From Demand to Circularity: Rethinking National Strategy on Automobile Battery Supply Chain for Sustainability

From Demand to Circularity: Rethinking National Strategy on Automobile Battery Supply Chain for Sustainability | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article From Demand to Circularity: Rethinking National Strategy on Automobile Battery Supply Chain for Sustainability Yi Dou, Aya Heiho, Yasunori Kikuchi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7959887/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The rapid electrification of transport is driving soaring demand for lithium-ion batteries (LIBs), straining critical mineral supply chains. While policy efforts increasingly emphasize circularity, the diverse and uncertain impacts of supply chain interventions remain poorly understood. We develop a globally applicable scenario-based dynamic material flow simulator incorporating eight drivers with 20 policy options to assess their individual and combined effects on resource conservation and circularity in automotive LIBs. Using the world’s largest car exporter, Japan, as a case, we show that even late EV adopters can rapidly close critical mineral loops through intensive policy measures, though results depend strongly on policy combinations. Supplier-side policies can at best reduce mineral demand, while user-side actions more strongly boost circularity. Accelerated recycling of end-of-life LIBs is most influential, followed by advanced battery design. Cross-border traceability, mandatory collection, recycling infrastructure, carbon-neutral fuels, and compact urban design moderately reduce demand but contribute less to circularity. Extending battery life presents trade-offs while restricting the export of used vehicles has a limited effect. We reveal strong synergies among coordinated policies and trade-offs between short-term resource efficiency and long-term circularity. Our results stress the need for integrated, stage-specific strategies that align resource security with circular economy goals. Openly accessible online, the simulator enables nations to craft tailored policies and support international negotiation. Earth and environmental sciences/Environmental sciences/Environmental impact Scientific community and society/Business and industry/Industry Scientific community and society/Energy and society/Energy security Earth and environmental sciences/Environmental social sciences/Sustainability Earth and environmental sciences/Environmental social sciences/Climate-change mitigation critical mineral lithium-ion battery material flow analysis electric mobility supply chain circular economy decarbonization Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1 Introduction The rapid expansion of electric vehicles (EVs) and batteries is reshaping climate and industrial strategies. EV deployment and battery recycling are increasingly recognized as essential for transport decarbonization 1 , while also raising concerns over economic security and supply chain resilience 2 . In 2022, the transport sector emitted 7.98 Gt-CO₂, accounting for 23% of global emissions 3 . Expanding EV adoption with a decarbonized power system is therefore critical, but it requires large amounts of critical minerals for lithium-ion batteries (LIBs) 4 , including lithium 5 , nickel, cobalt 6 , and manganese 7 . The global EV stock reached 28 million in 2022 and is projected to grow to 790 million by 2035 to align with net-zero targets for 2050 8 . This growth would raise mineral demand 20–40 times by 2040 compared with 2020 levels 9 , with prices expected to rise sharply under net-zero scenarios 10 . Given these pressures, together with risks of shortages and humanitarian crises linked to conflict minerals, improving resource efficiency and advancing circularity in the automotive LIB sector is imperative 11 . To address these challenges, numerous policy measures have been proposed and tested, yet no single effective solution has emerged due to limited quantitative assessment of their merits and drawbacks. While advances in battery technology and recycling are widely recognized strategies to improve resource efficiency in the automotive LIB supply chain 12 , they cannot immediately close the gap between the increasing demand and the delayed secondary supply of critical minerals 13 . Reducing the cobalt content of batteries through chemical shifts 14 , such as wider adoption of lithium iron phosphate (LFP) 15 , or raising energy density with lithium-sulphur (Li-S) and lithium-air (Li-Air) batteries 16 can reduce dependence on primary minerals. However, recycling of LFP batteries lacks economic incentives 17 due to the absence of collection premiums and low lithium recovery rates 18 , with even the questionable quality of recovered lithium requisitioned for reuse in LIB manufacturing 19 . Next-generation chemistries require decades to commercialize 20 and reducing cobalt increases nickel demand 21 , while cobalt is still projected to remain in use for performance gains 22 . Recycling maximizes the recovery of critical minerals 23 but is hindered by the low collection rates and secondary use 24 and by challenges in environmental impacts 25 – recent mainstream pyro- or hydrometallurgy treatments cannot avoid huge energy and resource inputs 26 . Furthermore, expedited recycling could forfeit substantial economic benefits from secondary use in peak shaving and stationary storage 27 . Beyond these strategies, improving collection and recycling rates and extending battery lifespans 28 are also frequently emphasized. In summary, the extent to which such measures can drive meaningful improvements individually or together in the circularity of critical minerals remains insufficiently understood. To reshape a sustainable automotive LIB supply chain, leading EV manufacturers and exporters are accelerating efforts to secure recycled materials, strengthen supply chain resilience, and increase material circularity. The EU has enacted stringent battery regulations together with the Carbon Border Adjustment Mechanism, enforcing circularity targets and deadlines for critical minerals in LIBs 29 . This creates strong pressure on manufacturers and exporters worldwide. In the USA, the revised Inflation Reduction Act excludes batteries containing critical minerals extracted, processed, or recycled by foreign entities of concern from the Clean Vehicle Tax Credit. China has rushed investments into recycling capacity that are quetioned to double the global supply of end-of-life batteries by 2030 8 . The large exports of used hybrid vehicles from Japan 30 have sparked debates on restricting used-EV exports for collecting spent LIBs 31 . With more countries designating battery minerals as strategic resources, national battery passports and traceability systems are being introduced. The EU has already launched its own battery passport, and Japan has initiated the Ouranos Ecosystem Project to track EV and LIB supply chains 32 . Looking ahead, the global LIB industry will be subject to growing policy interventions at nation level, even in times of world crisis, direct governmental control remains possible. Two major challenges emerge during rapid global shifts. First, policies across countries are fragmented, covering the entire supply chain yet lacking prioritization. Regulations on battery recycling differ widely in enforcement, producer responsibility, waste classification, targets, design standards, public participation, and incentives 33 . Such disparities impede cross-border data sharing and unified regulation, and only a small share of retired LIBs currently reach high-quality reuse or recycling facilities 34 . Given the complexity of supply chains and the uneven resource distribution, even national measures can have global ripple effects, making international coordination on standards essential 35 . Second, market responses to battery electric vehicles (BEVs) diverge. For example, the United States trails the EU and China, Japan is still at an early stage of development, and Southeast Asia is now an emerging market after the EU and China 36 . Since extraction and smelting still dominate life cycle burdens 26 , distribution of industrial development, EV markets, and socio-environmental impacts reveal high disparity. National-level assessment of individual and combined supply chain policies is crucial for advancing regional governance, international coordination, and life cycle management 37 . Japan, which is both the world’s largest automobile exporter and a latecomer in EV adoption, is particularly exposed to domestic and foreign policy shifts, making it a representative case for circular strategy design. This study develops a scenario-based integrated dynamic material flow simulator to model material circulation in automotive LIBs, grounded in ongoing global debates on resource security policies. The simulator is designed as a transparent and easy-to-use tool: by setting local parameters and choosing policies, users can automatically calculate the outcomes of any combination of policy options. It can thus be adapted by any nation to design optimized circularity strategies, strengthen its negotiating position, and support constructive international dialogue. Building on previous dynamic materials flow analyses, our model incorporates a broad set of supply- and demand-side factors, including battery upgrades, lifespan, traceability, recycling progress, EV penetration, secondary use, used-car exports, and traffic demand management (Fig. 1 ). We apply the simulator to Japan, a nation with limited mineral resources but a leading role in global automobile exports. The results show that even Japan, a latecomer in EV industrial development, could reduce total demand for critical minerals by up to 82% and raise circularity above 80% by 2050 through robust combined policy interventions. The complex interactions between supplier- and user-side measures produce diverse impacts on the LIB supply chain, and these uncertainties were explicitly quantified in our simulation. These findings underscore the role of comprehensive resource management in advancing sustainable battery supply chains and shaping fairer international negotiations. 