Life Cycle Assessment (LCA) is a compilation and evaluation of the inputs, outputs and potential environmental impacts of a product system throughout its life cycle. LCA describes the life cycle as consecutive and interlinked stages of a product system extending from the acquisition of raw materials through materials processing, technology manufacturing/construction, technology use/maintenance/upgrade, and the technology retirement. LCA also provides a framework for understanding economic and social impacts. In an LCA, data are collected at the unit process level, intended to represent a single industrial activity, in this case the food and agriculture industry. Each single industrial activity (a) produces product and sometimes co-products; (b) uses resources from the environment; (c) uses resources from other unit processes in the technosphere; and (d) generates emissions to the environment. In an LCA, the inventory analysis combines unit process data for the life cycle and the impact assessment estimates the impact associated with activities and flows to and from the environment for the inventory. Datasets have been developed for the LCA Commons in response to a national need for data representing US operations. The LCA Commons database is an open access database developed by the United States Department of Agriculture (USDA) National Agricultural Library (NAL) for use in LCAs to support policy assessment, technology implementation decision-making, and publicly disclosed comparative product or technology assertions. K7612-17: Photo by Scott Bauer; http://www.ars.usda.gov/is/graphics/photos/sep97/k7612-17.htm Resources in this dataset:Resource Title: LCA Commons website. File Name: Web Page, url: https://www.lcacommons.gov/

The global Life Cycle Assessment (LCA) Database market size is projected to reach USD 247.4 million by 2033, exhibiting a CAGR of 12.1% during the forecast period. The increasing demand for sustainable products and services, along with stringent environmental regulations, is driving the growth of the market. Additionally, the growing adoption of LCA in various industries, such as manufacturing, construction, and transportation, is contributing to the market's expansion. The on-premise segment held a dominant market share in 2025, owing to the high cost of cloud-based solutions and the need for data security and control among enterprises. Key trends influencing the market include the rise of Industry 4.0 technologies, which enable real-time data collection and analysis, and the increasing adoption of cloud-based LCA platforms, which offer flexibility and scalability. However, the high cost of LCA software and the lack of trained professionals may pose challenges to the market's growth. Key players in the market include GHG Protocol, Ecochain, Sphera, openLCA Nexus, AssessCCUS, Ecoinvent, openLCA, Swedish Life Cycle Center, Psilca, Fraunhofer IBP, Metsims - Sustainability Consulting, and Carbon Minds. North America and Europe are expected to remain the dominant regional markets, driven by the presence of a large number of environmental regulations and the growing demand for sustainable products and services in these regions.

