Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
118
datasets available to search
ShareScore release 0.9.0
Dataset results
118 results for “gases”
Geogenic Gases in a Red Wood-Ant Nest and Soil in the Neuwied Basin, Germany 2016
Geochemical tracers of crustal fluids (CO2, He, Rn) provide a useful tool for the identification of buried fault structures. We acquired geochemical data during 7 months of continual sampling to identify causal processes underlying correlations between ambient air and degassing patterns of three gases (CO2, He, Rn) in a nest of red wood ants (Formica polyctena; “RWA”) and the soil at Goloring in the Neuwied Basin, a part of the East Eifel Volcanic Field (EEVF). We explored whether temporal relations and degassing rhythms in soil and nest gas concentrations could be indicators of hidden faults through which the gases migrate to the surface from depth. In nest gas, the coupled system of CO2-He and He concentrations exceeding atmospheric standards 2-3 fold suggested that RWA nests may be biological indicators of hidden degassing faults and fractures at small scales. Equivalently periodic degassing infradian rhythms in the RWA nest, soil, and three nearby mineral springs suggested NW-SE and NE-SW tectonic linkages. Because volcanic activity in the EEVF is dormant, more detailed information on the EEVF’s tectonic, magmatic, and degassing systems and its active tectonic fault zones are needed. Such data could provide additional insights into earthquake processes that are related to magmatic processes at the lower crust.
Data associated with the FLooded Upland Dynamics EXperiment (FLUDEX), conducted at the IISD Experimental Lakes Area 1997 to 2003, investigating reservoir flooding impacts on ecosystems, particularly the release of mercury and greenhouse gases.
The data included in this repository were collected over the course of the FLooded Upland Dynamics Experiment (FLUDEX) conducted at the IISD Experimental Lakes Area (IISD-ELA) from 1997 to 2003. A plethora of data was collected over five years of flooding three upland reservoir sites, in order to examine the relationship between the amount of flooded, and thus decomposed, terrestrial organic matter and the production of methylmercury (MeHg), total mercury (THg), and greenhouse gases (GHGs) in the reservoirs. Findings from this experiment suggest that the amount of organic carbon stored in a flooded site does not directly influence the amount of THg, MeHg, and GHGs produced, but it does affect the persistence of mercury in the reservoir and food web. This version of the repository contains data collected on water chemistry, benthic invertebrate (chironomid) emergence, mercury and methylmercury concentrations in the water and food web, stable isotopes of carbon and nitrogen in emerging insects and zooplankton, and abundance and biomass of zooplankton, phytoplankton, and bacteria. This data package contains only some of the data from the FLUDEX project. IISD-ELA hopes to add more data in subsequent versions.
Particle concentration data from: Long-term measurement of sub-3nm particles and their precursor gases in the boreal forest
<p>The knowledge of the dynamics of sub-3nm particles in the atmosphere is crucial for our understanding of first steps of atmospheric new particle formation. Therefore, accurate and stable long-term measurements of the smallest atmospheric particles are needed. In this study, we analyzed over five years of particle concentrations in size classes 1.1–1.7 nm and 1.7–2.5 nm obtained with the Particle Size Magnifier (PSM) and three years of precursor vapor concentrations measured with the Chemical Ionization Atmospheric Pressure Interface Time-of-Flight mass spectrometer (CI-APi-ToF) at the SMEAR II station in Hyytiälä, Finland. The results show that the 1.1–1.7 nm particle concentrations have a daytime maximum during all seasons, which is due to increased photochemical activity. There are significant seasonal differences in median concentrations of 1.7–2.5 nm particles, underlining the different frequency of new particle formation between seasons. Aerosol precursor vapors have notable diurnal and seasonal differences as well. Sulfuric acid and highly