Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 19, issue 17
Articles | Volume 19, issue 17
https://doi.org/10.5194/acp-19-11303-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/acp-19-11303-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 19, issue 17
Research article
 | 
06 Sep 2019
Research article |  | 06 Sep 2019

Assessing the impact of clean air action on air quality trends in Beijing using a machine learning technique

Tuan V. Vu, Zongbo Shi, Jing Cheng, Qiang Zhang, Kebin He, Shuxiao Wang, and Roy M. Harrison

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Short summary
A 5-year Clean Air Action Plan was implemented in 2013 to improve ambient air quality in Beijing. Here, we applied a novel machine-learning-based model to determine the real trend in air quality from 2013 to 2017 in Beijing to assess the efficacy of the plan. We showed that the action plan led to a major reduction in primary emissions and significant improvement in air quality. The marked decrease in PM2.5 and SO2 is largely attributable to a reduction in coal combustion.
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