Accurate forecasting of air quality demands better estimates of aerosol emissions. The accuracy of conventional bottom‐up approaches to estimate aerosol emissions depends on the degree to which various influencing parameters… Click to show full abstract
Accurate forecasting of air quality demands better estimates of aerosol emissions. The accuracy of conventional bottom‐up approaches to estimate aerosol emissions depends on the degree to which various influencing parameters are estimated. The availability of satellite observations not only enhances the capability of determining various influencing parameters, but also provides alternate ways of assessing aerosol sources. The present study employs a Lagrangian approach to the Advection Diffusion Equation (ADE) to estimate the transported aerosols and hence the Aerosol Source Strength (ASS) using satellite‐measured Aerosol Optical Depth (AOD) and reanalysis wind data. This top‐down approach is based on the advection and diffusion of atmospheric aerosols considering wind circulation and atmospheric conditions rather than using indicative parameters. ASS was computed every 3 hr at a 0.25°×0.25° grid across California during July 2018. For the computation, AOD retrievals were obtained from the Geostationary Operational Environmental Satellite (GOES)‐16 with observations every 15 min. The data were resampled to the grid every 3 hr, and backward trajectories were run at every gridpoint to ascertain the initial aerosol concentration for the ADE. The final aerosol concentrations obtained from the ADE model were then compared with the observed AOD to obtain the ASS during that time period. The results are indicative of higher ASS around wildfire locations. The ASS values also show good correlation (R2=0.886) with Fire Radiative Power (FRP) obtained from Terra MODIS fire product. The method was further applied to investigate the spatial correlation of ASS with power plant density, which reveals a steady increase in ASS with power plant density (R2=0.82).
               
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