Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 22, issue 18
Articles | Volume 22, issue 18
https://doi.org/10.5194/acp-22-11945-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-22-11945-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 22, issue 18
Research article
 | 
16 Sep 2022
Research article |  | 16 Sep 2022

Contributions of meteorology and anthropogenic emissions to the trends in winter PM2.5 in eastern China 2013–2018

Yanxing Wu, Run Liu, Yanzi Li, Junjie Dong, Zhijiong Huang, Junyu Zheng, and Shaw Chen Liu

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Short summary
Multiple linear regression (MLR) analyses often interpret the correlation coefficient (r2) as the contribution of an independent variable to the dependent variable. Since a good correlation does not imply a causal relationship, we propose that r2 should be interpreted as the maximum possible contribution. Moreover, MLR results are sensitive to the length of time analyzed; long-term analysis gives a more accurate assessment because of its additional constraints.
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