Bioenergy technologies in long-run climate change mitigation: results from the EMF-33 study

Vassilis Daioglou (), Steven K. Rose, Nico Bauer, Alban Kitous, Matteo Muratori, Fuminori Sano, Shinichiro Fujimori, Matthew J. Gidden, Etsushi Kato, Kimon Keramidas, David Klein, Florian Leblanc, Junichi Tsutsui, Marshal Wise and Detlef P. Vuuren
Additional contact information
Vassilis Daioglou: PBL Netherlands Environmental Assessment Agency
Steven K. Rose: Electric Power Research Institute
Nico Bauer: Leibniz Association
Alban Kitous: Joint Research Centre of the European Commission
Matteo Muratori: National Renewable Energy Laboratory
Fuminori Sano: Research Institute of Innovative Technology for the Earth
Shinichiro Fujimori: National Institute for Environmental Studies
Matthew J. Gidden: International Institute for Applied Systems Analysis (IIASA)
Etsushi Kato: The Institute of Applied Energy
David Klein: Leibniz Association
Florian Leblanc: International Research Center on the Environment and Development (CIRED)
Junichi Tsutsui: Central Research Institute of Electric Power Industry
Marshal Wise: Pacific Northwest National Laboratory and the University of Maryland
Detlef P. Vuuren: PBL Netherlands Environmental Assessment Agency

Climatic Change, 2020, vol. 163, issue 3, No 26, 1603-1620

Abstract: Abstract Bioenergy is expected to play an important role in long-run climate change mitigation strategies as highlighted by many integrated assessment model (IAM) scenarios. These scenarios, however, also show a very wide range of results, with uncertainty about bioenergy conversion technology deployment and biomass feedstock supply. To date, the underlying differences in model assumptions and parameters for the range of results have not been conveyed. Here we explore the models and results of the 33rd study of the Stanford Energy Modeling Forum to elucidate and explore bioenergy technology specifications and constraints that underlie projected bioenergy outcomes. We first develop and report consistent bioenergy technology characterizations and modeling details. We evaluate the bioenergy technology specifications through a series of analyses—comparison with the literature, model intercomparison, and an assessment of bioenergy technology projected deployments. We find that bioenergy technology coverage and characterization varies substantially across models, spanning different conversion routes, carbon capture and storage opportunities, and technology deployment constraints. Still, the range of technology specification assumptions is largely in line with bottom-up engineering estimates. We then find that variation in bioenergy deployment across models cannot be understood from technology costs alone. Important additional determinants include biomass feedstock costs, the availability and costs of alternative mitigation options in and across end-uses, the availability of carbon dioxide removal possibilities, the speed with which large scale changes in the makeup of energy conversion facilities and integration can take place, and the relative demand for different energy services.

Keywords: Bioenergy; Biomass; Climate policy; Technological change; Scenario analysis; Integrated assessment models (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (7)

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DOI: 10.1007/s10584-020-02799-y

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