High resolution models of key pollutants

Our team members have modeled NO2 using land-use regression (LUR) for the past ten years. We plan to standardize and document the models, and temporally adjust them to monthly and annual periods (2000 to present). Looking forward, a new suite of temporally-adjusted LURs incorporating a chemical transport model (a project from Health Canada and Environment and Climate Change Canada) is in the works.

Looking ahead – hourly air pollution from North America’s geostationary satellite

In 2019 the world’s first geostationary satellite (TEMPO) for measuring air pollution will produce high resolution (~5km) maps every daytime hour of tropospheric NO2, SO2, and aerosols. These maps can be used to estimate pollutant concentrations for all Canadian cities. CANUE members Randall Martin and Chris McLinden are part of the TEMPO science team. Prior to the launch, we will develop algorithms to access these data in real-time to map surface concentrations.