9 citations as recorded by crossref.

1. Divergent Ozone Predictions in China Under Carbon Neutrality: Why Chemical Mechanisms Disagree X. Weng et al. https://doi.org/10.1021/acs.est.5c10697
2. China’s air pollution: Remarkable progress and ongoing challenges under new standards from combined surface-satellite observations (2015–2024) Y. Chen et al. https://doi.org/10.1016/j.jhazmat.2026.142461
3. What Drives the Spatiotemporal Characteristics and Evolution of Near-Surface Ozone Across Multiple Scales? Implications for Sustainable Air Quality Management in Coastal Southeast China Y. Wu et al. https://doi.org/10.3390/su18136842
4. Surface Ozone Increases over Northwest China Linked to North Pacific SST-Driven Warming Y. Han et al. https://doi.org/10.3390/rs18111800
5. Attribution of Black Carbon Variability in China (2000–2019) from a Perspective of Machine Learning R. Fan et al. https://doi.org/10.3390/atmos16121378
6. Spatiotemporal characteristics and meteorological drivers of background ozone in China's Pearl River Delta region X. Liu et al. https://doi.org/10.1016/j.apr.2025.102868
7. Decoding ozone pollution in Beijing-Tianjin-Hebei: A machine learning approach to disentangling meteorological and anthropogenic drivers X. Liu et al. https://doi.org/10.1016/j.aeaoa.2026.100460
8. Impact of tropospheric ozone-radiation interactions on summer ozone air quality over eastern China during 2010–2019 Y. Guan et al. https://doi.org/10.1016/j.atmosres.2026.108817
9. Machine learning estimation of surface ozone using Sentinel-5P data and meteorological and ground observations A. Sam-Khaniani et al. https://doi.org/10.1016/j.asr.2026.04.089