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A probabilistic approach for handling uncertainty in infrastructure LCA

A probabilistic approach for handling uncertainty in infrastructure LCA
Autor(en): , ORCID,
Beitrag für IABSE Congress: Challenges in Design and Construction of an Innovative and Sustainable Built Environment, Stockholm, Sweden, 21-23 September 2016, veröffentlicht in , S. 1677-1685
DOI: 10.2749/stockholm.2016.1673
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To demonstrate and support sustainability of large-scale infrastructure projects, life cycle assessment (LCA) has become a common tool used in the evaluation of environmental impact. However, LCA i...
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Bibliografische Angaben

Autor(en): (Structural Engineering, Lund University, Lund, Sweden)
ORCID (SP Technical Research Institute of Sweden, Göteborg, Sweden)
(IVL Swedish Environmental Research Institute, Göteborg, Sweden)
Medium: Tagungsbeitrag
Sprache(n): Englisch
Tagung: IABSE Congress: Challenges in Design and Construction of an Innovative and Sustainable Built Environment, Stockholm, Sweden, 21-23 September 2016
Veröffentlicht in:
Seite(n): 1677-1685 Anzahl der Seiten (im PDF): 9
Seite(n): 1677-1685
Anzahl der Seiten (im PDF): 9
Jahr: 2016
DOI: 10.2749/stockholm.2016.1673
Abstrakt:

To demonstrate and support sustainability of large-scale infrastructure projects, life cycle assessment (LCA) has become a common tool used in the evaluation of environmental impact. However, LCA includes a number of phases, which are all associated with uncertainties. Decisions made without regard to these uncertainties may be suboptimal and/or misleading. The current paper discusses some important issues about how to deal with uncertainties in LCA. Two case studies are presented that shows the effect of including uncertainty in various parameters. The results show that a reduction in uncertainty due to manufacturing improvements can increase the reliability of the results significantly. It was also found that the uncertainty assumptions for parameters where data is not available have a large impact on the LCA-results.

Stichwörter:
Unsicherheit probabilistische Untersuchung