Hybrid LCA database generated using ecoinvent and EXIOBASE, i.e., each process of the original ecoinvent database is added new direct inputs (coming from EXIOBASE) deemed missing (e.g., services). Each process of the resulting hybrid database is thus not (or at least less) truncated and the calculated lifecycle emissions/impacts should therefore be closer to reality. For license reasons, only the added inputs for each process of ecoinvent are provided (and not all the inputs). Why are there two versions for hybrid-ecoinvent3.5? One of the version corresponds to ecoinvent hybridized with the normal version of EXIOBASE and the other is hybridized with a capital-endogenized version of EXIOBASE. What does capital endogenization do? It matches capital goods formation to the value chains of products where they are required. In a more LCA way of speaking, EXIOBASE in its normal version does not allocate capital use to value chains. It's like if ecoinvent processes had no inputs of buildings, etc. in their unit process inventory. For more detail on this, refer to (Södersten et al., 2019) or (Miller et al., 2019). So which version do I use? Using the version "with capitals" gives a more comprehensive coverage. Using the "without capitals" version means that if a process of ecoinvent misses inputs of capital goods (e.g., a process does not include the company laptops of the employees), it won't be added. It comes with its fair share of assumptions and uncertainties however. Why is it only available for hybrid-ecoinvent3.5? The work used for capital endogenization is not available for exiobase3.8.1. How do I use the dataset? First, to use it, you will need both the corresponding ecoinvent [cut-off] and EXIOBASE [product x product] versions. For the reference year of EXIOBASE to-be-used, take 2011 if using the hybrid-ecoinvent3.5 and 2019 for hybrid-ecoinvent3.6 and 3.7.1. In the four datasets of this package, only added inputs are given (i.e. inputs from EXIOBASE added to ecoinvent processes). Ecoinvent and EXIOBASE processes/sectors are not included, for copyright issues. You thus need both ecoinvent and EXIOBASE to calculate life cycle emissions/impacts. Module to get ecoinvent in a Python format: https://github.com/majeau-bettez/ecospold2matrix (make sure to take the most up-to-date branch) Module to get EXIOBASE in a Python format: https://github.com/konstantinstadler/pymrio (can also be installed with pip) If you want to use the "with capitals" version of the hybrid database, you also need to use the capital endogenized version of EXIOBASE, available here: https://zenodo.org/record/3874309. Choose the pxp version of the year you plan to study (which should match with the year of the EXIOBASE version). You then need to normalize the capital matrix (i.e., divide by the total output x of EXIOBASE). Then, you simply add the normalized capital matrix (K) to the technology matrix (A) of EXIOBASE (see equation below). Once you have all the data needed, you just need to apply a slightly modified version of the Leontief equation: (\begin{equation} \textbf{q}^{hyb} = \begin{bmatrix} \textbf{C}^{lca}\cdot\textbf{S}^{lca} & \textbf{C}^{io}\cdot\textbf{S}^{io} \end{bmatrix} \cdot \left( \textbf{I} - \begin{bmatrix} \textbf{A}^{lca} & \textbf{C}^{d} \ \textbf{C}^{u} & \textbf{A}^{io}+\textbf{K}^{io} \end{bmatrix} \right) ^{-1} \cdot \left( \begin{bmatrix} \textbf{y}^{lca} \ 0 \end{bmatrix} \right) \end{equation}) qhyb gives the hybridized impact, i.e., the impacts of each process including the impacts generated by their new inputs. Clca and Cio are the respective characterization matrices for ecoinvent and EXIOBASE. Slca and Sio are the respective environmental extension matrices (or elementary flows in LCA terms) for ecoinvent and EXIOBASE. I is the identity matrix. Alca and Aio are the respective technology matrices for ecoinvent and EXIOBASE (the ones loaded with ecospold2matrix and pymrio). Kio is the capital matrix. If you do not use the endogenized version, do not include this matrix in the calculation. Cu (or upstream cut-offs) is the matrix that you get in this dataset. Cd (or downstream cut-offs) is simply a matrix of zeros in the case of this application. Finally you define your final demand (or functional unit/set of functional units for LCA) as ylca. Can I use it with different versions/reference years of EXIOBASE? Technically speaking, yes it will work, because the temporal aspect does not intervene in the determination of the hybrid database presented here. However, keep in mind that there might be some inconsistencies. For example, you would need to multiply each of the inputs of the datasets by a factor to account for inflation. Prices of ecoinvent (which were used to compile the hybrid databases, for all versions presented here) are defined in €2005. What are the weird suite of numbers in the columns? Ecoinvent processes are identified through unique identifiers (uuids) to which metadata (i....

Life Cycle Assessment (LCA) is a compilation and evaluation of the inputs, outputs and potential environmental impacts of a product system throughout its life cycle. LCA describes the life cycle as consecutive and interlinked stages of a product system extending from the acquisition of raw materials through materials processing, technology manufacturing/construction, technology use/maintenance/upgrade, and the technology retirement. LCA also provides a framework for understanding economic and social impacts. In an LCA, data are collected at the unit process level, intended to represent a single industrial activity, in this case the food and agriculture industry. Each single industrial activity (a) produces product and sometimes co-products; (b) uses resources from the environment; (c) uses resources from other unit processes in the technosphere; and (d) generates emissions to the environment. In an LCA, the inventory analysis combines unit process data for the life cycle and the impact assessment estimates the impact associated with activities and flows to and from the environment for the inventory. Datasets have been developed for the LCA Commons in response to a national need for data representing US operations. The LCA Commons database is an open access database developed by the United States Department of Agriculture (USDA) National Agricultural Library (NAL) for use in LCAs to support policy assessment, technology implementation decision-making, and publicly disclosed comparative product or technology assertions.

This document provides instructions for editing and submitting unit process or product system models to the USDA LCA Commons life cycle inventory (LCI) database. The LCA Commons LCI database uses the openLCA life cycle modeling tool's database schema. Therefore, this document describes how to import and edit data in openLCA and name and classify flows such that they properly import into and operate in the database. This document also describes metadata or documentation requirements for posting models to the LCA Commons. This document is an evolving standard for LCA Commons data. As USDA-NAL continues to gain experience in managing a general purpose LCI database and global conventions continue to evolve, so too will the LCA Commons Submission Guidelines. Resources in this dataset:Resource Title: LCA Commons Submission Guidelines_12/09/2015. File Name: lcaCommonsSubmissionGuidelines_Final_2015-12-09.pdf

