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140 results for “methane emission”
National contributions to climate change due to historical emissions of carbon dioxide, methane and nitrous oxide
<p>A complete description of the dataset is given by <a href="http://doi.org/10.1038/s41597-023-02041-1">Jones et al. (2023)</a>. Key information is provided below.</p> <p><strong>Background</strong></p> <p>A dataset describing the global warming response to national emissions CO<sub>2</sub>, CH<sub>4</sub> and N<sub>2</sub>O from fossil and land use sources during 1851-2021.</p> <p>National CO<sub>2 </sub>emissions data are collated from the Global Carbon Project (Andrew and Peters, 2024; Friedlingstein et al., 2024). </p> <p>National CH<sub>4</sub> and N<sub>2</sub>O emissions data are collated from PRIMAP-hist (HISTTP) (Gütschow et al., 2024).</p> <p>We construct a time series of cumulative CO2-equivalent emissions for each country, gas, and emissions source (fossil or land use). Emissions of CH<sub>4</sub> and N<sub>2</sub>O emissions are related to cumulative CO2-equivalent emissions using the Global Warming Potential (GWP*) approach, with best-estimates of the coefficients taken from the IPCC AR6 (Forster et al., 2021).</p> <p>Warming in response to cumulative CO2-equivalent emissions is estimated using the transient climate response to cumulative carbon emissions (TCRE) approach, with best-estimate value of TCRE taken from the IPCC AR6 (Forster et al., 2021, Canadell et al., 2021). 'Warming' is specifically the change in global mean surface temperature (GMST).</p> <p>The data files provide emissions, cumulative emissions and the GMST response by country, gas (CO<sub>2</sub>, CH<sub>4</sub>, N<sub>2</sub>O or 3-GHG total) and source (fossil emissions, land use emissions or the total).</p> <p><strong>Data records: overview</strong></p> <p>The data records include three comma separated values (.csv) files as described below.</p> <p>All files are in ‘long’ format with one value provided in the <em>Data</em> column for each combination of the categorical variables <em>Year, Country Name, Country ISO3 code, Gas, and Component</em> columns.</p> <p><em>Component</em> specifies fossil emissions, LULUCF emissions or total emissions of the gas.</p> <p><em>Gas</em> specifies CO<sub>2</sub>, CH<sub>4</sub>, N<sub>2</sub>O or the three-gas total (labelled 3-GHG).</p> <p><em>Country ISO3 codes</em> are specifically the unique ISO 3166-1 alpha-3 codes of each country.</p> <p><strong>Data records: specifics</strong></p> <p>Data are provided relative to 2 reference years (denoted <em>ref_year </em>below): 1850 and 1991. 1850 is a mutual first year of data spanning all input datasets. 1991 is relevant because the United Nations Framework Convention on Climate Change was operationalised in 1992.</p> <p><em>EMISSIONS_ANNUAL_{ref_year-20}-2023.csv:</em> <em>Data </em>includes annual emissions of CO<sub>2</sub> (Pg CO<sub>2</sub> year<sup>-1</sup>), CH<sub>4</sub> (Tg CH<sub>4</sub> year<sup>-1</sup>) and N<sub>2</sub>O (Tg N<sub>2</sub>O year<sup>-1</sup>) during the period <em>ref_year-20 </em>to 2023. The <em>Data</em> column provides values for every combination of the categorical variables. Data are provided from <em>ref_year-20</em> because these data are required to calculate GWP* for CH<sub>4</sub>.</p> <p><em>EMISSIONS_CUMULATIVE_CO2e100_{ref_year+1}-2023.csv: Data </em>includes the cumulative CO<sub>2</sub> equivalent emissions in units Pg CO<sub>2</sub>-e<sub>100</sub> during the period <em>ref_year+1</em> to 2023 (i.e. since the reference year). The <em>Data</em> column provides values for every combination of the categorical variables. </p> <p><em>GMST_response_{ref_year+1}-2023.csv:</em> <em>Data</em> includes the change in global mean surface temperature (GMST) due to emissions of the three gases in units °C during the period <em>ref_year+1</em> to 2023 (i.e. since the reference year). The <em>Data</em> column provides values for every combination of the categorical variables. </p> <p><strong>Accompanying Code</strong></p> <p>Code is available at: <a href="https://github.com/jonesmattw/National_Warming_Contributions">https://github.com/jonesmattw/National_Warming_Contributions</a> .