While thermal coal is being phased out, metallurgical coal is likely to remain essential for steel production for several more decades. Reducing the climate impact of ongoing coal mining requires accurate quantification and mitigation of methane emissions. Reliable emission estimates are crucial for designing effective mitigation strategies and for reporting under frameworks such as the UNFCCC and the Global Methane Pledge. Traditional approaches to estimating coal mine methane emissions rely on generalized models, such as Langmuir isotherms, which consider only coal rank and mine depth. These first-order approximations fail to capture the considerable variability in emissions across individual mines, mining methods, production regimes, and operational practices such as ventilation and methane drainage. Recent advances in satellite remote sensing now allow for inversion-based measurement of methane emissions at the scale of individual ventilation shafts and drainage stations. The International Methane Emissions Observatory (IMEO) Steel Methane Programme (SMP) leverages these observations by integrating satellite measurements with aircraft campaigns, published studies, and a comprehensive bottom-up inventory. The SMP applies a Bayesian inference framework to effectively integrate incomplete and heterogeneous data, delivering the first empirically grounded global dataset of methane emission estimates from metallurgical coal mines. Supported by a transparent deterministic methodology, the SMP framework will produce a publicly accessible database of coal mine methane emissions, alongside IMEO’s best estimate of annual mine-level emissions. By providing a transparent, empirically grounded framework, this work also establishes a scalable approach that can be applied to thermal coal production and integrated into global greenhouse gas monitoring initiatives.

Ambition on methane emissions reduction is growing, and open, reliable, measurement-based and actionable data is essential to track changes in emissions over time. The ability of countries and companies to meet their goals requires a thorough understanding of the magnitude and location of methane emissions, as well as being able to demonstrate progress towards these goals. As a core implementing partner of the Global Methane Pledge, the UN Environment Programme’s International Methane Emissions Observatory (IMEO) has been tasked with creating a sound scientific basis for methane emissions estimates and is providing reliable, public, policy-relevant data to facilitate actions to reduce methane emissions. IMEO is collecting and integrating diverse methane emissions data streams, including satellite remote sensing data, science studies, national inventories, and measurement-based industry reporting to establish a global, centralized public record of empirically verified methane emissions. Here, we will show the progress of IMEO towards developing its global, public dataset of policy-relevant methane data, highlighting successful mitigation case studies for the oil and gas industry from the pilot phase of IMEO’s Methane Alert and Response System (MARS), and from IMEO’s Methane Science Studies. We demonstrate how empirical data can drive real, tangible mitigation action in countries around the world.

Methane (CH4) is the second most important anthropogenic greenhouse gas (GHG), and its emissions reduction has been identified as an essential mitigation target to slow down climate change. According to inventories, fossil fuel production and usage account for roughly 17% of the global CH4 emissions, of which approximately 33% originate from coal mining. Accurate identification of coal mining-related CH4 sources and quantification of their annual emission rate is needed for corporate reporting requirements, national inventory verification, and the development of CH4 mitigation strategies.A previous study estimated CH4 emissions for six coal mines in the Bowen Basin in Queensland, Australia, using TROPOMI satellite measurements. It covered a sub-area of the Bowen Basin, where coal is mined at over 40 active mining locations distributed over 60,000 km2. The study showed a significant discrepancy compared to inventory estimates by a factor of 7 during 2018 and 2019.To further verify satellite estimates and improve knowledge of the distribution, persistence, and strength of emissions of this mining region, the Bowen Basin CH4 Mapping (BBCMap) Campaign was conducted in September-October 2023, funded by and performed in collaboration with UNEP's International Methane Emissions Observatory. During this campaign, two HK36 Eco-Dimona research aircraft carrying complementary sensing instrumentation were deployed. The MAMAP2D-Light (Methane Airborne MAPper 2D – Light) imaging spectrometer for estimating atmospheric CH4 and CO2 column anomalies and a lidar for topography scans were deployed on one DIMONA HK36 research aircraft, while the second identical aircraft was equipped with an in-situ payload consisting of an LGR OA-ICOS gas analyser for simultaneous measurements of atmospheric CH4, CO2, and water vapor concentrations, a turbulence probe for wind statistics, and a bag sampler for collecting multiple gas samples during each flight for later 13C isotope analyses in the laboratory. This two-aircraft strategy allowed coordinated measurements of CH4 emissions from different coal mines with both remote sensing and in-situ instruments and simultaneous wind measurements, which is essential for deriving a robust flux estimate.During the campaign, 39 flights were conducted, covering approximately 33 mines across roughly 20,000 km2, focussing on the northern part of the Bowen Basin. Preliminary MAMAP2D-Light measurements of atmospheric CH4 column anomalies and emission estimates for both open-cut and underground coal mines will be presented and discussed.

