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.
38
datasets available to search
ShareScore release 0.9.0
Dataset results
38 results for “CO2 Removal”
Dataset for article Rodriguez et al "Assessing global urban CO2 removal"
<p>This is a complementary dataset associated with the following publication: Rodriguez et al. "Assessing global urban CO2 removal" <em>Nature Cities.</em></p>
Scenario data, model source code and plotting routine for manuscript: Separating CO2 emission from removal targets comes with limited cost impacts
<p>This data archive contains REMIND model setup, results data and data analysis files for manuscript:<br><strong>Separating CO2 emission reduction from removal targets comes with limited cost impact.<br><br>plotting</strong>(directory) contains results data, manuscript specific data analysis and plotting routine scripts used to generate the figures of the manuscript.<br><strong>remind</strong>(directory) contains REMIND model source code and scenario set-up. Detailed scenario configurations are set in remind/config/scenario_config_SepMark.csv.<br><strong>remind2</strong>(directory) contains the slightly modified R-library package used for post-processing of REMIND output.<br><br>AMENDMENT<br><strong>Plots_SeparateMarkets_afterReviewProcess.Rmd</strong> After the review process, the new plotting script was added including the additional figures in the Supplementary Material. This file should replace the previous R-markdown file SepMark_essential/plotting/Plots_SeparateMarkets.Rmd.</p>
Wastewater alkalinity addition enhancement for carbon emission reduction and marine CO2 removal
<p>The ROMS_RCA model settings of 2010 runs. The reference date of the 'TIME' variable is 1983-01-01.</p> <p>The files with 'Y2010_' in their names contain the boundary data and initial fileds for the model run. The file "ROMSeutro_1strun.inp" lists all the model parameters, while the files with 'CPB_WWTP_ps' in the names are the settings of the discharges from each WWTP outlet. </p> <p>The data used to generate the figures are provided in the MAT file.</p>
Feasibility of CO2 Pipeline Construction to Enable Gigaton-Scale Carbon Dioxide Removals: Evidence from historical precedent
<p>Various quantitative and qualitative data on the history, present status, and future projections of CO2 pipelines, as well as historical data and historical timelines of oil and gas pipelines to inform the potential future upscaling of CO2 pipelines.</p>
LULC input and CLM5 carbon output "Chemistry-albedo feedbacks offset up to a third of forestation's CO2 removal benefits."
<p>Land use land cover (LULC) files for the CESM and UKESM simulations performed for the study "Chemistry-albedo feedbacks from reforestation reduce climate benefits and crop yields. The input data was processed to make it compatible for UKESM as described in Weber et al (2022) https://doi.org/10.5194/egusphere-2022-748.</p>
Soil, litter and vegetation carbon for the 6 simulations performed in CLM5 of "Chemistry-albedo feedbacks offset up to a third of forestation's CO2 removal benef"
<p>Soil, litter and vegetation carbon for the 6 simulations performed in CLM5 (Table S1) of "Chemistry-albedo feedbacks from reforestation reduce climate benefits and crop yields"</p> <p>i.clm5.global_MF_SSP1.h1.2015-2100_zip.nc - SSP126_MF_Land</p> <p>i.clm5.global_SSP1_nolulcc.clm2.h1.2015-2100_zip.nc - SSP126_2015_Land </p> <p>i.clm5.global_SSP1.h1.2015-2100_zip.nc - SSP126_Land</p> <p>i.clm5.global_MF_SSP3.02.h1.2015-2100_zip.nc - SSP370_MF_Land</p> <p>i.clm5.global_SSP3.02.h1.2015-2100_zip.nc - SSP370_Land</p> <p>i.clm5.global_SSP3_nolulcc.clm2.h1.2015-2100_zip.nc - SSP370_2015_Land</p> <p> </p> <p>These simulations were performed by Dr James King, University of Sheffield.</p> <p> </p>
UKESM1 Data accompanying "Chemistry-albedo feedbacks offset up to a third of forestation's CO2 removal benefit"
<p>UKESM1 Data accompanying "Chemistry-albedo feedbacks from reforestation reduce climate benefits and crop yields".</p> <p>The UKESM1_README provides an explanation of the diagnostics.</p> <p>These simulations were performed by Dr James Weber, University of Sheffield.</p> <p> </p>
CESM2 Data accompanying "Chemistry-albedo feedbacks offset up to a third of forestation's CO2 removal benefits."
