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1. Upscaling Wetland Methane Emissions From the FLUXNET‐CH4 Eddy Covariance Network (UpCH4 v1.0): Model Development, Network Assessment, and Budget Comparison

   https://doi.org/10.1029/2023AV000956  

   McNicol, Gavin; Fluet‐Chouinard, Etienne; Ouyang, Zutao; Knox, Sara; Zhang, Zhen; Aalto, Tuula; Bansal, Sheel; Chang, Kuang‐Yu; Chen, Min; Delwiche, Kyle; et al (October 2023, AGU Advances)

   Abstract Wetlands are responsible for 20%–31% of global methane (CH₄) emissions and account for a large source of uncertainty in the global CH₄budget. Data‐driven upscaling of CH₄fluxes from eddy covariance measurements can provide new and independent bottom‐up estimates of wetland CH₄emissions. Here, we develop a six‐predictor random forest upscaling model (UpCH4), trained on 119 site‐years of eddy covariance CH₄flux data from 43 freshwater wetland sites in the FLUXNET‐CH4 Community Product. Network patterns in site‐level annual means and mean seasonal cycles of CH₄fluxes were reproduced accurately in tundra, boreal, and temperate regions (Nash‐Sutcliffe Efficiency ∼0.52–0.63 and 0.53). UpCH4 estimated annual global wetland CH₄emissions of 146 ± 43 TgCH₄ y⁻¹for 2001–2018 which agrees closely with current bottom‐up land surface models (102–181 TgCH₄ y⁻¹) and overlaps with top‐down atmospheric inversion models (155–200 TgCH₄ y⁻¹). However, UpCH4 diverged from both types of models in the spatial pattern and seasonal dynamics of tropical wetland emissions. We conclude that upscaling of eddy covariance CH₄fluxes has the potential to produce realistic extra‐tropical wetland CH₄emissions estimates which will improve with more flux data. To reduce uncertainty in upscaled estimates, researchers could prioritize new wetland flux sites along humid‐to‐arid tropical climate gradients, from major rainforest basins (Congo, Amazon, and SE Asia), into monsoon (Bangladesh and India) and savannah regions (African Sahel) and be paired with improved knowledge of wetland extent seasonal dynamics in these regions. The monthly wetland methane products gridded at 0.25° from UpCH4 are available via ORNL DAAC (https://doi.org/10.3334/ORNLDAAC/2253). 

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2. The Global Methane Budget 2000–2017

   https://doi.org/10.5194/essd-12-1561-2020  

   Saunois, Marielle; Stavert, Ann R; Poulter, Ben; Bousquet, Philippe; Canadell, Josep G; Jackson, Robert B; Raymond, Peter A; Dlugokencky, Edward J; Houweling, Sander; Patra, Prabir K; et al (January 2020, Earth System Science Data)

