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Hydrofluorocarbons (HFCs) are powerful anthropogenic greenhouse gases (GHGs) with high global-warming potentials (GWPs). They have been widely used as refrigerants, insulation foam-blowing agents, aerosol propellants, and fire suppression agents. Since the mid-1990s, emissions of HFCs have been increasing rapidly as they are used in many applications to replace ozone-depleting chlorofluorocarbons (CFCs) and hydrochlorofluorocarbons (HCFCs) whose consumption and production have been phased out under the Montreal Protocol (MP). Due to the high GWP of HFCs, the Kigali Amendment to the MP requires the phasedown of production and consumption of HFCs to gradually achieve an 80 %–85 % reduction by 2047, starting in 2019 for non-Article 5 (developed) countries with a 10 % reduction against each defined baseline and later schedules for Article 5 (developing) countries. In this study, we have examined long-term high-precision measurements of atmospheric abundances of five major HFCs (HFC-134a, HFC-143a, HFC-32, HFC-125, and HFC-152a) at Gosan station, Jeju Island, South Korea, from 2008 to 2020. Background abundances of HFCs gradually increased, and the inflow of polluted air masses with elevated abundances from surrounding source regions were detected over the entire period. From these pollution events, we inferred regional and country-specific HFC emission estimates using two independent Lagrangian particle dispersion models and Bayesian inversion frameworks (FLEXPART-FLEXINVERT+ and NAME-InTEM). The spatial distribution of the derived “top-down” (measurement based) emissions for all HFCs shows large fluxes from megacities and industrial areas in the region. Our most important finding is that HFC emissions in eastern China and Japan have sharply increased from 2016 to 2018. The contribution of East Asian HFC emissions to the global total increased from 9 % (2008–2014) to 13 % (2016–2020). In particular, HFC emissions in Japan (Annex I country) rose rapidly from 2016 onward, with accumulated total inferred HFC emissions being ∼ 114 Gg yr−1, which is ∼ 76 Gg yr−1 higher for 2016–2020 than the “bottom-up” (i.e., based on activity data and emission factors) emissions of ∼ 38 Gg yr−1 reported to the United Nations Framework Convention on Climate Change (UNFCCC). This is likely related to the increase in domestic demand in Japan for refrigerants and air-conditioning-system-related products and incomplete accounting. A downward trend of HFC emissions that started in 2019 reflects the effectiveness of the F-gas policy in Japan. Eastern China and South Korea, though not obligated to report to the UNFCCC, voluntarily reported emissions, which also show differences between top-down and bottom-up emission estimates, demonstrating the need for atmospheric measurements, comprehensive data analysis, and accurate reporting for precise emission management. Further, the proportional contribution of each country's CO2-equivalent HFC emissions has changed over time, with HFC-134a decreasing and HFC-125 increasing. This demonstrates the transition in the predominant HFC substances contributing to global warming in each country.

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.

Production and consumption of CFC-11 (trichlorofluoromethane, CCl3F), CFC-12 (dichlorodifluoromethane, CCl2F2) and CCl4 (carbon tetrachloride) are controlled under the regulations of the Montreal Protocol and have been phased out globally since 2010. Only CCl4 is still widely produced as a chemical feedstock. After 2010, emissions of CFC-11 and CFC-12 should therefore mostly originate from existing banks (e.g. from foams, mobile air conditioning units and refrigerators); however evidence has emerged of an increase in global emissions of CFC-11 in the last decade, some of which has not been fully accounted for. The motivation for this work was to assess the emissions of CFC-11, CFC-12 and CCl4 from western Europe. All countries in this region have been subject to the controls of the Montreal Protocol since the late 1980s and, as non-Article 5 Parties, have been prohibited from producing CFCs and CCl4 for dispersive use since 1996. Four different inverse modelling systems are used to estimate emissions of these gases from 2008 to 2021 using data from four atmospheric measurement stations: Mace Head (Ireland), Jungfraujoch (Switzerland), Monte Cimone (Italy) and Tacolneston (UK). The average of the four model studies found that western European emissions of CFC-11, CFC-12 and CCl4 between 2008 and 2021 were declining at 3.5 % yr−1 (2.7 % yr−1–4.8 % yr−1), 7.7 % yr−1 (6.3 % yr−1–8.0 % yr−1) and 4.4 % yr−1 (2.6 % yr−1–6.4 % yr−1), respectively. Even though the emissions were declining throughout the period, the area including northern France, Belgium, the Netherlands and Luxembourg showed consistently elevated emissions of CFC-11 compared with the surrounding regions. Emissions of CFC-12 were slightly elevated in the same region. CCl4 emissions were the highest in the south of France. France had the highest emissions of all three gases over the period 2008–2021. Emissions from western Europe (2008–2021) were on average 2.4 ± 0.4 Gg (CFC-11), 1.3 ± 0.3 Gg (CFC-12) and 0.9 ± 0.2 Gg (CCl4). Our estimated decline in emissions of CFC-11 is consistent with a western European bank release rate of 3.4 % (2.6 %–4.5 %). This study concludes that emissions of CFC-11, CFC-12 and CCl4 have all declined from 2008 to 2021 in western Europe. Therefore, no evidence is found that western European emissions contributed to the unexplained part of the global increase in atmospheric concentrations of CFC-11 observed in the last decade.

Abstract Biophysical cohesion, introduced predominantly by Extracellular Polymeric Substances (EPS) during mineral flocculation in subaqueous environments, plays important role in morphodynamics, biogeochemical cycles and ecosystem processes. However, the mechanism of how EPS functioning with cohesive particles and affects settling behaviors remain poorly understood. We measure initial flocculation rate, floc size and settling velocity of mineral and artificial EPS (Xanthan gum) mixtures. Combining results from these and previous studies demonstrate coherent intensification of EPS-related flocculation compare with those of pure mineral and oil-mineral mixtures. Importantly, the presence of EPS fundamentally changes floc structure and reduces variability of settling velocity. Measured data shows that ratios of microfloc and macrofloc settling velocity for pure mineral flocs is 3.9 but greatly reduced to a lowest value of 1.6 due to biological EPS addition. The low variability of settling velocity due to EPS participation explains the seemingly inconsistent results previously observed between field and laboratory studies.

Knowledge of the spatial distribution of the fluxes of greenhouse gases (GHGs) and their temporal variability as well as flux attribution to natural and anthropogenic processes is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement and to inform its global stocktake. This study provides a consolidated synthesis of CH4 and N2O emissions using bottom-up (BU) and top-down (TD) approaches for the European Union and UK (EU27 + UK) and updates earlier syntheses (Petrescu et al., 2020, 2021). The work integrates updated emission inventory data, process-based model results, data-driven sector model results and inverse modeling estimates, and it extends the previous period of 1990–2017 to 2019. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported by parties under the United Nations Framework Convention on Climate Change (UNFCCC) in 2021. Uncertainties in NGHGIs, as reported to the UNFCCC by the EU and its member states, are also included in the synthesis. Variations in estimates produced with other methods, such as atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arise from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. By comparing NGHGIs with other approaches, the activities included are a key source of bias between estimates, e.g., anthropogenic and natural fluxes, which in atmospheric inversions are sensitive to the prior geospatial distribution of emissions. For CH4 emissions, over the updated 2015–2019 period, which covers a sufficiently robust number of overlapping estimates, and most importantly the NGHGIs, the anthropogenic BU approaches are directly comparable, accounting for mean emissions of 20.5 Tg CH4 yr−1 (EDGARv6.0, last year 2018) and 18.4 Tg CH4 yr−1 (GAINS, last year 2015), close to the NGHGI estimates of 17.5±2.1 Tg CH4 yr−1. TD inversion estimates give higher emission estimates, as they also detect natural emissions. Over the same period, high-resolution regional TD inversions report a mean emission of 34 Tg CH4 yr−1. Coarser-resolution global-scale TD inversions result in emission estimates of 23 and 24 Tg CH4 yr−1 inferred from GOSAT and surface (SURF) network atmospheric measurements, respectively. The magnitude of natural peatland and mineral soil emissions from the JSBACH–HIMMELI model, natural rivers, lake and reservoir emissions, geological sources, and biomass burning together could account for the gap between NGHGI and inversions and account for 8 Tg CH4 yr−1. For N2O emissions, over the 2015–2019 period, both BU products (EDGARv6.0 and GAINS) report a mean value of anthropogenic emissions of 0.9 Tg N2O yr−1, close to the NGHGI data (0.8±55 % Tg N2O yr−1). Over the same period, the mean of TD global and regional inversions was 1.4 Tg N2O yr−1 (excluding TOMCAT, which reported no data). The TD and BU comparison method defined in this study can be operationalized for future annual updates for the calculation of CH4 and N2O budgets at the national and EU27 + UK scales. Future comparability will be enhanced with further steps involving analysis at finer temporal resolutions and estimation of emissions over intra-annual timescales, which is of great importance for CH4 and N2O, and may help identify sector contributions to divergence between prior and posterior estimates at the annual and/or inter-annual scale. Even if currently comparison between CH4 and N2O inversion estimates and NGHGIs is highly uncertain because of the large spread in the inversion results, TD inversions inferred from atmospheric observations represent the most independent data against which inventory totals can be compared. With anticipated improvements in atmospheric modeling and observations, as well as modeling of natural fluxes, TD inversions may arguably emerge as the most powerful tool for verifying emission inventories for CH4, N2O and other GHGs. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.7553800 (Petrescu et al., 2023).

