This study aimed at developing models to predict nitrogen dioxide (NO(2)) and sulfur dioxide (SO(2)) concentrations in Sarnia, "Chemical Valley", Ontario, Canada, and model the intra-urban variation of ambient NO(2) and SO(2) in the city for a community health study. NO(2) and SO(2) samples were monitored with Ogawa passive samplers at 39 locations across the city for 2 wk during the fall of 2005. The final land use regression models were constructed to generate independent variables that might best predict NO(2) and SO(2) concentrations. The coefficients of determinations for the final NO(2) and SO(2) models were .79 and .66, respectively. The explanatory variables in the final NO(2) model were: proximity to the industrial core, industrial areas within 1600 m, highways within 400 m, and dwelling counts within 2400 m. The variables in the final SO(2) model were: proximity to the industrial core, industrial areas within 1200 m, and major roads within 100 m. The spatial variations captured in these analyses are being used to estimate ambient pollution concentrations for a large health study.

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http://dx.doi.org/10.1080/15287390802414158DOI Listing

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