Models that study the socio-economic metabolism often apply a lifetime approach to capture the stock dynamics of products. The lifetime is usually obtained empirically from statistical information and is assumed to describe the dynamics of the product and its components. However, for new types of products for which historic outflow data is limited, or in cases where a critical component plays a significant role in determining product end-of-life, a more refined understanding of the dynamics of product-component systems is needed. Here, we provide a new framework for product-component systems and 12 different approaches to model their stock dynamics. Then, we discuss which approaches are best suited in different contexts.We illustrate the use of the framework with a case study on electric vehicles and their batteries, highlighting the potential of battery replacement and reuse for reducing material demand. Improving the understanding of these complex systems is relevant for the study of the socio-economic metabolism because (i) accounting for component dynamics can support identifying unintended consequences of product-specific policies; (ii) component replacement and reuse can be a key circular economy strategy to foster efficient resource use; and (iii) accounting for these complex dynamics can lead to more accurate estimates for resource demand and waste-generation expectations, creating more resilient information streams. This article met the requirements for a Gold-Gold JIE data openness badge described at https://jie.click/badges.

Retired passenger battery electric vehicles (BEVs) are expected to generate significant volumes of lithium-ion batteries (LIBs), opening business opportunities for second life and recycling. In order to evaluate these, robust estimates of the future quantity and composition of LIBs are imperative. Here, we analyzed BEV fate in the Norwegian passenger vehicle fleet and estimated the corresponding battery capacity in retired vehicles from 2011 to 2030, using a stock-flow vehicle cohort model linked to analysis of the battery types and sizes contained in different BEVs. Results based on this combination of modeled and highly disaggregated technical data show that (i) the LIB energy capacity available for second use or recycling from end-of-life vehicles is expected to reach 0.6 GWh in 2025 and 2.1 GWh in 2030 (not accounting for any losses); (ii) most LIBs are currently contained within the weight segment 1500-1599 kg followed by 2000+ kg; (iii) highest sales currently exist for BEVs containing lithium nickel manganese cobalt oxide (NMC) batteries; and (iv) lithium nickel cobalt aluminum oxide batteries initially constitute the largest overall capacity in retired vehicles, but will later be surpassed by NMCs. The results demonstrate rapidly growing opportunities for businesses to make use of retired batteries and a necessity to adapt to changing battery types and sizes.

No abstract

No abstract