Articles | Volume 19, issue 17
Atmos. Chem. Phys., 19, 11303–11314, 2019
https://doi.org/10.5194/acp-19-11303-2019

Special issue: In-depth study of air pollution sources and processes within...

Atmos. Chem. Phys., 19, 11303–11314, 2019
https://doi.org/10.5194/acp-19-11303-2019

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 et al.

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AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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AR: Author's response | RR: Referee report | ED: Editor decision
AR by Zongbo Shi on behalf of the Authors (10 Jun 2019)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (17 Jun 2019) by James Allan
RR by Anonymous Referee #1 (19 Jun 2019)
RR by Anonymous Referee #2 (24 Jul 2019)
ED: Publish as is (24 Jul 2019) by James Allan
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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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