Abstract

Methods commonly used to assess the environmental exposure risk at a location (e.g., proximity models) are usually based on different assumptions, leading to conflicting results and recommendations in epidemiological studies. In this case study, a comparative evaluation of the accuracy levels associated with four commonly used exposure risk estimate models [i.e., traditional proximity model (TPM), emission weighted proximity model (EWPM), the American Meteorological Society/EPA regulatory model (AERMOD), and ordinary kriging interpolation (OKI)] were conducted. Results show that at the annual and the monthly scales, the normalized exposure risk values simulated by AERMOD and EWPM have higher accuracy levels than the simulations from the TPM and OKI methods. However, AERMOD has higher accuracy than that of the EWPM, and this was attributed to the differences of input data. EWPM provided the most accurate simulations when analysts have access to only point emission source data. The results also indicate that the accuracies of the exposure risks simulated by AERMOD and EWPM can be influenced by factors such as the modeling extent, the distance settings, and so forth.

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