oxygenated organic molecule (HOM) monomer concentrations have clear daytime maxima, while HOM dimers have their maxima during the night. HOM concentrations for both monomers and dimers are the highest during summer and the lowest during winter. Higher median concentrations during summer result from increased biogenic activity in the surrounding forest. Sulfuric acid concentrations are the highest during spring and summer, with autumn and winter concentrations being two to three times lower. A correlation analysis between the sub-3nm concentrations and aerosol precursor vapor concentrations indicates that HOMs, particularly their dimers, and sulfuric acid play a significant role in new particle formation in the boreal forest. Our analysis also suggests that there might be seasonal differences in new particle formation pathways that need to be investigated further. </p> <p> </p>
Dissolved greenhouse gas concentrations derived from the NEON dissolved gases in surface water data product (DP1.20097.001)
This dataset contains partial pressure and molar concentration of dissolved carbon dioxide, methane, and nitrous oxide in 34 streams, rivers, and lakes calculated from headspace equilibration samples collected by the National Ecological Observatory Network (NEON). All input data were collected by NEON and is available on the NEON data portal at https://data.neonscience.org. Specifically, in situ dissolved gas concentrations were calculated from the air and headspace mixing ratios provided by the NEON Dissolved gases in surface water data product (DP1.20097.001), adjusted for sample and water temperature (DP1.20097.001, DP1.20264.001, DP1.20053.001), barometric pressure (DP1.20097.001, DP1.00004.001), and alkalinity (DP1.20093.001). The final set of inputs is found in the file, input_file, and the processing scripts are available at https://github.com/kellyaho/NEON-GHG-processing. The file, output_file, contains the raw outputs from running the input_file through the processing scripts. There are three outputs for each gas for each sample, one for each of three different pre-equilibration headspace mixing ratios (paired atmospheric samples, loess smoothing of atmospheric samples, and site-specific median). The file, GHG_final, contains the final dataset. This GHG_final uses the outputs from output_file calculated with paired atmospheric samples, and substitutes 0.01 μatm, 0.001 μM, 0.001 μatm, and 0.001 μM for any negative instances of pCH4, [CH4], pN2O, and [N2O], respectively. See methods for more detail. Please cite the NEON data inputs (listed below), in addition to this dataset, when using the data. NEON is sponsored by the National Science Foundation (NSF) and operated under cooperative agreement by Battelle. This material is based in part upon work supported by NSF through the NEON Program.
MAR2PROTECT - Coconut shell derived activated carbon for effective separation of greenhouse gases - DATASET
<p>The need for innovative and efficient adsorptive materials with enhanced structural characteristics that facilitate the selective capture of greenhouse gases (GHGs) is critical. Porosity and surface area play an important role in the adsorptive capture and separation of GHGs, enabling the design of processes that reduce GHGs emissions. This study shows how residual coconut shell (CS) biomass can be reused for the design of novel biomaterials (CS-CO<sub>2</sub>, CS-ZnCl<sub>2</sub>) with structural characteristics that promote the selective adsorption of GHGs. Additionally, the results are compared with those obtained with activated carbon monoliths (ACM) and a Metal-Organic Framework (MOF Fe-BTC) to understand the impact of different porous solid matrices on adsorptive GHG capture. In this context, the adsorption performance of difluoromethane (R-32), pentafluoroethane (R-125), 1,1,1,1-tetrafluoroethane (R-134a), 1,1,1,1-trifluoroethane (R-143a), carbon dioxide (CO<sub>2</sub>), and methane (CH<sub>4</sub>) on CS-CO<sub>2</sub>, CS-ZnCl<sub>2</sub>, ACM and Fe-BTC were measured by gravimetry at 283.15 K, 303.15 K and 323.15 K. The experimental data are correlated using the dual-site Langmuir adsorption model, and the selectivities of the commercial mixtures