This study investigates uncertainties in greenhouse gas (GHG) emission factors related to switchgrass-based biofuel production in Michigan. Using three life cycle assessment (LCA) databases— US lifecycle inventory database (USLCI), GREET, and Ecoinvent—each with multiple versions, we recalculated the global warming intensity (GWI) and GHG mitigation potential in a static calculation. Employing Monte Carlo simulations along with local and global sensitivity analyses, we assess uncertainties and pinpoint key parameters influencing GWI. The convergence of results across our previous study, static calculations, and Monte Carlo simulations enhances the credibility of estimated GWI values. Static calculations, validated by Monte Carlo simulations, offer reasonable central tendencies, providing a robust foundation for policy considerations. However, the wider range observed in Monte Carlo simulations underscores the importance of potential variations and uncertainties in real-world applications. Sensitivity analyses identify biofuel yield, GHG emissions of electricity, and soil organic carbon (SOC) change as pivotal parameters influencing GWI. Decreasing uncertainties in GWI may be achieved by making greater efforts to acquire more precise data on these parameters. Our study emphasizes the significance of considering diverse GHG factors and databases in GWI assessments and stresses the need for accurate electricity fuel mixes, crucial information for refining GWI assessments and informing strategies for sustainable biofuel production.

Supplementary Data 2. Ranking of impacts by impact category and methods in the ten most commonly served commodities in NSLP. This table is provided as an excel file. To construct this table, we first identified the ten most commonly served commodities in the NSLP. We then assessed the environmental impacts of these commodities using various combinations of impact assessment methods and databases. A list of the methods and database combinations is available below as SI Table 7. We then ranked the impacts of each commodity from 1 to 10 within each of the methods/database combinations. For example, using the World Food LCA Database version 3.5 and Product Environmental Footprint (PEF) impact assessment methods in Simapro, we assessed the climate impacts of producing 1 kg of apples and 1 kg of beef. Rankings were determined for each food within a given method/database combination. For this example, the rank of apple for climate impact was 2 and the rank of beef was 10. Rankings were compared using the standard deviation of rankings for each commodity and across impact categories.

In the SHARP-ID, environmental impact assessment was based on attributional life cycle analyses using environmental indicators greenhouse gas emission (GHGE) and land use (LU). Life cycle inventory data of 182 primary products were combined with data on production, trade and transport, and adjusted for consumption amount using conversions factors for production, edible portion, cooking losses and gains, and for food losses and waste in order to derive estimates of GHGE and LU for the foods as eaten. Towards a public database for environmental sustainability SHARP-ID Towards a public database for environmental sustainability

This material is part of the free Environmental Performance in Construction (EPiC) Database. The EPiC Database contains embodied environmental flow coefficients for 250+ construction materials using a comprehensive hybrid life cycle inventory approach.Water is used in significant quantities for construction activities, site preparation and as a material additive/solvent. It is also essential for all known forms of life on earth. Although water covers approximately 70% of the earth's surface, only a small proportion is readily available for use in construction projects. With a growing population, and increasing demand for housing, construction and infrastructure projects, water is becoming an increasingly scarce resource.

This material is part of the free Environmental Performance in Construction (EPiC) Database. The EPiC Database contains embodied environmental flow coefficients for 250+ construction materials using a comprehensive hybrid life cycle inventory approach.Concrete is a composite material combining sand or other fine aggregates, coarse aggregates, a binder and water. Portland cement is the most commonly used binder, however other binders, such as polymers, may also be used. Supplementary Cementitious Materials (SCM) such as Fly Ash and Ground, Granulated Blast Furnace Slag (GGBFS), are also commonly used as a part replacement for Portland cement. Additives, such as plasticisers can be added to the mix to control concrete properties, such as workability. Concrete is usually combined with steel reinforcement to improve tensile strength.Concrete is one of the most commonly used construction materials. It is highly durable and is thus typically used for structural elements in buildings and infrastructure projects. Concrete can be manufactured to meet a variety of strength grades. Concrete 40 MPa is commonly used in commercial and civil construction, for structural beams and columns, where increased durability and load-bearing capacity are required.

This study presents the development of a novel ecodesign approach based on a parametric life cycle assessment (LCA). The developed method allows for the comparison of environmental impacts of a vast number of different product configurations, which are derived automatically by determining every possible combination of the given design options. The life cycle model features a stochastic failure and repair simulation to account for a wide range of use cases as well as a recycling simulation that can determine the environmentally optimal recycling route. The developed method is tested on an exemplary case study of a smartphone. Despite efficiency limitations of the accompanying software tool prototype that was developed and used for the case study, it could be shown that the method allows to identify the environmental influence of different design options as well as the product configuration with the least annual global warming potential.

