The ongoing development of the Global Carbon Project (GCP) global methane (CH₄) budget shows a continuation of increasing CH₄ emissions and CH₄ accumulation in the atmosphere during 2000–2017. Here, we decompose the global budget into 19 regions (18 land and 1 oceanic) and five key source sectors to spatially attribute the observed global trends. A comparison of top‐down (TD) (atmospheric and transport model‐based) and bottom‐up (BU) (inventory‐ and process model‐based) CH₄ emission estimates demonstrates robust temporal trends with CH₄ emissions increasing in 16 of the 19 regions. Five regions—China, Southeast Asia, USA, South Asia, and Brazil—account for >40% of the global total emissions (their anthropogenic and natural sources together totaling >270 Tg CH₄ yr⁻¹ in 2008–2017). Two of these regions, China and South Asia, emit predominantly anthropogenic emissions (>75%) and together emit more than 25% of global anthropogenic emissions. China and the Middle East show the largest increases in total emission rates over the 2000 to 2017 period with regional emissions increasing by >20%. In contrast, Europe and Korea and Japan show a steady decline in CH₄ emission rates, with total emissions decreasing by ~10% between 2000 and 2017. Coal mining, waste (predominantly solid waste disposal) and livestock (especially enteric fermentation) are dominant drivers of observed emissions increases while declines appear driven by a combination of waste and fossil emission reductions. As such, together these sectors present the greatest risks of further increasing the atmospheric CH₄ burden and the greatest opportunities for greenhouse gas abatement.

Up in the air: Understanding ocean-atmospheric carbon dioxide (CO ₂ ) fluxes in the Southern Ocean is necessary for quantifying the global CO ₂ budget, but measurements in the harsh conditions there make collecting good data difficult, so a quantitative picture still is out of reach. Long et al . present measurements of atmospheric CO ₂ concentrations made by aircraft and show that the annual net flux of carbon into the ocean south of 45°S is large, with stronger summertime uptake and less wintertime outgassing than other recent observations have indicated. —HJS

Under the UK-focused Greenhouse gAs and Uk and Global Emissions (GAUGE) project, two new tall tower greenhouse gas (GHG) observation sites were established in the 2013/2014 Northern Hemispheric winter. These sites, located at existing telecommunications towers, utilized a combination of cavity ring-down spectroscopy (CRDS) and gas chromatography (GC) to measure key GHGs (CO₂, CH₄, CO, N₂O and SF₆). Measurements were made at multiple intake heights on each tower. CO₂ and CH₄ dry mole fractions were calculated from either CRDS measurements of wet air, which were post-corrected with an instrument-specific empirical correction, or samples dried to between 0.05 % H₂O and 0.3 % H₂O using a Nafion^® dryer, with a smaller correction applied for the residual H₂O. The impact of these two drying strategies was examined. Drying with a Nafion^® dryer was not found to have a significant effect on the observed CH₄ mole fraction; however, Nafion^® drying did cause a 0.02 µmol mol⁻¹ CO₂ bias. This bias was stable for sample CO₂ mole fractions between 373 and 514 µmol mol⁻¹ and for sample H₂O up to 3.5 %. As the calibration and standard gases are treated in the same manner, the 0.02 µmol mol⁻¹ CO₂ bias is mostly calibrated out with the residual error (≪0.01 µmol mol⁻¹ CO₂) well below the World Meteorological Organization (WMO) reproducibility requirements. Of more concern was the error associated with the empirical instrument-specific water correction algorithms. These corrections are relatively stable and reproducible for samples with H₂O between 0.2 % and 2.5 %, CO₂ between 345 and 449 µmol mol⁻¹, and CH₄ between 1743 and 2145 nmol mol⁻¹. However, the residual errors in these corrections increase to > 0.05 µmol mol⁻¹ for CO₂ and > 1 nmol mol⁻¹ for CH₄ (greater than the WMO internal reproducibility guidelines) at higher humidities and for samples with very low (< 0.5 %) water content. These errors also scale with the absolute magnitude of the CO₂ and CH₄ mole fractions. As such, water corrections calculated in this manner are not suitable for samples with low (< 0.5 %) or high (> 2.5 %) water contents and either alternative correction methods should be used or partial drying or humidification considered prior to sample analysis.