</p> <p>The code requires Input.zip to run (see README at the GitHub link).</p> <p><strong>Further info: Country Groupings</strong></p> <p>We also provide estimates of the contributions of various country groupings as defined by the UNFCCC:</p> <ul> <li>Annex I countries (number of countries, n = 42)</li> <li>Annex II countries (n = 23)</li> <li>economies in transition (EITs; n = 15)</li> <li>the least developed countries (LDCs; n = 47)</li> <li>the like-minded developing countries (LMDC; n = 24).</li> </ul> <p>And other country groupings:</p> <ul> <li>the organisation for economic co-operation and development (OECD; n = 38)</li> <li>the European Union (EU27 post-Brexit)</li> <li>the Brazil, South Africa, India and China (BASIC) group.</li> </ul> <p>See COUNTRY_GROUPINGS.xlsx for the lists of countries in each group.</p>
Summertime methane and carbon dioxide emission rates and associated variables from a national-scale survey of 146 reservoirs in the United States, 2016-2023
Reservoirs are globally important sources of greenhouse gases, but the magnitude of their emissions is highly uncertain. Here we present data for 146 reservoirs from two surveys of reservoir methane and carbon dioxide emissions, one at the regional scale in the midwestern United States and one at the national scale in the conterminous United States, plus data from one reservoir in Washington and another in Puerto Rico. At all reservoirs, ebullitive and diffusive emissions and basic physiochemistry were measured at 15-70 locations during one 22 to 64-hour period during the summers of 2016-2023, with four reservoirs revisited a second time. Concomitant water chemistry measurements were also made at an index site. The dataset is comprised of two geospatial files and seven .csv files containing greenhouse gas emissions, water chemistry, morphology, and other relevant data. These data comprise the largest multi-reservoir emissions dataset ever assembled using consistent measurement methods.
Ebullitive methane emissions from oxygenated wetland streams at North Temperate Lakes LTER 2013
Stream and river carbon dioxide emissions are an important component of the global carbon cycle. Methane emissions from streams could also contribute to regional or global greenhouse gas cycling, but there are relatively few data regarding stream and river methane emissions. Furthermore, the available data do not typically include the ebullitive (bubble-mediated) pathway, instead focusing on emission of dissolved methane by diffusion or convection. Here, we show the importance of ebullitive methane emissions from small streams in the regional greenhouse gas balance of a lake and wetland-dominated landscape in temperate North America and identify the origin of the methane emitted from these well-oxygenated streams. Stream methane flux densities from this landscape tended to exceed those of nearby wetland diffusive fluxes as well as average global wetland ebullitive fluxes. Total stream ebullitive methane flux at the regional scale (103 Mg C yr-1; over 6400 km2) was of the same magnitude as diffusive methane flux previously documented at the same scale. Organic-rich stream sediments had the highest rates of bubble release and higher enrichment of methane in bubbles, but glacial sand sediments also exhibited high bubble emissions relative to other studied environments. Our results from a database of groundwater chemistry support the hypothesis that methane in bubbles is produced in anoxic near-stream sediment porewaters, and not in deeper, oxygenated groundwaters. Methane interacts with other key elemental cycles such as nitrogen, oxygen, and sulfur, which has implications for ecosystem changes such as drought and increased nutrient loading. Our results support the contention that streams, particularly those draining wetland landscapes of the northern hemisphere, are an important component of the global methane cycle.
