Comparisons of high spatiotemporal resolution air quality modeling frameworks for prescribed burning simulations at a military base in the southeastern United States
| Authors: | Zongrun Li, Rime El Asmar, Susan O'Neill, Yongtao Hu, Haofei Yu, Yunyao Li, David J. Tanner, L. Gregory Huey, Rodney J. Weber, Armistead G. Russell, M. Talat Odman |
| Year: | 2025 |
| Type: | Scientific Journal |
| Station: | Pacific Northwest Research Station |
| DOI: | https://doi.org/10.1029/2025JD044677 |
| Source: | Journal of Geophysical Research: Atmospheres |
Abstract
High spatiotemporal resolution air quality modeling is essential for air quality impact assessments and decision‐making for prescribed burns. Accurate representation of the heterogeneous distribution of fuels and the structure of smoke plumes requires high‐resolution modeling frameworks. In this study, we conducted simulations of prescribed burns in Fort Benning, Georgia, with BlueSky‐CMAQ and WRF‐SFIRE modeling frameworks and compared the differences between the results. BlueSky‐CMAQ was run at a 1‐km resolution, while WRF‐SFIRE operated at a 200‐m resolution, both generating outputs every 20 min. We compared the emission profiles, smoke plume structures, and ground‐level concentrations of pollutants between these two modeling frameworks. We used measurements of winds and pollutant concentrations collected at the military base to evaluate model performance and identify critical factors affecting simulation accuracy, including the plume rise scheme, uncertainties from satellite‐detected fire start time and FRP, and biases in wind simulations. All settings of the simulation frameworks showed a correlation higher than 0.21 with measurements of PM 2.5 during the prescribed burning periods. The WRF‐SFIRE had the highest correlation (r = 0.29) with observation, and the BlueSky‐CMAQ with Freitas plume rise scheme showed the best performance for simulating the intensity of detected smoke, with a regression slope of 0.93. The findings and lessons learned are presented to inform future field measurement design and model implementations for studying the prescribed fire impacts on local air quality.