<p>CESM2 Data accompanying "Chemistry-albedo feedbacks from reforestation reduce climate benefits and crop yields".</p> <p>The CESM2_README provides an explanation of the diagnostics.</p> <p>These simulations were performed by Dr James King, University of Sheffield.</p>
Additional data supporting "Chemistry-albedo feedbacks offset up to a third of forestation's CO2 removal benefits."
<p>Additional data for study "Chemistry-albedo feedbacks offset up to a third of forestation’s CO2 removal benefits". UKESM data is prefixed with "UKESM_" and CESM data starts with "CAM-Chem_". Please see READMEs for additional details on the UKESM and CESM data.</p> <p> </p> <p> </p>
Effects of Trunk Postural Change on CO2 Removal Efficiency in ARDS Patients: Quasi-experimental Study
ClinicalTrials.gov study NCT05281536. IPD Sharing: NO. Countries: 1. Publications: 4.
Demand-side flexibility enables cost savings in a Reversible pH-swing electrochemical process for Oceanic Co2 Removal
<p>Raw datasets and codes used in our manuscript of the same title. Figure numbers correspond with the figure numbers in the manuscript.</p> <p><strong>Figure 2: </strong>Process Overview(a) Steps of the proposed, reversible, oceanic CDR process, starting with acidification of the ocean water, followed by vacuum stripping of the CO2, basification of the oceanwater, and return to the ocean to equilibrate with the atmosphere. (b) Corresponding effects on pH and dissolved inorganic carbon (DIC) at each step in the oceanic CDR process. Oceanwater pH decreases from 8.1 during acidification to produce a shift in speciation from HCO3 todissolved CO2, which is phase-separated between step 2-3 to capture pure CO2 which decreases the DIC. Basification negates these changes through the addition of the same concentration of OH− ions as H+ ions added to ocean water during acidification, resulting in pH > 8.1 at the end of basification. CO2-starved ocean water will re-equilibrate with the atmosphere and get buffered back to a neutral-pH to re-enter acidification and the cycle continues.</p> <div> <div> <div> <div> <div> <div> <div> <div> <div> <div> <div> <div><strong>Figure 3:</strong> Predicted Performance from 0-D Equivalent Circuit Modeling (Sec. Prediction of current-volatge behavior) for (a,c) acidification and (b,d) basification to determine (a,b) polarization behavior and (c,d) Faradaic efficiencies; including (c) power density produced during acidification.<br>Different mass-transfer conditions and therefore limiting currents are modeled by varying the liquid-side boundary layer thicknesses, (δl). Two different pH-shift conditions are modeled for the low and high pH values at the end of acidification and basification, that are respectively constrained by the concentration of H+ and OH− additions to be equal during both steps – (pHlow, pHhigh): (4,10.7) and (6,9) as described in Sec. S3. Baseline parameter values listed in Table S1 are used in the equivalent circuit models with consideration of desired and competing reactions. Note the differences in the current and potential ranges plotted between (a) acidification and (b) basification steps.</div> <div> </div> <div><strong>Figure 4: </strong>Energy Intensity Comparisons (a-c) Predictions for electrochemical energy intensity normalized by the amount of CO2 captured (Eq. (14)) in (GJ/tCO2 ) as a function of the current density when jbase = jacid (a) without and (b) with competing reactions modeled. Dashed lines on the plot indicates a baseline cell resistance of 2.18 Ω cm2 and the shaded areas are indica-tive of this ohmic resistance in the range of 0 - 5 Ω cm2; the shades of blue are indicative of theliquid-side boundary layer thicknesses, δl, modeled. Electrochemical energy intensities from (a)and (b) where δl = 50 μm are shown in (c), and compared with state-of-the-art ocean water CDRprocess intensities reported by Digdaya et al.,15 Kim et al.,23 and Yan et al.22 The gray filled areashows possible