Articles | Volume 25, issue 11
https://doi.org/10.5194/acp-25-5837-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-25-5837-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Surface-observation-constrained high-frequency coal mine methane emissions in Shanxi, China, reveal more emissions than inventories, consistent with satellite inversion
Fan Lu
Jiangsu Key Laboratory of Coal-Based Greenhouse Gas Control and Utilization, School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, China
Jiangsu Key Laboratory of Coal-Based Greenhouse Gas Control and Utilization, School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, China
Jiangsu Key Laboratory of Coal-Based Greenhouse Gas Control and Utilization, School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, China
Jiangsu Key Laboratory of Coal-Based Greenhouse Gas Control and Utilization, School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, China
Pravash Tiwari
Jiangsu Key Laboratory of Coal-Based Greenhouse Gas Control and Utilization, School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, China
Jiangsu Key Laboratory of Coal-Based Greenhouse Gas Control and Utilization, School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, China
Chang Ye
Jiangsu Key Laboratory of Coal-Based Greenhouse Gas Control and Utilization, School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, China
Yanan Shan
Jiangsu Key Laboratory of Coal-Based Greenhouse Gas Control and Utilization, School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, China
Qing Xu
Jiangsu Key Laboratory of Coal-Based Greenhouse Gas Control and Utilization, School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, China
Shuo Wang
Jiangsu Key Laboratory of Coal-Based Greenhouse Gas Control and Utilization, School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, China
Qiansi Tu
School of Mechanical Engineering, Tongji University, Shanghai, China
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Cited
9 citations as recorded by crossref.
- Attributing GHG emissions to individual facilities using multi-temporal hyperspectral images: Methodology and applications Y. Zhang et al. https://doi.org/10.1016/j.isprsjprs.2026.01.014
- Application of CH4 monitoring technology based on UAV platform in Shengli Oilfield H. He et al. https://doi.org/10.3389/fenvs.2026.1746916
- Carbon emission reduction requires attention to the contribution of natural gas use: Combustion and leakage H. Chen et al. https://doi.org/10.5194/acp-26-1359-2026
- Two decades of methane budgets at the sub-national scale in China P. Zhao et al. https://doi.org/10.1016/j.scib.2026.06.019
- Improving estimation of surface PM2.5 by including satellite observations of gases, aerosols, and radiation in tandem J. Kang et al. https://doi.org/10.1088/1748-9326/ae1e17
- Evaluation of satellite-derived methane emissions from coal mines using the Gaussian plume model in a topographically complex area Y. Gao et al. https://doi.org/10.1016/j.atmosenv.2026.122004
- Satellite-Derived Approaches for Coal Mine Methane Estimation: A Review A. Chauhan & S. Raval https://doi.org/10.3390/rs17213652
- In-tandem multi-waveband particulate absorption and size observations yield substantial changes in radiative forcing over industrial Central China L. Guan et al. https://doi.org/10.5194/acp-26-3107-2026
- An Intercomparison of Underground Coal Mine Methane Emission Estimation in Shanxi, China: S5P/TROPOMI vs. GF-5B/AHSI Z. Yang et al. https://doi.org/10.3390/rs18040603
9 citations as recorded by crossref.
- Attributing GHG emissions to individual facilities using multi-temporal hyperspectral images: Methodology and applications Y. Zhang et al. https://doi.org/10.1016/j.isprsjprs.2026.01.014
- Application of CH4 monitoring technology based on UAV platform in Shengli Oilfield H. He et al. https://doi.org/10.3389/fenvs.2026.1746916
- Carbon emission reduction requires attention to the contribution of natural gas use: Combustion and leakage H. Chen et al. https://doi.org/10.5194/acp-26-1359-2026
- Two decades of methane budgets at the sub-national scale in China P. Zhao et al. https://doi.org/10.1016/j.scib.2026.06.019
- Improving estimation of surface PM2.5 by including satellite observations of gases, aerosols, and radiation in tandem J. Kang et al. https://doi.org/10.1088/1748-9326/ae1e17
- Evaluation of satellite-derived methane emissions from coal mines using the Gaussian plume model in a topographically complex area Y. Gao et al. https://doi.org/10.1016/j.atmosenv.2026.122004
- Satellite-Derived Approaches for Coal Mine Methane Estimation: A Review A. Chauhan & S. Raval https://doi.org/10.3390/rs17213652
- In-tandem multi-waveband particulate absorption and size observations yield substantial changes in radiative forcing over industrial Central China L. Guan et al. https://doi.org/10.5194/acp-26-3107-2026
- An Intercomparison of Underground Coal Mine Methane Emission Estimation in Shanxi, China: S5P/TROPOMI vs. GF-5B/AHSI Z. Yang et al. https://doi.org/10.3390/rs18040603
Saved (final revised paper)
Latest update: 23 Jun 2026
Short summary
This work describes a field campaign and new fast emissions estimation approach to attribute methane from a large known and previously unknown coal mine in Shanxi, China. The emissions computed are shown to be larger than known oil and gas sources, indicating that methane from coal mines may play a larger role in the global methane budget. The results are found to be slightly larger than or similar to satellite observational campaigns over the same region.
This work describes a field campaign and new fast emissions estimation approach to attribute...
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