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The rising demand for critical raw materials (CRMs) driven by renewable energy technologies poses challenges like price volatility, supply chain disruptions, and geopolitical risks. As most CRMs are sourced internationally, their supply is vulnerable; recycling provides a key solution. In this respect, this study develops a multi-period mixed-integer linear programming model under uncertainty to optimise Italy's CRM recycling supply chain. Photovoltaic panels, electric vehicle batteries, and neodymium magnets from wind turbines and electric vehicles are considered under various future scenarios, including net-zero emissions. Projections for 2030 and 2050 indicate a sharp rise in waste availability, requiring significant infrastructure expansion. Costs are expected to double by 2031, driven primarily by battery recycling, and reach 2154 M€ by 2050 under the net-zero scenario. Strategic placement of facilities is essential to balance processing and transport costs and adapt to evolving waste availability trends, ensuring a resilient and efficient supply chain.
Crîstiu et al. (Fri,) studied this question.