Search

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.

Large stores of carbon frozen in the Arctic as permafrost are under threat of thawing as temperatures in the Arctic increase at a rate four times that of the global mean. This study uses recent atmospheric data from the North Slope of Alaska and Northeast Siberia to provide the most up-to-date assessment of emissions and trends from these two major high-latitude regions.We use two methods to quantify emissions and assess trends across different seasons: 1) Using 35 years of data from Barrow, Alaska, a wind sector method that quantifies trends in emissions by calculating concentration enhancements over background using wind direction to identify the land sector (first used in Sweeney et al., 2016), and 2) using Barrow data and recent data from three Siberian stations, an inversion method with the high-resolution atmospheric transport model NAME that quantifies both emissions and trends from these regions. We use results from these two approaches to quantify the temperature sensitivity (Q10) of soils based on correlations between surface air and ground temperatures with methane emissions.With the inclusion of atmospheric concentration data after 2015, we now show that land emissions from the North Slope of Alaska have been increasing since 2000, reflecting a change from previous analyses, which showed no significant increase in summertime methane emissions between 1986-2014 (Sweeney et al., 2016). We find significant emissions from the late shoulder season (Autumn-Winter), which has historically been undermeasured and underrepresented in models and emissions inventories, in this region of Alaska as well as two North-eastern Siberian locations, the Taymyr Peninsula and the East Siberian Lowlands. We show that emissions during this late-season have been growing over the past two decades at a rate similar to summer-time emissions.Our results based on long-term atmospheric data can be used to show that important change is happening in the Arctic, with an increasing emissions trend and the presence of late shoulder season emissions.

With the successful implementation of the Montreal Protocol on Substances that Deplete the Ozone Layer, the atmospheric abundance of ozone-depleting substances continues to decrease slowly and the Antarctic ozone hole is showing signs of recovery. However, growing emissions of unregulated short-lived anthropogenic chlorocarbons are offsetting some of these gains. Here, we report an increase in emissions from China of the industrially produced chlorocarbon, dichloromethane (CH2Cl2). The emissions grew from 231 (213–245) Gg yr−1 in 2011 to 628 (599–658) Gg yr−1 in 2019, with an average annual increase of 13 (12–15) %, primarily from eastern China. The overall increase in CH2Cl2 emissions from China has the same magnitude as the global emission rise of 354 (281−427) Gg yr−1 over the same period. If global CH2Cl2 emissions remain at 2019 levels, they could lead to a delay in Antarctic ozone recovery of around 5 years compared to a scenario with no CH2Cl2 emissions., Dichloromethane (CH2Cl2) is an unregulated ozone depleting substance whose emissions have strongly increased in recent years. Here, the authors show that rising emissions of dichloromethane in China between 2011 and 2019 can explain much of this global increase.

Methane (CH 4 ) mole fractions from the large semiseasonal Llanos de Moxos wetlands (∼70,000 km 2 ) in northern Bolivia were measured by aircraft flights and ground sampling during early March 2019 (late wet season). Daily fluxes of CH 4 determined from the measurements using box models and inverse modeling were between 168 (± 50) and 456 (± 145) mg CH 4 ⋅m −2 ⋅d −1 for the areas overflown, very high compared with those of previous Amazon basin studies. If the seasonality of the CH 4 emissions is comparable to other parts of the Amazon Basin, the region could contribute as much as 8% of annual Amazonian CH 4 emissions.

Nitrous oxide is a potent greenhouse gas (GHG) and ozone-depleting substance, whose atmospheric abundance has risen throughout the contemporary record. In this work, we carry out the first global hierarchical Bayesian inversion to solve for nitrous oxide emissions, which includes prior emissions with truncated Gaussian distributions and Gaussian model errors, in order to examine the drivers of the atmospheric surface growth rate. We show that both emissions and climatic variability are key drivers of variations in the surface nitrous oxide growth rate between 2011 and 2020. We derive increasing global nitrous oxide emissions, which are mainly driven by emissions between 0 and 30∘ N, with the highest emissions recorded in 2020. Our mean global total emissions for 2011–2020 of 17.2 (16.7–17.7 at the 95 % credible intervals) Tg N yr−1, comprising of 12.0 (11.2–12.8) Tg N yr−1 from land and 5.2 (4.5–5.9) Tg N yr−1 from ocean, agrees well with previous studies, but we find that emissions are poorly constrained for some regions of the world, particularly for the oceans. The prior emissions used in this and other previous work exhibit a seasonal cycle in the extra-tropical Northern Hemisphere that is out of phase with the posterior solution, and there is a substantial zonal redistribution of emissions from the prior to the posterior. Correctly characterizing the uncertainties in the system, for example in the prior emission fields, is crucial for deriving posterior fluxes that are consistent with observations. In this hierarchical inversion, the model-measurement discrepancy and the prior flux uncertainty are informed by the data, rather than solely through “expert judgement”. We show cases where this framework provides different plausible adjustments to the prior fluxes compared to inversions using widely adopted, fixed uncertainty constraints.