Tunable diode laser absorption spectrometers (TDLAS) are versatile devices with a wide range of applications. In particular, they can be used to detect methane using an analyzer that operates with an infrared band (1.6 – 1.7 μm) laser beam configured in an open path architecture. This setup is suitable for nonhomogeneous airflow coming from coal mine ventilation shafts. TDLAS devices are compact, robust, easy to install, and require minimal maintenance.Methane emissions from the coal mining sector in Poland account for approximately 0.5 million tons of methane per year and are significant contributors to the continental budget of this gas. Most of the emissions occur through the ventilation shafts, where the methane content can vary from 0.05% to 0.7%.During June 2023, a TDLAS analyzer (Unisearch, LasIR) was installed at a selected ventilation shaft air diffuser. The device operated for one month, recording the methane concentration in the ventilated air with a temporal resolution of 1 second. In addition to TDLAS, two other instruments were used to determine methane content: an ICOS analyzer (LGR/ABB, mGGA-918) and a pellistor sensor (EMAG, DCH). The ICOS analyzer was used to cross calibrate the TDLAS instrument across a wide range of methane concentrations. The pellistor sensor is a popular type of sensor used in coal mines for safety reasons. Typically, methane emissions are determined through gas chromatographic analyses conducted using periodically collected samples (e.g., once a month). However, methane content in ventilated air can vary on shorter timescales of hours, days, and weeks. Additionally, pellistor sensors are less precise, and the uncertainty of a single measurement cannot be better than 0.1%. In contrast, TDLAS analyzers can be commonly used by coal mine operators for methane reporting, as their precision is usually better than 0.01%.The presentation will address the challenges associated with using TDLAS for methane emission calculations and highlight its advantages over other commonly used techniques. It will also provide insights into interpreting pellistor sensor readings for quantifying methane emissions and assessing associated uncertainties. Finally, the presentation will discuss the benefits of deploying TDLAS techniques in the coal mining industry, both in the short term and as a potential long-term solution of the reporting of CH4 release. This research was funded by and performed in collaboration with UNEP's International Methane Emissions Observatory. The results presented here are part of the findings from a series of three measurement campaigns performed in Poland’s Upper Silesia coal basin.

Accurate and measurement-based methane data is urgently needed by countries to support science-based policy for the achievement of their methane reduction ambitions. The United Nations Environment Program (UNEP)’s International Methane Emissions Observatory (IMEO) is responding to this need by collecting and integrating diverse methane emissions data streams, one of which is data from Methane Science Studies funded by IMEO. IMEO’s Methane Science Studies (MSS) are making a difference through funding methane measurement studies and collaborating with scientists worldwide. The overarching aim of the MSS is to close the knowledge gaps and improve the understanding of the locations and magnitude of methane emissions across sectors, especially in regions where there is limited or no publicly available data. The studies have initially focused on the oil and gas sector but are now branching out into other anthropogenic sectors. By Jan 2024, IMEO has launched 35 studies around the world with 32 academic/research institutions and 22 peer-reviewed papers published so far. In Europe alone, IMEO has initiated 8 studies in countries including Romania, Poland, Germany, France, Netherlands, Norway, and the UK. In this presentation, we will provide an overview of i) the current scope of IMEO Methane Science Studies ii) key study achievements and findings of the completed studies, and iii) potential opportunities and resources for interested research institutes.

