The potential relationship between urban background pollution and urban-rural differences of biomass burning aerosol radiative effects in the North China Plain

Accurate quantitative assessment of biomass burning (BB) aerosol radiative effects (BBARE) in the North China Plain is a key scientific issue in regional aerosol radiative effects research. However, there is currently a lack of comparative analysis between BBARE based on observation and model simulations of BBARE, especially with regard to the differences between the two BBARE estimates in urban-rural differences. This study focuses on 10 typical BB events that affected Beijing during July, September and October 2014 in the North China Plain, and quantifies the BBARE at various radiation stations using both observational data-based machine learning approach and the WRF-Chem model. Based on the quantitative results, the BBARE obtained through the two methods was analysed in direct comparison and in terms of urban-rural differences. Direct comparison results indicate that the BBARE simulated by WRF-Chem shows an overall underestimation compared to the results based on observations. In terms of urban-rural differences in BBARE, observation-based BBARE was on average 91.28 % lower in urban stations than in rural stations, while model-simulated BBARE showed the opposite urban-rural difference (the urban stations' BBARE was on average 38.52 % higher than rural stations). This urban-rural difference in BBARE based on observations is due to the fact that urban SSR is more severely affected by background aerosols, resulting in limited changes in SSR caused by additional BB aerosols. However, the model simulation only considers the reduction in SSR caused by increased BB aerosols, neglecting the influence of pre-existing aerosol. By identifying these disparities, this study will help to enhance the accuracy of model simulations of BBARE.