Clay-rich flocculated suspended sediments are an important constituent of estuarine and coastal systems globally. They are responsible for the host, movement and deposition of a variety of pollutants, contaminants and sediment itself. Accurate modelling of the movement of these sediments is crucial for a number of industries including fisheries, aquaculture, shipping and waste management. This requires an accurate and reliable measurements of the physical properties of flocs and their behaviour. Porosity is a key element in floc structures, and this research provides updated 3D quantified porosity and pore space morphological data in relation to influences on floc settling behaviour. We report the questionable relationship between floc size and settling velocity, and explore alternative influences such as floc composition, porosity and pore morphology. These outcomes suggest that a shift in focus from floc size to a combination of factors is necessitated to understand the complex movement behaviour of flocculated suspended sediments.

An extensive field campaign, the Ems-Dollard Measurements (EDoM), was executed in the Ems Estuary, bordering the Netherlands and Germany, aimed at better understanding the mechanisms that drive the exchange of water and sediments between a relatively exposed outer estuary and a hyper-turbid tidal river. More specifically, the reasons for the large up-estuary sediment accumulation rates and the role of the tidal river on the turbidity in the outer estuary were insufficiently understood. The campaign was designed to unravel the hydrodynamic and sedimentary exchange mechanisms, comprising two hydrographic surveys during contrasting environmental conditions using eight concurrently operating ships and 10 moorings measuring for at least one spring–neap tidal cycle. All survey locations were equipped with sensors measuring flow velocity, salinity, and turbidity (and with stationary ship surveys taking water samples), while some of the survey ships also measured turbulence and sediment settling properties. These observations have provided important new insights into horizontal sediment fluxes and density-driven exchange flows, both laterally and longitudinally. An integral analysis of these observations suggests that large-scale residual transport is surprisingly similar during periods of high and low discharge, with higher river discharge resulting in both higher seaward-directed fluxes near the surface and landward-directed fluxes near the bed. Sediment exchange seems to be strongly influenced by a previously undocumented lateral circulation cell driving residual transport. Vertical density-driven flows in the outer estuary are influenced by variations in river discharge, with a near-bed landward flow being most pronounced in the days following a period with elevated river discharge. The study site is more turbid during winter conditions, when the estuarine turbidity maximum (ETM) is pushed seaward by river flow, resulting in a more pronounced impact of suspended sediments on hydrodynamics. All data collected during the EDoM campaign, but also standard monitoring data (waves, water levels, discharge, turbidity, and salinity) collected by Dutch and German authorities are made publicly available at 4TU Centre for Research Data (https://doi.org/10.4121/c.6056564.v3; van Maren et al., 2022).

Global emissions of the ozone-depleting gas HCFC-141b (1,1-dichloro-1-fluoroethane, CH3CCl2F) derived from measurements of atmospheric mole fractions increased between 2017 and 2021 despite a fall in reported production and consumption of HCFC-141b for dispersive uses. HCFC-141b is a controlled substance under the Montreal Protocol, and its phase-out is currently underway, after a peak in reported consumption and production in developing (Article 5) countries in 2013. If reported production and consumption are correct, our study suggests that the 2017–2021 rise is due to an increase in emissions from the bank when appliances containing HCFC-141b reach the end of their life, or from production of HCFC-141b not reported for dispersive uses. Regional emissions have been estimated between 2017–2020 for all regions where measurements have sufficient sensitivity to emissions. This includes the regions of northwestern Europe, east Asia, the United States and Australia, where emissions decreased by a total of 2.3 ± 4.6 Gg yr−1, compared to a mean global increase of 3.0 ± 1.2 Gg yr−1 over the same period. Collectively these regions only account for around 30 % of global emissions in 2020. We are not able to pinpoint the source regions or specific activities responsible for the recent global emission rise.

Top-down greenhouse gas measurements can be used to independently assess the accuracy of bottom-up emission estimates. We report atmospheric methane (CH4) mole fractions and δ13CH4 measurements from Imperial College London from early 2018 onwards using a Picarro G2201-i analyser. Measurements from March 2018 to October 2020 were compared to simulations of CH4 mole fractions and δ13CH4 produced using the NAME (Numerical Atmospheric-dispersion Modelling Environment) dispersion model coupled with the UK National Atmospheric Emissions Inventory, UK NAEI, and a global inventory, the Emissions Database for Global Atmospheric Research (EDGAR), with model spatial resolutions of ∼ 2, ∼ 10, and ∼ 25 km. Simulation–measurement comparisons are used to evaluate London emissions and the source apportionment in the global (EDGAR) and UK national (NAEI) emission inventories. Observed mole fractions were underestimated by 30 %–35 % in the NAEI simulations. In contrast, a good correspondence between observations and EDGAR simulations was seen. There was no correlation between the measured and simulated δ13CH4 values for either NAEI or EDGAR, however, suggesting the inventories' sectoral attributions are incorrect. On average, natural gas sources accounted for 20 %–28 % of the above background CH4 in the NAEI simulations and only 6 %–9 % in the EDGAR simulations. In contrast, nearly 84 % of isotopic source values calculated by Keeling plot analysis (using measurement data from the afternoon) of individual pollution events were higher than −45 ‰, suggesting the primary CH4 sources in London are actually natural gas leaks. The simulation–observation comparison of CH4 mole fractions suggests that total emissions in London are much higher than the NAEI estimate (0.04 Tg CH4 yr−1) but close to, or slightly lower than, the EDGAR estimate (0.10 Tg CH4 yr−1). However, the simulation–observation comparison of δ13CH4 and the Keeling plot results indicate that emissions due to natural gas leaks in London are being underestimated in both the UK NAEI and EDGAR.

We present a method for estimating fossil fuel methane emissions using observations of methane and ethane, accounting for uncertainty in their emission ratio. The ethane:methane emission ratio is incorporated as a spatially and temporally variable parameter in a Bayesian model, with its own prior distribution and uncertainty. We find that using an emission ratio distribution mitigates bias from using a fixed, potentially incorrect emission ratio and that uncertainty in this ratio is propagated into posterior estimates of emissions. A synthetic data test is used to show the impact of assuming an incorrect ethane:methane emission ratio and demonstrate how our variable parameter model can better quantify overall uncertainty. We also use this method to estimate UK methane emissions from high-frequency observations of methane and ethane from the UK Deriving Emissions linked to Climate Change (DECC) network. Using the joint methane–ethane inverse model, we estimate annual mean UK methane emissions of approximately 0.27 (95 % uncertainty interval 0.26–0.29) Tg yr−1 from fossil fuel sources and 2.06 (1.99–2.15) Tg yr−1 from non-fossil fuel sources, during the period 2015–2019. Uncertainties in UK fossil fuel emissions estimates are reduced on average by 15 % and up to 35 % when incorporating ethane into the inverse model, in comparison to results from the methane-only inversion.

Atmospheric measurements can be used as a tool to evaluate national greenhouse gas inventories through inverse modelling. Using 8 years of continuous methane (CH4) concentration data, this work assesses the United Kingdom's (UK) CH4 emissions over the period 2013–2020. Using two different inversion methods, we find mean emissions of 2.10 ± 0.09 and 2.12 ± 0.26 Tg yr−1 between 2013 and 2020, an overall trend of −0.05 ± 0.01 and −0.06 ± 0.04 Tg yr−2 and a 2 %–3 % decrease each year. This compares with the mean emissions of 2.23 Tg yr−1 and the trend of −0.03 Tg yr−2 (1 % annual decrease) reported in the UK's 2021 inventory between 2013 and 2019. We examine how sensitive these estimates are to various components of the inversion set-up, such as the measurement network configuration, the prior emissions estimate, the inversion method and the atmospheric transport model used. We find the decreasing trend to be due, primarily, to a reduction in emissions from England, which accounts for 70 % of the UK CH4 emissions. Comparisons during 2015 demonstrate consistency when different atmospheric transport models are used to map the relationship between sources and atmospheric observations at the aggregation level of the UK. The posterior annual national means and negative trend are found to be consistent across changes in network configuration. We show, using only two monitoring sites, that the same conclusions on mean UK emissions and negative trend would be reached as using the full six-site network, albeit with larger posterior uncertainties. However, emissions estimates from Scotland fail to converge on the same posterior under different inversion set-ups, highlighting a shortcoming of the current observation network in monitoring all of the UK. Although CH4 emissions in 2020 are estimated to have declined relative to previous years, this decrease is in line with the longer-term emissions trend and is not necessarily a response to national lockdowns.

National greenhouse gas inventories (GHGIs) are submitted annually to the United Nations Framework Convention on Climate Change (UNFCCC). They are estimated in compliance with Intergovernmental Panel on Climate Change (IPCC) methodological guidance using activity data, emission factors and facility-level measurements. For some sources, the outputs from these calculations are very uncertain. Inverse modelling techniques that use high-quality, long-term measurements of atmospheric gases have been developed to provide independent verification of national GHGIs. This is considered good practice by the IPCC as it helps national inventory compilers to verify reported emissions and to reduce emission uncertainty. Emission estimates from the InTEM (Inversion Technique for Emission Modelling) model are presented for the UK for the hydrofluorocarbons (HFCs) reported to the UNFCCC (HFC-125, HFC-134a, HFC-143a, HFC-152a, HFC-23, HFC-32, HFC-227ea, HFC-245fa, HFC-43-10mee and HFC-365mfc). These HFCs have high global warming potentials (GWPs), and the global background mole fractions of all but two are increasing, thus highlighting their relevance to the climate and a need for increasing the accuracy of emission estimation for regulatory purposes. This study presents evidence that the long-term annual increase in growth of HFC-134a has stopped and is now decreasing. For HFC-32 there is an early indication, its rapid global growth period has ended, and there is evidence that the annual increase in global growth for HFC-125 has slowed from 2018. The inverse modelling results indicate that the UK implementation of European Union regulation of HFC emissions has been successful in initiating a decline in UK emissions from 2018. Comparison of the total InTEM UK HFC emissions in 2020 with the average from 2009–2012 shows a drop of 35 %, indicating progress toward the target of a 79 % decrease in sales by 2030. The total InTEM HFC emission estimates (2008–2018) are on average 73 (62–83) % of, or 4.3 (2.7–5.9) Tg CO2-eq yr−1 lower than, the total HFC emission estimates from the UK GHGI. There are also significant discrepancies between the two estimates for the individual HFCs.