Methane (CH4) is a potent greenhouse gas with a warming potential 84 times that of carbon dioxide (CO2) over a 20-year period. Atmospheric CH4 concentrations have been rising since the nineteenth century but the cause of large increases post-2007 is disputed. Tropical wetlands are thought to account for ∼20% of global CH4 emissions, but African tropical wetlands are understudied and their contribution is uncertain. In this work, we use the first airborne measurements of CH4 sampled over three wetland areas in Zambia to derive emission fluxes. Three independent approaches to flux quantification from airborne measurements were used: Airborne mass balance, airborne eddy-covariance, and an atmospheric inversion. Measured emissions (ranging from 5 to 28 mg m−2 hr−1) were found to be an order of magnitude greater than those simulated by land surface models (ranging from 0.6 to 3.9 mg m−2 hr−1), suggesting much greater emissions from tropical wetlands than currently accounted for. The prevalence of such underestimated CH4 sources may necessitate additional reductions in anthropogenic greenhouse gas emissions to keep global warming below a threshold of 2°C above preindustrial levels.

We present the first spatially resolved distribution of the [Formula: see text] signature of wetland methane emissions and assess its impact on atmospheric [Formula: see text]. The [Formula: see text] signature map is derived by relating [Formula: see text] of precipitation to measured [Formula: see text] of methane wetland emissions at a variety of wetland types and locations. This results in strong latitudinal variation in the wetland [Formula: see text] source signature. When [Formula: see text] is simulated in a global atmospheric model, little difference is found in global mean, inter-hemispheric difference and seasonal cycle if the spatially varying [Formula: see text] source signature distribution is used instead of a globally uniform value. This is because atmospheric [Formula: see text] is largely controlled by OH fractionation. However, we show that despite these small differences, using atmospheric records of [Formula: see text] to infer changes in the wetland emissions distribution requires the use of the more accurate spatially varying [Formula: see text] source signature. We find that models will only be sensitive to changes in emissions distribution if spatial information can be exploited through the spatially resolved source signatures. In addition, we also find that on a regional scale, at sites measuring excursions of [Formula: see text] from background levels, substantial differences are simulated in atmospheric [Formula: see text] if using spatially varying or uniform source signatures. This article is part of a discussion meeting issue 'Rising methane: is warming feeding warming? (part 1)'.

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.

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 (1 σ ) 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.

Source characteristics of methane emissions in Africa are not well understood, despite methane’s role as the second largest anthropogenic contributor to climate change. Here, we present monthly methane emission estimates from Algeria, Egypt, Libya, Morocco, and Tunisia between 2010 and 2017, a region dominated by anthropogenic emissions. Emissions are estimated using observations from the GOSAT satellite and a Markov chain Monte Carlo inverse algorithm. Our top-down North African methane emissions are generally in line with inventory estimates and national reporting to the United Nations Framework Convention on Climate Change (UNFCCC). An exception is that summertime emissions from the Nile Delta region are considerably higher than those predicted by inventory estimates, possibly due to agricultural practices and the influence of the Nile.

Atmospheric methane (CH4) concentrations have shown a puzzling resumption in growth since 2007 following a period of stabilization from 2000 to 2006. Multiple hypotheses have been proposed to explain the temporal variations in CH4 growth, and attribute the rise of atmospheric CH4 either to increases in emissions from fossil fuel activities, agriculture and natural wetlands, or to a decrease in the atmospheric chemical sink. Here, we use a comprehensive ensemble of CH4 source estimates and isotopic δ13C-CH4 source signature data to show that the resumption of CH4 growth is most likely due to increased anthropogenic emissions. Our emission scenarios that have the fewest biases with respect to isotopic composition suggest that the agriculture, landfill and waste sectors were responsible for 53 ± 13% of the renewed growth over the period 2007–2017 compared to 2000–2006; industrial fossil fuel sources explained an additional 34 ± 24%, and wetland sources contributed the least at 13 ± 9%. The hypothesis that a large increase in emissions from natural wetlands drove the decrease in atmospheric δ13C-CH4 values cannot be reconciled with current process-based wetland CH4 models. This finding suggests the need for increased wetland measurements to better understand the contemporary and future role of wetlands in the rise of atmospheric methane and climate feedback. Our findings highlight the predominant role of anthropogenic activities in driving the growth of atmospheric CH4 concentrations.

Methane is an important greenhouse gas with a range of anthropogenic sources, including livestock farming and fossil fuel production. It is important that methane emissions can be correctly attributed to their source, to aid climate change policy and emissions mitigation efforts. For source attribution, many ‘top-down’ models of atmospheric methane use spatial maps of sources from emissions inventory data coupled with an atmospheric transport model. However, this can cause difficulties if sources are co-located or if there is uncertainty in the sources’ spatial distributions.To help with this issue and reduce overall uncertainty in estimates of methane emissions, recent methods have used observations of a secondary trace gas and its correlation with methane to infer methane emissions from a target sector. Most previous work has assumed a fixed emissions ratio between the two gases, which often does not reflect the true range of possible emission ratios. In this work, measurements of atmospheric ethane and its emissions ratio relative to methane are used to infer emissions of methane from fossil fuel sources. Instead of assuming a fixed emission ratio, our method allows for uncertainty in the emission ratio to be statistically propagated through the inverse model and incorporated into the sectoral estimates of methane emissions. We further demonstrate the inaccuracies that can result in an assessment of fossil fuel methane emissions if this uncertainty is not considered.We present this novel method for modelling sectoral methane emissions with examples from a synthetic data experiment and give results from a case study of UK methane emissions. Methane and ethane observations from a tall tower network across the UK were used with this model to produce monthly estimates of UK fossil fuel methane emissions with improved uncertainty characterisation.

