The production of carbon dioxide (CO2) is the largest contributor to global warming. The primary source of these emissions is petroleum-derived fuel used in transportation, specifically in internal combustion engine vehicles. In response, the European Union (EU) has implemented a low-emission mobility strategy, aiming to shift towards low-carbon transportation. This strategy includes ambitious targets for electric vehicle (EV) adoption with at least 30 million zero-emission vehicles expected to be on European roads by 2030. This push towards EVs is driving up demand for lithium-ion batteries (LIBs).
While efforts to improve efficiency in EV battery production and use are intended to reduce environmental impacts, they might potentially lead to unintended consequences known as rebound effects. Rebound effects occur when efficiency improvements result in increased consumption or production elsewhere in the system, negating the expected benefits. These effects can arise from both behavioural and systemic responses to efficiency gains. Current discussions and policy frameworks often overlook the potential rebound effects in CE activities, particularly concerning EV batteries. This oversight poses a significant risk to the effectiveness of initiatives aimed at reducing CO2 emissions and advancing CE practices. Therefore, it is crucial to investigate these rebound effects within the CE context for EV batteries to develop effective mitigation strategies.
There is a noticeable gap in the existing literature regarding the interconnected dynamics of CE practices and rebound effects in the context of EV batteries. While some studies have explored rebound effects in other sectors, limited research examines how CE practices for EV batteries contribute to rebound effects across different lifecycle stages. To ensure the sustainability of CE initiatives, it is essential to adopt a systemic view that considers these effects. By doing so, businesses can develop strategies that not only focus on recycling and efficiency but also address broader systemic impacts, ensuring that increased demand does not negate the benefits of circular practices.
The research employs qualitative SD to examine potential rebound effects in the CE system for EV batteries. This approach allows for a comprehensive understanding of the system's dynamics by identifying causal relationships between physical and behavioural components. The study uses CLDs to represent the interconnections and feedback processes within the circular economy of EV batteries, helping to identify reinforcing and balancing feedback loops that drive system behaviour. The initial phase involves identifying key variables that influence the system's behaviour. These variables include economic incentives, technological advancements, regulatory frameworks, consumer behaviour, and environmental impacts. The relationships between these variables are mapped to create CLDs, which are then iteratively refined based on expert feedback to ensure accuracy and relevance.
Expert interviews are conducted to validate and refine the constructed CLDs. Professionals with in-depth knowledge of the circular economy and EV batteries provide insights that help verify the model's assumptions, structure, and behaviour. This validation process includes discussions on potential oversights or nuances that the initial model may not fully capture. The methodology also involves developing Circular Business Models (CBMs) as strategies to mitigate rebound effects. A review of existing business model innovations in the CE context is conducted to identify patterns relevant to EV batteries. These business model patterns are categorized to align with the rebound mechanism categories, facilitating a cohesive analysis.
The study identifies key mechanisms within the EV battery lifecycle that can lead to rebound effects, particularly during the usage phase. Three significant mechanisms—Income, Substitution, and Demand Adjustment by Efficiency—were found to be most prominent in this phase. To mitigate these effects, the research proposes various strategies. Dynamic Pricing emerges as the most effective strategy, capable of addressing all three mechanisms by adjusting prices in response to real-time market conditions, thereby preventing excessive consumption and production. Alternative strategies such as Pay per Use and Subscription models also show promise in mitigating rebound effects by promoting efficient use and reducing the need for outright ownership.
The research highlights the importance of understanding these mechanisms and selecting suitable strategies to mitigate rebound effects. Firms must focus on the identified mechanisms and integrate appropriate strategies into their business models to ensure sustainable practices. Furthermore, the study underscores the necessity of engaging a diverse range of stakeholders, including consumers, policymakers, and industry practitioners, to develop comprehensive and inclusive CE strategies. Future research should continue to refine these strategies and explore the dynamic interactions within the EV battery lifecycle to enhance the effectiveness of CE initiatives.