An 11 hours survey was performed on the 17th of September 2014 in the Rhine Region Of Freshwater Influence (Rhine-ROFI) about 10 km downstream of the mouth of the Rotterdam Waterway during calm weather conditions. Suspended Particle Matter (SPM) measurements were performed during a full tidal cycle, near the seabed, at neap tide, and samples were taken at 0.6 meter above bed for on-board analysis. The measurements were performed with (a) LISST 100X, a submersible particle size analyzer, (b) LISST-HOLO, a submersible digital holographic camera, (c) a home-made underwater camera and (d) an on-board LabSFLOC2 video microscopy equipment that used in-situ collected samples. The first aim of the present study was to compare the results obtained from the different monitoring techniques and to characterize the different types of suspended particles found in-situ. It was found that that the highly anisotropic particles present in the water column lead to multiple peaks in the Particle Size Distributions (PSD) found using the LISST 100X. Using the LISST-HOLO, underwater camera and LabSFLOC2 camera these particles could properly be imaged and meaningful PSD’s were obtained using these techniques in the size range > 20 μm. LabSFLOC2, LISST-HOLO and the underwater camera moreover provide information on the size and aspect ratio of particles. On the other hand, LISST 100X can be used to detect the fine fraction ( 200 μm. A large range of settling velocities (0.1 - 10 mm/s) and aspect ratios between 1 and 10 were recorded by video microscopy (LabSFLOC2). This spreading in settling velocities and aspect ratio was due to the different properties (shape, effective density and size) of the particles in the water column. The second aim of the study was to reproduce the flocs found in-situ in the lab and investigate the kinetics of flocculation between inorganic and living organic matter. Laboratory experiments were conducted with grab samples obtained from Port of Rotterdam harbour and living microalgae (Skeletonema costatum). The results of these experiments showed a shift in effective density upon addition of living algae to the sediment, which confirmed the flocculation ability between sediment and microalgae. The flocculation occured on a timescale of minutes and lead to flocs having a large spread in density for a given size, due to the heteregeous inorganic/organic composition of the flocs. This spread in density was at the origin of the large range of settling velocities for a given floc size observed in-situ, which leads to conclude that organic matter should be an important input parameter in sediment transport models.

Reliable quantification of the sources and sinks of greenhouse gases, together with trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement. This study provides a consolidated synthesis of CH4 and N2O emissions with consistently derived state-of-the-art bottom-up (BU) and top-down (TD) data sources for the European Union and UK (EU27 + UK). We integrate recent emission inventory data, ecosystem process-based model results and inverse modeling estimates over the period 1990–2017. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported to the UN climate convention UNFCCC secretariat in 2019. For uncertainties, we used for NGHGIs the standard deviation obtained by varying parameters of inventory calculations, reported by the member states (MSs) following the recommendations of the IPCC Guidelines. For atmospheric inversion models (TD) or other inventory datasets (BU), we defined uncertainties from the spread between different model estimates or model-specific uncertainties when reported. In comparing NGHGIs with other approaches, a key source of bias is the activities included, e.g., anthropogenic versus anthropogenic plus natural fluxes. In inversions, the separation between anthropogenic and natural emissions is sensitive to the geospatial prior distribution of emissions. Over the 2011–2015 period, which is the common denominator of data availability between all sources, the anthropogenic BU approaches are directly comparable, reporting mean emissions of 20.8 Tg CH4 yr−1 (EDGAR v5.0) and 19.0 Tg CH4 yr−1 (GAINS), consistent with the NGHGI estimates of 18.9 ± 1.7 Tg CH4 yr−1. The estimates of TD total inversions give higher emission estimates, as they also include natural emissions. Over the same period regional TD inversions with higher-resolution atmospheric transport models give a mean emission of 28.8 Tg CH4 yr−1. Coarser-resolution global TD inversions are consistent with regional TD inversions, for global inversions with GOSAT satellite data (23.3 Tg CH4 yr−1) and surface network (24.4 Tg CH4 yr−1). The magnitude of natural peatland emissions from the JSBACH–HIMMELI model, natural rivers and lakes emissions, and geological sources together account for the gap between NGHGIs and inversions and account for 5.2 Tg CH4 yr−1. For N2O emissions, over the 2011–2015 period, both BU approaches (EDGAR v5.0 and GAINS) give a mean value of anthropogenic emissions of 0.8 and 0.9 Tg N2O yr−1, respectively, agreeing with the NGHGI data (0.9 ± 0.6 Tg N2O yr−1). Over the same period, the average of the three total TD global and regional inversions was 1.3 ± 0.4 and 1.3 ± 0.1 Tg N2O yr−1, respectively. The TD and BU comparison method defined in this study can be operationalized for future yearly updates for the calculation of CH4 and N2O budgets both at the EU+UK scale and at the national scale. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.4590875 (Petrescu et al., 2020b).

Perfluorocarbons (PFCs) are amongst the most potent greenhouse gases listed under the United Nations Framework Convention on Climate Change (UNFCCC). With atmospheric lifetimes on the order of thousands to tens of thousands of years, PFC emissions represent a permanent alteration to the global atmosphere on human timescales. While the industries responsible for the vast majority of these emissions – aluminium smelting and semi-conductor manufacturing – have made efficiency improvements and introduced abatement measures, the global mean mole fractions of three PFCs, namely tetrafluoromethane (CF4, PFC-14), hexafluoroethane (C2F6, PFC-116) and octafluoropropane (C3F8, PFC-218), continue to grow. In this study, we update baseline growth rates using in situ high-frequency measurements from the Advanced Global Atmospheric Gases Experiment (AGAGE) and, using data from four European stations, estimate PFC emissions for northwest Europe. The global growth rate of CF4 decreased from 1.3 ppt yr−1 in 1979 to 0.6 ppt yr−1 around 2010 followed by a renewed steady increase to 0.9 ppt yr−1 in 2019. For C2F6, the growth rate grew to a maximum of 0.125 ppt yr−1 around 1999, followed by a decline to a minimum of 0.075 ppt yr−1 in 2009, followed by weak growth thereafter. The C3F8 growth rate was around 0.007 ppt yr−1 until the early 1990s and then quickly grew to a maximum of 0.03 ppt yr−1 in 2003–2004. Following a period of decline until 2012 to 0.015 ppt yr−1, the growth rate slowly increased again to ∼ 0.017 ppt yr−1 in 2019. We used an inverse modelling framework to infer PFC emissions for northwest Europe. No statistically significant trend in regional emissions was observed for any of the PFCs assessed. For CF4, European emissions in early years were linked predominantly to the aluminium industry. However, we link large emissions in recent years to a chemical manufacturer in northwest Italy. Emissions of C2F6 are linked to a range of sources, including a semi-conductor manufacturer in Ireland and a cluster of smelters in Germany's Ruhr valley. In contrast, northwest European emissions of C3F8 are dominated by a single source in northwest England, raising the possibility of using emissions from this site for a tracer release experiment.

We report a 40-year history of SF6 atmospheric mole fractions measured at the Advanced Global Atmospheric Gases Experiment (AGAGE) monitoring sites, combined with archived air samples, to determine emission estimates from 1978 to 2018. Previously we reported a global emission rate of 7.3±0.6 Gg yr−1 in 2008 and over the past decade emissions have continued to increase by about 24 % to 9.04±0.35 Gg yr−1 in 2018. We show that changing patterns in SF6 consumption from developed (Kyoto Protocol Annex-1) to developing countries (non-Annex-1) and the rapid global expansion of the electric power industry, mainly in Asia, have increased the demand for SF6-insulated switchgear, circuit breakers, and transformers. The large bank of SF6 sequestered in this electrical equipment provides a substantial source of emissions from maintenance, replacement, and continuous leakage. Other emissive sources of SF6 occur from the magnesium, aluminium, and electronics industries as well as more minor industrial applications. More recently, reported emissions, including those from electrical equipment and metal industries, primarily in the Annex-1 countries, have declined steadily through substitution of alternative blanketing gases and technological improvements in less emissive equipment and more efficient industrial practices. Nevertheless, there are still demands for SF6 in Annex-1 countries due to economic growth, as well as continuing emissions from older equipment and additional emissions from newly installed SF6-insulated electrical equipment, although at low emission rates. In addition, in the non-Annex-1 countries, SF6 emissions have increased due to an expansion in the growth of the electrical power, metal, and electronics industries to support their continuing development. There is an annual difference of 2.5–5 Gg yr−1 (1990–2018) between our modelled top-down emissions and the UNFCCC-reported bottom-up emissions (United Nations Framework Convention on Climate Change), which we attempt to reconcile through analysis of the potential contribution of emissions from the various industrial applications which use SF6. We also investigate regional emissions in East Asia (China, S. Korea) and western Europe and their respective contributions to the global atmospheric SF6 inventory. On an average annual basis, our estimated emissions from the whole of China are approximately 10 times greater than emissions from western Europe. In 2018, our modelled Chinese and western European emissions accounted for ∼36 % and 3.1 %, respectively, of our global SF6 emissions estimate.

We present a method to infer spatially and spatio-temporally correlated emissions of greenhouse gases from atmospheric measurements and a chemical transport model. The method allows fast computation of spatial emissions using a hierarchical Bayesian framework as an alternative to Markov chain Monte Carlo algorithms. The spatial emissions follow a Gaussian process with a Matérn correlation structure which can be represented by a Gaussian Markov random field through a stochastic partial differential equation approach. The inference is based on an integrated nested Laplacian approximation (INLA) for hierarchical models with Gaussian latent fields. Combining an autoregressive temporal correlation and the Matérn field provides a full spatio-temporal correlation structure. We first demonstrate the method on a synthetic data example and follow this using a well-studied test case of inferring UK methane emissions from tall tower measurements of atmospheric mole fraction. Results from these two test cases show that this method can accurately estimate regional greenhouse gas emissions, accounting for spatio-temporal uncertainties that have traditionally been neglected in atmospheric inverse modelling.