2 Results 2.1 Framing of policy options and scenario design To capture the variability in the demand for and circularity of critical minerals stemming from policy interventions across the automotive LIB supply chain, we identified eight key drivers and 20 policy options which span both supplier- and user-side interventions (Fig. 1 b). Supplier-side options include: ① Battery chemical shifts – accounting for transitions from Co-rich chemistries to Co-free alternatives, such as LFP, and future candidates, such as Li-S or Li-Air; ② Service life of LIBs – reflecting durability and performance enhancements through policy and technological innovation; ③ Tracing and mandatory collection – encompassing domestic regulations and Japan’s influence via overseas export channels; ④ Advancements in recycling – addressing the current challenges in LFP recycling and improving recovery rates for critical minerals. User-side options include: ⑤ BEV penetration vs. carbon-neutral fuels (CNF) penetration – reflecting the balance between BEV deployment and the adoption of CNF in plug-in hybrid electric vehicles (PHEVs); ⑥ Secondary use vs. expedited recycling – capturing trade-offs between economic value and critical mineral circulation speed; ⑦ Regulation on used-car exports – targeting material losses through untracked cross-border flows; ⑧ Traffic demand management – leveraging compact city planning and car-sharing schemes to reduce passenger car demand. These socio-economic changes and policy interventions drive key variations. In Japan, passenger vehicle ownership is anticipated to decline from 60.7 million in 2024 to 53.2 million by 2050 due to depopulation, and further to 47.2 million under compact city and car-sharing policies (Figure S10). Annual registrations and deregistrations are also expected to both fall by about 20% during 2025–2050 (Figure S16). By 2050, internal-combustion engine vehicles (ICEVs) will have nearly disappeared, while hybrid electric vehicle (HEV) ownership peaks in 2040 before dropping to 20 million by 2050. EVs account for about two-thirds of passenger vehicles (Figure S21). Depending on policy combinations, spent LIB collection in 2050 ranges from 400 to 3,000 kt pack weight with diverse chemistries (Figure S25). Meanwhile, used-EV exports steadily rise, reaching about 400,000 units by 2050 (Figure S27). To systematically explore the interactions among these policies, each option was assigned a level of influence (i.e. 1 = weak, 2 = moderate and 3 = strong), forming a 3⋅3 matrix of nine scenarios (i.e. S11–S33, Fig. 1 c). These scenarios represent varying degrees of policy ambition and system transformation. S11 reflects the status quo in Japan with minimal supply chain intervention, while S33 represents an ambitious pathway where all policies are enacted at their strongest levels. Intermediate scenarios (e.g. S21, S22, S23, S32) reflect mixed levels of policy intensity. An additive scenario matrix is further constructed to assess both the individual and synergistic effects of each option relative to the baseline (S11), thereby identifying effective strategies for enhancing critical mineral circularity. The selection and structuring of these policy options are based on the premise of leveraging national influence to govern various segments of the battery supply chain and thereby control the material flow of critical metals. Disruptive innovations or major shifts in international dynamics that are unpredictable or beyond national control are not included in this study. Parameter settings are detailed in the Materials and Methods section and Supplementary Document. 2.2 Critical mineral demand and circularity across integrated scenarios The above nine integrated scenarios reveal that Japan can substantially reduce the total input of critical minerals for automotive LIBs by 2050 – up to 82% compared with the baseline (S11) – but this heavily depends on combined policy interventions. Reductions are more responsive to supplier-side than user-side interventions. Figure 2 shows the projected critical mineral demand from 2025 to 2050. Without intervention (S11), cumulative input reaches 11.1 Mt-LiNiCoMn. In the most ambitious scenario (S33), this drops to 2.0 Mt. Supplier-side policies alone (S11–S13) reduce inputs by 53%, while user-side policies (S11–S31) achieve a 39% reduction. Even in LFP-oriented scenarios, NMC batteries remain a major contributor to critical mineral demand. Immediate recycling slightly increases LIB use in stationary storage but has a limited impact due to degraded battery health and LFP dominance in stationary applications. Mid-level supplier-side interventions (e.g. S22, S23) appear sufficient for balancing resource conservation with policy feasibility. Figure 3 highlights a more complex relationship between the material flow and circularity. While virgin material inputs can be reduced significantly, improving circulation rates is more difficult. In S11, virgin inputs rise steadily, reaching 705.2 kt/year by 2050. Under stronger interventions (S12, S13, S21, S31), virgin inputs stabilize by 2035 at ~ 300 kt/year, or peak earlier (2030) in S33, dropping to ~ 35 kt/year by 2050. User-side interventions (S11–S31) place greater stress on recycling systems, whereas supplier-side interventions (S11–S13) more effectively minimize both demand and losses. Recycling capacity alone cannot offset inefficiencies without complementary tracing and chemical shifts. In S33, a near-closed-loop system emerges post-2040, enabled by policy synergies. Although user-side interventions contribute less to demand reduction, they are key for increasing circularity, particularly by boosting inflow and outflow circulation rates through expedited recycling. Supplier-side measures like longer battery life may delay recycling, reducing short-term circularity. However, they help reduce total demand and support recovery when paired with collection and recycling upgrades. Overall, average circulation rates align more closely with inflows than outflows, due to mismatches between the secondary supply and material demand. Strong user-side interventions help narrow this gap significantly. Figure 4 compares scenario performance across multiple indicators. Across scenarios, stronger interventions yield generally better outcomes, but not uniformly. Some indicators exhibit trade-offs or reversals, particularly in scenarios combining long service life with delayed recycling. S11 performs worst on demand indicators, while S12 and S13 underperform on circularity. Supplier-side policies are more effective in reducing demand, while user-side policies better enhance circulation. However, scaling up supplier-side actions often introduces uncertainty or trade-offs, with divergent effects on short- and long-term outcomes (indicators in 2050 reveal relatively worse from 2035 in S12, S21, S22, S31, and S32, see Figure S33). 