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Quantified Uncertainties in Comparative Life Cycle Assessment: What Can Be Concluded?
Angelica Mendoza Beltran1, Valentina Prado1,2, David Font Vivanco3
1Institute of Environmental Sciences (CML), Department of Industrial Ecology, Leiden University , Einsteinweg 2, 2333 CC Leiden, The Netherlands.
Environmental Science & Technology
|February 7, 2018
Summary
Interpreting comparative Life Cycle Assessment (LCA) results requires robust uncertainty-statistics methods (USMs). Modified null hypothesis significance testing (NHST) is recommended for confirmatory analysis, while discernibility analysis is suggested for exploratory purposes.
Area of Science:
- Environmental Science
- Sustainability Studies
- Industrial Ecology
Background:
- Comparative Life Cycle Assessment (LCA) interpretation is complex due to inherent uncertainties.
- Existing uncertainty-statistics methods (USMs) lack standardized application and comparison.
- Guidance is needed for practitioners to effectively interpret comparative LCA outcomes.
Purpose of the Study:
- To provide guidance for interpreting comparative LCA results by analyzing uncertainty-statistics methods (USMs).
- To review and compare five distinct USMs: discernibility analysis, impact category relevance, overlap area of probability distributions, null hypothesis significance testing (NHST), and modified NHST.
- To establish a common framework including notation, terminology, and calculation for USMs.
Main Methods:
- A comprehensive review of five USMs was conducted.
- A cross-comparison of the selected USMs was performed using a case study on electric cars.
- The USMs were categorized into confirmatory and exploratory statistical branches.
Main Results:
- The effectiveness of USMs depends on common uncertainties and the magnitude of impact differences.
- Disregarding common uncertainties can lead to erroneous recommendations in comparative LCAs.
- Modified NHST emerged as a reliable confirmatory USM, and discernibility analysis as a useful exploratory USM.
Conclusions:
- Modified NHST is recommended as a robust confirmatory USM for comparative LCA.
- Discernibility analysis is recommended as an exploratory USM, with suggestions for enhancement to consider impact magnitude.
- The study provides a foundation for more reliable decision-making in LCA by improving the interpretation of uncertainty.
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