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

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.

Authors

PBL Authors
Vassilis Daioglou Detlef van Vuuren
Other authors
Alexandre C. Köberle
Pedro Rochedo
André F. P. Lucena
Alexandre Szklo
Shinichiro Fujimori
Thierry Brunelle
Etsushi Kato
Alban Kitous
Roberto Schaeffer

Specifications

Publication title
Can global models provide insights into regional mitigation strategies? A diagnostic model comparison study of bioenergy in Brazil
Publication date
4 January 2022
Publication type
Article
Publication language
English
Magazine
Climatic Change
Issue
volume 170, Article number: 2 (2022)
Product number
4899