Articles | Volume 24, issue 5
https://doi.org/10.5194/acp-24-3009-2024
© 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-24-3009-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Mar 2024
Research article |
| 08 Mar 2024
| 08 Mar 2024
Individual coal mine methane emissions constrained by eddy covariance measurements: low bias and missing sources
Jiangsu Key Laboratory of Coal-Based Greenhouse Gas Control and Utilization, School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, 221116, 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, 221116, 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, 221116, China
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, 221116, China
Jason Blake Cohen
CORRESPONDING AUTHOR
Jiangsu Key Laboratory of Coal-Based Greenhouse Gas Control and Utilization, School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, 221116, China
Viewed
Total article views: 6,552 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 06 Jul 2023)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 4,456 | 1,919 | 177 | 6,552 | 453 | 210 | 312 |
- HTML: 4,456
- PDF: 1,919
- XML: 177
- Total: 6,552
- Supplement: 453
- BibTeX: 210
- EndNote: 312
Total article views: 3,833 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 08 Mar 2024)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 3,011 | 720 | 102 | 3,833 | 192 | 115 | 142 |
- HTML: 3,011
- PDF: 720
- XML: 102
- Total: 3,833
- Supplement: 192
- BibTeX: 115
- EndNote: 142
Total article views: 2,719 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 06 Jul 2023)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 1,445 | 1,199 | 75 | 2,719 | 261 | 95 | 170 |
- HTML: 1,445
- PDF: 1,199
- XML: 75
- Total: 2,719
- Supplement: 261
- BibTeX: 95
- EndNote: 170
Viewed (geographical distribution)
Total article views: 6,552 (including HTML, PDF, and XML)
Thereof 6,472 with geography defined
and 80 with unknown origin.
Total article views: 3,833 (including HTML, PDF, and XML)
Thereof 3,784 with geography defined
and 49 with unknown origin.
Total article views: 2,719 (including HTML, PDF, and XML)
Thereof 2,688 with geography defined
and 31 with unknown origin.
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
Cited
19 citations as recorded by crossref.
- 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
- Satellite-Derived Approaches for Coal Mine Methane Estimation: A Review A. Chauhan & S. Raval https://doi.org/10.3390/rs17213652
- 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
- European Climate Policy in the Context of the Problem of Methane Emissions from Coal Mines in Poland B. Gajdzik et al. https://doi.org/10.3390/en17102396
- 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
- High-Resolution Satellite Reveals the Methane Emissions from China’s Coal Mines X. Li et al. https://doi.org/10.3390/rs17020220
- Remote Sensing Enables Basin-Scale Inventories of Coal Mine Methane E. Penn et al. https://doi.org/10.1021/acs.est.5c14976
- Satellite Insights into methane Super-Emitters: Regional emissions and yearly growth on Turkmenistan’s west coast Z. He et al. https://doi.org/10.1016/j.jag.2025.104975
- 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
- Revising the coal mining CH4 emission factor based on multiple inventories and atmospheric inversion approach at one of the world's largest coal production areas: Shanxi province, China X. Shi et al. https://doi.org/10.1016/j.scitotenv.2025.178616
- Mitigating climate change by abating coal mine methane: A critical review of status and opportunities C. Karacan et al. https://doi.org/10.1016/j.coal.2024.104623
- Evaluation of coal mine methane inventory methods using aircraft-based approaches in the Bowen Basin, Australia S. Harris et al. https://doi.org/10.5194/acp-26-10043-2026
- Surface-observation-constrained high-frequency coal mine methane emissions in Shanxi, China, reveal more emissions than inventories, consistent with satellite inversion F. Lu et al. https://doi.org/10.5194/acp-25-5837-2025
- Analysis of Methane (CH4) Distribution in Northeast Asia Based on Satellite Measurement Data J. Koo et al. https://doi.org/10.5572/KOSAE.2025.41.5.826
- 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
- Synergistic analysis and vertical transport attribution of carbon monoxide surface concentrations and satellite column loadings over China S. Wang et al. https://doi.org/10.1016/j.rse.2026.115562
- Quantifying CH4 emissions from coal mine aggregation areas in Shanxi, China, using TROPOMI observations and the wind-assigned anomaly method Q. Tu et al. https://doi.org/10.5194/acp-24-4875-2024
- Spatiotemporal variations in atmospheric CH4 concentrations and enhancements in northern China based on a comprehensive dataset: ground-based observations, TROPOMI data, inventory data, and inversions P. Han et al. https://doi.org/10.5194/acp-25-4965-2025
- Space-based inversion reveals underestimated carbon monoxide emissions over Shanxi X. Li et al. https://doi.org/10.1038/s43247-025-02301-5
19 citations as recorded by crossref.
