尽管向电动汽车（EVs）转型对于交通系统脱碳至关重要，但电动汽车的生产和分销会产生大量碳成本。为确保这些排放得到准确核算并被有效缓解，本研究引入了一个电动汽车供应链数字孪生，以弥补当前电动汽车生命周期分析中的关键空白，并首次对其环境可持续性和韧性进行全面量化。该仿真模型复现全球市场动态，捕捉电动汽车供应链的复杂性和不确定性，从而能够全面评估其碳足迹、可持续性、韧性，以及针对替代市场结构的假设反事实情景。结果表明，在不同电池技术下，平均供应链排放量介于6.42至6.94 Kg e-CO2/KWh之间。此外，物质流分析显示，供应链各阶段均存在不平衡的依赖关系，其中一个地理区域在供应链结构中占据显著主导地位，突显出当前供应链架构韧性低、脆弱性高。基于这些发现，本研究提出了一个用于枢纽与资源配置布局的优化模型，可将脆弱性水平和供应链排放有效降低至多80%。
英文摘要：
While the transition to electric vehicles (EVs) is essential for decarbonizing the transportation system, the production and distribution of EVs entail substantial carbon costs. To ensure these emissions are accurately accounted for and effectively mitigated, this research introduces a digital twin of the EV's supply chain, addressing a critical gap in current EV life cycle analyses and providing the first comprehensive quantification of its environmental sustainability and resilience. This simulation model replicates global market dynamics and captures the complexity and uncertainty of the EV supply chain, enabling a thorough evaluation of its carbon footprint, sustainability, resilience, and what-if counterfactual scenarios for alternative market structures. The results reveal that average supply chain emissions range from 6.42 to 6.94 Kg e-CO2/KWh across different battery technologies. Additionally, the mass flow analysis shows unbalanced dependencies at all supply phases, with one geographical region significantly dominating the supply chain structure, highlighting the current supply chain architecture's low resilience and high vulnerability. In light of these findings, the study introduces an optimization model for hub and resource allocation configuration, effectively reducing vulnerability levels and supply chain emissions by up to 80%.
An Analytical Framework for the Linear Best-Worst Method and its Application to Achieve Sustainable Development Goals--Oriented Agri-Food Supply Chains
An Environmentally Sustainable Closed-Loop Supply Chain Network Design under Uncertainty: Application of Optimization
Rajshahi University of Engineering & Technology (RUET)（拉杰沙希工程技术大学）；University of Arkansas at Little Rock（阿肯色大学小石城分校）；North Dakota State University（北达科他州立大学）；University of Alberta（阿尔伯塔大学）
Planning resilient hydrogen supply chains under disruption risk
Brandenburg University of Technology Cottbus–Senftenberg（勃兰登堡工业大学）；Potsdam Institute for Climate Impact Research（波茨坦气候影响研究所）；Interdisciplinary Transformation University Austria（奥地利跨学科转型大学）
Climate-resilient electric vehicle charging infrastructure for sustainable cities: An interpretable causal-ensemble framework for preventive maintenance and low-carbon mobility
Foshan University（佛山科学技术学院）；Jilin University（吉林大学）；National University of Singapore（新加坡国立大学）
