain because it considers only one type of cancer, it is based on one epidemiological study in Iowa, and involves various assumptions regarding exposure. Our results highlight the need for improved epidemiological studies.

Global health impacts and costs due to mercury emissions.

Since much of the emission is in the form of metallic Hg whose atmospheric residence time is long enough to cause nearly uniform mixing in the hemisphere, much of the impact is global. This article presents a first estimate of global average neurotoxic impacts and costs by defining a comprehensive transfer factor for ingestion of methyl-Hg as ratio of global average dose rate and global emission rate. For the dose-response function (DRF) we use recent estimates of IQ decrement as function of Hg concentration in blood, as well as correlations between blood concentration and Hg ingestion. The cost of an IQ point is taken as $18,000 in the United States and applied in other countries in proportion to per capita GDP, adjusted for purchase power parity. The mean estimate of the global average of the marginal damage cost per emitted kg of Hg is about $1,500/kg, if one assumes a dose threshold of 6.7 mug/day of methyl-Hg per person, and $3,400/kg without threshold. The average global lifetime impact and cost per person at current emission levels are 0.02 IQ points lost and $78 with and 0.087 IQ points and $344 without threshold. These results are global averages; for any particular source and emission site the impacts can be quite different. An assessment of the overall uncertainties indicates that the damage cost could be a factor 4 smaller or larger than the median estimate (the uncertainty distribution is approximately log normal and the ratio median/mean is approximately 0.4).

Environmental impacts and costs of solid waste: a comparison of landfill and incineration.

The methodology for evaluating the impacts and damage costs ('external costs') due to pollution from waste treatment is described and the results are presented, based on the ExternE project series of the European Commission. The damage costs of landfill and incineration of municipal solid waste are compared, with due account for energy and materials recovery, as well as possible differences in transport distance. We have not been able to quantify the total damage costs of leachates because of the complexity of the environmental pathways and of the long time horizon of some persistent pollutants, but we consider an extreme scenario to show that they are not worth worrying about in the sense that reducing the pollutants in leachates beyond current regulations would bring negligible benefit in comparison with the abatement of other sources of the same pollutants. The damage costs due to the construction of the waste treatment facility are negligible. The damage costs of waste transport, which are illustrated by an arbitrary choice of a 100 km round trip by a 16 tonne truck, are also negligible. The benefits of materials recovery make a small contribution to the total damage cost. The only significant contributions come from direct emissions (of the landfill or incinerator) and from avoided emissions due to energy recovery (from an incinerator). Damage costs for incineration range from about 4 to 21 EUR tonne waste(-1), and they are extremely dependent on the assumed scenario for energy recovery. For landfill the cost ranges from about 10 to 13 EUR tonne waste(-1); it is dominated by greenhouse gas emissions because only a fraction of the CH4 can be captured (here assumed to be 70%). Amenity costs (odour, visual impact, noise) are highly site-specific and we only cite results from a literature survey which indicates that such costs could make a significant contribution, very roughly on the order of 1 EUR tonne waste(-1).

Improving policy responses to the risk of air pollution.

This paper offers a brief review of the need for cost-benefit analysis (CBA) and the available policy instruments for air pollution. To prioritize different possible actions, one needs to know which source of pollution causes how much damage. This requires an impact pathway analysis, that is, an analysis of the chain emission --> dispersion --> dose-response function --> monetary valuation. The methodology for this is described and illustrated with the results of the ExternE (External Costs of Energy) project series of the European Commission. Two examples of an application to CBA are shown: one where a proposed reduction of emission limits is justified, and one where it is not. It is advisable to subject any proposed regulation to a CBA, including an analysis of the uncertainties. Even if the uncertainties are large and a policy decision may have to take other considerations into account, a well-documented CBA clarifies the issues and provides a basis for rational discussion. One of the main sources of uncertainty lies in the monetary valuation of premature mortality, the dominant contribution to the damage cost of air pollution. As an alternative, an innovative policy tool is described, the Life Quality Index (LQI), a compound indicator comprising societal wealth and life expectancy. It is applied to the Canada-wide standards for particulate matter and ozone. Regardless of monetary valuation, a 50% reduction of PM10 concentrations in Europe and North America has been shown to yield a population-average life expectancy increase on the order of 4 to 5 mo.

Environmental impacts and costs of energy.

Environmental damage is one of the main justifications for continued efforts to reduce energy consumption and to shift to cleaner sources such as solar energy. In recent years there has been much progress in the analysis of environmental damages, in particular thanks to the ExternE (External Costs of Energy) Project of the European Commission. This article presents a summary of the methodology and key results for the external costs of the major energy technologies. Even though the uncertainties are large, the results provide substantial evidence that the classical air pollutants (particles, No(x), and SO(2)) from fossil fuels impose significant public health costs, comparable to the cost of global warming from CO(2) emissions. The total external costs are relatively low for natural gas (in the range of about 0.5-1 eurocents/kWh for most EU countries), but much higher for coal and lignite (in the range of about 2-6 eurocents/kWh for most EU countries). By contrast, the external costs of nuclear, wind, and photovoltaics are very low. The external costs of hydro are extremely variable from site to site, and the ones of biomass depend strongly on the specific technologies used and can be quite large for combustion.

Analysis of air pollution mortality in terms of life expectancy changes: relation between time series, intervention, and cohort studies.