   Abstract. Understanding and quantifying the global methane (CH4) budgetis important for assessing realistic pathways to mitigate climate change.Atmospheric emissions and concentrations of CH4 continue to increase,making CH4 the second most important human-influenced greenhouse gas interms of climate forcing, after carbon dioxide (CO2). The relativeimportance of CH4 compared to CO2 depends on its shorteratmospheric lifetime, stronger warming potential, and variations inatmospheric growth rate over the past decade, the causes of which are stilldebated. Two major challenges in reducing uncertainties in the atmosphericgrowth rate arise from the variety of geographically overlapping CH4sources and from the destruction of CH4 by short-lived hydroxylradicals (OH). To address these challenges, we have established aconsortium of multidisciplinary scientists under the umbrella of the GlobalCarbon Project to synthesize and stimulate new research aimed at improvingand regularly updating the global methane budget. Following Saunois et al. (2016), we present here the second version of the living review paperdedicated to the decadal methane budget, integrating results of top-downstudies (atmospheric observations within an atmospheric inverse-modellingframework) and bottom-up estimates (including process-based models forestimating land surface emissions and atmospheric chemistry, inventories ofanthropogenic emissions, and data-driven extrapolations). For the 2008–2017 decade, global methane emissions are estimated byatmospheric inversions (a top-down approach) to be 576 Tg CH4 yr−1 (range 550–594, corresponding to the minimum and maximumestimates of the model ensemble). Of this total, 359 Tg CH4 yr−1 or∼ 60 % is attributed to anthropogenic sources, that isemissions caused by direct human activity (i.e. anthropogenic emissions; range 336–376 Tg CH4 yr−1 or 50 %–65 %). The mean annual total emission for the new decade (2008–2017) is29 Tg CH4 yr−1 larger than our estimate for the previous decade (2000–2009),and 24 Tg CH4 yr−1 larger than the one reported in the previousbudget for 2003–2012 (Saunois et al., 2016). Since 2012, global CH4emissions have been tracking the warmest scenarios assessed by theIntergovernmental Panel on Climate Change. Bottom-up methods suggest almost30 % larger global emissions (737 Tg CH4 yr−1, range 594–881)than top-down inversion methods. Indeed, bottom-up estimates for naturalsources such as natural wetlands, other inland water systems, and geologicalsources are higher than top-down estimates. The atmospheric constraints onthe top-down budget suggest that at least some of these bottom-up emissionsare overestimated. The latitudinal distribution of atmosphericobservation-based emissions indicates a predominance of tropical emissions(∼ 65 % of the global budget, < 30∘ N)compared to mid-latitudes (∼ 30 %, 30–60∘ N)and high northern latitudes (∼ 4 %, 60–90∘ N). The most important source of uncertainty in the methanebudget is attributable to natural emissions, especially those from wetlandsand other inland waters. Some of our global source estimates are smaller than those in previouslypublished budgets (Saunois et al., 2016; Kirschke et al., 2013). In particular wetland emissions are about 35 Tg CH4 yr−1 lower due toimproved partition wetlands and other inland waters. Emissions fromgeological sources and wild animals are also found to be smaller by 7 Tg CH4 yr−1 by 8 Tg CH4 yr−1, respectively. However, the overalldiscrepancy between bottom-up and top-down estimates has been reduced byonly 5 % compared to Saunois et al. (2016), due to a higher estimate of emissions from inland waters, highlighting the need for more detailed research on emissions factors. Priorities for improving the methanebudget include (i) a global, high-resolution map of water-saturated soilsand inundated areas emitting methane based on a robust classification ofdifferent types of emitting habitats; (ii) further development ofprocess-based models for inland-water emissions; (iii) intensification ofmethane observations at local scales (e.g., FLUXNET-CH4 measurements)and urban-scale monitoring to constrain bottom-up land surface models, andat regional scales (surface networks and satellites) to constrainatmospheric inversions; (iv) improvements of transport models and therepresentation of photochemical sinks in top-down inversions; and (v) development of a 3D variational inversion system using isotopic and/orco-emitted species such as ethane to improve source partitioning. The data presented here can be downloaded fromhttps://doi.org/10.18160/GCP-CH4-2019 (Saunois et al., 2020) and from theGlobal Carbon Project. 

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3. Global Methane Budget 2000–2020

   https://doi.org/10.5194/essd-2024-115  

   Saunois, Marielle; Martinez, Adrien; Poulter, Benjamin; Zhang, Zhen; Raymond, Peter; Regnier, Pierre; Canadell, Joseph G; Jackson, Robert B; Patra, Prabir K; Bousquet, Philippe; et al (June 2024, Copernicus)

