Articles | Volume 24, issue 8
https://doi.org/10.5194/acp-24-4875-2024
© Author(s) 2024. 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-24-4875-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
25 Apr 2024
Research article |
| 25 Apr 2024
| 25 Apr 2024
Quantifying CH4 emissions from coal mine aggregation areas in Shanxi, China, using TROPOMI observations and the wind-assigned anomaly method
School of Mechanical Engineering, Tongji University, Shanghai, China
Frank Hase
Institute of Meteorology and Climate Research (IMK-ASF), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, China
Jason Blake Cohen
School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, China
Farahnaz Khosrawi
Jülich Supercomputing Centre (JSC), Forschungszentrum Jülich GmbH, Jülich, Germany
Xinrui Zou
School of Mechanical Engineering, Tongji University, Shanghai, China
Matthias Schneider
School of Mechanical Engineering, Tongji University, Shanghai, China
Fan Lu
School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, China
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Cited
18 citations as recorded by crossref.
- Assessing Methane Emission Patterns and Sensitivities at High-Emission Point Sources in China via Gaussian Plume Modeling H. Li et al. https://doi.org/10.3390/environments13010062
- Coal mine methane mitigation in China toward carbon neutrality: Characteristics, potential, and driving mechanisms Y. Sun et al. https://doi.org/10.1016/j.eiar.2026.108508
- COCCON Measurements of XCO2, XCH4 and XCO over Coal Mine Aggregation Areas in Shanxi, China, and Comparison to TROPOMI and CAMS Datasets Q. Tu et al. https://doi.org/10.3390/rs16214022
- Unveiling nitrogen oxide emissions from open-pit copper mines through satellite observations I. Ialongo et al. https://doi.org/10.1088/1748-9326/adb767
- Satellite-Based Emission Inversion for Air Pollutants and Greenhouse Gases: A Review Z. Jiang et al. https://doi.org/10.1007/s13351-025-4914-7
- Quantifying the Impact of Environmental Factors on the Methane Point-Source Emission Algorithm Z. Wang et al. https://doi.org/10.3390/rs17050799
- High-resolution regional inversion reveals overestimation of anthropogenic methane emissions in China S. Feng et al. https://doi.org/10.5194/acp-25-15121-2025
- Industrial Mineral Perspectives on Coal: Econometric Evidence of Extraction, Utilization, and Environmental Impacts on Global Coal-Producing Nations M. Mohsin & S. Naseem https://doi.org/10.1007/s42461-026-01486-3
- Enhancing the Detection of Potential Anthropogenic Methane Emission Sources in China Using Machine Learning and TROPOMI Observations S. Yu et al. https://doi.org/10.1021/acs.estlett.6c00115
- Satellite-Based Estimation of Urban CO2 Emissions in Shandong Province, China, Using TROPOMI NO2 Observations and Differential Evolution Algorithm Y. Xie et al. https://doi.org/10.3390/rs18101470
- Novel lightweight based coal mine methane emission framework exhibits transferability between observations in Poland and Shanxi B. Zheng et al. https://doi.org/10.1088/2515-7620/ae67e9
- 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
- Quantifying methane emissions from large coal mine using Sentinel-5 Precursor satellite data and Gaussian plume model Y. Chen et al. https://doi.org/10.1016/j.jag.2026.105491
- A comprehensive inventory of China's methane emissions: Insights and changes from 2010 to 2020 Y. Shi et al. https://doi.org/10.1016/j.jclepro.2025.146089
- 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
- Analysis of Carbon Emission Drivers and Climate Mitigation Pathways in the Energy Industry: Evidence from Shanxi, China C. Ning et al. https://doi.org/10.3390/atmos16080986
- Satellite-Derived Approaches for Coal Mine Methane Estimation: A Review A. Chauhan & S. Raval https://doi.org/10.3390/rs17213652
- Emission characteristics of greenhouse gases and air pollutants in a Qinghai-Tibetan Plateau city using a portable Fourier transform spectrometer and TROPOMI observations Q. Tu et al. https://doi.org/10.5194/acp-25-17779-2025
18 citations as recorded by crossref.