2.3 Impact assessment on individual policies and combinations To complement the integrated scenario analysis, we conducted a scenario matrix evaluation to isolate the individual effects of each policy option and explore potential synergies between the paired interventions. Figure 5 illustrates the outcomes in terms of two key indicators (i.e. annual virgin input of critical minerals and inflow circulation rate) at two time points: 2035 and 2050. The diagonal points represent the impact of individual policy options, while the off-diagonal points capture the combined effects of two policies, all benchmarked against the baseline (S11). In the short term (2035), only policy ⑥ (expedited recycling) demonstrates a dual benefit – substantially reducing virgin material input while also increasing circularity. Policies ① (i.e. battery chemical shifts to LFP), ② (i.e. extended battery life), and ⑧ (i.e. traffic demand reduction) show moderate reductions in virgin inputs but limited effect on circularity. Notably, while policy ② appears effective in reducing virgin inputs, it consistently suppresses circularity across all pairings, due to delays in material return to the recycling loop. In the long term (i.e. until 2050), more policy options contribute to reduced virgin material input, with policy ① (i.e. shifting toward Li-S/Air chemistry) yielding the largest gains. The effectiveness of policy ⑥ further amplifies in combination with policies ①, ③ (i.e. mandatory collection), or ④ (i.e. recycling technology advancement), resulting in the lowest virgin inputs and highest inflow circularity. In contrast, policy ⑤ (CNF-oriented PHEV expansion) performs better than policy ⑧ in reducing long-term virgin input and boosting circularity. Policy ⑦ (i.e. used-car export regulation) has only a marginal effect on both indicators, suggesting limited leverage unless other policies fail. A simple test on synergy effects also indicates significant synergies between policy ⑥ (i.e. expedited recycling) and other options, while policy ② (i.e. extended battery life) appears to enter a trade-off against the other policies (Figures S37, S38). Taken together, these results reveal that expedited recycling consistently delivers strong returns, both independently and in combination, whereas extended service life may conflict with circularity goals if not paired with enhanced collection and recycling. Policy designs should consider synergies and conflicts. 3 Discussions Our results indicate that even economies with slower EV adoption can still achieve high circularity, though only under intensive policy intervention. In the case of Japan, the primary demand for critical minerals has the possibility to fall by up to 80% while circulation exceeds 80% by 2040, without relying on imported secondary resources. This suggests that ‘latecomer’ economies are not excluded from circularity transitions. However, Japan really has difficulties in regulating or interfering with the market. Initial boom for buying EVs is crucial to form a faster recycled material market from spent LIBs, but consumers’ willingness to purchase EVs still remains very low 36 , even in Japan, which has provided attractive subsidies for EV purchases in 2022 38 . Japan appears to face difficulties in cultivating a domestic EV market large enough to support the secondary mineral supply inputs for EV exports. A shortage of both primary and secondary resources may increase supply chain risks and weaken industrial competitiveness in pioneer economies. In response to this concern, Japan may rush to extend producer responsibilities, including importing companies, restrict the used-car exports, and even mandate collecting all spent LIBs for recycling locally, as in the case of solar panels 39 . However, these options involve great trade-offs with market heat and corporate profit, which leaves the pathway to circularity highly contested. Therefore, regulations on early circularity indeed appear more favourable to pioneer economies with existing advantages in recycling systems 40 . Evidence-based policy design must carefully balance demand reduction and circularity, as our simulation reveals mismatches between these goals, complex interactions among policies, and uneven indicator changes across time horizons. Setting early-stage circularity targets without well-organized strategies risks unintended trade-offs. Increasing circularity does not necessarily reduce primary demand (e.g. S12/S13 vs. S21/S31), and policies differ in their short- versus long-term effectiveness: for example, S12, S22, and S32 perform better on demand reduction by 2035, while S21 and S31 achieve higher circularity by 2035 but not by 2050. Overemphasis on a single indicator, such as immediate recycling of all spent LIBs or maximizing battery lifetime, can distort outcomes, either reducing user value or suppressing circularity. Similarly, batteries’ short guarantee periods may accelerate circularity but increase resource input, while rapid LFP adoption reduces critical mineral use but may hinder the diffusion of advanced chemistries. Our results highlight that policy combinations generate greater and more stable improvements than individual measures, with synergies that can even offset trade-offs. For Japan, which is a market-driven economy, flexible policy-making is essential by adjusting intensity, timing, and combinations of measures to accommodate uncertainties. Expedited recycling consistently proves globally impactful, while excluding LFP from secondary use or requiring LIB pre-removal from exported vehicles appears less decisive unless other policies fail. Investments in recycling infrastructure should be scaled cautiously to avoid overcapacity risks, given uncertain LIB availability. Ultimately, advancing a closed-loop system for critical minerals requires refined management of multiple indicators, balancing feasibility with policy incentives, and dynamically adjusting strategies to guide the industry toward long-term sustainability. Given the diversity of national conditions and the interaction effects among policies, international coordination should emphasize negotiation and rule-making rather than simply competing to raise circulation rate targets. Key priorities include harmonizing extended producer responsibility, clarifying ownership of spent LIBs, establishing traceability systems for second-hand EVs, and regulating cross-border flows of spent LIBs. Without such coordination, setting rigid global targets risks disadvantaging late-adopting economies, forcing them into costly competition for recycled materials already controlled by pioneers, thereby slowing EV penetration. Competition has already begun. For example, China is revising regulations to capture global flows of spent LIBs 41 , while Japanese firms test overseas recycling to secure secondary supply 42 . To move forward, consensus on flexible targets and fair governance mechanisms is essential. International efforts, such as unique traceability codes for LIBs 43 , battery passports with circularity information 44 , and International Organization for Standardization policies (e.g. TC323, TC333) show progress, but stronger negotiation frameworks are needed. We suggest prioritizing international consensus and cooperative rule-making, which would allow diverse national strategies while avoiding excessive costs and ensuring a fair and effective transition toward circularity. Under relatively lenient international rules, an economy can enjoy path dependence in technology development without precluding balanced circular strategies. Japan has established strength in NMC and solid-state batteries 45 and the relative weakness in LFP technologies 46 illustrates the risks of abrupt chemical shifts on national research and development 47 . A forced shift to LFP could undermine domestic capabilities. However, our analysis shows that even NMC-oriented strategies can halve total primary critical mineral demand and achieve 50–80% circulation by 2050 under interventions (see Figure S39). In contrast, in the case of maximizing user value, all secondary-use strategies can also potentially halve the demand while remaining an acceptable circularity (see Figure S40). Combining these measures offers a feasible pathway toward both reduced input and enhanced circularity, suggesting that transitions must be adaptive to industrial legacies rather than prescriptive toward one chemistry. Such path dependence will support a wider public acceptance towards EVs and stimulate the enterprises’ investment enthusiasm. Our simulator enables a nation/region to evaluate and investigate customized policy combinations that align with the established technology roadmap. Our simulation also supports, different minerals respond very differently to circular economy interventions, requiring tailored policy mixes. Under most intensive policy intervention, Co primary demand can be almost eliminated by 2040 (Figure S29), while Ni primary demand accordingly declines but slower due to the substitution of Co in battery chemical shifts (Figure S30), which is consistent with previous studies 21 . Li is far more resistant: that is, only expedited recycling or breakthroughs such as Li-S/Air achieve substantial reductions (Figure S28). Thus, the lithium supply chain will still be dominated by several exportors 48 in the near future. Additional analysis on Cu flow proves even less flexible with demand continuing to rise until 2050 under all scenarios (Figure S31), which verifies the concerns from the International Energy Agency (IEA) report 36 . These contrasting trajectories highlight that circularity is not a uniform challenge. Effective policy design will depend on mineral-specific strategies aligned with both technological potential and market dynamics. 