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Sulfur hexafluoride (SF6) is the most potent greenhouse gas (GHG), and its atmospheric abundance, albeit small, has been increasing rapidly. Although SF6 is used to assess atmospheric transport modeling and its emissions influence the climate for millennia, SF6 emission magnitudes and distributions have substantial uncertainties. In this study, we used NOAA's ground-based and airborne measurements of SF6 to estimate SF6 emissions from the United States between 2007 and 2018. Our results suggest a substantial decline of US SF6 emissions, a trend also reported in the US Environmental Protection Agency's (EPA) national inventory submitted under the United Nations Framework Convention on Climate Change (UNFCCC), implying that US mitigation efforts have had some success. However, the magnitudes of annual emissions derived from atmospheric observations are 40 %–250 % higher than the EPA's national inventory and substantially lower than the Emissions Database for Global Atmospheric Research (EDGAR) inventory. The regional discrepancies between the atmosphere-based estimate and EPA's inventory suggest that emissions from electric power transmission and distribution (ETD) facilities and an SF6 production plant that did not or does not report to the EPA may be underestimated in the national inventory. Furthermore, the atmosphere-based estimates show higher emissions of SF6 in winter than in summer. These enhanced wintertime emissions may result from increased maintenance of ETD equipment in southern states and increased leakage through aging brittle seals in ETD in northern states during winter. The results of this study demonstrate the success of past US SF6 emission mitigations and suggest that substantial additional emission reductions might be achieved through efforts to minimize emissions during servicing or through improving sealing materials in ETD.

The likelihood for successful emission control and mitigation efforts of trace gases having adverse environmental effects can be enhanced by using a multi-faceted framework for quantifying and understanding emissions. While bottom-up activity-based inventories provide a quantification of various source sectors, appropriately designed atmosphere-based (top-down) approaches are able to independently evaluate the inventory and further refine temporal changes and spatial distributions. Differences between bottom-up and top-down estimates are oftentimes observed and represent prime opportunities for increasing understanding and refining estimates of emissions. Here we will present results derived from atmospheric observations made in the remote global atmosphere as well as from our North American measurement network. The remote global observations enabled the identification of an apparent violation of the Montreal Protocol. After our atmospheric measurements identified this unexpected issue, fairly quick resolution appears to have been achieved, in part due to the additional understanding of likely underlying causes provided by industry experts. Our North American measurement network also allows for trace-gas emission estimates on national and state scales. Results from these efforts will be discussed, with an emphasis on describing how the interaction between inventory-derived and atmosphere-based information has led to an improved understanding of emission magnitudes along with identifying areas needing additional study.

Methane is a major greenhouse gas (GHG) that has contributed to one third of the warming induced by all GHGs since the preindustrial era (IPCC, 2021). Reliable quantification of methane emissions is critical for tracking progress towards methane mitigation, especially for the countries that join the Global Methane Pledge and that have firm plans for reducing methane emissions over the next decades, such as the US. In this study, we quantified US methane emissions using inverse modeling of ground- and airborne- methane measurements made from the NOAA Greenhouse Gas Reference Network for 2007 – 2021. We conducted 12 inversion runs using two high-resolution transport models (HYSPLIT-NAMs and WRF-STILT), three background estimates, and two prior emission fields. Multiple estimates of wetland emissions were considered and subtracted from our inversion-derived total emission estimates. Our derived anthropogenic emissions show a consistent increasing trend after 2015 across our inversion ensemble members and a seasonal cycle in emission magnitude that repeats every year during our study period. Both the trend and seasonal variation seem to correlate with US natural gas consumption. A similar seasonal variability has been reported previously, but only on an urban scale; this is the first time it has been derived on a national scale. Furthermore, we also compared our estimates with US EPA’s national GHG inventory reporting and investigated the impact of the COVID-19 pandemic on emissions in 2020 relative to 2019 and 2021.

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.

