An approach for estimating exposure to ambient concentrations.

The degree of certainty in epidemiological studies is probably limited more by estimates of exposure than by any other component. We present a methodology for computing daily pollutant concentration fields that reduces exposure uncertainty and bias by taking account of spatial variation in air quality. This approach, using elliptical influence functions, involves the optimum blending of observations from a monitoring network with gridded pollution fields predicted by the complex air quality model TAPM.