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UWME DFE Lab

The UWME Design for Environment Lab promotes Sustainability and Design for Environment (DFE) through the advancement of Life Cycle Assessment (LCA) and Industrial Ecology (IE).

Life Cycle Assessment Data

Accessibility to LCA data, e.g., for Product Category Rules (PCRs) and Environmental Product Declarations (EPDs), is improving in large part due to national database development efforts.

USDA LCA Digital Commons

Open source data, like that in the USDA LCA Digital Commons, promise more transparency for LCAs. Features include data parameterization and extended meta data.

Design for Environment Courses

In ME515 Life Cycle Assessment, Beren Landaas Wells McKay presented this photo as part of his LCA of photography.  Visit the "Salmon Waves" sculpture at the Hiram M. Chittenden Locks.

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Department of Mechanical Engineering, University of Washington

 

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Submit data to the LCA Digital Commons

Project funded by the USDA National Agricultural Library

 

The vision for the USDA LCA Digital Commons is for it to become a repository for a wide range of LCA data developed by a wide range of practitioners.  The USDA’s objective is to collect newly developed unit process data related to agriculture and based on primary data collection to the maximum extent possible.

Within the USDA, it is the USDA National Agricultural Library that is developing and hosting the Commons.  As such, metadata are key to the data submission process.  To assure that data users have the metadata needed to select and correctly use all datasets in the Commons, the USDA-NAL will guide contributors through an interactive submission process and internal administrative review focused on creating complete metadata that thoroughly describe the data.  Then, the data will be assigned a persistent identifier and posted to the Commons.

Submitting data

There will soon be a website that will interactively guide contributors through the metadata review/ data submission process. In the meantime, here is a draft of some important aspects of the data submission process, as of November 4, 2013.

DRAFT Data format

Data can be submitted to the in ecospold v.1, ecospold v.2, and ILCD formats. The Commons is currently structured by the openLCA schema as are the metadata elements below. Unit processes built in openLCA can easily be exported and then submitted in ecospold v.1, ecospold v.2, and ILCD formats.  

These 3 formats can be generated using LCA software tools such as openLCA, GaBi, and SimaPro.  Unparameterized ecospold v1 files can be generated using the Excel2EcoSold add-in within EcoSpoldAccess.  Also, ILCD xml files can be generated from data existing in excel using the beta UWDFE Lab Excel to ILCD File Generator.

 

 

DRAFT Metadata elements

General Information

  • Name (e.g., soybeans; at harvest in 2002; at farm, production mix; 85%-92% moisture): Include the five elements listed below (base name, treatment/standards/routes, location type, mix type and quantitative reference flow properties) in the name field.  See http://lct.jrc.ec.europa.eu/pdf-directory/ILCD-Nomenclature-and-other-conventions-March2010.pdf for more info and examples.

    • Base name (e.g., soybeans): Provide a general descriptive name of the product produced using technical language. If the product is waste management, include the phrase “waste management” or something similar.

    • Treatment, standards, and routes (e.g., at harvest in 2002): Provide qualitative information on the product produced: treatment received, standard fulfilled, product quality, use information, production route name, educt name, primary / secondary etc. separated by commas.

    • Location type (e.g., at farm): Describe the location type of availability (such as e.g. “to consumer” or “at plant”).

    • Mix type (e.g., production mix): Provide specifying information on being a production mix or consumption mix if applicable.

    • Quantitative reference flow properties (e.g., 85%-92% moisture): Provide quantitative specifying information on the reference flow if applicable: qualifying constituent contents, energy-content per unit, etc. separated by commas.

  • Category (e.g., ISIC 0111: Growing of cereals (except rice), leguminous crops and oil seeds): Provide the 4-digit ISIC rev 4 code and the ISIC name as defined at http://unstats.un.org/unsd/cr/registry/regcst.asp?Cl=27

  • Description: Describe the process and the technical scope (e.g. gate-to-gate or cradle-to-grave) and any aggregation used. Define the technology being used, its operating conditions, and the temporal and geographic representativeness.  Name any coproducts and describe how they are accounted, noting that unallocated datasets are preferred (e.g., “soybean residue is included as a coproduct” is preferred over “flows have been mass allocated to 1 kg soybeans to account for the coproduction of 0.788 kg residue”).

  • Quantitative Reference: Provide the quantitative reference to which the size of the inputs and outputs in the process relate. This is the reference flow (e.g. 1 kg soybeans).

  • Start and end dates (mm/dd/yyyy): Provide the start and end dates for the period of time which the data represent.

  • Temporal representatives comment: Describe the temporal characteristics of the data including the period of time for which they refer and are valid and any temporal aggregation and temporal incongruence of supporting data.

  • Location (e.g., e.g., US-IA (the state of Iowa, USA): Provide the location code according to ISO 3166-2 Sub-division/State Code.

