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Validating Wildfire Smoke Transport within a High-density, Low-cost Sensor Network
KERRY KELLY, Derek Mallia, Adam Kochanski, Wei Xing, Tofigh Sayahi, Tom Becnel, Pierre-Emmanuel Gaillardon, Ross Whitaker, University of Utah
Abstract Number: 54
Working Group: Instrumentation and Methods
Abstract
Short-term exposure to fine particulate matter (PM2.5) pollution is linked to numerous adverse health effects. Wildfires can lead to substantial increases in PM2.5 levels, and these impacts are becoming a growing concern as both the number and size of wildfires continues to increase. Although many smoke modeling tools exist, accurately simulating smoke production and dispersion is difficult, especially in regions with complex terrain where smoke plumes tend to exhibit substantial spatiotemporal variability. One of the fundamental problems associated with smoke modeling is the lack of highly resolved validation data. In this study, we use a network of 503 sensors (AQ&U and PurpleAir) located along Utah’s Wasatch front to evaluate the performance of a coupled fire-atmosphere model (WRF-SFIRE-CHEM) to simulate fire emissions and smoke dispersion during the Pole Creek Wildfire. This fire burned an area over 260 km2 adjacent the Wasatch Front during the summer of 2018 and led to PM2.5 levels that exceeded 90 µg/m3. The sensor measurements and modeling results reveal dramatic spatiotemporal differences in PM2.5 concentration during this episode and suggest that coupled fire-atmosphere models such as WRF-SFIRE-CHEM can resolve local drainage flow and the downwind dispersion of wildfire smoke plumes in regions of significant topographic relief.
Conflict of Interest: Drs. Gaillardon and Kelly have a financial interest in the company Tetrad: Sensor Network Solutions, LLC, which commercializes solutions for environmental monitoring.