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How to Simplify Life Cycle Assessment for Industrial Applications—A Comprehensive Review

Author

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  • Steffen Kiemel

    (Fraunhofer-Institute for Manufacturing Engineering and Automation IPA, Nobelstraße 12, 70569 Stuttgart, Germany)

  • Chantal Rietdorf

    (Fraunhofer-Institute for Manufacturing Engineering and Automation IPA, Nobelstraße 12, 70569 Stuttgart, Germany)

  • Maximilian Schutzbach

    (Fraunhofer-Institute for Manufacturing Engineering and Automation IPA, Nobelstraße 12, 70569 Stuttgart, Germany
    Institute for Energy Efficiency in Production (EEP), University of Stuttgart, Nobelst. 12, 70569 Stuttgart, Germany)

  • Robert Miehe

    (Fraunhofer-Institute for Manufacturing Engineering and Automation IPA, Nobelstraße 12, 70569 Stuttgart, Germany)

Abstract

Life cycle assessment (LCA) has established itself as the dominant method for identifying the environmental impact of products or services. However, conducting an LCA is labor and time intensive (especially regarding data collection). This paper, therefore, aims to identify methods and tools that enhance the practicability of LCA, especially with regard to product complexity and variance. To this end, an initial literature review on the LCA of complex products was conducted to identify commonly cited barriers and potential solutions. The obtained information was used to derive search strategies for a subsequent comprehensive and systematic literature review of approaches that address the identified barriers and facilitate the LCA process. We identified five approaches to address the barriers of time and effort, complexity, and data intensity. These are the parametric approach, modular approach, automation, aggregation/grouping, and screening. For each, the concept as well as the associated advantages and disadvantages are described. Especially, the automated calculation of results as well as the automated generation of life cycle inventory (LCI) data exhibit great potential for simplification. We provide an overview of common LCA software and databases and evaluate the respective interfaces. As it was not considered in detail, further research should address options for automated data collection in production by utilizing sensors and intelligent interconnection of production infrastructure as well as the interpretation of the acquired data using artificial intelligence.

Suggested Citation

  • Steffen Kiemel & Chantal Rietdorf & Maximilian Schutzbach & Robert Miehe, 2022. "How to Simplify Life Cycle Assessment for Industrial Applications—A Comprehensive Review," Sustainability, MDPI, vol. 14(23), pages 1-26, November.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:23:p:15704-:d:984105
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    References listed on IDEAS

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    1. Davide Rovelli & Carlo Brondi & Michele Andreotti & Elisabetta Abbate & Maurizio Zanforlin & Andrea Ballarino, 2022. "A Modular Tool to Support Data Management for LCA in Industry: Methodology, Application and Potentialities," Sustainability, MDPI, vol. 14(7), pages 1-31, March.
    2. Malmqvist, Tove & Glaumann, Mauritz & Scarpellini, Sabina & Zabalza, Ignacio & Aranda, Alfonso & Llera, Eva & Díaz, Sergio, 2011. "Life cycle assessment in buildings: The ENSLIC simplified method and guidelines," Energy, Elsevier, vol. 36(4), pages 1900-1907.
    3. Lara Waltersmann & Steffen Kiemel & Julian Stuhlsatz & Alexander Sauer & Robert Miehe, 2021. "Artificial Intelligence Applications for Increasing Resource Efficiency in Manufacturing Companies—A Comprehensive Review," Sustainability, MDPI, vol. 13(12), pages 1-26, June.
    4. Rafael Horn & Sebastian Ebertshäuser & Roberta Di Bari & Olivia Jorgji & René Traunspurger & Petra von Both, 2020. "The BIM2LCA Approach: An Industry Foundation Classes (IFC)-Based Interface to Integrate Life Cycle Assessment in Integral Planning," Sustainability, MDPI, vol. 12(16), pages 1-30, August.
    5. José Pedro Carvalho & Fernanda Schmitd Villaschi & Luís Bragança, 2021. "Assessing Life Cycle Environmental and Economic Impacts of Building Construction Solutions with BIM," Sustainability, MDPI, vol. 13(16), pages 1-23, August.
    6. 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.
    7. David Moher & Alessandro Liberati & Jennifer Tetzlaff & Douglas G Altman & The PRISMA Group, 2009. "Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement," PLOS Medicine, Public Library of Science, vol. 6(7), pages 1-6, July.
    8. Anita Naneva & Marcella Bonanomi & Alexander Hollberg & Guillaume Habert & Daniel Hall, 2020. "Integrated BIM-Based LCA for the Entire Building Process Using an Existing Structure for Cost Estimation in the Swiss Context," Sustainability, MDPI, vol. 12(9), pages 1-17, May.
    9. Peters, Jens F. & Baumann, Manuel & Zimmermann, Benedikt & Braun, Jessica & Weil, Marcel, 2017. "The environmental impact of Li-Ion batteries and the role of key parameters – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 491-506.
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    Cited by:

    1. Ana Fonseca & Edgar Ramalho & Ana Gouveia & Filipa Figueiredo & João Nunes, 2023. "Life Cycle Assessment of PLA Products: A Systematic Literature Review," Sustainability, MDPI, vol. 15(16), pages 1-19, August.
    2. Elif Kaynak & Imelda Saran Piri & Oisik Das, 2025. "Revisiting the Basics of Life Cycle Assessment and Lifecycle Thinking," Sustainability, MDPI, vol. 17(16), pages 1-17, August.

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