   Abstract. Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. Emissions and atmospheric concentrations of CH4 continue to increase, maintaining CH4 as the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO2). The relative importance of CH4 compared to CO2 for temperature change is related to its shorter atmospheric lifetime, stronger radiative effect, and acceleration in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in reducing uncertainties in the factors explaining the well-observed atmospheric growth rate arise from diverse, geographically overlapping CH4 sources and from the uncertain magnitude and temporal change in the destruction of CH4 by short-lived and highly variable hydroxyl radicals (OH). To address these challenges, we have established a consortium of multi-disciplinary scientists under the umbrella of the Global Carbon Project to improve, synthesise and update the global CH4 budget regularly and to stimulate new research on the methane cycle. Following Saunois et al. (2016, 2020), we present here the third version of the living review paper dedicated to the decadal CH4 budget, integrating results of top-down CH4 emission estimates (based on in-situ and greenhouse gas observing satellite (GOSAT) atmospheric observations and an ensemble of atmospheric inverse-model results) and bottom-up estimates (based on process-based models for estimating land-surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). We present a budget for the most recent 2010–2019 calendar decade (the latest period for which full datasets are available), for the previous decade of 2000–2009 and for the year 2020. The revision of the bottom-up budget in this edition benefits from important progress in estimating inland freshwater emissions, with better accounting of emissions from lakes and ponds, reservoirs, and streams and rivers. This budget also reduces double accounting across freshwater and wetland emissions and, for the first time, includes an estimate of the potential double accounting that still exists (average of 23 Tg CH4 yr-1). Bottom-up approaches show that the combined wetland and inland freshwater emissions average 248 [159–369] Tg CH4 yr-1 for the 2010–2019 decade. Natural fluxes are perturbed by human activities through climate, eutrophication, and land use. In this budget, we also estimate, for the first time, this anthropogenic component contributing to wetland and inland freshwater emissions. Newly available gridded products also allowed us to derive an almost complete latitudinal and regional budget based on bottom-up approaches. For the 2010–2019 decade, global CH4 emissions are estimated by atmospheric inversions (top-down) to be 575 Tg CH4 yr-1 (range 553–586, corresponding to the minimum and maximum estimates of the model ensemble). Of this amount, 369 Tg CH4 yr-1 or ~65 % are attributed to direct anthropogenic sources in the fossil, agriculture and waste and anthropogenic biomass burning (range 350–391 Tg CH4 yr-1 or 63–68 %). For the 2000–2009 period, the atmospheric inversions give a slightly lower total emission than for 2010–2019, by 32 Tg CH4 yr-1 (range 9–40). Since 2012, global direct anthropogenic CH4 emission trends have been tracking scenarios that assume no or minimal climate mitigation policies proposed by the Intergovernmental Panel on Climate Change (shared socio-economic pathways SSP5 and SSP3). Bottom-up methods suggest 16 % (94 Tg CH4 yr-1) larger global emissions (669 Tg CH4 yr-1, range 512–849) than top-down inversion methods for the 2010–2019 period. The discrepancy between the bottom-up and the top-down budgets has been greatly reduced compared to the previous differences (167 and 156 Tg CH4 yr-1 in Saunois et al. (2016, 2020), respectively), and for the first time uncertainty in bottom-up and top-down budgets overlap. The latitudinal distribution from atmospheric inversion-based emissions indicates a predominance of tropical and southern hemisphere emissions (~65 % of the global budget, <30° N) compared to mid (30° N–60° N, ~30 % of emissions) and high-northern latitudes (60° N–90° N, ~4 % of global emissions). This latitudinal distribution is similar in the bottom-up budget though the bottom-up budget estimates slightly larger contributions for the mid and high-northern latitudes, and slightly smaller contributions from the tropics and southern hemisphere than the inversions. Although differences have been reduced between inversions and bottom-up, the most important source of uncertainty in the global CH4 budget is still attributable to natural emissions, especially those from wetlands and inland freshwaters. We identify five major priorities for improving the CH4 budget: i) producing a global, high-resolution map of water-saturated soils and inundated areas emitting CH4 based on a robust classification of different types of emitting ecosystems; ii) further development of process-based models for inland-water emissions; iii) intensification of CH4 observations at local (e.g., FLUXNET-CH4 measurements, urban-scale monitoring, satellite imagery with pointing capabilities) to regional scales (surface networks and global remote sensing measurements from satellites) to constrain both bottom-up models and atmospheric inversions; iv) improvements of transport models and the representation of photochemical sinks in top-down inversions, and v) integration of 3D variational inversion systems using isotopic and/or co-emitted species such as ethane as well as information in the bottom-up inventories on anthropogenic super-emitters detected by remote sensing (mainly oil and gas sector but also coal, agriculture and landfills) to improve source partitioning. The data presented here can be downloaded from https://doi.org/10.18160/GKQ9-2RHT (Martinez et al., 2024). 

