Inverse modeling of SO2 and NOx emissions over China using multisensor satellite data – Part 1: Formulation and sensitivity analysis

Wang, Yi; Wang, Jun; Xu, Xiaoguang; Henze, Daven K.; Qu, Zhen; Yang, Kai

doi:https://doi.org/10.5194/acp-20-6631-2020

Articles | Volume 20, issue 11

https://doi.org/10.5194/acp-20-6631-2020

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

https://doi.org/10.5194/acp-20-6631-2020

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

Articles | Volume 20, issue 11

Research article

|

05 Jun 2020

Research article |

| 05 Jun 2020

Inverse modeling of SO₂ and NO_x emissions over China using multisensor satellite data – Part 1: Formulation and sensitivity analysis

Yi Wang, Jun Wang, Xiaoguang Xu, Daven K. Henze, Zhen Qu, and Kai Yang

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Final revised paper (published on 05 Jun 2020)
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Preprint (discussion started on 12 Nov 2019)
Supplement to the preprint

Interactive discussion

Status: closed

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

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RC1: 'acp-2019-879 review', Anonymous Referee #1, 11 Dec 2019
- AC1: 'Replies', Jun Wang, 14 Mar 2020
RC2: 'Review', Anonymous Referee #2, 01 Jan 2020
- AC2: 'Replies', Jun Wang, 14 Mar 2020

Peer-review completion

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

AR by Anna Wenzel on behalf of the Authors (23 Mar 2020) Author's response

ED: Referee Nomination & Report Request started (24 Mar 2020) by Leiming Zhang

RR by Anonymous Referee #1 (12 Apr 2020)

ED: Publish subject to technical corrections (14 Apr 2020) by Leiming Zhang

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Short summary

The use of OMPS satellite observations to inverse-model SO₂ and NO₂ emissions is presented through the GEOS-Chem adjoint modeling framework. The work is illustrated over China. The robustness of the results is studied through separate and joint inversions of SO₂ and NO₂ and the consideration of NH₃ uncertainty. Independent validation is performed with OMI SO₂ and NO₂ data. It is shown that simultaneous inversion of NO₂ and SO2 from OMPS provides an effective way to rapidly update emissions.