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hal.structure.identifierInstitut de Mécanique et d'Ingénierie de Bordeaux [I2M]
dc.contributor.authorSILVA, Fernanda Belezario
hal.structure.identifierInstitut de Mécanique et d'Ingénierie de Bordeaux [I2M]
dc.contributor.authorYOSHIDA, Olga Satomi
hal.structure.identifierInstitut de Mécanique et d'Ingénierie de Bordeaux [I2M]
dc.contributor.authorHORTA ARDUIN, Rachel
hal.structure.identifierInstitut de Mécanique et d'Ingénierie de Bordeaux [I2M]
dc.contributor.authorSOUZA, Carolina Almeida
hal.structure.identifierInstitut de Mécanique et d'Ingénierie de Bordeaux [I2M]
dc.contributor.authorTEIXEIRA, Cladia Echevenga
hal.structure.identifierSão Paulo State Institute for Technological Research
dc.contributor.authorALVES DE OLIVEIRA, Luciana
dc.date.accessioned2021-05-14T09:45:23Z
dc.date.available2021-05-14T09:45:23Z
dc.date.issued2017-06
dc.date.conference2017-06-12
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/76930
dc.description.abstractEnUncertainty estimation is an important part of Life Cycle Assessment (LCA), especially when comparing product alternatives. This work presents a study carried out for nine construction products in Brazil, with the aim of estimating the uncertainty of the Global Warming Potential (GWP) indicator and its main uncertainty sources. Product Life Cycle Inventories (LCIs) were developed based on national data for the product manufacturing processes, which were collected from local manufacturers and/or from literature, and upstream and downstream processes were modelled using datasets from Ecoinvent v. 3.2. GWP was calculated using the IPCC 2013 method with 100 years’ timeframe and its coefficient of variation (CV) was estimated using the Monte Carlo sampling available in Simapro v. 8.2, with 10.000 interactions. Afterwards ANOVA was conducted for each product, in order to identify the distribution of the CV between the process itself and upstream and downstream processes. The ANOVA also allowed to identify the process that most contributed to the final uncertainty. GWP CVs were on average 16%. For seven products, upstream and downstream processes contributed most to the uncertainty (79% of CV on average); while for two products (wood based) the process itself was prevalent (82% of CV on average). The upstream processes that most contributed to the uncertainty (and also to the GWP indicator) were electricity production, diesel combustion, cement production and acrylic binder production. It can be concluded that upstream processes are a major uncertainty source in the LCA of construction products, and reinforces the importance of a national database for increasing LCA reliability.
dc.language.isoen
dc.subject.enLife cycle assessent
dc.subject.enLife cycle inventory
dc.subject.enUncertainty
dc.subject.enPedigree matrix
dc.subject.enANOVA
dc.title.enUncertainty sources in the life cycle assessment of construction products in Brazil
dc.typeAutre communication scientifique (congrès sans actes - poster - séminaire...)
dc.subject.halSciences de l'environnement/Ingénierie de l'environnement
bordeaux.hal.laboratoriesInstitut de Mécanique et d’Ingénierie de Bordeaux (I2M) - UMR 5295*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.institutionINRAE
bordeaux.institutionArts et Métiers
bordeaux.countryCO
bordeaux.title.proceedingVII International Conference on Life Cycle Assessment in Latin America
bordeaux.conference.cityMedellin
bordeaux.peerReviewednon
hal.identifierhal-01944331
hal.version1
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-01944331v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.date=2017-06&rft.au=SILVA,%20Fernanda%20Belezario&YOSHIDA,%20Olga%20Satomi&HORTA%20ARDUIN,%20Rachel&SOUZA,%20Carolina%20Almeida&TEIXEIRA,%20Cladia%20Echevenga&rft.genre=conference


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