High-resolution modeling of gaseous air pollutants over Tehran and validation with surface and satellite data

This study addresses the question of how skillful regional air quality modeling can be when using downscaled globally-available emission inventories. paper applies global datasets to prepare fine-resolution priori inventories for an urban area. Emissions Database Global Atmospheric Research (EDGAR), Gridded Population World, and output from Fossil Fuel Data Assimilation System are used downscale spatiotemporal resolution finer scale. The resultant high-resolution inventory is taken as input off-line run Community Multi-Scale Air Quality (CMAQ) system simulate concentrations pollutants in Tehran during August 2018, November February 2019, May 2019. These runs forced with meteorology Weather Forecasting (WRF) model. Retrievals atmospheric composition TROPOspheric Monitoring Instrument (TROPOMI) surface measurements (split into ‘road’ or ‘city’ type stations) compare modeled NO2, CO, O3 assess capability applied framework concentration estimations. Comparison NO2 tropospheric column shows that model captures spatial temporal distribution Pearson correlation above 0.7 0.6, respectively absolute bias under 0.08 ppb. offline WRF-CMAQ simulations overestimate CO underestimate O3. diurnal variations a between 0.91, 0.6–0.8, 0.5–0.98 less than 69 ppb, 1.15 ppm, 12.5 respectively. overall performance observing sufficient credible inversion emissions, which intended purpose this set-up.