ABSTRACT
Land use regression (LUR) modeling is proposed as a promising approach to meet some of the challenges of assessing the intra-urban spatial variability of ambient air pollutants in urban and industrial settings. However, most of the LUR models to date have focused on nitrogen oxides and particulate matter. This study aimed at developing LUR models to predict BTEX (benzene, toluene, ethylbenzene, m/p-xylene, and o-xylene) concentrations in Sarnia, “Chemical Valley,” Ontario, and model the intraurban variability of BTEX compounds in the city for a community health study.
