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23 results for “life cycle modelling”
Life cycle inventories for the article: Circular Battery Production in the EU: Insights from integrating Life Cycle Assessment into System Dynamics Modeling on Recycled Content and Environmental Impacts
<p>This repository provides the unregionalized life cycle inventories to the paper "<span>Ginster, R.</span>, <span>Blömeke, S.</span>, <span>Popien, J. L.</span>, <span>Scheller, C.</span>, <span>Cerdas, F.</span>, <span>Herrmann, C.</span>, & <span>Spengler, T. S.</span> (<span>2024</span>). <span>Circular battery production in the EU: Insights from integrating life cycle assessment into system dynamics modeling on recycled content and environmental impacts</span>. <em>Journal of Industrial Ecology</em>, <span>1</span>–<span>18</span>. <a href="https://doi.org/10.1111/jiec.13527">https://doi.org/10.1111/jiec.13527</a>".</p> <h2>Contents</h2> <p>The repository is split into 2 parts and comprises the following files:</p> <p><strong>01_production: </strong>contains the necessary life cycle inventories for battery production.</p> <ul> <li><strong>01_primary</strong>: contains the life cycle inventories for battery production from primary materials.</li> <li><strong>02_secondary</strong>: contains the life cycle inventories for battery production from secondary materials.</li> <li><strong>03_active_material</strong>: contains the life cycle inventories for the active battery materials from primary materials.</li> <li><strong>04_active_material</strong>: contains the life cycle inventories for the active battery materials from secondary materials.</li> </ul> <p> </p> <p><strong>02_recycling: </strong>contains the necessary inventories for battery recycling.</p> <ul> <li><strong>01_process</strong>: contains the life cycle inventories for battery recycling.</li> <li><strong>02_intermediate</strong>: contains the life cycle inventories for the intermediate system for battery recycling.</li> <li><strong>03_output</strong>: contains the life cycle inventories for the resulting substances from battery recycling.</li> </ul> <h2>Summary</h2> <p>These files allow to reproduce the results of our study. Each file contains the life cycle inventory of one distinct battery capacity (20, 45, 68, 85, 95, 100 kWh) with a specific cell chemistry (LFP, NCA, NMC333, NMC532, NMC622, NMC811, NMC955) for battery production (based on Knehr et al. 2022) or for battery recycling (based on Blömeke et al. 2023).</p> <h2>Related publication</h2> <p>More details on the scientific context is provided in the publication itself:</p> <p><span>Ginster, R.</span>, <span>Blömeke, S.</span>, <span>Popien, J. L.</span>, <span>Scheller, C.</span>, <span>Cerdas, F.</span>, <span>Herrmann, C.</span>, & <span>Spengler, T. S.</span> (<span>2024</span>). <span>Circular battery production in the EU: Insights from integrating life cycle assessment into system dynamics modeling on recycled content and environmental impacts</span>. <em>Journal of Industrial Ecology</em>, <span>1</span>–<span>18</span>. <a href="https://doi.org/10.1111/jiec.13527">https://doi.org/10.1111/jiec.13527</a></p> <h2>Funding</h2> <p>This publication (Raphael Ginster and Steffen Blömeke) was created within the Research Training Group CircularLIB, supported by the Ministry of Science and Culture of Lower Saxony with funds from the program zukunft.niedersachsen of the Volkswagen Foundation (MWK | ZN3678).</p> <p>The publication on which this dataset is based were funded by the German Federal Ministry of Education and Research within the Competence Cluster Recycling & Green Battery (greenBatt) under the grant numbers 03XP0302A (Christian Scheller) and 03XP0331A (Jan-Linus Popien). The authors are responsible for the contents of this publication.</p>
A CO2 valorization plant to produce light hydrocarbons: kinetic model, process design and life cycle assessment
<p>Supplementary material: Reaction indexes, Conservation equations, boundary conditions and used coefficients. Additional experimental results, Experimental data fitting, Stream properties and composition of the CO2 plant, Life Cycle Assessment indicators, assumptions and data input </p>
A core ontology for modeling life cycle sustainability assessment on the Semantic Web with Accompanying Database
<p>To enable and support the uptake of semantic ontologies, we present a core ontology developed specifically to capture the data relevant for life cycle sustainability assessment. We further demonstrate the utility of the ontology by using it to integrate data relevant to sustainability assessments, such as EXIOBASE and the Yale Stocks and Flow Database to the Semantic Web. These datasets can be accessed by the machine-readable endpoint using SPARQL, a semantic query language.</p>
Delta smelt (Hypomesus transpacificus) life cycle model input data.