4 Materials and methods 4.1 Modelling, definitions, and research boundary As shown in Fig. 1 (a), we developed a scenario-based dynamic material flow 49,50 simulator to simulate the demand and circularity of lithium, cobalt, nickel, and manganese in Japan’s automotive LIB supply chain from 2025 to 2050. The model integrates projections of passenger car ownership, battery technology adoption, material composition, and end-of-life recycling. Vehicle fleet size and powertrain composition are projected under demographic, economic, and mobility scenarios using an econometric stock model calibrated to Japanese transport data. Battery technology configurations (e.g. NMC, NCA, LFP, Li–S/Air) are assigned according to scenario-specific technological trajectories drawn from literature and policy outlooks. End-of-life flows are modelled for both domestic and exported vehicles using a Weibull distribution calibrated to 2020 fleet data. Closed-loop recycling is tracked through a mass balance framework, while open-loop flows and cross-border returns are conservatively excluded in the baseline. Three indicators (i.e. inflow circulation rate, outflow circulation rate, and weighted average circulation rate) quantify circularity outcomes annually and cumulatively. Nine integrated scenarios explore interactions between battery strategies and circular economy policies, including extended producer responsibility, direct recycling, and domestic production support. Full methodological details are provided in the Supplementary Document. The system boundary excludes buses, trucks, and special vehicles, which are in a small proportion or are expected to favour fuel cell technologies. The simulation focuses on LIBs originally installed in passenger EVs for the Japanese market or for export. Directly exported new LIBs (OEM) are excluded due to their unclear market share and limited data. The extraction phase of virgin raw materials is not modelled. Several key assumptions also apply. First, all spent automotive LIBs for potential secondary use are assumed to be collected and controlled by companies and are 100% collected after retirement, though losses occur during dismantling and used-car trading due to weak regulatory oversight. Second, the secondary-use market is assumed to have unlimited capacity to accept spent LIBs from Japan. Third, all passenger vehicles follow a common survival curve, and battery refurbishment is treated as a service-life extension. Fourth, all first-use stationary energy storage systems are assumed to employ LFP batteries. 4.2 Policy options and the parameter settings The dynamic material flow simulator accounts for annual changes in stock, usage, recycling, and disposal flows of LIBs under varying policy conditions. Key parameters are calibrated based on literature and national statistics. For instance, the predicted market shares of battery chemistries under the ‘Battery Chemistry Shift’ option were derived from Xu, et al. 20 . The potential doubling of LIB service life is based on projected technology roadmaps 51 . The collection rates for spent LIBs in domestic regions are informed by METI surveys 52 , while overseas collection rates consider local regulations 29 and the proportion of passenger cars sent to these regions 53 . Critical mineral recovery rates are set based on the latest assessments 17 . EV penetration trajectories and the share of PHEVs using CNF follow estimates from JAMA 54 . The trade-off between secondary use and expedited recycling is modelled by adjusting delay times before recycling 28 . Export restrictions are reflected through reduced outflows of used vehicles and improved traceability, while traffic demand shifts are modelled via reductions in car stock per capita, aligned with demographic trends. As summarized in Fig. 1 (b) and Table 1 , these options are ordered from ‘a’ to ‘b’ to ‘c’, based on the regulatory intensity of resource conservation and circulation. Table 1 Policy options in the LIB supply chain and parameter settings. Factors Policy options Descriptions ① Battery chemistry a. NCX-oriented NMC batteries dominate the automobile market. Figure S24(a). b. LFP-oriented LFP batteries dominate the automobile market. Figure S24(b). c. Li-S/Air-oriented Li-S/Air batteries dominate the automobile market. Figure S24(c). ② Battery service life a. Current situation unchanged The guarantee periods of LIBs for BEVs, PHEVs, and stationary energy storage are set at 7, 8, and 10 years, respectively 13 . b. Extended scenario The above guarantee periods are extended to 11, 12, and 15 years, respectively (average during 2025–2050) 51 (Table S8). ③ Tracing & mandatory collection a. Current situation unchanged 75% of spent LIBs domestically and 10% overseas are collected in closed-loop systems 52 . b. Strengthened via sales network 95% of spent LIBs domestically and 40% overseas are collected in closed-loop systems. c. Strengthened via international rule-making 95% of spent LIBs domestically and 90% overseas are collected in closed-loop systems (Table S11). ④ Recycling progress a. Low level LFP batteries are not recycled; the recycling rate for Li is 50%, and for Ni, Co, and Mn it reaches 90% 17 . b. Moderate level LFP batteries are recycled; the recycling rate for Li, Ni, Co, and Mn reaches 90%. c. Ambitious level LFP batteries are recycled; the recycling rate for Li, Ni, Co, and Mn reaches 99% (Table S10). ⑤ EV penetration a. BEV-oriented ICEVs exit the domestic new sales market by 2035, while BEVs dominate by 2050. Overseas market share changes follow IEA projections 8 (Figure S19(a)). b. CNF-oriented ICEVs exit the domestic new sales market by 2035, while BEVs and PHEVs each account for about half of the market by 2050. Overseas market share changes follow IEA projections 8 (Figure S19(b)). ⑥ Secondary use a. All to secondary use All spent LIBs are accepted for stationary energy storage and used worldwide. b. LFP–only secondary use Only LFP batteries are accepted for stationary energy storage and used worldwide. c. All to immediate recycling All spent LIBs are immediately recycled. Instead, stationary energy storage demand is met by new LFP batteries. The substitution ratio of spent LIBs for new LIBs is set at 80% (State of health = 80%) (Table S29). ⑦ Used-car export a. Export with LIB LIBs are exported with used cars as usual. b. Export without LIB LIBs are prohibited from being exported with used cars (Figure S27). ⑧ Traffic demand management a. Current situation unchanged No reduction in road infrastructure or promotion of car-sharing domestically. b. Car-sharing & compact city Road infrastructure is reduced due to depopulation, and car-sharing is promoted domestically (Figure S10). 4.3 Vehicle fleet and market projections We first estimate the size and composition of Japan’s passenger car fleet. Total domestic passenger car ownership ( \(\:S\) ) is projected using a modified econometric model adapted from Nakamura et al. 55 , incorporating the number of households ( \(\:N\) ), annual household income ( \(\:\stackrel{-}{I}\) ), average vehicle purchase price ( \(\:\stackrel{-}{P}\) ), and car-sharing trends: $$\:S=\frac{N·\gamma\:·(1-\eta\:·\delta\:)}{1+\alpha\:·\text{e}\text{x}\text{p}(-\beta\:·\frac{\stackrel{-}{I}}{\stackrel{-}{P}})}$$ 1 Here, \(\:\eta\:\) is the car-sharing membership rate, and \(\:\delta\:\) is the reduction in car ownership per membership, based on findings from a report by the ECOMO 56 . The parameter \(\:\gamma\:\) , representing mobility demand, is estimated as a function of paved road length per capita ( \(\:r\) ) and population density in densely inhabited districts ( \(\:{D}_{DID}\) ): $$\:\gamma\:={\epsilon\:}_{1}·{r}^{{\epsilon\:}_{2}}·{{D}_{DID}}^{-{\epsilon\:}_{3}}$$ 2 Coefficients \(\:\alpha\:\) , \(\:\beta\:\) , \(\:{\epsilon\:}_{1}\) , \(\:{\epsilon\:}_{2}\) , and \(\:{\epsilon\:}_{3}\) are calibrated using Japanese transport data (see Table S4). A compact city scenario assumes constant population density in DIDs and proportional decline in local road infrastructure (accounting for 80% of the total) after 2025. Vehicle usage intensity will be reduced by compact city policies, but it should be partially offset by car-sharing services. Passenger vehicle survival rate at age \(\:t\) ( \(\:F\left(t\right)\) ) is modelled using a Weibull distribution calibrated to 2020 fleet data 57 : $$\:F\left(t\right)=1-{e}^{-{\left(\frac{t}{}\right)}^{m}}$$ 3 Parameters \(\:m\) and µ are calibrated to 1.93 and 16.02, respectively. Passenger car exports are assumed to remain constant at the 2017–2023 average: that is, 3.82 million new and 25% of deregistered vehicles annually exported. Market shares for new vehicle sales follow the IEA’s Announced Pledges Scenarios 8 : 48% BEVs and PHEVs in 2030, 67% in 2035, and 98% in 2050. 