Estimating environmental exposures to sulfur dioxide from multiple industrial sources for a case–control study

Abstract

This paper first discusses how population exposures to environmental pollutants are estimated from environmental monitoring data and the problems that are encountered in estimating risk from pollutants on the basis of ecologic studies. We then present a technique of estimating individualized exposures to an atmospheric pollutant, sulfur dioxide (SO₂), through atmospheric transport modeling for a case–control study. The transport model uses the quantities of SO₂ released from 30 geographically identified industrial facilities and meteorological data (wind speed and direction) to predict the downwind ground-level concentrations of SO₂ at geographically identified residences, receptors, of 797 study subjects. A distribution of facility SO₂ emissions, uncertainties in effective stack height, and model uncertainty are incorporated to examine the uncertainty in the predicted versus ambient monitoring SO₂ levels, and to generate an exposure uncertainty distribution for both the cases and controls. The transport model's accuracy is evaluated by comparing recorded ambient measurements of SO₂ with the model's predicted SO₂ estimates at geographically identified ambient monitoring stations.