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38 results for “net zero”
Net Zero Stocktake 2023
<p>The underlying dataset for the Net Zero Tracker's Net Zero Stocktake Report 2023.</p>
Net-zero transition of the global chemical industry with CO2-feedstock by 2050: feasible yet challenging
<p>This dataset contains supplementary data and code for the following publication:</p> <p>Title: Net-zero transition of the global chemical industry with CO2-feedstock by 2050: feasible yet challenging<br> Authors: Jing Huo, Zhanyun Wang, Christopher Oberschelp, Gonzalo Guillén-Gosálbez and Stefanie Hellweg<br> Year: 2023<br> Journal: Green Chemistry<br> Issue: 25<br> Pages: 415-430<br> Publisher: Royal Society of Chemistry<br> Direct link: https://doi.org/10.1039/D2GC03047K</p> <p>Please read "read_me.txt" for more details.</p>
Net-zero 1.5 °C sectorial pathways for G20 countries: energy and emissions data to inform science-based decarbonization targets
<p><span>This data for global, regional (EU-27), and country-specific (G20 member countries) energy and emission pathways required to achieve a defined carbon budget of under 450 Gt/CO2, developed to limit the mean global temperature rise to 1.5°C, over 50% likelihood. The data were calculated with the 1.5°C sectorial pathways of the One Earth Climate Model—an integrated energy assessment model devised at the University of Technology Sydney (UTS). </span></p> <p><span>The data consist of the following six zip-folder datasets (refer to Section 2 for an explanation of the data):</span></p> <p><span>1. </span><span>Appendix folder: Each file contains one worksheet, which summarizes the overall 1.5°C scenario.</span></p> <p><span>2. </span><span>Sector folder (XLSX): Each file contains one worksheet, which summarizes the industry sectors analysed.</span></p> <p><span>3. </span><span>Sector folder (CSV): The data contained are the same as those described in point 2.</span></p> <p><span>4. </span><span>Sector emissions folder: Each file contains one worksheet, which summarizes the total annual emissions for each industry sector.</span></p> <p><span>5. </span><span>Scope emissions folder (XLSX): Each file contains one worksheet, which summarizes the total annual emissions for each industry sector—with the additional specificity of emission scope. </span></p> <p><span>6. </span><span>Scope emissions folder (CSV): The data contained are the same as those described in point 5.</span></p>
Summary dataset for Indonesia Net-Zero electricity scenarios
<p>Dataset of “Net-Zero Electricity” study as visualized in <a href="https://masadepanenergi.id">https://masadepanenergi.id</a>. This data is generated for electricity sector analysis using Spatially-explicit Energy and LAnd system InfrastRUcture (SELARU) modelling framework.</p> <p>Full documentation and scientific publication of the study is still in preparation. However, technical details, including input datasets and basic assumptions of SELARU modelling framework, can be found in the model’s public repository (<a href="https://github.com/iiasa/selaru">https://github.com/iiasa/selaru</a>).</p> <p>This Upload contains the summary datasets for generation capacity and output of Net-Zero electricity scenarios for each spatial unit (spatial unit GIS file provided in “spatial_unit_nze_2023.gpkg”), as well as provincial and national summary for investment requirements and carbon emissions.</p> <p>Dataset of “Net-Zero Electricity” study as visualized in <a href="https://masadepanenergi.id">https://masadepanenergi.id</a>. This data is generated for electricity sector analysis using Spatially-explicit Energy and LAnd system InfrastRUcture (SELARU) modelling framework.</p> <p>Full documentation and scientific publication of the study is still in preparation. However, technical details, including input datasets and basic assumptions of SELARU modelling framework, can be found in the model’s public repository (<a href="https://github.com/iiasa/selaru">https://github.com/iiasa/selaru</a>).</p> <p>This Upload contains the summary datasets for generation capacity and output of Net-Zero electricity scenarios for each spatial unit (spatial unit GIS file provided in “spatial_unit_nze_2023.gpkg”), as well as provincial and national summary for investment requirements and carbon emissions.</p>
Net-zero 1.5 °C sectorial pathways for G20 countries: energy and emissions data to inform science-based decarbonization targets
Open the record for dataset details and reuse information.
