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1. 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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2. Methane emissions from Arctic landscapes during 2000–2015: an analysis with land and lake biogeochemistry models

   https://doi.org/10.5194/bg-20-1181-2023  

   Liu, Xiangyu; Zhuang, Qianlai (January 2023, Biogeosciences)

   Abstract. Wetlands and freshwater bodies (mainly lakes) are the largestnatural sources of the greenhouse gas CH4 to the atmosphere. Great effortshave been made to quantify these source emissions and their uncertainties.Previous research suggests that there might be significant uncertaintiescoming from “double accounting” emissions from freshwater bodies andwetlands. Here we quantify the methane emissions from both land andfreshwater bodies in the pan-Arctic with two process-based biogeochemistrymodels by minimizing the double accounting at the landscape scale. Twonon-overlapping dynamic areal change datasets are used to drive the models.We estimate that the total methane emissions from the pan-Arctic are 36.46 ± 1.02 Tg CH4 yr−1 during 2000–2015, of which wetlands andfreshwater bodies are 21.69 ± 0.59 Tg CH4 yr−1 and 14.76 ± 0.44 Tg CH4 yr−1, respectively. Our estimation narrows thedifference between previous bottom-up (53.9 Tg CH4 yr−1) andtop-down (29 Tg CH4 yr−1) estimates. Our correlation analysisshows that air temperature is the most important driver for methane emissionsof inland water systems. Wetland emissions are also significantly affected byvapor pressure, while lake emissions are more influenced by precipitation andlandscape areal changes. Sensitivity tests indicate that pan-Arctic lakeCH4 emissions were highly influenced by air temperature but less bylake sediment carbon increase. 

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3. Monthly gridded data product of northern wetland methane emissions based on upscaling eddy covariance observations

   https://doi.org/10.5194/essd-11-1263-2019  

   Peltola, Olli; Vesala, Timo; Gao, Yao; Räty, Olle; Alekseychik, Pavel; Aurela, Mika; Chojnicki, Bogdan; Desai, Ankur R.; Dolman, Albertus J.; Euskirchen, Eugenie S.; et al (January 2019, Earth System Science Data)

   Abstract. Natural wetlands constitute the largest and most uncertain sourceof methane (CH4) to the atmosphere and a large fraction of them are found in the northern latitudes. These emissions are typically estimated using process (“bottom-up”) or inversion (“top-down”) models. However, estimates from these two types of models are not independent of each other since the top-down estimates usually rely on the a priori estimation of these emissions obtained with process models. Hence, independent spatially explicit validation data are needed. Here we utilize a random forest (RF) machine-learning technique to upscale CH4 eddy covariance flux measurements from 25 sites to estimate CH4 wetland emissions from the northern latitudes (north of 45∘ N). Eddy covariance datafrom 2005 to 2016 are used for model development. The model is then used to predict emissions during 2013 and 2014. The predictive performance of the RF model is evaluated using a leave-one-site-out cross-validation scheme. The performance (Nash–Sutcliffe model efficiency =0.47) is comparable to previous studies upscaling net ecosystem exchange of carbon dioxide and studies comparing process model output against site-level CH4 emission data. The global distribution of wetlands is one major source of uncertainty for upscaling CH4. Thus, three wetland distribution maps are utilized in the upscaling. Depending on the wetland distribution map, the annual emissions for the northern wetlands yield 32 (22.3–41.2, 95 % confidence interval calculated from a RF model ensemble), 31 (21.4–39.9) or 38 (25.9–49.5) Tg(CH4) yr−1. To further evaluate the uncertainties of the upscaled CH4 flux data products we also compared them against output from two process models (LPX-Bern and WetCHARTs), and methodological issues related to CH4 flux upscaling are discussed. The monthly upscaled CH4 flux data products are available athttps://doi.org/10.5281/zenodo.2560163 (Peltola et al., 2019). 