GHG Dataset for the frontiers publication "Soil Nitrous Oxide Emission and Methane Exchange from Diversified Cropping Systems in Pannonian Region"
<p>GHG Dataset used in the Frontiers Publication "Soil Nitrous Oxide Emission and Methane Exchange from Diversified Cropping Systems in Pannonian Region". Additionally including CO2 besides N2O and CH4. Includes 3 cropping seasons.</p> <p>The data is also available online on the GHG flux visualisation and calculation tool "gasflxvis": https://sae-interactive-data.ethz.ch/gasflxvis/</p> <p>Further details on the calulation are provided both on gasflxvis and the Frontiers publication. Calculation procedure according the following PLOS ONE publication: http://dx.doi.org/10.1371/journal.pone.0200876</p>
Emissions of nitrous oxide and methane after field application of liquid organic fertilizers and biochar
<p>This dataset corresponds to the open access article "Emissions of nitrous oxide and methane after field application of liquid organic fertilizers and biochar" published in Agriculture, Ecosystems & Environment (<a href="https://doi.org/10.1016/j.agee.2023.108642">https://doi.org/10.1016/j.agee.2023.108642</a>) funded by the Swiss Federal Offices for the Environment (BAFU), Agriculture (BLW) and Energy (BFE).</p> <p> </p> <p> </p>
Monthly methane emissions estimated with the atmospheric inversion model CarbonTracker Europe - CH4
<p>Monthly estimates of global methane emissions from CarbonTracker Europe - CH4 (CTE-CH4). CTE-CH4 is a Bayesian inversion framework based on an ensemble Kalman filter algorithm using the Eulerian global atmospheric transport model TM5. The gridded fluxes are available with a resolution of 1.0x1.0 degrees and in units of kgCH4/m2/month. The gridded flux file contains variables for posterior fluxes from soils (bio_flux_opt) and anthropogenic sources (anth_flux_opt) and the total posterior flux (total_flux_opt). Priors used: Anthropogenic: EDGAR v6, biosphere/wetlands (soils): LPX-Bern DYPTOP v1.4, Ocean: Weber et al. (2019), Biomass burning: GFED v4.1, Termites: VISIT. A more detailed setup of the inversion is documented in Erkkilä, A., Tenkanen, M., Tsuruta, A., Rautiainen, K., and Aalto, T.: Environmental and Seasonal Variability of High Latitude Methane Emissions Based on Earth Observation Data and Atmospheric Inverse Modelling, Remote Sensing, 15, https://doi.org/10.3390/rs15245719, 2023. Note: Fluxes are optimised at 1.0x1.0 degrees in northern high latitudes (USA, Canada, Europe and Russia), but are also provided here at the same resolution for other regions.</p>
Estimated individual methane emission rates for oil and gas facilities from the continental United States in 2021
<p>File containing 500 separate estimates of 673,940 individual facility-level methane emission rates for oil and gas facilities for the year 2021 in the continental United States. Each column contains one full estimate of the individual facility-level emissions, presented in units of kilograms per hour of methane per facility. The facility categories included in these estimates are production well sites, gathering and boosting compressor stations, transmission and storage compressor stations, processing plants, and flares. This data can be used to recreate the 500 emission distributions presented in Figure 3 in the following manuscript (link: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1402) which is currently under review. This dataset may be updated as the review stages progress</p>
High-resolution oil and gas methane emission inventory for the Permian Basin