We present the first spatially varying map of the δD-CH4 signature of wetland methane emissions and model its impact on atmospheric δD-CH4. The δD-CH4 signature map is derived by relating the δD-H2O of precipitation to the measured δD-CH4 of methane wetland emissions at a variety of wetland types and locations. Since the δD-H2O of precipitation is highly latitude-dependent, including this spatial variation has the potential to have a large impact on the distribution of δD-CH4 observed in the atmosphere. This latitude-dependence means that wetland emissions at different latitudes can have very different impacts on atmospheric δD-CH4, which could provide a useful way to constrain the location of wetland methane emissions in future inverse modelling studies. Here, we assess the implications for model studies on the differences that arise by treating δD-CH4 wetland source signatures as globally uniform rather than accounting for the large spatial variation. We also assess the potential for δD-CH4 to provide an independent constraint on wetland emissions over the more abundant and widely measured δ13C-CH4.

The potent greenhouse gas sulfuryl fluoride (SO2F2) is increasingly used as a fumigant, replacing methyl bromide, whose structural and soil fumigation uses have been phased out under the Montreal Protocol. We use measurements on archived air samples and in situ observations from the Advanced Global Atmospheric Gases Experiment (AGAGE) and a box model of the global atmosphere to show a global increase of SO2F2 mole fraction from 0.3 ± 0.02 to 2.5 ± 0.08 ppt along with a global increase in emissions from 0.5 ± 0.4 Gg yr−1 to 2.9 ± 0.4 Gg yr−1 from 1978 to 2019. Based on a hybrid model incorporating bottom-up industry data and a top-down downscaling approach, we estimate the spatial distribution and trend in SO2F2 regional emissions between 2000 and 2019 and propose that the global emissions increase is driven by the growing use of SO2F2 in structural fumigation in North America and in postharvest treatment of grains and other agricultural products worldwide.

China’s anthropogenic methane emissions are the largest of any country in the world. A recent study using atmospheric observations suggested that recent policies aimed at reducing emissions of methane due to coal production in China after 2010 had been largely ineffective. Here, based on a longer observational record and an updated modelling approach, we find a statistically significant positive linear trend (0.36 ± 0.04 ( ± 1 σ ) Tg CH4 yr−2) in China’s methane emissions for 2010–2017. This trend was slowing down at a statistically significant rate of -0.1 ± 0.04 Tg CH4 yr−3. We find that this decrease in growth rate can in part be attributed to a decline in China’s coal production. However, coal mine methane emissions have not declined as rapidly as production, implying that there may be substantial fugitive emissions from abandoned coal mines that have previously been overlooked. We also find that emissions over rice-growing and aquaculture-farming regions show a positive trend (0.13 ± 0.05 Tg CH4 yr−2 for 2010–2017) despite reports of shrinking rice paddy areas, implying potentially significant emissions from new aquaculture activities, which are thought to be primarily located on converted rice paddies.

Unregulated chlorocarbons, here defined as dichloromethane (CH2Cl2), perchloroethene (C2Cl4), chloroform (CHCl3), and methyl chloride (CH3Cl), are gases not regulated by the Montreal Protocol. While CH3Cl is the largest contributor of atmospheric chlorine, recent studies have shown that growth in emissions of the less abundant chlorocarbons could pose a significant threat to the recovery of the ozone layer. Despite this, there remain many regions for which no atmospheric monitoring exists, leaving gaps in our understanding of global emissions. Here, we report on a new time series of chlorocarbon measurements from Cape Point, South Africa for 2017, which represent the first published high-frequency measurements of these gases from Africa. For CH2Cl2 and C2Cl4, the majority of mole fraction enhancements were observed from the north, consistent with anthropogenically modified air from Cape Town, while for CHCl3 and CH3Cl, we found evidence for both oceanic and terrestrial sources. Using an inverse method, we estimated emissions for south-western South Africa (SWSA). For each chlorocarbon, SWSA accounted for less than 1% of global emissions. For CH2Cl2 and C2Cl4, we extrapolated using population statistics and found South African emissions of 8.9 (7.4-10.4) Gg yr-1 and 0.80 (0.64-1.04) Gg yr-1, respectively.

Eastern Boundary Upwelling Systems (EBUSs) are coastal hotspots of the potent greenhouse gas nitrous oxide (N2O). However, estimates of their emissions suffer from large uncertainties due to their significant spatial and temporal heterogeneity. Here, we derive the first multiyear, monthly resolution N2O emissions from three of the four major EBUSs using high-frequency coastal atmospheric measurements and an inverse method. We find average combined N2O emissions from the northern California, Benguela, and southern Canary upwelling systems to be 57.7 (51.4-63.9) Gg-N yr(-1). We also find an offshore region near the Benguela EBUS that exhibits large pulses of emissions with emissions that reach 677 Gg-N yr(-1) in 1 month. Our findings highlight that atmospheric measurements coupled with inverse modeling can capture the large variability in EBUS emissions by quantifying emissions over large spatial distances and over long time periods compared to previous methods using traditional oceanographic measurements. Plain Language Summary Eastern Boundary Upwelling Systems (EBUSs) are important emissions hotspots of marine nitrous oxide to the atmosphere, where it acts as a greenhouse gas and ozone depleting substance. Emissions from the EBUSs are highly episodic, and most previous estimates are snapshots derived from ship-based measurements. The variability in emissions combined with the sparsity of measurements makes EBUS emission estimates highly uncertain. Here, we use multiyear, near-continuous atmospheric measurements from coastal stations and an inverse modeling framework to derive emissions from three of the four major EBUSs. Our results quantify the significant spatial and temporal variability in emissions, which is not well-represented in global studies of marine nitrous oxide emissions.

