33 citations as recorded by crossref.

1. Research on Ozone Pollution Characteristics and Source Apportionment During the COVID-19 Lockdown in Jilin City in 2022 C. Fang et al. https://doi.org/10.3390/atmos15111324
2. Assessing the co-benefits of reductions in mobile-source CO2 and pollutant emissions for urban air quality and public health C. Li et al. https://doi.org/10.1016/j.ecoenv.2025.119569
3. PM2.5 accumulation mechanism and health risks in basin-type cities: a case study of Linfen, China J. Tang et al. https://doi.org/10.1007/s10661-026-15337-7
4. Assessing the effectiveness of PM2.5 pollution control from the perspective of interprovincial transport and PM2.5 mitigation costs across China Y. Wang et al. https://doi.org/10.1016/j.ese.2024.100448
5. Characterization and Atmospheric Drivers of Nocturnal Ozone Enhancement in Putian City, China C. Fang et al. https://doi.org/10.3390/atmos16010045
6. Industrial Condensable Particulate Matter: A Missing Source in PM2.5 Source Apportionment Driving Winter Pollution in China Y. Su et al. https://doi.org/10.1021/acs.est.6c02727
7. Dynamic assessment of NO2 plume rise and pollution contributions from steel industry point sources in an energy-intensive region of China C. Gao et al. https://doi.org/10.1016/j.apr.2026.102921
8. Quantifying the Impact of Fertilizer-Induced Reactive Nitrogen Emissions on Surface Ozone Formation in China: Insights from FEST-C* and CMAQ Simulations M. Zhang et al. https://doi.org/10.3390/agriculture15060612
9. Source apportionment and process analysis of a typical summer ozone episode in Linyi, China, using WRF-CMAQ J. Wang et al. https://doi.org/10.1016/j.apr.2026.103090
10. Analysis of the Causes of an O3 Pollution Event in Suqian on 18–21 June 2020 Based on the WRF-CMAQ Model J. Wang et al. https://doi.org/10.3390/atmos15070831
11. Quantitative source apportionment of surface ozone in Liaoning Province, China, under the Asian summer monsoon background N. Liu et al. https://doi.org/10.1016/j.apr.2025.102540
12. A New Framework for Medium- to Long-Term PM2.5 Predictions Using AI-Based High-Resolution Meteorological Forecasts H. Gu et al. https://doi.org/10.1021/cbe.5c00074
13. Influence of weather patterns on ground-level ozone pollution: a 2023 summer case study in Jilin City with health risk assessment A. Akhtar et al. https://doi.org/10.1007/s10661-026-15520-w
14. The reward and penalty for ozone pollution control caused by natural sources and regional transport: A case study in Guangdong province R. Wang et al. https://doi.org/10.1016/j.scitotenv.2024.174984
15. Intercomparison of multiple two-way coupled meteorology and air quality models (WRF v4.1.1–CMAQ v5.3.1, WRF–Chem v4.1.1, and WRF v3.7.1–CHIMERE v2020r1) in eastern China C. Gao et al. https://doi.org/10.5194/gmd-17-2471-2024
16. MEIAT-CMAQ: A modular emission inventory allocation tool for Community Multiscale Air Quality Model H. Wang et al. https://doi.org/10.1016/j.atmosenv.2024.120604
17. Impact of Meteorological Conditions on PM2.5 Pollution in Changchun and Associated Health Risks Analysis C. Fang et al. https://doi.org/10.3390/atmos15050616
18. Air quality and health benefits for different heating decarbonization pathways in China K. Liu et al. https://doi.org/10.1016/j.scitotenv.2024.170976
19. Research on the urban-rural differences in ozone concentration contributed by biogenic emissions under the influence of anthropogenic emission reduction W. Zhang et al. https://doi.org/10.1016/j.uclim.2026.103090
20. Gridemis V2.0: A highly integrated algorithm scheme for high-resolution and multi-component allocation of emission inventories used in air quality models C. Wang et al. https://doi.org/10.1016/j.envsoft.2025.106416
21. Source apportionment and formation of warm season ozone pollution in Chengdu based on CMAQ-ISAM Y. Xian et al. https://doi.org/10.1016/j.uclim.2024.102017
22. Characterization of winter PM2.5 source contributions and impacts of meteorological conditions and anthropogenic emission changes in the Sichuan Basin, 2002–2020 Y. Xian et al. https://doi.org/10.1016/j.scitotenv.2024.174557
23. An iteratively optimized downscaling method for city-scale air quality forecast emission inventory establishment C. Lu et al. https://doi.org/10.1016/j.scitotenv.2024.176824
24. Application of regional meteorology and air quality models based on the microprocessor without interlocked piped stages (MIPS) and LoongArch CPU platforms Z. Bai et al. https://doi.org/10.5194/gmd-17-4383-2024
25. Vertical Distribution of Sources and Atmospheric Impacts of HONO in the North China Plain H. Xuan et al. https://doi.org/10.1021/acs.est.5c01801
26. Effects of agricultural sources on air quality in Lahore, Pakistan, based on CMAQ simulation A. Abbasi et al. https://doi.org/10.1007/s11356-025-37010-1
27. Source Attribution Analysis of an Ozone Concentration Increase Event in the Main Urban Area of Xi’an Using the WRF-CMAQ Model J. Wang et al. https://doi.org/10.3390/atmos15101208
28. Model Intercomparisons of MEGAN and BEIS: Synergistic Impacts of Biogenic VOCs and Soil NO Emissions on Summer Ozone and Secondary Organic Aerosol Formation in China C. Gao et al. https://doi.org/10.1021/acsestair.5c00038
29. An integrated modeling framework for PM2.5 source apportionment in the Yangtze River Delta using WRF-CMAQ and ISAM Q. Li et al. https://doi.org/10.1016/j.apr.2025.102637
30. Attribution of a typical ozone pollution episode in Handan: WRF-CMAQ modeling and process analysis based on a local emission inventory C. Fang et al. https://doi.org/10.1016/j.apr.2025.102862
31. Fast optimization of the emission reduction pathways of major air pollutants in China: From the perspective of different decision preferences Y. Wang et al. https://doi.org/10.1016/j.envint.2025.109282
32. BVOCs' role in dynamic shifts of summer ozone formation regimes across China and policy implications C. Gao et al. https://doi.org/10.1016/j.jenvman.2025.124150
33. Spatiotemporal characteristics of ozone and PM2.5 pollution in Jilin City: insights from observations in 2020 and 2023 A. Akhtar et al. https://doi.org/10.1007/s10661-026-15929-3