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61 results for “life cycle assessment”
Long-term Performance and Life Cycle Assessment of Energy Piles in three Different Climatic Conditions_Dataset
<p>In this file it is possible to find the dataset linked to the related pubblication. In the file each spreadsheet corresponf to a picture of the paper.</p>
IMPACT World+ / a globally regionalized method for life cycle impact assessment
<p><strong>IMPACT World+</strong> is a life cycle impact assessment method which characterizes thousands of substances spanning across various compartments and sub-compartments of the environment. It differentiates 19 impact categories at midpoint level and 34 impact categories at damage level. For more information on IW+, refer to our <a href="https://www.impactworldplus.org/">website</a> and <a href="https://doi.org/10.1007/s11367-019-01583-0">scientific article</a>. For information on the updates of IMPACT World+, you can register to the <a href="http://eepurl.com/dEeeJL">newsletter</a> of CIRAIG.</p> <p>The v2.1 update is the biggest update of the IMPACT World+ method in many years as it introduces new impact categories and updates many models with the latest available research.</p> <p>IMPACT World+ comes in three interpretation levels: <em><strong>midpoint</strong></em>, <em><strong>expert</strong></em> and <em><strong>footprint</strong></em>. You can find explanations for these three interpretation levels <a href="https://www.impactworldplus.org/version-2-0-1/">here</a>.</p> <p>The <em><strong>expert</strong></em> and <em><strong>midpoint</strong></em> versions of IMPACT World+ also come with two different implementations regarding how to account for <strong>biogenic carbon</strong>. One with the traditional biogenic <em>carbon neutrality approach</em> (e.g., where biogenic carbon dioxide is set at 0 and biogenic methane is set at 27kgCO2eq for GWP100) and one including the uptake of biogenic carbon dioxide, where the release of biogenic carbon is therefore set at the same CFs as fossil carbon, but the uptake is with a negative sign, i.e., a <em>-1/+1 approach</em> for biogenic carbon (look for the files marked “(incl. CO2 uptake)”).</p> <p>While we provide the -<em>/+1 approach</em>, we must make it clear to the users that this approach is heavily dependent on the quality of the inventory you are using, and that there are still <strong>issues </strong>currently with the LCI databases (even in ecoinvent 3.10). Furthermore, if you are using this approach, you either <strong>MUST </strong>adopt a <em>cradle-to-grave </em>approach to both account for the uptake and release of biogenic carbon (otherwise you will only account for the uptake of the carbon and have skewed results) or if you adopt a <em>cradle-to-gate</em> approach because you need to provide results to someone downstream of your supply chain you <strong>MUST </strong>communicate with that downstream user to tell them that they should account for the release of biogenic carbon in a <em>-1/+1 approach</em> also, otherwise, you and your downstream user will <strong>double count the benefits</strong> of using biogenic products, which is incorrect. This is especially true is the case of food products where the carbon emissions post consumption are typically not included in the inventories, which could result in a substantial under estimation of the impacts of this product over its life cycle.</p> <h3>Description of the files</h3> <p>- The dev file is a file useful for developers and maintainers of databases/datasets who wish to link IW+ 2.1 to their databases/datasets. It regroups all existing characterization factors of the IW+ LCIA method in an Excel format, using the terminology of IW+.</p> <p>- The "ecoinvent" files are Excel files matching with "pure" ecoinvent and its flow name terminology (as in unaltered by various software) in an Excel table. This is useful if you are using ecoinvent outside of LCA software.</p> <p>- The exiobase file links IW+ to the <a href="https://doi.org/10.5281/zenodo.5589597">Exiobase GMRIO database</a>. Once the file is read through pandas (pandas.read_excel()), the resulting matrix can directly be multiplied to the environmental extensions of exiobase (S, F or F_Y if using the pymrio package).