How to decide and visualize whether uncertainty or variability is dominating in life cycle assessment results: A systematic review. (November 2020)
- Record Type:
- Journal Article
- Title:
- How to decide and visualize whether uncertainty or variability is dominating in life cycle assessment results: A systematic review. (November 2020)
- Main Title:
- How to decide and visualize whether uncertainty or variability is dominating in life cycle assessment results: A systematic review
- Authors:
- Michiels, Freya
Geeraerd, Annemie - Abstract:
- Abstract: LCA results are typically reported as deterministic, while reality is uncertain and variable. Through a systematic review, we studied which methodologies and associated visualizations have already been used to assess both uncertainty and variability, as separate concepts, in the same LCA study. We aim to select the most appropriate one(s) that allow to decide whether uncertainty or variability is dominating in the results. 562 studies were identified by combining four topics (uncertainty, variability, LCA and methodology) of which eleven were eligible. These studies used a multi-step approach, often combining Monte Carlo simulations with a local and/or global sensitivity analysis and statistical measures. Based on our review, we recommend Monte Carlo simulations visualized in uncertainty and variability ratios and global sensitivity analysis visualized using total sensitivity indices for future use in LCA. Ratios allow to clearly decide whether uncertainty or variability is dominating and sensitivity indices allow to identify essential parameters. Highlights: Data used in Life Cycle Assessments are uncertain and variable. We reviewed used methodologies to assess combinations of uncertainty and variability. Monte Carlo simulations visualized in ratios allows to decide which is dominating. Global sensitivity analysis allows this through visualizing essential parameters.
- Is Part Of:
- Environmental modelling & software. Volume 133(2020)
- Journal:
- Environmental modelling & software
- Issue:
- Volume 133(2020)
- Issue Display:
- Volume 133, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 133
- Issue:
- 2020
- Issue Sort Value:
- 2020-0133-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-11
- Subjects:
- Methodology -- Uncertainty -- Variability -- Life cycle assessment -- Monte Carlo simulation -- Sensitivity
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 - Journal URLs:
- http://www.sciencedirect.com/science/journal/13648152 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.envsoft.2020.104841 ↗
- Languages:
- English
- ISSNs:
- 1364-8152
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
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