With the rapid growth in the number of new energy pure electric vehicles, China is about to enter a phase of concentrated retirement of power batteries. The recycling and treatment of retired batteries will have significant environmental impacts and exhibit spatial heterogeneity. Existing research primarily focuses on national aggregate levels, lacking integrated analysis of the “spatiotemporal distribution of retired batteries—environmental impacts of recycling processes—regional environmental impact variations.” This study forecasts the retirement volume of ternary lithium batteries across Chinas 31 provinces (autonomous regions and municipalities) from 2025 to 2031 based on pure electric vehicle ownership, integrating this with life cycle assessment (LCA). Within SimPro, an inventory model was established using “combined thermal-wet recycling of 1 kg of end-of-life ternary lithium battery cells” as the functional unit. The ReCiPe2016 Midpoint methodology was employed to quantify indicators, including global warming potential (GWP), human toxicity (HT), eutrophication potential (EP), acidification potential (AP), and ozone depletion potential (ODP). The unit impacts were further scaled to regional levels to derive the environmental impact potential at the regional level during the wave of battery retirement. Results indicate significant provincial variations in retired ternary lithium batteries and their environmental impact potential. Provinces with substantial environmental impacts are primarily concentrated in regions with high new energy vehicle penetration and dense economic activity. By 2025, Beijing and Guangdong should prioritize optimizing battery recycling technologies. By 2031, a trend toward expansion into Central China emerges, with impacts concentrated in Central, East, South, and North China, where the highest carbon emissions could reach 12 million tons. Guangdong and Jiangsu will replace Beijing as the highest carbon emitters, while Qinghai will replace Tibet as one of the lowest emitters. Process contribution analysis indicates that energy consumption and key chemical inputs during the wet processing stage dominate multiple indicators. This research provides quantitative evidence for prioritizing recycling zone planning and process optimization.
Jun et al. (Tue,) studied this question.