Brazil's CH4 emissions over the period 2010–2018 were derived for the three main sectors of activity: anthropogenic, wetland and biomass burning. Our inverse modelling estimates were derived from GOSAT (Greenhouse gases Observing SATellite) satellite measurements of XCH4 combined with surface data from Ragged Point, Barbados, and the high-resolution regional atmospheric transport model NAME (Numerical Atmospheric-dispersion Modelling Environment). We find that Brazil's mean emissions over 2010–2018 are 33.6±3.6Tgyr-1, which are comprised of 19.0±2.6Tgyr-1 from anthropogenic (primarily related to agriculture and waste), 13.0±1.9Tgyr-1 from wetlands and 1.7±0.3Tgyr-1 from biomass burning sources. In addition, between the 2011–2013 and 2014–2018 periods, Brazil's mean emissions rose by 6.9±5.3Tgyr-1 and this increase may have contributed to the accelerated global methane growth rate observed during the latter period. We find that wetland emissions from the western Amazon increased during the start of the 2015–2016 El Niño by 3.7±2.7Tgyr-1 and this is likely driven by increased surface temperatures. We also find that our estimates of anthropogenic emissions are consistent with those reported by Brazil to the United Framework Convention on Climate Change. We show that satellite data are beneficial for constraining national-scale CH4 emissions, and, through a series of sensitivity studies and validation experiments using data not assimilated in the inversion, we demonstrate that (a) calibrated ground-based data are important to include alongside satellite data in a regional inversion and that (b) inversions must account for any offsets between the two data streams and their representations by models.

Chloroform contributes to the depletion of the stratospheric ozone layer. However, due to its short lifetime and predominantly natural sources, it is not included in the Montreal Protocol that regulates the production and uses of ozone-depleting substances. Atmospheric chloroform mole fractions were relatively stable or slowly decreased during 1990–2010. Here we show that global chloroform mole fractions increased after 2010, based on in situ chloroform measurements at seven stations around the world. We estimate that the global chloroform emissions grew at the rate of 3.5% yr−1 between 2010 and 2015 based on atmospheric model simulations. We used two regional inverse modelling approaches, combined with observations from East Asia, to show that emissions from eastern China grew by 49 (41–59) Gg between 2010 and 2015, a change that could explain the entire increase in global emissions. We suggest that if chloroform emissions continuously grow at the current rate, the recovery of the stratospheric ozone layer above Antarctica could be delayed by several years. Atmospheric levels of chloroform increased after 2010, as a result of emissions in eastern China, according to analyses of measurements and inverse modelling.

We present the first spatially‐resolved wetland δ13C(CH4) source signature map based on data characterizing wetland ecosystems and demonstrate good agreement with wetland signatures derived from atmospheric observations. The source signature map resolves a latitudinal difference of ~10‰ between northern high‐latitude (mean ‐67.8‰) and tropical (mean ‐56.7‰) wetlands, and shows significant regional variations on top of the latitudinal gradient. We assess the errors in inverse modeling studies aiming to separate CH4 sources and sinks by comparing atmospheric δ13C(CH4) derived using our spatially‐resolved map against the common assumption of globally uniform wetland δ13C(CH4) signature. We find a larger interhemispheric gradient, a larger high‐latitude seasonal cycle and smaller trend over the period 2000‐2012. The implication is that erroneous CH4 fluxes would be derived to compensate for the biases imposed by not utilizing spatially‐resolved signatures for the largest source of CH4 emissions. These biases are significant when compared to the size of observed signals.Plain Language SummaryConcentrations of methane are increasing in the atmosphere. In order to understand the reasons behind such variations, carbon isotopes are used to help identify changes in emission sources and sinks. We present a new global map of the carbon isotope signature associated with wetland methane emissions, the largest global source of methane to the atmosphere. We show how this newly synthesized information can lead to more accurate understanding of the causes of variations in the amount and rate of increase of methane in the atmosphere.

We present the first spatially resolved distribution of theδD-CH4signature of wetland methane emissions and assess its impact on atmosphericδD-CH4. TheδD-CH4signature map is derived by relatingδD-H2Oof precipitation to measuredδD-CH4of methane wetland emissions at a variety of wetland types and locations. This results in strong latitudinal variation in the wetlandδD-CH4source signature. WhenδD-CH4is simulated in a global atmospheric model, little difference is found in global mean, inter-hemispheric difference and seasonal cycle if the spatially varyingδD-CH4source signature distribution is used instead of a globally uniform value. This is because atmosphericδD-CH4is largely controlled by OH fractionation. However, we show that despite these small differences, using atmospheric records ofδD-CH4to infer changes in the wetland emissions distribution requires the use of the more accurate spatially varyingδD-CH4source signature. We find that models will only be sensitive to changes in emissions distribution if spatial information can be exploited through the spatially resolved source signatures. In addition, we also find that on a regional scale, at sites measuring excursions ofδD-CH4from background levels, substantial differences are simulated in atmosphericδD-CH4if using spatially varying or uniform source signatures.This article is part of a discussion meeting issue ‘Rising methane: is warming feeding warming? (part 1)’.