R-410A, R-407C, R-404A and CO<sub>2</sub>/CH<sub>4</sub> are calculated using the Ideal Adsorption Solution theory (IAST). CS-ZnCl<sub>2</sub> has a higher selectivity for R-125 over R-32 in the separation of R-410A at low pressure, and also a higher selectivity for R-407C due to its larger pore volume. In the separation of the R-404A refrigerant blend, CS-CO<sub>2</sub> adsorbs predominantly R-134a and R-143a over R-125. Finally, the ACM material preferentially adsorbs CO<sub>2</sub> over CH<sub>4</sub>, owing to its large and elongated micropores that favour the adsorption of the smaller molecule. This study introduces novel and innovative materials to enhance the separation of GHGs mixtures, contributing to a reduction in their emissions.</p>
various ZIF modifications and diffusivities of various gases
<p>A dataset that includes ZIFs where their sub-units are varied, along with molecular dynamics simulation results for: the aperture size of each ZIF, the stretched aperture when a gas lies in its center, and diffusivities for each gas molecule.</p> <p>The modifications are in the form of replacement for the metal center, organic linker and the functional group. The gas molecules are: He, H2, O2, CO2, N2, CH4, C2H4, C2H6, C3H6, C3H8, n-C4H10, iso-C4H10.</p> <p>The dataset is used in Machine Learning routing, to find the structure modification-gas diffusivity correlation.</p>
Emissions Database for Global Atmospheric Research, version v4.3.2 part I Greenhouse gases
<p>The Emissions Database for Global Atmospheric Research (EDGAR) v4.3.2, partim Greenhouse gases compiles anthropogenic emissions data for CO2, CH4 and N2O based on international statistics and emission factors. The version v4.3.2 of the EDGAR emission inventory provides global estimates, broken down to IPCC-relevant source-sector levels, from 1970 (the year of EU’s first Air Quality Directive) to 2012 (the end year of the first commitment period of the Kyoto Protocol (KP)). Strengths of EDGAR v4.3.2 include global geo-coverage (226 countries), continuity in time, and comprehensiveness in activities. Emission sources of the multiple gases include all human activities except the land-use, land-use change and forestry sector and are compiled following a bottom-up and IPCC-compliant approach. The dataset provides in addition to the complete timeseries 1970-2012 also annual and global gridmaps of 0.1 degree by 0.1 degree resolution for each source-sector and each year. For 2010 also 12 monthly gridmaps per source-sector are provided.</p>
Test dataset for "Steam condensation scaled experiment in the presence of non-condensable gases for small modular reactor containment passive safety"
<p>This study presents scaled experiments using steam condensation with non-condensable gas (NCG)—helium (He), simulating hydrogen, and nitrogen (N<sub>2</sub>)—as these experiments are pivotal for water-cooled reactor passive containment cooling system (PCCS) design and analysis. Research into PCCSs for small modular reactors (SMRs) is especially important in light of SMR system design; however, studies in the literature reflect limitations due to test geometry and operational condition variations, without considering SMR prototypic design. To address these challenges, a scaled test facility was developed to accurately replicate SMR PCCSs. This facility includes vertical down-flow condensing test sections with 1-, 2-, and 4-in.-diameter condensing tubes, accompanied by annular water cooling. Experiments were conducted using both superheated and saturated steam, with steam mass flow rates in the presence of NCG varying from: (a) 55 to 66 kg/hr. of steam, and 1.8 to 22 kg/hr. of He (as the NCG); (b) 58 to 63 kg/hr. of steam, and 4.4 to 13.3 kg/hr. of N<sub>2</sub> (as the NCG). Test data were collected on (a) the axial temperatures of the annular cooling water; (b) the outer wall temperature of the condensers; and (c) the mass flow rate, temperature, and pressure at the test section inlets and outlets. These primary test data were used in conjunction with a standard data reduction methodology to estimate essential thermal parameters such as heat fluxes, heat transfer coefficients, and condensation rates. The effects of NCGs on steam condensation within the geometry of the scaled test sections were then presented in regard to various testing conditions.</p>
