Methane (CH₄) is the second most important anthropogenic greenhouse gas, whose atmospheric concentration is modulated by human-induced activities, and it has a larger global warming potential than carbon dioxide (CO₂). Because of its short atmospheric lifetime relative to that of CO₂, the reduction of the atmospheric abundance of CH₄ is an attractive target for short-term climate mitigation strategies. However, reducing the atmospheric CH₄ concentration requires a reduction of its emissions and, therefore, knowledge of its sources. For this reason, the CO₂ and Methane (CoMet) campaign in May and June 2018 assessed emissions of one of the largest CH₄ emission hot spots in Europe, the Upper Silesian Coal Basin (USCB) in southern Poland, using top-down approaches and inventory data. In this study, we will focus on CH₄ column anomalies retrieved from spectral radiance observations, which were acquired by the 1D nadir-looking passive remote sensing Methane Airborne MAPper (MAMAP) instrument, using the weighting-function-modified differential optical absorption spectroscopy (WFM-DOAS) method. The column anomalies, combined with wind lidar measurements, are inverted to cross-sectional fluxes using a mass balance approach. With the help of these fluxes, reported emissions of small clusters of coal mine ventilation shafts are then assessed. The MAMAP CH₄ column observations enable an accurate assignment of observed fluxes to small clusters of ventilation shafts. CH₄ fluxes are estimated for four clusters with a total of 23 ventilation shafts, which are responsible for about 40 % of the total CH₄ mining emissions in the target area. The observations were made during several overflights on different days. The final average CH₄ fluxes for the single clusters (or sub-clusters) range from about 1 to 9 t CH₄ h⁻¹ at the time of the campaign. The fluxes observed at one cluster during different overflights vary by as much as 50 % of the average value. Associated errors (1σ) are usually between 15 % and 59 % of the average flux, depending mainly on the prevailing wind conditions, the number of flight tracks, and the magnitude of the flux itself. Comparison to known hourly emissions, where available, shows good agreement within the uncertainties. If only emissions reported annually are available for comparison with the observations, caution is advised due to possible fluctuations in emissions during a year or even within hours. To measure emissions even more precisely and to break them down further for allocation to individual shafts in a complex source region such as the USCB, imaging remote sensing instruments are recommended.

Coal mining accounts for ∼12 % of the total anthropogenic methane (CH₄) emissions worldwide. The Upper Silesian Coal Basin (USCB), 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, coal bed 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 speed, and surface wind direction. We 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. As an alternative, we have developed three upscaling approaches, i.e., by scaling the European Pollutant Release and Transfer Register (E-PRTR) annual inventory, the quantified shaft-averaged emission rate, and the shaft-averaged emission rate, which are derived from the hourly emission inventory. These estimates are in the range of 256–383 kt CH₄ yr⁻¹ for the inverse Gaussian (IG) approach and 228–339 kt CH₄ yr⁻¹ for the mass balance (MB) approach. We have also estimated the total CO₂ emissions from coal mining ventilation shafts based on the observed ratio of ${\mathrm{CH}}_{\mathrm{4}}/{\mathrm{CO}}_{\mathrm{2}}$ and found that the estimated regional CO₂ emissions are not a major source of CO₂ in the USCB. This study shows that the UAV-based active AirCore system can be a useful tool to quantify local to regional point source methane emissions.

Anthropogenic emissions are the primary source of the increase in atmospheric methane (CH₄) levels. However, estimates of anthropogenic CH₄ emissions still show large uncertainties at global and regional scales. Differences in CH₄ isotopic source signatures δ¹³C and δ²H can help to constrain different source contributions (e.g., fossil, waste, agriculture). The Upper Silesian Coal Basin (USCB) represents one of the largest European CH₄ emission regions, with more than 500 Gg CH₄ yr⁻¹ released from more than 50 coal mine ventilation shafts, landfills, and wastewater treatment plants. During the CoMet (Carbon Dioxide and Methane Mission) campaign in June 2018 methane observations were conducted from a variety of platforms including aircraft and cars to quantify these emissions. Besides the continuous sampling of atmospheric methane concentration, numerous air samples were taken from inside and around the ventilation shafts (1–2 km distance) and aboard the High Altitude and Long Range Research Aircraft (HALO) and DLR Cessna Caravan aircraft, and they were analyzed in the laboratory for the isotopic composition of CH₄. The airborne samples downwind of the USCB contained methane from the entire region and thus enabled determining the mean signature of the USCB accurately. This mean isotopic signature of methane emissions was $-\mathrm{50.9}\pm \mathrm{0.7}$ ‰ for δ¹³C and $-\mathrm{226}\pm \mathrm{9}$ ‰ for δ²H. This is in the range of previous USCB studies based on samples taken within the mines for δ¹³C but more depleted in δ²H than reported before. Signatures of methane enhancements sampled upwind of the mines and in the free troposphere clearly showed the influence of biogenic sources. We determined the source signatures of individual coal mine ventilation shafts using ground-based samples. These signatures displayed a considerable range between different mines and also varied for individual shafts from day to day. Different layers of the USCB coal contain thermogenic methane, isotopically similar to natural gas, and methane formed through biogenic carbonate reduction. The signatures vary depending on what layer of coal is mined at the time of sampling. Mean shaft signatures range from −60 ‰ to −42 ‰ for δ¹³C and from −200 ‰ to −160 ‰ for δ²H. A gradient in the signatures of subregions of the USCB is reflected both in the aircraft data and in the ground samples, with emissions from the southwest being most depleted in δ²H and emissions from the south being most depleted in δ¹³C, which is probably associated with the structural and lithostratigraphic history of the USCB and generation and migration processes of methane in the coal. The average signature of $-\mathrm{49.8}\pm \mathrm{5.7}$ ‰ in δ¹³C and $-\mathrm{184}\pm \mathrm{32}$ ‰ in δ²H from the ventilation shafts clearly differs from the USCB regional signature in δ²H. This makes a source attribution using δ²H signatures possible, which would not be possible with only the δ¹³C isotopic signatures. We assume that the USCB plume mainly contains fossil coal mine methane and biogenic methane from waste treatment, because the USCB is a highly industrialized region with few other possible methane sources. Assuming a biogenic methane signature between and −320 ‰ and −280 ‰ for δ²H, the biogenic methane emissions from the USCB account for 15 %–50 % of total emissions. The uncertainty range shows the need of comprehensive and extensive sampling from all possible source sectors for source apportionment. The share of anthropogenic–biogenic emissions of 0.4 %–14 % from this densely populated industrial region is underestimated in commonly used emission inventories. Generally, this study demonstrates the importance of δ²H-CH₄ observations for methane source apportionment in regions with a mix of thermogenic and biogenic sources and, especially in our case, where the δ¹³C signature of the coal mine gas has a large variability.