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4. Methane flux from Beringian coastal wetlands for the past 20,000 years

   https://doi.org/10.1016/j.quascirev.2024.108976  

   Fuchs, Matthias; Jones, Miriam C; Gowan, Evan J; Frolking, Steve; Walter_Anthony, Katey; Grosse, Guido; Jones, Benjamin M; O'Donnell, Jonathan A; Brosius, Laura; Treat, Claire (November 2024, Quaternary Science Reviews)

   Atmospheric methane (CH4) concentrations have gone through rapid changes since the last deglaciation; however, the reasons for abrupt increases around 14,700 and 11,600 years before present (yrs BP) are not fully understood. Concurrent with deglaciation, sea-level rise gradually inundated vast areas of the low-lying Beringian shelf. This transformation of what was once a terrestrial-permafrost tundra-steppe landscape, into coastal, and subsequently, marine environments led to new sources of CH4 from the region to the atmosphere. Here, we estimate, based on an extended geospatial analysis, the area of Beringian coastal wetlands in 1000-year intervals and their potential contribution to northern CH4 flux (based on present day CH4 fluxes from coastal wetland) during the past 20,000 years. At its maximum (∼14,000 yrs BP) we estimated CH4 fluxes from Beringia coastal wetlands to be 3.5 (+4.0/-1.9) Tg CH4 yr−1. This shifts the onset of CH4 fluxes from northern regions earlier, towards the Bølling-Allerød, preceding peak emissions from the formation of northern high latitude thermokarst lakes and wetlands. Emissions associated with the inundation of Beringian coastal wetlands better align with polar ice core reconstructions of northern hemisphere sources of atmospheric CH4 during the last deglaciation, suggesting a connection between rising sea level, coastal wetland expansion, and enhanced CH4 emissions. 

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5. BAWLD-CH₄: a comprehensive dataset of methane fluxes from boreal and arctic ecosystems

   https://doi.org/10.5194/essd-13-5151-2021  

   Kuhn, McKenzie A.; Varner, Ruth K.; Bastviken, David; Crill, Patrick; MacIntyre, Sally; Turetsky, Merritt; Walter Anthony, Katey; McGuire, Anthony D.; Olefeldt, David (January 2021, Earth System Science Data)

   Abstract. Methane (CH4) emissions from the boreal and arcticregion are globally significant and highly sensitive to climate change.There is currently a wide range in estimates of high-latitude annualCH4 fluxes, where estimates based on land cover inventories andempirical CH4 flux data or process models (bottom-up approaches)generally are greater than atmospheric inversions (top-down approaches). Alimitation of bottom-up approaches has been the lack of harmonizationbetween inventories of site-level CH4 flux data and the land coverclasses present in high-latitude spatial datasets. Here we present acomprehensive dataset of small-scale, surface CH4 flux data from 540terrestrial sites (wetland and non-wetland) and 1247 aquatic sites (lakesand ponds), compiled from 189 studies. The Boreal–Arctic Wetland and LakeMethane Dataset (BAWLD-CH4) was constructed in parallel with acompatible land cover dataset, sharing the same land cover classes to enablerefined bottom-up assessments. BAWLD-CH4 includes information onsite-level CH4 fluxes but also on study design (measurement method,timing, and frequency) and site characteristics (vegetation, climate,hydrology, soil, and sediment types, permafrost conditions, lake size anddepth, and our determination of land cover class). The different land coverclasses had distinct CH4 fluxes, resulting from definitions that wereeither based on or co-varied with key environmental controls. Fluxes ofCH4 from terrestrial ecosystems were primarily influenced by watertable position, soil temperature, and vegetation composition, while CH4fluxes from aquatic ecosystems were primarily influenced by watertemperature, lake size, and lake genesis. Models could explain more of thebetween-site variability in CH4 fluxes for terrestrial than aquaticecosystems, likely due to both less precise assessments of lake CH4fluxes and fewer consistently reported lake site characteristics. Analysisof BAWLD-CH4 identified both land cover classes and regions within theboreal and arctic domain, where future studies should be focused, alongsidemethodological approaches. Overall, BAWLD-CH4 provides a comprehensivedataset of CH4 emissions from high-latitude ecosystems that are usefulfor identifying research opportunities, for comparison against new fielddata, and model parameterization or validation. BAWLD-CH4 can bedownloaded from https://doi.org/10.18739/A2DN3ZX1R (Kuhn et al., 2021). 

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