Quantifying CH4 emissions from coal-mine ventilation in the Upper Silesian Coal Basin (Poland) using COCCON spectrometers
Authors: Luther Andreas , Kostinek Julian , Kleinschek Ralph , Defratyka Sara , Stanisavljevic Mila , Forstmaier Andreas , Dandocsi Alexandru , Scheidweiler Leon , Dubravica Darko , Wildmann Norman , Hase Frank , Frey Matthias M. , Chen Jia , Dietrich Florian , Necki Jaroslaw , Swolkien Justyna , Knote Christoph , Vardag Sanam N. , Roiger Anke , Butz André 
Published: March 2022

&lt;p&gt;The Upper Silesian Coal Basin (USCB), with its coal mines ventilating methane (CH4), is among the&lt;br&gt;largest localized CH4 sources in Europe. The reported emission rates, however, vary broadly among&lt;br&gt;the emission inventories ranging between 405 ktCH4 (GESAPU, for the year 2010) and 720 kt (EDGAR&lt;br&gt;v4.3.2, for the year 2017). Thus, independent verification is required to constrain the actual&lt;br&gt;emissions better.&lt;br&gt;Here, we report on a demonstration study conducted in May/June 2018 in the framework of the&lt;br&gt;CoMet campaign in the USCB. During the campaign, five direct-sun spectrometers of the COCCON-&lt;br&gt;type (Carbon Column Observing Network) were deployed in the region measuring column&lt;br&gt;concentrations of CH4. One of the spectrometers was operated on a van sampling plumes of&lt;br&gt;individual ventilation facilities [Luther et al., 2019]; the other four spectrometers were operated in a&lt;br&gt;stationary network at a distance of roughly 50 km enclosing the USCB [Luther et al., 2021]. In&lt;br&gt;addition, we ran three wind-lidars in the region to constrain atmospheric transport. The&lt;br&gt;spectrometers detected downwind enhancements of CH4 concentrations unambiguously&lt;br&gt;attributable to coal mine ventilation. For the mobile spectrometer, we used a mass balance method&lt;br&gt;to infer emission rates for individual facilities. For the network, we used pairwise upwind-downwind&lt;br&gt;concentration gradients together with air mass trajectory modelling by WRF/FLEXPART to estimate&lt;br&gt;emission rates for groups of facilities. The Tikhonov-based inverse method delivered the diagnostics&lt;br&gt;for quantifying the information content attributable to the facilities. We show that our approach&lt;br&gt;allows estimating emissions rates with uncertainties of 20-35% largely dominated by uncertainties in&lt;br&gt;atmospheric transport. This stresses the importance of wind measurements together with the CH4&lt;br&gt;observations. Overall, scaling our hourly-to-daily emission estimates to a year indicates that they are&lt;br&gt;greater or equal to the ones reported by EPRTR (European Pollutant Release and Transfer Register).&lt;/p&gt;&lt;p&gt;Luther, A., Kostinek, J., Kleinschek, R., Defratyka, S., Stanisavljevic, M., Forstmaier, A., Dandocsi, A.,&lt;br&gt;Scheidweiler, L., Dubravica, D., Wildmann, N., Hase, F., Frey, M. M., Chen, J., Dietrich, F., Necki, J.,&lt;br&gt;Swolkien, J., Knote, C., Vardag, S. N., Roiger, A., and Butz, A.: Observational constraints on methane&lt;br&gt;emissions from Polish coal mines using a ground-based remote sensing network, Atmos. Chem. Phys.&lt;br&gt;Discuss. [preprint], https://doi.org/10.5194/acp-2021-978, in review, 2021.&lt;/p&gt;&lt;p&gt;&lt;br&gt;Luther, A., Kleinschek, R., Scheidweiler, L., Defratyka, S., Stanisavljevic, M., Forstmaier, A., Dandocsi,&lt;br&gt;A., Wolff, S., Dubravica, D., Wildmann, N., Kostinek, J., J&amp;#246;ckel, P., Nickl, A.-L., Klausner, T., Hase, F.,&lt;br&gt;Frey, M., Chen, J., Dietrich, F., Ne&amp;#807;cki, J., Swolkie&amp;#324;, J., Fix, A., Roiger, A., and Butz, A.: Quantifying CH 4&lt;br&gt;emissions from hard coal mines using mobile sun-viewing Fourier transform spectrometry, Atmos.&lt;br&gt;Meas. Tech., 12, 5217&amp;#8211;5230, https://doi.org/10.5194/amt-12-5217-2019, 2019.&lt;/p&gt;