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40 results for “energy pathways”
Impacts of invasive species on food web energy pathways and quality, St. Lawrence River, 2018-2021.
This dataset contains field measurements collected between 2018 and 2021 from three fluvial lakes in the Upper St. Lawrence River (Canada), including both invaded systems (with dreissenid mussels and round goby) and uninvaded reference sites. Data include georeferenced sampling information (site, lake, latitude, longitude, month, year), water chemistry (total phosphorus, µg/L; conductivity, µS/cm), and habitat descriptors (substrate). Biological records encompass seston, macroinvertebrates, and fish. Fish data comprise species identity, sex, total length (mm), weight (g), relative weight index (Wr), and detailed fatty acid composition expressed as relative proportions (%) and concentrations (µg/mg), including essential LC-PUFAs (EPA, DHA), n-3 and n-6 polyunsaturated fatty acids. Stable isotope data are provided, including carbon (δ13C) and nitrogen (δ15N) ratios, C:N ratios, and isotopic baselines from pelagic (δ13Cpel, δ15Npel) and benthic (δ13Cben, δ15Nben) sources. Derived variables, such as pelagic diet proportion and trophic position, were calculated using the two-source mixing model described by Post (2002) (DOI: https://doi.org/10.1890/0012-9658(2002)083[0703:USITET]2.0.CO;2). These data provide a comprehensive resource for examining food web structure, energy pathways, and the ecological impacts of invasive species in large river ecosystems.
Data Repository - Distinct Roles of Direct and Indirect Electrification in Pathways to a Renewables-dominated European Energy System
<p>This is the data repository to reproduce the scenario analysis of the paper "<a href="https://www.cell.com/one-earth/fulltext/S2590-3322(24)00037-X?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS259033222400037X%3Fshowall%3Dtrue">Distinct roles of direct and indirect electrification in pathways to a renewables-dominated European energy system</a>".</p> <p>The source code for the REMIND version used in this study is available at <a href="https://github.com/fschreyer/remind/tree/ElecH2_prod">https://github.com/fschreyer/remind/tree/ElecH2_prod</a>. The scenario config file that was used to start the specific model runs of the paper and that inlucdes all scenario-specific model settings can be found in the repository under <a href="https://github.com/fschreyer/remind/blob/ElecH2_prod/config/21_regions_EU11/scenario_config_ElecH2.csv">./config/21_regions_EU11/scenario_config_ElecH2.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/v3.2.1">https://github.com/remindmodel/remind/tree/v3.2.1</a> and <a href="https://doi.org/10.5281/zenodo.7852740">https://doi.org/10.5281/zenodo.7852740</a>. The 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>Model output data as well as other data that were used in the study are stored in data.zip. Moreover, we added a PlotsData.zip file, which contains the data shown in the figures of the paper. The R script to produce the figures and analysis of the paper can be found in ElecH2paper_Plots.Rmd. We 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> </p> <p>Contact:<br>Felix Schreyer<br>Potsdam Institute for Climate Impact Research<br>felix.schreyer@pik-potsdam.de</p>
Data deposit accompanying Accurate Energy Barriers for Catalytic Reaction Pathways: An Automatic Training Protocol for Machine Learning Force Fields
<p>Dataset accompanying the paper: <em>"Accurate Energy Barriers for Catalytic Reaction Pathways: An Automatic Training Protocol for Machine Learning Force Fields"</em>. Contains the training sets curated during active learning as well as .xyz files used for creating the Figures. <br> <br> The paper highlights that the computational efficiency of ML force fields not only results in decreased computational costs for routine catalytic investigations but also facilitates more comprehensive exploration of catalytic pathways.</p> <p><strong>Published in NPJ Computational Materials</strong>: <a href="https://www.nature.com/articles/s41524-023-01124-2">https://www.nature.com/articles/s41524-023-01124-2</a><br> Formerly on Arxiv: <a href="https://arxiv.org/abs/2301.09931">https://arxiv.org/abs/2301.09931</a></p>
Dataset: 800 QM/MM minimum energy pathway conformations for the acylation reactions of Toho-1/ampicillin and Toho-1/cefalexin
