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Futura: A new tool for transparent and shareable scenario analysis in prospective life cycle assessment

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  • P. James Joyce
  • Anna Björklund

Abstract

While it may be impossible to accurately predict what the world will look like in the future, we can be certain that it will be different from the world of today. By extension, we know that using today's data in life cycle assessment (LCA) studies claiming to represent future scenarios is problematic. For the future impact of products to be estimated in a consistent and meaningful manner in LCA, the background system, most commonly the ecoinvent database, needs to be projected into the future alongside the foreground system modeled in a given study. Futura is a new piece of open‐source software which allows LCA practitioners to create and share novel background databases representing arbitrary scenarios. It allows users to import a base database and then start making targeted changes. These changes take three main forms—adding new technologies, regionalizing new or existing technologies, and altering market compositions. All changes made are automatically added to a "recipe." This recipe file can be shared publicly. This recipe can be imported by other users and used to exactly recreate the modified database. The additive and transparent nature of this system means that initially simple scenarios can be built upon by others to progress toward more comprehensive scenarios in a stepwise manner. The inability to build on the work of others is a serious barrier to the progress of the LCA field. Futura goes some way to reduce this barrier in the field of prospective LCA.

Suggested Citation

  • P. James Joyce & Anna Björklund, 2022. "Futura: A new tool for transparent and shareable scenario analysis in prospective life cycle assessment," Journal of Industrial Ecology, Yale University, vol. 26(1), pages 134-144, February.
  • Handle: RePEc:bla:inecol:v:26:y:2022:i:1:p:134-144
    DOI: 10.1111/jiec.13115
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    References listed on IDEAS

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    1. Edgar Hertwich & Niko Heeren & Brandon Kuczenski & Guillaume Majeau†Bettez & Rupert J. Myers & Stefan Pauliuk & Konstantin Stadler & Reid Lifset, 2018. "Nullius in Verba: Advancing Data Transparency in Industrial Ecology," Journal of Industrial Ecology, Yale University, vol. 22(1), pages 6-17, February.
    2. Hanjiro Ambrose & Alissa Kendall, 2020. "Understanding the future of lithium: Part 2, temporally and spatially resolved life‐cycle assessment modeling," Journal of Industrial Ecology, Yale University, vol. 24(1), pages 90-100, February.
    3. Brandon Kuczenski, 2019. "Disclosure of Product System Models in Life Cycle Assessment: Achieving Transparency and Privacy," Journal of Industrial Ecology, Yale University, vol. 23(3), pages 574-586, June.
    4. Stefan Pauliuk & Niko Heeren & Mohammad Mahadi Hasan & Daniel B. Müller, 2019. "A general data model for socioeconomic metabolism and its implementation in an industrial ecology data commons prototype," Journal of Industrial Ecology, Yale University, vol. 23(5), pages 1016-1027, October.
    5. Angelica Mendoza Beltran & Brian Cox & Chris Mutel & Detlef P. van Vuuren & David Font Vivanco & Sebastiaan Deetman & Oreane Y. Edelenbosch & Jeroen Guinée & Arnold Tukker, 2020. "When the Background Matters: Using Scenarios from Integrated Assessment Models in Prospective Life Cycle Assessment," Journal of Industrial Ecology, Yale University, vol. 24(1), pages 64-79, February.
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