UK net-zero policy design - from optimisation to robustness
File(s)
Published version
Author(s)
Mendez, Quirina Rodriguez
Workman, Mark
Darch, Geoff
Type
Journal Article
Abstract
The need to deal with the deep uncertainty and system complexity associated to Net-Zero pathways, especially those relying on emergent greenhouse gas removal (GGR) technologies, has resulted in a growing body of literature on alternative decision-support approaches. Exploratory modelling, and specifically Robust Decision Making (RDM), are potential approaches capable of addressing these challenges: by exploring a wide range of conceivable futures, they explicitly embrace deep uncertainties while seeking to reduce system vulnerabilities. However, though RDM methods have been well documented, there is little insight as to how such approach might be integrated into Net-Zero policy design processes. By means of a workshop (n=17) and interviews (n=13) with the UK climate policy and energy modelling communities, this contribution provides insights into the role and potential of RDM in explicitly dealing with the deep uncertainties that pervade in the establishment of a 60–100 MtCO2 UK GGR sector within three decades. The consultation process revealed that there is an appetite from the decision-making and analytical communities in integrating exploratory modelling concepts into UK policy design processes. It is recommended that to bridge the gap between theoretical RDM constructs and their broader adoption, the analytical process should include a broader set of disciplines and expertise. Specifically for the modelling community, this work suggests that in-use computational models should be adapted, rather than new tools developed. Key challenges also arise from the time and resources required, suggesting small scale place-based pilots could promote the acceptability and foster the adoption of the RDM methodology.
Date Issued
2024-08
Date Acceptance
2024-06-02
Citation
Environmental Science and Policy, 2024, 158
ISSN
1462-9011
Publisher
Elsevier
Journal / Book Title
Environmental Science and Policy
Volume
158
Copyright Statement
© 2024 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
License URL
Identifier
https://www.sciencedirect.com/science/article/pii/S1462901124001382?via%3Dihub
Subjects
Climate modelling
CONTEXTS
DECISION-MAKING
Deep Uncertainty
DEEP UNCERTAINTY
Environmental Sciences
Environmental Sciences & Ecology
Greenhouse Gas Removal
Life Sciences & Biomedicine
Robust Decision Making
Science & Technology
United Kingdom Net-Zero target
Publication Status
Published
Article Number
103804
Date Publish Online
2024-06-07