4.4 Battery technology configurations We model four major LIB types: LFP, NCA, NMC, and Li-S/Air, and tentatively exclude sodium-ion and magnesium batteries, etc 58 . The market share trajectory of each battery type is dependent on the scenario. The baseline assumes continued dominance of NMC and NCA in EVs, with LFP adoption limited by Japan’s cost disadvantage and reliance on imports. Li-S and Li-Air represent high-performance post-Li-ion technologies with potential for domestic leadership. Battery parameters (e.g. energy density, material content per kWh, cycle life, and vehicle range) are derived from peer-reviewed literature and industry reports as mentioned before, with values summarized in Tables S6 and S7. Advanced configurations assume Li-S/Air batteries reach technical maturity after 2035 under certain scenarios. A unified battery design is assumed for each technology per scenario. Annual material demand for new Evs is calculated by multiplying projected EV sales by battery capacity per vehicle and per-kWh material intensities. 4.5 End-of-life flows and circularity indicators Considering service life of battery mismatches with vehicles 59 , we track LIBs from both domestic and exported vehicles according to their usage abroad and potential return or recycling in foreign markets. Exported used vehicles are assumed to serve their full lifespan overseas. As shown in Figure S4, material flows include closed-loop recycling ( \(\:e\) ) (i.e. recovered LIB materials reused within Japan’s automotive battery production), and final disposal ( \(\:c\) ) (i.e. uncollected or unrecoverable LIB materials). Open-loop recycling ( \(\:b\) , \(\:d\) ), which represents flows to/from other industries or countries, is excluded due to insufficient data. Recycling yields and collection efficiencies are parameterized by battery chemistry and recovery technology, drawing from prior studies and updated projections mentioned before (Table S8–S11). Delamination and direct recycling processes are ranged for advanced scenarios. The Indicators for evaluating the Impact on critical mineral circularity IIe the cumulative Input of critical minerals, the annual input of virgin raw critical minerals, and the circulation rate. We adopt three indicators to evaluate circularity outcomes for critical minerals. The inflow circulation rate is defined as the proportion of recycled materials in total resource input. The outflow circulation rate indicates the share of recovered materials in the post-consumer waste flow. The weighted average circulation rate combines these two, capturing both supply- and demand-side effects. These are calculated as follows: Inflow circulation rate \(\:{R}_{in}=\frac{e}{a+b+e}\) (4) Outflow circulation rate \(\:{R}_{out}=\frac{e}{c+d+e}\) (5) Weighted average circulation rate \(\:\stackrel{-}{R}=\frac{{R}_{in}·(a+b+e)+{R}_{out}·(c+d+e)}{(a+b+e)+(c+d+e)}\) (6) where \(\:a\) denotes the inflow of virgin material input. These indicators are computed annually and cumulatively from 2025 to 2050, aligned with definitions by WBCSD 60 . More details can be found in the Supplementary Document. 4.6 Limitations and uncertainties Our scenario-based simulation inevitably involves uncertainties stemming from assumptions about EV adoption, battery technology evolution, and vehicle longevity. Future EV adoption in Japan and worldwide may diverge from current projections due to shifting consumer preferences 61 and evolving domestic and international tendencies 62 . Rapid battery innovation may also lead to more diverse application scenarios 63 and higher efficiency, energy densities and stability than anticipated 64 . The service life of EVs remains uncertain compared to conventional cars, with studies showing much shorter lifespans in China 65 compared to parity in Great Britain 66 . We also assume fixed battery capacities, although trends suggest increasing demand for high-capacity batteries, particularly for heavy-duty transport. To address these uncertainties, we conducted sensitivity analyses on key parameters; detailed results are available in the Supplementary Information (Figure S41). Given these constantly evolving conditions, further parameter adjustments and validation of results are necessary. Declarations Lead contact Further information and requests for resources should be directed to the lead contact, Yi Dou ( [email protected] ), Yasunori Kikuchi ( [email protected] ). Declaration of interests The authors declare no competing interests. Author contributions Conceptualization, Y.D.; methodology, Y.D.; investigation, Y.D.; writing—original draft, Y.D.; writing—review & editing, Y.D., A.H., and Y.K.; funding acquisition, Y.D., A.H., and Y.K.; resources, Y.D. and A.H.; supervision, Y.D., A.H., and Y.K. All authors contributed to writing this paper. 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Nakamura, K., Kato, H. & Hayashi, Y. Forecast of Motorization Progress Considering Railway Improvement Timing In Asian Developing Mega-Cities. Journal of Japan Society of Civil Engineers, Ser. D3 (Infrastructure Planning and Management) 68 , I_823-I_830 (2012). https://doi.org/10.2208/jscejipm.68.I_823 ECOMO. Verification of the eco effects brought about from car-sharing. (Foundation for Promoting Personal Mobility and Ecological Transportation (ECOMO), Tokyo, 2013). AIRIA. Survey on vehicles average age by the end of fiscal year 2018. (Automobile Inspection & Registration Information Association (AIRIA), Tokyo, 2019). Zeng, X. Q. et al. Commercialization of Lithium Battery Technologies for Electric Vehicles. Adv Energy Mater 9 (2019). https://doi.org/ARTN 1900161 10.1002/aenm.201900161 Richa, K., Babbitt, C. W., Gaustad, G. & Wang, X. A future perspective on lithium-ion battery waste flows from electric vehicles. 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Nature Energy 10 , 354-364 (2025). https://doi.org/10.1038/s41560-024-01698-1 Additional Declarations There is NO Competing Interest. Supplementary Files 03Supplementarydocument.docx Supplementary information Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7959887","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":563980303,"identity":"98a6875c-51ba-4b3c-b093-dfb5deb44bec","order_by":0,"name":"Yi Dou","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA60lEQVRIiWNgGAWjYFCCBAaGDwZyPBDOAaigBAEtjDMMjEFaGBuI1sLMw2DMgKoFHzA4nnxM2qbAQIZBIoH9wYczh+UY2A8/YLDcgUfLmWdp0jkGBjxALYyNM24cNmbgSTNgkDyDR8uNHDOglj9ALfkfm3k+HE5sYMhhYJBsI6DFAmoLRAv/GyK0MMC13ABqkSBgi+SZZ8mWPUAtbDwPGGfOOJNuzCbxzOAAPr/wHU8+eOPHHwN7fvYEhg8fjlnL8fMnP3wsiSfEFA5AGWwQqhnMOCzZgFuLPJpcHZhk/IhHyygYBaNgFIw4AAAVK0t0jXDy+wAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-6665-1653","institution":"The University of Tokyo","correspondingAuthor":true,"prefix":"","firstName":"Yi","middleName":"","lastName":"Dou","suffix":""},{"id":563980304,"identity":"8dab4e2d-d822-4a85-8eca-95016ec7ad25","order_by":1,"name":"Aya Heiho","email":"","orcid":"","institution":"Tokyo City University","correspondingAuthor":false,"prefix":"","firstName":"Aya","middleName":"","lastName":"Heiho","suffix":""},{"id":563980305,"identity":"cdfda6ea-3922-437e-a5f7-e2f0a240b5fc","order_by":2,"name":"Yasunori Kikuchi","email":"","orcid":"https://orcid.org/0000-0003-0002-8233","institution":"University of Tokyo","correspondingAuthor":false,"prefix":"","firstName":"Yasunori","middleName":"","lastName":"Kikuchi","suffix":""}],"badges":[],"createdAt":"2025-10-27 13:14:55","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7959887/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7959887/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101833729,"identity":"e994d30d-9f7e-4b83-8f07-f1c79d259005","added_by":"auto","created_at":"2026-02-04 07:05:54","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":370790,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSchematic of the model framework and scenario design.\u003c/strong\u003e The combination of these levels yields nine integrated scenarios, labelled S11 to S33, where ‘S’ denotes ‘Scenario’ and the numbers correspond to the strength of supplier- and user-side policy implementation. BEV, battery electric vehicle; CNF, carbon-neutral fuel; FCV, fuel cell vehicle; HEV, hybrid electric vehicle; ICEV, internal-combustion engine vehicle; Li-Air, lithium-air battery; Li-S, lithium-sulfur battery; LFP, lithium iron phosphate; NCA, lithium nickel cobalt aluminium oxide; NCX, NCA- and NMC-dominant; NMC, lithium nickel manganese cobalt oxide; PHEV, plug-in hybrid electric vehicle.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-7959887/v1/277670bad734deac030baf37.png"},{"id":101881363,"identity":"44a1193d-9a98-4e7f-bd1f-cde98461fa4e","added_by":"auto","created_at":"2026-02-04 15:11:45","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":286650,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDemand for critical minerals across integrated scenarios.\u003c/strong\u003e The red lines indicate total inputs, while the stacked areas denote materials controlled by battery chemistry type. The dotted areas reflect additional LIB demand for stationary energy storage under immediate recycling.