Truncation Error Estimates in Process Life Cycle Assessment Using Input‐Output Analysis.
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| Title: | Truncation Error Estimates in Process Life Cycle Assessment Using Input‐Output Analysis. |
|---|---|
| Authors: | Ward, Hauke1,2,3 ward@mcc-berlin.net, Wenz, Leonie2,3,4, Steckel, Jan C.2,3, Minx, Jan C.2,5 |
| Source: | Journal of Industrial Ecology. Oct2018, Vol. 22 Issue 5, p1080-1091. 12p. 1 Diagram, 5 Charts, 5 Graphs. |
| Subjects: | Product life cycle assessment, Balanced truncation, Robust control, Information resources management, Data modeling |
| Abstract: | Summary: Process life cycle assessment (PLCA) is widely used to quantify environmental flows associated with the manufacturing of products and other processes. As PLCA always depends on defining a system boundary, its application involves truncation errors. Different methods of estimating truncation errors are proposed in the literature; most of these are based on artificially constructed system complete counterfactuals. In this article, we review the literature on truncation errors and their estimates and systematically explore factors that influence truncation error estimates. We classify estimation approaches, together with underlying factors influencing estimation results according to where in the estimation procedure they occur. By contrasting different PLCA truncation/error modeling frameworks using the same underlying input‐output (I‐O) data set and varying cut‐off criteria, we show that modeling choices can significantly influence estimates for PLCA truncation errors. In addition, we find that differences in I‐O and process inventory databases, such as missing service sector activities, can significantly affect estimates of PLCA truncation errors. Our results expose the challenges related to explicit statements on the magnitude of PLCA truncation errors. They also indicate that increasing the strictness of cut‐off criteria in PLCA has only limited influence on the resulting truncation errors. We conclude that applying an additional I‐O life cycle assessment or a path exchange hybrid life cycle assessment to identify where significant contributions are located in upstream layers could significantly reduce PLCA truncation errors. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Industrial Ecology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 131861995 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Truncation Error Estimates in Process Life Cycle Assessment Using Input‐Output Analysis. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Ward%2C+Hauke%22">Ward, Hauke</searchLink><relatesTo>1,2,3</relatesTo><i> ward@mcc-berlin.net</i><br /><searchLink fieldCode="AR" term="%22Wenz%2C+Leonie%22">Wenz, Leonie</searchLink><relatesTo>2,3,4</relatesTo><br /><searchLink fieldCode="AR" term="%22Steckel%2C+Jan+C%2E%22">Steckel, Jan C.</searchLink><relatesTo>2,3</relatesTo><br /><searchLink fieldCode="AR" term="%22Minx%2C+Jan+C%2E%22">Minx, Jan C.</searchLink><relatesTo>2,5</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Industrial+Ecology%22">Journal of Industrial Ecology</searchLink>. Oct2018, Vol. 22 Issue 5, p1080-1091. 12p. 1 Diagram, 5 Charts, 5 Graphs. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Product+life+cycle+assessment%22">Product life cycle assessment</searchLink><br /><searchLink fieldCode="DE" term="%22Balanced+truncation%22">Balanced truncation</searchLink><br /><searchLink fieldCode="DE" term="%22Robust+control%22">Robust control</searchLink><br /><searchLink fieldCode="DE" term="%22Information+resources+management%22">Information resources management</searchLink><br /><searchLink fieldCode="DE" term="%22Data+modeling%22">Data modeling</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Summary: Process life cycle assessment (PLCA) is widely used to quantify environmental flows associated with the manufacturing of products and other processes. As PLCA always depends on defining a system boundary, its application involves truncation errors. Different methods of estimating truncation errors are proposed in the literature; most of these are based on artificially constructed system complete counterfactuals. In this article, we review the literature on truncation errors and their estimates and systematically explore factors that influence truncation error estimates. We classify estimation approaches, together with underlying factors influencing estimation results according to where in the estimation procedure they occur. By contrasting different PLCA truncation/error modeling frameworks using the same underlying input‐output (I‐O) data set and varying cut‐off criteria, we show that modeling choices can significantly influence estimates for PLCA truncation errors. In addition, we find that differences in I‐O and process inventory databases, such as missing service sector activities, can significantly affect estimates of PLCA truncation errors. Our results expose the challenges related to explicit statements on the magnitude of PLCA truncation errors. They also indicate that increasing the strictness of cut‐off criteria in PLCA has only limited influence on the resulting truncation errors. We conclude that applying an additional I‐O life cycle assessment or a path exchange hybrid life cycle assessment to identify where significant contributions are located in upstream layers could significantly reduce PLCA truncation errors. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Industrial Ecology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1111/jiec.12655 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 12 StartPage: 1080 Subjects: – SubjectFull: Product life cycle assessment Type: general – SubjectFull: Balanced truncation Type: general – SubjectFull: Robust control Type: general – SubjectFull: Information resources management Type: general – SubjectFull: Data modeling Type: general Titles: – TitleFull: Truncation Error Estimates in Process Life Cycle Assessment Using Input‐Output Analysis. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Ward, Hauke – PersonEntity: Name: NameFull: Wenz, Leonie – PersonEntity: Name: NameFull: Steckel, Jan C. – PersonEntity: Name: NameFull: Minx, Jan C. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 10 Text: Oct2018 Type: published Y: 2018 Identifiers: – Type: issn-print Value: 10881980 Numbering: – Type: volume Value: 22 – Type: issue Value: 5 Titles: – TitleFull: Journal of Industrial Ecology Type: main |
| ResultId | 1 |