</p> <p>- The openLCA file can be directly imported in the openLCA software as a JSON-LD file.</p> <p>- The SimaPro file can be directly imported in the SimaPro software as a CSV file.</p> <p>- The brightway2 files are ecoinvent-version dependent, so you need to select the correct file to work with the correct version of ecoinvent. Else, some of the ecoinvent flows which name did change in between versions of ecoinvent would not be characterized, leading to underestimated results. To import a file, you need to pass through brightway2 itself (it cannot be done through the activity-browser for now). The function to import a .bw2package file is bw2.BW2Package.import_file().</p> <p>- Finally, the source file regroups all the native information used by IW+ to derive the characterization factors. This file is primarily useful for the IW+ internal team. It is provided for transparency, as well as for curious users or users who wish to generate all these files themselves through the <a href="https://github.com/CIRAIG/IWP_Reborn">open-access code of IW+</a>.</p> <h3>New indicators</h3> <p>- <em>Plastic physical effect on biota</em></p> <p>This new indicator measures the effect of plastic resins emitted in the water environments (both freshwater and marine) on biota, in PDF.m2.yr. It also comes with a midpoint indicator in CTUe. This indicator is the result of the work of the <a href="https://marilca.org/characterization-factors/">MariLCA working group</a>.</p> <p>- <em>Fisheries impact</em></p> <p>This new indicator measures the impact on biodiversity of fisheries activities. It is only assessed at the ecosystem quality damage level (in PDF.m2.yr). This is based on the work of <a href="https://doi.org/10.3390/su16093870">Stanford-Clark et al.</a></p> <p>- <em>Marine ecotoxicity</em></p> <p>In the v2.1 we decided to finally integrate these two ecotoxicity indicators, at the damage level only. These are based on an old version of Usetox (v2.02). As the v3 of Usetox is on the verge of being released, all ecotoxicity and toxicity categories will be updated in the next version of IW+.</p> <p>- <em>Terrestrial ecotoxicity</em></p> <p>In the v2.1 we decided to finally integrate these two ecotoxicity indicators, at the damage level only. These are based on an old version of Usetox (v2.02). As the v3 of Usetox is on the verge of being released, all ecotoxicity and toxicity categories will be updated in the next version of IW+.</p> <p>- <em>Photochemical ozone formation</em></p> <p>For this impact category, IW+ adopts what the ReCiPe methodology recommends. In their <a href="https://doi.org/10.1007/s11367-016-1246-y">2016 update</a>, ReCiPe renamed the indicator "Photochemical oxidant formation" to "Photochemical ozone formation". In addition, they calculated the impact of this category on ecosystem quality. There are thus two corresponding impact categories at damage level: "Photochemical ozone formation, human health" and "Photochemical ozone formation, ecosystem quality"</p> <h3>Updated indicators</h3> <p>- <em>All climate change indicators</em></p> <p>IMPACT World+ v2.1 proposes the carbon neutrality approach (i.e., CO2-bio = 0) as well as the -1/+1 approach (CO2-bio uptake = -1 / CO2-bio release = +1). However, the latter is only available in the expert and midpoint versions. In the footprint version, the carbon neutrality assumption is still being used.</p> <p>Furthermore, we added CFs for temporary storage of biogenic carbon that can be used (e.g., Correction for delayed emissions, carbon dioxide, biogenic).</p> <p>- <em>Climate change, human health</em></p> <p>In the v2.0.1, we updated the GWP100 and GTP100 indicators following the recommendations of the AR6 from the IPCC2021. Now in the v2.1, we are also updating our damage indicators for climate change to follow the AR6 recommendations. Notably, the cumulative AGTP500 used in the derivation of these CFs was recalculated with updated equations (which we obtained thanks to Yue He and Thomas Gasser from the International Institute for Applied Systems Analysis - IIASA). In addition, the effect factors were also updated. Previously it was based on data from the World Health Organization from 2003, it is now based on the WHO 2014 report as well as the <a href="https://backend.orbit.dtu.dk/ws/portalfiles/portal/329521472/PhD_Thesis_Lea_Rupcic.pdf">work of L</a><a href="https://backend.orbit.dtu.dk/ws/portalfiles/portal/329521472/PhD_Thesis_Lea_Rupcic.pdf">. </a><a href="https://backend.orbit.dtu.dk/ws/portalfiles/portal/329521472/PhD_Thesis_Lea_Rupcic.pdf">Rupcic</a>.