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Atmospheric methane (CH4) is the second-most-important anthropogenic greenhouse gas and has a 20-year global warming potential 82 times greater than carbon dioxide (CO2). Anthropogenic sources account for ∼ 60 % of global CH4 emissions, of which 20 % come from oil and gas exploration, production and distribution. High-resolution satellite-based imaging spectrometers are becoming important tools for detecting and monitoring CH4 point source emissions, aiding mitigation. However, validation of these satellite measurements, such as those from the commercial GHGSat satellite constellation, has so far not been documented for active leaks. Here we present the monitoring and quantification, by GHGSat's satellites, of the CH4 emissions from an active gas leak from a downstream natural gas distribution pipeline near Cheltenham, UK, in the spring and summer of 2023 and provide the first validation of the satellite-derived emission estimates using surface-based mobile greenhouse gas surveys. We also use a Lagrangian transport model, the UK Met Office's Numerical Atmospheric-dispersion Modelling Environment (NAME), to estimate the flux from both satellite- and ground-based observation methods and assess the leak's contribution to observed concentrations at a local tall tower site (30 km away). We find GHGSat's emission estimates to be in broad agreement with those made from the in situ measurements. During the study period (March–June 2023) GHGSat's emission estimates are 236–1357 kg CH4 h−1, whereas the mobile surface measurements are 634–846 kg CH4 h−1. The large variability is likely down to variations in flow through the pipe and engineering works across the 11-week period. Modelled flux estimates in NAME are 181–1243 kg CH4 h−1, which are lower than the satellite- and mobile-survey-derived fluxes but are within the uncertainty. After detecting the leak in March 2023, the local utility company was contacted, and the leak was fixed by mid-June 2023. Our results demonstrate that GHGSat's observations can produce flux estimates that broadly agree with surface-based mobile measurements. Validating the accuracy of the information provided by targeted, high-resolution satellite monitoring shows how it can play an important role in identifying emission sources, including unplanned fugitive releases that are inherently challenging to identify, track, and estimate their impact and duration. Rapid, widespread access to such data to inform local action to address fugitive emission sources across the oil and gas supply chain could play a significant role in reducing anthropogenic contributions to climate change.

Atmospheric methane (CH4) concentrations have more than doubled since the beginning of the industrial age, making CH4 the second most important anthropogenic greenhouse gas after carbon dioxide (CO2). The oil and gas sector represents one of the major anthropogenic CH4 emitters as it is estimated to account for 22 % of global anthropogenic CH4 emissions. An airborne field campaign was conducted in April–May 2019 to study CH4 emissions from offshore gas facilities in the southern North Sea with the aim of deriving emission estimates using a top-down (measurement-led) approach. We present CH4 fluxes for six UK and five Dutch offshore platforms or platform complexes using the well-established mass balance flux method. We identify specific gas production emissions and emission processes (venting and fugitive or flaring and combustion) using observations of co-emitted ethane (C2H6) and CO2. We compare our top-down estimated fluxes with a ship-based top-down study in the Dutch sector and with bottom-up estimates from a globally gridded annual inventory, UK national annual point-source inventories, and operator-based reporting for individual Dutch facilities. In this study, we find that all the inventories, except for the operator-based facility-level reporting, underestimate measured emissions, with the largest discrepancy observed with the globally gridded inventory. Individual facility reporting, as available for Dutch sites for the specific survey date, shows better agreement with our measurement-based estimates. For all the sampled Dutch installations together, we find that our estimated flux of (122.9 ± 36.8) kg h−1 deviates by a factor of 0.64 (0.33–12) from reported values (192.8 kg h−1). Comparisons with aircraft observations in two other offshore regions (the Norwegian Sea and the Gulf of Mexico) show that measured, absolute facility-level emission rates agree with the general distribution found in other offshore basins despite different production types (oil, gas) and gas production rates, which vary by 2 orders of magnitude. Therefore, mitigation is warranted equally across geographies.

In-flight measurements of atmospheric methane (CH4(a)) and mass balance flux quantification studies can assist with verification and improvement in the UNFCCC National Inventory reported CH4 emissions. In the Surat Basin gas fields, Queensland, Australia, coal seam gas (CSG) production and cattle farming are two of the major sources of CH4 emissions into the atmosphere. Because of the rapid mixing of adjacent plumes within the convective boundary layer, spatially attributing CH4(a) mole fraction readings to one or more emission sources is difficult. The primary aims of this study were to use the CH4(a) isotopic composition (δ13CCH4(a)) of in-flight atmospheric air (IFAA) samples to assess where the bottom–up (BU) inventory developed specifically for the region was well characterised and to identify gaps in the BU inventory (missing sources or over- and underestimated source categories). Secondary aims were to investigate whether IFAA samples collected downwind of predominantly similar inventory sources were useable for characterising the isotopic signature of CH4 sources (δ13CCH4(s)) and to identify mitigation opportunities. IFAA samples were collected between 100–350 m above ground level (m a.g.l.) over a 2-week period in September 2018. For each IFAA sample the 2 h back-trajectory footprint area was determined using the NOAA HYSPLIT atmospheric trajectory modelling application. IFAA samples were gathered into sets, where the 2 h upwind BU inventory had > 50 % attributable to a single predominant CH4 source (CSG, grazing cattle, or cattle feedlots). Keeling models were globally fitted to these sets using multiple regression with shared parameters (background-air CH4(b) and δ13CCH4(b)). For IFAA samples collected from 250–350 m a.g.l. altitude, the best-fit δ13CCH4(s) signatures compare well with the ground observation: CSG δ13CCH4(s) of −55.4 ‰ (confidence interval (CI) 95 % ± 13.7 ‰) versus δ13CCH4(s) of −56.7 ‰ to −45.6 ‰; grazing cattle δ13CCH4(s) of −60.5 ‰ (CI 95 % ± 15.6 ‰) versus −61.7 ‰ to −57.5 ‰. For cattle feedlots, the derived δ13CCH4(s) (−69.6 ‰, CI 95 % ± 22.6 ‰), was isotopically lighter than the ground-based study (δ13CCH4(s) from −65.2 ‰ to −60.3 ‰) but within agreement given the large uncertainty for this source. For IFAA samples collected between 100–200 m a.g.l. the δ13CCH4(s) signature for the CSG set (−65.4 ‰, CI 95 % ± 13.3 ‰) was isotopically lighter than expected, suggesting a BU inventory knowledge gap or the need to extend the population statistics for CSG δ13CCH4(s) signatures. For the 100–200 m a.g.l. set collected over grazing cattle districts the δ13CCH4(s) signature (−53.8 ‰, CI 95 % ± 17.4 ‰) was heavier than expected from the BU inventory. An isotopically light set had a low δ13CCH4(s) signature of −80.2 ‰ (CI 95 % ± 4.7 ‰). A CH4 source with this low δ13CCH4(s) signature has not been incorporated into existing BU inventories for the region. Possible sources include termites and CSG brine ponds. If the excess emissions are from the brine ponds, they can potentially be mitigated. It is concluded that in-flight atmospheric δ13CCH4(a) measurements used in conjunction with endmember mixing modelling of CH4 sources are powerful tools for BU inventory verification.