EM27/SUN devices are portable solar-viewing Fourier transform spectrometers (FTSs) that are being widely used to constrain measurements of greenhouse gas emissions and validate satellite trace gas measurements. On a 6-week-long campaign in the summer of 2018, four EM27/SUN devices were taken to five Total Carbon Column Observing Network (TCCON) stations in North America, to measure side by side, to better understand their durability, the accuracy and precision of retrievals from their trace gas measurements, and to constrain site-to-site bias among TCCON sites. We developed new EM27/SUN data products using both previous and current versions of the retrieval algorithm (GGG2014 and GGG2020) and used coincident AirCore measurements to tie the gas retrievals to the World Meteorological Organization (WMO) trace gas standard scales. We also derived air-mass-dependent correction factors for the EM27/SUN devices. Pairs of column-averaged dry-air mole fractions (denoted with an X) measured by the EM27/SUN devices remained consistent compared to each other during the entire campaign, with a 10 min averaged precision of 0.3 ppm (parts per million) for XCO2, 1.7 ppb (parts per billion) for XCH4, and 2.5 ppb for XCO. The maximum biases between TCCON stations were reduced in GGG2020 relative to GGG2014 from 1.3 to 0.5 ppm for XCO2 and from 5.4 to 4.3 ppb for XCH4 but increased for XCO from 2.2 to 6.1 ppb. The increased XCO biases in GGG2020 are driven by measurements at sites influenced by urban emissions (Caltech and the Armstrong Flight Research Center) where the priors overestimate surface CO. In addition, in 2020, one EM27/SUN instrument was sent to the Canadian Arctic TCCON station at Eureka, and side-by-side measurements were performed in March–July. In contrast to the other TCCON stations that showed an improvement in the biases with the newer version of GGG, the biases between Eureka's TCCON measurements and those from the EM27/SUN degraded with GGG2020, but this degradation was found to be caused by a temperature dependence in the EM27/SUN oxygen retrievals that is not apparent in the GGG2014 retrievals.

The radiative balance of the upper atmosphere is dependent on the magnitude and distribution of greenhouse gases and aerosols in that region. Climate models predict that with increasing surface temperature, the primary mechanism for transporting tropospheric air into the stratosphere (known as the Brewer–Dobson circulation) will strengthen, leading to changes in the distribution of atmospheric water vapor, other greenhouse gases, and aerosols. Stratospheric relationships between greenhouse gases and other long-lived trace gases with various photochemical properties (such as N2O, SF6, and chlorofluorocarbons) provide a strong constraint for tracking changes in the stratospheric circulation. Therefore, a cost-effective approach is needed to monitor these trace gases in the stratosphere. In the past decade, the balloon-borne AirCore sampler developed at NOAA's Global Monitoring Laboratory has been routinely used to monitor the mole fractions of CO2, CH4, and CO from the ground to approximately 25 km above mean sea level. Our recent development work adapted a gas chromatograph coupled with an electron capture detector (GC-ECD) to measure a suite of trace gases (N2O, SF6, CFC-11, CFC-12, H-1211, and CFC-113) in the stratospheric portion of AirCores. This instrument, called the StratoCore-GC-ECD, allows us to retrieve vertical profiles of these molecules at high resolution (5–7 hPa per measurement). We launched four AirCore flights and analyzed the stratospheric air samples for these trace gases. The results showed consistent and expected tracer–tracer relationships and good agreement with recent aircraft campaign measurements. Our work demonstrates that the StratoCore-GC-ECD system provides a low-cost and robust approach to measuring key stratospheric trace gases in AirCore samples and for evaluating changes in the stratospheric circulation.

Approximately half of the carbon dioxide (CO 2) released annually by the combustion of fossil fuels stays in the atmosphere (Friedlingstein et al., 2022; Keeling et al., 1976; Schimel et al., 2001). The remaining CO 2 is taken up by the terrestrial biosphere and ocean in roughly equal proportions (Keeling & Manning, 2014; Khatiwala et al., 2009; Sabine et al., 2004). The efficiency of the ocean and land sinks varies with both climate and atmospheric CO 2 , representing an important feedback in the climate system (e.g., Ballantyne et al., 2012

This article provides an overview of the NASA Atmospheric Tomography (ATom) mission and a summary of selected scientific findings to date. ATom was an airborne measurements and modeling campaign aimed at characterizing the composition and chemistry of the troposphere over the most remote regions of the Pacific, Southern, Atlantic, and Arctic Oceans, and examining the impact of anthropogenic and natural emissions on a global scale. These remote regions dominate global chemical reactivity and are exceptionally important for global air quality and climate. ATom data provide the in situ measurements needed to understand the range of chemical species and their reactions, and to test satellite remote sensing observations and global models over large regions of the remote atmosphere. Lack of data in these regions, particularly over the oceans, has limited our understanding of how atmospheric composition is changing in response to shifting anthropogenic emissions and physical climate change. ATom was designed as a global-scale tomographic sampling mission with extensive geographic and seasonal coverage, tropospheric vertical profiling, and detailed speciation of reactive compounds and pollution tracers. ATom flew the NASA DC-8 research aircraft over four seasons to collect a comprehensive suite of measurements of gases, aerosols, and radical species from the remote troposphere and lower stratosphere on four global circuits from 2016 to 2018. Flights maintained near-continuous vertical profiling of 0.15–13-km altitudes on long meridional transects of the Pacific and Atlantic Ocean basins. Analysis and modeling of ATom data have led to the significant early findings highlighted here.

