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Can global models provide insights into regional mitigation strategies? A diagnostic model comparison study of bioenergy in Brazil

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Title: Can global models provide insights into regional mitigation strategies? A diagnostic model comparison study of bioenergy in Brazil
Authors: Köberle, AC
Daioglou, V
Rochedo, P
Lucena, AFP
Szklo, A
Fujimori, S
Brunelle, T
Kato, E
Kitous, A
Van Vuuren, DP
Schaeffer, R
Item Type: Journal Article
Abstract: The usefulness of global integrated assessment model (IAM) results for policy recommendation in specific regions has not been fully assessed to date. This study presents the variation in results across models for a given region, and what might be behind this variation and how model assumptions and structures drive results. Understanding what drives the differences across model results is important for national policy relevance of global scenarios. We focus on the use of bioenergy in Brazil, a country expected to play an important role in future bioenergy production. We use results of the Stanford University Energy Modeling Forum’s 33rd Study (EMF-33) model comparison exercise to compare and assess projections of Brazil’s bioenergy pathways under climate mitigation scenarios to explore how 10 global IAMs compare to recent trends in the country. We find that, in their current form, global IAMs have limited potential to supply robust insights into regional mitigation strategies. Our results suggest fertile ground for a new research agenda to improve regional representation in global IAMs with improved spatial and technological resolutions.
Issue Date: Jan-2022
Date of Acceptance: 2-Oct-2021
URI: http://hdl.handle.net/10044/1/94168
DOI: 10.1007/s10584-021-03236-4
ISSN: 0165-0009
Publisher: Springer Science and Business Media LLC
Start Page: 1
End Page: 31
Journal / Book Title: Climatic Change
Volume: 170
Issue: 1-2
Copyright Statement: © The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Keywords: Meteorology & Atmospheric Sciences
Publication Status: Published
Open Access location: https://link.springer.com/article/10.1007/s10584-021-03236-4
Article Number: 2
Online Publication Date: 2022-01-04
Appears in Collections:Grantham Institute for Climate Change



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