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Wetlands are the largest natural source of methane (CH4) emissions globally. Northern wetlands (>45° N), accounting for 42 % of global wetland area, are increasingly vulnerable to carbon loss, especially as CH4 emissions may accelerate under intensified high-latitude warming. However, the magnitude and spatial patterns of high-latitude CH4 emissions remain relatively uncertain. Here we present estimates of daily CH4 fluxes obtained using a new machine learning-based wetland CH4 upscaling framework (WetCH4) that applies the most complete database of eddy covariance (EC) observations available to date, and satellite remote sensing informed observations of environmental conditions at 10-km resolution. The most important predictor variables included near-surface soil temperatures (top 40 cm), vegetation reflectance, and soil moisture. Our results, modeled from 138 site-years across 26 sites, had relatively strong predictive skill with a mean R2 of 0.46 and 0.62 and a mean absolute error (MAE) of 23 nmol m-2 s-1 and 21 nmol m-2 s-1 for daily and monthly fluxes, respectively. Based on the model results, we estimated an annual average of 20.8 ±2.1 Tg CH4 yr-1 for the northern wetland region (2016–2022) and total budgets ranged from 13.7–44.1 Tg CH4 yr-1, depending on wetland map extents. Although 86 % of the estimated CH4 budget occurred during the May–October period, a considerable amount (1.4 ±0.2 Tg CH4) occurred during winter. Regionally, the West Siberian wetlands accounted for a majority (51 %) of the interannual variation in domain CH4 emissions. Significant issues with data coverage remain, with only 23 % of the sites observing year-round and most of the data from 11 wetland sites in Alaska and 10 bog/fen sites in Canada and Fennoscandia, and in general, Western Siberian Lowlands are underrepresented by EC CH4 sites. Our results provide high spatiotemporal information on the wetland emissions in the high-latitude carbon cycle and possible responses to climate change. Continued, all-season tower observations and improved soil moisture products are needed for future improvement of CH4 upscaling. The dataset can be found at https://doi.org/10.5281/zenodo.10802154 (Ying et al., 2024). [ABSTRACT FROM AUTHOR]

We have constructed an atmospheric inversion framework based on TM5-4DVAR to jointly assimilate measurements of methane and δ13C of methane in order to estimate source-specific methane emissions. Here we present global emission estimates from this framework for the period 1999–2016. We assimilate a newly constructed, multi-agency database of CH4 and δ13C measurements. We find that traditional CH4 -only atmospheric inversions are unlikely to estimate emissions consistent with atmospheric δ13C data, and assimilating δ13C data is necessary to derive emissions consistent with both measurements. Our framework attributes ca. 85 % of the post-2007 growth in atmospheric methane to microbial sources, with about half of that coming from the tropics between 23.5 ∘ N and 23.5 ∘ S. This contradicts the attribution of the recent growth in the methane budget of the Global Carbon Project (GCP). We find that the GCP attribution is only consistent with our top-down estimate in the absence of δ13C data. We find that at global and continental scales, δ13C data can separate microbial from fossil methane emissions much better than CH4 data alone, and at smaller scales this ability is limited by the current δ13C measurement coverage. Finally, we find that the largest uncertainty in using δ13C data to separate different methane source types comes from our knowledge of atmospheric chemistry, specifically the distribution of tropospheric chlorine and the isotopic discrimination of the methane sink. [ABSTRACT FROM AUTHOR]

We have constructed an atmospheric inversion framework based on TM5 4DVAR to jointly assimilate measurements of methane and d13C of methane in order to estimate source-specific methane emissions. Here we present global emission estimates from this framework for the period 1999-2016. We assimilate a newly constructed, multi-agency database of CH4 and d13CH4 measurements. We find that traditional CH4-only atmospheric inversions are unlikely to estimate emissions consistent with atmospheric d13CH4 data, and assimilating d13CH4 data is necessary to deriving emissions consistent with both measurements. Our framework attributes ca. 85% of the post-2007 growth in atmospheric methane to microbial sources, with about half of that coming from the Tropics between 23.5 °N and 23.5 °S. This contradicts the attribution of the recent growth in the methane budget of the Global Carbon Project (GCP). We find that the GCP attribution is only consistent with our top-down estimate in the absence of d13CH4 data. We find that at global and continental scales, d13CH4 data can separate microbial from fossil methane emissions much better than CH4 data alone can, and at smaller scales this ability is limited by the current d13CH4 measurement coverage. Finally, we find that the largest uncertainty in using d13CH4 data to separate different methane source types comes from our knowledge of atmospheric chemistry, specifically the distribution of tropospheric chlorine and the isotopic discrimination of the methane sink. [ABSTRACT FROM AUTHOR]

Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. Atmospheric emissions and concentrations of CH4 are continuing to increase, making CH4 the second most important human-influenced greenhouse gas in terms of climate forcing, after carbon dioxide (CO2). Assessing the relative importance of CH4 in comparison to CO2 is complicated by its shorter atmospheric lifetime, stronger warming potential, and atmospheric growth rate variations over the past decade, the causes of which are still debated. Two major difficulties in reducing uncertainties arise from the variety of geographically overlapping CH4 sources and from the destruction of CH4 by short-lived hydroxyl radicals (OH). To address these difficulties, we have established a consortium of multi-disciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. Following Saunois et al. (2016), we present here the second version of the living review paper dedicated to the decadal methane budget, integrating results of top-down studies (atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up estimates (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). For the 2008–2017 decade, global methane emissions are estimated by atmospheric inversions (top-down approach) to be 572 Tg CH4 yr−1 (range 538–593, corresponding to the minimum and maximum estimates of the ensemble), of which 357 Tg CH4 yr−1 or ~ 60 % are attributed to anthropogenic sources (range 50–65 %). This total emission is 27 Tg CH4 yr−1 larger than the value estimated for the period 2000–2009 and 24 Tg CH4 yr−1 larger than the one reported in the previous budget for the period 2003–2012 (Saunois et al. 2016). Since 2012, global CH4 emissions have been tracking the carbon intensive scenarios developed by the Intergovernmental Panel on Climate Change (Gidden et al., 2019). Bottom-up methods suggest larger global emissions (737 Tg CH4 yr−1, range 583–880) than top-down inversion methods, mostly because of larger estimated natural emissions from sources such as natural wetlands, other inland water systems, and geological sources. However the strength of the atmospheric constraints on the top-down budget, suggest that these bottom-up emissions are overestimated. The latitudinal distribution of atmospheric-based emissions indicates a predominance of tropical emissions (~ 65 % of the global budget, < 30° N) compared to mid (~ 30 %, 30° N–60° N) and high northern latitudes (~ 4 %, 60° N–90° N). Our analyses suggest that uncertainties associated with estimates of anthropogenic emissions are smaller than those of natural sources, with top-down inversions yielding larger uncertainties than bottom-up inventories and models. The most important source of uncertainty in the methane budget is attributable to natural emissions, especially those from wetlands and other inland waters. Some global source estimates are smaller compared to the previously published budgets (Saunois et al. 2016; Kirschke et al. 2013), particularly for vegetated wetland emissions that are lower by about 35 Tg CH4 yr−1 due to efforts to partition vegetated wetlands and inland waters. Emissions from geological sources are also found to be smaller by 7 Tg CH4 yr−1, and wild animals by 8 Tg CH4 yr−1. However the overall discrepancy between bottom-up and top-down estimates has been reduced by only 5 % compared to Saunois et al. (2016), due to a higher estimate of freshwater emissions resulting from recent research and the integration of emissions from estuaries. Priorities for improving the methane budget include: i) a global, high-resolution map of water-saturated soils and inundated areas emitting methane based on a robust classification of different types of emitting habitats; ii) further development of process-based models for inland-water emissions; iii) intensification of methane observations at local scales (e.g., FLUXNET-CH4 measurements and urban monitoring to constrain bottom-up land surface models, and at regional scales (surface networks and satellites) to constrain atmospheric inversions; iv) improvements of transport models and the representation of photochemical sinks in top-down inversions, and v) development of a 3D variational inversion system using isotopic and/or co-emitted species such as ethane. [ABSTRACT FROM AUTHOR]

We consider the utility of the annual inter-polar difference (IPD) as a metric for changes in Arctic emissions of methane (CH4). The IPD has been previously defined as the difference between weighted annual means of CH4 mole fraction data collected at stations from the two polar regions (defined as latitudes poleward of 53 ∘ N and 53 ∘ S, respectively). This subtraction approach (IPD) implicitly assumes that extra-polar CH4 emissions arrive within the same calendar year at both poles. We show using a continuous version of the IPD that the metric includes not only changes in Arctic emissions but also terms that represent atmospheric transport of air masses from lower latitudes to the polar regions. We show the importance of these atmospheric transport terms in understanding the IPD using idealized numerical experiments with the TM5 global 3-D atmospheric chemistry transport model that is run from 1980 to 2010. A northern mid-latitude pulse in January 1990, which increases prior emission distributions, arrives at the Arctic with a higher mole fraction and ≃12 months earlier than at the Antarctic. The perturbation at the poles subsequently decays with an e -folding lifetime of ≃4 years. A similarly timed pulse emitted from the tropics arrives with a higher value at the Antarctic ≃11 months earlier than at the Arctic. This perturbation decays with an e -folding lifetime of ≃7 years. These simulations demonstrate that the assumption of symmetric transport of extra-polar emissions to the poles is not realistic, resulting in considerable IPD variations due to variations in emissions and atmospheric transport. We assess how well the annual IPD can detect a constant annual growth rate of Arctic emissions for three scenarios, 0.5 %, 1 %, and 2 %, superimposed on signals from lower latitudes, including random noise. We find that it can take up to 16 years to detect the smallest prescribed trend in Arctic emissions at the 95 % confidence level. Scenarios with higher, but likely unrealistic, growth in Arctic emissions are detected in less than a decade. We argue that a more reliable measurement-driven approach would require data collected from all latitudes, emphasizing the importance of maintaining a global monitoring network to observe decadal changes in atmospheric greenhouse gases. [ABSTRACT FROM AUTHOR]