Synthesized data used for fitting delta smelt population dynamics models, essentially consisting of predictor variables (environmental conditions and indices of prey and predators) and response variables (abundance indices). Input data is sourced from a variety of both federal and California state government monitoring programs taking place within the San Francisco Estuary, California. These include California Department of Fish and Wildlife fish surveys, Interagency Ecological Program's Environmental Monitoring Program for zooplankton, California Department of Water Resources' Dayflow, and United States Geological Survey water monitoring data. The sourced data are recorded from sub-hourly to monthly time scales and at various spatial scales, aggregated at monthly or greater time scales using summary statistics (e.g. means) and are not spatially explicit but use spatial stratification approaches for statistic calculation as appropriate.
Fig. 2 in A modelling approach to describe the Anthonomus eugenii (Coleoptera: Curculionidae) life cycle in plant protection: a priori and a posteriori analysis
Fig. 2. Simulation output from the model (1) evaluating the daily average temperature with the Logan development rate function.
Fig. 1 in A modelling approach to describe the Anthonomus eugenii (Coleoptera: Curculionidae) life cycle in plant protection: a priori and a posteriori analysis
Fig. 1. Simulation output from the model (1) evaluating the daily average temperature with the Briére development rate function.
Fig. 3 in A modelling approach to describe the Anthonomus eugenii (Coleoptera: Curculionidae) life cycle in plant protection: a priori and a posteriori analysis
Fig. 3. Briére development rate function compared with life tables point from Toapanta et al. (2005).
Data: Testing the mating system model of parasite complex life cycle evolution reveals demographically driven mixed mating
<p>Abstract: Many parasite species use multiple host species to complete development; however, empirical tests of models that seek to understand factors impacting evolutionary changes or maintenance of host number in parasite life cycles are scarce. Specifically, Brown et al.’s (2001) mating system model, which posits multi-host life cycles are an adaptation to prevent inbreeding in hermaphroditic parasites and thus, preclude inbreeding depression, remains untested. The model assumes loss of a host results in parasite inbreeding and predicts host loss can only evolve if there is no parasite inbreeding depression. <a name="_Hlk169780726"></a>We provide the first empirical tests of this model using a novel approach we developed for assessing inbreeding depression from field-collected, parasite samples. The method compares genetically-based, selfing-rate estimates to a demographic-based selfing rate, which was derived from the closed mating system experienced by endoparasites. Results from the hermaphroditic trematode <em>Alloglossidium renale</em>, which has a derived 2-host life cycle, supported both the assumption and prediction of the mating system model as this highly inbred species had no indication of inbreeding depression. Additionally, comparisons of genetic and demographic selfing rates revealed <a name="_Hlk169781073"></a>a mixed mating system that could be explained completely by the parasite’s demography, i.e., its infection intensities.</p>
Dataset of life cycle assessment (LCA) model for sugar beet pulp biorefinery
<p>This dataset contains information of the foreground and background systems used to model a sugar beet pulp biorefinery. More information can be found in the file.</p>
[Supplementary Information] Model uncertainty versus variability in the life cycle assessment of commercial fisheries
<p>Supporting information from the manuscript: <em>Model uncertainty versus variability in the life cycle assessment of commercial fisheries</em>. The study analyses the life cycle assessment of fish species landed by Danish trawlers, comparing sources of uncertainty (such as modelling approaches) with sources of variability (vessel length and years).</p> <p>Supporting information 1: In depth description of the different models used in the study, the fuel disaggregation processes and the sensitivity analysis performed</p> <p>Supporting information 2: Contains the excel table with the datasets and related calculations to replicate the results described in the paper and the R code used to analyze the results.</p>
Redwood Creek Chinook salmon life cycle model code and data
Open the record for dataset details and reuse information.
Earth System Model-based Life Cycle Assessment of Ocean Alkalinity Enhancement
<ol> <li>“Fig2data.xlsx”, “Fig5data.xlsx” and “Fig4data.xlsx” are the original data to create Fig.2, Fig.3 and Fig.5. The data are calculated from UVic results.</li> <li>“Fig4.txt” is the code to create Fig.4 by Pyferret from UVic results.</li> <li>“X.f” are the update codes in our UVic model.</li> </ol>
Modeling cyanobacteria life cycle dynamics and historical nitrogen fixation in the Baltic Proper - Datasets
<p>Observational and model datasets used in: Modeling cyanobacteria life cycle dynamics and historical nitrogen fixation in the Baltic Proper.</p>
Hybridization selects for prime-numbered life cycles in Magicicada: an individual-based simulation model of a structured periodical cicada population
Open the record for dataset details and reuse information.
