A land use regression road map for the Burrard Inlet Area Local Air Quality Study Brauer, Michael; Henderson, Sarah B.; Marshall, Julian
This report includes a road map for developing land use regression models to describe spatial variability of air pollution concentrations within urban areas. Land use regression attempts to better estimate exposure levels for a given population by measuring pollutants at multiple sites specifically selected to capture the complete intra-urban range of its concentrations. Geographic attributes that might be associated with those concentrations are measured around each site in a Geographic Information System (GIS). Typical geographic predictor variables describe site location, surrounding land use, population density, and traffic patterns. Linear regression is used to correlate measured concentrations with the most predictive variables, and the resulting equation can be used to estimate pollutant concentrations anywhere that all of the predictors can be measured. Concentration maps with high spatial resolution can be generated by rendering the regression model in GIS.
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