Retrofitting coal-fired power plants with biomass co-firing and CCS for net zero carbon emission: A plant-by-plant assessment based on GIS-LCA framework
<p>Dataset for "Retrofitting coal-fired power plants with biomass co-firing and CCS for net zero carbon emission: A plant-by-plant assessment based on GIS-LCA framework"</p>
Minimizing habitat conflicts in meeting net-zero energy targets in the western United States
<p>This dataset contains spatial and non-spatial input and output data generated for and from the <a href="https://www.nature.org/en-us/what-we-do/our-priorities/tackle-climate-change/climate-change-stories/power-of-place/">Power of Place West</a> study, published in the Proceedings of the National Academy of Science (PNAS). See readme pdf for more details. </p>
Supplemental data for the paper "Managing CO2 under global and country-specific net-zero emissions targets in Europe"
<p>This repository includes results discussed in the paper "Managing CO2 under global and country-specific net-zero emissions targets in Europe".</p>
Pathways to a net zero building sector in Colombia: insights from a circular economy perspective
<p>This dataset contains the input data and core results of the RECC v2.5 model for the analysis of circular economy strategies in the Colombian residential sector. For details about the RECC model, see DOI <a href="https://doi.org/10.1111/jiec.13023" target="_blank" rel="noopener">https://doi.org/10.1111/jiec.13023</a> and the RECC model landing page: <a href="https://www.industrialecology.uni-freiburg.de/odym-recc" target="_blank" rel="noopener">https://www.industrialecology.uni-freiburg.de/odym-recc</a></p> <p>The following data are included in this dataset:</p> <ul> <li>The entire model input database (120 model parameters)</li> <li>The parameters for the sensitivity analysis (8 parameters)</li> <li>The 70 folders with the core results</li> <li>The master classification file RECC_Classifications_Master_V2.0.xlsx</li> <li>The model config file RECC_Config.xlsx</li> <li>The list of scenario configurations RECC_ModelConfig_List.xlsx</li> <li>The result compilation and exporting configuration file RECCv2.5_EXPORT_Combine_Select.xlsx</li> <li>The main result summary file (extracted from the 70 result folders) Results_Extracted_RECCv2.5_10Regs_sep.xlsx</li> <li>The results of the sensitivity analysis</li> </ul> <p> </p> <p>The model itself is available as Python code from <a href="https://github.com/IndEcol/RECC-ODYM" target="_blank" rel="noopener">https://github.com/IndEcol/RECC-ODYM</a></p>
An assessment of energy system transformation pathways to achieve net-zero carbon dioxide emissions in Switzerland. Supplementary Information Assumptions and Results
<p>This dataset accompanies the corresponding article in Communications Earth and Environment. It contains the key assumptions used in the energy system modelling with the Swiss TIMES energy systems model (STEM) for assessing net-zero carbon dioxide emissions scenarios for Switzerland. In addition, contains extensive results from STEM for each one of the core scenarios and variants assessed in the study.</p> <p>The following files are contained in this repository:</p> <ul> <li><strong>Supplementary Data 1</strong>: This is the EXCEL file "Supplementary_Information_Assumptions.xslx" which contains key assumptions of the long-term scenarios assessed with STEM. These include among others: the major energy and climate policies in each scenario, the economic and demographic assumptions, key drivers for the residential energy demand (e.g., floor reference area or appliances), key drivers for the energy demand in the services sectors (e.g., Gross Value Added or floor area), key drivers for the energy demand in industry (e.g., production index or Gross Value Added), mobility demands, energy import prices, hourly electricity import prices, net transfer capacities, domestic sustainable renewable resource potentials, energy supply and demand technologies costs and efficiencies</li> <li><strong>Supplementary Data 2</strong>: This is the EXCEL file "Supplementary_Information_Results.xlsx" which contains energy balances from the baseline and the net-zero CO<sub>2</sub> emissions scenarios. The results for each scenario are: domestic production by fuel, net imports by fuel, primary energy consumption by fuel, input to conversion sectors by fuel, electricity supply and capacities by fuel, district heating supply by fuel, final energy consumption by fuel and sector, CO2 emissions by source, energy system costs, and indicators such as energy consumption per capita, energy intensity of GDP, CO2 emissions per capita and CO2 intensity of GDP. </li> <li><strong>Supplementary Data 3</strong>: The ZIP file "Source_code_and_data_for_charts.zip" contains source codes and data for reproducing the figures in the manuscript. </li> </ul>
Nature-based solutions are critical for putting Brazil on track towards net-zero emissions by 2050
<p>This dataset supports the findings of the article "Nature-based solutions are critical for putting Brazil on track towards net-zero emissions by 2050" from Soterroni et al. (2023) accepted in Global Change Biology.</p>
Data from: Warming enhances sedimentation and decomposition of organic carbon in shallow macrophyte-dominated systems with zero net effect on carbon burial
Open the record for dataset details and reuse information.
