[go: up one dir, main page]

IDEAS home Printed from https://ideas.repec.org/a/bla/inecol/v26y2022i2p374-391.html
   My bibliography  Save this article

Implementation of uncertainty analysis and moment‐independent global sensitivity analysis for full‐scale life cycle assessment models

Author

Listed:
  • Stefano Cucurachi
  • Carlos Felipe Blanco
  • Bernhard Steubing
  • Reinout Heijungs
Abstract
Life cycle assessment (LCA) models and databases have increased in size, resolution, and complexity, requiring analysts to rely on an ever‐increasing number of uncertain model inputs. Such increased complexity calls for systematic approaches to assessing the uncertainty of the output results of LCA models and the sensitivity of LCA model outputs to the model's uncertain inputs. In this contribution, we provide a theoretical basis and present a practical software implementation that combines uncertainty analysis and moment‐independent global sensitivity analysis, which can be readily applied to full‐scale LCA models. We implemented our approach in the Activity‐Browser open source LCA software and it is made available for use in LCA studies. We demonstrate the approach and software implementation with a case study of crystalline silicon photovoltaics.

Suggested Citation

  • Stefano Cucurachi & Carlos Felipe Blanco & Bernhard Steubing & Reinout Heijungs, 2022. "Implementation of uncertainty analysis and moment‐independent global sensitivity analysis for full‐scale life cycle assessment models," Journal of Industrial Ecology, Yale University, vol. 26(2), pages 374-391, April.
  • Handle: RePEc:bla:inecol:v:26:y:2022:i:2:p:374-391
    DOI: 10.1111/jiec.13194
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/jiec.13194
    Download Restriction: no

