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23 results for “Carbon neutrality”
Diversity of options to eliminate fossil fuels and reach carbon-neutrality across the entire European energy system
<p><strong>Sector-coupled Euro-Calliope model outputs</strong></p> <p>The subdirectories found here cover cost-optimal and cost relaxation (SPORES) carbon-neutrality runs for a sector-coupled, sub-national resolution European energy system model.</p> <p>The underlying model to produce these results, <a href="https://github.com/calliope-project/sector-coupled-euro-calliope">Sector-coupled Euro-Calliope</a>, is an extension of the power-sector only <a href="https://github.com/calliope-project/euro-calliope">Euro-Calliope model</a>. It incorporates all energy consuming sectors and includes a more detailed representation of transmission capacities between 98 model regions in Europe.</p> <p>The model runs here are based on specific Sector-Coupled Euro-Calliope minor releases:</p> <ul> <li><a href="https://github.com/calliope-project/euro-calliope-2.0/commit/74f6a9b2e157b6147e155b556f521c03ef23246a">cost-opt</a></li> <li><a href="https://github.com/calliope-project/euro-calliope-2.0/commit/519a4fb26920114e451b8247b38ed86b93b6af89">slack-*</a></li> </ul> <p>The models were optimised using the <a href="https://github.com/calliope-project/calliope">Calliope open energy system modelling framework</a>, again based on different minor releases:</p> <ul> <li><a href="https://github.com/calliope-project/calliope/commit/1faed85eeddbe41c29d52982a6bfb147ef9001a3">cost-opt</a></li> <li><a href="https://github.com/calliope-project/calliope/commit/19460da2e23e752995a9a02ae6dca49379565d43">slack-*</a></li> </ul> <p><code>slack-*</code> results are for cost relaxation runs, where <code>*</code> refers to the percentage relaxation from the optimal cost of the 2018 energy system. All results use the <a href="https://github.com/sentinel-energy/friendly_data">friendly data</a> format. Data files are structured according to standardised sector-coupled Euro-Calliope output processing provided by the <a href="https://github.com/brynpickering/friendly-calliope">friendly-calliope</a> package + additional processing to produce data relevant to nine high-level metrics (see script <a href="https://github.com/calliope-project/sector-coupled-euro-calliope/blob/main/src/analyse/result_to_friendly.py">here</a>).</p> <p>Both cost optimal and SPORES results related to a projected demand scenario are given in the directories ending in "demand-update".</p> <p>To explore the data, please refer to the <a href="https://sentinel-energy.github.io/friendly_data/">friendly data documentation</a>.</p>
GCAM input files for "Decarbonization pathways for Korea's industrial sector towards its 2050 carbon neutrality goal"
<p>GCAM input files for "Decarbonization pathways for Korea's industrial sector towards its 2050 carbon neutrality goal"</p>
Data and code for "Carbon neutrality should not be the end goal: Lessons for institutional climate action from U.S. higher education"
<p>Code and data for the paper "Carbon neutrality should not be the end goal: Lessons for institutional climate action from U.S. higher education"</p> <p>File descriptions:</p> <p>'HEI_analysis_OneEarth.Rmd' is the code with improved annotation and colorblind-friendly figures.</p> <p>All other data files are provided as excel and csv for convenience.</p> <p>'working_master_data' contains data from the Second Nature reporting platform on emissions by category for each institution analyzed in the paper (measured in metric tons). All adjustments necessary to fill in the data gaps in this file are documented at the beginning of 'HEI_analysis'.</p> <p>'offsets' contains data on the type(s) of offsets purchased by each school in their carbon neutral year (measured in metric tons). This data was assembled from a variety of sources which are documented at the beginning of 'HEI_analysis'.</p> <p>'carbon_neutral_years' contains yearly counts of higher education neutrality goals that were reported to Second Nature as of November 2020.</p>
