Abstract. Methane (CH4) emissions from coal production amount to roughly one-third of European anthropogenic CH4 emissions in the atmosphere. Poland is the largest hard coal producer in the European Union with the Polish side of the Upper Silesian Coal Basin (USCB) as the main part of it. Emission estimates for CH4 from the USCB for individual coal mine ventilation shafts range between 0.03 and 20 kt a−1, amounting to a basin total of roughly 440 kt a−1 according to the European Pollutant Release and Transfer Register (E-PRTR, http://prtr.ec.europa.eu/, 2014). We mounted a ground-based, portable, sun-viewing FTS (Fourier transform spectrometer) on a truck for sampling coal mine ventilation plumes by driving cross-sectional stop-and-go patterns at 1 to 3 km from the exhaust shafts. Several of these transects allowed for estimation of CH4 emissions based on the observed enhancements of the column-averaged dry-air mole fractions of methane (XCH4) using a mass balance approach. Our resulting emission estimates range from 6±1 kt a−1 for a single shaft up to 109±33 kt a−1 for a subregion of the USCB, which is in broad agreement with the E-PRTR reports. Three wind lidars were deployed in the larger USCB region providing ancillary information about spatial and temporal variability of wind and turbulence in the atmospheric boundary layer. Sensitivity studies show that, despite drawing from the three wind lidars, the uncertainty of the local wind dominates the uncertainty of the emission estimates, by far exceeding errors related to the XCH4 measurements themselves. Wind-related relative errors on the emission estimates typically amount to 20 %.

and JA RO SL AW N . N E C K I , a sustained CO 2 loss of that magnitude is unlikely to be true. We sought alternative explanations for the observed CO 2 build-up into transport changes and into regional redistribution of fossil fuel CO 2 emissions. Boundary layer heights becoming shallower can only explain 32% of the variance of the signal. Regional changes of emissions may explain up to 27% of the build-up. More insights are given in the Aulagnier et al. companion paper.

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Abstract. We have constructed an atmospheric inversion framework based on TM5-4DVAR to jointly assimilate measurements of methane and δ13C of methane in order to estimate source-specific methane emissions. Here we present global emission estimates from this framework for the period 1999–2016. We assimilate a newly constructed, multi-agency database of CH4 and δ13C measurements. We find that traditional CH4-only atmospheric inversions are unlikely to estimate emissions consistent with atmospheric δ13C data, and assimilating δ13C data is necessary to derive emissions consistent with both measurements. Our framework attributes ca. 85 % of the post-2007 growth in atmospheric methane to microbial sources, with about half of that coming from the tropics between 23.5∘ N and 23.5∘ S. This contradicts the attribution of the recent growth in the methane budget of the Global Carbon Project (GCP). We find that the GCP attribution is only consistent with our top-down estimate in the absence of δ13C data. We find that at global and continental scales, δ13C data can separate microbial from fossil methane emissions much better than CH4 data alone, and at smaller scales this ability is limited by the current δ13C measurement coverage. Finally, we find that the largest uncertainty in using δ13C data to separate different methane source types comes from our knowledge of atmospheric chemistry, specifically the distribution of tropospheric chlorine and the isotopic discrimination of the methane sink.

Abstract. A severe reduction of greenhouse gas emissions is necessary to reach the objectives of the Paris Agreement. The implementation and continuous evaluation of mitigation measures requires regular independent information on emissions of the two main anthropogenic greenhouse gases, carbon dioxide (CO2) and methane (CH4). Our aim is to employ an observation-based method to determine regional-scale greenhouse gas emission estimates with high accuracy. We use aircraft- and ground-based in situ observations of CH4, CO2, carbon monoxide (CO), and wind speed from two research flights over the Upper Silesian Coal Basin (USCB), Poland, in summer 2018. The flights were performed as a part of the Carbon Dioxide and Methane (CoMet) mission above this European CH4 emission hot-spot region. A kriging algorithm interpolates the observed concentrations between the downwind transects of the trace gas plume, and then the mass flux through this plane is calculated. Finally, statistic and systematic uncertainties are calculated from measurement uncertainties and through several sensitivity tests, respectively. For the two selected flights, the in-situ-derived annual CH4 emission estimates are 13.8±4.3 and 15.1±4.0 kg s−1, which are well within the range of emission inventories. The regional emission estimates of CO2, which were determined to be 1.21±0.75 and 1.12±0.38 t s−1, are in the lower range of emission inventories. CO mass balance emissions of 10.1±3.6 and 10.7±4.4 kg s−1 for the USCB are slightly higher than the emission inventory values. The CH4 emission estimate has a relative error of 26 %–31 %, the CO2 estimate of 37 %–62 %, and the CO estimate of 36 %–41 %. These errors mainly result from the uncertainty of atmospheric background mole fractions and the changing planetary boundary layer height during the morning flight. In the case of CO2, biospheric fluxes also add to the uncertainty and hamper the assessment of emission inventories. These emission estimates characterize the USCB and help to verify emission inventories and develop climate mitigation strategies.