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Integrated Metrics for Improving the Life Cycle Approach to Assessing Product System Sustainability

Author

Listed:
  • Wesley Ingwersen

    (US Environmental Protection Agency, National Risk Management Laboratory, 26 W Martin Luther King Drive, Cincinnati, OH 45268, USA)

  • Heriberto Cabezas

    (US Environmental Protection Agency, National Risk Management Laboratory, 26 W Martin Luther King Drive, Cincinnati, OH 45268, USA)

  • Anne V. Weisbrod

    (Global Product Stewardship and Product Supply, The Procter & Gamble Company, Cincinnati, OH 45268, USA)

  • Tarsha Eason

    (US Environmental Protection Agency, National Risk Management Laboratory, 26 W Martin Luther King Drive, Cincinnati, OH 45268, USA)

  • Bayou Demeke

    (US Environmental Protection Agency, National Risk Management Laboratory, 26 W Martin Luther King Drive, Cincinnati, OH 45268, USA)

  • Xin Ma

    (US Environmental Protection Agency, National Risk Management Laboratory, 26 W Martin Luther King Drive, Cincinnati, OH 45268, USA)

  • Troy R. Hawkins

    (US Environmental Protection Agency, National Risk Management Laboratory, 26 W Martin Luther King Drive, Cincinnati, OH 45268, USA)

  • Seung-Jin Lee

    (US Environmental Protection Agency, National Risk Management Laboratory, 26 W Martin Luther King Drive, Cincinnati, OH 45268, USA)

  • Jane C. Bare

    (US Environmental Protection Agency, National Risk Management Laboratory, 26 W Martin Luther King Drive, Cincinnati, OH 45268, USA)

  • Manuel Ceja

    (Global Product Stewardship and Product Supply, The Procter & Gamble Company, Cincinnati, OH 45268, USA)

Abstract

Life cycle approaches are critical for identifying and reducing environmental burdens of products. While these methods can indicate potential environmental impacts of a product, current Life Cycle Assessment (LCA) methods fail to integrate the multiple impacts of a system into unified measures of social, economic or environmental performance related to sustainability. Integrated metrics that combine multiple aspects of system performance based on a common scientific or economic principle have proven to be valuable for sustainability evaluation. In this work, we propose methods of adapting four integrated metrics for use with LCAs of product systems: ecological footprint , emergy , green net value added , and Fisher information . These metrics provide information on the full product system in land, energy, monetary equivalents, and as a unitless information index; each bundled with one or more indicators for reporting. When used together and for relative comparison, integrated metrics provide a broader coverage of sustainability aspects from multiple theoretical perspectives that is more likely to illuminate potential issues than individual impact indicators. These integrated metrics are recommended for use in combination with traditional indicators used in LCA. Future work will test and demonstrate the value of using these integrated metrics and combinations to assess product system sustainability.

Suggested Citation

  • Wesley Ingwersen & Heriberto Cabezas & Anne V. Weisbrod & Tarsha Eason & Bayou Demeke & Xin Ma & Troy R. Hawkins & Seung-Jin Lee & Jane C. Bare & Manuel Ceja, 2014. "Integrated Metrics for Improving the Life Cycle Approach to Assessing Product System Sustainability," Sustainability, MDPI, vol. 6(3), pages 1-28, March.
  • Handle: RePEc:gam:jsusta:v:6:y:2014:i:3:p:1386-1413:d:34156
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    References listed on IDEAS

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    Cited by:

    1. Sergiy Smetana & Christine Tamásy & Alexander Mathys & Volker Heinz, 2015. "Sustainability and regions: sustainability assessment in regional perspective," Regional Science Policy & Practice, Wiley Blackwell, vol. 7(4), pages 163-186, November.
    2. Peter Tarne & Marzia Traverso & Matthias Finkbeiner, 2017. "Review of Life Cycle Sustainability Assessment and Potential for Its Adoption at an Automotive Company," Sustainability, MDPI, vol. 9(4), pages 1-23, April.
    3. Rawlings, E.Soraya & Barrera-Martinez, J.C. & Rico-Ramirez, Vicente, 2020. "Fisher information calculation in a complex ecological model: An optimal control-based approach," Ecological Modelling, Elsevier, vol. 416(C).

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