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Energy system models as a means of visualising barriers and drivers of forest-based biofuels: An interview study of developers and potential users
Linköping University, Sweden.
RISE - Research Institutes of Sweden, Built Environment, Energy and Circular Economy.
Luleå University of Technology, Sweden.
2017 (English)In: Sustainability, ISSN 2071-1050, E-ISSN 2071-1050, Vol. 9, no 10, article id 1792Article in journal (Refereed) Published
Abstract [en]

Forest-derived biofuels have been on the agenda for several decades. Despite extensive research and development efforts, forest biofuel concepts have nevertheless not yet been realized on any significant scale. The discrepancy between the expectations from the research community and the lack of momentum regarding biofuel production raises the question of if and how research results can be used to achieve such goals. Here, we report results from an interview study with the aim of evaluating how energy system models can be used to illustrate barriers and drivers for forest biofuels, with focus on Swedish conditions, using the BeWhere model as case. The study is framed as an example of expertise, and problematizes how energy system models are interpreted among expected users. While the interviews revealed some general scepticism regarding models, and what kinds of questions they can answer, the belief was also expressed that increased complexity might be an advantage in terms of being able to accommodate more barriers against forest biofuels. The study illustrates the complexity of this policy area, where an energy system model can answer some, but never all, 'what if.?' questions. The results reveal a need for reformation in energy system modelling in order to more explicitly make society the subject of the work, and also illustrate that the belief in expertise as a tool for consensus-building in decision-making should be questioned.

Place, publisher, year, edition, pages
2017. Vol. 9, no 10, article id 1792
Keywords [en]
Barriers and drivers, Biofuels, Energy system models, Energy systems analysis, Expertise, Interviews
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:ri:diva-32423DOI: 10.3390/su9101792Scopus ID: 2-s2.0-85030460193OAI: oai:DiVA.org:ri-32423DiVA, id: diva2:1153824
Available from: 2017-10-31 Created: 2017-10-31 Last updated: 2017-10-31Bibliographically approved

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CiteExportLink to record
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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
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