Title: The importance of population susceptibility for air pollution risk assessment: a case study of power plants near Washington, DC.

Authors: Levy, Jonathan I; Greco, Susan L; Spengler, John D

Published In Environ Health Perspect, (2002 Dec)

Abstract: In evaluating risks from air pollution, health impact assessments often focus on the magnitude of the impacts without explicitly considering the distribution of impacts across subpopulations. In this study, we constructed a model to estimate the magnitude and distribution of health benefits associated with emission controls at five older power plants in the Washington, DC, area. We used the CALPUFF atmospheric dispersion model to determine the primary and secondary fine-particulate-matter (< 2.5 micro m in aerodynamic diameter) concentration reductions associated with the hypothetical application of "Best Available Control Technology" to the selected power plants. We combined these concentration reductions with concentration-response functions for mortality and selected morbidity outcomes, using a conventional approach as well as considering susceptible subpopulations. Incorporating susceptibility had a minimal effect on total benefits, with central estimates of approximately 240 fewer premature deaths, 60 fewer cardiovascular hospital admissions (CHA), and 160 fewer pediatric asthma emergency room visits (ERV) per year. However, because individuals with lower education appear to have both higher background mortality rates and higher relative risks for air-pollution-related mortality, stratifying by educational attainment implies that 51% of the mortality benefits accrue among the 25% of the population with less than high school education. Similarly, diabetics and African Americans bear disproportionate shares of the CHA and ERV benefits, respectively. Although our ability to characterize subpopulations is constrained by the available information, our analysis demonstrates that incorporation of susceptibility information significantly affects demographic and geographic patterns of health benefits and enhances our understanding of individuals likely to benefit from emission controls.

PubMed ID: 12460806

MeSH Terms: No MeSH terms associated with this publication