<p>This dataset consists of a high-resolution (0.01<sup>o</sup> × 0.01<sup>o</sup>) oil and gas methane emission inventory for the Permian Basin, developed at Environmental Defense Fund (<a href="http://www.edf.org">www.edf.org</a>). The Permian Basin in western Texas and southern New Mexico is the largest oil producing basin in the U.S., accounting for more than 40% of national oil production in 2021. It is also the nation's largest methane emitting basin, with recent measurement-based estimates of more than three million metric tons per year. Here, we develop an improved inventory of oil and gas methane emissions for the Permian Basin, based on recent facility-scale measurements and updated oil and gas activity data for the year 2021.</p> <p>Full details for the oil and gas methane emission inventory development and key results can be found in the following journal paper, which is under review at Earth System Science Data journal.</p> <p>Please cite the paper when using the methane inventory dataset:</p> <p>Omara, M., Gautam, R., O'Brien, M.A., Himmelberger, A., Franco, A., Meisenhelder, K., Hauser, G., Lyon, D.R., Chulakadaba, A., Miller, C.C., Franklin, J., Wofsy, S., and Hamburg, S.P. Developing a spatially explicit global oil and gas infrastructure database for characterizing methane emission sources at high resolution. <em>In review</em>, Earth System Science Data journal (2023).</p> <p>Points of Contact at Environmental Defense Fund: Mark Omara (momara@edf.org) and Ritesh Gautam (rgautam@edf.org).</p>
Gridded products of global river methane concentrations, flux rates and emissions
<p><strong>Information on the products on this repository</strong></p> <p>These data is created using the R scripts with the random forest models and upscaling procedures found in: https://github.com/rocher-ros/RiverMethaneFlux.</p> <p>Raw files to reproduce this product can be found in https://doi.org/10.5281/zenodo.7733604</p> <p>The results of this analysis are published in the article "Global Methane emissions form rivers and streams" (in Nature) (https://doi.org/10.1038/s41586-023-06344-6).</p> <p>Main author is Gerard Rocher-Ros, for which correspondence can be sent to g.rocher.ros@gmail.com</p> <p>Units of the variables in the product are:<br> -River methane concentration: mmol CH4 m-3<br> -River methane diffusive flux rates: mmol CH4 m-2 d-1 (of river area)<br> -River methane diffusive emissions: Mega grams of C-CH4 (for each pixel).</p> <p>The spatial resolution of the product is 0.25 degrees (which corresponds to around 27 km). The files are in WGS84.</p> <p>There are four main products in this folder, packed as geotiff files, and described below.</p> <p>+ The file "river_methane_yearly.tiff" contains three layers:<br> - Yearly average river CH4 concentrations (ch4_conc_avg)<br> - Yearly average river CH4 diffusive flux rates (ch4_flux_avg)<br> - Yearly total river CH4 diffusive emissions (ch4_emissions_year)</p> <p>+ The file "river_methane_concs_monthly.tiff" contains twelve layers, with the modelled river methane concentrations for each month.</p> <p>+ The file "river_methane_flux_monthly.tiff" contains twelve layers, with the modelled river methane flux rates for each month.</p> <p>+ The file "river_methane_emissions_monthly.tiff" contains twelve layers, with the total river methane emissions for each month.</p>
Dataset for "Topography-based statistical modelling reveals high spatial variability and seasonal emission patches in forest floor methane flux"
<p>This dataset provides measured and upscaled forest floor methane (CH4) fluxes and soil moisture.</p> <p>This dataset is related to the following manuscript:</p> <p>Vainio et al., Topography-based statistical modelling reveals high spatial variability and seasonal emission patches in forest floor methane flux, Biogeosciences, in review. (The discussion preprint is available at https://doi.org/10.5194/bg-2020-263.)</p>
Daily European biospheric methane emissions estimated with the ecosystem model JSBACH-HIMMELI.