</p> <p>- <em>Climate change, ecosystem quality</em></p> <p>Similarly to the human health indicator the cumulative AGTP500 were recalculated. However, the effect factor was not updated yet for this impact category.</p> <p>- <em>Particulate matter formation</em></p> <p>Those CFs were updated to the latest model from Fantke, et al. This is composed of a series of articles on updates to <a href="https://doi.org/10.1021/acs.est.7b02589">fate</a> and <a href="https://doi.org/10.1021/acs.est.9b01800">effect</a> factors</p> <p>This model now provides regionalized characterization factors per town of more than 100,000 inhabitants. The CFs at the town-level are available in the source file, but in the dev file and in the different software versions, we only provide national/regional (e.g., RER) as well as global values, aggregated from the town-level factors.</p> <p>- <em>Water availability, human health</em></p> <p>Those CFs were updated to the latest model of L. Debarre (2024) [<em>publication in review, link will be added once published</em>]. This model includes a harmonization of methodology between the domestic and agriculture water use, updates the exposition factors using the latest Gross National Income data and updates the EF. Overall, the values of the characterization factors of this category have dramatically decreased, by a minimum of 65%.</p> <p>- <em>Water availability, terrestrial ecosystems</em></p> <p>While the original value of the characterization was not updated (e.g., 0.21 PDF.m2.yr in Netherlands), the regionalization was updated based on an estimation of depths of groundwater, based on <a href="https://doi.org/10.1126/science.abc2755">Jasechko (2021)</a>.</p> <p>- <em>Water scarcity</em></p> <p>Those CFs were updated to the latest update of the AWARE model Seitfudem (2024) [<em>publication in review, link will be added once published</em>].</p> <p>- <em>Fossil and nuclear energy use</em></p> <p>The HHV values were updated to match the updated HHVs in ecoinvent.</p> <p>- <em>Ozone layer depletion</em></p> <p>Those CFs were adapted to match the latest data from the <a href="https://ozone.unep.org/sites/default/files/2023-02/Scientific-Assessment-of-Ozone-Depletion-2022.pdf">World Meteorological Organization (2022)</a>. In addition, the time horizon has now been extended to the infinite instead of limiting it to 500 years.</p> <h3>Methodology</h3> <p>For more detail on the methodology behind each impact category, refer to our <a href="https://github.com/CIRAIG/IWP_Reborn/tree/master/Methodology">Github</a>, in the future it will be available directly on our website.</p> <h3>Corrections</h3> <p>In this section we only provide information on the major corrections that were made. For a full report of all the changes please refer to out <a href="https://github.com/CIRAIG/IWP_Reborn/tree/master/Report_changes">Github</a>.</p> <p>- There are challenges associated with using IMPACT World+ files across databases or software for which they were not specifically designed. For instance, this is why we now provide files adapted to particular ecoinvent versions in brightway2. Similarly, both SimaPro and openLCA periodically update the names of their elementary flows. When an impact assessment method has previously been imported into one of these tools, an embedded procedure in their update processes is supposed to adjust the characterization factor names in line with the new flow names, ensuring compatibility with the updated list. However, we lack detailed knowledge of this procedure, meaning we cannot guarantee that the updated versions of IW+ in these tools would align with our specific modeling choices. Likewise, the IW+ versions we provide for a given release of SimaPro or openLCA might be incompatible with previous or subsequent versions due to discrepancies in flow names and characterization factors. Consequently, users of these software should verify which flows are characterized and make adjustments if necessary.