Life cycle inventory data quality issues for bioplastics feedstocks

Alix Grabowski, Susan E M Selke, Rafael Auras, Martin K. Patel, Ramani Narayan

    Research output: Contribution to journalArticle

    • 2 Citations

    Abstract

    Purpose: Bioplastics are a growing field, but with their expansion come unique environmental issues associated with the cultivation and processing of feedstocks. Availability of appropriate, high-quality data is a problem in life cycle assessment (LCA) of biopolymers and other bio-based materials that limits the accuracy and usefulness of study results. It is therefore critical that these data gaps be closed. To determine what data is needed to close these gaps, this study reviews currently available life cycle inventory data for biopolymer feedstocks and assesses the data quality for the selected feedstocks of corn, sugarcane, and soy. Methods: Life cycle inventory databases and relevant publications were searched for appropriate data, and the results collected into a summary table. The quality review was conducted using a pedigree matrix type scoring system which was adapted from the ILCD handbook, and an overall quality score for each dataset was calculated based on the matrix scores. Results: A total of 287 datasets were collected during the review for a total of 22 different feedstocks. The majority of these datasets are from Europe and the USA, with most of Asia, the Middle East, and Africa having very limited data available. Conclusions: From the quality analysis, it was determined that more datasets that capture regional variations in crop cultivation are needed, as well as more data on land use change.

    Original languageEnglish (US)
    Pages (from-to)584-596
    Number of pages13
    JournalInternational Journal of Life Cycle Assessment
    Volume20
    Issue number5
    DOIs
    StatePublished - May 1 2015

    Profile

    life cycle
    data quality
    matrix
    environmental issue
    land use change
    maize
    crop

    Keywords

    • Bio-based polymers
    • Corn
    • Data quality
    • Feedstocks
    • LCA
    • Soy
    • Sugar cane

    ASJC Scopus subject areas

    • Environmental Science(all)

    Cite this

    Life cycle inventory data quality issues for bioplastics feedstocks. / Grabowski, Alix; Selke, Susan E M; Auras, Rafael; Patel, Martin K.; Narayan, Ramani.

    In: International Journal of Life Cycle Assessment, Vol. 20, No. 5, 01.05.2015, p. 584-596.

    Research output: Contribution to journalArticle

    Grabowski, Alix; Selke, Susan E M; Auras, Rafael; Patel, Martin K.; Narayan, Ramani / Life cycle inventory data quality issues for bioplastics feedstocks.

    In: International Journal of Life Cycle Assessment, Vol. 20, No. 5, 01.05.2015, p. 584-596.

    Research output: Contribution to journalArticle

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    abstract = "Purpose: Bioplastics are a growing field, but with their expansion come unique environmental issues associated with the cultivation and processing of feedstocks. Availability of appropriate, high-quality data is a problem in life cycle assessment (LCA) of biopolymers and other bio-based materials that limits the accuracy and usefulness of study results. It is therefore critical that these data gaps be closed. To determine what data is needed to close these gaps, this study reviews currently available life cycle inventory data for biopolymer feedstocks and assesses the data quality for the selected feedstocks of corn, sugarcane, and soy. Methods: Life cycle inventory databases and relevant publications were searched for appropriate data, and the results collected into a summary table. The quality review was conducted using a pedigree matrix type scoring system which was adapted from the ILCD handbook, and an overall quality score for each dataset was calculated based on the matrix scores. Results: A total of 287 datasets were collected during the review for a total of 22 different feedstocks. The majority of these datasets are from Europe and the USA, with most of Asia, the Middle East, and Africa having very limited data available. Conclusions: From the quality analysis, it was determined that more datasets that capture regional variations in crop cultivation are needed, as well as more data on land use change.",
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    AU - Selke,Susan E M

    AU - Auras,Rafael

    AU - Patel,Martin K.

    AU - Narayan,Ramani

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