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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. [ABSTRACT FROM AUTHOR]

Open-field crop residue burning (OCRB) is a widespread agricultural practice with significant impacts on regional environments and public health. The effective management of OCRB remains a challenging task that requires timely access to various forms of monitored and forecasted information. Addressing this worldwide need, an open-source platform named AgriFireInfo v1.0, which is specifically tailored to monitoring and regulating regional OCRB activities, was developed. This technical note thoroughly illustrates the platform's architecture, major modules, and visualization processes. Through AgriFireInfo v1.0, government agencies can access timely information about the spatial distribution of fire spots and emissions as well as meteorological conditions and air quality status. AgriFireInfo v1.0 also introduces an innovative Prevention Alarming Index, designed to identify regions prone to OCRB and promote comprehensive crop residue utilization. Furthermore, it offers the burning window and crop residue yields for controlled OCRB activities and can be used to analyze shifts in farmers' burning behaviors and intensities. Future enhancements will focus on supplying holistic information on the burning windows and burning amounts of crop residues to further facilitate refined controlled burning activities and optimize decision-making processes. The flexibility and scalability of this platform can potentially allow users to easily customize and apply it to other regions or countries. [ABSTRACT FROM AUTHOR]

Harbin is a northmost megacity in the cold regions of China and experiences severe PM2.5 pollution. However, comprehensive investigations for severe haze formation are few. In this study, we simultaneously measured aerosol composition in real time to assess the sources apportionment, regional transport and its interaction with meteorology from 1 October 2018 to 1 May 2019 by using the single particle aerosol mass spectrometer (SPAMS). The daily average PM2.5 concentration was 51.21 µg/m3 with the hourly maximum of 900.45 µg/m3. Winter coal combustion was the largest source of PM2.5 aerosols during this period. Open straw burning from surrounding and adjacent areas by short-distance transport could aggravate air quality deterioration in Harbin. Three extreme haze events (i.e., Ep1, Ep2 and Ep3) were observed in this study, showing the typical characteristics of local winter pollution. The pollutants of PM2.5 and SO2 emitted from coal combustion played an important role in haze episode during Ep1, whereas Ep2 was caused by the joint effect of coal combustion and straw burning. Ep3 was characterized by long-distance transport of windblown dust from southeast Inner Mongolia and northwest Harbin. Real-time source apportionment of fine particulate matter highlights the importance of joint control of coal and straw burning from the surrounding cities of Harbin. [ABSTRACT FROM AUTHOR]

Atmospheric particulate matter (PM) from agricultural activities aggravates global, regional, and local air pollution. The detailed emission evaluation for major crops can be used to understand, predict, and control the release of atmospheric PM from or in agriculture. However, previous studies on sources of emissions from agricultural activities have tended to focus only on straw burning, livestock or fertilizer, etc. at a macro scale, such that there is a lack of spatial–temporal and high-resolution quantitative data on particulate emissions generated from typical farming and harvesting activities. In this study, we developed high-resolution emission inventory of atmospheric PM10 generated as a result of tilling and harvesting in China using a crop emission factor–based approach, combining agricultural, meteorological, and soil information. Temporal, spatial, and historical features of agricultural PM10 emission in China were analyzed, and an optimization methodology was proposed. The historical trends (1978–2015) for agricultural emissions have been increasing with rate of 4.3% per year for the period. The annual emissions from all agricultural operations were estimated to be 986.8kt in 2015. The contribution rate for tilling (51.0%) was higher than that for harvesting (39.0%) and planting (10.0%). The PM10 emissions at the county level were all higher by 30.5% than those at the high-resolution scale. After correction, the decreases of M2 (optimization of soil texture), M3 (optimization of soil texture and moisture), and M4 (optimization of soil texture, soil moisture, and wind speed) were 52.3%, 82.5%, and 89.6%, respectively. These results indicate the soil texture and moisture are the main factors for the decrease of emissions. The high-resolution inventory of emissions of PM10 due to farming practices and harvesting is helpful for assessing the impact of agricultural activities on regional air quality in China and providing a scientific basis for the development of pollution control measures in agriculture. [ABSTRACT FROM AUTHOR]