03 Jan 2022
03 Jan 2022
Status: a revised version of this preprint is currently under review for the journal ACP.

Local to regional methane emissions from the Upper Silesia Coal Basin (USCB) quantified using UAV-based atmospheric measurements

Truls Andersen1, Marcel de Vries1, Jaroslaw Necki4, Justyna Swolkien5, Malika Menoud6, Thomas Röckmann6, Anke Roiger7, Andreas Fix7, Wouter Peters1,3, and Huilin Chen1,2 Truls Andersen et al.
  • 1Centre for Isotope Research, Energy and Sustainability Institute Groningen (ESRIG), University of Groningen, Groningen, Netherlands
  • 2Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing, China
  • 3Meteorology and Air Quality, Wageningen University and Research Center, Wageningen, Netherlands
  • 4Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, Krakow, Poland
  • 5Faculty Civil Engineering and Resource Management, AGH University of Science and Technology, Krakow, Poland
  • 6Institute for Marine and Atmospheric Research Utrecht (IMAU), Utrecht University, Utrecht, Netherlands
  • 7Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR), Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany

Abstract. Coal mining accounts for ~ 12 % of the total anthropogenic methane emissions worldwide. The Upper Silesian Coal Basin, Poland, where large quantities of CH4 are emitted to the atmosphere via ventilation shafts of underground hard coal (anthracite) mines, is one of the hot spots of methane emissions in Europe. However, coalbed CH4 emissions into the atmosphere are poorly characterized. As part of the Carbon Dioxide and CH4 mission 1.0 (CoMet 1.0) that took place in May – June 2018, we flew a recently developed active AirCore system aboard an unmanned aerial vehicle (UAV) to obtain CH4 and CO2 mole fractions 150–300 m downwind of five individual ventilation shafts in the USCB. In addition, we also measured δ13C-CH4, δ2H-CH4, ambient temperature, pressure, relative humidity, surface wind speeds and directions. We have used 34 UAV flights and two different approaches (inverse Gaussian approach and mass balance approach) to quantify the emissions from individual shafts. The quantified emissions were compared to both annual and hourly inventory data, and were used to derive the estimates of CH4 emissions in the USCB. We found a high correlation (R2 = 0.7 – 0.9) between the quantified and hourly inventory data-based shaft-averaged CH4 emissions, which in principle would allow regional estimates of CH4 emissions to be derived by upscaling individual hourly inventory data of all shafts. Currently, such inventory data is available only for the five shafts we quantified though. As an alternative, we have developed three upscaling approaches, i.e., by scaling the E-PRTR annual inventory, the quantified shaft-averaged emission rate, and the shaft-averaged emission rate that are derived from the hourly emission inventory. These estimates are in the range of 325 – 447 kt CH4/year for the inverse Gaussian approach and 268 – 347 kt CH4/year for the mass balance approach, respectively. This study shows that the UAV-based active AirCore system can be a useful tool to quantify local to regional point source methane emissions.

Truls Andersen et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on acp-2021-1061', Anonymous Referee #1, 24 Jan 2022
  • RC2: 'Comment on acp-2021-1061', Anonymous Referee #2, 06 May 2022

Truls Andersen et al.

Truls Andersen et al.


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Short summary
The Upper Silesian Coal Basin, Poland is one of the hot spots of methane emissions in Europe. Using an unmanned aerial vehicle (UAV), we performed atmospheric measurements of methane concentrations downwind of five ventilation shafts in this region and determined the emission rates from the individual shafts. We found a strong correlation between quantified shaft-averaged emission rates and hourly inventory data, which also allows us to estimate the methane emissions from the entire region.