Recent climate change mitigation strategies rely on the reduction of methane (CH4) emissions. Carbon and hydrogen isotope ratio (δ13CCH4 and δ2HCH4) measurements can be used to distinguish sources and thus to understand the CH4 budget better. The CH4 emission estimates by models are sensitive to the isotopic signatures assigned to each source category, so it is important to provide representative estimates of the different CH4 source isotopic signatures worldwide. We present new measurements of isotope signatures of various, mainly anthropogenic, CH4 sources in Europe, which represent a substantial contribution to the global dataset of source isotopic measurements from the literature, especially for δ2HCH4. They improve the definition of δ13CCH4 from waste sources, and demonstrate the use of δ2HCH4 for fossil fuel source attribution. We combined our new measurements with the last published database of CH4 isotopic signatures and with additional literature, and present a new global database. We found that microbial sources are generally well characterised. The large variability in fossil fuel isotopic compositions requires particular care in the choice of weighting criteria for the calculation of a representative global value. The global dataset could be further improved by measurements from African, South American, and Asian countries, and more measurements from pyrogenic sources. We improved the source characterisation of CH4 emissions using stable isotopes and associated uncertainty, to be used in top-down studies. We emphasise that an appropriate use of the database requires the analysis of specific parameters in relation to source type and the region of interest. The final version of the European CH4 isotope database coupled with a global inventory of fossil and non-fossil δ13CCH4 and δ2HCH4 source signature measurements is available at https://doi.org/10.24416/UU01-YP43IN (Menoud et al., 2022a).

The oil and gas (O&G) sector is a significant source of methane (CH4) emissions. Quantifying these emissions remains challenging, with many studies highlighting discrepancies between measurements and inventory-based estimates. In this study, we present CH4 emission fluxes from 21 offshore O&G facilities collected in 10 O&G fields over two regions of the Norwegian continental shelf in 2019. Emissions of CH4 derived from measurements during 13 aircraft surveys were found to range from 2.6 to 1200 t yr−1 (with a mean of 211 t yr−1 across all 21 facilities). Comparing this with aggregated operator-reported facility emissions for 2019, we found excellent agreement (within 1σ uncertainty), with mean aircraft-measured fluxes only 16 % lower than those reported by operators. We also compared aircraft-derived fluxes with facility fluxes extracted from a global gridded fossil fuel CH4 emission inventory compiled for 2016. We found that the measured emissions were 42 % larger than the inventory for the area covered by this study, for the 21 facilities surveyed (in aggregate). We interpret this large discrepancy not to reflect a systematic error in the operator-reported emissions, which agree with measurements, but rather the representativity of the global inventory due to the methodology used to construct it and the fact that the inventory was compiled for 2016 (and thus not representative of emissions in 2019). This highlights the need for timely and up-to-date inventories for use in research and policy. The variable nature of CH4 emissions from individual facilities requires knowledge of facility operational status during measurements for data to be useful in prioritising targeted emission mitigation solutions. Future surveys of individual facilities would benefit from knowledge of facility operational status over time. Field-specific aggregated emissions (and uncertainty statistics), as presented here for the Norwegian Sea, can be meaningfully estimated from intensive aircraft surveys. However, field-specific estimates cannot be reliably extrapolated to other production fields without their own tailored surveys, which would need to capture a range of facility designs, oil and gas production volumes, and facility ages. For year-on-year comparison to annually updated inventories and regulatory emission reporting, analogous annual surveys would be needed for meaningful top-down validation. In summary, this study demonstrates the importance and accuracy of detailed, facility-level emission accounting and reporting by operators and the use of airborne measurement approaches to validate bottom-up accounting.

The Zeppelin Observatory (78.90∘ N, 11.88∘ E) is located on Zeppelin Mountain at 472 m a.s.l. on Spitsbergen, the largest island of the Svalbard archipelago. Established in 1989, the observatory is part of Ny-Ålesund Research Station and an important atmospheric measurement site, one of only a few in the high Arctic, and a part of several European and global monitoring programmes and research infrastructures, notably the European Monitoring and Evaluation Programme (EMEP); the Arctic Monitoring and Assessment Programme (AMAP); the Global Atmosphere Watch (GAW); the Aerosol, Clouds and Trace Gases Research Infrastructure (ACTRIS); the Advanced Global Atmospheric Gases Experiment (AGAGE) network; and the Integrated Carbon Observation System (ICOS). The observatory is jointly operated by the Norwegian Polar Institute (NPI), Stockholm University, and the Norwegian Institute for Air Research (NILU). Here we detail the establishment of the Zeppelin Observatory including historical measurements of atmospheric composition in the European Arctic leading to its construction. We present a history of the measurements at the observatory and review the current state of the European Arctic atmosphere, including results from trends in greenhouse gases, chlorofluorocarbons (CFCs) and hydrochlorofluorocarbons (HCFCs), other traces gases, persistent organic pollutants (POPs) and heavy metals, aerosols and Arctic haze, and atmospheric transport phenomena, and provide an outline of future research directions.

