Abstract:
Smoke forecasts for wildfires in central Utah were evaluated using low-cost air quality sensors and measurements from an instrument attached to a public transit train car. Preliminary results from this study suggest that calibrated low-cost sensors can measure pollutant concentrations during wildfire smoke events within 10% of values measured by traditional air quality stations. A unique benefit of low-cost sensor and mobile measurement networks is that they can delineate the edges of smoke plumes and are useful for identifying small-scale processes that effect smoke plume dispersion. Smoke forecasts from a weather prediction model were able to capture the timing of a smoke plume, which inundated the Salt Lake Valley during the morning of 15 September 2018. However, local observations indicated that forecasted smoke was overpredicted by a factor of 2. Smoke forecast errors could potentially be attributed to fire growth errors in the fire spread model used within the weather prediction model.

(Co-authors: Derek V. Mallia, Adam K. Kochanski, Kerry E. Kelly, Ross Whitaker, Wei Xing, Logan E. Mitchell, Alex Jacques, Angel Farguell, Jan Mandel, Pierre-Emmanuel Gaillardon, Tom Becnel, Steven K. Krueger)

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https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2020JD032712

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