  • Geographic representativeness comment: Describe the geographical representativeness of the data including the geographic area over which the data are valid and any geographic aggregations.

  • Technology Description: Provide a short general description of the technology to inform users about the technical relevance of the data. Include a list of processes/ activities (anthropogenic or natural) included in the dataset, such as a description of any fate and transport modeling used.

  • Intended Application: Describe the intended application for the data including the larger context within which the data were developed and the objectives of the research. The intended application may differ due to project scope or system boundaries, data aggregation methods, and/or data gaps.

Administrative Information

  • Data generator (first and last name): Identify the person responsible for developing the data.

    • Affiliations and position: Identify the data generator's affiliations and position.

    • Telephone: Provide the data generator's telephone number.

    • Address: Provide the data generator's address.

    • e-mail address: Provide the data generator's email address.

    • Website: Provide a link to the data generator's website.

    • Project: Provide information about the project through which the data were generated. Include the project name, funding institutions/organizations and grant/contract name and numbers where applicable.

  • Publication: Provide bibliographic information for a foundational publication which illustrates how the data were used. Bibliographic information is to be based on American Psychological Association (APA) style, e.g.,

    • First author (last name, initials only for first & middle names), additional authors (last name, initials only for first & middle names), title, publication name, publisher, place of publication, government agency, volume and issue, number, year, page numbers , DOI, URL

  • Access and Use Restrictions: Provide a clear statement about how the data and metadata may be released outside of the Commons if applicable.

  • Copyright (Y/N): Note whether or not the data are copyrighted.

Modeling and Validation

  • Process Type: Indicate whether the data represent a unit or system process, where a system process is an LCI result.

  • Sources: List the data sources used to generate this unit process including both primary and secondary data.

  • Allocation methods: Name the allocation methods used as none, causal allocation, economic allocation, and/or physical allocation.  For data submitted to the Commons, the preference is not to allocate (e.g., responding “none”).

  • Data completeness:

    • Treatment of missing flow data: List and describe methods for accounting missing data (e.g., cut off rules, use of service processes) and/or intended omissions. 

    • As applicable, for crop/biomass production include mention of missing data on:

  1. Coproduction

  2. Flows from the environment (occupied area, transformed area, water withdrawal, nutrients from air and soil (in crops, co-products, and above and belowground residues))

  3. Technosphere/ intermediate flows (field residue burning, residue management, soil preparation, planting or sowing, seed or feed use and storage, irrigation, fertilizer application, liming material application, secondary materials application, pesticide application, application materials storage, transport/ distribution, harvest)

  4. Flows to the environment (residue burning emissions, residue left on the field (above and below ground), water (in irrigation, with manure applications, in sewage sludge applied), substances applied in fertilizers, manures, secondary applications, and pesticides)

    • As applicable, for equipment operation include mention of missing data on:

      1. Coproduction

      2. Flows from the environment (water withdrawal, air used in combustion, other directly extracted resources)

      3. Technosphere/ intermediate flows (energy use, product materials use, ancillary materials use, transport/ distribution, equipment construction and retirement, spare parts, facility use)

      4. Flows to the environment (operating emissions including unrecovered product and ancillary materials)

    • Unsubmitted intermediate flow data sets: When intermediate flows are specified in datasets being submitted but the associated “upstream” or “downstream” data sets are not simultaneously being submitted to the Commons:

      1. List the intermediate flows that are cutoff (when the upstream or downstream data sets to not yet exist) and/or

      2. List the intermediate flows and the associated database(s) in which the upstream or downstream data sets can be found (e.g., in the SimaPro or GaBi software, in ecoinvent, in ELCD, etc.)

    • Mass balance: Either:

      1. Quantify and describe the mass imbalance (as the mass of outputs less that of inputs) or

      2. Describe the mass balance as unknown

  • Data Treatment: Provide a detailed description of the methods and assumptions used to transform primary and secondary data into flow quantities through recalculating, reformatting, aggregation, or proxy data. Please also describe data quality according to Commons convention described in Cooper, J.S., E. Kahn “Commentary on issues in data quality analysis in life cycle assessment.” International Journal of Life Cycle Assessment 17(4) 499-503 (2012).

  • Boundary conditions and sampling procedures: Provide a detailed description of how boundary conditions were defined, how data were collected, and how variability and uncertainty are estimated.

  • Data collection period: Describe the period of time within which the data were collected (e.g., ARMS data were collected in years denoted in data. Unit process data were compiled in June, 2012).

  • Reviewer: Provide the name and affiliation of the peer review chair or lead reviewer as relevant.

  • Review description: Describe how the data were reviewed as: no review, dependent internal review, independent external review, panel review, independent internal review, or other.  Add a description as appropriate; including a list of reviewers beyond the peer review chair.

For more information, contact Peter Arbuckle at Peter.Arbuckle1@ARS.USDA.GOV

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