Application of Land Use Regression to Identify Sources and Assess Spatial Variation in Urban SVOC Concentrations

Abstract

Land use regression (LUR), a geographic information system (GIS), and measured air concentrations were used to identify potential sources of semivolatile organic contaminants (SVOCs) within an urban/suburban region, using Toronto, Canada as a case study. Regression results suggested that air concentrations of polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), polycyclic aromatic hydrocarbons (PAHs), and polycyclic musks (PCMs) were correlated with sources at a scale of <5 km. LUR was able to explain 73–90% of the variability in PCBs and PCMs, and 36–89% of PBDE and PAH variability, suggesting that the latter have more spatially complex emission sources, particularly for the lowest and highest molecular weight compounds/congeners.LUR suggested that ∼75% of the PCB air concentration variability was related to the distribution of PCBs in use/storage/building sealants, ∼60% of PBDE variability was related to building volume, ∼55% of the PAH variability was related to the distribution of transportation infrastructure, and ∼65% of the PCM variability was related to population density. Parameters such as population density and household income were successfully used as surrogates to infer sources and air concentrations of SVOCs in Toronto. This is the first application of LUR methods to explain SVOC concentrations