BACKGROUND: Information on life expectancy change is of great concern for policy makers, as evidenced by the discussions of the so-called "harvesting" issue (i.e. the question being, how large a loss each death corresponds to in the mortality results of time series studies). METHODS: Whereas most epidemiological studies of air pollution mortality have been formulated in terms of mortality risk, this paper shows that a formulation in terms of life expectancy change is mathematically equivalent, but offers several advantages: it automatically takes into account the constraint that everybody dies exactly once, regardless of pollution; it provides a unified framework for time series, intervention studies and cohort studies; and in time series and intervention studies, it yields the life expectancy change directly as a time integral of the observed mortality rate. RESULTS: Results are presented for life expectancy change in time series studies. Determination of the corresponding total number of attributable deaths (as opposed to the number of observed deaths) is shown to be problematic. The time variation of mortality after a change in exposure is shown to depend on the processes by which the body can repair air pollution damage, in particular on their time constants. Hypothetical results are presented for repair models that are plausible in view of the available intervention studies of air pollution and of smoking cessation. If these repair models can also be assumed for acute effects, the results of cohort studies are compatible with those of time series. CONCLUSION: The proposed life expectancy framework provides information on the life expectancy change in time series studies, and it clarifies the relation between the results of time series, intervention, and cohort studies.

Air pollution mortality: harvesting and loss of life expectancy.

This article concerns the interpretation of epidemiological studies of air pollution mortality and the choice of indicators for quantifying the impact, for communication with policymakers. It is shown that the total mortality impact (measured by cohort studies) can only be quantified in terms of loss of life expectancy (LLE), not number of premature deaths. Time-series (TS) studies of mortality observe only acute impacts, that is, deaths due to short-term exposure ("acute mortality"); they allow the estimation of a number of deaths without providing any information on the LLE per death. However, even if the average loss per death is as long as 6 mo, acute mortality is only a very small percentage of the total mortality attributable to air pollution. Estimates of the population-average LLE due to air pollution are provided, for acute mortality, total adult mortality, and infant mortality.

Uncertainty of air pollution cost estimates: to what extent does it matter?

How large is the social cost penalty if one makes the wrong choice because of uncertainties in the estimates of the costs and benefits of environmental policy measures? For discrete choices there is no general rule other than the recommendation to always carefully compare costs and benefits when introducing policies for environmental protection. For continuous choices (e.g., the ceiling for the total emissions of a pollutant by an entire sector or region), it is instructive to look at the cost penalty as a function of the error in the incremental damage cost estimate. Using abatement cost curves for NOx, SO2, dioxins, and CO2, this paper evaluates the cost penalty for errors in the following: national emission ceilings for NOx and SO2 in each of 12 countries of Europe, an emission ceiling for dioxins in the UK, and limits for the emission of CO2 in Europe. The cost penalty turns out to be remarkably insensitive to errors. An error by a factor of 3 due to uncertainties in the damage estimates for NOx and SO2 increases the total social cost by at most 20% and in most cases much less. For dioxins, the total social cost is increased by at most 10%. For CO2, several different possible cost curves are examined: for some the sensitivity to uncertainties is greater than for the other pollutants, but even here the penalty is less than 30% and in most cases much less if the true damage costs are twice as high as the ones estimated. The paper also quantifies the benefit of improving the accuracy of damage cost estimates by further research.

Pathway analysis for population-total health impacts of toxic metal emissions.

This article describes a simple model for quantifying the health impacts of toxic metal emissions. In contrast to most traditional models it calculates the expectation value of the total damage (summed over the total population and over all time) for typical emission sites, rather than "worst-case" estimates for specific sites or episodes. Such a model is needed for the evaluation of many environmental policy measures, e.g., the optimal level of pollution taxes or emission limits. Based on the methodology that has been developed by USEPA for the assessment of multimedia pathways, the equations and parameters are assembled for the assessment of As, Cd, Cr, Hg, Ni, and Pb, and some typical results are presented (the dose from seafood is not included and for Hg the results are extremely uncertain); the model is freely available on the web. The structure of the model is very simple because, as we show, if the parameters can be approximated by time-independent constants (the case for the USEPA methodology), the total impacts can be calculated with steady-state models even though the environment is never in steady state. The collective ingestion dose is found to be roughly 2 orders of magnitude larger than the collective dose via inhalation. The uncertainties are large, easily an order of magnitude, the main uncertainties arising from the parameter values of the model, in particular the transfer factors. Using linearized dose-response functions, estimates are provided for cancers due to As, Cd, Cr, and Ni as well as IQ loss due to Pb emissions in Europe.

Interpretation of air pollution mortality: number of deaths or years of life lost?

This paper examines the relation between the results of epidemiologic studies of air pollution mortality and impact indicators that can be informative for environmental policy decisions. Using models that are simple and transparent, yet contain the essential features, it is shown that (1) number of deaths is not meaningful for air pollution, whereas loss of life expectancy (LLE) is an appropriate impact indicator; (2) the usual short-term (time series) studies yield a change in daily number of deaths attributable to acute effects of pollution, without any information on the associated LLE (although some information on this has recently become available by extending the observation window of time series); and (3) long-term studies yield a change in age-specific mortality, which makes it possible to calculate the total population averaged LLE (acute and chronic effects) but not the total number of premature deaths attributable to air pollution. The latter is unobservable because one cannot distinguish whether few individuals suffer a large or many suffer a small LLE. The paper calculates the LLE from exposure to PM10, as implied by the long-term mortality studies of adults and infants; population LLE for infants turns out to be an order of magnitude smaller than for adults. The LLE implied by short-term studies is a small fraction of the total loss implied by long-term studies, even if one assumes a very high loss per death. Applied to environmental policy, taking a permanent 50-70% reduction of PM10 as a reasonable goal, one finds a corresponding increase of average life expectancy in urban areas of the European Union (EU) and the United States of approximately four months.