The 2015 Paris Agreement of the United Nations Framework Convention on Climate Change aims to keep global average temperature increases well below 2 °C of preindustrial levels in the Year 2100. Vital to its success is achieving a decrease in the abundance of atmospheric methane (CH4), the second most important anthropogenic greenhouse gas. If this reduction is to be achieved, individual nations must make and meet reduction goals in their nationally determined contributions, with regular and independently verifiable global stock taking. Targets for the Paris Agreement have been set, and now the capability must follow to determine whether CH4 reductions are actually occurring. At present, however, there are significant limitations in the ability of scientists to quantify CH4 emissions accurately at global and national scales and to diagnose what mechanisms have altered trends in atmospheric mole fractions in the past decades. For example, in 2007, mole fractions suddenly started rising globally after a decade of almost no growth. More than a decade later, scientists are still debating the mechanisms behind this increase. This study reviews the main approaches and limitations in our current capability to diagnose the drivers of changes in atmospheric CH4 and, crucially, proposes ways to improve this capability in the coming decade. Recommendations include the following: (i) improvements to process‐based models of the main sectors of CH4 emissions—proposed developments call for the expansion of tropical wetland flux measurements, bridging remote sensing products for improved measurement of wetland area and dynamics, expanding measurements of fossil fuel emissions at the facility and regional levels, expanding country‐ specific data on the composition of waste sent to landfill and the types of wastewater treatment systems implemented, characterizing and representing temporal profiles of crop growing seasons, implementing parameters related to ruminant emissions such as animal feed, and improving the detection of small fires associated with agriculture and deforestation; (ii) improvements to measurements of CH4 mole fraction and its isotopic variations—developments include greater vertical profiling at background sites, expanding networks of dense urban measurements with a greater focus on relatively poor countries, improving the precision of isotopic ratio measurements of 13CH4, CH3D, 14CH4, and clumped isotopes, creating isotopic reference materials for international‐scale development, and expanding spatial and temporal characterization of isotopic source signatures; and (iii) improvements to inverse modeling systems to derive emissions from atmospheric measurements—advances are proposed in the areas of hydroxyl radical quantification, in systematic uncertainty quantification through validation of chemical transport models, in the use of source tracers for estimating sector‐level emissions, and in the development of time and spaceresolved national inventories. These and other recommendations are proposed for the major areas of CH4 science with the aim of improving capability in the coming decade to quantify atmospheric CH4 budgets on the scales necessary for the success of climate policies. Plain Language Summary Methane is the second largest contributor to climate warming from human activities since preindustrial times. Reducing human‐made emissions by half is a major component of the 2015 Paris Agreement target to keep global temperature increases well below 2 °C. In parallel to the methane emission reductions pledged by individual nations, new capabilities are needed to determine independently whether these reductions are actually occurring and whether methane concentrations in the atmosphere are changing for reasons that are clearly understood. At present significant challenges limit the ability of scientists to identify the mechanisms causing changes in atmospheric methane. This study reviews current and emerging tools in methane science and proposes major advances needed in the coming decade to achieve this crucial capability. We recommend further developing the models that simulate the processes behind methane emissions, improving atmospheric measurements of methane and its major carbon and hydrogen isotopes, and advancing abilities to infer the rates of methane being emitted and removed from the atmosphere from these measurements. The improvements described here will play a major role in assessing emissions commitments as more cities, states, and countries report methane emission inventories and commit to specific emission reduction targets.

Atmospheric inversions have been used for the past two decades to derive large scale constraints on the sources and sinks of CO2 into the atmosphere. The development of high density in-situ surface observation networks, such as ICOS in Europe, enables in theory inversions at a resolution close to the country scale in Europe. This has led to the development of many regional inversion systems capable of assimilating these high-resolution data, in Europe and elsewhere. The EUROCOM project (EUROpean atmospheric transport inversion COMparison) is a collaboration between seven European research institutes, which aims at producing a collective assessment of the net carbon flux between the terrestrial ecosystems and the atmosphere in Europe for the period 2006–2015. It aims in particular at investigating the capacity of the inversions to deliver consistent flux estimates from the country scale up to the continental scale. The project participants were provided with a common database of in-situ observed CO2 concentrations (including the observation sites that are now part of the ICOS network), and were tasked with providing their best estimate of the net terrestrial carbon flux for that period, and for a large domain covering the entire European Union. The inversion systems differ by the transport model, the inversion approach and the choice of observation and prior constraints, enabling us to widely explore the space of uncertainties. This paper describes the intercomparison protocol and the participating systems, and it presents the first results from a reference set of inversions, at the continental scale and in four large regions. At the continental scale, the regional inversions support the assumption that European ecosystems are a relatively small sink (−0.21 ± 0.2 PgC/year). We find that the convergence of the regional inversions at this scale is not better than that obtained in state-of-the-art global inversions. However, more robust results are obtained for sub-regions within Europe, and in these areas with dense observational coverage, the objective of delivering robust country scale flux estimates appears achievable in the near future.