Quantitative satellite observations only provide an assessment of ice sheet mass loss over the last four decades. To assess long-term drivers of ice sheet change, geological records are needed. Here we present the first millennial-scale reconstruction of David Glacier, the largest East Antarctic outlet glacier in Victoria Land. To reconstruct changes in ice thickness, we use surface exposure ages of glacial erratics deposited on nunataks adjacent to fast-flowing sections of David Glacier. We then use numerical modelling experiments to determine the drivers of glacial thinning. Thinning profiles derived from 45 10Be and 3He surface exposure ages show David Glacier experienced rapid thinning of up to 2 m/yr during the mid-Holocene (∼ 6.5 ka). Thinning slowed at 6 ka, suggesting the initial formation of the Drygalski Ice Tongue at this time. Our work, along with ice thinning records from adjacent glaciers, shows simultaneous glacier thinning in this sector of the Transantarctic Mountains occurred 4–7 kyr after the peak period of ice thinning indicated in a suite of published ice sheet models. The timing and rapidity of the reconstructed thinning at David Glacier is similar to reconstructions in the Amundsen and Weddell embayments. To identify the drivers of glacier thinning along the David Glacier, we use a glacier flowline model designed for calving glaciers and compare modelled results against our geological data. We show that glacier thinning and marine-based grounding-line retreat are controlled by either enhanced sub-ice-shelf melting, reduced lateral buttressing or a combination of the two, leading to marine ice sheet instability. Such rapid glacier thinning events during the mid-Holocene are not fully captured in continental- or catchment-scale numerical modelling reconstructions. Together, our chronology and modelling identify and constrain the drivers of a ∼ 2000-year period of dynamic glacier thinning in the recent geological past.

In regions where there are multiple sources of methane (CH4) in close proximity, it can be difficult to apportion the CH4 measured in the atmosphere to the appropriate sources. In the Surat Basin, Queensland, Australia, coal seam gas (CSG) developments are surrounded by cattle feedlots, grazing cattle, piggeries, coal mines, urban centres and natural sources of CH4. The characterization of carbon (δ13C) and hydrogen (δD) stable isotopic composition of CH4 can help distinguish between specific emitters of CH4. However, in Australia there is a paucity of data on the various isotopic signatures of the different source types. This research examines whether dual isotopic signatures of CH4 can be used to distinguish between sources of CH4 in the Surat Basin. We also highlight the benefits of sampling at nighttime. During two campaigns in 2018 and 2019, a mobile CH4 monitoring system was used to detect CH4 plumes. Sixteen plumes immediately downwind from known CH4 sources (or individual facilities) were sampled and analysed for their CH4 mole fraction and δ13CCH4 and δDCH4 signatures. The isotopic signatures of the CH4 sources were determined using the Keeling plot method. These new source signatures were then compared to values documented in reports and peer-reviewed journal articles. In the Surat Basin, CSG sources have δ13CCH4 signatures between −55.6 ‰ and −50.9 ‰ and δDCH4 signatures between −207.1 ‰ and −193.8 ‰. Emissions from an open-cut coal mine have δ13CCH4 and δDCH4 signatures of -60.0±0.6 ‰ and -209.7±1.8 ‰ respectively. Emissions from two ground seeps (abandoned coal exploration wells) have δ13CCH4 signatures of -59.9±0.3 ‰ and -60.5±0.2 ‰ and δDCH4 signatures of -185.0±3.1 ‰ and -190.2±1.4 ‰. A river seep had a δ13CCH4 signature of -61.2±1.4 ‰ and a δDCH4 signature of -225.1±2.9 ‰. Three dominant agricultural sources were analysed. The δ13CCH4 and δDCH4 signatures of a cattle feedlot are -62.9±1.3 ‰ and -310.5±4.6 ‰ respectively, grazing (pasture) cattle have δ13CCH4 and δDCH4 signatures of -59.7±1.0 ‰ and -290.5±3.1 ‰ respectively, and a piggery sampled had δ13CCH4 and δDCH4 signatures of -47.6±0.2 ‰ and -300.1±2.6 ‰ respectively, which reflects emissions from animal waste. An export abattoir (meat works and processing) had δ13CCH4 and δDCH4 signatures of -44.5±0.2 ‰ and -314.6±1.8 ‰ respectively. A plume from a wastewater treatment plant had δ13CCH4 and δDCH4 signatures of -47.6±0.2 ‰ and -177.3±2.3 ‰ respectively. In the Surat Basin, source attribution is possible when both δ13CCH4 and δDCH4 are measured for the key categories of CSG, cattle, waste from feedlots and piggeries, and water treatment plants. Under most field situations using δ13CCH4 alone will not enable clear source attribution. It is common in the Surat Basin for CSG and feedlot facilities to be co-located. Measurement of both δ13CCH4 and δDCH4 will assist in source apportionment where the plumes from two such sources are mixed.

Emissions of methane (CH4) from offshore oil and gas installations are poorly ground-truthed, and quantification relies heavily on the use of emission factors and activity data. As part of the United Nations Climate & Clean Air Coalition (UN CCAC) objective to study and reduce short-lived climate pollutants (SLCPs), a Twin Otter aircraft was used to survey CH4 emissions from UK and Dutch offshore oil and gas installations. The aims of the surveys were to (i) identify installations that are significant CH4 emitters, (ii) separate installation emissions from other emissions using carbon-isotopic fingerprinting and other chemical proxies, (iii) estimate CH4 emission rates, and (iv) improve flux estimation (and sampling) methodologies for rapid quantification of major gas leaks. In this paper, we detail the instrument and aircraft set-up for two campaigns flown in the springs of 2018 and 2019 over the southern North Sea and describe the developments made in both the planning and sampling methodology to maximise the quality and value of the data collected. We present example data collected from both campaigns to demonstrate the challenges encountered during offshore surveys, focussing on the complex meteorology of the marine boundary layer and sampling discrete plumes from an airborne platform. The uncertainties of CH4 flux calculations from measurements under varying boundary layer conditions are considered, as well as recommendations for attribution of sources through either spot sampling for volatile organic compounds (VOCs) ∕ δ13CCH4 or using in situ instrumental data to determine C2H6–CH4 ratios. A series of recommendations for both planning and measurement techniques for future offshore work within marine boundary layers is provided.