We present Δ14CO2 observations and related greenhouse gas measurements at a background site in Ireland (Mace Head, MHD) and a tall tower site in the east of the UK (Tacolneston, TAC) that is more strongly influenced by fossil fuel sources. These observations have been used to calculate the contribution of fossil fuel sources to the atmospheric CO2 mole fractions; this can be done, as emissions from fossil fuels do not contain 14CO2 and cause a depletion in the observed Δ14CO2 value. The observations are compared to simulated values. Two corrections need to be applied to radiocarbon-derived fossil fuel CO2 (ffCO2): one for pure 14CO2 emissions from nuclear industry sites and one for a disequilibrium in the isotopic signature of older biospheric emissions (heterotrophic respiration) and CO2 in the atmosphere. Measurements at both sites were found to only be marginally affected by 14CO2 emissions from nuclear sites. Over the study period of 2014–2015, the biospheric correction and the correction for nuclear 14CO2 emissions were similar at 0.34 and 0.25 ppm ffCO2 equivalent, respectively. The observed ffCO2 at the TAC tall tower site was not significantly different from simulated values based on the EDGAR 2010 bottom-up inventory. We explored the use of high-frequency CO observations as a tracer of ffCO2 by deriving a constant ratio of CO enhancements to ffCO2 ratio for the mix of UK fossil fuel sources. This ratio was found to be 5.7 ppb ppm−1, close to the value predicted using inventories and the atmospheric model of 5.1 ppb ppm−1. The TAC site, in the east of the UK, was strategically chosen to be some distance from pollution sources so as to allow for the observation of well-integrated air masses. However, this distance from pollution sources and the large measurement uncertainty in 14CO2 lead to a large overall uncertainty in the ffCO2, being around 1.8 ppm compared to typical enhancements of 2 ppm.

As the second most populous country and third fastest growing economy, India has emerged as a global economic power. As such, its emissions of greenhouse and ozone-depleting gases are of global significance. However, unlike neighbouring China, the Indian sub-continent is very poorly monitored by atmospheric measurement networks. India's halocarbon emissions, here defined as chlorofluorocarbons (CFCs), hydrochlorofluorocarbons (HCFCs), hydrofluorocarbons (HFCs) and chlorocarbons, are not well-known. Previous measurements from the region have been obtained at observatories many hundreds of kilometres from source regions, or at high altitudes, limiting their value for the estimation of regional emission rates. Given the projected rapid growth in demand for refrigerants and solvents in India, emission estimates of these halocarbons are urgently needed to provide a benchmark against which future changes can be evaluated. In this study, we report atmospheric-measurement-derived halocarbon emissions from India. With the exception of dichloromethane, these top-down estimates are the first for India's halocarbons. Air samples were collected at low altitude during an aircraft campaign in June and July 2016, and emissions were derived from measurements of these samples using an inverse modelling framework. These results were evaluated to assess India's progress in phasing out ozone-depleting substances under the Montreal Protocol. India's combined CFC emissions are estimated to be 54 (27–86) Tg CO2 eq. yr−1 (5th and 95th confidence intervals are shown in parentheses). HCFC-22 emissions of 7.8 (6.0–9.9) Gg yr−1 are of similar magnitude to emissions of HFC-134a (8.2 (6.1–10.7) Gg yr−1). We estimate India's HFC-23 emissions to be 1.2 (0.9–1.5) Gg yr−1, and our results are consistent with resumed venting of HFC-23 by HCFC-22 manufacturers following the discontinuation of funding for abatement under the Clean Development Mechanism. We report small emissions of HFC-32 and HFC-143a and provide evidence to suggest that HFC-32 emissions were primarily due to fugitive emissions during manufacturing processes. A lack of significant correlation among HFC species and the small emissions derived for HFC-32 and HFC-143a indicate that in 2016, India's use of refrigerant blends R-410A, R-404A and R-507A was limited, despite extensive consumption elsewhere in the world. We also estimate emissions of the regulated chlorocarbons carbon tetrachloride and methyl chloroform from northern and central India to be 2.3 (1.5–3.4) and 0.07 (0.04–0.10) Gg yr−1 respectively. While the Montreal Protocol has been successful in reducing emissions of many ozone-depleting substances, growth in the global emission rates of the unregulated very short-lived substances poses an ongoing threat to the recovery of the ozone layer. Emissions of dichloromethane are found to be 96.5 (77.8–115.6) Gg yr−1, and our estimate suggests a 5-fold increase in emissions since the last estimate derived from atmospheric data in 2008. We estimate perchloroethene emissions from India and chloroform emissions from northern–central India to be 2.9 (2.5–3.3) and 32.2 (28.3–37.1) Gg yr−1 respectively. Given the rapid growth of India's economy and the likely increase in demand for halocarbons such as HFCs, the implementation of long-term atmospheric monitoring in the region is urgently required. Our results provide a benchmark against which future changes to India's halocarbon emissions may be evaluated.

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.

We reconstruct atmospheric abundances of the potent greenhouse gas c-C4F8 (perfluorocyclobutane, perfluorocarbon PFC-318) from measurements of in situ, archived, firn, and aircraft air samples with precisions of ∼1 %–2 % reported on the SIO-14 gravimetric calibration scale. Combined with inverse methods, we found near-zero atmospheric abundances from the early 1900s to the early 1960s, after which they rose sharply, reaching 1.66 ppt (parts per trillion dry-air mole fraction) in 2017. Global c-C4F8 emissions rose from near zero in the 1960s to 1.2±0.1 (1σ) Gg yr−1 in the late 1970s to late 1980s, then declined to 0.77±0.03 Gg yr−1 in the mid-1990s to early 2000s, followed by a rise since the early 2000s to 2.20±0.05 Gg yr−1 in 2017. These emissions are significantly larger than inventory-based emission estimates. Estimated emissions from eastern Asia rose from 0.36 Gg yr−1 in 2010 to 0.73 Gg yr−1 in 2016 and 2017, 31 % of global emissions, mostly from eastern China. We estimate emissions of 0.14 Gg yr−1 from northern and central India in 2016 and find evidence for significant emissions from Russia. In contrast, recent emissions from northwestern Europe and Australia are estimated to be small (≤1 % each). We suggest that emissions from China, India, and Russia are likely related to production of polytetrafluoroethylene (PTFE, “Teflon”) and other fluoropolymers and fluorochemicals that are based on the pyrolysis of hydrochlorofluorocarbon HCFC-22 (CHClF2) in which c-C4F8 is a known by-product. The semiconductor sector, where c-C4F8 is used, is estimated to be a small source, at least in South Korea, Japan, Taiwan, and Europe. Without an obvious correlation with population density, incineration of waste-containing fluoropolymers is probably a minor source, and we find no evidence of emissions from electrolytic production of aluminum in Australia. While many possible emissive uses of c-C4F8 are known and though we cannot categorically exclude unknown sources, the start of significant emissions may well be related to the advent of commercial PTFE production in 1947. Process controls or abatement to reduce the c-C4F8 by-product were probably not in place in the early decades, explaining the increase in emissions in the 1960s and 1970s. With the advent of by-product reporting requirements to the United Nations Framework Convention on Climate Change (UNFCCC) in the 1990s, concern about climate change and product stewardship, abatement, and perhaps the collection of c-C4F8 by-product for use in the semiconductor industry where it can be easily abated, it is conceivable that emissions in developed countries were stabilized and then reduced, explaining the observed emission reduction in the 1980s and 1990s. Concurrently, production of PTFE in China began to increase rapidly. Without emission reduction requirements, it is plausible that global emissions today are dominated by China and other developing countries. We predict that c-C4F8 emissions will continue to rise and that c-C4F8 will become the second most important emitted PFC in terms of CO2-equivalent emissions within a year or two. The 2017 radiative forcing of c-C4F8 (0.52 mW m−2) is small but emissions of c-C4F8 and other PFCs, due to their very long atmospheric lifetimes, essentially permanently alter Earth's radiative budget and should be reduced. Significant emissions inferred outside of the investigated regions clearly show that observational capabilities and reporting requirements need to be improved to understand global and country-scale emissions of PFCs and other synthetic greenhouse gases and ozone-depleting substances.

Under the UK-focused Greenhouse gAs and Uk and Global Emissions (GAUGE) project, two new tall tower greenhouse gas (GHG) observation sites were established in the 2013/2014 Northern Hemispheric winter. These sites, located at existing telecommunications towers, utilized a combination of cavity ring-down spectroscopy (CRDS) and gas chromatography (GC) to measure key GHGs (CO2, CH4, CO, N2O and SF6). Measurements were made at multiple intake heights on each tower. CO2 and CH4 dry mole fractions were calculated from either CRDS measurements of wet air, which were post-corrected with an instrument-specific empirical correction, or samples dried to between 0.05 % H2O and 0.3 % H2O using a Nafion® dryer, with a smaller correction applied for the residual H2O. The impact of these two drying strategies was examined. Drying with a Nafion® dryer was not found to have a significant effect on the observed CH4 mole fraction; however, Nafion® drying did cause a 0.02 µmol mol−1 CO2 bias. This bias was stable for sample CO2 mole fractions between 373 and 514 µmol mol−1 and for sample H2O up to 3.5 %. As the calibration and standard gases are treated in the same manner, the 0.02 µmol mol−1 CO2 bias is mostly calibrated out with the residual error (≪0.01 µmol mol−1 CO2) well below the World Meteorological Organization (WMO) reproducibility requirements. Of more concern was the error associated with the empirical instrument-specific water correction algorithms. These corrections are relatively stable and reproducible for samples with H2O between 0.2 % and 2.5 %, CO2 between 345 and 449 µmol mol−1, and CH4 between 1743 and 2145 nmol mol−1. However, the residual errors in these corrections increase to > 0.05 µmol mol−1 for CO2 and > 1 nmol mol−1 for CH4 (greater than the WMO internal reproducibility guidelines) at higher humidities and for samples with very low (CO2 and CH4 mole fractions. As such, water corrections calculated in this manner are not suitable for samples with low ( 2.5 %) water contents and either alternative correction methods should be used or partial drying or humidification considered prior to sample analysis.

