Spatial Variability of Ambient Nitrogen Dioxide and Sulfur Dioxide in Sarnia, “Chemical Valley,” Ontario, Canada

Abstract

This study aimed at developing models to predict nitrogen dioxide (NO₂) and sulfur dioxide (SO₂) concentrations in Sarnia, “Chemical Valley”, Ontario, Canada, and model the intra-urban variation of ambient NO₂ and SO₂ in the city for a community health study. NO₂ and SO₂ 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 NO₂ and SO₂ concentrations. The coefficients of determinations for the final NO₂ and SO₂ models were .79 and .66, respectively. The explanatory variables in the final NO₂ 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 SO₂ 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.

This project is funded by the Social Sciences and Humanities Research Council of Canada grant to Dr. Luginaah, Dr. Xu, and Dr. Fung, and Canada Research Chair funding to Dr. Luginaah. The authors thank the Ontario Ministry of Transportation for providing assistance in accessing the highways traffic count data and the City of Sarnia Works Administration and Engineering Department for providing the local daily traffic counts. The authors \ also thank the students at the University of Windsor for assisting in air quality data collection. We thank the anonymous reviewers for their very constructive suggestions and comments.