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Evaluating Wildfire Smoke Transport Within a Coupled Fire‐Atmosphere Model Using a High‐Density Observation Network for an Episodic Smoke Event Along Utah's Wasatch Front
Author(s) -
Mallia Derek V.,
Kochanski Adam K.,
Kelly Kerry E.,
Whitaker Ross,
Xing Wei,
Mitchell Logan E.,
Jacques Alex,
Farguell Angel,
Mandel Jan,
Gaillardon PierreEmmanuel,
Becnel Tom,
Krueger Steven K.
Publication year - 2020
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1029/2020jd032712
Subject(s) - smoke , environmental science , plume , atmosphere (unit) , air quality index , meteorology , terrain , atmospheric dispersion modeling , event (particle physics) , atmospheric sciences , dispersion (optics) , air pollution , geology , geography , cartography , physics , ecology , quantum mechanics , optics , biology
One of the primary challenges associated with evaluating smoke models is the availability of observations. The limited density of traditional air quality monitoring networks makes evaluating wildfire smoke transport challenging, particularly over regions where smoke plumes exhibit significant spatiotemporal variability. In this study, we analyzed smoke dispersion for the 2018 Pole Creek and Bald Mountain Fires, which were located in central Utah. Smoke simulations were generated using a coupled fire‐atmosphere model, which simultaneously renders fire growth, fire emissions, plume rise, smoke dispersion, and fire‐atmosphere interactions. Smoke simulations were evaluated using PM 2.5 observations from publicly accessible fixed sites and a semicontinuously running mobile platform. Calibrated measurements of PM 2.5 made by low‐cost sensors from the Air Quality and yoU (AQ&U) network were within 10% of values reported at nearby air quality sites that used Federal Equivalent Methods. Furthermore, results from this study show that low‐cost sensor networks and mobile measurements are useful for characterizing smoke plumes while also serving as an invaluable data set for evaluating smoke transport models. Finally, coupled fire‐atmosphere model simulations were able to capture the spatiotemporal variability of wildfire smoke in complex terrain for an isolated smoke event caused by local fires. Results here suggest that resolving local drainage flow could be critical for simulating smoke transport in regions of significant topographic relief.