Uncertainty sources in the life cycle assessment of construction products in Brazil
| Autor: | SILVA, Fernanda Belezario, YOSHIDA, Olga Satomi, HORTA ARDUIN, Rachel, SOUZA, Carolina Almeida, TEIXEIRA, Cladia Echevenga, Alves de Oliveira, Luciana |
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| Přispěvatelé: | Institut de Mécanique et d'Ingénierie de Bordeaux (I2M), Institut National de la Recherche Agronomique (INRA)-Université de Bordeaux (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Institut Polytechnique de Bordeaux-Centre National de la Recherche Scientifique (CNRS), São Paulo State Institute for Technological Research, École Nationale Supérieure d'Arts et Métiers (ENSAM), HESAM Université (HESAM)-HESAM Université (HESAM)-Institut Polytechnique de Bordeaux-Centre National de la Recherche Scientifique (CNRS)-Université de Bordeaux (UB)-Institut National de la Recherche Agronomique (INRA), Administrateur Ensam, Compte De Service |
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: | |
| Zdroj: | VII International Conference on Life Cycle Assessment in Latin America VII International Conference on Life Cycle Assessment in Latin America, Jun 2017, Medellin, Colombia. 2017 |
| Popis: | International audience; Uncertainty 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. |
| Databáze: | OpenAIRE |
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