Contribution-based prioritization of LCI database improvements: Method design, demonstration, and evaluation. (December 2016)

• Record Type: Journal Article
• Authors: Reinhard, Juergen; Mutel, Christopher L.; Wernet, Gregor; Zah, Rainer; Hilty, Lorenz M.
• Is Part Of: Environmental modelling & software. Volume 86(2016)
• Page Start: 204
• Page End: 218
• Publication Date: 2016-12
• Subjects: Prioritization -- Life Cycle Inventory database -- Meta analysis -- Contribution analysis -- Life Cycle Assessment; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2016.09.018
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: The largest Life Cycle Inventory (LCI) databases contain about 10, 000 unit process datasets. Assuming that updating one dataset would, on average, require one working day, then updating the entire database would roughly require the continuous work of five workers for ten years. Methods are therefore needed to prioritize datasets to be updated, and such a method should be able to identify the unit processes that contribute the most across different Life Cycle Impact Assessment (LCIA) methods. To date, such prioritization methods are not available. This paper presents an operational prioritization method. We demonstrate and evaluate our method by applying it to the ecoinvent database. The case study shows that prioritization of improvement efforts is highly useful because a robust nucleus of unit processes proves to be consistently important across all product systems and many LCIA methods. Focusing research efforts on these processes allows the effective improvement of the LCI database. Highlights: Guiding research efforts is key for the effective improvement of LCI databases. We demonstrate and evaluate a contribution-based prioritization method. The method identifies the most important processes across different LCIA indicators. Prioritization is important if the quality of a small set of processes is crucial. This holds true across the entire LCI database and across many LCIA indicators.