Abstract
Methane (CH4) emissions from human activities are a threat to the resilience of our current climate system, and to the adherence of the Paris Agreement goals. The stable isotopic composition of methane (δ13C and δ2H) allows to distinguish between the different CH4 origins. A significant part of the European CH4
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emissions, 3.6 % in 2018, comes from coal extraction in Poland; the Upper Silesian Coal Basin (USCB) being the main hotspot. Measurements of CH4 mole fraction (χ(CH4)), δ13C and δ2H in CH4 in ambient air were performed continuously during 6 months in 2018 and 2019 at Krakow, Poland, 50 km east of the USCB. In addition, air samples were collected during parallel mobile campaigns, from multiple CH4 sources in the footprint area of the continuous measurements. The resulting isotopic signatures from sampled plumes allowed us to distinguish between natural gas leaks, coal mine fugitive emissions, landfill and sewage, and ruminants. The use of δ2H in CH4 is crucial to distinguish the fossil fuel emissions in the case of Krakow, because their relatively depleted δ13C values overlap with the ones of microbial sources. The observed χ(CH4) time series showed regular daily night-time accumulations, sometimes combined with irregular pollution events during the day. The isotopic signatures of each peak were obtained using the Keeling plot method, and generally fall in the range of thermogenic CH4 formation – with δ13C between −55.3 and −39.4 ‰ V-PDB, and δ2H between −285 and −124 ‰ V-SMOW. They compare well with the signatures measured for gas leaks in Krakow and USCB mines. The CHIMERE transport model was used to compute the CH4 and isotopic composition time series in Krakow, based on two emission inventories. The χ(CH4) are generally under-estimated in the model. The simulated isotopic source signatures, obtained with Keeling plots on each simulated peak using the EDGAR v5.0 inventory, indicate that a higher contribution from fuel combustion sources in EDGAR would lead to a better agreement. The isotopic mismatches between model and observations are mainly caused by uncertainties in the assigned isotopic signatures for each source category, and the way they are classified in the inventory. These uncertainties are larger for emissions close to the study site, which are more heterogenous than the ones advected from the USCB coal mines. Our isotope approach proves to be very sensitive in this region, thus helping to evaluate emission estimates.
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