</p> <p>- Harmonization of regionalized flows</p> <p>Regionalized impact model do not operate at the same geographical granularity. In the previous version, some flows were characterized in one impact category but not in the other. For instance, the flow "Water, lake, US-TRE" was characterized for the "water scarcity" indicator but not for "Water availability, human health". All regionalized flows are now characterized for all the impact categories they affect. This is also true for the newest regionalized impact category (Particulate matter formation) where SO<sub>2</sub> for example is regionalized at a much more granular level than in the freshwater acidification impact category.</p> <p>- Fossil and nuclear energy use</p> <p>For the SimaPro version of the v2.0.1, some flows that only exist in SimaPro were not characterized, such as "Oil, crude, 43.4 MJ per kg". Now they are properly characterized using the energy content value specified in the name. Results obtained with SimaPro will thus differ from results obtained with brightway2 and openLCA, since the latter do not use such flows and only use flow such as "Oil, crude".</p> <p>- Thermally polluted water</p> <p>In the v2.0.1, the flows "Water, turbine use, unspecified natural origin" were not linked to the correct proxy, which meant they did not impact the Thermally polluted water category, which underestimated the impact of this category.</p> <p>- The problem of "Nitrogen"</p> <p>"Nitrogen" can mean two different things. It can literally mean the "N" element, but it can also mean the "N2" molecule. The issue is that it is not clear in the LCI databases, which meaning does "Nitrogen" have. Previously, our understanding was that "Nitrogen" meant "N" but since then, ecoinvent notably, added formulas to the elementary flows they provide and associated the formula "N2" to their "Nitrogen" flows, indicating that they understand it as "N2" and not "N". Furthermore, in SimaPro and openLCA, the associated CAS number is generally "7727-37-9" which again corresponds to "N2". Thus, we now consider that “Nitrogen” represents dinitrogen, and thus does not impact the "Marine eutrophication" impact category anymore. We also corrected a previous mistake: N<sub>2</sub>O is not characterized anymore for this impact category.</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>
Datasets and OpenLCA foreground data processes for the article: Understanding environmental trade-offs and resource demand of direct air capture technologies through comparative life-cycle assessment
<p>This data set contains the supplementary data sets (1-3) and exported foreground data processes from OpenLCA for the manuscript “Understanding environmental trade-offs and resource demand of direct air capture technologies through comparative life-cycle assessment”, submitted to Nature Energy.</p> <p>This repository contains:</p> <ul> <li>Supplementary data set 1: Ancillary calculations and numerical values for HT-Aq DAC</li> <li>Supplementary data set 2: Ancillary calculations and numerical values for TSA DAC</li> <li>Supplementary data set 3: Ancillary calculations and numerical values shown in plots and table 3</li> <li>Foreground data from OpenLCA. OpenLCA process model for different cases of HT-Aq DAC and TSA DAC. To re-run the LCA calculations, OpenLCA (freeware) and the Ecoinvent 3.5 database (license required) need to be installed on a standard desktop computer or laptop with at least 8 GB RAM.</li> </ul>
Life Cycle Assessment of the LiftWEC Design Dataset
<p>The Life Cycle Assessment Dataset contains data used to perform the cradle to grave LCA methodology to quantify the carbon and energy intensity of the proposed device configuration.<br> The dataset includes input data obtained through a combination of project partner contributions, peer-reviewed literature, and pre-existing databases, as well as results of environmental impacts found through the application of LCA techniques in the SimaPro tool and using Ecoinvent database.<br> These data were compiled and used to conduct a LCA of the LiftWEC device in Work Package 9, to evaluate and inform device design choices. The findings of this assessment were presented as part of Task 9.4 and included in Deliverable D9.4, titled "Life Cycle Assessment of the LiftWEC Design.</p>
Data set for the journal article: Social life cycle assessment of green methanol and benchmarking against conventional fossil methanol