<p>This dataset consists of 800 coordinate files (in the CHARMM psf/cor format) for the QM/MM minimum energy pathways of the acylation reactions between a Class A beta-lactamases (Toho-1) and two beta-lactam antibiotic molecules (ampicillin and cefalexin).</p> <p>These files are:</p> <ul> <li>toho_amp.r1-ae.zip: The R1-AE acylation pathways for Toho-1/Ampicillin (200 pathways);</li> <li>toho_amp.r2-ae.zip: The R2-AE acylation pathways for Toho-1/Ampicillin (200 pathways);</li> <li>toho_cex.r1-ae.zip: The R1-AE acylation pathways for Toho-1/Cefalexin (200 pathways);</li> <li>toho_cex.r2-ae.zip: The R2-AE acylation pathways for Toho-1/Cefalexin (200 pathways);</li> <li>energies.zip: the replica energies at B3LYP-D3/6-31+G**/C36 level;</li> <li>chelpgs.zip: the ChElPG charges of all reactant replicas at B3LYP-D3/6-31+G**/C36 level;</li> <li>farrys.zip: the featurzied NumPy arrays for model training;</li> <li>peephole.zip: an example file for how the optimized MEPs look like; </li> <li>dftb3_benchmark.zip: the reference calculations to justify the use of DFTB3/3OB-F/C36 in MEP optimizations, the reference level of theory is B3LYP-D3/6-31G**/C36. </li> </ul> <p>The R1-AE pathways are the acylation uses Glu166 as the general base; the R2-AE pathways uses Lys73 and Glu166 as the concerted base. </p> <p>All QM/MM pathways are optimized at the DFTB3/3OB-f/CHARMM36 level of theory. </p> <p>Z. Song et al Mechanistic Insights into Enzyme Catalysis from Explaining Machine-Learned Quantum Mechanical and Molecular Mechanical Minimum Energy Pathways. <em>ACS Phys. Chem Au</em> 2022, <strong>2</strong>, 4, 316–330. DOI: <a href="https://doi.org/10.1021/acsphyschemau.2c00005">10.1021/acsphyschemau.2c00005</a></p>
Data from: Sectorial pathways to achieve net-zero and 1.5°C targets for Eu-27: Energy and emissions data to inform science-based decarbonization targets
Open the record for dataset details and reuse information.
ANGUSII Scenarios: Pathways to 100% Renewable German Energy System
<p>The data set contains an open source energy system model based on the Open Energy Modelling Framework (oemof) for Germany. Results are calculated for different scenarios for the year 2030, 2040 and 2050.</p> <p>A documentation file can be found on <a href="https://github.com/znes/angus-scenarios/blob/3d76ee93d075c3cd83e39ee60ccc34aa13da5732/documentation/scenario-description.pdf">Github.</a></p> <p> </p>
Dataset: 1,000 QM/MM minimum energy pathway conformations for the deacylation reactions of GES-5/imipenem
<p>This dataset consists of 1,000 coordinate files (in the CHARMM psf/cor format) for the QM/MM minimum energy pathways of the deacylation reactions between a Class A beta-lactamases (GES-5) and the imipenem antibiotic molecules.</p> <p>All pathway conformations were optimized at DFTB3/3OB-f/CHARMM36 level with 36 replicas.</p> <p>All single point calculations and charge population analysis were done at B3LYP-D3/6-31+G(d,p)/CHARMM36 level.</p> <ul> <li>0.paths_ges_imi_d1.tar.gz: 500 pathway conformations for GES-5/IPM-Delta1 deacylation reactions.</li> <li>0.paths_ges_imi_d2.tar.gz: 500 pathway conformations for GES-5/IPM-Delta1 deacylation reactions.</li> <li>1.eners.zip: The single point replica energies along all GES-5/IPM pathways.</li> <li>1.chrgs.zip: The NBO charges of the QM region of all replica conformations along all GES-5/IPM pathways.</li> <li>2.datasets.zip: The Python codes to postprocess the molecular data and the featurized the NumPy arrays.</li> <li>3.gnn.zip: The Python codes that implements the edge-conditioned graph convolutional NN to predict the deacylation barriers.</li> <li>5.representative_conf.zip: The pathway conformations of all cluster centroids and an energetic representative (pathway id 22) pathway. Note: This file also serves as a peephole of how the pathway conformations from Reaction Path with Holonomic Constrains calculations looks like.</li> <li>6.benchmark.zip: The benchmark calculations that validates the DFTB3/3OB-f/CHARMM36 against DFTB3/3OB/CHARMM36 and B3LYP/6-31G(d,p)/CHARMM36 level of theory on the energetic representative (pathway id 22) pathway conformations. </li> <li>p.figures.zip: A series of Jupyter Notebooks that produces the visualizations in the work.</li> <li>README.md: A markdown file that contains additional descriptions.</li> <li>environment.yml: The Conda environment used for the graph-learning. </li> </ul> <p>Z. Song and P. Tao, Graph-Learning Guided Mechanistic Insights into Imipenem Hydrolysis in GES Carbapenemases. <strong><em>Electron. Struct.</em></strong> 2022, <strong>4</strong>, 034001. DOI: <a href="https://doi.org/10.1088/2516-1075/ac7993">10.1088/2516-1075/ac7993</a></p>
Additional Data and Code from "Increased energy use for adaptation significantly impacts mitigation pathways".