We present a new modelling approach for assessing atmospheric emissions from a city, using an aircraft measurement sampling strategy similar to that employed by previous mass balance studies. Unlike conventional mass balance methods, our approach does not assume that city-scale emissions are confined to a well-defined urban area and that peri-urban emissions are negligible. We apply our new approach to a case study conducted in March 2016, investigating CO, CH4 and CO2 emissions from a region focussed around Greater London using aircraft sampling of the downwind plume. For each species, we simulate the flux per unit area that would be observed at the aircraft sampling locations based on emissions from the UK national inventory, transported using a Lagrangian dispersion model. To reconcile this simulation with the measured flux per unit area, assuming the transport model is not biased, we require that inventory values of CO, CH4 and CO2 are scaled by 1.03, 0.71 and 1.61, respectively. However, our result for CO2 should not be considered a direct comparison with the inventory which only includes anthropogenic fluxes. For comparison, we also calculate fluxes using a conventional mass balance approach and compare these to the emissions inventory aggregated over the Greater London area. Using this method we derive much higher inventory scale factors for all three gases, as a direct consequence of the failure to account for emissions outside the Greater London boundary. That substantially different conclusions are drawn using the conventional mass balance method demonstrates the danger of using this technique for cities whose emissions cannot be separated from significant surrounding sources.

We present a method to derive atmospheric-observation-based estimates of carbon dioxide (CO2) fluxes at the national scale, demonstrated using data from a network of surface tall-tower sites across the UK and Ireland over the period 2013–2014. The inversion is carried out using simulations from a Lagrangian chemical transport model and an innovative hierarchical Bayesian Markov chain Monte Carlo (MCMC) framework, which addresses some of the traditional problems faced by inverse modelling studies, such as subjectivity in the specification of model and prior uncertainties. Biospheric fluxes related to gross primary productivity and terrestrial ecosystem respiration are solved separately in the inversion and then combined a posteriori to determine net ecosystem exchange of CO2. Two different models, Data Assimilation Linked Ecosystem Carbon (DALEC) and Joint UK Land Environment Simulator (JULES), provide prior estimates for these fluxes. We carry out separate inversions to assess the impact of these different priors on the posterior flux estimates and evaluate the differences between the prior and posterior estimates in terms of missing model components. The Numerical Atmospheric dispersion Modelling Environment (NAME) is used to relate fluxes to the measurements taken across the regional network. Posterior CO2 estimates from the two inversions agree within estimated uncertainties, despite large differences in the prior fluxes from the different models. With our method, averaging results from 2013 and 2014, we find a total annual net biospheric flux for the UK of 8±79 Tg CO2 yr−1 (DALEC prior) and 64±85 Tg CO2 yr−1 (JULES prior), where negative values represent an uptake of CO2. These biospheric CO2 estimates show that annual UK biospheric sources and sinks are roughly in balance. These annual mean estimates consistently indicate a greater net release of CO2 than the prior estimates, which show much more pronounced uptake in summer months.

Atmospheric inverse modelling has become an increasingly useful tool for evaluating emissions of greenhouse gases including methane, nitrous oxide, and synthetic gases such as hydrofluorocarbons (HFCs). Atmospheric inversions for emissions of CO2 from fossil fuel combustion (ffCO2) are currently being developed. The aim of this paper is to investigate potential errors and uncertainties related to the spatial and temporal prior representation of emissions and modelled atmospheric transport for the inversion of ffCO2 emissions in the US state of California. We perform simulation experiments based on a network of ground-based observations of CO2 concentration and radiocarbon in CO2 (a tracer of ffCO2), combining prior (bottom-up) emission models and transport models currently used in many atmospheric studies. The potential effect of errors in the spatial and temporal distribution of prior emission estimates is investigated in experiments by using perturbed versions of the emission estimates used to create the pseudo-data. The potential effect of transport error was investigated by using three different atmospheric transport models for the prior and pseudo-data simulations. We find that the magnitude of biases in posterior total state emissions arising from errors in the spatial and temporal distribution in prior emissions in these experiments are 1 %–15 % of posterior total state emissions and are generally smaller than the 2σ uncertainty in posterior emissions. Transport error in these experiments introduces biases of −10 % to +6 % into posterior total state emissions. Our results indicate that uncertainties in posterior total state ffCO2 estimates arising from the choice of prior emissions or atmospheric transport model are on the order of 15 % or less for the ground-based network in California we consider. We highlight the need for temporal variations to be included in prior emissions and for continuing efforts to evaluate and improve the representation of atmospheric transport for regional ffCO2 inversions.

Decadal trends in the atmospheric abundances of carbon tetrafluoride (CF4) and nitrogen trifluoride (NF3) have been well characterised and have provided a time series of global total emissions. Information on locations of emissions contributing to the global total, however, is currently poor. We use a unique set of measurements between 2008 and 2015 from the Gosan station, Jeju Island, South Korea (part of the Advanced Global Atmospheric Gases Experiment network), together with an atmospheric transport model, to make spatially disaggregated emission estimates of these gases in East Asia. Due to the poor availability of good prior information for this study, our emission estimates are largely influenced by the atmospheric measurements. Notably, we are able to highlight emission hotspots of NF3 and CF4 in South Korea due to the measurement location. We calculate emissions of CF4 to be quite constant between the years 2008 and 2015 for both China and South Korea, with 2015 emissions calculated at 4.3±2.7 and 0.36±0.11 Gg yr−1, respectively. Emission estimates of NF3 from South Korea could be made with relatively small uncertainty at 0.6±0.07 Gg yr−1 in 2015, which equates to ∼ 1.6 % of the country's CO2 emissions. We also apply our method to calculate emissions of CHF3 (HFC-23) between 2008 and 2012, for which our results find good agreement with other studies and which helps support our choice in methodology for CF4 and NF3.

We describe the motivation, design, and execution of the Greenhouse gAs Uk and Global Emissions (GAUGE) project. The overarching scientific objective of GAUGE was to use atmospheric data to estimate the magnitude, distribution, and uncertainty of the UK greenhouse gas (GHG, defined here as CO2, CH4, and N2O) budget, 2013–2015. To address this objective, we established a multi-year and interlinked measurement and data analysis programme, building on an established tall-tower GHG measurement network. The calibrated measurement network comprises ground-based, airborne, ship-borne, balloon-borne, and space-borne GHG sensors. Our choice of measurement technologies and measurement locations reflects the heterogeneity of UK GHG sources, which range from small point sources such as landfills to large, diffuse sources such as agriculture. Atmospheric mole fraction data collected at the tall towers and on the ships provide information on sub-continental fluxes, representing the backbone to the GAUGE network. Additional spatial and temporal details of GHG fluxes over East Anglia were inferred from data collected by a regional network. Data collected during aircraft flights were used to study the transport of GHGs on local and regional scales. We purposely integrated new sensor and platform technologies into the GAUGE network, allowing us to lay the foundations of a strengthened UK capability to verify national GHG emissions beyond the project lifetime. For example, current satellites provide sparse and seasonally uneven sampling over the UK mainly because of its geographical size and cloud cover. This situation will improve with new and future satellite instruments, e.g. measurements of CH4 from the TROPOspheric Monitoring Instrument (TROPOMI) aboard Sentinel-5P. We use global, nested, and regional atmospheric transport models and inverse methods to infer geographically resolved CO2 and CH4 fluxes. This multi-model approach allows us to study model spread in a posteriori flux estimates. These models are used to determine the relative importance of different measurements to infer the UK GHG budget. Attributing observed GHG variations to specific sources is a major challenge. Within a UK-wide spatial context we used two approaches: (1) Δ14CO2 and other relevant isotopologues (e.g. δ13CCH4) from collected air samples to quantify the contribution from fossil fuel combustion and other sources, and (2) geographical separation of individual sources, e.g. agriculture, using a high-density measurement network. Neither of these represents a definitive approach, but they will provide invaluable information about GHG source attribution when they are adopted as part of a more comprehensive, long-term national GHG measurement programme. We also conducted a number of case studies, including an instrumented landfill experiment that provided a test bed for new technologies and flux estimation methods. We anticipate that results from the GAUGE project will help inform other countries on how to use atmospheric data to quantify their nationally determined contributions to the Paris Agreement.