Methane is one of the most powerful greenhouse gases that has contributed to about a third of the 2010-2019 global warming relative to the pre-industrial times in 1850-1900. The Upper Silesian Coal Basin in southern Poland is one of the strongest anthropogenic methane (CH4) emitters in Europe, with emissions ranging from 228 to 339 ktCH4yr-1. In that region, ventilation shafts and drainage stations used in coal mines are the main sources of CH4 emissions, of which the mass flows and their sources of uncertainties can be assessed using an adapted version of the Integrated Mass Enhancement (IME) method.This challenge can be tackled using observations from Fabry-Perot imaging Short Wave InfraRed (SWIR) spectrometers onboard of the GHGSat aircraft and GHGSat satellite constellation. GHGSat acquisitions were made in June and July 2022 during a campaign including other measurements and which was partially funded in the framework of UNEP’s International Methane Emissions Observatory. The GHGSat level-2 data provide full-swath CH4 concentration estimations and filtered CH4 plumes with spatial resolutions < 1.1 m on a swath width < 0.75 km for the aircraft, and < 28 m on a swath width < 12 km for the satellites, both featuring a spectral resolution of 0.1 nm. Furthermore, another version of the methane plumes was generated through a Z-test filter.These observations were complemented with local wind profile and plume profile observations to estimate the effective wind speed that accounts for the effects of turbulent diffusion in the plume dissipation. This was achieved using two instruments from the University of Heidelberg: a wind lidar measuring the wind profile up to 200 m height at a sampling rate of ~8 seconds and a hyperspectral SWIR camera featuring a 1 min scanning time, a spatial resolution of 0.8 m and a spectral resolution of 7 nm. Since local wind profile measurements are rarely accessible, this study attempted to find a relationship between the effective wind speed for the methane plumes of that region as a function of the wind speed at 10 m height from the ERA5-Land reanalysis (spatial resolution of 9 km and temporal resolution of 1 h).Finally, a comparison is performed between the methane mass flow estimations derived from GHGSat satellites and aircraft observations with coinciding mass flow estimation from the CH4 safety sensors located inside four of the same ventilation shafts (data collected by AGH University of Kraków) and the hyperspectral camera in June and July 2022. Moreover, another comparison is done with data acquired from a helicopter towed probe (HELiPOD) operated by the DLR and the Technical University of Braunschweig over one of the same shafts in June 2022. While bottom-up inventories may have delays of a few years before being available and require a certain level of trust, satellites can solve these issues through a faster top-down approach but still with relatively high uncertainties and multiple sources. The findings presented in this study can help to quantify the level of contribution from the different sources of uncertainties with high resolution data.

Methane has a short atmospheric lifetime compared to carbon dioxide (CO2), ∼decade versus ∼centuries, but it has a much higher global warming potential (GWP), highlighting how reducing methane emissions can slow the rate of climate change. When considering the contribution of greenhouse gas (GHG) emissions to current global warming (2010–2019) relative to the industrial revolution (1850–1900) levels, methane contributes 0.5 °C or ∼ a third of the total. The most recent post-2023 global estimates of methane emissions by bottom-up (BU) and top-down (TD) approaches for the coal mining sector are in the range of ∼41 ± 3 Tg yr−1 and 33 ± 5 Tg yr−1, respectively. This divergence, notwithstanding overlapping confidence intervals, is a result of differences between applied TD global inversion models and BU emission inventories. Further research can help to better refine emissions from the various contributing coal mine methane (CMM) emissions sources. The coal mining sector accounts for over 10 % of global anthropogenic methane emissions. The contribution of CMM emissions to the global budget have increased since 2000, although upward and downward regional trends have been observed.The Global Methane Pledge (GMP), which was signed by more than 150 nations, aims to reduce methane emissions by 30 % from 2020 levels by 2030. This could eliminate 0.2 °C of warming by 2050. The success or failure to reach the emission reduction targets of the GMP will depend on engagement with different sectors of the economy. In that regard, the coal sector could play a significant role for mitigating emissions and reaching emission reduction targets. The International Energy Agency (IEA) and United States Environmental Protection Agency (U.S. EPA) both estimate that over half of global methane emissions from coal operations could be avoided with the application of existing technologies. However, setting up emission reduction scenario targets for the coal mining sector poses significant challenges, which require clear understanding of the magnitude and behavior of CMM emission sources. Notwithstanding regional differences, with improved reporting and data transparency, emission control potential can be more accurately defined, which can inform effective and defensible policy approaches.This paper highlights the climate forcing role of methane in the atmosphere and presents a detailed review of CMM emission sources along the coal lifecycle, traditional and new inventory practices applied in different countries, the status of estimating CMM emissions, and opportunities and difficulties associated with mitigating emissions from different CMM sources. Different policy approaches utilizing regulatory and economic mechanisms are explored and concluding remarks for importance and tools of CMM emission mitigation are provided. Ultimately, this paper aims to inform global CMM mitigation and emission reduction scenario targets for the coal mining sector.