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-7959887/v1/c9eeba28e3bdbf2c93b82ef3.png"},{"id":101833734,"identity":"31c55898-7249-4c78-9a2a-17c6638af4a0","added_by":"auto","created_at":"2026-02-04 07:05:55","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":433441,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMaterial flows and circularity of critical minerals across integrated scenarios.\u003c/strong\u003e The initial fluctuations in the outflow circulation rate were mainly due to the small amount of material being recycled, which made the indicator calculation highly sensitive to the statistical data.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-7959887/v1/418f36ce9b03fdd92d8662c6.png"},{"id":101833731,"identity":"4fceb243-5cc1-4783-8ed9-32c525aff612","added_by":"auto","created_at":"2026-02-04 07:05:54","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":259350,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparison of indicators across integrated scenarios.\u003c/strong\u003e A higher score means higher performance on the corresponding indicator. CRM, critical minerals.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-7959887/v1/a0a64f8358dd881e14b550c5.png"},{"id":101833730,"identity":"cd4a3129-b17a-4b24-b608-d9aafb399ee7","added_by":"auto","created_at":"2026-02-04 07:05:54","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":165979,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVirgin critical mineral input and circulation rates in 2035 and 2050 under the scenario matrix.\u003c/strong\u003e Data can be found in Figures S34–36.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-7959887/v1/f90f0eff9104e85c269285bd.png"},{"id":101943106,"identity":"711890b8-29b0-44ad-87a6-a1fd2660edd2","added_by":"auto","created_at":"2026-02-05 09:40:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2132758,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7959887/v1/bc727dd3-94a9-4902-80c3-f3026219dffe.pdf"},{"id":101833733,"identity":"682e0e89-9ff1-4fdc-b0ab-122bbc5f7ff9","added_by":"auto","created_at":"2026-02-04 07:05:55","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":2972741,"visible":true,"origin":"","legend":"Supplementary information","description":"","filename":"03Supplementarydocument.docx","url":"https://assets-eu.researchsquare.com/files/rs-7959887/v1/fc36d58f67db4ab3b6962ed0.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"From Demand to Circularity: Rethinking National Strategy on Automobile Battery Supply Chain for Sustainability","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eThe rapid expansion of electric vehicles (EVs) and batteries is reshaping climate and industrial strategies. EV deployment and battery recycling are increasingly recognized as essential for transport decarbonization\u003csup\u003e1\u003c/sup\u003e, while also raising concerns over economic security and supply chain resilience\u003csup\u003e2\u003c/sup\u003e. In 2022, the transport sector emitted 7.98 Gt-CO₂, accounting for 23% of global emissions\u003csup\u003e3\u003c/sup\u003e. Expanding EV adoption with a decarbonized power system is therefore critical, but it requires large amounts of critical minerals for lithium-ion batteries (LIBs)\u003csup\u003e4\u003c/sup\u003e, including lithium\u003csup\u003e5\u003c/sup\u003e, nickel, cobalt\u003csup\u003e6\u003c/sup\u003e, and manganese\u003csup\u003e7\u003c/sup\u003e. The global EV stock reached 28\u0026nbsp;million in 2022 and is projected to grow to 790\u0026nbsp;million by 2035 to align with net-zero targets for 2050\u003csup\u003e8\u003c/sup\u003e. This growth would raise mineral demand 20\u0026ndash;40 times by 2040 compared with 2020 levels\u003csup\u003e9\u003c/sup\u003e, with prices expected to rise sharply under net-zero scenarios\u003csup\u003e10\u003c/sup\u003e. Given these pressures, together with risks of shortages and humanitarian crises linked to conflict minerals, improving resource efficiency and advancing circularity in the automotive LIB sector is imperative\u003csup\u003e11\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTo address these challenges, numerous policy measures have been proposed and tested, yet no single effective solution has emerged due to limited quantitative assessment of their merits and drawbacks. While advances in battery technology and recycling are widely recognized strategies to improve resource efficiency in the automotive LIB supply chain\u003csup\u003e12\u003c/sup\u003e, they cannot immediately close the gap between the increasing demand and the delayed secondary supply of critical minerals\u003csup\u003e13\u003c/sup\u003e. Reducing the cobalt content of batteries through chemical shifts\u003csup\u003e14\u003c/sup\u003e, such as wider adoption of lithium iron phosphate (LFP)\u003csup\u003e15\u003c/sup\u003e, or raising energy density with lithium-sulphur (Li-S) and lithium-air (Li-Air) batteries\u003csup\u003e16\u003c/sup\u003e can reduce dependence on primary minerals. However, recycling of LFP batteries lacks economic incentives\u003csup\u003e17\u003c/sup\u003e due to the absence of collection premiums and low lithium recovery rates\u003csup\u003e18\u003c/sup\u003e, with even the questionable quality of recovered lithium requisitioned for reuse in LIB manufacturing\u003csup\u003e19\u003c/sup\u003e. Next-generation chemistries require decades to commercialize\u003csup\u003e20\u003c/sup\u003e and reducing cobalt increases nickel demand\u003csup\u003e21\u003c/sup\u003e, while cobalt is still projected to remain in use for performance gains\u003csup\u003e22\u003c/sup\u003e. Recycling maximizes the recovery of critical minerals\u003csup\u003e23\u003c/sup\u003e but is hindered by the low collection rates and secondary use\u003csup\u003e24\u003c/sup\u003e and by challenges in environmental impacts\u003csup\u003e25\u003c/sup\u003e \u0026ndash; recent mainstream pyro- or hydrometallurgy treatments cannot avoid huge energy and resource inputs\u003csup\u003e26\u003c/sup\u003e. Furthermore, expedited recycling could forfeit substantial economic benefits from secondary use in peak shaving and stationary storage\u003csup\u003e27\u003c/sup\u003e. Beyond these strategies, improving collection and recycling rates and extending battery lifespans\u003csup\u003e28\u003c/sup\u003e are also frequently emphasized. In summary, the extent to which such measures can drive meaningful improvements individually or together in the circularity of critical minerals remains insufficiently understood.\u003c/p\u003e \u003cp\u003eTo reshape a sustainable automotive LIB supply chain, leading EV manufacturers and exporters are accelerating efforts to secure recycled materials, strengthen supply chain resilience, and increase material circularity. The EU has enacted stringent battery regulations together with the Carbon Border Adjustment Mechanism, enforcing circularity targets and deadlines for critical minerals in LIBs\u003csup\u003e29\u003c/sup\u003e. This creates strong pressure on manufacturers and exporters worldwide. In the USA, the revised Inflation Reduction Act excludes batteries containing critical minerals extracted, processed, or recycled by foreign entities of concern from the Clean Vehicle Tax Credit. China has rushed investments into recycling capacity that are quetioned to double the global supply of end-of-life batteries by 2030\u003csup\u003e8\u003c/sup\u003e. The large exports of used hybrid vehicles from Japan\u003csup\u003e30\u003c/sup\u003e have sparked debates on restricting used-EV exports for collecting spent LIBs\u003csup\u003e31\u003c/sup\u003e. With more countries designating battery minerals as strategic resources, national battery passports and traceability systems are being introduced. The EU has already launched its own battery passport, and Japan has initiated the Ouranos Ecosystem Project to track EV and LIB supply chains\u003csup\u003e32\u003c/sup\u003e. Looking ahead, the global LIB industry will be subject to growing policy interventions at nation level, even in times of world crisis, direct governmental control remains possible.