<p>Single File containing:</p> <ul> <li>Green Methanol Inventories: numerical data as displayed in Figure 4, Main social life cycle inventory data of the green methanol system. </li> <li>Conventional Methanol Inventories: numerical data as displayed in Figure 5, Main social life cycle inventory data of the conventional methanol system. </li> <li>Supplementary information: Diagrams and tables describing teh flowsheet of the simulations used in this work: <ul> <li> <p>Green methanol production process (flowsheet and stream table)</p> </li> <li> <p>Syngas production through Steam Methane Reforming (flowsheet and stream table)</p> </li> <li> <p>Conventional methanol production process (flowsheet and stream table)</p> </li> </ul> </li> </ul>
Towards alternative solutions for flaring : life cycle assessment and carbon substance flow analysis of associated gas conversion into C3 chemicals
<p>Supplementary material and used data for the publication.</p>
START Workshop - Use of Life Cycle Assessment as an Environmental Impact Tool
<p>Video from an internal workshop on Life Cycle Assessment that was held in June 2023 by 3drivers (speakers were Eduardo Santos and Ana Braga) as a basic training for other consortium members, with the goal of creating a common ground among partners for the subsequent environmental impact assessment activities that START will carry out on the thermoelectric solutions that will be delivered.</p> <p>The video is related to the general introduction given by E. Santos on the basics of the LCA approach and applications. It may be useful to you if new to the topic.</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>
Raw NMR and GC reports for the article Electrochemical Hydrogenation of Alkenes over a Nickel Foam Guided by Life Cycle, Safety and Toxicological Assessments, Green Chemistry, doi: https://doi.org/10.1039/D4GC02924K
<p>Raw NMR for the article Electrochemical Hydrogenation of Alkenes over a Nickel Foam Guided by Life Cycle, Safety and Toxicological Assessments, Green Chemistry, doi: https://doi.org/10.1039/D4GC02924K</p> <p>The raw NMR data files for all compounds reported in the article are included. The numbering corresponds to those in the article.</p> <p>Each parent folder contains subfolders with different files. In order to process this data, the full parent folder must be dragged into either Mestrenova or Topspin and then the data is automatically processed. If the name of the raw data files are renamed, the software (<a href="https://mestrelab.com/" target="_blank" rel="noopener noreferrer">Mestrenova</a> or <a href="https://www.bruker.com/en/products-and-solutions/mr/nmr-software/topspin.html" target="_blank" rel="noopener noreferrer">Topspin</a>) will not be able to process the files</p> <p> </p>
A critical perspective on uncertainty appraisal and sensitivity analysis in life cycle assessment - supporting material
<p>Publication dataset - A critical perspective on uncertainty appraisal and sensitivity analysis in life cycle assessment (<em>accepted for publication in the Journal of Industrial Ecology</em>).</p>
Codes and data for the article: Biodiversity on the Line: Life Cycle Impact Assessment of Power Lines on Birds and Mammals in Norway
<p>This repository contains all input data required to run the habitat conversion, collision, and electrocution LCIA models and reproduce the results, as well as all output data generated in various formats. The models are described in the paper "Biodiversity on the Line: Life Cycle Impact Assessment of Power Lines on Birds and Mammals in Norway" (https://doi.org/10.1088/2634-4505/ad5bfd).</p> <p>"The files "01_Get_GBIF_points.R, "02_SDMs_maxent.R" describe how to create the species distribution maps.</p> <p>"03_Data_preparation.R", "04_Pylon_cleaning.py" are to prepare and modify the raw data for the analysis. The raw data are not provided, yet links to the sources are provided either in the R codes or the paper.</p> <p>To run the models, run the "05_SHR_modelling.R" and "06_Collision_electrocution_models.R" files.</p> <p>To calculate characterization factors, run the "07_Characterisation_factors.R" file.</p> <p>To export the tables in the Supporting Information 1, run the file "08_Supporting_Information.R".</p> <p>Finally, the file "09_Sensitivity_analysis.R" performs the sensitivity analyses.</p>
