An exploration and evaluation framework for climate change mitigation scenarios with varying feasibility and desirability

Beath, H., Mittal, S., Lamboll, R., & Rogelj, J. ORCID: https://orcid.org/0000-0003-2056-9061 (2025). An exploration and evaluation framework for climate change mitigation scenarios with varying feasibility and desirability. Environmental Research Letters 20 (7) e074020. 10.1088/1748-9326/addd35.

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Abstract

Ensembles of climate change mitigation scenarios present users with a collection of strategies for limiting global warming. These strategies may differ in their associated feasibility challenges, mitigation co-impacts, and ultimately their relative societal desirability. Understanding these scenario characteristics is therefore crucial when scenarios are used to inform strategic decisions. One approach to enhance this understanding is to establish scenario archetypes and select contrasting illustrative scenarios from a larger ensemble. We present a new multidimensional framework for the systematic comparison of scenarios at the global or regional level. We illustrate the framework with comparisons in seven dimensions: economic feasibility, mineral resource availability, impacts on societal resilience, near-term scenario robustness, environmental sustainability, interregional fairness, and speed of societal transformation. Using cluster analysis, the framework can be used to select a group of illustrative scenarios with contrasting scores across the dimensions. Beyond the selection of scenarios, our exploration and evaluation framework also allows the identification of gaps in the scenario space that may be of interest but are not covered by the literature. We demonstrate these use cases by applying our framework to a set of mitigation scenarios that limit warming to 1.5 °C. Our results show our framework systematically selects contrasting scenarios, with our illustrative pathways having diverging energy mixes and uses of carbon dioxide removal. Further, we highlight considerable regional differences in the distribution of indicator and dimension scores as a key area for further investigation.

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