Canopy Trimming Experiment (CTE) trace gases
This data set provides the monthly trace effluxes measured across the soil-atmosphere interface from five soil surface chambers in all the CTE plots. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
Anthropogenic emissions of CH4, N2O, F-gases and BC from GAINS, for EU-countries plus CH, NO, UK developed under the EYE-CLIMA project - March 2025 update
<p><span>As part of the EYE-CLIMA project, GAINS emission data for CH<sub>4</sub>, N<sub>2</sub>O, BC and selected F-gases (HFC-125, HFC-134a, HFC-143a, HFC-23, HFC-32 and SF<sub>6</sub></span>) were released for all EU-27 countries plus UK, Switzerland, and Norway for the period 1990 to 2020 (with exception of F-gases, from 2005 only, and BC/CH<sub>4</sub> emissions from agricultural waste burning, from 2000). Results have been documented in EYE-CLIMA deliverable D2.8 (<a href="http://folk.nilu.no/~rthompson/eyeclima_reports/EYECLIMA_D2.8.pdf">http://folk.nilu.no/~rthompson/eyeclima_reports/EYECLIMA_D2.8.pdf</a>), and they are publicly available at the Zenodo repository under <a href="https://doi.org/10.5281/zenodo.11032177">https://doi.org/10.5281/zenodo.11032177</a>. All data is available on a 0.1°x0.1° grid and in monthly resolution. Emissions are attributed to the respective source categories according to GNFR.</p> <p>The motivation of an update resulted from the need to extending the emission data time series to 2023. With underlying statistics and national emission data currently available till 2022 only (the latter submitted to UNFCCC only by December 2024), the historical data series also could only be established for 2022. Here we use the GAINS scenario feature to extrapolate between 2022 historical data and the first scenario point, 2025 which is based on IEA’s Word Energy Outlook 2023 (https://www.iea.org/reports/world-energy-outlook-2023). Obviously, this also means that emission results for 2023 are not any more based on robust statistics but represent an extrapolation.</p> <p>Extrapolation of spatially explicit data is only possible when the spatial resolution conveys a realistic signal. For the sector “agricultural waste burning” (files with “AWB” as sector, see notation below) spatial allocation is based on actual observation from satellites. As such data products on agricultural fires have been made available until 2022 only, no spatial or temporal signal exists for 2023. The time series provided thus has to end in 2022. No recommendation can be given to modellers, other than to either use 2022 also for 2023 (understanding that the pattern will be strikingly different) or to use a five-year average (which will remove a lot of spatial specificity).</p> <p>The updated dataset covers files as follows (internally, all files now carry version number V05):</p> <p>ALL_FLUX_ALL_EUR_MOD_MONTH_19900101_20231231_GAINS_IIASA_V05.csv</p> <p>BC_FLUX_ALL_EUR_MOD_MONTH_19900101_20231231_GAINS_IIASA_V05.nc</p> <p>BC_FLUX_AWB_EUR_MOD_MONTH_20000101_20221231_GAINS_IIASA_V05.nc</p> <p>CH4_FLUX_ALL_EUR_MOD_MONTH_19900101_20231231_GAINS_IIASA_V05.nc</p> <p>CH4_FLUX_AWB_EUR_MOD_MONTH_20000101_20221231_GAINS_IIASA_V05.nc</p> <p>HFC_FLUX_ALL_EUR_MOD_YEAR_20050101_20231231_GAINS_IIASA_V05.nc</p> <p>N2O_FLUX_ALL_EUR_MOD_MONTH_19900101_20231231_GAINS_IIASA_V05.nc</p> <p>SF6_FLUX_ALL_EUR_MOD_YEAR_20050101_20231231_GAINS_IIASA_V05.nc</p> <p>This is version 2.0 of the dataset. It extends from version 1.0 by covering into the year 2023, but also benefits from a number of additional GAINS improvements. Emissions of emitted compounds are provided as kg/m²/s. File names follow the notation developed for the H-Europe project EYE-CLIMA, i.e. species _ variable-type _ sector _ region _ method (MOD=model) _ timestep _ fromTime _ toTime _ model _ institute _ version . filetype.</p> <p>This version is available at <a href="https://doi.org/10.5281/zenodo.15536170">https://doi.org/10.5281/zenodo.15536170</a>. The generic address of the dataset is <a href="https://doi.org/10.5281/zenodo.10886780">https://doi.org/10.5281/zenodo.10886780</a>, resolving to the latest update available at Zenodo. No further updates are planned in EYE-CLIMA, so this version is expected to also reflect the final update within the project.