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

Download

Final revised paper (published on 05 Jun 2020)
Supplement to the final revised paper
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

- Printer-friendly version

- Supplement

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 Jun Wang on behalf of the Authors (14 Mar 2020) Manuscript

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

AR by Jun Wang on behalf of the Authors (15 Apr 2020) Manuscript

Download

Article (14552 KB)
Full-text XML

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.