Environmental Research Letters (Jan 2020)

Review of life-cycle based methods for absolute environmental sustainability assessment and their applications

  • Anders Bjørn,
  • Chanjief Chandrakumar,
  • Anne-Marie Boulay,
  • Gabor Doka,
  • Kai Fang,
  • Natacha Gondran,
  • Michael Zwicky Hauschild,
  • Annemarie Kerkhof,
  • Henry King,
  • Manuele Margni,
  • Sarah McLaren,
  • Carina Mueller,
  • Mikołaj Owsianiak,
  • Greg Peters,
  • Sandra Roos,
  • Serenella Sala,
  • Gustav Sandin,
  • Sarah Sim,
  • Marcial Vargas-Gonzalez,
  • Morten Ryberg

DOI
https://doi.org/10.1088/1748-9326/ab89d7
Journal volume & issue
Vol. 15, no. 8
p. 083001

Abstract

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In many regions and at the planetary scale, human pressures on the environment exceed levels that natural systems can sustain. These pressures are caused by networks of human activities, which often extend across countries and continents due to global trade. This has led to an increasing requirement for methods that enable absolute environmental sustainability assessment (AESA) of anthropogenic systems and which have a basis in life cycle assessment (LCA). Such methods enable the comparison of environmental impacts of products, companies, nations, etc, with an assigned share of environmental carrying capacity for various impact categories. This study is the first systematic review of LCA-based AESA methods and their applications. After developing a framework for LCA-based AESA methods, we identified 45 relevant studies through an initial survey, database searches and citation analysis. We characterized these studies according to their intended application, impact categories, basis of carrying capacity estimates, spatial differentiation of environmental model and principles for assigning carrying capacity. We then characterized all method applications and synthesized their results. Based on this assessment, we present recommendations to practitioners on the selection and use of existing LCA-based AESA methods, as well as ways to perform assessments and communicate results to decision-makers. Furthermore, we identify future research priorities intended to extend coverage of all components of the proposed method framework, improve modeling and increase the applicability of methods.

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