We present the organization, instrumentation, datasets, data interpretation, modeling, and accomplishments of the multinational global atmospheric measurement program AGAGE (Advanced Global Atmospheric Gases Experiment). AGAGE is distinguished by its capability to measure globally, at high frequency, and at multiple sites all the important species in the Montreal Protocol and all the important non-carbon-dioxide (non-CO2) gases assessed by the Intergovernmental Panel on Climate Change (CO2 is also measured at several sites). The scientific objectives of AGAGE are important in furthering our understanding of global chemical and climatic phenomena. They are the following: (1) to accurately measure the temporal and spatial distributions of anthropogenic gases that contribute the majority of reactive halogen to the stratosphere and/or are strong infrared absorbers (chlorocarbons, chlorofluorocarbons – CFCs, bromocarbons, hydrochlorofluorocarbons – HCFCs, hydrofluorocarbons – HFCs and polyfluorinated compounds (perfluorocarbons – PFCs), nitrogen trifluoride – NF3, sulfuryl fluoride – SO2F2, and sulfur hexafluoride – SF6) and use these measurements to determine the global rates of their emission and/or destruction (i.e., lifetimes); (2) to accurately measure the global distributions and temporal behaviors and determine the sources and sinks of non-CO2 biogenic–anthropogenic gases important to climate change and/or ozone depletion (methane – CH4, nitrous oxide – N2O, carbon monoxide – CO, molecular hydrogen – H2, methyl chloride – CH3Cl, and methyl bromide – CH3Br); (3) to identify new long-lived greenhouse and ozone-depleting gases (e.g., SO2F2, NF3, heavy PFCs (C4F10, C5F12, C6F14, C7F16, and C8F18) and hydrofluoroolefins (HFOs; e.g., CH2 = CFCF3) have been identified in AGAGE), initiate the real-time monitoring of these new gases, and reconstruct their past histories from AGAGE, air archive, and firn air measurements; (4) to determine the average concentrations and trends of tropospheric hydroxyl radicals (OH) from the rates of destruction of atmospheric trichloroethane (CH3CCl3), HFCs, and HCFCs and estimates of their emissions; (5) to determine from atmospheric observations and estimates of their destruction rates the magnitudes and distributions by region of surface sources and sinks of all measured gases; (6) to provide accurate data on the global accumulation of many of these trace gases that are used to test the synoptic-, regional-, and global-scale circulations predicted by three-dimensional models; and (7) to provide global and regional measurements of methane, carbon monoxide, and molecular hydrogen and estimates of hydroxyl levels to test primary atmospheric oxidation pathways at midlatitudes and the tropics. Network Information and Data Repository: http://agage.mit.edu/data or http://cdiac.ess-dive.lbl.gov/ndps/alegage.html (https://doi.org/10.3334/CDIAC/atg.db1001).

A network of three tall tower measurement stations was set up in 2012 across the United Kingdom to expand measurements made at the long-term background northern hemispheric site, Mace Head, Ireland. Reliable and precise in situ greenhouse gas (GHG) analysis systems were developed and deployed at three sites in the UK with automated instrumentation measuring a suite of GHGs. The UK Deriving Emissions linked to Climate Change (UK DECC) network uses tall (165–230 m) open-lattice telecommunications towers, which provide a convenient platform for boundary layer trace gas sampling. In this paper we describe the automated measurement system and first results from the UK DECC network for CO2, CH4, N2O, SF6, CO and H2. CO2 and CH4 are measured at all of the UK DECC sites by cavity ring-down spectroscopy (CRDS) with multiple inlet heights at two of the three tall tower sites to assess for boundary layer stratification. The short-term precisions (1σ on 1 min means) of CRDS measurements at background mole fractions for January 2012 to September 2015 is −1 for CO2 and −1 for CH4. Repeatability of standard injections (1σ) is −1 for CO2 and −1 for CH4 for the same time period. N2O and SF6 are measured at three of the sites, and CO and H2 measurements are made at two of the sites, from a single inlet height using gas chromatography (GC) with an electron capture detector (ECD), flame ionisation detector (FID) or reduction gas analyser (RGA). Repeatability of individual injections (1σ) on GC and RGA instruments between January 2012 and September 2015 for CH4, N2O, SF6, CO and H2 measurements were −1, −1, −1, −1 and −1, respectively. Instrumentation in the network is fully automated and includes sensors for measuring a variety of instrumental parameters such as flow, pressures, and sampling temperatures. Automated alerts are generated and emailed to site operators when instrumental parameters are not within defined set ranges. Automated instrument shutdowns occur for critical errors such as carrier gas flow rate deviations. Results from the network give good spatial and temporal coverage of atmospheric mixing ratios within the UK since early 2012. Results also show that all measured GHGs are increasing in mole fraction over the selected reporting period and, except for SF6, exhibit a seasonal trend. CO2 and CH4 also show strong diurnal cycles, with night-time maxima and daytime minima in mole fractions.

High frequency measurements of trifluoromethane (HFC-23, CHF3), a potent hydrofluorocarbon greenhouse gas, largely emitted to the atmosphere as a by-product of the production of the hydrochlorofluorocarbon HCFC-22 (CHClF2), at five core stations of the Advanced Global Atmospheric Gases Experiment (AGAGE) network, combined with measurements on firn air, old Northern Hemisphere air samples and Cape Grim Air Archive (CGAA) air samples, are used to explore the current and historic changes in the atmospheric abundance of HFC-23. These measurements are used in combination with the AGAGE 2-D atmospheric 12-box model and a Bayesian inversion methodology to determine model atmospheric mole fractions and the history of global HFC-23 emissions. The global modelled annual mole fraction of HFC-23 in the background atmosphere was 28.9 ± 0.6 pmol mol−1 at the end of 2016, representing a 28 % increase from 22.6 ± 0.4 pmol mol−1 in 2009. Over the same time frame, the modelled mole fraction of HCFC-22 increased by 19 % from 199 ± 2 to 237 ± 2 pmol mol−1. However, unlike HFC-23, the annual average HCFC-22 growth rate slowed from 2009 to 2016 at an annual average rate of −0.5 pmol mol−1 yr−2. This slowing atmospheric growth is consistent with HCFC-22 moving from dispersive (high fractional emissions) to feedstock (low fractional emissions) uses, with HFC-23 emissions remaining as a consequence of incomplete mitigation from all HCFC-22 production.Our results demonstrate that, following a minimum in HFC-23 global emissions in 2009 of 9.6 ± 0.6, emissions increased to a maximum in 2014 of 14.5 ± 0.6 Gg yr−1 and then declined to 12.7 ± 0.6 Gg yr−1 (157 Mt CO2 eq. yr−1) in 2016. The 2009 emissions minimum is consistent with estimates based on national reports and is likely a response to the implementation of the Clean Development Mechanism (CDM) to mitigate HFC-23 emissions by incineration in developing (non-Annex 1) countries under the Kyoto Protocol. Our derived cumulative emissions of HFC-23 during 2010–2016 were 89 ± 2 Gg (1.1 ± 0.2 Gt CO2 eq.), which led to an increase in radiative forcing of 1.0 ± 0.1 mW m−2 over the same period. Although the CDM had reduced global HFC-23 emissions, it cannot now offset the higher emissions from increasing HCFC-22 production in non-Annex 1 countries, as the CDM was closed to new entrants in 2009. We also find that the cumulative European HFC-23 emissions from 2010 to 2016 were ∼ 1.3 Gg, corresponding to just 1.5 % of cumulative global HFC-23 emissions over this same period. The majority of the increase in global HFC-23 emissions since 2010 is attributed to a delay in the adoption of mitigation technologies, predominantly in China and East Asia. However, a reduction in emissions is anticipated, when the Kigali 2016 amendment to the Montreal Protocol, requiring HCFC and HFC production facilities to introduce destruction of HFC-23, is fully implemented.

We present inverse modelling (top down) estimates of European methane (CH4) emissions for 2006–2012 based on a new quality-controlled and harmonised in situ data set from 18 European atmospheric monitoring stations. We applied an ensemble of seven inverse models and performed four inversion experiments, investigating the impact of different sets of stations and the use of a priori information on emissions. The inverse models infer total CH4 emissions of 26.8 (20.2–29.7) Tg CH4 yr−1 (mean, 10th and 90th percentiles from all inversions) for the EU-28 for 2006–2012 from the four inversion experiments. For comparison, total anthropogenic CH4 emissions reported to UNFCCC (bottom up, based on statistical data and emissions factors) amount to only 21.3 Tg CH4 yr−1 (2006) to 18.8 Tg CH4 yr−1 (2012). A potential explanation for the higher range of top-down estimates compared to bottom-up inventories could be the contribution from natural sources, such as peatlands, wetlands, and wet soils. Based on seven different wetland inventories from the Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP), total wetland emissions of 4.3 (2.3–8.2) Tg CH4 yr−1 from the EU-28 are estimated. The hypothesis of significant natural emissions is supported by the finding that several inverse models yield significant seasonal cycles of derived CH4 emissions with maxima in summer, while anthropogenic CH4 emissions are assumed to have much lower seasonal variability. Taking into account the wetland emissions from the WETCHIMP ensemble, the top-down estimates are broadly consistent with the sum of anthropogenic and natural bottom-up inventories. However, the contribution of natural sources and their regional distribution remain rather uncertain. Furthermore, we investigate potential biases in the inverse models by comparison with regular aircraft profiles at four European sites and with vertical profiles obtained during the Infrastructure for Measurement of the European Carbon Cycle (IMECC) aircraft campaign. We present a novel approach to estimate the biases in the derived emissions, based on the comparison of simulated and measured enhancements of CH4 compared to the background, integrated over the entire boundary layer and over the lower troposphere. The estimated average regional biases range between −40 and 20 % at the aircraft profile sites in France, Hungary and Poland.

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.