</p> <p>Compared to version 1.0, GAINS benefitted from a number of new developments such as the following:</p> <p>*) Previously, GAINS has been available in five-year timesteps only (with the aim of allowing for scenarios at that resolution). For data version 1.0, a makeshift solution was found to convert into annual data. A recent update now allows, for historic data, to store and retrieve information on an annual basis (from 1990).</p> <p>*) The energy data were obtained from IEA’s world energy balances 2024 (July version, https://www.iea.org/data-and-statistics/data-product/world-energy-balances#documentation), extending into 2022 and extrapolated towards 2025, downscaled from IEA to GAINS sectors and sub-sectors. Additionally, the annual activity of industrial production is estimated using a linear approach, based on five-year timestep data.</p> <p>*) Agricultural statistics were retrieved from Eurostat (and from FAO globally) and extended to 2022, extrapolated towards 2025.</p> <p>*) Interpretation of GAINS data was reconfirmed and updated in consultations with national experts of multiple EU countries. While the process resulted in revised emission projections to be used in the Clean Air Outlook 4 (see <a title="Protected by Check Point: https://environment.ec.europa.eu/topics/air/clean-air-outlook_en" href="https://protect.checkpoint.com/v2/r02/___https:/environment.ec.europa.eu/topics/air/clean-air-outlook_en___.YzJlOmlpYXNhOmM6bzoyYzdiNDRhNDI4Njc3ZjI5MGFjMTU1N2I2OWVmNzM2ZTo3OjE5OTM6ZTFiY2IzMDMxZGViNGE0MjI0ODRmNWQ4NzA3ZDY3Njc4M2U2NzUxNmEwNzQ0ODViNDBhODc1NmNhZmMzY2FlMjpoOkY6Tg"><span lang="EN-GB">https://environment.ec.europa.eu/topics/air/clean-air-outlook_en</span></a><span lang="EN-GB">). While the details of improvements on the individual aspects cannot be disclosed, they are useful to describe historic data most adequately, and have been integrated also in this assessment. That not only leads to changes in absolute emissions for a given year, but also affects trends that now are more plausible and confirmed through the exchange with the national experts.</span></p> <p><span lang="EN-GB">*) Technical adjustments have improved the precision of temporal allocation of emissions and the conversion of grid sizes to actual area.</span></p>
Dataset of publication "Investigation of the discharge coefficient in the laminar boundary layer regime of critical flow Venturi nozzles calibrated with different gases including hydrogen"
<p>The attached files contain experimental raw data and fluid properties for the nozzles 1 and 2 mentioned in the paper. The data in the attached files can be used to calculate the Cd values published in the paper.</p>
Paleoclimate signals and groundwater age distributions from 39 public water works in the Netherlands; insights from noble gases and carbon, hydrogen and oxygen isotope tracers [Data set].
<p>Data set covering the meta data of the 39 well fields, the macro chemistry data and the data of the noble gases and carbon, hydrogen and oxygen isotope tracers used for assessing the paleoclimate signals and age distributions in the publication in Water Resources Research (2021)</p> <p><strong>Paleoclimate signals and groundwater age distributions from 39 public water works in the Netherlands; insights from noble gases and carbon, hydrogen and oxygen isotope tracers</strong></p> <p>Hans Peter Broers, Jürgen Sültenfuß<sup> </sup>, Werner Aeschbach, Arne Kersting,, Armin Menkovich, Jasperien de Weert and Jeroen Castelijns</p>
Observations of trace gases in the lowermost stratosphere and upper troposphere from the SPURT aircraft measurement program
