To quantify the impact of the direct aerosol effect accurately, this study incorporated the Geostationary Ocean Color Imager (GOCI) aerosol optical depth (AOD) into a coupled meteorology‐chemistry model. We designed three model simulations to observe the impact of AOD assimilation and aerosol feedback during the KORUS‐AQ campaign (May–June 2016). By assimilating the GOCI AOD with high temporal and spatial resolutions, we improve the statistics from the comparison AOD and AERONET data (root‐mean‐square error: 0.12, R: 0.77, index of agreement: 0.69, mean‐absolute error: 0.08). The inclusion of the direct effect of aerosols produces the best model performance (root‐mean‐square error: 0.10, R: 0.86, index of agreement: 0.72, mean‐absolute error: 0.07). AOD values increased as much as 0.15, which is associated with an average reduction in solar radiation of ‐31.39 W/m2, a planetary boundary layer height (‐104.70 m), an air temperature (‐0.58 °C), and a surface wind speed (‐0.07 m/s) over land. In addition, concentrations of major gaseous and particulate pollutants at the surface (SO2, NO2, NH3,
normalSO42−,
normalNO3−,
normalNH4+, and PM2.5) increase by 7.87–34%, while OH concentration decreases by ‐4.58%. Changes in meteorology and air quality appear to be more significant in high‐aerosol loading areas. The integrated process rate analysis shows decelerated vertical transport, resulting in an accumulation of air pollutants near the surface and the amount of nitrate, which is higher than that of sulfate because of its response to reduced temperature. We conclude that constraining aerosol concentrations using geostationary satellite data is a prerequisite for quantifying the impact of aerosols on meteorology and air quality.