One hydrochlorofluorocarbon and two hydrofluorocarbons (HCFC-22, HFC-125, and HFC-152a) were measured in air samples at the Cape Point observatory (CPT), South Africa, during 2017. These data represent the first such atmospheric measurements of these compounds from southwestern South Africa (SWSA). Baseline atmospheric growth rates were estimated to be 8.36, 4.10, and 0.71 ppt year-1 for HCFC-22, HFC-125, and HFC-152a, respectively. The CPT measurements were combined with an inverse model to investigate emissions from SWSA. For all three halocarbons, Cape Town was found to be the dominant source within SWSA. These estimates were extrapolated, based on population statistics, to estimate emissions for the whole of South Africa. We estimate South Africa's 2017 emissions to be 3.0 (1.6-4.4), 0.8 (0.5-1.2), and 1.1 (0.6-1.6) Gg year-1 for HCFC-22, HFC-125, and HFC-152a, respectively. For all three halocarbons, South Africa's contribution to global emissions is small (

We present a method to infer spatially and spatiotemporally 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 spatiotemporal 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 spatiotemporal uncertainties that have traditionally been neglected in atmospheric inverse modelling.

The recovery of the stratospheric ozone layer relies on the continued decline in the atmospheric concentrations of ozone-depleting gases such as chlorofluorocarbons1. The atmospheric concentration of trichlorofluoromethane (CFC-11), the second-most abundant chlorofluorocarbon, has declined substantially since the mid-1990s2. A recently reported slowdown in the decline of the atmospheric concentration of CFC-11 after 2012, however, suggests that global emissions have increased3,4. A concurrent increase in CFC-11 emissions from eastern Asia contributes to the global emission increase, but the location and magnitude of this regional source are unknown3. Here, using high-frequency atmospheric observations from Gosan, South Korea, and Hateruma, Japan, together with global monitoring data and atmospheric chemical transport model simulations, we investigate regional CFC-11 emissions from eastern Asia. We show that emissions from eastern mainland China are 7.0 ± 3.0 (±1 standard deviation) gigagrams per year higher in 2014–2017 than in 2008–2012, and that the increase in emissions arises primarily around the northeastern provinces of Shandong and Hebei. This increase accounts for a substantial fraction (at least 40 to 60 per cent) of the global rise in CFC-11 emissions. We find no evidence for a significant increase in CFC-11 emissions from any other eastern Asian countries or other regions of the world where there are available data for the detection of regional emissions. The attribution of any remaining fraction of the global CFC-11 emission rise to other regions is limited by the sparsity of long-term measurements of sufficient frequency near potentially emissive regions. Several considerations suggest that the increase in CFC-11 emissions from eastern mainland China is likely to be the result of new production and use, which is inconsistent with the Montreal Protocol agreement to phase out global chlorofluorocarbon production by 2010. Emissions from eastern China account for approximately 40 to 60 per cent of the global rise in emissions of trichlorofluoromethane (CFC-11), which may be a result of new production and use.

While the Montreal Protocol has been successful in reducing emissions of many long-lived ozone-depleting substances, growth in the global emission rates of unregulated very short-lived substances (VSLS) poses a potential threat to the recovery of the ozone layer. The sources of these VSLS are not well-constrained, with major source regions poorly monitored by existing measurement networks. Given India's rapidly growing economy, its emissions of both regulated chlorocarbons and unregulated VSLS chlorocarbons are suspected to have global significance. Furthermore, VSLS from the Asian monsoon regions have a greater impact on ozone-depletion than those emitted elsewhere due to the ability of monsoon systems to rapidly transport pollutants to the lower stratosphere. Previous atmospheric measurements of chlorocarbons from the Indian sub-continent are scarce. Here we present a new set of observations, derived from flask samples collected during a 2-month aircraft campaign in India and use these measurements to infer India's chlorocarbon emissions. We show that emissions of carbon tetrachloride from northern and central India (2.3 (1.5–3.4) Gg yr−1), are likely due to inadvertent production and release during the manufacture of chloromethanes (specifically dichloromethane and chloroform) and account for approximately 7 % of the global total. Emissions of methyl chloroform from the same region were estimated to be 0.07 (0.04–0.10) Gg yr−1 which account for less than 5 % of remaining global emissions. We used a population scaling to estimate India's emissions of the very short-lived chlorocarbons dichloromethane, perchloroethene and chloroform, which were estimated to be 69.2 (55.8–82.9) Gg yr−1, 2.9 (2.5–3.3) Gg yr−1 and 25.7 (21.6–29.9) Gg yr−1 respectively. In the case of dichloromethane, our estimate is consistent with a 3-fold increase in emissions since the last estimate derived from atmospheric data in 2008.

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 existing measurement networks. Of the greenhouse/ozone-depleting gases, India's emissions of synthetic halocarbons (here defined as chlorofluorocarbons (CFCs), hydrochlorofluorocarbons (HCFCs) and hydrofluorocarbons (HFCs)) are not well-known. Previous measurements from the region have been obtained at observatories many hundreds of miles 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 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 the first atmospheric-measurement derived emissions of the ozone-depleting CFCs and HCFCs, and potent greenhouse gas HFCs from India. Air samples were collected at low-altitude during a 2-month aircraft campaign between June and July 2016. Emissions were derived from measurements of these samples using an inverse modelling framework and evaluated to assess India's progress in phasing out ozone-depleting substances (ODS) under the Montreal Protocol. Our CFC estimates show that India contributed 52 (26–83) Tg CO2eq yr−1, which were 7 (4–12) % of global emissions in 2016. HCFC-22 emissions at 7.8 (6.0–9.9) Gg yr−1 were of similar magnitude to emissions of HFC-134a (8.2 (6.1–10.7) Gg yr−1), suggesting that India used a range of HCFC and HFC refrigerants in 2016. We estimated 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 that HFC-32 emissions were primarily due to fugitive emissions during manufacturing processes. 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.