- Assessing Methane Emission Patterns and Sensitivities at High-Emission Point Sources in China via Gaussian Plume Modeling H. Li et al. https://doi.org/10.3390/environments13010062
- Coal mine methane mitigation in China toward carbon neutrality: Characteristics, potential, and driving mechanisms Y. Sun et al. https://doi.org/10.1016/j.eiar.2026.108508
- COCCON Measurements of XCO2, XCH4 and XCO over Coal Mine Aggregation Areas in Shanxi, China, and Comparison to TROPOMI and CAMS Datasets Q. Tu et al. https://doi.org/10.3390/rs16214022
- Unveiling nitrogen oxide emissions from open-pit copper mines through satellite observations I. Ialongo et al. https://doi.org/10.1088/1748-9326/adb767
- Satellite-Based Emission Inversion for Air Pollutants and Greenhouse Gases: A Review Z. Jiang et al. https://doi.org/10.1007/s13351-025-4914-7
- Quantifying the Impact of Environmental Factors on the Methane Point-Source Emission Algorithm Z. Wang et al. https://doi.org/10.3390/rs17050799
- High-resolution regional inversion reveals overestimation of anthropogenic methane emissions in China S. Feng et al. https://doi.org/10.5194/acp-25-15121-2025
- Industrial Mineral Perspectives on Coal: Econometric Evidence of Extraction, Utilization, and Environmental Impacts on Global Coal-Producing Nations M. Mohsin & S. Naseem https://doi.org/10.1007/s42461-026-01486-3
- Enhancing the Detection of Potential Anthropogenic Methane Emission Sources in China Using Machine Learning and TROPOMI Observations S. Yu et al. https://doi.org/10.1021/acs.estlett.6c00115
- Satellite-Based Estimation of Urban CO2 Emissions in Shandong Province, China, Using TROPOMI NO2 Observations and Differential Evolution Algorithm Y. Xie et al. https://doi.org/10.3390/rs18101470
- Novel lightweight based coal mine methane emission framework exhibits transferability between observations in Poland and Shanxi B. Zheng et al. https://doi.org/10.1088/2515-7620/ae67e9
- 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
- Quantifying methane emissions from large coal mine using Sentinel-5 Precursor satellite data and Gaussian plume model Y. Chen et al. https://doi.org/10.1016/j.jag.2026.105491
- A comprehensive inventory of China's methane emissions: Insights and changes from 2010 to 2020 Y. Shi et al. https://doi.org/10.1016/j.jclepro.2025.146089
- 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
- Analysis of Carbon Emission Drivers and Climate Mitigation Pathways in the Energy Industry: Evidence from Shanxi, China C. Ning et al. https://doi.org/10.3390/atmos16080986
- Satellite-Derived Approaches for Coal Mine Methane Estimation: A Review A. Chauhan & S. Raval https://doi.org/10.3390/rs17213652
- Emission characteristics of greenhouse gases and air pollutants in a Qinghai-Tibetan Plateau city using a portable Fourier transform spectrometer and TROPOMI observations Q. Tu et al. https://doi.org/10.5194/acp-25-17779-2025
Saved (final revised paper)
Latest update: 27 Jul 2026
Short summary
Four-year satellite observations of XCH4 are used to derive CH4 emissions in three regions of China’s coal-rich Shanxi province. The wind-assigned anomalies for two opposite wind directions are calculated, and the estimated emission rates are comparable to the current bottom-up inventory but lower than the CAMS and EDGAR inventories. This research enhances the understanding of emissions in Shanxi and supports climate mitigation strategies by validating emission inventories.
Four-year satellite observations of XCH4 are used to derive CH4 emissions in three regions of...
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