Sulfur hexafluoride (SF6) is the most potent greenhouse gas (GHG), and its atmospheric abundance, albeit small, has been increasing rapidly. Although SF6 is used to assess atmospheric transport modeling and its emissions influence the climate for millennia, SF6 emission magnitudes and distributions have substantial uncertainties. In this study, we used NOAA's ground-based and airborne measurements of SF6 to estimate SF6 emissions from the United States between 2007 and 2018. Our results suggest a substantial decline of US SF6 emissions, a trend also reported in the US Environmental Protection Agency's (EPA) national inventory submitted under the United Nations Framework Convention on Climate Change (UNFCCC), implying that US mitigation efforts have had some success. However, the magnitudes of annual emissions derived from atmospheric observations are 40 %–250 % higher than the EPA's national inventory and substantially lower than the Emissions Database for Global Atmospheric Research (EDGAR) inventory. The regional discrepancies between the atmosphere-based estimate and EPA's inventory suggest that emissions from electric power transmission and distribution (ETD) facilities and an SF6 production plant that did not or does not report to the EPA may be underestimated in the national inventory. Furthermore, the atmosphere-based estimates show higher emissions of SF6 in winter than in summer. These enhanced wintertime emissions may result from increased maintenance of ETD equipment in southern states and increased leakage through aging brittle seals in ETD in northern states during winter. The results of this study demonstrate the success of past US SF6 emission mitigations and suggest that substantial additional emission reductions might be achieved through efforts to minimize emissions during servicing or through improving sealing materials in ETD.

The Copernicus Atmosphere Monitoring Service (CAMS) has recently produced a greenhouse gas reanalysis (version egg4) that covers almost 2 decades from 2003 to 2020 and which will be extended in the future. This reanalysis dataset includes carbon dioxide (CO2) and methane (CH4). The reanalysis procedure combines model data with satellite data into a globally complete and consistent dataset using the European Centre for Medium-Range Weather Forecasts' Integrated Forecasting System (IFS). This dataset has been carefully evaluated against independent observations to ensure validity and to point out deficiencies to the user. The greenhouse gas reanalysis can be used to examine the impact of atmospheric greenhouse gas concentrations on climate change (such as global and regional climate radiative forcing), assess intercontinental transport, and serve as boundary conditions for regional simulations, among other applications and scientific uses. The caveats associated with changes in assimilated observations and fixed underlying emissions are highlighted, as is their impact on the estimation of trends and annual growth rates of these long-lived greenhouse gases.

The continued warming of the Arctic could release vast stores of carbon into the atmosphere from high-latitude ecosystems, especially from thawing permafrost. Increasing uptake of carbon dioxide (CO2) by vegetation during longer growing seasons may partially offset such release of carbon. However, evidence of significant net annual release of carbon from site-level observations and model simulations across tundra ecosystems has been inconclusive. To address this knowledge gap, we combined top-down observations of atmospheric CO2 concentration enhancements from aircraft and a tall tower, which integrate ecosystem exchange over large regions, with bottom-up observed CO2 fluxes from tundra environments and found that the Alaska North Slope is not a consistent net source nor net sink of CO2 to the atmosphere (ranging from −6 to +6 Tg C yr−1 for 2012–2017). Our analysis suggests that significant biogenic CO2 fluxes from unfrozen terrestrial soils, and likely inland waters, during the early cold season (September–December) are major factors in determining the net annual carbon balance of the North Slope, implying strong sensitivity to the rapidly warming freeze-up period. At the regional level, we find no evidence of the previously reported large late-cold-season (January–April) CO2 emissions to the atmosphere during the study period. Despite the importance of the cold-season CO2 emissions to the annual total, the interannual variability in the net CO2 flux is driven by the variability in growing season fluxes. During the growing season, the regional net CO2 flux is also highly sensitive to the distribution of tundra vegetation types throughout the North Slope. This study shows that quantification and characterization of year-round CO2 fluxes from the heterogeneous terrestrial and aquatic ecosystems in the Arctic using both site-level and atmospheric observations are important to accurately project the Earth system response to future warming.

