Strategies to accelerate US coal power phase-out using contextual retirement vulnerabilities

Sidney Gathrid, Jeremy Wayland, Stuart Wayland, Ranjit Deshmukh and Grace C. Wu ()
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Sidney Gathrid: University of California Santa Barbara
Jeremy Wayland: Krv Analytics
Stuart Wayland: Krv Analytics
Ranjit Deshmukh: University of California Santa Barbara
Grace C. Wu: University of California Santa Barbara

Nature Energy, 2025, vol. 10, issue 10, 1274-1288

Abstract: Abstract Strategically planning the phase-out of coal power is critical to achieve climate targets, yet current approaches often fail to account for the context-specific barriers and vulnerabilities to retirement. Here we introduce a framework that combines graph theory and topological data analysis to classify the US coal fleet into eight distinct groups based on technical, economic, environmental and socio-political characteristics. We calculate each non-retiring coal plant’s ‘contextual retirement vulnerability’ score, a metric developed to quantify susceptibility to retirement drivers using the graph-based distance to a coal plant with an announced early retirement. Separately, we identify ‘retirement archetypes’ that explain the key factors driving announced retirements within each group, which are used to inform group-specific strategies for accelerating retirements. Our findings reveal the diverse strategies that are required to accelerate the phase-out of remaining coal plants, including regulatory compliance, public health campaigns and economic incentives.

Date: 2025
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DOI: 10.1038/s41560-025-01871-0

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