Wildland fires are a natural phenomenon in many ecosystems, and have become a growing concern in the united states

With widespread population growth in the wildland-urban interface, wildfires pose a greater risk to human health and properties. Efforts to improve air quality over the past decades show promising trends, as evidenced from reductions in particulate matter pollution in the majority of the U.S., except in wildfire-prone regions where air quality has been worsening. As a result, wildfires are a vital component in modern air quality forecast systems. Despite decades of research, wildfire modeling still faces challenges in essentially all air quality models, leading to uncertainties in evaluating the wildfire impacts on human health as well as short-term weather forecast skills. This project will develop an improved wildfire representation in a community air quality modeling framework motivated by fundamental challenges and practical needs: (I) a computationally efficient mach