Atmospheric methane (CH4) continues to increase, but there are multiple anthropogenic source categories that can be targeted for cost-effective emissions reduction. Cities emit CH4 to the atmosphere from a mixture of anthropogenic CH4 sources, which include, but are not limited to, fugitive emissions from natural gas distribution systems, wastewater treatment facilities, waste-and rainwater networks, and landfills. Therefore, to target mitigation measures, it is important to locate and quantify local urban emissions to prioritize mitigation opportunities in large cities. Using mobile measurement techniques, we located street-level CH4 leak indications, measured flux rates, and determined potential source origins (using carbon and hydrogen stable isotopic composition along with ethane: CH4 ratios) of CH4 in Bucharest, Romania. We found 969 confirmed CH4 leak indication locations, where the maximum mole fraction elevation (above background) was 38.3 ppm (mean = 0.9 ppm ± 0.1 ppm s.e.; n = 2482). Individual leak indicator fluxes, derived using a previously established empirical relation, ranged up to around 15 metric tons CH4 yr-1 (mean = 0.8 metric tons yr-1 ± 0.05, s.e.; n = 969). The total estimated city emission rate is 1832 tons CH4 yr-1 (min = 1577 t yr-1 and max = 2113 t yr-1). More than half (58%–63%) of the CH4 elevations were attributed to biogenic wastewater, mostly from venting storm grates and manholes connecting to sewer pipelines. Hydrogen isotopic composition of CH4 and ethane:methane ratios were the most useful tracers of CH4 sources, due to similarities in carbon isotope ratios between wastewater gas and natural gas. The annual city-wide CH4 emission estimate of Bucharest exceeded emissions of Hamburg, Germany by 76% and Paris, France by 90%.

Since 1850 the concentration of atmospheric methane (CH4), a potent greenhouse gas, has more than doubled. Recent studies suggest that emission inventories may be missing sources and underestimating emissions. To investigate whether offshore oil and gas platforms leak CH4 during normal operation, we measured CH4 mole fractions around eight oil and gas production platforms in the North Sea which were neither flaring gas nor offloading oil. We use the measurements from summer 2017, along with meteorological data, in a Gaussian plume model to estimate CH4 emissions from each platform. We find CH4 mole fractions of between 11 and 370 ppb above background concentrations downwind of the platforms measured, corresponding to a median CH4 emission of 6.8 g CH4 s−1 for each platform, with a range of 2.9 to 22.3 g CH4 s−1. When matched to production records, during our measurements individual platforms lost between 0.04 % and 1.4 % of gas produced with a median loss of 0.23 %. When the measured platforms are considered collectively (i.e. the sum of platforms' emission fluxes weighted by the sum of the platforms' production), we estimate the CH4 loss to be 0.19 % of gas production. These estimates are substantially higher than the emissions most recently reported to the National Atmospheric Emission Inventory (NAEI) for total CH4 loss from United Kingdom platforms in the North Sea. The NAEI reports CH4 losses from the offshore oil and gas platforms we measured to be 0.13 % of gas production, with most of their emissions coming from gas flaring and offshore oil loading, neither of which was taking place at the time of our measurements. All oil and gas platforms we observed were found to leak CH4 during normal operation, and much of this leakage has not been included in UK emission inventories. Further research is required to accurately determine total CH4 leakage from all offshore oil and gas operations and to properly include the leakage in national and international emission inventories.

Ice sheet numerical modeling is an important tool to estimate the dynamic contribution of the Antarctic ice sheet to sea level rise over the coming centuries. The influence of initial conditions on ice sheet model simulations, however, is still unclear. To better understand this influence, an initial state intercomparison exercise (initMIP) has been developed to compare, evaluate, and improve initialization procedures and estimate their impact on century-scale simulations. initMIP is the first set of experiments of the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6), which is the primary Coupled Model Intercomparison Project Phase 6 (CMIP6) activity focusing on the Greenland and Antarctic ice sheets. Following initMIP-Greenland, initMIP-Antarctica has been designed to explore uncertainties associated with model initialization and spin-up and to evaluate the impact of changes in external forcings. Starting from the state of the Antarctic ice sheet at the end of the initialization procedure, three forward experiments are each run for 100 years: a control run, a run with a surface mass balance anomaly, and a run with a basal melting anomaly beneath floating ice. This study presents the results of initMIP-Antarctica from 25 simulations performed by 16 international modeling groups. The submitted results use different initial conditions and initialization methods, as well as ice flow model parameters and reference external forcings. We find a good agreement among model responses to the surface mass balance anomaly but large variations in responses to the basal melting anomaly. These variations can be attributed to differences in the extent of ice shelves and their upstream tributaries, the numerical treatment of grounding line, and the initial ocean conditions applied, suggesting that ongoing efforts to better represent ice shelves in continental-scale models should continue.

