Plume height plays a vital role in wildfire smoke dispersion and the subsequent effects on air quality and human health. In this study, we assess the impact of different plume rise schemes on predicting the dispersion of wildfire air pollution and the exceedances of the National Ambient Air Quality Standards (NAAQS) for fine particulate matter (PM2.5 ) during the 2020 western United States wildfire season. Three widely used plume rise schemes (Briggs, 1969; Freitas et al., 2007; Sofiev et al., 2012) are compared within the Community Multiscale Air Quality (CMAQ) modeling framework. The plume heights simulated by these schemes are comparable to the aerosol height observed by the Multi-angle Imaging SpectroRadiometer (MISR) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). The performance of the simulations with these schemes varies by fire case and weather conditions. On average, simulations with higher plume injection heights predict lower aerosol optical depth (AOD) and surface PM2.5 concentrations near the source region but higher AOD and PM2.5 in downwind regions due to the faster spread of the smoke plume once ejected. The 2-month mean AOD difference caused by different plume rise schemes is approximately 20 %–30 % near the source regions and 5 %– 10 % in the downwind regions. Thick smoke blocks sunlight and suppresses photochemical reactions in areas with high AOD. The surface PM2.5 difference reaches 70 % on the West Coast of the USA, and the difference is lower than 15 % in the downwind regions. Moreover, the plume injection height affects pollution exceedance (> 35 µg m−3 ) predictions. Higher plume heights generally produce larger downwind PM2.5 exceedance areas. The PM2.5 exceedance areas predicted by the three schemes largely overlap, suggesting that all schemes perform similarly during large wildfire events when the predicted concentrations are well above the exceedance threshold.
Impacts of estimated plume rise on PM2.5 exceedance prediction during extreme wildfire events: A comparison of three schemes (Briggs, Freitas, and Sofiev)
Li, Y., D. Tong, S. Ma, S.R. Freitas, R. Ahmadov, M. Sofiev, X. Zhang, S. Kondragunta, R.A. Kahn, Y. Tang, B. Baker, P. Campbell, R. Saylor, I. Stajner, and G. Grell (2022), Impacts of estimated plume rise on PM2.5 exceedance prediction during extreme wildfire events: A comparison of three schemes (Briggs, Freitas, and Sofiev), Atmos. Chem. Phys., 23, 3083-3101, doi:10.5194/acp-23-3083-2023.
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Research Program
Applied Sciences Program (ASP)
Atmospheric Composition
Atmospheric Composition Modeling and Analysis Program (ACMAP)
Mission
Terra- MISR
Terra-MODIS
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