High-frequency, in situ global observations of HCFC-22 (CHClF2), HCFC-141b (CH3CCl2F), HCFC-142b (CH3CClF2) and HCFC-124 (CHClFCF3) and their main HFC replacements, HFC-134a (CH2FCF3), HFC-125 (CHF2CF3), HFC-143a (CH3CF3) and HFC-32 (CH2F2), have been used to determine their changing global growth rates and emissions in response to the Montreal Protocol and its recent amendments. Global mean mole fractions of HCFC-22, -141b, and -142b have increased throughout the observation period, reaching 234, 24.3 and 22.4 pmol mol−1, respectively, in 2015. HCFC-124 reached a maximum global mean mole fraction of 1.48 pmol mol−1 in 2007 and has since declined by 23 % to 1.14 pmol mol−1 in 2015. The HFCs all show increasing global mean mole fractions. In 2015 the global mean mole fractions (pmol mol−1) were 83.3 (HFC-134a), 18.4 (HFC-125), 17.7 (HFC-143a) and 10.5 (HFC-32). The 2007 adjustment to the Montreal Protocol required the accelerated phase-out of emissive uses of HCFCs with global production and consumption capped in 2013 to mitigate their environmental impact as both ozone-depleting substances and important greenhouse gases. We find that this change has coincided with a stabilisation, or moderate reduction, in global emissions of the four HCFCs with aggregated global emissions in 2015 of 449 ± 75 Gg yr−1, in CO2 equivalent units (CO2 eq.) 0.76 ± 0.1 Gt yr−1, compared with 483 ± 70 Gg yr−1 (0.82 ± 0.1 Gt yr−1 CO2 eq.) in 2010 (uncertainties are 1σ throughout this paper). About 79 % of the total HCFC atmospheric burden in 2015 is HCFC-22, where global emissions appear to have been relatively similar since 2011, in spite of the 2013 cap on emissive uses. We attribute this to a probable increase in production and consumption of HCFC-22 in Montreal Protocol Article 5 (developing) countries and the continuing release of HCFC-22 from the large banks which dominate HCFC global emissions. Conversely, the four HFCs all show increasing mole fraction growth rates with aggregated global HFC emissions of 327 ± 70 Gg yr−1 (0.65 ± 0.12 Gt yr−1 CO2 eq.) in 2015 compared to 240 ± 50 Gg yr−1 (0.47 ± 0.08 Gt yr−1 CO2 eq.) in 2010. We also note that emissions of HFC-125 and HFC-32 appear to have increased more rapidly averaged over the 5-year period 2011–2015, compared to 2006–2010. As noted by Lunt et al. (2015) this may reflect a change to refrigerant blends, such as R-410A, which contain HFC-32 and -125 as a 50 : 50 blend.

Carbon tetrachloride (CCl4) is a long-lived radiatively active compound with the ability to destroy stratospheric ozone. Due to its inclusion in the Montreal Protocol on Substances that Deplete the Ozone Layer (MP), the last two decades have seen a sharp decrease in its large-scale emissive use with a consequent decline in its atmospheric mole fractions. However, the MP restrictions do not apply to the use of carbon tetrachloride as feedstock for the production of other chemicals, implying the risk of fugitive emissions from the industry sector. The occurrence of such unintended emissions is suggested by a significant discrepancy between global emissions as derived from reported production and feedstock usage (bottom-up emissions), and those based on atmospheric observations (top-down emissions). In order to better constrain the atmospheric budget of carbon tetrachloride, several studies based on a combination of atmospheric observations and inverse modelling have been conducted in recent years in various regions of the world. This study is focused on the European scale and based on long-term high-frequency observations at three European sites, combined with a Bayesian inversion methodology. We estimated that average European emissions for 2006–2014 were 2.2 (± 0.8) Gg yr−1, with an average decreasing trend of 6.9 % per year. Our analysis identified France as the main source of emissions over the whole study period, with an average contribution to total European emissions of approximately 26 %. The inversion was also able to allow the localisation of emission "hot spots" in the domain, with major source areas in southern France, central England (UK) and Benelux (Belgium, the Netherlands, Luxembourg), where most industrial-scale production of basic organic chemicals is located. According to our results, European emissions correspond, on average, to 4.0 % of global emissions for 2006–2012. Together with other regional studies, our results allow a better constraint of the global budget of carbon tetrachloride and a better quantification of the gap between top-down and bottom-up estimates.

Atmospheric trace gas inversions often attempt to attribute fluxes to a high-dimensional grid using observations. To make this problem computationally feasible, and to reduce the degree of under-determination, some form of dimension reduction is usually performed. Here, we present an objective method for reducing the spatial dimension of the parameter space in atmospheric trace gas inversions. In addition to solving for a set of unknowns that govern emissions of a trace gas, we set out a framework that considers the number of unknowns to itself be an unknown. We rely on the well-established reversible-jump Markov chain Monte Carlo algorithm to use the data to determine the dimension of the parameter space. This framework provides a single-step process that solves for both the resolution of the inversion grid, as well as the magnitude of fluxes from this grid. Therefore, the uncertainty that surrounds the choice of aggregation is accounted for in the posterior parameter distribution. The posterior distribution of this transdimensional Markov chain provides a naturally smoothed solution, formed from an ensemble of coarser partitions of the spatial domain. We describe the form of the reversible-jump algorithm and how it may be applied to trace gas inversions. We build the system into a hierarchical Bayesian framework in which other unknown factors, such as the magnitude of the model uncertainty, can also be explored. A pseudo-data example is used to show the usefulness of this approach when compared to a subjectively chosen partitioning of a spatial domain. An inversion using real data is also shown to illustrate the scales at which the data allow for methane emissions over north-west Europe to be resolved.

High frequency, in situ observations from 11 globally distributed sites for the period 1994–2014 and archived air measurements dating from 1978 onward have been used to determine the global growth rate of 1,1-difluoroethane (HFC-152a, CH3CHF2). These observations have been combined with a range of atmospheric transport models to derive global emission estimates in a top-down approach. HFC-152a is a greenhouse gas with a short atmospheric lifetime of about 1.5 years. Since it does not contain chlorine or bromine, HFC-152a makes no direct contribution to the destruction of stratospheric ozone and is therefore used as a substitute for the ozone depleting chlorofluorocarbons (CFCs) and hydrochlorofluorocarbons (HCFCs). The concentration of HFC-152a has grown substantially since the first direct measurements in 1994, reaching a maximum annual global growth rate of 0.84 ± 0.05 ppt yr−1 in 2006, implying a substantial increase in emissions up to 2006. However, since 2007, the annual rate of growth has slowed to 0.38 ± 0.04 ppt yr−1 in 2010 with a further decline to an annual average rate of growth in 2013–2014 of −0.06 ± 0.05 ppt yr−1. The annual average Northern Hemisphere (NH) mole fraction in 1994 was 1.2 ppt rising to an annual average mole fraction of 10.1 ppt in 2014. Average annual mole fractions in the Southern Hemisphere (SH) in 1998 and 2014 were 0.84 and 4.5 ppt, respectively. We estimate global emissions of HFC-152a have risen from 7.3 ± 5.6 Gg yr−1 in 1994 to a maximum of 54.4 ± 17.1 Gg yr−1 in 2011, declining to 52.5 ± 20.1 Gg yr−1 in 2014 or 7.2 ± 2.8 Tg-CO2 eq yr−1. Analysis of mole fraction enhancements above regional background atmospheric levels suggests substantial emissions from North America, Asia, and Europe. Global HFC emissions (so called “bottom up” emissions) reported by the United Nations Framework Convention on Climate Change (UNFCCC) are based on cumulative national emission data reported to the UNFCCC, which in turn are based on national consumption data. There appears to be a significant underestimate ( > 20 Gg) of “bottom-up” reported emissions of HFC-152a, possibly arising from largely underestimated USA emissions and undeclared Asian emissions.

Purpose: This research explores the nature of industry members willing to participate in agricultural industry school partnerships (ISPs) by understanding who these participants are, and how and why they want to participate. This will contribute to a greater understanding of the nature of ISPs. Methodology: A mixed methods case study utilising surveys and semi-structured interviews was used to collect data from 54 agricultural industry members from 2021-2023. Findings: Participants overwhelmingly want to partake in ISPs to promote their industry and the range of career opportunities. How they prefer to participate is mostly through hands-on learning and storytelling. Identified barriers include time, confidence, experience and teacher understanding, which may affect how and why they want to participate. Practical implications: These findings will contribute to a greater understanding of the nature of agricultural ISPs, helping those creating ISPs to consider and understand all stakeholders to deliver quality future partnerships. Theoretical implications: This paper explores industry participants as an important component of agricultural ISPs when theorised as an ecological system. Originality: This research analyses industry participants' perspectives of industry school partnerships, which are rarely identified in the literature.

The UK is one of several countries around the world that has enacted legislation to reduce its greenhouse gas emissions. In this study, we present top-down emissions of methane (CH4) and nitrous oxide (N2O) for the UK and Ireland over the period August~2012 to August~2014. These emissions were inferred using measurements from a network of four sites around the two countries. We used a hierarchical Bayesian inverse framework to infer fluxes as well as a set of covariance parameters that describe uncertainties in the system. We inferred average UK total emissions of 2.09 (1.65–2.67) Tg yr−1 CH4 and 0.101 (0.068–0.150) Tg yr−1 N2O and found our derived UK estimates to be generally lower than the a priori emissions, which consisted primarily of anthropogenic sources and with a smaller contribution from natural sources. We used sectoral distributions from the UK National Atmospheric Emissions Inventory (NAEI) to determine whether these discrepancies can be attributed to specific source sectors. Because of the distinct distributions of the two dominant CH4 emissions sectors in the UK, agriculture and waste, we found that the inventory may be overestimated in agricultural CH4 emissions. We found that annual mean N2O emissions were consistent with both the prior and the anthropogenic inventory but we derived a significant seasonal cycle in emissions. This seasonality is likely due to seasonality in fertilizer application and in environmental drivers such as temperature and rainfall, which are not reflected in the annual resolution inventory. Through the hierarchical Bayesian inverse framework, we quantified uncertainty covariance parameters and emphasized their importance for high-resolution emissions estimation. We inferred average model errors of approximately 20 and 0.4 ppb and correlation timescales of 1.0 (0.72–1.43) and 2.6 (1.9–3.9) days for CH4 and N2O, respectively. These errors are a combination of transport model errors as well as errors due to unresolved emissions processes in the inventory. We found the largest CH4 errors at the Tacolneston station in eastern England, which may be due to sporadic emissions from landfills and offshore gas in the North Sea.

