Surface Subsidence as an Effective Indicator of Methane Emissions From Underground Coal Mines

Abstract Methane (CH 4 ) emissions from underground coal mining remain a major and uncertain anthropogenic source. This study tests whether surface subsidence, a direct consequence of underground mining, can serve as an indicator of CH 4 emissions. We use the Changzhi coal belt in Shanxi of China, a major emission hotspot, as a case study. Time‐series Interferometric Synthetic Aperture Radar analysis of Sentinel‐1 SAR data (November 2019 to October 2024) revealed persistent subsidence across the region. Over a similar period, hyperspectral images from four satellite platforms (March 2019 to October 2024) detected 568 CH 4 plumes from 33 point sources. The two data sets showed strong spatial overlap. Annual subsidence volume was significantly negatively correlated with time‐averaged point‐source emissions ( r = −0.65 to −0.53, p < 0.01), indicating that subsidence, as a proxy for extracted coal volume, is a reliable indicator of cumulative emissions. Applying this hyperspectral‐calibrated relationship to areas with subsidence but no detected plumes yields total point‐source emissions of 0.288–0.508 Mt·a −1 , representing 13%–43% of regional inventory estimates. Hyperspectral satellites alone miss approximately 18%–32% of this total. Combining InSAR‐derived subsidence with hyperspectral plume observations thus provides a nearly all‐weather pathway for monitoring CH 4 emissions from underground coal mining.

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Publication Details

Journal
Journal of Geophysical Research Atmospheres
Published
2026-10-31
DOI
https://doi.org/10.1029/2025jd045292
Primary Topic
Synthetic Aperture Radar (SAR) Applications and Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Surface Subsidence as an Effective Indicator of Methane Emissions From Underground Coal Mines

Zhao‐Cheng Zeng, Zhonghua He, Miao Liang, Huilin Chen et al.
3 links
Journal of Geophysical Research Atmospheres
Synthetic Aperture Radar (SAR) Applications and Techniques
article

Surface Subsidence as an Effective Indicator of Methane Emissions From Underground Coal Mines

Zhao‐Cheng Zeng, Zhonghua He, Miao Liang, Huilin Chen, Changjun Zhao, Cunren Liang, Chunyan Zhou
article en

Abstract

Abstract Methane (CH 4 ) emissions from underground coal mining remain a major and uncertain anthropogenic source. This study tests whether surface subsidence, a direct consequence of underground mining, can serve as an indicator of CH 4 emissions. We use the Changzhi coal belt in Shanxi of China, a major emission hotspot, as a case study. Time‐series Interferometric Synthetic Aperture Radar analysis of Sentinel‐1 SAR data (November 2019 to October 2024) revealed persistent subsidence across the region. Over a similar period, hyperspectral images from four satellite platforms (March 2019 to October 2024) detected 568 CH 4 plumes from 33 point sources. The two data sets showed strong spatial overlap. Annual subsidence volume was significantly negatively correlated with time‐averaged point‐source emissions ( r = −0.65 to −0.53, p < 0.01), indicating that subsidence, as a proxy for extracted coal volume, is a reliable indicator of cumulative emissions. Applying this hyperspectral‐calibrated relationship to areas with subsidence but no detected plumes yields total point‐source emissions of 0.288–0.508 Mt·a −1 , representing 13%–43% of regional inventory estimates. Hyperspectral satellites alone miss approximately 18%–32% of this total. Combining InSAR‐derived subsidence with hyperspectral plume observations thus provides a nearly all‐weather pathway for monitoring CH 4 emissions from underground coal mining.

Journal of Geophysical Research AtmospheresVol. 131(21)
China Meteorological Administration (CN), University of Electronic Science and Technology of China (CN), Peking University (CN), Ministry of Ecology and Environment (CN), Zhejiang Meteorological Bureau (CN), Satellite Application Center for Ecology and Environment (CN), Nanjing University (CN)
National Natural Science Foundation of China, Chinese Academy of Sciences, China Meteorological Administration, Peking University, Natural Science Foundation of Zhejiang Province
Climate action
Openalex Percentile: Top 80%
Synthetic Aperture Radar (SAR) Applications and Techniques
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