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1. GRiMeDB: a comprehensive global database of methane concentrations and fluxes in fluvial ecosystems with supporting physical and chemical information

   https://doi.org/10.6073/pasta/f48cdb77282598052349e969920356ef  

   Stanley, Emily H.; Loken, Luke C.; Casson, Nora J.; Oliver, Samantha K.; Sponseller, Ryan A.; Wallin, Marcus B.; Zhang, Liwei; Rocher-Ros, Gerard (January 2023, Environmental Data Initiative)

   The Global River Methane Database (GriMeDB) is a compilation of measurements of CH4 concentrations and fluxes for flowing water environments derived from publications, reports, data repositories, and other outlets between 1973 and 2021. Assembly of GRiMeDB was motivated by the goal of having a centralized, standardized resource to facilitate further studies of CH4 pattern and process in flowing water systems, upscaling efforts, and identification of tendencies in when, where, and how CH4 has been sampled in streams and rivers across the world. Thus, CH4 data are supported by concurrent observations (as available) of aquatic CO2, N2O, temperature, conductivity, pH, dissolved oxygen, nitrogen, phosphorus, organic carbon, and discharge, along with site data (latitude, longitude, elevation, and [as available]: stream order, elevation, channel slope, catchment size, and codes for distinct or disturbed channel types). GRiMeDB includes over 24,000 records of CH4 concentration and greater than 8,000 flux measurements from over 5,000 unique sites, most of which are resolved to the daily time scale. 

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2. FLUXNET-CH₄: a global, multi-ecosystem dataset and analysis of methane seasonality from freshwater wetlands

   https://doi.org/10.5194/essd-13-3607-2021  

   Delwiche, Kyle B.; Knox, Sara Helen; Malhotra, Avni; Fluet-Chouinard, Etienne; McNicol, Gavin; Feron, Sarah; Ouyang, Zutao; Papale, Dario; Trotta, Carlo; Canfora, Eleonora; et al (January 2021, Earth System Science Data)

   null (Ed.)

   Abstract. Methane (CH4) emissions from natural landscapes constituteroughly half of global CH4 contributions to the atmosphere, yet largeuncertainties remain in the absolute magnitude and the seasonality ofemission quantities and drivers. Eddy covariance (EC) measurements ofCH4 flux are ideal for constraining ecosystem-scale CH4emissions due to quasi-continuous and high-temporal-resolution CH4flux measurements, coincident carbon dioxide, water, and energy fluxmeasurements, lack of ecosystem disturbance, and increased availability ofdatasets over the last decade. Here, we (1) describe the newly publisheddataset, FLUXNET-CH4 Version 1.0, the first open-source global dataset ofCH4 EC measurements (available athttps://fluxnet.org/data/fluxnet-ch4-community-product/, last access: 7 April 2021). FLUXNET-CH4includes half-hourly and daily gap-filled and non-gap-filled aggregatedCH4 fluxes and meteorological data from 79 sites globally: 42freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drainedecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we (2) evaluate FLUXNET-CH4 representativeness for freshwater wetland coverageglobally because the majority of sites in FLUXNET-CH4 Version 1.0 arefreshwater wetlands which are a substantial source of total atmosphericCH4 emissions; and (3) we provide the first global estimates of theseasonal variability and seasonality predictors of freshwater wetlandCH4 fluxes. Our representativeness analysis suggests that thefreshwater wetland sites in the dataset cover global wetland bioclimaticattributes (encompassing energy, moisture, and vegetation-relatedparameters) in arctic, boreal, and temperate regions but only sparselycover humid tropical regions. Seasonality metrics of wetland CH4emissions vary considerably across latitudinal bands. In freshwater wetlands(except those between 20∘ S to 20∘ N) the spring onsetof elevated CH4 emissions starts 3 d earlier, and the CH4emission season lasts 4 d longer, for each degree Celsius increase in meanannual air temperature. On average, the spring onset of increasing CH4emissions lags behind soil warming by 1 month, with very few sites experiencingincreased CH4 emissions prior to the onset of soil warming. Incontrast, roughly half of these sites experience the spring onset of risingCH4 emissions prior to the spring increase in gross primaryproductivity (GPP). The timing of peak summer CH4 emissions does notcorrelate with the timing for either peak summer temperature or peak GPP.Our results provide seasonality parameters for CH4 modeling andhighlight seasonality metrics that cannot be predicted by temperature or GPP(i.e., seasonality of CH4 peak). FLUXNET-CH4 is a powerful new resourcefor diagnosing and understanding the role of terrestrial ecosystems andclimate drivers in the global CH4 cycle, and future additions of sitesin tropical ecosystems and site years of data collection will provide addedvalue to this database. All seasonality parameters are available athttps://doi.org/10.5281/zenodo.4672601 (Delwiche et al., 2021).Additionally, raw FLUXNET-CH4 data used to extract seasonality parameterscan be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/ (last access: 7 April 2021), and a completelist of the 79 individual site data DOIs is provided in Table 2 of this paper. 