<p><strong>Introduction</strong></p> <p>SPURT (Spurenstofftransport in der Tropopausenregion, trace gas transport in the tropopause region) was an aircraft measurement program funded by the AFO 2000 programme of the German Ministry for Education and Research (BMBF). Eight campaigns (36 flights in total) were conducted between November 2001 and July 2003 to investigate trace gas transport in the extratropical upper troposphere and lowermost stratosphere in all seasons. A wide range of trace gases with different lifetimes and sink/source characteristics were measured in-situ from a Learjet 35A aircraft flying at altitudes up to 13.7 km. The data set is well suited for studies of atmospheric transport, for model validation, and for investigations of seasonal changes in the upper troposphere and lowermost stratosphere as demonstrated in numerous accompanying studies.</p> <p><strong>Dataset content</strong></p> <ol> <li>In-situ measurements of N<sub>2</sub>O, CH<sub>4</sub>, CO, CO<sub>2</sub>, CFC12, H<sub>2</sub>, SF<sub>6</sub>, NO, NO<sub>y</sub>, O<sub>3</sub> and H<sub>2</sub>O along all flight tracks.</li> <li>Position and meteorological quantities recorded by the aircraft along all flight tracks.</li> <li>Meteorological data from ECMWF analysis fields and derived products such as potential vorticity and equivalent latitude interpolated to all flight tracks.</li> <li>Merge files (extension .mrg) of all observations, aircraft positions and other data merged into one single file per flight at 5 sec temporal resolution. Due to different instrument response times or computer clocks, the individual measurements were typically shifted by several seconds relative to each other. These time shifts are corrected for in the merge files.</li> <li>Ten day backward trajectories started every 12 minutes along the flight tracks computed with <em>Lagranto</em> (<a href="https://dx.doi.org/10.5194/gmd-8-2569-2015">doi:10.5194/gmd-8-2569-2015</a>) based on 3-hourly ECMWF IFS analysis/forecast fields.</li> <li>Further information such as flight quicklooks, flight protocols, meteorological reports, etc.</li> </ol> <p>All measurement data are provided in NASA/Ames format (<a href="https://espo.nasa.gov/content/Ames_Format_Specification_v20">https://espo.nasa.gov/content/Ames_Format_Specification_v20</a>), which is a self-explaining ASCII format that can conveniently be read by many software packages, e.g. the nappy library for python.</p> <p><strong>Quick start guide</strong></p> <ol> <li>Download and unpack the gzip compressed tar file (unpacking generates the two directories <em>images </em>and <em>data</em>)</li> <li>Change to the directory <em>data </em>and open the file index.html with a web browser. This will open a web page providing an overview of the eight campaigns and associated data.</li> <li>For most purposes it will be sufficient to work with the merge files: Change to the <em>data</em> directory and list all merge files by typing "ls */*/*.mrg" (Linux) or "dir *\*\*.mrg" (Windows).</li> </ol> <p> </p> <p><strong>References:</strong></p> <p>The reference journal article for the SPURT project is</p> <p><em>Engel, A., Bönisch, H., Brunner, D., Fischer, H., Franke, H., Günther, G., Gurk, C., Hegglin, M., Hoor, P., Königstedt, R., Krebsbach, M., Maser, R., Parchatka, U., Peter, T., Schell, D., Schiller, C., Schmidt, U., Spelten, N., Szabo, T., Weers, U., Wernli, H., Wetter, T., and Wirth, V.: Highly resolved observations of trace gases in the lowermost stratosphere and upper troposphere from the Spurt project: an overview, Atmos. Chem. Phys., 6, 283–301, https://doi.org/10.5194/acp-6-283-2006, 2006. </em></p> <p>Many more scientific publications emerged from the project (see reference list and object identifiers).</p>
Zonal mean of atmospheric water vapour and water vapour perturbation by emitted trace gases of hypersonic aircraft
<p>This short movie (no sound) shows two figures with time steps of five days over a period of fourteen years (2000-2014). On the left the atmospheric mixing ratio of water vapour is presented in parts per million. On the right the perturbation of stratospheric water vapour is depicted in parts per million. The perturbation is created by emitted water vapour of hypersonic aircraft flying at high altitudes (35 km). Over the years the accumulation of water vapour up to equilibrium is shown.</p>
Dataset from "Quantifying air-sea gas exchange using noble gases in a coastal upwelling zone"