Data Repository - From net-zero to zero-fossil in transforming the EU energy system
<p>This is the data repository to reproduce the analysis of the manuscript "From net-zero to zero-fossil in transforming the EU energy system", which is currently under review for publication in a scientific journal. </p> <p>The source code for the REMIND version used in this study is available at <a href="https://github.com/fschreyer/remind/tree/FossilFree_master">https://github.com/fschreyer/remind/tree/FossilFree_master.</a> The scenario config file that was used to start the specific model runs of the analysis including all scenario-specific model settings can be found in the repository under <a href="https://github.com/fschreyer/remind/blob/FossilFree_master/config/scenario_config_fossilfree.csv">./config/scenario_config_fossilfree.csv</a>. The repository is a fork with slight changes relative to the main release version available at <a href="https://github.com/remindmodel/remind/tree/v3.3.1">https://github.com/remindmodel/remind/tree/v3.3.1</a> and <a href="https://zenodo.org/records/12104410">https://zenodo.org/records/12104410</a>. A general model documentation can be found at <a href="https://rse.pik-potsdam.de/doc/remind/3.2.0">https://rse.pik-potsdam.de/doc/remind/3.2.0</a>. </p> <p>The data repository contains the following files:</p> <p>data</p> <ul> <li>FossilFree_Plot.Rmd - R markdown file used for the analysis.</li> <li>AllScenarioData.mif - Data file containing REMIND scenario output data used for the analysis.</li> <li>MainFigures.xlsx - Data file containing all data plotted in main figures of the text.</li> <li>SIFigures.xlsx - Data file containing all data plotted in extended data figures and supplementary figures of the text.</li> <li>data folder: containing data and mapping files used for the FossilFree_Plot.Rmd script</li> <li>scripts folder: containing additional scripts and functions used in the FossilFree_Plot.Rmd script</li> </ul> <p>Note that we cannot provide the AR6 scenario data here. Please refer to <a href="https://zenodo.org/records/7197970">https://zenodo.org/records/7197970</a>. </p> <p>Disclaimer: We here publish a comprehensive dataset of our model output which includes more data than what is needed to reproduce the figures of the paper. Those data can be helpful to compare and contextualize our scenarios or use them for further analyses. However, due to the scope and complexity of our modeling framework, these data need to be used with care. The data used for the analysis of this study have been thoroughly validated. However, we cannot always perform such validation for the whole dataset and data need to treated with caution in particular at high regional or sectoral resolution and with respect to aspects that were not in the focus of the study as there maybe artefacts or limitations of our modeling approach. Please contact us in case you would like to use our scenarios for further analyses. We welcome open and constructive exchange on our data. </p> <p>Contact:<br>Felix Schreyer<br>Potsdam Institute for Climate Impact Research<br>felix.schreyer@pik-potsdam.de</p>
Repository for Tarshish, Jeevanjee, and Fung (2025), "Cooling after net zero".
<p>See REAME.pdf below. </p>
Data and code for the publication "Observed carbon decoupling of subnational production insufficient for net-zero goal by 2050"
Open the record for dataset details and reuse information.
Net-zero emissions aviation
<p>Dataset for Net-zero emissions aviation paper.</p> <p> </p> <p><strong>Abstract:</strong> International climate goals imply reaching net-zero global carbon dioxide (CO<sub>2</sub>) emissions by roughly mid-century (and net-zero greenhouse gas emissions by the end of the century). Among the most difficult emissions to avoid will be those from aviation given the industry’s need for energy-dense liquid fuels that lack commercially competitive substitutes, and the difficult-to-abate non-CO<sub>2</sub> radiative forcing. Here, we systematically assess pathways to net-zero emissions aviation, exploring the potential contribution of different approaches. We find that ambitious reductions in demand for air transport and improvements in the energy efficiency of aircraft might avoid up to 61% (2.8 GtCO<sub>2</sub> equivalent) and 27% (1.2 GtCO<sub>2-eq</sub>), respectively, of projected business-as-usual aviation emissions in 2050. However, further reductions will depend on replacing fossil jet fuel with large quantities of net-zero emissions biofuels or synthetic fuels (i.e. 2.5-19.8 EJ of sustainable aviation fuels)—which may be substantially more expensive. Moreover, up to 3.4 GtCO<sub>2-eq</sub> may need to be removed from the atmosphere to compensate for non-CO<sub>2</sub> forcing for the sector to achieve net-zero GHG. Our results may inform investments and priorities for innovation by highlighting plausible pathways to net-zero emissions aviation, including the relative potential and trade-offs of changes in behavior, technology, and energy sources.</p>
Data for "More intensive use and lifetime extension can enable net-zero emissions in China's cement cycle"
<p>Part of the data used and results in the paper "<em><strong>More intensive use and lifetime extension can enable net-zero emissions in China's cement cycle</strong></em>" published on the journal <em>Resources, Conservation, and Recycling</em>. </p>
Solutions to achieve net-zero emissions in irrigated agriculture
<p>The original geospatial data of the figure.S5-9.</p> <p>The dataset contains:</p> <p>-Global energy consumption and carbon emissions from irrigation . Units: Terajoule/year and Million tonnes CO2/year. </p> <p>-Energy consumption and carbon emissions with different irrigation systems. Units: Terajoule/year and Million tonnes CO2/year. </p> <p>-Global energy consumption under drip and sprinkler scenarios. Units: Terajoule/year</p>
ScienceDex guides
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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)
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.