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https://doi.org/10.5194/egusphere-2024-1903
https://doi.org/10.5194/egusphere-2024-1903
22 Jul 2024
 | 22 Jul 2024

Identifying Missing Sources and Reducing NOx Emissions Uncertainty over China using Daily Satellite Data and a Mass-Conserving Method

Lingxiao Lu, Jason Blake Cohen, Kai Qin, Xiaolu Li, and Qin He

Abstract. This study applies a mass-conserving model-free analytical approach to daily observations on a grid-by-grid basis of NO2 from TROPOMI, to rapidly and flexibly quantify changing and emerging sources of NOx emissions at high spatial and daily temporal resolution. The inverted NOx emissions and optimized underlying ranges include quantification of the underlying atmospheric in-situ processing, transport and physics. The results are presented over three changing regions in China, including Shandong and Hubei which are rapidly urbanizing and not frequently addressed in the global literature. The day-to-day and grid-by-grid emissions are found to be 1.96±0.27 µg/m2/s on pixels with available priori values (1.94 µg/m2/s), while 1.22±0.63 µg/m2/s extra emissions are found on pixels in which the a priori inventory is lower than 0.3 µg/m2/s. Source attribution based on thermodynamics of combustion temperature, atmospheric transport, and in-situ atmospheric processing successfully identify 5 different industrial source types. Emissions from these industrial sites adjacent to the Yangtze River are found to be 160.5±68.9 Kton/yr (163 % higher than the a priori) consistent with missing light and medium industry located along the river, contradicting previous studies attributing the water as the source of NOx emissions. Finally, the results demonstrate those pixels with an uncertainty larger than day-to-day variability, providing quantitative information for placement of future monitoring stations. It is hoped that these findings will drive a new approach to top-down emissions estimates, in which emissions are quantified and updated continuously based consistently on remotely sensed measurements and associated uncertainties that actively reflect land-use changes and quantify misidentified emissions, while quantifying new datasets to inform the bottom-up emissions community.

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Journal article(s) based on this preprint

21 Feb 2025
Identifying missing sources and reducing NOx emissions uncertainty over China using daily satellite data and a mass-conserving method
Lingxiao Lu, Jason Blake Cohen, Kai Qin, Xiaolu Li, and Qin He
Atmos. Chem. Phys., 25, 2291–2309, https://doi.org/10.5194/acp-25-2291-2025,https://doi.org/10.5194/acp-25-2291-2025, 2025
Short summary
Lingxiao Lu, Jason Blake Cohen, Kai Qin, Xiaolu Li, and Qin He

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-1903', Anonymous Referee #1, 09 Aug 2024
  • RC2: 'Comment on egusphere-2024-1903', Anonymous Referee #2, 28 Aug 2024

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-1903', Anonymous Referee #1, 09 Aug 2024
  • RC2: 'Comment on egusphere-2024-1903', Anonymous Referee #2, 28 Aug 2024

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Jason Cohen on behalf of the Authors (28 Oct 2024)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (19 Nov 2024) by Carl Percival
RR by Anonymous Referee #2 (20 Nov 2024)
ED: Publish as is (03 Dec 2024) by Carl Percival
AR by Jason Cohen on behalf of the Authors (07 Dec 2024)  Manuscript 

Journal article(s) based on this preprint

21 Feb 2025
Identifying missing sources and reducing NOx emissions uncertainty over China using daily satellite data and a mass-conserving method
Lingxiao Lu, Jason Blake Cohen, Kai Qin, Xiaolu Li, and Qin He
Atmos. Chem. Phys., 25, 2291–2309, https://doi.org/10.5194/acp-25-2291-2025,https://doi.org/10.5194/acp-25-2291-2025, 2025
Short summary
Lingxiao Lu, Jason Blake Cohen, Kai Qin, Xiaolu Li, and Qin He
Lingxiao Lu, Jason Blake Cohen, Kai Qin, Xiaolu Li, and Qin He

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Latest update: 21 Feb 2025
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Short summary
This study assimilates NO2 observations from TROPOMI in a mass-conserving manner and inverts daily NOx emissions. The results are presented over rapidly changing regions in China. Attribution is quantified using local observations and inverted proxy of combustion temperature. There are significant sources identified in some areas which are not in existing databases, especially small and medium industries along the Yangtze River. We also demonstrate which emissions are robust and which are not.
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