TY  - JOUR
AB  - 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.
AU  - Gathrid, S.*
AU  - Wayland, J.D.
AU  - Wayland, S.*
AU  - Deshmukh, R.*
AU  - Wu, G.C.*
C1  - 75918
C2  - 58184
CY  - Heidelberger Platz 3, Berlin, 14197, Germany
SP  - 1274-1288
TI  - Strategies to accelerate US coal power phase-out using contextual retirement vulnerabilities.
JO  - Nat. Energy
VL  - 10
IS  - 10
PB  - Nature Portfolio
PY  - 2025
SN  - 2058-7546
ER  -