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


Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

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
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.
Final-revised paper