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.

BackgroundIn deciding among competing approaches for emissions control, debates often hinge on the potential tradeoffs between efficiency and equity. However, previous health benefits analyses have not formally addressed both dimensions.ObjectivesWe modeled the public health benefits and the change in the spatial inequality of health risk for a number of hypothetical control scenarios for power plants in the United States to determine optimal control strategies.MethodsWe simulated various ways by which emission reductions of sulfur dioxide (SO2), nitrogen oxides, and fine particulate matter (particulate matter < 2.5 μm in diameter; PM2.5) could be distributed to reach national emissions caps. We applied a source–receptor matrix to determine the PM2.5 concentration changes associated with each control scenario and estimated the mortality reductions. We estimated changes in the spatial inequality of health risk using the Atkinson index and other indicators, following previously derived axioms for measuring health risk inequality.ResultsIn our baseline model, benefits ranged from 17,000–21,000 fewer premature deaths per year across control scenarios. Scenarios with greater health benefits also tended to have greater reductions in the spatial inequality of health risk, as many sources with high health benefits per unit emissions of SO2 were in areas with high background PM2.5 concentrations. Sensitivity analyses indicated that conclusions were generally robust to the choice of indicator and other model specifications.ConclusionsOur analysis demonstrates an approach for formally quantifying both the magnitude and spatial distribution of health benefits of pollution control strategies, allowing for joint consideration of efficiency and equity.

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Benefit-cost and regulatory impact analyses often use atmospheric dispersion models with coarse resolution to estimate the benefits of proposed mobile source emission control regulations. This approach may bias health estimates or miss important intra-urban variability for primary air pollutants. In this study, we estimate primary fine particulate matter (PM2.5) intake fractions (iF; the fraction of a pollutant emitted from a source that is inhaled by the population) for each of 23 398 road segments in the Boston Metro Core area to evaluate the potential for intra-urban variability in the emissions-to-exposure relationship. We estimate iFs using the CAL3QHCR line source model combined with residential populations within 5000 m of each road segment. The annual average values for the road segments range from 0.8 to 53 per million, with a mean of 12 per million. On average, 46% of the total exposure is realized within 200 m of the road segment, though this varies from 0 to 93% largely due to variable population patterns. Our findings indicate the likelihood of substantial intra-urban variability in mobile source primary PM2.5 iF that accounting for population movement with time, localized meteorological conditions, and street-canyon configurations would likely increase.

Air pollution benefit-cost analyses depend on dispersion models to predict population exposures to pollutants, but it is difficult to determine the reasonableness of the model estimates. This is in part because validation with field measurements is not feasible for marginal concentration changes and because few models can capture the necessary spatial and temporal domains with adequate sophistication. In this study, we use the concept of an intake fraction (the fraction of a pollutant or its precursor emitted that is eventually inhaled) to provide insight about population exposures and model performance. We apply CALPUFF, a regional-scale dispersion model common in health benefits assessments, to seven power plants in northern Georgia, considering both direct emissions of fine particulate matter (PM2.5) and secondarily formed ammonium sulfate and ammonium nitrate particles over a domain within 500 km of Atlanta. We estimate emission-weighted average intake fractions of 6 x 10(-7) for primary PM2.5, 2 x 10(-7) for ammonium sulfate from SO2, and 6 x 10(-8) for ammonium nitrate from NOx, with no effect of SO2 on ammonium nitrate. To provide insight about model strengths and limitations, we compare our findings with those from a frequently applied source-receptor (S-R) matrix. Using S-R matrix over an identical domain, the corresponding intake fractions are 5 x 10(-7), 2 x 10(-7), 3 x 10(-8), and -2 x 10(-8), respectively, with the values approximately doubling if the domain is expanded to cover the continental United States. Evaluation of model assumptions and comparison of past intake fraction estimates using these two models illustrates the importance of assumptions about the relative concentrations of ammonia, sulfate, and nitrate, which significantly influences ammonium nitrate intake fractions. These findings provide a framework for improved understanding of the factors that influence population exposures to particulate matter.

In the Mexico City metropolitan area, poor air quality is a public health concern. Diesel vehicles contribute significantly to the emissions that are most harmful to health. Harmful diesel emissions can be reduced by retrofitting vehicles with one of several technologies, including diesel particulate filters. We quantified the social costs and benefits, including health benefits, of retrofitting diesel vehicles in Mexico City with catalyzed diesel particulate filters, actively regenerating diesel particulate filters, or diesel oxidation catalysts, either immediately or in 2010, when capital costs are expected to be lower. Retrofit with either type of diesel particulate filter or an oxidation catalyst is expected to provide net benefits to society beginning immediately and in 2010. At current prices, retrofit with an oxidation catalyst provides greatest net benefits. However, as capital costs decrease, retrofit with diesel particulate filters is expected to provide greater net benefits. In both scenarios, retrofit of older, dirtier vehicles that circulate only within the city provides greatest benefits, and retrofit with oxidation catalysts provides greater health benefits per dollar spent than retrofit with particulate filters. Uncertainty about the magnitude of net benefits of a retrofit program is significant. Results are most sensitive to values used to calculate benefits, such as the concentration-response coefficient, intake fraction (a measure of exposure), and the monetary value of health benefits.