Case study result data set for Energy Economics (submitted) article "On Wholesale Electricity Prices and Market Values in a Carbon-Neutral Energy System"
<p>The data set contains wholesale power price time series data for Germany and France focussing on price setting effects in a long term low carbon European energy system context (scenario year 2050) generated with the model SCOPE SD of Fraunhofer Institute for Energy Economics and Energy System Technology IEE. The single time series are focussing on the price setting effects of different flexible technologies including both traditional and new market participants due to cross-sectoral integration.</p> <p>Unit: Euro/Megawatthour</p> <p><strong>Abbreviations:</strong></p> <ul> <li>BEV - Battery Electric Vehicles</li> <li>GER - Germany</li> <li>FRA - France</li> <li>OCGT - Open Cycle Gas Turbine</li> <li>PHEV - Plug-In Hybrid Vehicles</li> <li>RES - Renewable energy sources (here: wind and solar power)</li> <li>th. - thermal</li> </ul>
Katrin Mueller - Solar Energy for a Carbon-Neutral Society
<p>Are we on the right track towards reaching negative net-zero CO2 emissions by 2050? Find out more about how solar power could help achieve a climate-neutral Europe & don't miss our interview with Katrin Mueller, sustainability engineer at SIEMENS AG and a SUNRISE consortium member.</p>
Post‐processed data and analysis codes for the research "Significant reduction of potential exposure to extreme marine heatwaves by achieving carbon neutrality"
<p>[Earth's Future] Oh et al. "Significant reduction of potential exposure to extreme marine heatwaves by achieving carbon neutrality"</p> <p>1. Information for Raw datasets<br>- The data of eight global climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) can be accessed at https://esgf-node.llnl.gov/search/cmip6/, <br> and can also be accessed in Eyring et al. (2016). <br>- The NOAA OISST high resolution dataset can be obtained in Reynolds et al. (2007) or via https://psl.noaa.gov/data/gridded/data.noaa.oisst.v2.highres.html. <br>- The five ocean mask dataset can be obtained from https://reccap2-ocean.github.io/regions/. </p> <p>2. Information for Software<br>- The raw data in this study were analyzed using Fortran 90, R version 4.0.3, and Grads version 2.2.1.<br>- The Fortran 90 can be accessed at https://www.intel.com/content/www/us/en/developer/articles/tool/oneapi-standalone-components.html#fortran. <br>- The R version 4.0.3 is available from https://cran.r-project.org/bin/windows/base/old/4.0.3/. <br>- The Grads version 2.2.1 can be downloaded from http://cola.gmu.edu/grads/downloads.php.</p> <p>3. Information for Post-Processed data and Codes used in this work.<br>Please find each folder and the relevant post-processed dataset and codes.</p>
Model output data and code for Zhang et al., Cross-cutting scenarios and strategies for designing decarbonization pathways in the transport sector toward carbon neutrality
<p>Model output data and code for "Zhang et al., Cross-cutting scenarios and strategies for designing decarbonization pathways in the transport sector toward carbon neutrality" in Nature Communications.</p>
Carbon neutrality policy can deliver disproportionately higher gains for toxic trace elements control in China
<p>The dataset of carbon neutrality policy can deliver disproportionately higher gains for toxic trace elements control in China.</p>
"Power system investment optimization to identify carbon neutrality scenarios for Italy", scripts and data
<p>Script and data to reproduce the main results of "Power system investment optimization to identify carbon neutrality scenarios for Italy"</p>
Output data: China's energy-water-land system co-evolution under carbon neutrality goal and climate impacts
