The green gridlock: Projecting the unintended wildfire evacuation risks of EV adoption

Abstract

The rapid adoption of electric vehicles (EVs), while crucial for climate goals, introduces complex challenges for emergency management. This study addresses the urgent, yet under-researched risk of wildfire evacuations in EV-dependent communities, whose mobility is tightly coupled with a vulnerable electrical grid. We develop a novel geospatial framework grounded in the Vulnerability-Exposure-Sensitivity model and operationalized through a Community Preparedness Index that integrates socioeconomic, demographic, mobility, and infrastructural characteristics. Hotspot analysis identifies spatial clusters of wildfire exposure, EV sensitivity, and community preparedness, enabling classification of evacuation risk profiles driven by transportation system dependence on electrified mobility. A Gaussian Process Regression informed S-curve forecasting approach estimates when communities are likely to reach critical risk levels as EV adoption increases. Results show significant spatial disparities, providing evidence to strategically deploy charging resources, grid hardening, and evacuation focused planning. The framework supports proactive, data-informed planning for resilient electrified transportation systems in wildfire-prone regions.