How can we trust TROPOMI based methane emissions estimation: calculating emissions over unidentified source regions

Zheng, Bo; Cohen, Jason Blake; Lu, Lingxiao; Hu, Wei; Tiwari, Pravash; Lolli, Simone; Garzelli, Andrea; Su, Hui; Qin, Kai

doi:10.5194/acp-26-1931-2026

Articles | Volume 26, issue 3

https://doi.org/10.5194/acp-26-1931-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/acp-26-1931-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 26, issue 3

Research article

|

06 Feb 2026

Research article |

| 06 Feb 2026

How can we trust TROPOMI based methane emissions estimation: calculating emissions over unidentified source regions

Bo Zheng, Jason Blake Cohen, Lingxiao Lu, Wei Hu, Pravash Tiwari, Simone Lolli, Andrea Garzelli, Hui Su, and Kai Qin

Supplement

https://doi.org/10.5194/acp-26-1931-2026-supplement

Data sets

How can we trust TROPOMI based Methane Emissions Estimation: Calculating Emissions over Unidentified Source Regions B. Zheng et al. https://doi.org/10.6084/m9.figshare.30635951

ERA5 hourly data on pressure levels from 1940 to present H. Hersbach et al. https://doi.org/10.24381/cds.bd0915c6

MISR Level 3 Component Global Aerosol product in netCDF format covering a month V004 NASA/LARC/SD/ASDC https://doi.org/10.5067/Terra/MISR/MIL3MAEN_L3.004

How can we trust TROPOMI based Methane Emissions Estimation: Calculating Emissions over Unidentified Source Regions B. Zheng et al. https://doi.org/10.6084/m9.figshare.30635951

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Short summary

This study provides TROPOMI (TROPOspheric Monitoring Instrument) with a new methane emission estimation method that can accurately identify emission sources. Our results generate non-negative emission datasets using objective selection and filtering methods. The results include lower minimum emission thresholds for all power grids and fewer false positives. The new method provides more robust emission quantification in the face of data uncertainty, going beyond traditional plume identification and background subtraction.