American Association for Aerosol Research - Abstract Submission

AAAR 37th Annual Conference
October 14 - October 18, 2019
Oregon Convention Center
Portland, Oregon, USA

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Validating the Intervention Model for Air Pollution for Environmental Health and Justice Analysis in Canada

RIVKAH GARDNER-FROLICK, Christopher Tessum, Julian Marshall, Amanda Giang, University of British Columbia

     Abstract Number: 885
     Working Group: Urban Aerosols

Abstract
Reduced complexity air quality models are valuable for predicting pollutant concentrations while requiring less computing power and being more accessible to diverse knowledge users than traditional chemical transport models. The Intervention Model for Air Pollution (InMAP) is one such model that uses simplified chemistry and physics, paired with health impact formulas, to focus on the health impacts of fine particulate matter (PM2.5) and the distribution of impacts across populations. The model uses a variable grid with up to 1-km resolution, enabling estimates of urban exposures while still covering a large spatial domain. These characteristics make InMAP especially useful for a variety of applications, including those that aim to investigate environmental justice questions, those that necessitate many model runs, and projects that cannot use chemical transport models.

Currently, the InMAP domain includes Canada as part of the emissions scenario for the United States. However, the model has not yet been validated in Canada and has not been run with Canada-specific data. This project validates InMAP estimates against measured concentrations of PM2.5 and other criteria pollutants at Canadian government monitoring stations. In addition, the project validates InMAP results when the model is instead run with Canadian emissions and demographic data. Updating the model to include Canada-specific emissions and demographic data will enable InMAP’s use to answer uniquely Canadian environmental justice questions about PM2.5 exposure and distribution among vulnerable populations.