Methane is a powerful greenhouse gas responsible for around 20 % of radiative forcing (relative to the pre-industrial era) caused by all long-lived greenhouse gases (WMO, 2021). About 60 % of the global emissions are from anthropogenic sources, and coal mining is one of the largest contributors. Emissions are either estimated by bottom-up approaches (based on inventories) or top-down approaches (based on atmospheric measurements). Combining those with an accurate error estimation allows us to better characterise model errors e.g. caused by transport mechanisms. Here we provide a detailed description of factors influencing the coal mine methane emission variability. We use high-frequency (up to hourly) temporal data from seven coal mines in the Upper Silesian Coal Basin during the Carbon dioxide and Methane (CoMet 1.0) mission from 14 May to 13 June 2018. Knowledge of these factors for the individual ventilation shaft is essential for linking the observations achieved during the CoMet 1.0 mission with models, as most publicly available data in the bottom-up worldwide inventories provide annual emissions only. The methane concentrations in examined shafts ranged from 0.10 % to 0.55 %±0.1 % during the study period. Due to the changing scope of mining works performed underground, they were subjected to a significant variation on a day-to-day basis. The yearly methane average emission rate calculated based on 1 month's set of temporal data of the analysed subset of mines was of the order of 142.68 kt yr⁻¹ (σ=18.63 kt yr⁻¹), an estimate 27 % lower than the officially published State Mining Authority (WUG) data and 36 % lower than reported to the European Pollutant Release and Transfer Register (E-PRTR). We also found that emissions from individual coal mine facilities were over- and underestimated by between 4 % to 60 %, compared to the E-PRTR, when short-term records were analysed. We show that the observed discrepancies between annual emissions based on temporal data and public inventories result from (1) the incorrect assumption that the methane emissions are time-invariant, (2) the methodology of measurements, and lastly, (3) the frequency and timing of measurements. From the emission monitoring perspective, we recommend using a standardised emission measurement system for all coal mines, similar to the Methane Fire Teletransmission Monitoring System (SMP-NT/A). Legal safety requirements require all coal mines to implement this system. After an adaptation, the system could allow for gas flow quantification, necessary for accurate and precise estimations of methane emissions at a high temporal resolution. Using this system will also reduce the emission uncertainty due to factors like frequency and timing of measurements. In addition, it would be beneficial to separately identify the emissions from individual ventilation shafts and methane drainage stations. That would bridge the gap between bottom-up and top-down approaches for coal mine emissions. The intermittent releases of unutilised methane from the drainage stations are currently not considered when constructing regional methane budgets.

Underground excavations in which an airflow is present are affected by both natural and technological sources of heat. As a result, the air flowing through the mine excavations is characterised by high temperatures, which—combined with high humidity—causes microclimatic conditions to deteriorate. Bad microclimatic conditions affect miners underground, causing a reduction of perception, concentration, attention, and perceptiveness. This negative influence of temperature and humidity on the human body is referred to as the climatic hazard. For this reason, the design of ventilation and air conditioning systems to be implemented in underground mining plants is an issue of increasing significance. This article investigates the performance of cooling systems in the Polish hard-coal mining industry. Based on the conducted research on air-cooling installations in six hard-coal mines, the actual efficiency of air-cooling is presented. The calculated values of cooling power were compared with the design intent. The obtained results have allowed identifying with greater precision the factors that diminish the efficiency of cooling systems in the mining plants under analysis. These factors may be treated on equal terms with key performance indicators (KPIs), which can be used to monitor the performance of cooling system components and to provide managers with high-level indicators on which decisions can be based.