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

This paper first discusses how population exposures to environmental pollut ants are estimated from environmental monitoring data and the problems that are encountered in estimating risk from pollutants on the basis of ecologi c studies. We then present a technique of estimating individualized exposur es to an atmospheric pollutant, sulfur dioxide (SO2), through atmospheric t ransport modeling for a case-control study. The transport model uses the qu antities of SO2 released from 30 geographically identified industrial facil ities and meteorological data (wind speed and direction) to predict the dow nwind ground-level concentrations of SO2 at geographically identified resid ences, receptors, of 797 study subjects. A distribution of facility SO2 emi ssions, uncertainties in effective stack height, and model uncertainty are incorporated to examine the uncertainty in the predicted versus ambient mon itoring SO2 levels, and to generate an exposure uncertainty distribution fo r both the cases and controls. The transport model's accuracy is evaluated by comparing recorded ambient measurements of SO2 with the model's predicte d SO2 estimates at geographically identified ambient monitoring stations.