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4. Investigating methane emissions from geologic microseepage in Western New York State, United States

   https://doi.org/10.1525/elementa.2020.00066  

   Kazemi, Roxana; Schlageter, William; Hmiel, Benjamin; Weber, Thomas S.; Murray, Lee T.; Petrenko, Vasilii V. (January 2021, Elementa: Science of the Anthropocene)

   Methane is a powerful greenhouse gas and a key player in atmospheric chemistry. Important uncertainties remain in the global atmospheric methane budget, with natural geologic emissions being one of the particularly uncertain terms. In recent bottom-up studies, geologic emissions have been estimated to comprise up to 10% of the global budget (40–60 Teragrams of methane per year, Tg CH4 yr–1). In contrast, top-down constraints from 14C of methane in preindustrial air extracted from ice cores indicate that the geologic methane source is approximately an order of magnitude lower. Recent bottom-up inventories propose microseepage (diffuse low-level flux of methane through soils over large areas) as the largest single component of the geologic methane flux. In this study, we present new measurements of methane microseepage from the Appalachian Basin (Western New York State) and compare these with prior microseepage measurements from other regions and with predicted values from the most recent bottom-up inventory. Our results show lower microseepage values than most prior data sets and indicate that positive microseepage fluxes in this region are not as widespread as previously assumed. A statistical analysis of our results indicates that mean microseepage flux in this region has very likely been overestimated by the bottom-up inventory, even though our measurements more likely than not underestimate the true mean flux. However, this is a small data set from a single region and as such cannot be used to evaluate the validity of the microseepage emissions inventory as a whole. Instead, the results demonstrate the need for a more extensive network of direct geologic emission measurements in support of improved bottom-up inventories. 

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5. Permafrost Region Greenhouse Gas Budgets Suggest a Weak CO ₂ Sink and CH ₄ and N ₂ O Sources, But Magnitudes Differ Between Top‐Down and Bottom‐Up Methods

   https://doi.org/10.1029/2023GB007969  

   Hugelius, G; Ramage, J; Burke, E; Chatterjee, A; Smallman, T L; Aalto, T; Bastos, A; Biasi, C; Canadell, J G; Chandra, N; et al (October 2024, Global Biogeochemical Cycles)

   Abstract Large stocks of soil carbon (C) and nitrogen (N) in northern permafrost soils are vulnerable to remobilization under climate change. However, there are large uncertainties in present‐day greenhouse gas (GHG) budgets. We compare bottom‐up (data‐driven upscaling and process‐based models) and top‐down (atmospheric inversion models) budgets of carbon dioxide (CO₂), methane (CH₄) and nitrous oxide (N₂O) as well as lateral fluxes of C and N across the region over 2000–2020. Bottom‐up approaches estimate higher land‐to‐atmosphere fluxes for all GHGs. Both bottom‐up and top‐down approaches show a sink of CO₂in natural ecosystems (bottom‐up: −29 (−709, 455), top‐down: −587 (−862, −312) Tg CO₂‐C yr⁻¹) and sources of CH₄(bottom‐up: 38 (22, 53), top‐down: 15 (11, 18) Tg CH₄‐C yr⁻¹) and N₂O (bottom‐up: 0.7 (0.1, 1.3), top‐down: 0.09 (−0.19, 0.37) Tg N₂O‐N yr⁻¹). The combined global warming potential of all three gases (GWP‐100) cannot be distinguished from neutral. Over shorter timescales (GWP‐20), the region is a net GHG source because CH₄dominates the total forcing. The net CO₂sink in Boreal forests and wetlands is largely offset by fires and inland water CO₂emissions as well as CH₄emissions from wetlands and inland waters, with a smaller contribution from N₂O emissions. Priorities for future research include the representation of inland waters in process‐based models and the compilation of process‐model ensembles for CH₄and N₂O. Discrepancies between bottom‐up and top‐down methods call for analyses of how prior flux ensembles impact inversion budgets, more and well‐distributed in situ GHG measurements and improved resolution in upscaling techniques. 

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