Methane (CH4) is a powerful greenhouse gas. Its atmospheric mixing ratios have been increasing since 2005. Therefore, quantification of CH4 sources is essential for effective climate change mitigation. Here we report observations of the CH4 mixing ratios measured at the Zeppelin Observatory (Svalbard) in the Arctic and aboard the research vessel (RV) Helmer Hanssen over the Arctic Ocean from June 2014 to December 2016, as well as the long-term CH4 trend measured at the Zeppelin Observatory from 2001 to 2017. We investigated areas over the European Arctic Ocean to identify possible hotspot regions emitting CH4 from the ocean to the atmosphere, and used state-of-the-art modelling (FLEXPART) combined with updated emission inventories to identify CH4 sources. Furthermore, we collected air samples in the region as well as samples of gas hydrates, obtained from the sea floor, which we analysed using a new technique whereby hydrate gases are sampled directly into evacuated canisters. Using this new methodology, we evaluated the suitability of ethane and isotopic signatures (δ13C in CH4) as tracers for ocean-to-atmosphere CH4 emission. We found that the average methane / light hydrocarbon (ethane and propane) ratio is an order of magnitude higher for the same sediment samples using our new methodology compared to previously reported values, 2379.95 vs. 460.06, respectively. Meanwhile, we show that the mean atmospheric CH4 mixing ratio in the Arctic increased by 5.9±0.38 parts per billion by volume (ppb) per year (yr−1) from 2001 to 2017 and ∼8 pbb yr−1 since 2008, similar to the global trend of ∼ 7–8 ppb yr−1. Most large excursions from the baseline CH4 mixing ratio over the European Arctic Ocean are due to long-range transport from land-based sources, lending confidence to the present inventories for high-latitude CH4 emissions. However, we also identify a potential hotspot region with ocean–atmosphere CH4 flux north of Svalbard (80.4∘ N, 12.8∘ E) of up to 26 nmol m−2 s−1 from a large mixing ratio increase at the location of 30 ppb. Since this flux is consistent with previous constraints (both spatially and temporally), there is no evidence that the area of interest north of Svalbard is unique in the context of the wider Arctic. Rather, because the meteorology at the time of the observation was unique in the context of the measurement time series, we obtained over the short course of the episode measurements highly sensitive to emissions over an active seep site, without sensitivity to land-based emissions.

An uncontrolled gas leak from 25 March to 16 May 2012 led to evacuation of the Total Elgin wellhead and neighbouring drilling and production platforms in the UK North Sea. Initially the atmospheric flow rate of leaking gas and condensate was very poorly known, hampering environmental assessment and well control efforts. Six flights by the UK FAAM chemically instrumented BAe-146 research aircraft were used to quantify the flow rate. The flow rate was calculated by assuming the plume may be modelled by a Gaussian distribution with two different solution methods: Gaussian fitting in the vertical and fitting with a fully mixed layer. When both solution methods were used they compared within 6 % of each other, which was within combined errors. Data from the first flight on 30 March 2012 showed the flow rate to be 1.3 ± 0.2 kg CH4 s−1, decreasing to less than half that by the second flight on 17 April 2012. δ13CCH4 in the gas was found to be −43 ‰, implying that the gas source was unlikely to be from the main high pressure, high temperature Elgin gas field at 5.5 km depth, but more probably from the overlying Hod Formation at 4.2 km depth. This was deemed to be smaller and more manageable than the high pressure Elgin field and hence the response strategy was considerably simpler. The first flight was conducted within 5 days of the blowout and allowed a flow rate estimate within 48 h of sampling, with δ13CCH4 characterization soon thereafter, demonstrating the potential for a rapid-response capability that is widely applicable to future atmospheric emissions of environmental concern. Knowledge of the Elgin flow rate helped inform subsequent decision making. This study shows that leak assessment using appropriately designed airborne plume sampling strategies is well suited for circumstances where direct access is difficult or potentially dangerous. Measurements such as this also permit unbiased regulatory assessment of potential impact, independent of the emitting party, on timescales that can inform industry decision makers and assist rapid-response planning by government.

We report results from a worldwide interlaboratory comparison of samples among laboratories that measure (or measured) stable carbon and hydrogen isotope ratios of atmospheric CH4 (δ13C-CH4 and δD-CH4). The offsets among the laboratories are larger than the measurement reproducibility of individual laboratories. To disentangle plausible measurement offsets, we evaluated and critically assessed a large number of intercomparison results, some of which have been documented previously in the literature. The results indicate significant offsets of δ13C-CH4 and δD-CH4 measurements among data sets reported from different laboratories; the differences among laboratories at modern atmospheric CH4 level spread over ranges of 0.5 ‰ for δ13C-CH4 and 13 ‰ for δD-CH4. The intercomparison results summarized in this study may be of help in future attempts to harmonize δ13C-CH4 and δD-CH4 data sets from different laboratories in order to jointly incorporate them into modelling studies. However, establishing a merged data set, which includes δ13C-CH4 and δD-CH4 data from multiple laboratories with desirable compatibility, is still challenging due to differences among laboratories in instrument settings, correction methods, traceability to reference materials and long-term data management. Further efforts are needed to identify causes of the interlaboratory measurement offsets and to decrease those to move towards the best use of available δ13C-CH4 and δD-CH4 data sets.

Abstract A thorough understanding of methane sources is necessary to accomplish methane reduction targets. Urban environments, where a large variety of methane sources coexist, are one of the most complex areas to investigate. Methane sources are characterised by specific δ13C-CH4 signatures, so high precision stable isotope analysis of atmospheric methane can be used to give a better understanding of urban sources and their partition in a source mix. Diurnal measurements of methane and carbon dioxide mole fraction, and isotopic values at King’s College London, enabled assessment of the isotopic signal of the source mix in central London. Surveys with a mobile measurement system in the London region were also carried out for detection of methane plumes at near ground level, in order to evaluate the spatial allocation of sources suggested by the inventories. The measured isotopic signal in central London (−45.7 ±0.5‰) was more than 2‰ higher than the isotopic value calculated using emission inventories and updated δ13C-CH4 signatures. Besides, during the mobile surveys, many gas leaks were identified that are not included in the inventories. This suggests that a revision of the source distribution given by the emission inventories is needed.

