Bioenergy in energy transformation and climate management
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This study explores the importance of bioenergy to potential future energy transformation and climate change management. Using a large inter-model comparison of 15 models, we comprehensively characterize and analyze future dependence on, and the value of, bioenergy in achieving potential long-run climate objectives. Model scenarios project, by 2050, bioenergy growth of 1 to 10 % per annum reaching 1 to 35 % of global primary energy, and by 2100, bioenergy becoming 10 to 50 % of global primary energy. Non-OECD regions are projected to be the dominant suppliers of biomass, as well as consumers, with up to 35 % of regional electricity from biopower by 2050, and up to 70 % of regional liquid fuels from biofuels by 2050. Bioenergy is found to be valuable to many models with significant implications for mitigation and macroeconomic costs of climate policies. The availability of bioenergy, in particular biomass with carbon dioxide capture and storage (BECCS), notably affects the cost-effective global emissions trajectory for climate management by accommodating prolonged near-term use of fossil fuels, but with potential implications for climate outcomes. Finally, we find that models cost-effectively trade-off land carbon and nitrous oxide emissions for the long-run climate change management benefits of bioenergy. The results suggest opportunities, but also imply challenges. Overall, further evaluation of the viability of large-scale global bioenergy is merited.
KeywordsBiogas Climate Policy Biomass Feedstock Climate Target Climate Change Management
This article benefitted greatly from the comments of the anonymous reviewers, as well as from overall feedback from EMF-27 Study participants. The contribution of S.R. was supported by the Electric Power Research Institute. The contributions of E.K., A.P., and D.v.V. were supported by funding from the European Commission’s Seventh Framework Programme under the LIMITS project (grant agreement no. 282846). The contribution of R.B. was supported with funding from the Chair “Modeling for Sustainable Development.” The contribution of K.C. was supported by the Office of Science of the U.S. Department of Energy as part of the Integrated Assessment Research Program. The views expressed in this work are solely those of the authors and do not represent those of funding organizations. All errors are our own.
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