Articles | Volume 25, issue 21
https://doi.org/10.5194/acp-25-15487-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-25-15487-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Nov 2025
Research article |
| 13 Nov 2025
| 13 Nov 2025
Urban-rural patterns and driving factors of particulate matter pollution decrease in eastern China
Zhihao Song
College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China
Institute of Meteorological Artificial Intelligence Research, Lanzhou University, Lanzhou 730000, China
Bin Chen
CORRESPONDING AUTHOR
College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China
Institute of Meteorological Artificial Intelligence Research, Lanzhou University, Lanzhou 730000, China
Related authors
Zhihao Song, Bin Chen, Yue Huang, Li Dong, and Tingting Yang
Atmos. Meas. Tech., 14, 5333–5347, https://doi.org/10.5194/amt-14-5333-2021, https://doi.org/10.5194/amt-14-5333-2021, 2021
Short summary
Short summary
The linear hybrid machine learning model achieves the expected target well. The overall inversion accuracy (R2) of the model is 0.84, and the RMSE is 12.92 µg m−3. R2 was above 0.7 in more than 70 % of the sites, whereas RMSE and mean absolute error were below 20 and 15 µg m−3, respectively. There was severe pollution in winter with an average PM2.5 concentration of 62.10 µg m−3. However, there was only slight pollution in summer with an average PM2.5 concentration of 47.39 µg m−3.
Zhihao Song, Bin Chen, Yue Huang, Li Dong, and Tingting Yang
Atmos. Meas. Tech., 14, 5333–5347, https://doi.org/10.5194/amt-14-5333-2021, https://doi.org/10.5194/amt-14-5333-2021, 2021
Short summary
Short summary
The linear hybrid machine learning model achieves the expected target well. The overall inversion accuracy (R2) of the model is 0.84, and the RMSE is 12.92 µg m−3. R2 was above 0.7 in more than 70 % of the sites, whereas RMSE and mean absolute error were below 20 and 15 µg m−3, respectively. There was severe pollution in winter with an average PM2.5 concentration of 62.10 µg m−3. However, there was only slight pollution in summer with an average PM2.5 concentration of 47.39 µg m−3.
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Short summary
This study reveals that 2015–2023 particulate matter (PM) pollution in eastern China declined faster in urban than rural areas. Temperature and interannual variability were key drivers, with urban reductions concentrated in urban core zones and suburbs. The effect of interannual variability on PM decreased significantly, while other factors showed periodic fluctuations.
This study reveals that 2015–2023 particulate matter (PM) pollution in eastern China declined...
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