Atmospheric methane (CH4) concentrations have been rising since 2007 due to an imbalance between CH4 sources and sinks. The CH4 budget is generally estimated through top-down approaches using chemistry transport models (CTMs) and CH4 observations as constraints. The atmospheric isotopic CH4 composition, δ13C(CH4), can also provide additional constraints and helps to discriminate between emission categories. Nevertheless, to be able to use the information contained in these observations, the models must correctly account for processes influencing δ13C(CH4). The oxidation by chlorine (Cl) likely contributes less than 5 % to the total oxidation of atmospheric CH4. However, the large kinetic isotope effect of the Cl sink produces a large fractionation of 13C, compared with 12C in atmospheric CH4, and thus may strongly influence δ13C(CH4). When integrating the Cl sink in their setup to constrain the CH4 budget, which is not yet standard, atmospheric inversions prescribe different Cl fields, therefore leading to discrepancies between flux estimates. To quantify the influence of the Cl concentrations on CH4, δ13C(CH4), and CH4 budget estimates, we perform sensitivity simulations using four different Cl fields. We also test removing the tropospheric and the entire Cl sink. We find that the Cl fields tested here are responsible for between 0.3 % and 8.5 % of the total chemical CH4 sink in the troposphere and between 1.0 % and 1.6 % in the stratosphere. Prescribing these different Cl amounts in atmospheric inversions can lead to differences of up to 53.8 Tg CH4 yr−1 in global CH4 emissions and of up to 4.7 ‰ in the globally averaged isotopic signature of the CH4 source δ13C(CH4)source), although these differences are much smaller if only recent Cl fields are used. More specifically, each increase by 1000 molec.cm-3 in the mean tropospheric Cl concentration would result in an adjustment by +11.7 Tg CH4 yr−1, for global CH4 emissions, and −1.0 ‰, for the globally averaged δ13C(CH4)source. Our study also shows that the CH4 seasonal cycle amplitude is modified by less than 1 %–2 %, but the δ13C(CH4) seasonal cycle amplitude can be significantly modified by up to 10 %–20 %, depending on the latitude. In an atmospheric inversion performed with isotopic constraints, this influence can result in significant differences in the posterior source mixture. For example, the contribution from wetland emissions to the total emissions can be modified by about 0.8 % to adjust the globally averaged δ13C(CH4)source, corresponding to a 15 Tg CH4 yr−1 change. This adjustment is small compared to the current wetland source uncertainty, albeit far from negligible. Finally, tested Cl concentrations have a large influence on the simulated δ13C(CH4) vertical profiles above 30 km and a very small impact on the simulated CH4 vertical profiles. Overall, our model captures the observed CH4 and δ13C(CH4) vertical profiles well, especially in the troposphere, and it is difficult to prefer one Cl field over another based uniquely on the available observations of the vertical profiles.

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesise data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on land-use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly, and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) is estimated with global ocean biogeochemistry models and observation-based data-products. The terrestrial CO2 sink (SLAND) is estimated with dynamic global vegetation models. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the year 2021, EFOS increased by 5.1 % relative to 2020, with fossil emissions at 10.1 ± 0.5 GtC yr-1 (9.9 ± 0.5 GtC yr-1 when the cement carbonation sink is included), ELUC was 1.1 ± 0.7 GtC yr-1, for a total anthropogenic CO2 emission of 11.1 ± 0.8 GtC yr-1 (40.8 ± 2.9 GtCO2). Also, for 2021, GATM was 5.2 ± 0.2 GtC yr-1 (2.5 ± 0.1 ppm yr-1), SOCEAN was 2.9 ± 0.4 GtC yr-1 and SLAND was 3.5 ± 0.9 GtC yr-1, with a BIM of -0.6 GtC yr-1 (i.e. total estimated sources too low or sinks too high). The global atmospheric CO2 concentration averaged over 2021 reached 414.71 ± 0.1 ppm. Preliminary data for 2022, suggest an increase in EFOS relative to 2021 of +1.1 % (0 % to 1.7 %) globally, and atmospheric CO2 concentration reaching 417.3 ppm, more than 50 % above pre-industrial level. Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2021, but discrepancies of up to 1 GtC yr-1 persist for the representation of annual to semi-decadal variability in CO2 fluxes. Comparison of estimates from multiple approaches and observations shows: (1) a persistent large uncertainty in the estimate of land-use changes emissions, (2) a low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) a discrepancy between the different methods on the strength of the ocean sink over the last decade. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set (Friedlingstein et al., 2022a; Friedlingstein et al., 2020; Friedlingstein et al., 2019; Le Quéré et al., 2018b, 2018a, 2016, 2015b, 2015a, 2014, 2013). The data presented in this work are available at https://doi.org/10.18160/GCP-2022 (Friedlingstein et al., 2022b).