Influence of different LCIA methods on an exemplary scenario analysis from a process development LCA case study

Bibliographic Data

ID15105222
AuthorsDaniel Koch (0000-0002-4539-1346, TU Wien, corresponding author), Anton Friedl (0000-0002-0450-9707, TU Wien), Bettina Mihalyi (TU Wien)
Year2023
Volume25
Issue7
Pages6269-6293
Publication date2023-07-01
Open AccessYes
TypeARTICLE
VenueEnvironment Development and Sustainability (JOURNAL)
Journal identifiersISSN: 1387-585X • E-ISSN: 1573-2975
PublisherSpringer Science and Business Media LLC (PUBLISHER)
DOI10.1007/s10668-022-02302-w
OpenAlexW4224232389
LanguageEN
Citations received4
References cited37

Life cycle impact assessment (LCIA) methods quantify the impact of life cycle inventory data within each impact category by means of classification and characterization. This paper evaluated whether the selected LCIA method influenced the life cycle assessment (LCA) scenario analysis for decision support in process development and its possible reasons. For this study, a scenario analysis was used from a biorefinery LCA case study, as this is a key practice in process development. The analysis was investigated using various LCIA methods for the three midpoint impact categories of global warming potential (GWP, 12 LCIA methods totaling 48 subcategories), eutrophication potential (EP, 9 LCIA methods totaling 18 subcategories), and water assessment (WA, 10 LCIA methods totaling 26 subcategories). The GWP category showed consistent interpretations for the scenario analysis from different LCIA methods. The subcategory of marine EP from the two LCIA methods disagreed on the best-case scenario. Another discrepancy was identified within the three general EP indicators, where the trend of the scenario analysis was inverted in one method because of the sensitivity of a single substance (ethanol). Within the subcategories of WA, the inclusion or exclusion of hydropower water impacts changed the scenario analysis in the blue water use and total freshwater use subcategories, and the general WA indicators also disagreed on the best-case scenario. It is important to understand these influences and the reasons behind the variations for decision support in process development

Economics · Environmental resource management · Hydropower · Life-cycle assessment · Scenario analysis · Statistics · Chemistry and Chemical Engineering · Computer Science · Engineering · Environmental Impact and Sustainability · Environmental Science · Mathematics · Sustainable Supply Chain Management