\u003c/p\u003e \u003cp\u003eTwo major challenges emerge during rapid global shifts. First, policies across countries are fragmented, covering the entire supply chain yet lacking prioritization. Regulations on battery recycling differ widely in enforcement, producer responsibility, waste classification, targets, design standards, public participation, and incentives\u003csup\u003e33\u003c/sup\u003e. Such disparities impede cross-border data sharing and unified regulation, and only a small share of retired LIBs currently reach high-quality reuse or recycling facilities\u003csup\u003e34\u003c/sup\u003e. Given the complexity of supply chains and the uneven resource distribution, even national measures can have global ripple effects, making international coordination on standards essential\u003csup\u003e35\u003c/sup\u003e. Second, market responses to battery electric vehicles (BEVs) diverge. For example, the United States trails the EU and China, Japan is still at an early stage of development, and Southeast Asia is now an emerging market after the EU and China\u003csup\u003e36\u003c/sup\u003e. Since extraction and smelting still dominate life cycle burdens\u003csup\u003e26\u003c/sup\u003e, distribution of industrial development, EV markets, and socio-environmental impacts reveal high disparity. National-level assessment of individual and combined supply chain policies is crucial for advancing regional governance, international coordination, and life cycle management\u003csup\u003e37\u003c/sup\u003e. Japan, which is both the world\u0026rsquo;s largest automobile exporter and a latecomer in EV adoption, is particularly exposed to domestic and foreign policy shifts, making it a representative case for circular strategy design.\u003c/p\u003e \u003cp\u003eThis study develops a scenario-based integrated dynamic material flow simulator to model material circulation in automotive LIBs, grounded in ongoing global debates on resource security policies. The simulator is designed as a transparent and easy-to-use tool: by setting local parameters and choosing policies, users can automatically calculate the outcomes of any combination of policy options. It can thus be adapted by any nation to design optimized circularity strategies, strengthen its negotiating position, and support constructive international dialogue. Building on previous dynamic materials flow analyses, our model incorporates a broad set of supply- and demand-side factors, including battery upgrades, lifespan, traceability, recycling progress, EV penetration, secondary use, used-car exports, and traffic demand management (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). We apply the simulator to Japan, a nation with limited mineral resources but a leading role in global automobile exports. The results show that even Japan, a latecomer in EV industrial development, could reduce total demand for critical minerals by up to 82% and raise circularity above 80% by 2050 through robust combined policy interventions. The complex interactions between supplier- and user-side measures produce diverse impacts on the LIB supply chain, and these uncertainties were explicitly quantified in our simulation. These findings underscore the role of comprehensive resource management in advancing sustainable battery supply chains and shaping fairer international negotiations.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"2 Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Framing of policy options and scenario design\u003c/h2\u003e \u003cp\u003eTo capture the variability in the demand for and circularity of critical minerals stemming from policy interventions across the automotive LIB supply chain, we identified eight key drivers and 20 policy options which span both supplier- and user-side interventions (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003eSupplier-side options include: ① Battery chemical shifts \u0026ndash; accounting for transitions from Co-rich chemistries to Co-free alternatives, such as LFP, and future candidates, such as Li-S or Li-Air; ② Service life of LIBs \u0026ndash; reflecting durability and performance enhancements through policy and technological innovation; ③ Tracing and mandatory collection \u0026ndash; encompassing domestic regulations and Japan\u0026rsquo;s influence via overseas export channels; ④ Advancements in recycling \u0026ndash; addressing the current challenges in LFP recycling and improving recovery rates for critical minerals.\u003c/p\u003e \u003cp\u003eUser-side options include: ⑤ BEV penetration vs. carbon-neutral fuels (CNF) penetration \u0026ndash; reflecting the balance between BEV deployment and the adoption of CNF in plug-in hybrid electric vehicles (PHEVs); ⑥ Secondary use vs. expedited recycling \u0026ndash; capturing trade-offs between economic value and critical mineral circulation speed; ⑦ Regulation on used-car exports \u0026ndash; targeting material losses through untracked cross-border flows; ⑧ Traffic demand management \u0026ndash; leveraging compact city planning and car-sharing schemes to reduce passenger car demand.\u003c/p\u003e \u003cp\u003eThese socio-economic changes and policy interventions drive key variations. In Japan, passenger vehicle ownership is anticipated to decline from 60.7\u0026nbsp;million in 2024 to 53.2\u0026nbsp;million by 2050 due to depopulation, and further to 47.2\u0026nbsp;million under compact city and car-sharing policies (Figure S10). Annual registrations and deregistrations are also expected to both fall by about 20% during 2025\u0026ndash;2050 (Figure S16). By 2050, internal-combustion engine vehicles (ICEVs) will have nearly disappeared, while hybrid electric vehicle (HEV) ownership peaks in 2040 before dropping to 20\u0026nbsp;million by 2050. EVs account for about two-thirds of passenger vehicles (Figure S21). Depending on policy combinations, spent LIB collection in 2050 ranges from 400 to 3,000 kt pack weight with diverse chemistries (Figure S25). Meanwhile, used-EV exports steadily rise, reaching about 400,000 units by 2050 (Figure S27).\u003c/p\u003e \u003cp\u003eTo systematically explore the interactions among these policies, each option was assigned a level of influence (i.e. 1\u0026thinsp;=\u0026thinsp;weak, 2\u0026thinsp;=\u0026thinsp;moderate and 3\u0026thinsp;=\u0026thinsp;strong), forming a 3\u0026sdot;3 matrix of nine scenarios (i.e. S11\u0026ndash;S33, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). These scenarios represent varying degrees of policy ambition and system transformation. S11 reflects the status quo in Japan with minimal supply chain intervention, while S33 represents an ambitious pathway where all policies are enacted at their strongest levels. Intermediate scenarios (e.g. S21, S22, S23, S32) reflect mixed levels of policy intensity. An additive scenario matrix is further constructed to assess both the individual and synergistic effects of each option relative to the baseline (S11), thereby identifying effective strategies for enhancing critical mineral circularity. The selection and structuring of these policy options are based on the premise of leveraging national influence to govern various segments of the battery supply chain and thereby control the material flow of critical metals. Disruptive innovations or major shifts in international dynamics that are unpredictable or beyond national control are not included in this study. Parameter settings are detailed in the Materials and Methods section and Supplementary Document.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Critical mineral demand and circularity across integrated scenarios\u003c/h2\u003e \u003cp\u003eThe above nine integrated scenarios reveal that Japan can substantially reduce the total input of critical minerals for automotive LIBs by 2050 \u0026ndash; up to 82% compared with the baseline (S11) \u0026ndash; but this heavily depends on combined policy interventions. Reductions are more responsive to supplier-side than user-side interventions. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the projected critical mineral demand from 2025 to 2050. Without intervention (S11), cumulative input reaches 11.1 Mt-LiNiCoMn. In the most ambitious scenario (S33), this drops to 2.0 Mt. Supplier-side policies alone (S11\u0026ndash;S13) reduce inputs by 53%, while user-side policies (S11\u0026ndash;S31) achieve a 39% reduction. Even in LFP-oriented scenarios, NMC batteries remain a major contributor to critical mineral demand. Immediate recycling slightly increases LIB use in stationary storage but has a limited impact due to degraded battery health and LFP dominance in stationary applications. Mid-level supplier-side interventions (e.g. S22, S23) appear sufficient for balancing resource conservation with policy feasibility.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e highlights a more complex relationship between the material flow and circularity. While virgin material inputs can be reduced significantly, improving circulation rates is more difficult. In S11, virgin inputs rise steadily, reaching 705.2 kt/year by 2050. Under stronger interventions (S12, S13, S21, S31), virgin inputs stabilize by 2035 at ~\u0026thinsp;300 kt/year, or peak earlier (2030) in S33, dropping to ~\u0026thinsp;35 kt/year by 2050. User-side interventions (S11\u0026ndash;S31) place greater stress on recycling systems, whereas supplier-side interventions (S11\u0026ndash;S13) more effectively minimize both demand and losses. Recycling capacity alone cannot offset inefficiencies without complementary tracing and chemical shifts. In S33, a near-closed-loop system emerges post-2040, enabled by policy synergies. Although user-side interventions contribute less to demand reduction, they are key for increasing circularity, particularly by boosting inflow and outflow circulation rates through expedited recycling. Supplier-side measures like longer battery life may delay recycling, reducing short-term circularity. However, they help reduce total demand and support recovery when paired with collection and recycling upgrades. Overall, average circulation rates align more closely with inflows than outflows, due to mismatches between the secondary supply and material demand. Strong user-side interventions help narrow this gap significantly.