Observational constraints on methane emissions from Polish coal mines using a ground-based remote sensing network
<p><strong class="journal-contentHeaderColor">Abstract.</strong> Given its abundant coal mining activities, the Upper Silesian Coal Basin (USCB) in southern Poland is one of the largest sources of anthropogenic methane (CH<span class="inline-formula"><s...
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| Main Authors: | , , , , , , , , , , , , , , , , , , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
5 May 2022
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| In: |
Atmospheric chemistry and physics
Year: 2022, Volume: 22, Issue: 9, Pages: 5859-5876 |
| ISSN: | 1680-7324 |
| DOI: | 10.5194/acp-22-5859-2022 |
| Online Access: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.5194/acp-22-5859-2022 Verlag, lizenzpflichtig, Volltext: https://acp.copernicus.org/articles/22/5859/2022/ 
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| Author Notes: | Andreas Luther, Julian Kostinek, Ralph Kleinschek, Sara Defratyka, Mila Stanisavljević, Andreas Forstmaier, Alexandru Dandocsi, Leon Scheidweiler, Darko Dubravica, Norman Wildmann, Frank Hase, Matthias M. Frey, Jia Chen, Florian Dietrich, Jarosław Nȩcki, Justyna Swolkień, Christoph Knote, Sanam N. Vardag, Anke Roiger, and André Butz |
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| 245 | 1 | 0 | |a Observational constraints on methane emissions from Polish coal mines using a ground-based remote sensing network |c Andreas Luther, Julian Kostinek, Ralph Kleinschek, Sara Defratyka, Mila Stanisavljević, Andreas Forstmaier, Alexandru Dandocsi, Leon Scheidweiler, Darko Dubravica, Norman Wildmann, Frank Hase, Matthias M. Frey, Jia Chen, Florian Dietrich, Jarosław Nȩcki, Justyna Swolkień, Christoph Knote, Sanam N. Vardag, Anke Roiger, and André Butz |
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| 520 | |a <p><strong class="journal-contentHeaderColor">Abstract.</strong> Given its abundant coal mining activities, the Upper Silesian Coal Basin (USCB) in southern Poland is one of the largest sources of anthropogenic methane (CH<span class="inline-formula"><sub>4</sub></span>) emissions in Europe. Here, we report on CH<span class="inline-formula"><sub>4</sub></span> emission estimates for coal mine ventilation facilities in the USCB. Our estimates are driven by pairwise upwind-downwind observations of the column-average dry-air mole fractions of CH<span class="inline-formula"><sub>4</sub></span> (XCH<span class="inline-formula"><sub>4</sub></span>) by a network of four portable, ground-based, sun-viewing Fourier transform spectrometers of the type EM27/SUN operated during the CoMet campaign in May-June 2018. The EM27/SUN instruments were deployed in the four cardinal directions around the USCB approximately <span class="inline-formula">50</span> km from the center of the basin. We report on six case studies for which we inferred emissions by evaluating the mismatch between the observed downwind enhancements and simulations based on trajectory calculations releasing particles out of the ventilation shafts using the Lagrangian particle dispersion model FLEXPART. The latter was driven by wind fields calculated by WRF (Weather Research and Forecasting model) under assimilation of vertical wind profile measurements of three co-deployed wind lidars. For emission estimation, we use a Phillips-Tikhonov regularization scheme with the L-curve criterion. Diagnosed by the emissions averaging kernels, we find that, depending on the catchment area of the downwind measurements, our ad hoc network can resolve individual facilities or groups of ventilation facilities but that inspecting the emissions averaging kernels is essential to detect correlated estimates. Generally, our instantaneous emission estimates range between 80 and 133 kt CH<span class="inline-formula"><sub>4</sub></span> a<span class="inline-formula"><sup>−1</sup></span> for the southeastern part of the USCB and between 414 and 790 kt CH<span class="inline-formula"><sub>4</sub></span> a<span class="inline-formula"><sup>−1</sup></span> for various larger parts of the basin, suggesting higher emissions than expected from the annual emissions reported by the E-PRTR (European Pollutant Release and Transfer Register). Uncertainties range between 23 % and 36 %, dominated by the error contribution from uncertain wind fields.</p> | ||
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