Modeling study of impacts on surface ozone of regional transport and emissions reductions over North China Plain in summer 2015

Han, Xiao; Zhu, Lingyun; Wang, Shulan; Meng, Xiaoyan; Zhang, Meigen; Hu, Jun

doi:https://doi.org/10.5194/acp-18-12207-2018

Articles | Volume 18, issue 16

https://doi.org/10.5194/acp-18-12207-2018

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

https://doi.org/10.5194/acp-18-12207-2018

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

Articles | Volume 18, issue 16

Research article

|

23 Aug 2018

Research article |

| 23 Aug 2018

Modeling study of impacts on surface ozone of regional transport and emissions reductions over North China Plain in summer 2015

Xiao Han, Lingyun Zhu, Shulan Wang, Xiaoyan Meng, Meigen Zhang, and Jun Hu

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Final revised paper (published on 23 Aug 2018)
Preprint (discussion started on 04 May 2018)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'referee comment', Anonymous Referee #2, 21 May 2018
- AC1: 'Response to RC1', Meigen Zhang, 29 Jun 2018
RC2: 'review on Han et al.', Anonymous Referee #1, 02 Jun 2018
- AC2: 'Response to RC2', Meigen Zhang, 29 Jun 2018

Peer-review completion

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

AR by Meigen Zhang on behalf of the Authors (19 Jul 2018) Author's response Manuscript

ED: Publish as is (29 Jul 2018) by Stefano Galmarini

AR by Meigen Zhang on behalf of the Authors (04 Aug 2018) Manuscript

Short summary

In this paper, we applied an air quality modeling system called RAMS-CMAQ coupled with the ISAM module to investigate the regional contributions of O₃ among major regions of the NCP and to quantify the relative amount of O₃ originating from specific VOC and NO_x emissions sources. The modeling system allows us to capture valuable information regarding how to choose the correct sequence and efficient combinations by exploring the key thresholds from the bulk of sensitivity tests.