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-frequency, in situ observations from the Advanced Global Atmospheric Gases Experiment (AGAGE), for the period 2003 to 2012, combined with archive flask measurements dating back to 1977, have been used to capture the rapid growth of HFC-143a (CH3CF3) and HFC-32 (CH2F2) mole fractions and emissions into the atmosphere. Here we report the first in situ global measurements of these two gases. HFC-143a and HFC-32 are the third and sixth most abundant hydrofluorocarbons (HFCs) respectively and they currently make an appreciable contribution to the HFCs in terms of atmospheric radiative forcing (1.7 ± 0.04 and 0.7 ± 0.02 mW m−2 in 2012 respectively). In 2012 the global average mole fraction of HFC-143a was 13.4 ± 0.3 ppt (1σ) in the lower troposphere and its growth rate was 1.4 ± 0.04 ppt yr−1; HFC-32 had a global mean mole fraction of 6.2 ± 0.2 ppt and a growth rate of 1.1 ± 0.04 ppt yr−1 in 2012. The extensive observations presented in this work have been combined with an atmospheric transport model to simulate global atmospheric abundances and derive global emission estimates. It is estimated that 23 ± 3 Gg yr−1 of HFC-143a and 21 ± 11 Gg yr−1 of HFC-32 were emitted globally in 2012, and the emission rates are estimated to be increasing by 7 ± 5% yr−1 for HFC-143a and 14 ± 11% yr−1 for HFC-32.

We present a hierarchical Bayesian method for atmospheric trace gas inversions. This method is used to estimate emissions of trace gases as well as "hyper-parameters" that characterize the probability density functions (PDFs) of the a priori emissions and model-measurement covariances. By exploring the space of "uncertainties in uncertainties", we show that the hierarchical method results in a more complete estimation of emissions and their uncertainties than traditional Bayesian inversions, which rely heavily on expert judgment. We present an analysis that shows the effect of including hyper-parameters, which are themselves informed by the data, and show that this method can serve to reduce the effect of errors in assumptions made about the a priori emissions and model-measurement uncertainties. We then apply this method to the estimation of sulfur hexafluoride (SF6) emissions over 2012 for the regions surrounding four Advanced Global Atmospheric Gases Experiment (AGAGE) stations. We find that improper accounting of model representation uncertainties, in particular, can lead to the derivation of emissions and associated uncertainties that are unrealistic and show that those derived using the hierarchical method are likely to be more representative of the true uncertainties in the system. We demonstrate through this SF6 case study that this method is less sensitive to outliers in the data and to subjective assumptions about a priori emissions and model-measurement uncertainties than traditional methods.

Bromine plays an important role in ozone chemistry in both the troposphere and stratosphere. When measured by mass, bromoform (CHBr3) is thought to be the largest organic source of bromine to the atmosphere. While seaweed and phytoplankton are known to be dominant sources, the size and the geographical distribution of CHBr3 emissions remains uncertain. Particularly little is known about emissions from the Maritime Continent, which have usually been assumed to be large, and which appear to be especially likely to reach the stratosphere. In this study we aim to reduce this uncertainty by combining the first multi-annual set of CHBr3 measurements from this region, and an inversion process, to investigate systematically the distribution and magnitude of CHBr3 emissions. The novelty of our approach lies in the application of the inversion method to CHBr3. We find that local measurements of a short-lived gas like CHBr3 can be used to constrain emissions from only a relatively small, sub-regional domain. We then obtain detailed estimates of CHBr3 emissions within this area, which appear to be relatively insensitive to the assumptions inherent in the inversion process. We extrapolate this information to produce estimated emissions for the entire tropics (defined as 20° S–20° N) of 225 Gg CHBr3 yr−1. The ocean in the area we base our extrapolations upon is typically somewhat shallower, and more biologically productive, than the tropical average. Despite this, our tropical estimate is lower than most other recent studies, and suggests that CHBr3 emissions in the coastline-rich Maritime Continent may not be stronger than emissions in other parts of the tropics.

High-frequency atmospheric measurements of methane (CH4), nitrous oxide (N2O) and sulfur hexafluoride (SF6) from Darjeeling, India are presented from December 2011 (CH4)/March 2012 (N2O and SF6) through February 2013. These measurements were made on a gas chromatograph equipped with a flame ionization detector and electron capture detector, and were calibrated on the Tohoku University, the Scripps Institution of Oceanography (SIO)-98 and SIO-2005 scales for CH4, N2O and SF6, respectively. The observations show large variability and frequent pollution events in CH4 and N2O mole fractions, suggesting significant sources in the regions sampled by Darjeeling throughout the year. By contrast, SF6 mole fractions show little variability and only occasional pollution episodes, likely due to weak sources in the region. Simulations using the Numerical Atmospheric dispersion Modelling Environment (NAME) particle dispersion model suggest that many of the enhancements in the three gases result from the transport of pollutants from the densely populated Indo-Gangetic Plains of India to Darjeeling. The meteorology of the region varies considerably throughout the year from Himalayan flows in the winter to the strong south Asian summer monsoon. The model is consistent in simulating a diurnal cycle in CH4 and N2O mole fractions that is present during the winter but absent in the summer and suggests that the signals measured at Darjeeling are dominated by large-scale (~100 km) flows rather than local (

We use NAME, a trajectory model, to investigate the routes and timescales over which air parcels reach the tropical tropopause layer (TTL). Our aim is to assist the planning of aircraft campaigns focussed on improving knowledge of such transport. We focus on Southeast Asia and the Western Pacific which appears to be a particularly important source of air that enters the TTL. We first study the TTL above Borneo in November 2008, under neutral El Niño/Southern Oscillation (ENSO) conditions. Air parcels (trajectories) arriving in the lower TTL (below ~15 km) are most likely to have travelled from the boundary layer (BL;

We present a method for estimating emissions of long-lived trace gases from a sparse global network of high-frequency observatories, using both a global Eulerian chemical transport model and Lagrangian particle dispersion model. Emissions are derived in a single step after determining sensitivities of the observations to initial conditions, the high-resolution emissions field close to observation points, and larger regions further from the measurements. This method has the several advantages over inversions using one type of model alone, in that: high-resolution simulations can be carried out in limited domains close to the measurement sites, with lower resolution being used further from them; the influence of errors due to aggregation of emissions close to the measurement sites can be minimized; assumptions about boundary conditions to the Lagrangian model do not need to be made, since the entire emissions field is estimated; any combination of appropriate models can be used, with no code modification. Because the sensitivity to the entire emissions field is derived, the estimation can be carried out using traditional statistical methods without the need for multiple steps in the inversion. We demonstrate the utility of this approach by determining global SF6 emissions using measurements from the Advanced Global Atmospheric Gases Experiment (AGAGE) between 2007 and 2009. The global total and large-scale patterns of the derived emissions agree well with previous studies, whilst allowing emissions to be determined at higher resolution than has previously been possible, and improving the agreement between the modeled and observed mole fractions at some sites.

Continuous high-frequency in situ measurements of a range of non-methane hydrocarbons have been made at Mace Head since January 2005. Mace Head is a background Northern Hemispheric site situated on the eastern edge of the Atlantic. Five year measurements (2005–2009) of six C2–C5 non-methane hydrocarbons have been separated into baseline Northern Hemispheric and European polluted air masses, among other sectors. Seasonal cycles in baseline Northern Hemispheric air masses and European polluted air masses arriving at Mace Head have been studied. Baseline air masses show a broad summer minima between June and September for shorter lived species, longer lived species show summer minima in July/August. All species displayed a winter maxima in February. European air masses showed baseline elevated mole fractions for all non-methane hydrocarbons. Largest elevations (of up to 360 ppt for ethane maxima) from baseline data were observed in winter maxima, with smaller elevations observed during the summer. Analysis of temporal trends using the Mann-Kendall test showed small (−1) but statistically significant decreases in the butanes and i-pentane between 2005 and 2009 in European air. No significant trends were found for any species in baseline air.

We report measurements of bromoform made by gas chromatography during the OP3 campaign in 2008. Measurements were made simultaneously for a few days at the World Meteorological Organization (WMO) Global Atmospheric Watch (GAW) site in the Danum Valley, a rainforest location in Sabah, Borneo, and at a nearby coastal site at Kunak. Background values at Kunak were higher than those measured in the rainforest (2–5 ppt compared with 1 ppt) and excursions away from the background were very much higher, reaching 10 s of ppt. Measurements of C2Cl4, an industrial tracer, showed no significant difference in background at the two sites. Modelling using two different models can reproduce a number of the observed features. The data are consistent with a strong, local coastal source of bromoform in eastern Sabah and can be used to infer the strength of the source of bromoform in South East Asia. However, they provide only a very weak constraint on global emissions. The global model results highlight the difficulty for short-lived species of extrapolating limited duration, local measurements to a global source.

Continuous high-frequency measurements of atmospheric molecular hydrogen have been made at Mace Head atmospheric research station on the west coast of Ireland from March 1994 to December 2008. The presented data provides information on long term trends and seasonal cycles of hydrogen in background northern hemispheric air. Individual measurements have been sorted using a Lagrangian dispersion model to separate clean background air from regionally polluted European air masses and those transported from southerly latitudes. No significant trend was observed in background northern hemispheric air over the 15 year record, elevations in yearly means were accounted for from large scale biomass burning events. Seasonal cycles show the expected pattern with maxima in spring and minima in late autumn. The mean hydrogen mole fraction in baseline northern hemispheric air was found to be 500.1 ppb. Air transported from southerly latitudes showed an elevation from baseline mean of 11.0 ppb, reflecting both the latitudinal gradient of hydrogen, with higher concentrations in the Southern Hemisphere, and the photochemical source of hydrogen from low northern latitudes. European polluted air masses arriving at Mace Head showed mean elevation of 5.3 ppb from baseline air masses, reflecting hydrogen's source from primary emissions like fossil fuel combustion. Forward modelling of transport of hydrogen to Mace Head suggests that the ratio of hydrogen to carbon monoxide in primary emissions is considerably less in non-traffic sources than traffic sources.