High methane (CH4) mixing ratios (up to 4 ppm) have occurred sporadically at our measurement site in Haddenham, Cambridgeshire, since July 2012. Isotopic measurements and back trajectories show that the source is the Waterbeach Waste Management Park 7 km SE of Haddenham. To investigate this further, measurements were made on 30 June and 1 July 2015 at other locations nearer to the source. Landfill emissions have been estimated using three different approaches at different scales; near source using the WindTrax inversion dispersion model, middle distance using a Gaussian plume (GP) model and at the landscape scale using the Numerical Atmospheric Modelling Environment (NAME) Inversion Technique for Emission Modelling (InTEM) inversion. The emission estimates derived using the WindTrax and Gaussian plume (GP) approaches agree well for the period of intense observations. Applying the Gaussian plume approach to all periods of elevated measurements seen at Haddenham produces year-round and monthly landfill emission estimates with an estimated annual emission of 11.6 Gg CH4 yr−1. The monthly emission estimates are highest in winter (2160 kg h−1 in February) and lowest in summer (620 kg h−1 in July). These data identify the effects of environmental conditions on landfill CH4 production and highlight the importance of year-round measurements to capture seasonal variability in CH4 emission.

We present a global methane modelling study assessing the sensitivity of Arctic atmospheric CH4 mole fractions, δ13C-CH4 and δD-CH4 to uncertainties in Arctic methane sources. Model simulations include methane tracers tagged by source and isotopic composition and are compared with atmospheric data at four northern high-latitude measurement sites. We find the model's ability to capture the magnitude and phase of observed seasonal cycles of CH4 mixing ratios, δ13C-CH4 and δD-CH4 at northern high latitudes is much improved using a later spring kick-off and autumn decline in northern high-latitude wetland emissions than predicted by most process models. Results from our model simulations indicate that recent predictions of large methane emissions from thawing submarine permafrost in the East Siberian Arctic Shelf region could only be reconciled with global-scale atmospheric observations by making large adjustments to high-latitude anthropogenic or wetland emission inventories.

Currently, the atmospheric methane burden is rising rapidly, but the extent to which shifts in coal production contribute to this rise is not known. Coalbed methane emissions into the atmosphere are poorly characterised, and this study provides representative δ13CCH4 signatures of methane emissions from specific coalfields. Integrated methane emissions from both underground and opencast coal mines in the UK, Australia and Poland were sampled and isotopically characterised. Progression in coal rank and secondary biogenic production of methane due to incursion of water are suggested as the processes affecting the isotopic composition of coal-derived methane. An averaged value of −65 ‰ has been assigned to bituminous coal exploited in open cast mines and of −55 ‰ in deep mines, whereas values of −40 and −30 ‰ can be allocated to anthracite opencast and deep mines respectively. However, the isotopic signatures that are included in global atmospheric modelling of coal emissions should be region- or nation-specific, as greater detail is needed, given the wide global variation in coal type.

We evaluate the capability of the global atmospheric transport model TM5 to simulate the boundary layer dynamics and associated variability of trace gases close to the surface, using radon (222Rn). Focusing on the European scale, we compare the boundary layer height (BLH) in the TM5 model with observations from the National Oceanic and Atmospheric Admnistration (NOAA) Integrated Global Radiosonde Archive (IGRA) and also with ceilometer and lidar (light detection and ranging) BLH retrievals at two stations. Furthermore, we compare TM5 simulations of 222Rn activity concentrations, using a novel, process-based 222Rn flux map over Europe (Karstens et al., 2015), with harmonised 222Rn measurements at 10 stations. The TM5 model reproduces relatively well the daytime BLH (within 10–20 % for most of the stations), except for coastal sites, for which differences are usually larger due to model representation errors. During night, however, TM5 overestimates the shallow nocturnal BLHs, especially for the very low observed BLHs ( The 222Rn activity concentration simulations based on the new 222Rn flux map show significant improvements especially regarding the average seasonal variability, compared to simulations using constant 222Rn fluxes. Nevertheless, the (relative) differences between simulated and observed daytime minimum 222Rn activity concentrations are larger for several stations (on the order of 50 %) than the (relative) differences between simulated and observed BLH at noon. Although the nocturnal BLH is often higher in the model than observed, simulated 222Rn nighttime maxima are actually larger at several continental stations. This counterintuitive behaviour points to potential deficiencies of TM5 to correctly simulate the vertical gradients within the nocturnal boundary layer, limitations of the 222Rn flux map, or issues related to the definition of the nocturnal BLH. At several stations the simulated decrease of 222Rn activity concentrations in the morning is faster than observed. In addition, simulated vertical 222Rn activity concentration gradients at Cabauw decrease faster than observations during the morning transition period, and are in general lower than observed gradients during daytime. Although these effects may be partially due to the slow response time of the radon detectors, they clearly point to too fast vertical mixing in the TM5 boundary layer during daytime. Furthermore, the capability of the TM5 model to simulate the diurnal BLH cycle is limited by the current coarse temporal resolution (3 h/6 h) of the TM5 input meteorology.

High-precision analyses of the isotopic composition of methane in ambient air can potentially be used to discriminate between different source categories. Due to the complexity of isotope ratio measurements, such analyses have generally been performed in the laboratory on air samples collected in the field. This poses a limitation on the temporal resolution at which the isotopic composition can be monitored with reasonable logistical effort. Here we present the performance of a dual isotope ratio mass spectrometric system (IRMS) and a quantum cascade laser absorption spectroscopy (QCLAS)-based technique for in situ analysis of the isotopic composition of methane under field conditions. Both systems were deployed at the Cabauw Experimental Site for Atmospheric Research (CESAR) in the Netherlands and performed in situ, high-frequency (approx. hourly) measurements for a period of more than 5 months. The IRMS and QCLAS instruments were in excellent agreement with a slight systematic offset of (+0.25 ± 0.04) ‰ for δ13C and (−4.3 ± 0.4) ‰ for δD. This was corrected for, yielding a combined dataset with more than 2500 measurements of both δ13C and δD. The high-precision and high-temporal-resolution dataset not only reveals the overwhelming contribution of isotopically depleted agricultural CH4 emissions from ruminants at the Cabauw site but also allows the identification of specific events with elevated contributions from more enriched sources such as natural gas and landfills. The final dataset was compared to model calculations using the global model TM5 and the mesoscale model FLEXPART-COSMO. The results of both models agree better with the measurements when the TNO-MACC emission inventory is used in the models than when the EDGAR inventory is used. This suggests that high-resolution isotope measurements have the potential to further constrain the methane budget when they are performed at multiple sites that are representative for the entire European domain.

