Spatial Modelling of Air Pollutants in the City of Calgary and Surrounding Areas

This study presents a spatial analysis of air quality over the City of Calgary and surrounding areas to support local air zone management strategies and air pollution health studies. Land use regression (LUR) models were estimated for nitrogen dioxide (NO2), particulate matter (PM10, PM2.5), and a group of volatile organic compounds (BTEX) in summer 2015 and winter 2016. Both ordinary least squares (OLS) regression and geographically weighted regression (GWR) methods were applied. The results showed that GWR consistently performed statistically better and provides a more appropriate tool to model the spatial variability of air pollutant at the intra-urban level and across the urban-rural continuum. LUR models are consistent over a 5-year interval.