<p>Additional Data and Code from: "Increased energy use for adaptation significantly impacts mitigation pathways".</p> <p>Authors: Francesco Pietro Colelli, Johannes Emmerling, Giacomo Marangoni, Malcolm Mistry, Enrica De Cian</p> <p>This repository contains:</p> <p>- The output data and R-scripts to produce the figures of the manuscript.</p> <p>- The code building the additional WITCH modules and input data generated. The results obtained in the study can be replicated by running the additional WITCH modules and input data in combination with the open source WITCH available in the repository: https://github.com/witch-team/witchmodel</p> <p> </p>
Case study input data set for article "Stochastic planning of energy system transformation pathways under uncertain industry demands"
<p>The data set contains input data for the model EMPRISE of Fraunhofer Institute for Energy Economics and Energy System Technology IEE. </p>
Body size, trophic position, and the coupling of different energy pathways across a saltmarsh landscape
<p>Here, we listed the bulk stable isotope values (δ13C and δ15N) and body size measurements of organisms that were analyzed in the manuscript "Body size, trophic position, and the coupling of different energy pathways across a saltmarsh landscape", published in Limnology and Oceanography Letters. Our dataset is a compilation of samplings obtained by the Southern Louisiana marsh food webs project within the Coastal Waters Consortium (CWC) II (Lopez-Duarte et al. 2017a [https://doi.org/10.7266/N7XS5SGD], Lopez-Duarte et al. 2017b [https://doi.org/10.7266/N79W0CJW], Polito et al. 2019 [https://doi.org/10.7266/n7-6277-1216]). The dataset consists of 1563 individual samples from 77 taxa, including basal sources (plants, phytoplankton, detritus, and microphytobenthos), fishes, invertebrates (insects, crustaceans, and spiders), infauna, seaside sparrows (Ammospiza maritima), and marsh rice rats (Oryzomys palustris). Samplings were conducted in three sites, Bay Sansbois, Bay Batiste, and West Pointe à la Hache, located in northeastern Barataria Bay. Bay Sansbois and Bay Batiste were sampled in May and October 2015, and May 2016, whereas West Pointe à la Hache was sampled only in May 2016. Body size measurements are available for 59% of all samples (52 taxa) while δ13C and δ15N are available for all samples.</p>
Supporting Data and Guidance: Modeling policy pathways to maximize renewable energy growth and investment in Democratic Republic of the Congo using OSeMOSYS
<p>This repository contains data files and guidance documents that are supplementary materials to accompany the policy paper "Modeling policy pathways to maximize renewable energy growth and investment in Democratic Republic of the Congo using OSeMOSYS" available on Research Square here: <a href="https://www.researchsquare.com/article/rs-2702275/v1">https://www.researchsquare.com/article/rs-2702275/v1</a></p>
CCG: Beyond the Dams: Combatting Hydropower Over-reliance & Securing Pathways for a Low-carbon Future for Laos' Electricity Sector using OSeMOSYS (Open-Source Energy Modelling System)
<p>Seven clicSAND scenario files for <strong>Beyond the Dams: Combatting Hydropower Over-reliance & Securing Pathways for a Low-carbon Future for Laos' Electricity Sector using OSeMOSYS (Open-Source Energy Modelling System).</strong> </p> <p><strong>How to Visualise Results Online and Offline</strong> outline the steps required to re-run the scenarios on OSeMOSYS Cloud</p> <p><strong>Scenario Short Note</strong> outlines the steps to replicate the analysis and rebuild the scenarios</p> <p><strong>Annex - Input Data and Assumptions</strong> listing the data sources and assumptions in the scenarios</p>
Deep decarbonisation pathways of the energy system in times of unprecedented uncertainty in the energy sector. Energy Policy (2023). Supplementary Information on Assumptions and Results
<p>This dataset supplements the article with the title "Deep decarbonisation pathways of the energy system in times of unprecedented uncertainty in the energy sector", published in Energy Policy. </p> <p>The dataset contains the following:</p> <ul> <li>The Latin Hypercube Sample of the multipliers that are applied to the key input parameters of ETSAP-TIAM in order to generate 1000 different states of the world regarding economic and demographic growth, energy resources potentials, energy technology costs, climate sensitivity and radiative forcing, LULUCF CO<sub>2</sub> sink potential, CO<sub>2</sub> sequestration potential, and decoupling between energy consumption and economic development. The multipliers are sampled from the underlying probability distributions described in the article. </li> <li>The results (at the global scale) from four scenario families for each one of the 1000 wofld states. These scenario families are: <ul> <li>BASE_SSP2: Describes the development of the global energy system consistent with recent trends and policies.