Burning agricultural straw before and/or after harvest is a common farming practice. Regional and extensive agricultural open field straw burning can cause serious air pollution events. This paper looks at the effects of biomass burning emission on regional haze that should be considered in the forecasting of regional haze. It describes the current state of crop residue burning in China, and analyzes the relationship between biomass burning and regional haze in terms of temporal/spatial patterns and chemical composition. Finally, some suggestions/recommendations are proposed for the recycling of agricultural straw to reduce the impact of biomass burning on regional haze and air quality. We suggest that prescribed open burning would be a more suitable solution in China. We hope that this report about biomass burning and regional haze will bring the issue to the attention of governments and other researchers.

Atmospheric aerosols can exert an influence on meteorology and air quality through aerosol–radiation interaction (ARI) and aerosol–cloud interaction (ACI), and this two-way feedback has been studied by applying two-way coupled meteorology and air quality models. As one of the regions with the highest aerosol loading in the world, Asia has attracted many researchers to investigate the aerosol effects with several two-way coupled models (WRF-Chem, WRF-CMAQ, GRAPES-CUACE, WRF-NAQPMS, and GATOR-GCMOM) over the last decade. This paper attempts to offer a bibliographic analysis regarding the current status of applications of two-way coupled models in Asia, related research focuses, model performances, and the effects of ARI and/or ACI on meteorology and air quality. There were a total of 160 peer-reviewed articles published between 2010 and 2019 in Asia meeting the inclusion criteria, with more than 79 % of papers involving the WRF-Chem model. The number of relevant publications has an upward trend annually, and East Asia, India, and China, as well as the North China Plain are the most studied areas. The effects of ARI and both ARI and ACI induced by natural aerosols (particularly mineral dust) and anthropogenic aerosols (bulk aerosols, different chemical compositions, and aerosols from different sources) are widely investigated in Asia. Through the meta-analysis of surface meteorological and air quality variables simulated by two-way coupled models, the model performance affected by aerosol feedbacks depends on different variables, simulation time lengths, selection of two-way coupled models, and study areas. Future research perspectives with respect to the development, improvement, application, and evaluation of two-way coupled meteorology and air quality models are proposed.

Two-way coupled meteorology and air quality models, which account for aerosol–radiation–cloud interactions, have been employed to simulate meteorology and air quality more realistically. Although numerous related studies have been conducted, none have compared the performances of multiple two-way coupled models in simulating meteorology and air quality over eastern China. Thus, we systematically evaluated annual and seasonal meteorological and air quality variables simulated by three open-source, widely utilized two-way coupled models (Weather Research and Forecasting (WRF)–Community Multiscale Air Quality (WRF–CMAQ), WRF coupled with chemistry (WRF–Chem), and WRF coupled with a regional chemistry-transport model named CHIMERE (WRF–CHIMERE)) by validating their results with surface and satellite observations for eastern China in 2017. Although we have made every effort to evaluate these three coupled models by using configurations that are as consistent as possible, there are still unavoidable differences between them in their treatments of physical and chemical processes. Our thorough evaluations revealed that all three two-way coupled models captured the annual and seasonal spatiotemporal characteristics of meteorology and air quality reasonably well. Notably, the role of the aerosol–cloud interaction (ACI) in improving the models' performances was limited compared to that of the aerosol–radiation interaction (ARI). The sources of uncertainties and bias in the different ACI schemes in the two-way coupled models were identified. With sufficient computational resources, these models can provide more accurate air quality forecasting to support atmospheric environment management and deliver timely warnings of heavy air pollution events. Finally, we propose potential improvements to two-way coupled models for future research.