Abstract The Middle East (ME) is threatened by severe air pollution due to human‐induced sulfur dioxide () emissions from the oil and gas industry, power, and desalination plants. emissions contribute to sulfate aerosol generation, impacting cloud formation and climate. This study refines the daily OMI‐HTAP emissions from 134 point sources (mainly in the ME) for 2016 using inverse modeling, Ozone Mapping Profiling Suite (OMPS) column loading observations, and the Lagrangian particle dispersion FLEXPART‐WRF model. This model used hourly meteorological data from the Weather Research and Forecasting model coupled with chemistry (WRF‐Chem) run with OMI‐HTAP inventory with zeroed emissions from the point sources. This allowed the exclusion of the “background” column loadings caused by the spatially distributed emissions from the OMPS observations. The WRF‐Chem's code for simulating sinks (dry deposition, oxidation) was ported into the FLEXPART‐WRF. The annual mean RMSE computed for posterior column loadings relative to OMPS observations improved by 21%. The total posterior point emissions rate dropped by 18%. We found that this overestimation of prior emissions is inherent to data‐driven emission quantification methods (e.g., the Gaussian plume fitting method), which are not capable of removing “background” column loadings in areas with a high density of strong point sources. The proposed approach avoids this deficiency. For some countries, seasonal variations of inverted emission rates are observed. The enhanced OMI‐HTAP data set will be applied in air‐quality modeling over the ME.
Ukhov et al. (Fri,) studied this question.