废旧三元锂离子电池回收利用碳足迹

公路运输是我国交通运输领域主要温室气体排放源,新能源汽车行业作为实现交通运输领域“双碳”目标的重要抓手,未来面临大批动力电池报废情况,为量化评估废旧锂电池回收利用行业产生的碳减排效益,从生命周期角度构建废旧三元锂电池回收利用碳足迹核算模型,通过优化电力结构和运输结构,对废旧锂电池回收利用的碳减排潜力作预测评估,此外,使用误差传播方程进行不确定性分析保证碳足迹结果的可靠有效.结果表明,当前中国企业使用湿法技术回收1 kg废旧三元锂电池的碳足迹为-2760.90 g（定向循环工艺）和-3752.78 g（循环再造工艺）,碳足迹的不确定性分别为16 %（定向循环工艺）和15 %（循环再造工艺）.从碳排放贡献率分析,再生产品阶段是废旧三元锂电池湿法回收利用减碳首要贡献来源,电池获取、拆解和末端处置阶段是增碳主要来源.相比于优化运输结构,通过优化电力结构,可有效实现更大的碳减排潜力,协同优化情景下,相比于优化前可实现14 %~19 %的碳减排,与原生产品相比定向循环工艺和循环再造工艺分别可实现9 %和11 %的减排潜力.

Carbon Footprint of Spent Ternary Lithium-Ion Battery Waste Recycling

Road transport is the primary source of greenhouse gas emissions in China''s transportation field. As an important means to achieve the "double carbon" goal in the transportation field, the new energy automobile industry will face a large number of power battery scrapping in the future. In order to quantitatively assess the carbon emission reduction benefits generated by the spent ternary lithium-ion battery waste recycling industry, the carbon footprint accounting model of spent ternary lithium-ion battery waste recycling and utilization was constructed from the life cycle perspective. By optimizing the power structure and transportation structure, the carbon emission reduction potential of spent ternary lithium-ion battery waste recycling was predicted and evaluated. In addition, the uncertainty analysis was conducted using the propagation of uncertainty equation to ensure the reliability and effectiveness of the carbon footprint results. The results showed that the current carbon footprint of Chinese enterprises using wet technology to recover 1 kg waste lithium batteries was -2 760.90 g (directional recycling process) and -3 752.78 g (recycling process), and the uncertainty of the carbon footprint was 16 % (directional recycling process) and 15 % (recycling process), respectively. From the analysis of carbon emission contribution, the regenerated product stage was the primary source of carbon reduction in the wet recycling and utilization of waste ternary lithium batteries, whereas the battery acquisition, disassembly, and end treatment stages were the main sources of carbon increase. Compared to optimizing the transportation structure, optimizing the power structure could effectively achieve greater carbon emission reduction potential. Under the collaborative optimization scenario, compared to that before optimization, 14 %-19 % carbon emission reduction could be achieved. Compared with native products, the directional circulation process and recycling process could achieve 9 % and 11 % emission reduction potential, respectively.