<p>Daily estimates of European biospheric methane emissions from JSBACH-HIMMELI model from year 1990 to year 2023. JSBACH-HIMMELI is an ecosystem process model based on JSBACH land surface model, YASSO soil carbon model and HIMMELI methane emission model. The gridded fluxes are available with a resolution of 0.1x0.1 degrees and in units of mol m-2 s-1 (m-2 refers to grid cell area). The gridded flux file contains a variable for methane fluxes, including a sum of methane fluxes from peatlands, inundated lands and mineral soils. More information of the model set-up is documented in Petrescu, A. M. R., et al., The consolidated European synthesis of CH4 and N2O emissions for the European Union and United Kingdom: 1990–2019, Earth Syst. Sci. Data, 15, 1197–1268, https://doi.org/10.5194/essd-15-1197-2023, 2023, Tyystjärvi, V., 2024. Future methane fluxes of peatlands are controlled by management practices and fluctuations in hydrological conditions due to climatic variability. EGUsphere 1–37. https://doi.org/10.5194/egusphere-2023-3037 and Raivonen, M. et al., 2017. HIMMELI v1.0: HelsinkI Model of MEthane buiLd-up and emIssion for peatlands. Geoscientific Model Development 10, 4665–4691. <a href="https://doi.org/10.5194/gmd-10-4665-2017">https://doi.org/10.5194/gmd-10-4665-2017</a></p>
Non-methane volatile organic compound emissions over China estimated using TROPOMI HCHO retrievals
<p>We used the Regional multi-Air Pollutant Assimilation System (RAPAS) with the EnKF algorithm to optimize daily NMVOC emissions in China by assimilating TROPOMI HCHO retrievals. </p><p>airqual.qc.csv includes assimilated and verified surface NO2 observations.</p><p>HCHO.tar.gz includes assimilated TROPOMI HCHO retrievals.</p><p>posterior_emission_27km.nc and posterior_emission_mg_27km.nc includes inferred daily posterior anthropogenic and biogenic NMVOC emissions respectively for August 2022.</p>
Assessment of whole-site methane emissions from anaerobic digestion plants: towards establishing emission factors for various plant configurations
<p>This dataset supplements the publication "Assessment of whole-site methane emissions from anaerobic digestion plants: towards establishing emission factors for various plant configurations" by Wechselberger et al. (2025).</p> <p>The dataset contains primary and secondary data underlying the statistical analysis and reported methane emission factors. Emission factors were calculated as described in section 2.3 of the paper. </p> <p>Available files (UTF-8 encoded):</p> <ul> <li>Data.csv (dataset)</li> <li>Glossary.csv (column/variable descriptions of dataset)</li> </ul> <p>The dataset includes plant characteristics and whole-site methane losses of 135 anaerobic digestion plants, covering normal and various other-than-normal operating conditions (155 rows). For statistical analysis, only periods during normal operation and plants with information on the analyzed emission factors and plant characteristics were considered (cf. supplementary information C of the paper). Consequently, the final dataset contained 109 anaerobic digestion plants for statistical analysis on the methane emission factor (% of methane produced) and 28 plants when analyzing the wastewater-specific emission factor (kg methane per population equivalent and year). All but one facility continuously processed feedstock without any post-rotting stages. Plant DE-MH_WP5_1 of the secondary data implemented garage digesters.</p> <p>Data from three plants were collected only after completion of statistical analyses. These data were used to compare methane losses during normal and other-than-normal operating conditions. The respective rows are marked accordingly in the dataset (column “data_collected_after_statistical_analyses”).</p> <p>Version v2 contains the final reference to the publication Wechselberger et al. (2025). The data are the same as in version v1.</p>
Methane and Carbon Dioxide Production and Emission Pathways in the Belowground and Draining Water Bodies of a Tropical Peatland Plantation Forest
<p>This is the data repository for the second version (revised) of the manuscript "Methane and Carbon Dioxide Production and Emission Pathways in the Belowground and Draining Water Bodies of a Tropical Peatland Plantation Forest<strong>"</strong> submitted to Geophysical Research Letters on 10 January 2025.</p>
The key role of production efficiency changes in livestock methane emission mitigation
