The green gridlock: Projecting the unintended wildfire evacuation risks of EV adoption
研究电动汽车普及如何因依赖脆弱电网而增加野火疏散风险，开发地理空间框架识别高风险社区，为充电资源部署和疏散规划提供依据。
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.