A Comprehensive Framework for Life-Cycle Cost Assessment of Reinforced Concrete Bridge Decks
<p>Corresponding data set for Tran-SET Project No. 18STOKS02. Abstract of the final report is stated below for reference:</p> <p>"Various environmental and mechanical stressors cause deterioration of concrete bridge decks. Normal wear and tear, freeze and thaw cycles, and chloride penetration due to deicing salts can cause aggressive deterioration that usually require frequent interventions during the life-cycle of the bridge. These interventions include deck maintenance and repairs (e.g., application of sealers or overlay placement) as well as bridge deck replacement. The quantification of the life-cycle cost of bridge decks considering maintenance and repair activities represents a significant challenge facing local and state transportation agencies. The life-cycle maintenance activities not only increase the direct life-cycle cost of the bridge, but they also lead to significant indirect user costs due to increasing traffic delays, work zone crashes, and operating cost. Moreover, these traffic delays increase the carbon footprint of the bridge and adversely affect the life-cycle bridge sustainability. Accordingly, the proper quantification of indirect costs associated with life-cycle bridge management activities including maintenance, repair, and rehabilitation activities is of paramount importance. The research attempts to fill in the knowledge gaps in quantifying the indirect costs associated with bridge deck maintenance activities and their impact on the overall bridge life-cycle cost."</p>
Supporting material: Prospective life-cycle assessment of sustainable alternatives for road freight transport
<p><span>This study investigates decarbonization pathways for the road freight transport sector</span><span> </span><span>by evaluating three alternatives to conventional</span><span> </span><span>diesel trucks:</span><span> </span><span>trucks powered by biofuels, battery electric trucks, and fuel cell trucks with hydrogen</span><span>. A prospective life cycle assessment of these options is conducted under two policy scenarios for decarbonization across 12 distinct regions over the century. Employing a cradle-to-grave approach, the assessment covers activities from fuel and electricity production to the end-of-life of truck components. Findings reveal that, in eight of the 12 regions examined, an early transition to battery electric trucks could increase life-cycle greenhouse gas emissions by up to 70% by 2030 compared to the continued use of conventional diesel trucks, underscoring the significance of liquid fuels for short to medium-term decarbonization. However, in the long term, as electricity mixes and hydrogen production are decarbonized, battery electric trucks and hydrogen fuel cell trucks emerge as superior alternatives in all regions, emitting, at least, 29% less greenhouse gases than trucks powered by biofuels, and 45% less than diesel trucks.</span><span> </span><span>The optimal transition from conventional diesel trucks to trucks powered by biofuels and, subsequently, to battery electric trucks and/or hydrogen could avoid 134-204 Gt CO<sub>2-eq</sub> worldwide and prevent a temperature rise of 0.22-0.33°C compared to the diesel-based scenario. This emphasizes the crucial role of appropriate policies for the timely transformation of the road freight transport sector. </span></p>
Archetype-based Life-Cycle Assessment of National Residential Building Stocks: Resource Use and Greenhouse Gas Emissions in Western Asia and Northern Africa
<p><strong>Dataset Name:</strong><br><em>Literature Data and Archetype Parameter Sheets for the publication, named Archetype-based Life-Cycle Assessment of National Residential Building Stocks: Resource Use and Greenhouse Gas Emissions in Western Asia and Northern Africa.</em></p> <p><strong>Description:</strong><br>This dataset includes Excel sheets containing literature sources and archetypal data on Western Asian and North African countries' residential dwelling typologies. As well as Vacancy rates used and simulation results.