Subsea permafrost and hydrates in the East Siberian Arctic Shelf (ESAS) constitute a substantial carbon pool, and a potentially large source of methane to the atmosphere. Previous studies based on interpolated oceanographic campaigns estimated atmospheric emissions from this area at 8–17 TgCH4 yr−1. Here, we propose insights based on atmospheric observations to evaluate these estimates. The comparison of high-resolution simulations of atmospheric methane mole fractions to continuous methane observations during the whole year 2012 confirms the high variability and heterogeneity of the methane releases from ESAS. A reference scenario with ESAS emissions of 8 TgCH4 yr−1, in the lower part of previously estimated emissions, is found to largely overestimate atmospheric observations in winter, likely related to overestimated methane leakage through sea ice. In contrast, in summer, simulations are more consistent with observations. Based on a comprehensive statistical analysis of the observations and of the simulations, annual methane emissions from ESAS are estimated to range from 0.0 to 4.5 TgCH4 yr−1. Isotopic observations suggest a biogenic origin (either terrestrial or marine) of the methane in air masses originating from ESAS during late summer 2008 and 2009.

In situ and simultaneous measurement of the three most abundant isotopologues of methane using mid-infrared laser absorption spectroscopy is demonstrated. A field-deployable, autonomous platform is realized by coupling a compact quantum cascade laser absorption spectrometer (QCLAS) to a preconcentration unit, called trace gas extractor (TREX). This unit enhances CH4 mole fractions by a factor of up to 500 above ambient levels and quantitatively separates interfering trace gases such as N2O and CO2. The analytical precision of the QCLAS isotope measurement on the preconcentrated (750 ppm, parts-per-million, µmole mole−1) methane is 0.1 and 0.5 ‰ for δ13C- and δD-CH4 at 10 min averaging time. Based on repeated measurements of compressed air during a 2-week intercomparison campaign, the repeatability of the TREX–QCLAS was determined to be 0.19 and 1.9 ‰ for δ13C and δD-CH4, respectively. In this intercomparison campaign the new in situ technique is compared to isotope-ratio mass spectrometry (IRMS) based on glass flask and bag sampling and real time CH4 isotope analysis by two commercially available laser spectrometers. Both laser-based analyzers were limited to methane mole fraction and δ13C-CH4 analysis, and only one of them, a cavity ring down spectrometer, was capable to deliver meaningful data for the isotopic composition. After correcting for scale offsets, the average difference between TREX–QCLAS data and bag/flask sampling–IRMS values are within the extended WMO compatibility goals of 0.2 and 5 ‰ for δ13C- and δD-CH4, respectively. This also displays the potential to improve the interlaboratory compatibility based on the analysis of a reference air sample with accurately determined isotopic composition.

European CH4 and N2O emissions are estimated for 2006 and 2007 using four inverse modelling systems, based on different global and regional Eulerian and Lagrangian transport models. This ensemble approach is designed to provide more realistic estimates of the overall uncertainties in the derived emissions, which is particularly important for verifying bottom-up emission inventories. We use continuous observations from 10 European stations (including 5 tall towers) for CH4 and 9 continuous stations for N2O, complemented by additional European and global discrete air sampling sites. The available observations mainly constrain CH4 and N2O emissions from north-western and eastern Europe. The inversions are strongly driven by the observations and the derived total emissions of larger countries show little dependence on the emission inventories used a priori. Three inverse models yield 26–56% higher total CH4 emissions from north-western and eastern Europe compared to bottom-up emissions reported to the UNFCCC, while one model is close to the UNFCCC values. In contrast, the inverse modelling estimates of European N2O emissions are in general close to the UNFCCC values, with the overall range from all models being much smaller than the UNFCCC uncertainty range for most countries. Our analysis suggests that the reported uncertainties for CH4 emissions might be underestimated, while those for N2O emissions are likely overestimated.

Airborne and ground-based measurements of methane (CH4), carbon dioxide (CO2) and boundary layer thermodynamics were recorded over the Fennoscandian landscape (67–69.5° N, 20–28° E) in July 2012 as part of the MAMM (Methane and other greenhouse gases in the Arctic: Measurements, process studies and Modelling) field campaign. Employing these airborne measurements and a simple boundary layer box model, net regional-scale (~ 100 km) fluxes were calculated to be 1.2 ± 0.5 mg CH4 h−1 m−2 and −350 ± 143 mg CO2 h−1 m−2. These airborne fluxes were found to be relatively consistent with seasonally averaged surface chamber (1.3 ± 1.0 mg CH4 h−1 m−2) and eddy covariance (1.3 ± 0.3 mg CH4 h−1 m−2 and −309 ± 306 mg CO2 h−1 m−2) flux measurements in the local area. The internal consistency of the aircraft-derived fluxes across a wide swath of Fennoscandia coupled with an excellent statistical comparison with local seasonally averaged ground-based measurements demonstrates the potential scalability of such localised measurements to regional-scale representativeness. Comparisons were also made to longer-term regional CH4 climatologies from the JULES (Joint UK Land Environment Simulator) and HYBRID8 land surface models within the area of the MAMM campaign. The average hourly emission flux output for the summer period (July–August) for the year 2012 was 0.084 mg CH4 h−1 m−2 (minimum 0.0 and maximum 0.21 mg CH4 h−1 m−2) for the JULES model and 0.088 mg CH4 h−1 m−2 (minimum 0.0008 and maximum 1.53 mg CH4 h−1 m−2) for HYBRID8. Based on these observations both models were found to significantly underestimate the CH4 emission flux in this region, which was linked to the under-prediction of the wetland extents generated by the models.

