Model bias in simulating major chemical components of PM<sub>2.5</sub> in China

Miao, Ruqian; Chen, Qi; Zheng, Yan; Cheng, Xi; Sun, Yele; Palmer, Paul I.; Shrivastava, Manish; Guo, Jianping; Zhang, Qiang; Liu, Yuhan; Tan, Zhaofeng; Ma, Xuefei; Chen, Shiyi; Zeng, Limin; Lu, Keding; Zhang, Yuanhang

doi:https://doi.org/10.5194/acp-20-12265-2020

Articles | Volume 20, issue 20

https://doi.org/10.5194/acp-20-12265-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/acp-20-12265-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 20, issue 20

Research article

|

28 Oct 2020

Research article |

| 28 Oct 2020

Model bias in simulating major chemical components of PM_2.5 in China

Ruqian Miao, Qi Chen, Yan Zheng, Xi Cheng, Yele Sun, Paul I. Palmer, Manish Shrivastava, Jianping Guo, Qiang Zhang, Yuhan Liu, Zhaofeng Tan, Xuefei Ma, Shiyi Chen, Limin Zeng, Keding Lu, and Yuanhang Zhang

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Final revised paper (published on 28 Oct 2020)
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Preprint (discussion started on 04 May 2020)
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Status: closed

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

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RC1: 'Review of Miao et al', Anonymous Referee #1, 01 Jun 2020
- AC1: 'Response to Referee #1', Qi Chen, 18 Aug 2020
RC2: 'Referee comment', Anonymous Referee #2, 06 Jul 2020
- AC2: 'Response to Referee #2', Qi Chen, 18 Aug 2020

Peer-review completion

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

AR by Qi Chen on behalf of the Authors (19 Aug 2020) Author's response Manuscript

ED: Publish as is (15 Sep 2020) by Kostas Tsigaridis

AR by Qi Chen on behalf of the Authors (18 Sep 2020) Manuscript

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Short summary

In this study we evaluated the model performances for simulating secondary inorganic aerosol (SIA) and organic aerosol (OA) in PM_2.5 in China against comprehensive datasets. The potential biases from factors related to meteorology, emission, chemistry, and atmospheric removal are systematically investigated. This study provides a comprehensive understanding of modeling PM_2.5, which is important for studies on the effectiveness of emission control strategies.

Model bias in simulating major chemical components of PM2.5 in China

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Interactive discussion

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Model bias in simulating major chemical components of PM_2.5 in China