</li> <li>2C_SSP2: Introduces to the BASE_SSP2 scenario a global constraint of 2 °C as the maximum post-industrial temperature change from 2020 to 2100.</li> <li>2C_SSP2_DA30: Delayed climate action. The climate change mitigation policies of 2C_SSP2 start in 2030. </li> <li>1p5c_OS_SSP2: Introduces to the BASE_SSP2 scenario a global constraint of 1.5 °C as the maximum post-industrial temperature change from 2020 onwards to 2100</li> </ul> </li> </ul> <p>Key results included in the dataset are: Temperature change, Radiative Forcing, GHG concentrations, CO2 emissions, Marginal abatement cost, Electricity Supply Primary Energy Consumption, and Annual Total Global Energy System Cost.</p> <p>The dataset also includes sectoral results regarding energy consumption and use, such as shares of different electric uses, shares of hydrogen consumption in end-use sectors, hydrogen supply, Demand electrification by sector, Renewable energy consumption by sector, Alternative fuels consumption in transport, and Total final energy consumption by sector. </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>
Body size, trophic position, and the coupling of different energy pathways across a saltmarsh landscape
Open the record for dataset details and reuse information.
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.
Paving the Way: Analysing Energy Transition Pathways and Green Hydrogen Exports in Developing Countries – The Case of Algeria. Supplementary Data
<p>Supplementary material for peer review</p><ul><li>Model Input</li><li>Model Results (LEAP/NEMO)</li></ul>
Key results and plot files for the paper "Diversity of biomass usage pathways to achieve emissions targets in the European energy system"
<p>Key results and plot files for the paper:</p> <p>Millinger, M., Hedenus, F., Zeyen, E. <em>et al.</em> Diversity of biomass usage pathways to achieve emissions targets in the European energy system. <em>Nat Energy</em> <strong>10</strong>, 226–242 (2025). https://doi.org/10.1038/s41560-024-01693-6</p>
Data from: Functional traits and environmental conditions predict community isotopic niches and energy pathways across spatial scales
1. Despite ongoing research in food web ecology and functional biogeography, the links between food-web structure, functional traits and environmental conditions across spatial scales remain poorly understood. Trophic niches, defined as the amount of energy and elemental space occupied by species and food webs, may help bridge this divide. 2. Here, we ask how the functional traits of species, the environmental conditions of habitats and the spatial scale of analysis jointly determine the characteristics of trophic niches. We used isotopic niches as a proxy of trophic niches, and conducted analyses at spatial scales ranging from local food webs and metacommunities to geographically distant sites. 3. We sampled aquatic macroinvertebrates from 104 tank bromeliads distributed across five sites from Central to South America, and compiled the macroinvertebrates' functional traits and stable isotope values (δ15N and δ13C). We assessed how isotopic niches within each bromeliad were influenced by the functional trait composition of their associated invertebrates and environmental conditions (i.e., habitat size, canopy cover, and detrital concentration). We then evaluated whether the diet of dominant predators and, consequently, energy pathways within food webs, reflected functional and environmental changes among bromeliads across sites. Finally, we determined the extent to which the isotopic niches of macroinvertebrates within each bromeliad contributed to the metacommunity isotopic niches within each site, and compared these metacommunity-level niches over biogeographic scales. 4. At the bromeliad level, isotopic niches increased with the functional richness of species in the food web and the detrital concentration in the bromeliad. The diet of top predators tracked shifts in prey biomass along gradients of canopy cover and detrital concentration. Bromeliads that grew under heterogeneous canopy cover displayed less trophic redundancy and therefore combined to form larger metacommunity isotopic niches. Finally, the size of metacommunity niches depended on within-site heterogeneity in canopy cover. 5. Our results suggest that the trophic niches occupied by food webs can predictably scale from local food webs to metacommunities to biogeographic regions. This scaling process is determined by both the functional traits of species and heterogeneity in environmental conditions.
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>
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.