Naman Paul - The Canadian Optimized Statistical Smoke Exposure Model (CanOSSEM)

Understanding the acute and chronic health effects of biomass smoke exposure requires reliable estimates of PM2.5 concentrations during the wildfire season and throughout the year, particularly in areas without regulatory air quality monitoring stations. We have developed a machine learning approach that estimates daily mean (24-h) PM2.5 concentrations across populated areas of Canada at a 5 km2 spatial resolution between 2010 and 2019.CanOSSEM integrates data from multiple sources including smoke plumes traced from remote sensing imagery, satellite estimates of meteorological parameters, measurements of fire radiative power, and aerosol optical depth. These estimates are available on CANUE.

Mediasite Presenter

10/27/2022 5:35:00 PM