Tuesday, July 13 (10am AKDT)
Allison Baer | PhD Candidate
University of Maryland, Department of Geographical Sciences
The spatiotemporal coverage of regulatory-grade, ground-based air quality monitoring stations measuring PM2.5 concentrations is low across Alaska. Recently, there has been an increase in the number of low-cost air quality monitoring stations for PM2.5 that expand the spatiotemporal coverage of PM2.5 monitoring in Alaska and globally. This study uses a random forest model to predict PM2.5 concentrations from regulatory-grade data and corrected low-cost air quality monitoring data from the 2019 wildfire season (May through September) in Alaska. Results show that the model predicts a high amount of the variance at over 0.75. These results will inform mapping of PM2.5 continuous concentrations across Alaska.