POD diffusive samplers loaded with Carbopack X and Carbograph 5TD were exposed to certified calibration mixtures containing a total of 110 different ozone precursor and air toxic compounds. Constant sampling rates were identified for 39 ozone precursors and 33 air toxics. As 9 of these compounds were included in both mixtures, this meant a total of 63 different volatile and very volatile compounds were sampled using the POD with overall expanded uncertainties below 30 % for the sampling rate associated with the whole range of sampling times from 2 to 24 h.Carbograph 5TD exhibited superior performance for diffusive sampling of oxygenated and halogenated compounds in the air toxics mixture, while Carbopack X showed higher sampling efficiencies for aliphatic and aromatic hydrocarbons, as well as halogenated compounds derived from benzene and C2 carbon number hydrocarbons.A model has been developed and applied to estimate sampling rates, primarily for the more volatile and weakly adsorbed compounds, as a function of the collected amount of analyte and the exposure time. For an additional 9 ozone precursors on Carbopack X, and 11 air toxics on Carbograph 5TD, the expanded uncertainties of modelled sampling rates were reduced to below 30 % and have a significantly reduced uncertainty compared to those associated with an averaged sampling rate.The paper provides Freundlich's isotherm parameters for the estimated (modelled) sampling rates and defines a pragmatic approach to their application. It does so by identifying the best sampling time to use for the expected exposure concentrations and associated analyte masses. This allows for expansion of the sampling concentration range from hundreds ng m- 3 to mg m- 3, while avoiding saturation of the adsorbent.Finally, field measurement comparisons of POD samplers, pumped tube samplers and online gas chromatography (GC), for sampling periods of 3 and 7 days in a semi-rural background area, showed no significant differences between reported concentrations.

Hydrogen has a potentially important future role as a replacement for natural gas in the domestic sector in a zero-carbon economy for heating homes and cooking. To assess this potential, an understanding is required of the global warming potentials (GWPs) of methane and hydrogen and of the leakage rates of the natural gas distribution system and that of a hydrogen system that would replace it. The GWPs of methane and hydrogen were estimated using a global chemistry-transport model as 29.2 +/- 8 and 3.3 +/- 1.4, respectively, over a 100-year time horizon. The current natural gas leakage rates from the distribution system have been estimated for the UK by the ethane tracer method to be about 0.64 Tg CH4/year (2.3%) and for the US by literature review to be of the order of 0.69-2.9 Tg CH4/ year (0.5-2.1%). On this basis, with the inclusion of carbon dioxide emissions from combustion, replacing natural gas with green hydrogen in the domestic sectors of both countries should reduce substantially the global warming consequences of domestic sector energy use both in the UK and in the US, provided care is taken to reduce hydrogen leakage to a minimum. A perfectly sealed zero-carbon green hydrogen distribution system would save the entire 76 million tonnes CO2 equivalent per year in the UK. (c) 2021 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved. Superscript/Subscript Available

Other Test Method 33A (OTM 33A) is a near-source flux measurement method developed by the Environmental Protection Agency (EPA) primarily used to locate and estimate emission fluxes of methane from oil and gas (O&G) production facilities without requiring site access. A recent national estimate of methane emissions from O&G production included a large number of flux measurements of upstream O&G facilities made using OTM 33A and concluded the EPA National Emission Inventory underestimates this sector by a factor of ∼2.1 (Alvarez et al., 2018). The study presented here investigates the accuracy of OTM 33A through a series of test releases performed at the Methane Emissions Technology Evaluation Center (METEC), a facility designed to allow quantified amounts of natural gas to be released from decommissioned O&G equipment to simulate emissions from real facilities (Fig. 1). This study includes test releases from single and multiple points, from equipment locations at different heights, and spanned methane release rates ranging from 0.16 to 2.15 kg h−1. Approximately 95 % of individual measurements (N=45) fell within ±70 % of the known release rate. A simple linear regression of OTM 33A versus known release rates at the METEC site gives an average slope of 0.96 with 95 % CI (0.66,1.28), suggesting that an ensemble of OTM 33A measurements may have a small but statistically insignificant low bias.

