Estimating Upper Silesian coal mine methane emissions from airborne in situ observations and dispersion modeling

Abstract

Abstract. Abundant mining and industrial activities located in the Upper Silesian Coal Basin (USCB) lead to large emissions of the potent greenhouse gas (GHG) methane (CH4). The strong localization of CH4 emitters (mostly confined to known coal mine ventilation shafts) and the large emissions of 448 and 720 kt CH4 yr−1 reported in the European Pollutant Release and Transfer Register (E-PRTR 2017) and the Emissions Database for Global Atmospheric Research (EDGAR v4.3.2), respectively, make the USCB a prime research target for validating and improving CH4 flux estimation techniques. High-precision observations of this GHG were made downwind of local (e.g., single facilities) to regional-scale (e.g., agglomerations) sources in the context of the CoMet 1.0 campaign in early summer 2018. A quantum cascade–interband cascade laser (QCL–ICL)-based spectrometer adapted for airborne research was deployed aboard the German Aerospace Center (DLR) Cessna 208B to sample the planetary boundary layer (PBL) in situ. Regional CH4 emission estimates for the USCB are derived using a model approach including assimilated wind soundings from three ground-based Doppler lidars. Although retrieving estimates for individual emitters is difficult using only single flights due to sparse data availability, the combination of two flights allows for exploiting different meteorological conditions (analogous to a sparse tomography algorithm) to establish confidence on facility-level estimates. Emission rates from individual sources not only are needed for unambiguous comparisons between bottom-up and top-down inventories but also become indispensable if (independently verifiable) sanctions are to be imposed on individual companies emitting GHGs. An uncertainty analysis is presented for both the regional-scale and facility-level emission estimates. We find instantaneous coal mine emission estimates of 451/423 ± 77/79 kt CH4 yr−1 for the morning/afternoon flight of 6 June 2018. The derived fuel-exploitation emission rates coincide (±6 %) with annual-average inventorial data from E-PRTR 2017 although they are distinctly lower (−28 %/−32 %) than values reported in EDGAR v4.3.2. Discrepancies in available emission inventories could potentially be narrowed down with sufficient observations using the method described herein to bridge the gap between instantaneous emission estimates and yearly averaged inventories.

Quantification of methane emissions from hotspots and during COVID-19 using a global atmospheric inversion

“…In contrast, inverse estimates from a known persistent point source, the Appin Mine, were found to be in good agreement with a previous top-down estimate (Varon et al, 2020). For a 1-day period over a large region, the Upper Silesian Basin, inverse estimates agreed well with previous studies, (Fiehn et al, 2020;Kostinek et al, 2021). Overall, these case studies suggest our inverse system is suitable for regional scale (~100km 2 ) emission quantification over a short time-period (24-hour), given sufficient satellite observations are available.…”

“…To evaluate the feasibility of the system to quantify regional CH4 emission sources within a 24-hour window we performed a one-day inversion over the USCB. Results were compared with emission estimates derived using aircraft observations combined with Eulerian and Lagrangian dispersion models (Kostinek et al, 2021) and a mass balance approach (Fiehn et al, 2020). These studies used extensive flight data from the 6 th June 2018 to derive regional CH4 emission estimates of 0.42-0.48 Tg yr -1 .…”

Quantifying hard coal mines CH<sub>4</sub> emissions from TROPOMI and IASI observations using high-resolution CAMS forecast data and the wind-assigned anomaly method

“…It is probably because the CAMS inventory includes many sectors of anthropogenic sources, like wastes, and combustion from residential and commercial, which account for about 20%. Nevertheless, our results derived from satellite observations are close to the E-PRTR inventory of 5.33E26 molec./s and reasonablely compared to the CoMet inventory (6.6E26 molec./s), and to previous studies over the USCB region (ranging from 1.05E25 molec./s to 9.38E25 molec./s for a sub-clusters of shafts (Krautwurst et al, 2021) up to 5.68E26 molec./s derived from one flight (Kostinek et al (2021)). Similar 2D anomalies and plumes are also observed for TROPOMI XCH4 and TROPOMI+IASI TXCH4.…”

“…Register (E-PRTR, 2017; https://prtr.eea.europa.eu/, last access: 25 October 2021) reports that the total CH4 emissions from the USCB region amount to 448 kt yr-1 (5.33E26 molec./s). Most of these emissions are from mining activities and heavy industry (Kostinek et al, 2021), which makes this region a hot spot of CH4 emission in Europe. To investigate the CH4 emission from this hot spot, the Carbon Dioxide and Methane (CoMet) campaign was performed, covering roughly 3 weeks from May to June 2018 (more details can be found in Luther et al, 2019;Fiehn et al, 2020;Kostinek et al, 2021;Krautwurst et al, 2021).…”

“…Fiehn et al (2020) analyzed aircraft-and ground-based in situ observations and reported an emission estimate of 436 ± 115 kt yr-1 (5.19E26 ± 1.37E26 molec./s) and 477 ± 101 kt yr-1 (5.68E26 ± 1.20E26 molec./s) from two selected flights. An advanced model approach was introduced by Kostinek et al (2021) to investigate two research flights in the morning and afternoon, resulting in estimated CH4 emissions of 451 ± 77 kt yr-1 (5.37E26 ± 9.16E25 molec./s) and 423 ± 79 kt yr-1 (5.03E26 ± 9.40E25 molec./s), respectively. Another emission estimate based on the observations from the nadir-looking passive remote sensing Methane Airborne MAPper (MAMAP) instrument accounted for…”