Modelling Arsenic and Lead Surface Soil Concentrations using Land Use Regression
1 Department of Geography, University of Victoria, Victoria, Canada
2 Cancer Care Ontario, Toronto, Canada
Land Use Regression (LUR) models are increasingly used in environmental and exposure assessments to predict the concentration of contaminants in outdoor air. We explore the use of LUR as an alternative to more complex models to predict the concentration of metals in surface soil. Here, we used 55 soil samples of As and Pb collected in 1996 across British Columbia (BC), Canada by the Ministry of Environment. Predictor variables were derived for each sample site using Geographic Information System (GIS). For As (R2 = 0.44), the resulting linear regression model includes the total length of roads (m) within 25 km, and bedrock geology. For the Pb model (R2 =0.78), the predictor variables are the total surface area of industrial land use (m2) within 5 km , the emissions of Pb (t) within 10 and 25 km, and the presence of closed mines within 50 km. The study proposes that LUR can reasonably predict the concentrations of As and Pb in surface soil over large areas.
Key words: exposure / land use regression / geographic information systems / arsenic / lead
© Owned by the authors, published by EDP Sciences, 2013
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