Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 14, issue 8
Articles | Volume 14, issue 8
https://doi.org/10.5194/amt-14-5333-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-14-5333-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 14, issue 8
Research article
 | 
04 Aug 2021
Research article |  | 04 Aug 2021

Estimation of PM2.5 concentration in China using linear hybrid machine learning model

Zhihao Song, Bin Chen, Yue Huang, Li Dong, and Tingting Yang

Viewed

Total article views: 4,852 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
3,111 1,615 126 4,852 118 154
  • HTML: 3,111
  • PDF: 1,615
  • XML: 126
  • Total: 4,852
  • BibTeX: 118
  • EndNote: 154
Views and downloads (calculated since 30 Mar 2021)
Cumulative views and downloads (calculated since 30 Mar 2021)

Viewed (geographical distribution)

Total article views: 4,852 (including HTML, PDF, and XML) Thereof 4,686 with geography defined and 166 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 07 Apr 2026
Download
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.
Read more
Share