Towards the development of a Bayesian prognostic tool of air pollution in Ontario

Air pollution is a major concern in urban centers because not only does affect vulnerable populations, but also impacts the quality of life for urban dwellers. With the new implementation of the Air Quality Health Index (AQHI) by the Ontario Ministry of the Environment and Climate Change to replace the existing Ontario Air Quality Index (AQI), there is an emerging need to forecast future environmental impacts on air quality and assess the achievability of the newly-adopted index. This research will develop a risk-assessment methodological framework to project the trends of AQHI’s pollutant concentrations due to changes in atmospheric conditions resulting from climate change in Ontario. We will use a combination of Global Climate Models (GCMs) and Bayesian inference techniques to provide a novel risk-assessment tool that can effectively support policy analysis by the Provincial and Federal government to combat climate change.

Faculty Supervisor:

Willam Gough


Kinson He Yin Leung


University of Toronto


Environmental sciences


Environmental industry




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