Methane is a strong contributor to global climate change, yet our current understanding and quantification of its sources and their variability is incomplete. There is a growing need for comparisons between emission estimates produced using bottom-up inventory approaches and top-down inversion techniques based on atmospheric measurements, especially at higher spatial resolutions. To meet this need, this study presents using an inversion approach based on the Inversion Technique for Emissions Modelling (InTEM) framework and measurements from four sites in East Anglia, United Kingdom. Atmospheric methane concentrations were recorded at 1–2 minute time-steps at each location within the region of interest. These observations, coupled with the UK Met Office's Lagrangian particle dispersion model, NAME (Numerical Atmospheric dispersion Modelling Environment), were used within InTEM2014 to produce methane emission estimates for a 1-year period (June 2013–May 2014) in this eastern region of the UK (~ 100 × 150 km) at high spatial resolution (up to 4 × 4 km). InTEM2014 was able to produce realistic emissions estimates for East Anglia, and highlighted potential areas of difference from the UK National Atmospheric Emissions Inventory (NAEI). As this study was part of the UK Greenhouse gAs Uk and Global Emissions (GAUGE) project, observations were included within a national inversion using all eleven measurement sites across the UK to directly compare emission estimates for the East Anglia Region. Results show similar methane estimates for the East Anglia region. Methane emissions from Norfolk and Suffolk show good agreement with the estimates in NAEI, with differences of ~ 5 %. Larger differences are found for Cambridgeshire where our estimate is 22.5 % lower than that of NAEI. The addition of the EA sites within the national inversion system enabled finer spatial resolution and a decrease in the associated uncertainty for that area. Further development of our approach to include a more robust analysis of the methane concentration in the air entering this region and the uncertainty associated with the resulting emissions would strengthen this inverse method. Nonetheless, our results show there is value in high spatial resolution measurement networks and the resulting inversion emission estimates.

Carbon tetrachloride (CCl4) is an ozone-depleting substance, accounting for about 10% of the chlorine in the troposphere. Under the terms of the Montreal Protocol, its production for dispersive uses was banned from 2010. In this work we show that, despite the controls on production being introduced, CCl4 emissions from the eastern part of China did not decline between 2009 and 2016. This finding is in contrast to a recent bottom-up estimate, which predicted a significant decrease in emissions after the introduction of production controls. We find eastern Asian emissions of CCl4 to be 16 (9–24) Gg/year on average between 2009 and 2016, with the primary source regions being in eastern China. The spatial distribution of emissions that we derive suggests that the source distribution of CCl4 in China changed during the 8-year study period, indicating a new source or sources of emissions from China’s Shandong province after 2012., Plain Language Summary Carbon tetrachloride is one of several man-made gases that contribute to the depletion of the ozone layer high in the atmosphere. Because of this, restrictions were introduced on the use of this ozone-depleting substance, with the expectation that production should by now be close to 0. However, the slower than expected rate of decline of carbon tetrachloride in the atmosphere shows this is not the case, and a large portion of global emissions are unaccounted for. In this study we use atmospheric measurements of carbon tetrachloride from a site in East Asia to identify the magnitude and location of emissions from this region between 2009 and 2016. We find that there are significant ongoing emissions from eastern China and that these account for a large part of the missing emissions from global estimates. The presence of continued sources of this important ozone-depleting substance indicates that more could be done to speed up the recovery of the ozone layer.

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 primary productivity. Two different models, CARDAMOM and 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 (CARDAMOM prior) and −64 ± 85 Tg CO2 yr−1 (JULES prior), where -ve 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 are consistently higher than the prior estimates, which show much more pronounced uptake in the summer months.

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-CO[subscript 2]) gases assessed by the Intergovernmental Panel on Climate Change (CO[subscript 2] 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 – NF[subscript 3], sulfuryl fluoride – SO[subscript 2]F[subscript 2], and sulfur hexafluoride – SF[subscript 6]) 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-CO[subscript 2] biogenic–anthropogenic gases important to climate change and/or ozone depletion (methane – CH[subscript 4], nitrous oxide – N[subscript 2]O, carbon monoxide – CO, molecular hydrogen – H[subscript 2], methyl chloride – CH[subscript 3]Cl, and methyl bromide – CH[subscript 3]Br); (3) to identify new long-lived greenhouse and ozone-depleting gases (e.g., SO[subscript 2]F[subscript 2], NF[subscript 3], heavy PFCs (C[subscript 4]F[subscript 10], C[subscript 5]F[subscript 12], C[subscript 6]F[subscript 14], C[subscript 7]F[subscript 16], and C[subscript 8]F[subscript 18]) and hydrofluoroolefins (HFOs; e.g., CH[subscript 2] = CFCF[subscript 3]) 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 (CH[subscript 3]CCl[subscript 3]), 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)., United States. National Aeronautics and Space Administration (NAG5-12669), United States. National Aeronautics and Space Administration (NNX07AE89G), United States. National Aeronautics and Space Administration (NNX11AF17G), United States. National Aeronautics and Space Administration (NNX16AC98G)

