Abstract
Multi-city population-based epidemiological studies have observed significant heterogeneity in both the magnitude and direction of city-specific risk estimates, but tended to focus on regional differences in PM2.5 mortality risk estimates. Interpreting differences in risk estimates is complicated by city-to-city heterogeneity observed within regions due to city-to-city variations in the PM2.5 composition and the concentration of gaseous pollutants. We evaluate whether variations in PM2.5 composition and gaseous pollutant concentrations have a role in explaining the heterogeneity in PM2.5 mortality risk estimates observed in 27 US cities from 1997 to 2002. Within each region, we select the two cities with the largest and smallest mortality risk estimate. We compare for each region the within- and between-city concentrations and correlations of PM2.5 constituents and gaseous pollutants. We also attempt to identify source factors through principal component analysis (PCA) for each city. The results of this analysis indicate that identifying a PM constituent(s) that explains the differences in the PM2.5 mortality risk estimates is not straightforward. The difference in risk estimates between cities in the same region may be attributed to a group of pollutants, possibly those related to local sources such as traffic.
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Acknowledgements
We thank Lucas Neas of the US EPA’s National Health and Environmental Effects Research Laboratory. We would also like to thank Tom Luben of the US EPA’s National Center for Exposure Assessment and Kathie Dioniosio of the US EPA’s National Exposure Research Laboratory for their review of this paper.
DISCLAIMER
The United States Environmental Protection Agency through its Office of Research and Development funded and managed the research described here. It has been subjected to Agency's administrative review and approved for publication.
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Baxter, L., Duvall, R. & Sacks, J. Examining the effects of air pollution composition on within region differences in PM2.5 mortality risk estimates. J Expo Sci Environ Epidemiol 23, 457–465 (2013). https://doi.org/10.1038/jes.2012.114
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DOI: https://doi.org/10.1038/jes.2012.114
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