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Data for life cycle assessment of legume biorefining for alcohol.

ABSTRACT: Benchmarking the environmental sustainability of alcohol produced from legume starch against alcohol produced from cereal grains requires considering of crop production, nutrient cycling and use of protein-rich co-products via life cycle assessment. This article describes the mass balance flows behind the life cycle inventories for gin produced from wheat and peas (Pisum sativum L.) in an associated article summarising the environmental footprints of wheat- and pea-gin [1], and also presents detailed supplementary results. Activity data were collected from interviews with actors along the entire gin value chain including a distillery manager and ingredient and packaging suppliers. Important fertiliser and animal-feed substitution effects of co-product use were derived using detailed information and models on nutrient flows and animal feed composition, along with linear optimisation modelling. Secondary data on environmental burdens of specific materials and processes were obtained from the Ecoinvent v3.4 life cycle assessment database. This article provides a basis for further quantitative evaluation of the environmental sustainability of legume-alcohol value chains.

SUBMITTER: Lienhardt T

PROVIDER: S-EPMC6715788 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Data for life cycle assessment of legume biorefining for alcohol.

Lienhardt Theophile T Black Kirsty K Saget Sophie S Costa Marcela Porto MP Chadwick David D Rees Robert R Williams Michael M Spillane Charles C Iannetta Pietro P Walker Graeme G Styles David D

Data in brief 20190808

Benchmarking the environmental sustainability of alcohol produced from legume starch against alcohol produced from cereal grains requires considering of crop production, nutrient cycling and use of protein-rich co-products via life cycle assessment. This article describes the mass balance flows behind the life cycle inventories for gin produced from wheat and peas (Pisum sativum L.) in an associated article summarising the environmental footprints of wheat- and pea-gin [1], and also presents det ...[more]

PMID: 31485464

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Project description:PurposeDespite growing access to data, questions of "best fit" data and the appropriate use of results in supporting decision making still plague the life cycle assessment (LCA) community. This discussion paper addresses revisions to assessing data quality captured in a new US Environmental Protection Agency guidance document as well as additional recommendations on data quality creation, management, and use in LCA databases and studies.ApproachExisting data quality systems and approaches in LCA were reviewed and tested. The evaluations resulted in a revision to a commonly used pedigree matrix, for which flow and process level data quality indicators are described, more clarity for scoring criteria, and further guidance on interpretation are given.DiscussionIncreased training for practitioners on data quality application and its limits are recommended. A multi-faceted approach to data quality assessment utilizing the pedigree method alongside uncertainty analysis in result interpretation is recommended. A method of data quality score aggregation is proposed and recommendations for usage of data quality scores in existing data are made to enable improved use of data quality scores in LCA results interpretation. Roles for data generators, data repositories, and data users are described in LCA data quality management. Guidance is provided on using data with data quality scores from other systems alongside data with scores from the new system. The new pedigree matrix and recommended data quality aggregation procedure can now be implemented in openLCA software.Future workAdditional ways in which data quality assessment might be improved and expanded are described. Interoperability efforts in LCA data should focus on descriptors to enable user scoring of data quality rather than translation of existing scores. Developing and using data quality indicators for additional dimensions of LCA data, and automation of data quality scoring through metadata extraction and comparison to goal and scope are needed.

Dataset Information

Data for life cycle assessment of legume biorefining for alcohol.

Publications

Data for life cycle assessment of legume biorefining for alcohol.

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