Methane emission fluxes were estimated for 71 oil and gas well pads in the western Permian Basin (Delaware Basin), using a mobile laboratory and an inverse Gaussian dispersion method (OTM 33A). Sites with emissions that were below detection limit (BDL) for OTM 33A were recorded and included in the sample. Average emission rate per site was estimated by bootstrapping and by maximum likelihood best log-normal fit. Sites had to be split into "complex" (sites with liquid storage tanks and/or compressors) and "simple" (sites with only wellheads/pump jacks/separators) categories to achieve acceptable log-normal fits. For complex sites, the log-normal fit depends heavily on the number of BDL sites included. As more BDL sites are included, the log-normal distribution fit to the data is falsely widened, overestimating the mean, highlighting the importance of correctly characterizing low end emissions when using log-normal fits. Basin-wide methane emission rates were estimated for the production sector of the New Mexico portion of the Permian and range from ∼520 000 tons per year, TPY (bootstrapping, 95% CI: 300 000-790 000) to ∼610 000 TPY (log-normal fit method, 95% CI: 330 000-1 000 000). These estimates are a factor of 5.5-9.0 times greater than EPA National Emission Inventory (NEI) estimates for the region.

Flux estimates of volatile organic compounds (VOCs) from oil and gas (O&G) production facilities are fundamental in understanding hazardous air pollutant concentrations and ozone formation. Previous off-site emission estimates derive fluxes by ratioing VOCs measured in canisters to methane fluxes measured in the field. This study uses the Environmental Protection Agency's Other Test Method 33A (OTM 33A) and a fast-response proton transfer reaction mass spectrometer to make direct measurements of VOC emissions from O&G facilities in the Upper Green River Basin, Wyoming. We report the first off-site direct flux estimates of benzene, toluene, ethylbenzene, and xylenes from upstream O&G production facilities and find that these estimates can vary significantly from flux estimates derived using both the canister ratio technique and from the emission inventory. The 32 OTM 33A flux estimates had arithmetic mean (and 95% CI) as follows: benzene 17.83 (0.22, 98.05) g/h, toluene 34.43 (1.01, 126.76) g/h, C8 aromatics 37.38 (1.06, 225.34) g/h, and methane 2.3 (1.7, 3.1) kg/h. A total of 20% of facilities measured accounted for ∼67% of total BTEX emissions. While this heavy tail is less dramatic than previous observations of methane in other basins, it is more prominent than that predicted by the emission inventory.

Atmospheric methane emissions from active natural gas production sites in normal operation were quantified using an inverse Gaussian method (EPA's OTM 33a) in four major U.S. basins/plays: Upper Green River (UGR, Wyoming), Denver-Julesburg (DJ, Colorado), Uintah (Utah), and Fayetteville (FV, Arkansas). In DJ, Uintah, and FV, 72-83% of total measured emissions were from 20% of the well pads, while in UGR the highest 20% of emitting well pads only contributed 54% of total emissions. The total mass of methane emitted as a percent of gross methane produced, termed throughput-normalized methane average (TNMA) and determined by bootstrapping measurements from each basin, varied widely between basins and was (95% CI): 0.09% (0.05-0.15%) in FV, 0.18% (0.12-0.29%) in UGR, 2.1% (1.1-3.9%) in DJ, and 2.8% (1.0-8.6%) in Uintah. Overall, wet-gas basins (UGR, DJ, Uintah) had higher TNMA emissions than the dry-gas FV at all ranges of production per well pad. Among wet basins, TNMA emissions had a strong negative correlation with average gas production per well pad, suggesting that consolidation of operations onto single pads may reduce normalized emissions (average number of wells per pad is 5.3 in UGR versus 1.3 in Uintah and 2.8 in DJ).