operational points with varying extents of competing reactions with the maximumbounded by competing reactions occurring at mass-transfer limited rates. (d) Overall energy inten-sity (GJ/tCO2 ) including electrochemical and parasitic loads (as described in Sec. Energy IntensityCalculations) for the proposed process without competing reactions, calculated at an industrially-relevant current density of 100 mAcm−2, the baseline cell resistance, and pH shift of 6 to 9.6,compared with electrochemical and thermally-driven direct air capture (DAC) processes with data obtained from Singh et al.;24 error bars for the thermal DAC processes are from Viebahn et al.</div> <div> </div> <div><strong>Figure 5: </strong>Operating Energy Profiles and Effects of Load Shifting (a) Integration of solar and wind electricity production in California, CAISO 2022-2023,40 with predicted energy demand for the proposed oceanic CO2 removal process as a function of varying extents of yearly CO2 captured, 0 – 16 MtCO2,year. (b) Hourly power demand to capture 1 tCO2 per day. The gray curve indicates the process shown in (a), while the red curves shows a constant power demand process occurring at an equivalent energy intensity, i.e., the area underneath both curves are the same. (c) Hourly cost to capture 1 tCO2 per day. The gray curve indicates the hourly cost associated with variable energy process shown in (b) if all produced electricity is sold at market value, while the red curve compares it to the hourly cost associated with constant power consumption process shown in (b). Operating conditions of the proposed, variable process shown in (a-c) include jacid = 75 mA cm−2 and jbase = 150 mA cm−2, while still constraining the same volume of ocean water being treated over a 24-hour day in the individual steps (i.e. tbase = 0.5tacid). The process switches between acidification (occurring early mornings and evenings/nights when electricity price is high) and basification (occurring mid-day when electricity price is low) based on the supply and the cost of electricity purchased from CAISO (Sec S8.5). (d) Electricity cost savings for the proposed process operation compared to a process with constant energy usage at different ratios of tbase to tacid, assuming a time-weighted average operating current density of 100 mA cm−2. Different line styles indicate different proportions of market value at which produced electricity can be sold (0%, 50%, and 100%). For all cases: competing reactions are not considered, a thin boundary layer is assumed (δl = 10 μm), and the pH shift is from 6 to 9.6. Parasitic energy costs are included for CO2 phase separation, but not for pumping as we assume co-location with a desalination plant. Parasitics are assumed to only operate during the basification process, at high enough power to remove all CO2 treated over the day.</div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div>
Trajectories and metadata for Bach et al.: 'Holistic re-evaluation of Southern Ocean Iron Fertilization for atmospheric CO2 removal'
<p>Trajectory and metadata files from a Southern Ocean surface particle release experiment using Connectivity Modeling System (Paris et al. 2013, <a href="https://github.com/beatrixparis/connectivity-modeling-system">https://github.com/beatrixparis/connectivity-modeling-system</a>) run offline in the MOM01 model (Stewart et al., 2017; Spence et al., 2017; Morrison et al., 2020), a global 0.1° ocean sea-ice model, based on version 5 of the Modular Ocean Model (MOM) code (mom-ocean.github.io) (Griffies, 2012).</p> <p> Here particle trajectories are are split into 28 netcdf files (numbered traj_file_01.nc through traj_file_28.nc), and uploaded altogether as a single .tar.gz compressed file. Metadata files are also uploaded containing information on the CMS setup and release locations.