- 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
- Satellite-Derived Approaches for Coal Mine Methane Estimation: A Review A. Chauhan & S. Raval https://doi.org/10.3390/rs17213652
- 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
- European Climate Policy in the Context of the Problem of Methane Emissions from Coal Mines in Poland B. Gajdzik et al. https://doi.org/10.3390/en17102396
- 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
- High-Resolution Satellite Reveals the Methane Emissions from China’s Coal Mines X. Li et al. https://doi.org/10.3390/rs17020220
- Remote Sensing Enables Basin-Scale Inventories of Coal Mine Methane E. Penn et al. https://doi.org/10.1021/acs.est.5c14976
- Satellite Insights into methane Super-Emitters: Regional emissions and yearly growth on Turkmenistan’s west coast Z. He et al. https://doi.org/10.1016/j.jag.2025.104975
- 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
- Revising the coal mining CH4 emission factor based on multiple inventories and atmospheric inversion approach at one of the world's largest coal production areas: Shanxi province, China X. Shi et al. https://doi.org/10.1016/j.scitotenv.2025.178616
- Mitigating climate change by abating coal mine methane: A critical review of status and opportunities C. Karacan et al. https://doi.org/10.1016/j.coal.2024.104623
- Evaluation of coal mine methane inventory methods using aircraft-based approaches in the Bowen Basin, Australia S. Harris et al. https://doi.org/10.5194/acp-26-10043-2026
- Surface-observation-constrained high-frequency coal mine methane emissions in Shanxi, China, reveal more emissions than inventories, consistent with satellite inversion F. Lu et al. https://doi.org/10.5194/acp-25-5837-2025
- Analysis of Methane (CH4) Distribution in Northeast Asia Based on Satellite Measurement Data J. Koo et al. https://doi.org/10.5572/KOSAE.2025.41.5.826
- 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
- Synergistic analysis and vertical transport attribution of carbon monoxide surface concentrations and satellite column loadings over China S. Wang et al. https://doi.org/10.1016/j.rse.2026.115562
- Quantifying CH4 emissions from coal mine aggregation areas in Shanxi, China, using TROPOMI observations and the wind-assigned anomaly method Q. Tu et al. https://doi.org/10.5194/acp-24-4875-2024
- Spatiotemporal variations in atmospheric CH4 concentrations and enhancements in northern China based on a comprehensive dataset: ground-based observations, TROPOMI data, inventory data, and inversions P. Han et al. https://doi.org/10.5194/acp-25-4965-2025
- Space-based inversion reveals underestimated carbon monoxide emissions over Shanxi X. Li et al. https://doi.org/10.1038/s43247-025-02301-5
Saved (final revised paper)
Latest update: 21 Jul 2026
Short summary
We compute CH4 emissions and uncertainty on a mine-by-mine basis, including underground, overground, and abandoned mines. Mine-by-mine gas and flux data and 30 min observations from a flux tower located next to a mine shaft are integrated. The observed variability and bias correction are propagated over the emissions dataset, demonstrating that daily observations may not cover the range of variability. Comparisons show both an emissions magnitude and spatial mismatch with current inventories.
We compute CH4 emissions and uncertainty on a mine-by-mine basis, including underground,...
Altmetrics
Final-revised paper
Preprint