<p>Dataset of dissolved noble gas (He, Ne, Ar, Kr, and Xe) measurements in Monterey Bay, CA. Published as a supplement to: Manning, C.C., R.H.R. Stanley, D.P. Nicholson, and M.E. Squibb (2016). Quantifying air-sea gas exchange using noble gases in a coastal upwelling zone. <em>IOP Conference Series: Earth and Environmental Science</em>, 35, 012017 (13 pp). doi: 10.1088/1755-1315/35/1/012017</p>
Beating-free quantum oscillations in 2D electron gases with strong spin-orbit and Zeeman interactions
<p>Datafiles for figures in the paper:</p> <p><em>"Beating-free quantum oscillations in 2D electron gases with strong spin-orbit and Zeeman interactions"</em>, Phys. Rev. Research [<em>Accepted</em>]</p> <p>The datafiles relate to Figs. 2, 3, 10, 12, 14, 15, 16, and 17</p> <p>Figs. 1 and 13 contain schematics.</p> <p>Figs, 4, 6, and 8 are generated in a straightforwd manner using Eqs. (27), (34), and (40), respectively, using parameter values supplied in the figure captions.</p> <p>Fig. 5, is generated by Eq. (30) along with Eq. (29), using parameter values supplied in the figure captions.</p> <p>Fig. 7, is generated by Eq. (30) along with Eqs. (35) and (36), using parameter values supplied in the figure captions.</p> <p>Fig. 9, is generated by Eq. (30) along with Eqs. (41) and (42), using parameter values supplied in the figure captions.</p>
Data related to "Emissions of atmospherically reactive gases nitrous acid and nitric oxide from arctic permafrost peatlands"
<p>The data file contains the individual (each replicate) values of the soil variables and gas fluxes obtained from the study. It contains data shown in the both main text and supplementary files. </p>
Emission factors of trace gases and aerosols from wildfire events in central Portugal
<p>The aim of this data set is to provide a comprehensive overview of the chemical composition (trace elements, water-soluble ions and organic compounds) in smoke aerosol particles from some representative wildfires for use in emission inventorying and source apportionment modelling. </p> <p> </p>
MAR2PROTECT Biomass-derived Carbons for the Separation of Fluorinated Gases DATASET
<p>Fluorinated gases (F-gases) are widely used in the refrigeration industry and air conditioning equipment, being used as substitutes for ozone-depleting substances, since these compounds do not damage the atmospheric ozone layer, are non-toxic, and are not flammable. However, F-gases have high global warming potential, up to 23 000 times greater than carbon dioxide, and their atmospheric lifetime is up to 50 000 years. Then, small atmospheric concentrations of these gases can have large effects on global temperatures and on climate change. Hence, different legislations aim to combat their effect on the atmosphere, such as the EU regulation (No 517/2014) that targets to cut the emissions of these gases by 2/3 by 2030, compared to the levels of 2014. The aim of this work is to design, test, and validate climate-friendly processes, based on different Key Enabling Technologies (KETs), to separate and recover F-gases. These KETs are based on more efficient treatment systems, designed according to the principles of green chemistry, for the separation of the F-gases most used in air conditioning, commercial refrigeration, electrical circuit industry, thermal insulators, and electronic semiconductors at European level: R-134a - 1,1,1,2-tetrafluoroethane, R-32 – difluoromethane, R-125 – pentafluoroethane, SF<sub>6</sub> – sulfur hexafluoride ) and nitrogen (N<sub>2</sub>). In this work, the adsorption of these gases was studied on 4 different biocarbons (CC-1:3H<sub>3</sub>PO<sub>4</sub>, CC-1:1H<sub>3</sub>PO<sub>4</sub>, CC-K<sub>2</sub>CO<sub>3</sub> and CC-CO<sub>2</sub>). Then, this work contributes to reduce the environmental impact of these powerful greenhouse gases, answering one of the greatest current concerns of society, the environment, one central goal of EU Research.</p>
Model output files for Ou et al. 2021 (Deep Mitigation of CO2 and non-CO2 Greenhouse Gases towards 1.5°C and 2°C Futures)
<p>GCAM model output files used to reproduce Ou et al. (Deep Mitigation of CO<sub>2</sub> and non-CO<sub>2</sub> Greenhouse Gases towards 1.5°C and 2°C Futures)</p>
ScienceDex guides
Understand access before you commit
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)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.