High-resolution CH4 and CO2 measurements were made on board the FAAM BAe-146 UK (Facility for Airborne Atmospheric Measurements, British Aerospace-146) atmospheric research aircraft during a number of field campaigns. The system was based on an infrared spectrometer using the cavity-enhanced absorption spectroscopy technique. Correction functions to convert the mole fractions retrieved from the spectroscopy to dry-air mole fractions were derived using laboratory experiments and over a 3 month period showed good stability. Long-term performance of the system was monitored using WMO (World Meteorological Office) traceable calibration gases. During the first year of operation (29 flights) analysis of the system's in-flight calibrations suggest that its measurements are accurate to 1.28 ppb (1σ repeatability at 1 Hz = 2.48 ppb) for CH4 and 0.17 ppm (1σ repeatability at 1 Hz = 0.66 ppm) for CO2. The system was found to be robust, no major motion or altitude dependency could be detected in the measurements. An inter-comparison between whole-air samples that were analysed post-flight for CH4 and CO2 by cavity ring-down spectroscopy showed a mean difference between the two techniques of −2.4 ppb (1σ = 2.3 ppb) for CH4 and −0.22 ppm (1σ = 0.45 ppm) for CO2. In September 2012, the system was used to sample biomass-burning plumes in Brazil as part of the SAMBBA project (South AMerican Biomass Burning Analysis). From these and simultaneous CO measurements, emission factors for savannah fires were calculated. These were found to be 2.2 ± 0.2 g (kg dry matter)−1 for CH4 and 1710 ± 171 g (kg dry matter)−1 for CO2, which are in excellent agreement with previous estimates in the literature.

Methane emissions from Lompolojänkkä, a Finnish aapa mire within the Arctic Circle, were studied by non-intrusive Keeling plot methods, to place better constraints on the seasonal variations in isotopic signature of methane (δ13CCH4) emitted from Arctic wetland. Air samples were collected in Tedlar bags over the wetland at heights of 42 and 280 cm between May and October 2009 and in August 2008. The mixing ratio and δ13C of the methane in the samples were incorporated into Keeling plot analyses to derive bulk δ13CCH4 signatures for the methane inputs to the air above the wetland. The results show an unexpected consistence in δ13CCH4 from early to late summer, clustered around −68.5±0.7‰, but during spring thaw and autumnal freezing, δ13CCH4 is enriched by approximately 2 and 4‰, respectively. The techniques reported in this paper are simple and economical to employ, and give a bulk source signature for the methane inputs to the air above the entire wetland that can be extrapolated to a larger regional area.

We designed a method to simulate atmospheric CO2 concentrations at several continuous observation sites around the globe using surface fluxes at a very high spatial resolution. The simulations presented in this study were performed using the Global Eulerian-Lagrangian Coupled Atmospheric model (GELCA), comprising a Lagrangian particle dispersion model coupled to a global atmospheric tracer transport model with prescribed global surface CO2 flux maps at a 1 × 1 km resolution. The surface fluxes used in the simulations were prepared by assembling the individual components of terrestrial, oceanic and fossil fuel CO2 fluxes. This experimental setup (i.e. a transport model running at a medium resolution, coupled to a high-resolution Lagrangian particle dispersion model together with global surface fluxes at a very high resolution), which was designed to represent high-frequency variations in atmospheric CO2 concentration, has not been reported at a global scale previously. Two sensitivity experiments were performed: (a) using the global transport model without coupling to the Lagrangian dispersion model, and (b) using the coupled model with a reduced resolution of surface fluxes, in order to evaluate the performance of Eulerian-Lagrangian coupling and the role of high-resolution fluxes in simulating high-frequency variations in atmospheric CO2 concentrations. A correlation analysis between observed and simulated atmospheric CO2 concentrations at selected locations revealed that the inclusion of both Eulerian-Lagrangian coupling and high-resolution fluxes improves the high-frequency simulations of the model. The results highlight the potential of a coupled Eulerian-Lagrangian model in simulating high-frequency atmospheric CO2 concentrations at many locations worldwide. The model performs well in representing observations of atmospheric CO2 concentrations at high spatial and temporal resolutions, especially for coastal sites and sites located close to sources of large anthropogenic emissions. While this study focused on simulations of CO2 concentrations, the model could be used for other atmospheric compounds with known estimated emissions.

This paper presents an analysis of the recent tropospheric molecular hydrogen (H2) budget with a particular focus on soil uptake and European surface emissions. A variational inversion scheme is combined with observations from the RAMCES and EUROHYDROS atmospheric networks, which include continuous measurements performed between mid-2006 and mid-2009. Net H2 surface flux, then deposition velocity and surface emissions and finally, deposition velocity, biomass burning, anthropogenic and N2 fixation-related emissions were simultaneously inverted in several scenarios. These scenarios have focused on the sensibility of the soil uptake value to different spatio-temporal distributions. The range of variations of these diverse inversion sets generate an estimate of the uncertainty for each term of the H2 budget. The net H2 flux per region (High Northern Hemisphere, Tropics and High Southern Hemisphere) varies between −8 and +8 Tg yr−1. The best inversion in terms of fit to the observations combines updated prior surface emissions and a soil deposition velocity map that is based on bottom-up and top-down estimations. Our estimate of global H2 soil uptake is −59±9 Tg yr−1. Forty per cent of this uptake is located in the High Northern Hemisphere and 55% is located in the Tropics. In terms of surface emissions, seasonality is mainly driven by biomass burning emissions. The inferred European anthropogenic emissions are consistent with independent H2 emissions estimated using a H2/CO mass ratio of 0.034 and CO emissions within the range of their respective uncertainties. Additional constraints, such as isotopic measurements would be needed to infer a more robust partition of H2 sources and sinks.