The University of Utah Wilkes Center for Climate Science & Policy has released a new demonstration tool to provide advanced warnings for unhealthy air events from wildfire smoke.
The new physics-based tool, with machine learning and predictive analytics-based augmentation, demonstrates air quality forecasting capabilities that Trace Air Quality (Trace AQ), a U startup, has developed to meet the growing threat of wildfire smoke and pollution events.
The tool depicts a smoke forecast map generated in part using the Community Multiscale Air Quality (CMAQ) modeling system, which is the EPA’s open-source air quality modeling system, to simulate fire activity and the movement of wildfire smoke particulate matter across various scales. While the free version of the smoke tool generates forecasts out to one day, the subscription Trace AQ model can forecast out to four days in advance, available at TraceAQ.com.
“The Trace AQ smoke and air quality forecast is the product of nearly ten years of research and development at the University of Utah,” said Taylor (Kai) Wilmot, postdoctoral research associate in the U’s Department of Atmospheric Sciences and CTO at Trace AQ. “Insight developed through research into wildfire plume rise, wildfire emissions, fire-atmosphere interactions, atmospheric transport of smoke, and atmospheric chemistry informs the current iteration of the forecast, with further development on the horizon. We view this as the beginning of these efforts and aim to extend the body of knowledge driving this model.”
The model is supported by the Wilkes Center, National Science Foundation CIVIC Innovation Program, and the U’s Center for High Performance Computing.
Department of Atmospheric Sciences researchers Derek Mallia and Kai Wilmot, and Heather Holmes in the Department of Chemical Engineering developed the core technology over years of federally funded research at the U. They then partnered with Victor Gill, a tech executive with experience bringing cutting-edge digital technologies to market, for support with commercialization.
Continue reading Ross Chambless’ “U Scientists Develop AI-powered Tool to Forecast Wildfire Smoke” on @theU.