</p> <p><strong>Files:</strong><br>The following files are included in the dataset:</p> <ul> <li> <em>[CountryName]_LiteratureSources.xlsx:</em> Excel sheet containing literature sources and references,</li> <li> <em>[CountryName]_ArchetypeParameters.xlsx</em>: Archetype models' semantic, geometric, and technical data used in the generation of energy models,</li> <li><em> VacantHouses.xlsx</em>: Vacant house rates for the countries, the found articles on the web, literature sources, etc.,</li> <li> <em>Resource Use Results:</em> BuildME Simulation Results</li> </ul> <p><strong>Usage:</strong><br>The dataset is intended for researching and analyzing the Western Asian and North African countries' residential buildings. The literature sources included in the [CountryName]_LiteratureSources.xlsx and [CountryName]_ArchetypeParameters.xlsx files can be used to verify, support, or reproduce the research findings.</p> <p><strong>License:</strong><br>The dataset is licensed under Creative Commons Attribution 4.0 International.</p> <p><strong>Citation:</strong><br>If you use this dataset in your research, please cite it as follows and contact the corresponding author:</p> <p>Akin, Sahin, Aida Eghbali, Chibuikem Chrysogonus Nwagwu, and Edgar Hertwich. 2024. “Archetype-based Life-Cycle Assessment of National Residential Building Stocks: Resource Use and Greenhouse Gas Emissions in Western Asia and Northern Africa” https://doi.org/10.5281/zenodo.13380340.</p> <p><strong>Contact:</strong><br>The archetypes' energy models (DesignBuilder or IDF files) can be provided on request. If you have any questions or comments about the dataset, please contact <strong>sahin.akin@ntnu.no, the corresponding author.</strong></p>
Novel Endpoint Characterization Factors for Life Cycle Impact Assessment of Terrestrial Acidification
<p>This repository contains Excel files with the characterization factorsand the soil response factors for the publication entitled "Novel Endpoint Characterization Factors for Life Cycle Impact Assessment of Terrestrial Acidification", published in the "Journal of Ecological Indicators" .<br><br></p> <p>Content:</p> <p><strong>Datasets.zip</strong> is an folder containing the following Excel files: </p> <ul> <li><strong>CF_Terrestrial_Acidification_2024-08-01.xlsx</strong> with the following sheets <ul> <li><em>Dataframe</em> gathering terrestrial acidification marginal endpoint CF [PDF.yr/kg_emitted] values at country level (with the world average value), for 3 acidifying substances (NOx, NHx, SOx) at global and regional impact scales (with and without the inclusion of the Global Extinction Probability - GEP - respectively)</li> <li><em>Calc Info</em> summing up calculation informations</li> <li><em>Calc Table</em> registering input parameters used to run the calculations leading to the <em>Dataframe</em> sheet (substance used, original and adapted resolutions for emission and deposition compartments, resolutions for each CF components and spatial transformations, GEP normalization method)</li> </ul> </li> <li><strong>RF_NO3_2024-03-27.xlsx</strong> with the following sheet:<br> <ul> <li><em>RFs</em> containing the soil response values [(molH+ / L).(yr / kg_dep)] at ecoregion level (referred to as "idTarget") for a marginal increase of 10% in NO3 deposition rate. It also gathers the intermediate results leading the final RFs (sustances' deposition rates, reference and post-deposition increase pHs) </li> </ul> </li> <li><strong>RF_NH4_2024-03-25.xlsx</strong> with the following sheet:<br> <ul> <li><em>RFs</em> containing the soil response values [(molH+ / L).(yr / kg_dep)] at ecoregion level (referred to as "idTarget") for a marginal increase of 10% in NH4 deposition rate. It also gathers the intermediate results leading the final RFs (sustances' deposition rates, reference and post-deposition increase pHs)</li> </ul> </li> <li><strong>RF_SO4_2024-03-25.xlsx</strong> with the following sheet:<br> <ul> <li><em>RFs</em> containing the soil response values [(molH+ / L).(yr / kg_dep)] at ecoregion level (referred to as "idTarget") for a marginal increase of 10% in SO4 deposition rate. It also gathers the intermediate results leading the final RFs (sustances' deposition rates, reference and post-deposition increase pHs)</li> </ul> </li> </ul>
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>
Life-Cycle Inventory (LCI) For the comparative Life-Cycle Assessment of a restoration and renovation of a traditional Danish farmer house