Atmospheric trace gas measurements can be used to independently assess national greenhouse gas inventories through inverse modeling. Atmospheric nitrous oxide (N₂O) measurements made in the United Kingdom (UK) and Republic of Ireland are used to derive monthly N₂O emissions for 2013–2022 using two different inverse methods. We find mean UK emissions of 90.5 ± 23.0 (1σ) and 111.7 ± 32.1 (1σ) Gg N₂O yr⁻¹ for 2013–2022, and corresponding trends of −0.68 ± 0.48 (1σ) Gg N₂O yr⁻² and −2.10 ± 0.72 (1σ) Gg N₂O yr⁻², respectively, for the two inverse methods. The UK National Atmospheric Emissions Inventory (NAEI) reported mean N₂O emissions of 73.9 ± 1.7 (1σ) Gg N₂O yr⁻¹ across this period, which is 22%–51% smaller than the emissions derived from atmospheric data. We infer a pronounced seasonal cycle in N₂O emissions, with a peak occurring in the spring and a second smaller peak in the late summer for certain years. The springtime peak has a long seasonal decline that contrasts with the sharp rise and fall of N₂O emissions estimated from the bottom‐up UK Emissions Model (UKEM). Bayesian inference is used to minimize the seasonal cycle mismatch between the average top‐down (atmospheric data‐based) and bottom‐up (process model and inventory‐based) seasonal emissions at a sub‐sector level. Increasing agricultural manure management and decreasing synthetic fertilizer N₂O emissions reduces some of the discrepancy between the average top‐down and bottom‐up seasonal cycles. Other possibilities could also explain these discrepancies, such as missing emissions from NH₃ deposition, but these require further investigation.

The Southern Ocean (south of 30^∘ S) is a key global-scale sink of carbon dioxide (CO₂). However, the isolated and inhospitable nature of this environment has restricted the number of oceanic and atmospheric CO₂ measurements in this region. This has limited the scientific community's ability to investigate trends and seasonal variability of the sink. Compared to regions further north, the near-absence of terrestrial CO₂ exchange and strong large-scale zonal mixing demands unusual inter-site measurement precision to help distinguish the presence of midlatitude to high latitude ocean exchange from large CO₂ fluxes transported southwards in the atmosphere. Here we describe a continuous, in situ, ultra-high-precision Southern Ocean region CO₂ record, which ran at Macquarie Island (54^∘37^′ S, 158^∘52^′ E) from 2005 to 2016 using a LoFlo2 instrument, along with its calibration strategy, uncertainty analysis and baseline filtering procedures. Uncertainty estimates calculated for minute and hourly frequency data range from 0.01 to 0.05 µmol mol⁻¹ depending on the averaging period and application. Higher precisions are applicable when comparing Macquarie Island LoFlo measurements to those of similar instruments on the same internal laboratory calibration scale and more uncertain values are applicable when comparing to other networks. Baseline selection is designed to remove measurements that are influenced by local Macquarie Island CO₂ sources, with effective removal achieved using a within-minute CO₂ standard deviation metric. Additionally, measurements that are influenced by CO₂ fluxes from Australia or other Southern Hemisphere land masses are effectively removed using model-simulated radon concentration. A comparison with flask records of atmospheric CO₂ at Macquarie Island highlights the limitation of the flask record (due to corrections for storage time and limited temporal coverage) when compared to the new high-precision, continuous record: the new record shows much less noisy seasonal variations than the flask record. As such, this new record is ideal for improving our understanding of the spatial and temporal variability of the Southern Ocean CO₂ flux, particularly when combined with data from similar instruments at other Southern Hemispheric locations.