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3. GRiMeDB: the Global River Methane Database of concentrations and fluxes

   https://doi.org/10.5194/essd-15-2879-2023  

   Stanley, Emily H.; Loken, Luke C.; Casson, Nora J.; Oliver, Samantha K.; Sponseller, Ryan A.; Wallin, Marcus B.; Zhang, Liwei; Rocher-Ros, Gerard (January 2023, Earth System Science Data)

   Abstract. Despite their small spatial extent, fluvial ecosystems play a significant role in processing and transporting carbon in aquatic networks, which results in substantial emission of methane (CH4) into the atmosphere. For this reason, considerable effort has been put into identifying patterns and drivers of CH4 concentrations in streams and rivers and estimating fluxes to the atmosphere across broad spatial scales. However, progress toward these ends has been slow because of pronounced spatial and temporal variability of lotic CH4 concentrations and fluxes and by limited data availability across diverse habitats and physicochemical conditions. To address these challenges, we present a comprehensive database of CH4 concentrations and fluxes for fluvial ecosystems along with broadly relevant and concurrent physical and chemical data. The Global River Methane Database (GriMeDB; https://doi.org/10.6073/pasta/f48cdb77282598052349e969920356ef, Stanley et al., 2023) includes 24 024 records of CH4 concentration and 8205 flux measurements from 5029 unique sites derived from publications, reports, data repositories, unpublished data sets, and other outlets that became available between 1973 and 2021. Flux observations are reported as diffusive, ebullitive, and total CH4 fluxes, and GriMeDB also includes 17 655 and 8409 concurrent measurements of concentrations and 4444 and 1521 fluxes for carbon dioxide (CO2) and nitrous oxide (N2O), respectively. Most observations are date-specific (i.e., not site averages), and many are supported by data for 1 or more of 12 physicochemical variables and 6 site variables. Site variables include codes to characterize marginal channel types (e.g., springs, ditches) and/or the presence of human disturbance (e.g., point source inputs, upstream dams). Overall, observations in GRiMeDB encompass the broad range of the climatic, biological, and physical conditions that occur among world river basins, although some geographic gaps remain (arid regions, tropical regions, high-latitude and high-altitude systems). The global median CH4 concentration (0.20 µmol L−1) and diffusive flux (0.44 mmolm-2d-1) in GRiMeDB are lower than estimates from prior site-averaged compilations, although ranges (0 to 456 µmol L−1 and −136 to 4057 mmolm-2d-1) and standard deviations (10.69 and 86.4) are greater for this larger and more temporally resolved database. Available flux data are dominated by diffusive measurements despite the recognized importance of ebullitive and plant-mediated CH4 fluxes. Nonetheless, GriMeDB provides a comprehensive and cohesive resource for examining relationships between CH4 and environmental drivers, estimating the contribution of fluvial ecosystems to CH4 emissions, and contextualizing site-based investigations. 

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4. 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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5. . Drivers of diffusive CH4 emissions from shallow subarctic lakes on daily to multi-year time scales

   https://doi.org/doi.org/10.5194/bg-2019-322  

   Jansen, J. (January 2020, Biogeosciences)

   null (Ed.)

   Lakes and reservoirs contribute to regional carbon budgets via significant emissions of climate forcing trace gases. Here, for improved modelling, we use 8 years of floating chamber measurements from three small, shallow subarctic lakes (2010–2017, n = 1306) to separate the contribution of physical and biogeochemical processes to the turbulence-driven, diffusion-limited flux of methane (CH4) on daily to multi-year timescales. Correlative data include 9 years of surface water concentration measurements (2009–2017, n = 606), total water column storage (2009–2017, n = 1593) and in situ meteorological observations. We used the latter to compute near surface turbulence based on similarity scaling and then applied the surface renewal model to compute gas transfer velocities. Chamber fluxes averaged 6.9 ± 0.3 mg CH4 m−2 d−1 and gas transfer velocities (k600) averaged 4.0 ± 0.1 cm h−1. Chamber derived gas transfer velocities tracked the power-law wind speed relation of the model. Coefficients for the model and dissipation rates depended on shear production of turbulence, atmospheric stability, and exposure to wind. Fluxes increased with wind speed until daily average values exceeded 6.5 m s−1, at which point emissions were suppressed due to rapid water column degassing reducing the water–air concentration gradient. Arrhenius-type temperature functions of the CH4 flux (Ea‘ = 0.90 ± 0.14 eV) were robust (R2 ≥ 0.93, p < 0.01) and also applied to the surface CH4 concentration (Ea‘ = 0.88 ± 0.09 eV). These results imply that emissions were strongly coupled to production and supply to the water column. Spectral analysis indicated that on timescales shorter than a month, emissions were driven by wind shear whereas on longer timescales variations in water temperature governed the flux. Long-term monitoring efforts are essential to identify distinct functional relations that govern flux variability on timescales of weather and climate change. 

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