Climatological study of the Boundary-layer air Stagnation Index  for China and its relationship with air pollution

Huang, Qianqian; Cai, Xuhui; Wang, Jian; Song, Yu; Zhu, Tong

doi:https://doi.org/10.5194/acp-18-7573-2018

Articles | Volume 18, issue 10

Atmos. Chem. Phys., 18, 7573–7593, 2018

https://doi.org/10.5194/acp-18-7573-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue: Regional transport and transformation of air pollution in...

Atmos. Chem. Phys., 18, 7573–7593, 2018

https://doi.org/10.5194/acp-18-7573-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 18, issue 10

Research article 31 May 2018

Research article | 31 May 2018

Climatological study of the Boundary-layer air Stagnation Index for China and its relationship with air pollution

Qianqian Huang et al.

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Final revised paper (published on 31 May 2018)
Supplement to the final revised paper
Preprint (discussion started on 08 Jan 2018)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'Comments', Anonymous Referee #1, 23 Jan 2018
- AC1: 'Response to Referees', Qianqian Huang, 16 May 2018
RC2: 'Review of: Climatological study of new air stagnation index (ASI) for China and its relationship with air pollution', Anonymous Referee #2, 04 Feb 2018
- AC2: 'Response to Referees', Qianqian Huang, 16 May 2018

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Qianqian Huang on behalf of the Authors (16 May 2018) Author's response Manuscript

ED: Publish as is (17 May 2018) by Zhanqing Li

Short summary

Air stagnation index is a vital meteorological measure of the atmosphere's ability to dilute air pollutants. We propose a Boundary-layer air Stagnation Index (BSI) based on daily maximal ventilation, real latent instability and precipitation. The BSI is positively correlated with API during 2000–2012, tracks the day-by-day variation of PM_2.5 concentration during January 2013 in Beijing well, and successfully represents the improved air quality during November and December in 2017.