4.4 Article

Comparative LCA of ethanol versus gasoline in Brazil using different LCIA methods

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SPRINGER HEIDELBERG
DOI: 10.1007/s11367-012-0465-0

关键词

Biorefinery; Categories of impact; Environmental impacts; Life cycle impact assessment (LCIA); Midpoint modeling; Single score; Sugarcane

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  1. Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP)

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The main objective of this study is to expand the discussion about how, and to what extent, the environmental performance is affected by the use of different life cycle impact assessment (LCIA) illustrated by the case study of the comparison between environmental impacts of gasoline and ethanol form sugarcane in Brazil. The following LCIA methods have been considered in the evaluation: CML 2001, Impact 2002+, EDIP 2003, Eco-indicator 99, TRACI 2, ReCiPe, and Ecological Scarcity 2006. Energy allocation was used to split the environmental burdens between ethanol and surplus electricity generated at the sugarcane mill. The phases of feedstock and (bio)fuel production, distribution, and use are included in system boundaries. At the midpoint level, comparison of different LCIA methods showed that ethanol presents lower impacts than gasoline in important categories such as global warming, fossil depletion, and ozone layer depletion. However, ethanol presents higher impacts in acidification, eutrophication, photochemical oxidation, and agricultural land use categories. Regarding to single-score indicators, ethanol presented better performance than gasoline using ReCiPe Endpoint LCIA method. Using IMPACT 2002+, Eco-indicator 99, and Ecological Scarcity 2006, higher scores are verified for ethanol, mainly due to the impacts related to particulate emissions and land use impacts. Although there is a relative agreement on the results regarding equivalent environmental impact categories using different LCIA methods at midpoint level, when single-score indicators are considered, use of different LCIA methods lead to different conclusions. Single-score results also limit the interpretability at endpoint level, as a consequence of small contributions of relevant environmental impact categories weighted in a single-score indicator.

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