This file contains the database Excel file with data and calculations on failure and repair statistics, material compositions, and input tables for the software tool prototype developed in the study. It can be inspected as is to understand the underlying data and procedure presented in the study or used as an input for the Python source code to run the LCA model, which can be found here: https://zenodo.org/doi/10.5281/zenodo.10617863

Note: References to licensed environmental datasets from the Sphera and ecoinvent databases have been deleted in the published version. In order to run the software tool, please add the respective values for the Global Warming Potential (or alternative impact categories) in the "processes_data" sheet and delete the suffix "_noLCIA" from the file name.

This material is part of the free Environmental Performance in Construction (EPiC) Database. The EPiC Database contains embodied environmental flow coefficients for 250+ construction materials using a comprehensive hybrid life cycle inventory approach.Steel is a ferrous metal and is an alloy of iron and carbon, as well as potential other elements. It has a very high tensile strength. Steel has been used in the construction industry for over a century. Stainless steel is extremely resistant to corrosion.The core material for making steel is iron, which is found in iron ore. Iron is extracted from iron ore in blast furnaces through the smelting process, while controlling for the content of carbon. To render the steel stainless, chromium is needed and is typically added as stainless steel scraps. The molten steel is usually further processed before being extruded into its final shape.Steel is commonly used in the construction industry, mainly as a structural material. Extruded stainless steel can be used to produce a range of tubes for structural and finishing purposes as well as pipes.

In the SHARP-ID, environmental impact assessment was based on attributional life cycle analyses using environmental indicators greenhouse gas emission (GHGE) and land use (LU). Life cycle inventory data of 182 primary products were combined with data on production, trade and transport, and adjusted for consumption amount using conversions factors for production, edible portion, cooking losses and gains, and for food losses and waste in order to derive estimates of GHGE and LU for the foods as eaten.

ReCiPe2016 (Huijbregts 2017) is a life cycle impact assessment (LCIA) method. LCIA methods are collections of characterization factors, which are measures of relative potency or potential impact, for a given flow (e.g., NH3 to air) for a set of impact categories (e.g., acidification), provided in units of potency or impact equivalents per unit mass of the flowable associated with a given context (e.g., 1.88 kg SO2 eq/kg NH3 emitted to air). LCIA methods are typically used along with life cycle inventory data to estimate potential impacts in life cycle assessment (LCA). ReCiPe2016 produces 18 midpoint indicators and 3 endpoint indicators, and both midpoint and endpoint are provided using Individualist (I), Hierarchist (H), and Egalitarian (E) cultural perspectives.The FEDEFL or Federal LCA Commons Elementary Flow List (EPA 2019) is the standardized elementary flow list for use with data meeting the US Federal LCA Commons data guidelines.In this dataset, ReCiPe2016 is applied to FEDEFL v1.2.3 flows. This dataset was created by the LCIA Formatter v1.1.3 (https://github.com/USEPA/LCIAformatter). The LCIA Formatter is a tool for providing standardized life cycle impact assessment methods with characterization factors transparently applied to flows from an authoritative flow list, like the FEDEFL. The LCIA Formatter draws from the original ReCiPe2016 source file and the ReCiPe2016 to FEDEFL flow mapping. The LCIA formatter accesses this mapping file through the fedelemflowlist tool (https://github.com/USEPA/fedelemflowlist). Where a flow context is less specific in the FEDEFL (e.g., air) relative to the ReCiPe2016 flow contexts (e.g., air/rural), the LCIA Formatter applies the average of the relevant characterization factors from ReCiPe2016 to the FEDEFL flow.The zip files are a compressed archive of JSON files following the openLCA schema (https://greendelta.github.io/olca-schema). A separate .zip file is provided for each combination of indicator type (midpoint or endpoint) and perspective. Usage Notes for zip file: These files were tested to correctly import into an openLCA v2.1 database already containing flows from the FEDEFL v1.2. They will provide matching characterization factors for any FEDEFL elementary flow already present in the database. These files do not contain the elementary flows. Use of this "No Flows" method is described on https://www.lcacommons.gov/lcia-methods-without-flows. The complete FEDEFL v1.2 flow list may be retrieved from the Federal LCA Commons elementary flow list repository at https://www.lcacommons.gov.An associated .parquet file is available with the method in tabular format (https://dmap-data-commons-ord.s3.amazonaws.com/lciafmt/recipe/ReCiPe_2016_v1.1.1_27ba917.parquet). The .parquet file is in the LCIA Formatter's LCIAmethod format. https://github.com/USEPA/LCIAformatter/blob/v1.1.3/format specs/LCIAmethod.md. Usage notes for parquet file: The .parquet file can be read by any Apache parquet reader.ReferencesHuijbregts, M. A. J., et al. (2017). ReCiPe 2016: A harmonized life cycle impact assessment method at midpoint and endpoint level report i: characterization. International Journal of Life Cycle Assessment, 22(2), 138-147.EPA 2019. The Federal LCA Commons Elementary Flow List: Background, Approach, Description and Recommendations for Use. https://cfpub.epa.gov/si/si_public_record_Report.cfm?dirEntryId=347251.This dataset is associated with the following publication: Young, B., M. Srocka, W. Ingwersen, B. Morelli, S. Cashman, and A. Henderson. LCIA Formatter. Journal of Open Source Software, 6(66): 3392, (2021).