<p>This document provides the Life-Cycle Inventory of the study comparing the environmental performance of the restoration (Scenario 1, also mentioned as "S1") or renovation (Scenario 2, "S2") of a traditional Danish farmer house. The LCI is used as input for the life-cycle impact assessment phase in the LCA where the inputs and outputs of elementary flows in the LCI are characterized as potential impacts on the environment. The LCI is based on primary data from the "Apprentices' House" combined with secondary data from materials specific environmental product declaration and the large LCI database ecoinvent v3.</p> <p> </p> <p>The file contains several spreadsheets organized as follows:</p> <p>Thicknesses,S1 - Reports the materials and their corresponding thicknesses used for walls, ceilings, floors and insulation in S1</p> <p>Thicknesses, S1b - Reports the materials and their corresponding thicknesses used for walls, ceilings, floors and insulation in S1b</p> <p>Thicknesses, S1c - Reports the materials and their corresponding thicknesses used for walls, ceilings, floors and insulation in S1c</p> <p>Thicknesses, S2 - Reports the materials and their corresponding thicknesses used for walls, ceilings, floors and insulation in S2</p> <p>Surfaces - Reports the area of all surfaces of the house (walls, ceilings, floors) for all scenarios. </p> <p>Bill of materials - Sums up the list and quantity of all the materials used in all scenarios, providing details as to the quantity kept from the actual house, as well as the new input and output of materials during the restoration/renovation</p> <p>Heat loss, S1 - Provides details for the calculation of heat loss through the building envelope of the house in Scenario 1</p> <p>Heat loss, S1b - Provides details for the calculation of heat loss through the building envelope of the house in Scenario 1b</p> <p>Heat loss, S1c - Provides details for the calculation of heat loss through the building envelope of the house in Scenario 1c</p> <p>Heat loss, S2 - Provides details for the calculation of heat loss through the building envelope of the house in Scenario 2</p> <p>Parameters - Describes the main parameters used in the LCI and their corresponding uncertainty</p> <p>LCI Materials - Provides the full breakdown of the processes created and used for the LCI modelling on OpenLCA</p> <p>LCI Building - Provides the full breakdown of the processes created and used for the LCI modelling on OpenLCA</p>
Supporting Information - Fabbri et al. 2022 - Evaluation of sugar feedstocks for bio-based chemicals: A consequential, regionalized life cycle assessment
<p>The supporting information of the journal article "Evaluation of sugar feedstocks for bio-based chemicals: A consequential, regionalized life cycle assessment" from Fabbri et al. (2022) includes one file with the following content:</p> <p>S1 Details of consequential modelling: feedstock<br> S1.1 Identification type of changes (demand or supply)<br> S1.2 Identification of constrains in the market<br> S1.3 Identification of product substitutions<br> S1.4 Identification of affected production technology<br> S1.5 Identification of marginal crop and marginal supplier<br> S2 Details of consequential modelling: by-products<br> S3 Model parameters and unit processes<br> S3.1 Sugar beet<br> S3.2 Sugar cane<br> S3.3 Wheat<br> S3.4 Maize<br> S3.5 Wood<br> S3.6 Residual woodchips and sawdust<br> S4 Review of land use change accounting methods<br> S4.1 Direct land use change (dLUC)<br> S4.2. Indirect land use change (iLUC)<br> S5 Additional results<br> S5.1 Influence of spatial differentiation in LCIA<br> S5.2 Influence of indirect land use change (iLUC)<br> S6 References</p>
Social Life Cycle Assessment Video
<p>A set of explanatory videos was produced about sustainability analysis within the project, including Environmental Life Cycle Assessment, Social Life Cycle Assessment, and Life Cycle Costing. These informational videos were primarily produced for the International School on Water Reuse held at the Chemistry Department of the Torino University in Italy in late September 2022, but they were also placed on the project website and circulated on social media.</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.