Influence of aerosol–meteorology interactions on visibility during a wintertime heavily polluted episode in Central-East, China

Atmospheric visibility profoundly impacts daily life, and accurate prediction is crucial, particularly in conditions of low visibility characterized by high aerosol loading and humidity. This study employed the WRF-Chem model to simulate a severe wintertime haze pollution episode that transpired from January 17 to 19, 2010, in Central-East China (112–122° E, 34–42° N). The results reveal that excluding aerosol–meteorology interactions led to underestimated PM_2.5 concentrations and relative humidity in comparison with ground-based measurement data, accompanied by a significant overestimation of visibility. Aerosols can engage with meteorological elements, particularly humidity, resulting in positive feedback. Upon considering these feedback interactions, the simulation results showed an increase of 5.17% and 1.99% in PM_2.5 concentration and relative humidity, respectively, compared with the original simulation. This adjustment narrowed the bias between simulated and measured data. The overestimation of simulated visibility was reduced by 16% and 25% for the entire study period and the severe haze pollution period, respectively. These findings underscore the vital role of incorporating aerosol–meteorology interactions in visibility simulations using the WRF-Chem model. Notably, the inclusion of aerosol–meteorological feedback significantly enhances the accuracy of visibility predictions, particularly during heavily polluted periods.