Using data reported to CDP, we have previously built a dataset of 866 PCFs, from 145 companies, 30 industry groups, and 28 countries, showing trends of how upstream and downstream emissions vary by industry and how life cycle assessment (LCA) appears to aid companies in achieving steeper carbon reductions through improvements throughout a product’s value chain. Here, we present the greenhouse gas emissions and respective meta data for every product in this dataset. The Carbon Catalogue provides each product with name and description, PCF (in kg CO2e) and the respective LCA protocol/standard, product weight, as well as the name, industry, and country of incorporation of its manufacturer. For a subset of 421 products, the Carbon Catalogue further includes the PCF’s reported breakdown into two to nine separate stages of the product’s life cycle. For another subset of 250 products, the Carbon Catalogue includes how the respective PCFs changed and why the changes occurred.

This dataset contains the background scenarios for metal supply used for the publication "Environmental impacts of key metals' supply and low-carbon technologies are likely to decrease in the future" in the Journal of Industrial Ecology (2021).

The background scenarios are suitable for the life cycle inventory database of ecoinvent version 3.5 (allocation, cut-off by classification). They can be imported either via the brightway-based module of presamples or using the activity browser and its scenario-based calculation set-up.

These background scenarios comprise five variables for the metals of copper, nickel, zinc, and lead for the time period of 2010-2050. These variables are:
V1: ore grade decline and energy requirements

V2: market shares of primary production locations

V3: energy efficiency improvements during smelting and refining

V4: market shares of primary production routes

V5: market shares of primary and secondary production.

The associated article in the Journal of Industrial Ecology describes the modelling assumptions and data sources of the scenarios. It also conducts impact assessments for future metal supply and low-carbon technologies.

This zenodo dataset provides the scenario data for import into presamples, which can be used for any other prospective LCA based on ecoinvent 3.5. Before importing the dataset, please adjust the "database" field to the name of your database, such as "ecoinvent3.5".

License: The metal supply scenario data is licensed under the CC-BY 4.0 license.

Access: This will become open access once the associated paper has been published in the Journal of Industrial Ecology.

This dataset contains the complete inventory data for direct import and re-use in LCA software (ILCD and JSON-ID format; exported from openLCA), together with a short manual about the import and use of the provided LCI datasets in openLCA. Additionally, the modified and parametrized LCI data are also provided in tabulated form (supplementary information document). The LCI data are based on ecoinvent 3.3., and eventually require update for use with more recenzt ei databases (re-linking of providers / flows). Import into openLCA using the JSON-LD format should maintain all default providers except those that suffered changes between the ei versions

This material is part of the free Environmental Performance in Construction (EPiC) Database. The EPiC Database contains embodied environmental flow coefficients for 250+ construction materials using a comprehensive hybrid life cycle inventory approach.Fibre cement sheet is a non-structural material manufactured from Portland cement, cellulose fibres and water. Sheets come in standard sizes, generally 1800 to 3000 mm in length, 900 or 1200 mm wide and in thicknesses ranging from 4.5 mm to 24 mm. They can be easily cut to size on site. Thicker boards provide superior impact resistance while thinner boards are typically used in situations where impact resistance is not as crucial.Thermal and acoustic performance is generally poor and additional insulation is usually needed when used as external cladding. However, it is termite and rot resistant and has very high fire resistance properties.Fibre cement sheet is often used as a replacement for plasterboard, particularly in situations that are exposed to water (such as wet areas). It can be used for both residential and commercial buildings in a range of applications, including internal and external cladding, soffit linings and structural bracing.

There is a data set of life cycle assessment of edible oil packaging designs in seven categories, namely, glass, PET, HDPE, aluminum, tin, TetraPak and DoyPak. Each of the designs is made from several parts and materials, which is mentioned in related article. In addition, three end-of-life options are considered for packaging in our analysis. The negative impacts of design and EOL options are evaluated on the three pillars of sustainability (human health, ecosystem, natural resource consumption). This data set is a part of LCA SimaPro data base, which is depicted here as a summery.

Model fit information for competing latent class models.