Estimating methane emissions from surface coal mines using satellite observations
Abstract
Monitoring and mitigating methane emissions from super-emitting sources is critical for addressing climate change. The TROPOMI instrument onboard Sentinel-5P provides daily global coverage of methane concentrations at 5.5 × 7 km² resolution, enabling the detection of methane super-emitters (>~8 t hr⁻¹). These data are instrumental in identifying hotspots that can be further investigated using high-resolution (~25 m) satellite instruments to pinpoint facility-level emissions. In support of the UNEP-IMEO Methane Alert and Response System (MARS), we have identified over 250 super-emitter hotspots. These hotspots include oil and gas production sites and urban landfills, while a third are associated with coal mining operations, including unexpected sources like surface coal mines. Given the crucial role of coal in the global energy landscape and steel production, it is essential to monitor and accurately estimate the associated methane emissions.This work highlights the synergy between TROPOMI and high-resolution instruments through an analysis of surface coal mine clusters in Kazakhstan, Russia, and India. We estimate 2021-2023 annual methane emissions from these three clusters using TROPOMI data in a Bayesian inversion approach. Our results align with emissions calculated using UNFCCC emission factors and mine-level production data, except in India, where significantly lower emissions are observed. Comparisons with bottom-up gridded emission inventories EDGAR v7 & GFEI v2 reveal notable discrepancies, primarily due to inaccuracies in spatial disaggregation. In Kazakhstan, methane emissions increase substantially between 2021 and 2023 despite stable coal production, suggesting that coal seam characteristics and other factors influence emission dynamics. Our emission estimates align closely with GHGSat-based estimates across all mines and years where a sufficient number of GHGSat observations are available. Moreover, spatial correlations are identified between GHGSat-detected methane enhancements and mining activities within the mine. Additionally, atmospheric temperature inversions are found to significantly contribute to the accumulation of methane within the mine pit, complicating emission quantifications based on high-resolution observations. The findings of this study underscore the importance of combining TROPOMI data with high-resolution satellite data to refine methane emission estimates from complex sources like surface coal mines.
Authors 12
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Space Research Organisation Netherlands
Affiliation as printed
SRON Netherlands Institute for Space Research, Leiden, The Netherlands
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Space Research Organisation Netherlands
Affiliation as printed
SRON Netherlands Institute for Space Research, Leiden, The Netherlands
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Space Research Organisation Netherlands
Affiliation as printed
SRON Netherlands Institute for Space Research, Leiden, The Netherlands
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Affiliation as printed
GHGSat Inc, Montréal, Canada
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Affiliation as printed
GHGSat Inc, Montréal, Canada
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Affiliation as printed
GHGSat Inc, Montréal, Canada
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GHGSat (Canada) · Space Research Organisation Netherlands
Affiliation as printed
GHGSat Inc, Montréal, Canada
SRON Netherlands Institute for Space Research, Leiden, The Netherlands
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Space Research Organisation Netherlands
Affiliation as printed
SRON Netherlands Institute for Space Research, Leiden, The Netherlands
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Itziar Irakulis‐Loitxate corresponding
Universitat Politècnica de València
Affiliation as printed
International Methane Emission Observatory, United Nations Environment Program, Paris, France
Research Institute of Water and Environmental Engineering (IIAMA), Universitat Politècnica de València (UPV), Valencia, Spain
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Nicholas Balasus corresponding
Affiliation as printed
Harvard University, Cambridge, MA, US
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Daniel J. Varon corresponding
Affiliation as printed
Harvard University, Cambridge, MA, US
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Space Research Organisation Netherlands · Vrije Universiteit Amsterdam
Affiliation as printed
Department of Earth Sciences, Vrije Universiteit, Amsterdam, The Netherlands
SRON Netherlands Institute for Space Research, Leiden, The Netherlands
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