<p>Outputs for Wang, J., Duan, Y., Wang, C., 2023. China’s energy-water-land system co-evolution under carbon neutrality goal and climate impacts. (In progress)</p> <p>Folder demeter contains the spatially downscaled land use/land cover datasets.<br> Folder tethys contains the spatially downscaled water withdrawal datasets.</p> <p>The sub-folder names correspond to the scenarios described in the paper.</p> <p>For landcover datasets, land type ratios in each grid are presented. Land types include water, forest, shrub, grass, urban, snow, sparse and crops.</p> <p>For water withdrawal datasets, “wd” = “water withdrawal spatially downscaled”, “twd” = “water withdrawal spatially and temporally downscaled”, “dom”=”domestic/municipal sector”, “elec”=”electricity sector”, ”irr”=”irrigation sector”, “liv”=”livestock sector”, “mfg”=”manufacturing/industry sector”, “min”=”mining/primary energy sector”, “nonag”=”non-agricultural sector”, “total”=”all sectors”.<br> </p>
Provincial-Level Assessment of Carbon Dioxide Removal to Meet China's 2060 Carbon Neutrality Goal
<p>20240827_Provincial-Level Assessment of Carbon Dioxide Removal to Meet China's 2060 Carbon Neutrality Goal manuscript scenario Input xmls, output data, data processing code, Figures, figure generation code.</p> <p> </p> <p>Fig2 revised version</p>
Supplemental data and code for Improved air quality in China can enhance solar power performance and accelerate carbon neutrality targets
<p>Supplemental data and code for Improved air quality in China can enhance solar power performance and accelerate carbon neutrality targets</p>
Strengthened PM2.5 air quality improvement and health benefits by synergies of carbon peak, carbon neutrality, and clean air policies in China
<p>Dataset and code used in this research: (1) emission, major air pollutants (i.e., SO2, NOx, PM25, NMVOCs, NH3), and CO2 emissions during 2020-2060 under the scenario ensembles (i.e., reference, clean air, on-time peak-clean air, on-time peak-net zero-clean air, early peak-net zero-clean air). (2) PM2.5 exposure (NetCDF, 0.1×0.1), future PM2.5 concentrations (2025, 2030, 2035, 2040, 2045, 2050, 2055, 2060) under the scenario ensembles, re-gridded from the corresponding CMAQ simulations. (3) population, future population grid under the SSP1 scenario, re-gridded from SSP Datasets (<a href="http://clima-dods.ictp.it/Users/fcolon_g/ISI-MIP/">http://clima</a><a href="http://clima-dods.ictp.it/Users/fcolon_g/ISI-MIP/">-</a><a href="http://clima-dods.ictp.it/Users/fcolon_g/ISI-MIP/">dods.ictp.it/Users/fcolon_g/ISI</a><a href="http://clima-dods.ictp.it/Users/fcolon_g/ISI-MIP/">-</a><a href="http://clima-dods.ictp.it/Users/fcolon_g/ISI-MIP/">MIP/</a>). (4) death, PM2.5-related premature deaths (2025, 2030, 2035, 2040, 2045, 2050, 2055, 2060) under the scenario ensembles. (5) code for premature death calculation, with the method of GBD2019. (6) code for re-grid PM2.5 concentrations from CMAQ output.</p>
Codes for "Co-firing biomass and coal with retrofitted carbon capture and storage ease China to achieve carbon neutrality and net negative carbon in power sector"
<p>Codes for “Co-firing biomass and coal with retrofitted carbon capture and storage ease China to achieve carbon neutrality and net negative carbon in power sector”</p>
Towards carbon neutrality: mapping mass retrofit opportunities in Cambridge, UK
Open the record for dataset details and reuse information.
Carbon neutrality transitions from government-dependent towards free trade autonomy renewable markets with grid-demand-storage synergies
Open the record for dataset details and reuse information.
The Influencing Factors of Carbon Neutral Bonds and Blue Bonds Credit Spreads
Open the record for dataset details and reuse information.
The synergetic mitigation benefits on carbon and mercury emissions from carbon neutrality strategies and the Minamata Convention
<p>Results data</p>
The synergetic mitigation benefits on carbon and mercury emissions from carbon neutrality strategies and the Minamata Convention.
<p>This is the result of our paper data.</p>
Impacts of Carbon Neutrality on carbon emissions, economy and industrial water use in China
<p>The sectoral carbon emission, industrial water use, and output simulated by IMED|CGE model under the BaU and CNS scenarios in 2017, 2030, and 2060.</p>
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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.