<p>This dataset contains the R code, the input data, the parameters used, and the updated livestock methane emission for the period 1961-2023 using methods from Chang, J., Peng, S., Yin, Y., Ciais, P., Havlik, P., Herrero, M. (2021). The key role of production efficiency changes in livestock methane emission mitigation. AGU Advances, 2, e2021AV000391. DOI: https://doi. org/10.1029/2021AV000391 </p> <p>1. R code: Chang_et_al_Global_Livestock_CH4_Assessment_1961_2023.R<br>2. Input data and parameters: Data.zip (statistics on historical livestock numbers and production need to be downloaded from FAOSTAT (http://www.fao.org/faostat/en/)<br>3. Results on global livestock methane emissions during 1961-2023 were presented in the Global_Results.xlsx<br>4. Results on livestock methane emissions from enteric fermentation and manure management during the period 1961-2023 in each country/area were shown in the folder named Country_Results: Files are organized as "Country_[XX]CH4_[YY]_[ZZ].csv" where XX indicate emission from enteric fermentation (EF) or manure management (MM); YY indicates method used for the estimates; and ZZ indicates livestock categories.<br>5. Results on gridded livestock methane emissions at a resolution of 5 arc-min using the IPCC Mixed Tier 1 and Tier 2 (2019MT) and Tier 1 (2019T1) methods following the 2019 refinement to the 2006 IPCC guidelines for National Greenhouse Gas Inventories (Vol. 4) (IPCC, 2019): Livestock_CH4_map_5arcmin_1961_2023_2019MT_2019T1.nc4</p> <p>Please contact: Dr. Jinfeng Chang (changjf@zju.edu.cn) for any question on the dataset.</p>
A high-resolution gridded inventory of coal mine methane emissions for India and Australia
<p>The dataset contains the high-resolution gridded coal mine methane emissions file (.csv) for India and Australia. The emissions are estimated for the year 2018 at a resolution of 0.1° × 0.1°. The emission unit is ton/grid/year.</p>
Dataset - Controlled release experiment to investigate uncertainties in UAV-based emission quantification for methane point sources
<p>This dataset was created by Randulph Morales (randulph.morales@empa.ch) and was used for Morales et al. (2021) AMT publication (amt-2021-314). A short description of the files is written in <strong>readme.txt</strong></p> <p>The dataset contains:</p> <ul> <li>QCLAS methane measurement</li> <li>Active AirCore methane measurement</li> <li>Meteorology files</li> </ul>
Data supporting "Solar radiation drives methane emissions from the shoots of Scots pine"
<p>Data supporting our New Phytologist publication "Solar radiation drives methane emissions from the shoots of Scots pine". </p>
Estimating drivers and pathways for hydroelectric reservoir methane emissions using a new mechanistic model (estimated methane emissions for hydropower reservoir surfaces and potential dam emissions)
<p>Methane emissions data from hydropower reservoir surfaces and dams, as estimated with the ResME model. Emissions estimates available for hydropower reservoirs in the GRanD database (Lehner et al., 2011). </p> <p> </p> <p>References:</p> <p>Lehner, B., Liermann, C. Reidy, Revenga, C., Vörösmarty, C., Fekete, B., Crouzet, P., Döll, P., Endejan, M., Frenken, K., Magome, J., Nilsson, C., Robertson, J.C., Rodel, R., Sindorf, N., and Wisser, D. (2011). High-resolution mapping of the world’s reservoirs and dams for sustainable river-flow management. Frontiers in Ecology and the Environment, 9 (9): 494-502. https://doi.org/10.1890/100125.</p>
Paddy rice methane emissions across Monsoon Asia
<p>Although rice cultivation is one of the most important agricultural sources of methane and contributes ~8 % of total global anthropogenic emissions, large discrepancies remain among estimates of global methane emissions from rice cultivation due to a lack of observational constraints. The spatial distribution of paddy-rice emissions has been assessed at regional-to-global scales by bottom-up inventories and land surface models over coarse spatial resolution (e.g., > 0.5 degrees) or spatial units (e.g., agro-ecological zones). However, high-resolution CH4 flux estimates capable of capturing the effects of local climate and management practices on emissions, as well as replicating in situ data, remain challenging to produce because of the scarcity of high-resolution maps of paddy-rice and insufficient understanding of CH4 predictors. Here, we combined paddy-rice methane-flux data from 23 global eddy covariance sites and MODIS remote sensing data with machine learning, and produced gridded up-scaling estimates of rice methane emissions at 5000-m resolution at 8-day intervals across Monsoon Asia, where ~87% of global rice area is cultivated and ~90% of global rice production occurs.<br> </p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.