    File URL: https://libkey.io/10.1111/jiec.13194?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Sheetal Gavankar & Sarah Anderson & Arturo A. Keller, 2015. "Critical Components of Uncertainty Communication in Life Cycle Assessments of Emerging Technologies," Journal of Industrial Ecology, Yale University, vol. 19(3), pages 468-479, June.
    2. Heijungs, Reinout, 1994. "A generic method for the identification of options for cleaner products," Ecological Economics, Elsevier, vol. 10(1), pages 69-81, May.
    3. Borgonovo, E., 2007. "A new uncertainty importance measure," Reliability Engineering and System Safety, Elsevier, vol. 92(6), pages 771-784.
    4. Elmar Plischke & Emanuele Borgonovo, 2020. "Fighting the Curse of Sparsity: Probabilistic Sensitivity Measures From Cumulative Distribution Functions," Risk Analysis, John Wiley & Sons, vol. 40(12), pages 2639-2660, December.
    5. S. Cucurachi & E. Borgonovo & R. Heijungs, 2016. "A Protocol for the Global Sensitivity Analysis of Impact Assessment Models in Life Cycle Assessment," Risk Analysis, John Wiley & Sons, vol. 36(2), pages 357-377, February.
    6. Derennes, Pierre & Morio, Jérôme & Simatos, Florian, 2019. "A nonparametric importance sampling estimator for moment independent importance measures," Reliability Engineering and System Safety, Elsevier, vol. 187(C), pages 3-16.
    7. Patrik J G Henriksson & Reinout Heijungs & Hai M Dao & Lam T Phan & Geert R de Snoo & Jeroen B Guinée, 2015. "Product Carbon Footprints and Their Uncertainties in Comparative Decision Contexts," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-11, March.
    8. Manel Baucells & Emanuele Borgonovo, 2013. "Invariant Probabilistic Sensitivity Analysis," Management Science, INFORMS, vol. 59(11), pages 2536-2549, November.
    9. Plischke, Elmar & Borgonovo, Emanuele & Smith, Curtis L., 2013. "Global sensitivity measures from given data," European Journal of Operational Research, Elsevier, vol. 226(3), pages 536-550.
    10. Borgonovo, Emanuele & Plischke, Elmar, 2016. "Sensitivity analysis: A review of recent advances," European Journal of Operational Research, Elsevier, vol. 248(3), pages 869-887.
    11. Shannon M. Lloyd & Robert Ries, 2007. "Characterizing, Propagating, and Analyzing Uncertainty in Life‐Cycle Assessment: A Survey of Quantitative Approaches," Journal of Industrial Ecology, Yale University, vol. 11(1), pages 161-179, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. S. Cucurachi & E. Borgonovo & R. Heijungs, 2016. "A Protocol for the Global Sensitivity Analysis of Impact Assessment Models in Life Cycle Assessment," Risk Analysis, John Wiley & Sons, vol. 36(2), pages 357-377, February.
    2. Plischke, Elmar & Borgonovo, Emanuele, 2019. "Copula theory and probabilistic sensitivity analysis: Is there a connection?," European Journal of Operational Research, Elsevier, vol. 277(3), pages 1046-1059.
    3. Emanuele Borgonovo & Gordon B. Hazen & Elmar Plischke, 2016. "A Common Rationale for Global Sensitivity Measures and Their Estimation," Risk Analysis, John Wiley & Sons, vol. 36(10), pages 1871-1895, October.
    4. Derennes, Pierre & Morio, Jérôme & Simatos, Florian, 2021. "Simultaneous estimation of complementary moment independent and reliability-oriented sensitivity measures," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 182(C), pages 721-737.
    5. Tatsuya Sakurahara & Seyed Reihani & Ernie Kee & Zahra Mohaghegh, 2020. "Global importance measure methodology for integrated probabilistic risk assessment," Journal of Risk and Reliability, , vol. 234(2), pages 377-396, April.
    6. Tobias Fissler & Silvana M. Pesenti, 2022. "Sensitivity Measures Based on Scoring Functions," Papers 2203.00460, arXiv.org, revised Jul 2022.
    7. Yun, Wanying & Lu, Zhenzhou & Feng, Kaixuan & Li, Luyi, 2019. "An elaborate algorithm for analyzing the Borgonovo moment-independent sensitivity by replacing the probability density function estimation with the probability estimation," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 99-108.
    8. Pesenti, Silvana M. & Millossovich, Pietro & Tsanakas, Andreas, 2019. "Reverse sensitivity testing: What does it take to break the model?," European Journal of Operational Research, Elsevier, vol. 274(2), pages 654-670.
    9. López-Benito, Alfredo & Bolado-Lavín, Ricardo, 2017. "A case study on global sensitivity analysis with dependent inputs: The natural gas transmission model," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 11-21.
    10. Yun, Wanying & Lu, Zhenzhou & Jiang, Xian, 2019. "An efficient method for moment-independent global sensitivity analysis by dimensional reduction technique and principle of maximum entropy," Reliability Engineering and System Safety, Elsevier, vol. 187(C), pages 174-182.
    11. Soha Saad & Florence Ossart & Jean Bigeon & Etienne Sourdille & Harold Gance, 2021. "Global Sensitivity Analysis Applied to Train Traffic Rescheduling: A Comparative Study," Energies, MDPI, vol. 14(19), pages 1-29, October.
    12. Liu, Xing & Ferrario, Elisa & Zio, Enrico, 2019. "Identifying resilient-important elements in interdependent critical infrastructures by sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 423-434.
    13. Borgonovo, Emanuele & Plischke, Elmar, 2016. "Sensitivity analysis: A review of recent advances," European Journal of Operational Research, Elsevier, vol. 248(3), pages 869-887.
    14. Bosetti, Valentina & Marangoni, Giacomo & Borgonovo, Emanuele & Diaz Anadon, Laura & Barron, Robert & McJeon, Haewon C. & Politis, Savvas & Friley, Paul, 2015. "Sensitivity to energy technology costs: A multi-model comparison analysis," Energy Policy, Elsevier, vol. 80(C), pages 244-263.
    15. Xing Liu & Enrico Zio & Emanuele Borgonovo & Elmar Plischke, 2024. "A Systematic Approach of Global Sensitivity Analysis and Its Application to a Model for the Quantification of Resilience of Interconnected Critical Infrastructures," Energies, MDPI, vol. 17(8), pages 1-24, April.
    16. Samuele Lo Piano & Lorenzo Benini, 2022. "A critical perspective on uncertainty appraisal and sensitivity analysis in life cycle assessment," Journal of Industrial Ecology, Yale University, vol. 26(3), pages 763-781, June.
    17. Di Maio, Francesco & Nicola, Giancarlo & Borgonovo, Emanuele & Zio, Enrico, 2016. "Invariant methods for an ensemble-based sensitivity analysis of a passive containment cooling system of an AP1000 nuclear power plant," Reliability Engineering and System Safety, Elsevier, vol. 151(C), pages 12-19.
    18. Borgonovo, Emanuele & Hazen, Gordon B. & Jose, Victor Richmond R. & Plischke, Elmar, 2021. "Probabilistic sensitivity measures as information value," European Journal of Operational Research, Elsevier, vol. 289(2), pages 595-610.
    19. Cheng, Lei & Lu, Zhenzhou & Zhang, Leigang, 2015. "Application of Rejection Sampling based methodology to variance based parametric sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 9-18.
    20. Fissler, Tobias & Pesenti, Silvana M., 2023. "Sensitivity measures based on scoring functions," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1408-1423.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:inecol:v:26:y:2022:i:2:p:374-391. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=1088-1980 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.