Data from: Modeling the influence of genetic and environmental variation on the expression of plant life cycles across landscapes
Open the record for dataset details and reuse information.
Performance and environmental accounting of nutrient cycling models to estimate nitrogen emissions in agriculture and their sensitivity in life cycle assessment
<p>Abstract</p> <p>Purpose</p> <p>Several models are available in the literature to estimate agricultural emissions. From life cycle assessment (LCA) perspective, there is no standardized procedure for estimating emissions of nitrogen or other nutrients. This article aims to compare four agricultural models (PEF, SALCA, Daisy and Animo) with different complexity levels and test their suitability and sensitivity in LCA.</p> <p>Methods</p> <p>Required input data, obtained outputs, and main characteristics of the models are presented. Then, the performance of the models was evaluated according to their potential feasibility to be used in estimating nitrogen emissions in LCA using an adapted version of the criteria proposed by the United Nations Framework Convention on Climate Change (UNFCCC), and other relevant studies, to judge their suitability in LCA. Finally, nitrogen emissions from a case study of irrigated maize in Spain were estimated using the selected models and were tested in a full LCA to characterize the impacts.</p> <p>Results and discussion</p> <p>According to the set of criteria, the models scored, from best to worst: Daisy (77%), SALCA (74%), Animo (72%) and PEF (70%), being Daisy the most suitable model to LCA framework. Regarding the case study, the estimated emissions agreed to literature data for the irrigated corn crop in Spain and the Mediterranean, except N<sub>2</sub>O emissions. The impact characterization showed differences of up to 56% for the most relevant impact categories when considering nitrogen emissions. Additionally, an overview of the models used to estimate nitrogen emissions in LCA studies showed that many models have been used, but not always in a suitable or justified manner.</p> <p>Conclusions</p> <p>Although mechanistic models are more laborious, mainly due to the amount of input data required, this study shows that Daisy could be a suitable model to estimate emissions when fertilizer application is relevant for the environmental study. In addition, and due to LCA urgently needing a solid methodology to estimate nitrogen emissions, mechanistic models such as Daisy could be used to estimate default values for different archetype scenarios.</p>
Life Cycle Modeling of Tech & Strategies for a Sustainable Freight System in California
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Data from: A life-cycle model of human social groups produces a u-shaped distribution in group size
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A novel cell culture system modeling the SARS-CoV-2 life cycle
GEO Series GSE162629. Homo sapiens; Severe acute respiratory syndrome coronavirus 2. 2 samples. Type: Expression profiling by high throughput sequencing.
Characterization Factors for Microplastic Emissions in Life Cycle Assessment Considering Multimedia Fate Modelling
<p>These data provide supporting information for a forthcoming publication proposing new <strong>Regionalized Characterization Factors for Microplastic Emissions in Life Cycle Assessment</strong>. </p> <p>The Characterization Factors (CFs) are developed thanks to a fate model based on SimpleBox4Plastics: https://doi.org/10.5281/zenodo.5743268 and adapted to meet the USEtox methodology. </p> <p>They are derived from the "Regionalized_CFs_for_MP_emissions_in_LCIA.ipynb" script available on GitHub at https://github.com/Julouve/Regionalized_Characterization_Factors_for_Microplastic_Emissions_in_LCIA.git</p> <p>The CFs are developed for 14 polymers (EPS, PP, LDPE, HDPE, PS, PAN, PHA, PA, PLA, strach blend, PBAT, PET, PVC, TRWP) at 5 sizes (1, 10, 100, 1000, 5000 μm) for 9 different regions (North America, Latin America, Europe, Africa & Middle East, Central Asia, Southeast Asia, Northern regions, Oceania, World) for 9 environmental compartments (air, lake water, river water, sea water, their sediment, natural soil, agricultural soil) on two scales (continental & global) and for 3 ecosystems (marine, freshwater and terrestrial). </p> <p>CFs are computed thanks to 2 approaches: a surface approach (in PDF*m2*year/kg) and a species approach (in PDF*year/kg or species*year/kg). </p> <p> </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.