8 citations as recorded by crossref.

1. Using machine learning to quantify drivers of aerosol pollution trend in China from 2015 to 2022 Y. Ji et al. 10.1016/j.apgeochem.2023.105614
2. Statistical analysis and environmental impact of pre-existing particle growth events in a Northern Chinese coastal megacity: A 725-day study in 2010–2018 X. Wei et al. 10.1016/j.scitotenv.2024.173227
3. Long-term hourly air quality data bridging of neighboring sites using automated machine learning: A case study in the Greater Bay area of China B. Wu et al. 10.1016/j.atmosenv.2024.120347
4. Identifying decadal trends in deweathered concentrations of criteria air pollutants in Canadian urban atmospheres with machine learning approaches X. Yao & L. Zhang 10.5194/acp-24-7773-2024
5. Achievements and challenges in improving air quality in China: Analysis of the long-term trends from 2014 to 2022 H. Zheng et al. 10.1016/j.envint.2023.108361
6. An intercomparison of weather normalization of PM2.5 concentration using traditional statistical methods, machine learning, and chemistry transport models H. Zheng et al. 10.1038/s41612-023-00536-7
7. Seasonally Dependent Daytime and Nighttime Formation of Oxalic Acid Vapor and Particulate Oxalate in Tropical Coastal and Marine Atmospheres L. Yan et al. 10.3390/atmos16010098
8. Associations of interannual variation in summer tropospheric ozone with the Western Pacific Subtropical High in China from 1999 to 2017 X. Zhang et al. 10.5194/acp-23-15629-2023