</p> <p>Netcdf files contain particle trajectory positions, along with temperature, salinity, status in or out of the mixed layer, release date, and particle exit status (see <a href="https://github.com/beatrixparis/connectivity-modeling-system/blob/master/User-Guide-v2.pdf">CMS user guide</a> for details on trajectory files). Other CMS setup files included in each release directory are nest_1.nml, runconf.list, ibm.list, and releaseFile_matchtransport. These input files contain information needed to reproduce the experiment using the MOM01 model output, and are explained in detail in the <a href="https://github.com/beatrixparis/connectivity-modeling-system/blob/master/User-Guide-v2.pdf">CMS user guide</a>.</p> <p> </p> <p>Citation of associated paper: Bach, L., V. Tamsitt, K. Baldry, J. McGee, E. Laurenceau-Cornec, R. Strzepek, Y. Xie, P. W. Boyd, 2021. Holistic re-evaluation of Southern Ocean Iron Fertilization for atmospheric CO<sub>2</sub> removal, <em>submitted </em></p> <p> </p> <p>References:</p> <p>Griffies, S. M. (2012). Elements of the modular ocean model (MOM). <em>GFDL Ocean Group Tech. Rep</em>, 7(620), 47.</p> <p> Morrison, A. K., Hogg, A. M., England, M. H., & Spence, P. (2020). Warm Circumpolar Deep Water transport towards Antarctic driven by local dense water export in canyons. <em>Science Advances</em>, 6(18), eaav2516.</p> <p> Paris, C. B., Helgers, J., van Sebille, E., & Srinivasan, A. (2013). Connectivity Modeling System: A probabilistic modeling tool for the multi-scale tracking of biotic and abiotic variability in the ocean. <em>Environmental Modelling and Software</em>, 42, 47-54.</p> <p>Spence, P., Holmes, R. M., Hogg, A. M., Gries, S. M., Stewart, K. D., & England, M. H. (2017). Localized rapid warming of West Antarctic subsurface waters by remote winds. <em>Nature Climate Change</em>, 7(8), 595.</p> <p>Stewart, K., Hogg, A. M., Gries, S., Heerdegen, A., Ward, M., Spence, P., & England, M. H. (2017). Vertical resolution of baroclinic modes in global ocean models. <em>Ocean Modelling</em>, 113, 50-65.</p>
Data for the consolidated European synthesis of CO2 emissions and removals for EU27 and UK: 1990-2020
<p>The annual carbon dioxide fluxes used to create all graphs in the main text of McGrath et al, "European synthesis of CO2 emissions and removals for EU27 and UK: 1990-2020", submitted to Earth System Science Data.</p> <p> </p> <p>A second version was uploaded after responding to reviewer comments. The main difference is primarily that some data was discarded as the plot is no longer included; the units in the fossil fuel timeseries have been changed to Tg C instead of Tg CO2; and the uncertainties have been modified on the NGHGI data for FL, CL, and GL, resulting in a large change for GL (353.8% instead of 752%).</p>
Strategy of UltraProtective Lung Ventilation With Extracorporeal CO2 Removal for New-Onset Moderate to seVere ARDS
ClinicalTrials.gov study NCT02282657. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Extracorporeal CO2 Removal With the Hemolung RAS for Mechanical Ventilation Avoidance During Acute Exacerbation of COPD
ClinicalTrials.gov study NCT03255057. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Registry on the EXperience of Extracorporeal CO2 Removal in Intensive Care Units
ClinicalTrials.gov study NCT02965079. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Veno-venous Extracorporeal CO2 Removal in ARDS-patients to Treat Respiratory Acidosis
ClinicalTrials.gov study NCT01911533. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Extracorporeal CO2 Removal in Hypercapnic Patients
ClinicalTrials.gov study NCT02564406. IPD Sharing: Not stated. Countries: 1. Publications: 2.
"Low Flow" CO2 Removal on RRT
ClinicalTrials.gov study NCT02590575. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Protective Ventilation With Carbon Dioxide (CO2) -Removal Technique in Patients With Adult Respiratory Distress Syndrome (ARDS)
ClinicalTrials.gov study NCT00465309. IPD Sharing: Not stated. Countries: 1. Publications: 1.
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.