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Analyzing Temporal Variability in Inventory Data for Life Cycle Assessment: Implications in the Context of Circular Economy

Author

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  • Sayyed Shoaib-ul-Hasan

    (Department of Production Engineering, KTH Royal Institute of Technology, Brinellvägen 68, 100 44 Stockholm, Sweden)

  • Malvina Roci

    (Department of Production Engineering, KTH Royal Institute of Technology, Brinellvägen 68, 100 44 Stockholm, Sweden)

  • Farazee M. A. Asif

    (Department of Production Engineering, KTH Royal Institute of Technology, Brinellvägen 68, 100 44 Stockholm, Sweden)

  • Niloufar Salehi

    (Department of Production Engineering, KTH Royal Institute of Technology, Brinellvägen 68, 100 44 Stockholm, Sweden)

  • Amir Rashid

    (Department of Production Engineering, KTH Royal Institute of Technology, Brinellvägen 68, 100 44 Stockholm, Sweden)

Abstract

Life cycle assessment (LCA) is used frequently as a decision support tool for evaluating different design choices for products based on their environmental impacts. A life cycle usually comprises several phases of varying timespans. The amount of emissions generated from different life cycle phases of a product could be significantly different from one another. In conventional LCA, the emissions generated from the life cycle phases of a product are aggregated at the inventory analysis stage, which is then used as an input for life cycle impact assessment. However, when the emissions are aggregated, the temporal variability of inventory data is ignored, which may result in inaccurate environmental impact assessment. Besides, the conventional LCA does not consider the environmental impact of circular products with multiple use cycles. It poses difficulties in identifying the hotspots of emission-intensive activities with the potential to mislead conclusions and implications for both practice and policy. To address this issue and to analyze the embedded temporal variations in inventory data in a CE context, the paper proposes calculating the emission intensity for each life cycle phase. It is argued that calculating and comparing emission intensity, based on the timespan and amount of emissions for individual life cycle phases, at the inventory analysis stage of LCA offers a complementary approach to the traditional aggregate emission-based LCA approach. In a circular scenario, it helps to identify significant issues during different life cycle phases and the relevant environmental performance improvement opportunities through product, business model, and supply chain design.

Suggested Citation

  • Sayyed Shoaib-ul-Hasan & Malvina Roci & Farazee M. A. Asif & Niloufar Salehi & Amir Rashid, 2021. "Analyzing Temporal Variability in Inventory Data for Life Cycle Assessment: Implications in the Context of Circular Economy," Sustainability, MDPI, vol. 13(1), pages 1-12, January.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:1:p:344-:d:473787
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    References listed on IDEAS

    as
    1. J. W. Owens, 1997. "Life‐Cycle Assessment in Relation to Risk Assessment: An Evolving Perspective," Risk Analysis, John Wiley & Sons, vol. 17(3), pages 359-365, June.
    2. Shelie A. Miller & Stephen Moysey & Benjamin Sharp & Jose Alfaro, 2013. "A Stochastic Approach to Model Dynamic Systems in Life Cycle Assessment," Journal of Industrial Ecology, Yale University, vol. 17(3), pages 352-362, June.
    3. J. W. Owens, 1997. "Life‐Cycle Assessment: Constraints on Moving from Inventory to Impact Assessment," Journal of Industrial Ecology, Yale University, vol. 1(1), pages 37-49, January.
    4. Anand, Chirjiv Kaur & Amor, Ben, 2017. "Recent developments, future challenges and new research directions in LCA of buildings: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 408-416.
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