Methane emissions at the national scale in France in 2012 are inferred by assimilating continuous atmospheric mixing ratio measurements from nine stations of the European network ICOS located in France and surrounding countries. To assess the robustness of the fluxes deduced by our inversion system based on an objectified quantification of uncertainties, two complementary inversion set-ups are computed and analysed: i) a regional run correcting for the spatial distribution of fluxes in France, and ii) a sectorial run correcting fluxes for activity sectors at the national scale. In addition, our results for the two set-ups are compared with fluxes produced in the framework of the inversion inter-comparison exercise of the InGOS project. The seasonal variability of fluxes is consistent between different set-ups, with maximum emissions in summer, likely due to agricultural activity. However, very high monthly posterior uncertainties (up to ≈ 65 % to 74 % in the sectorial run in May and June) makes it difficult to attribute maximum emissions to a specific sector. At the yearly national scale, the two inversions range to 3835–4050 Gg CH4 and 3570–4190 Gg CH4 for the regional and sectorial run, respectively, consistently with the InGOS products. These estimates are 25 to 55 % higher than the total national emissions from bottom-up approaches (biogeochemical models from natural emissions, plus inventories for anthropogenic ones), consistently pointing at missing or under-estimated sources in the inventories and/or in natural sources. More specifically, in the sectorial set-up, agricultural emissions are inferred as 66 % larger than estimates reported to UNFCCC. Uncertainties on the total annual national budget are 108 Gg CH4 and 312 Gg CH4, i.e, 3 to 8 %, for the regional and sectorial run respectively, smaller than uncertainties in available bottom-up products, proving the added value of top-down atmospheric inversions. Therefore, even though the surface network used in 2012 does not allow to fully constrain all regions in France accurately, a regional inversion set-ups makes it possible to provide estimates of French methane fluxes with an uncertainty on the total budget less than 10 % at the yearly scale. Additional sites deployed since 2012 would help to constrain French emissions at finer spatial and temporal scales and attributing missing emissions to specific sectors.

Changes in tropical wetland, ruminant or rice emissions are thought to have played a role in recent variations in atmospheric methane (CH4) concentrations. India has the world’s largest ruminant population and produces ~ 20% of the world’s rice. Therefore, changes in these sources could have significant implications for global warming. Here, we infer India’s CH4 emissions for the period 2010–2015 using a combination of satellite, surface and aircraft data. We apply a high-resolution atmospheric transport model to simulate data from these platforms to infer fluxes at sub-national scales and to quantify changes in rice emissions. We find that average emissions over this period are 22.0 (19.6–24.3) Tg yr−1, which is consistent with the emissions reported by India to the United Framework Convention on Climate Change. Annual emissions have not changed significantly (0.2 ± 0.7 Tg yr−1) between 2010 and 2015, suggesting that major CH4 sources did not change appreciably. These findings are in contrast to another major economy, China, which has shown significant growth in recent years due to increasing fossil fuel emissions. However, the trend in a global emission inventory has been overestimated for China due to incorrect rate of fossil fuel growth. Here, we find growth has been overestimated in India but likely due to ruminant and waste sectors., India’s methane emissions have been quantified using atmospheric measurements to provide an independent comparison with reported emissions. Here Ganesan et al. find that derived methane emissions are consistent with India’s reports and no significant trend has been observed between 2010–2015.

United States. National Aeronautics and Space Administration (Upper Atmospheric Research Program Grant NNX11AF17G)

High-frequency atmospheric measurements of methane (CH[subscript 4]), nitrous oxide (N[subscript 2]O) and sulfur hexafluoride (SF[subscript 6]) from Darjeeling, India are presented from December 2011 (CH[subscript 4])/March 2012 (N[subscript 2]O and SF[subscript 6]) 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 CH[subscript 4], N[subscript 2]O and SF[subscript 6], respectively. The observations show large variability and frequent pollution events in CH[subscript 4] and N[subscript 2]O mole fractions, suggesting significant sources in the regions sampled by Darjeeling throughout the year. By contrast, SF[subscript 6] 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 CH[subscript 4] and N[subscript 2]O 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 (, Massachusetts Institute of Technology. Center for Global Change Science (Director's Fund), Massachusetts Institute of Technology. Joint Program on the Science & Policy of Global Change, Martin Family Society of Fellows for Sustainability, MIT Energy Initiative, MIT International Science and Technology Initiative, United States. National Aeronautics and Space Administration (Grant NNX11AF17G), United States. National Oceanic and Atmospheric Administration (Contract RA133R09CN0062)

Atmospheric trace-gas inversion is the procedure by which the sources and sinks of a trace gas are identified from observations of its mole fraction at isolated locations in space and time. This is inherently a spatio-temporal bivariate inversion problem, since the mole-fraction field evolves in space and time and the flux is also spatio-temporally distributed. Further, the bivariate model is likely to be non-Gaussian since the flux field is rarely Gaussian. Here, we use conditioning to construct a non-Gaussian bivariate model, and we describe some of its properties through auto- and cross-cumulant functions. A bivariate non-Gaussian, specifically trans-Gaussian, model is then achieved through the use of Box--Cox transformations, and we facilitate Bayesian inference by approximating the likelihood in a hierarchical framework. Trace-gas inversion, especially at high spatial resolution, is frequently highly sensitive to prior specification. Therefore, unlike conventional approaches, we assimilate trace-gas inventory information with the observational data at the parameter layer, thus shifting prior sensitivity from the inventory itself to its spatial characteristics (e.g., its spatial length scale). We demonstrate the approach in controlled-experiment studies of methane inversion, using fluxes extracted from inventories of the UK and Ireland and of Northern Australia., 45 pages, 7 figures

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 size 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 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, it allows the uncertainty in our choice of aggregation to be carried through to the solution. 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 allows methane emissions over north-west Europe to be resolved.