Abstract
Wildfires can inject smoke at high altitudes into the atmosphere. The resulting free tropospheric aerosols may affect inference of ground-level fine particulate matter (PM(2.5)) from satellite aerosol optical depth (AOD), yet the effects of accounting for plume height in this inference are poorly understood. Here, we include in the GEOS-Chem chemical transport model a fire plume height parametrization (GFAS, Global Fire Assimilation System) to examine its effect on PM(2.5) inferred from satellite AOD during wildfires over the United States and Canada. Comparison with six years satellite observations of plume height reveals a low bias of a factor 1.7 in the GFAS plume height over evergreen needleleaf forests. We scale the GFAS plume height over evergreen needleleaf forests in GEOS-Chem to better represent the satellite observations, focusing on 2018 and 2020 when large wildfires yield prominent signals. Replacing the default ground-level wildfire emissions in GEOS-Chem with the scaled GFAS vertically distributed emissions reduces the bias between measured PM(2.5) and PM(2.5) inferred from satellite AOD, and significantly improves the consistency of simulated AOD with sun photometer measurements. Overall, this study signifies the importance of vertically distributing wildfire emissions for the inference of PM(2.5) from satellite AOD.