Comprehensive Modelling and Visualization of Particulate Matter in Support of Air Quality Management in Prince George, British Columbia, Canada

Abstract

Prince George British Columbia has among the highest levels of ambient particulate matter (PM) in western Canada. In order to effectively lower ambient PM levels, management agencies need to be able to attribute ambient levels to specific sources, which can then be targeted for reduction. Dispersion modelling can be used to attribute sources to ambient levels, but one issue is that emissions from many PM sources are poorly known and must be estimated. The Calpuff dispersion modelling system was applied to all known sources of PM10, PM2.5, NOx and SO2 affecting the Prince George airshed over the three-year period 2003–2005. The model results were evaluated by comparison with ambient levels as well as with results from a speciation study using Positive Matrix Factorization and Chemical Mass Balance techniques. This resulted in constraints on the emissions of some of the more poorly characterized sources. In addition, a web-based visualization and scenario tool was developed for air quality managers to enable them to make science-based decisions to improve air quality. The results of the modelling and source attribution will be discussed, and the web-based scenario tool demonstrated.