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e compares scenario performance across multiple indicators. Across scenarios, stronger interventions yield generally better outcomes, but not uniformly. Some indicators exhibit trade-offs or reversals, particularly in scenarios combining long service life with delayed recycling. S11 performs worst on demand indicators, while S12 and S13 underperform on circularity. Supplier-side policies are more effective in reducing demand, while user-side policies better enhance circulation. However, scaling up supplier-side actions often introduces uncertainty or trade-offs, with divergent effects on short- and long-term outcomes (indicators in 2050 reveal relatively worse from 2035 in S12, S21, S22, S31, and S32, see Figure S33).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Impact assessment on individual policies and combinations\u003c/h2\u003e \u003cp\u003eTo complement the integrated scenario analysis, we conducted a scenario matrix evaluation to isolate the individual effects of each policy option and explore potential synergies between the paired interventions. Figure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e illustrates the outcomes in terms of two key indicators (i.e. annual virgin input of critical minerals and inflow circulation rate) at two time points: 2035 and 2050. The diagonal points represent the impact of individual policy options, while the off-diagonal points capture the combined effects of two policies, all benchmarked against the baseline (S11).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn the short term (2035), only policy ⑥ (expedited recycling) demonstrates a dual benefit \u0026ndash; substantially reducing virgin material input while also increasing circularity. Policies ① (i.e. battery chemical shifts to LFP), ② (i.e. extended battery life), and ⑧ (i.e. traffic demand reduction) show moderate reductions in virgin inputs but limited effect on circularity. Notably, while policy ② appears effective in reducing virgin inputs, it consistently suppresses circularity across all pairings, due to delays in material return to the recycling loop.\u003c/p\u003e \u003cp\u003eIn the long term (i.e. until 2050), more policy options contribute to reduced virgin material input, with policy ① (i.e. shifting toward Li-S/Air chemistry) yielding the largest gains. The effectiveness of policy ⑥ further amplifies in combination with policies ①, ③ (i.e. mandatory collection), or ④ (i.e. recycling technology advancement), resulting in the lowest virgin inputs and highest inflow circularity. In contrast, policy ⑤ (CNF-oriented PHEV expansion) performs better than policy ⑧ in reducing long-term virgin input and boosting circularity. Policy ⑦ (i.e. used-car export regulation) has only a marginal effect on both indicators, suggesting limited leverage unless other policies fail. A simple test on synergy effects also indicates significant synergies between policy ⑥ (i.e. expedited recycling) and other options, while policy ② (i.e. extended battery life) appears to enter a trade-off against the other policies (Figures S37, S38). Taken together, these results reveal that expedited recycling consistently delivers strong returns, both independently and in combination, whereas extended service life may conflict with circularity goals if not paired with enhanced collection and recycling. Policy designs should consider synergies and conflicts.\u003c/p\u003e \u003c/div\u003e"},{"header":"3 Discussions","content":"\u003cp\u003eOur results indicate that even economies with slower EV adoption can still achieve high circularity, though only under intensive policy intervention. In the case of Japan, the primary demand for critical minerals has the possibility to fall by up to 80% while circulation exceeds 80% by 2040, without relying on imported secondary resources. This suggests that \u0026lsquo;latecomer\u0026rsquo; economies are not excluded from circularity transitions. However, Japan really has difficulties in regulating or interfering with the market. Initial boom for buying EVs is crucial to form a faster recycled material market from spent LIBs, but consumers\u0026rsquo; willingness to purchase EVs still remains very low\u003csup\u003e36\u003c/sup\u003e, even in Japan, which has provided attractive subsidies for EV purchases in 2022\u003csup\u003e38\u003c/sup\u003e. Japan appears to face difficulties in cultivating a domestic EV market large enough to support the secondary mineral supply inputs for EV exports. A shortage of both primary and secondary resources may increase supply chain risks and weaken industrial competitiveness in pioneer economies. In response to this concern, Japan may rush to extend producer responsibilities, including importing companies, restrict the used-car exports, and even mandate collecting all spent LIBs for recycling locally, as in the case of solar panels\u003csup\u003e39\u003c/sup\u003e. However, these options involve great trade-offs with market heat and corporate profit, which leaves the pathway to circularity highly contested. Therefore, regulations on early circularity indeed appear more favourable to pioneer economies with existing advantages in recycling systems\u003csup\u003e40\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eEvidence-based policy design must carefully balance demand reduction and circularity, as our simulation reveals mismatches between these goals, complex interactions among policies, and uneven indicator changes across time horizons. Setting early-stage circularity targets without well-organized strategies risks unintended trade-offs. Increasing circularity does not necessarily reduce primary demand (e.g. S12/S13 vs. S21/S31), and policies differ in their short- versus long-term effectiveness: for example, S12, S22, and S32 perform better on demand reduction by 2035, while S21 and S31 achieve higher circularity by 2035 but not by 2050. Overemphasis on a single indicator, such as immediate recycling of all spent LIBs or maximizing battery lifetime, can distort outcomes, either reducing user value or suppressing circularity. Similarly, batteries\u0026rsquo; short guarantee periods may accelerate circularity but increase resource input, while rapid LFP adoption reduces critical mineral use but may hinder the diffusion of advanced chemistries. Our results highlight that policy combinations generate greater and more stable improvements than individual measures, with synergies that can even offset trade-offs. For Japan, which is a market-driven economy, flexible policy-making is essential by adjusting intensity, timing, and combinations of measures to accommodate uncertainties. Expedited recycling consistently proves globally impactful, while excluding LFP from secondary use or requiring LIB pre-removal from exported vehicles appears less decisive unless other policies fail. Investments in recycling infrastructure should be scaled cautiously to avoid overcapacity risks, given uncertain LIB availability. Ultimately, advancing a closed-loop system for critical minerals requires refined management of multiple indicators, balancing feasibility with policy incentives, and dynamically adjusting strategies to guide the industry toward long-term sustainability.\u003c/p\u003e \u003cp\u003eGiven the diversity of national conditions and the interaction effects among policies, international coordination should emphasize negotiation and rule-making rather than simply competing to raise circulation rate targets. Key priorities include harmonizing extended producer responsibility, clarifying ownership of spent LIBs, establishing traceability systems for second-hand EVs, and regulating cross-border flows of spent LIBs. Without such coordination, setting rigid global targets risks disadvantaging late-adopting economies, forcing them into costly competition for recycled materials already controlled by pioneers, thereby slowing EV penetration. Competition has already begun. For example, China is revising regulations to capture global flows of spent LIBs\u003csup\u003e41\u003c/sup\u003e, while Japanese firms test overseas recycling to secure secondary supply\u003csup\u003e42\u003c/sup\u003e. To move forward, consensus on flexible targets and fair governance mechanisms is essential. International efforts, such as unique traceability codes for LIBs\u003csup\u003e43\u003c/sup\u003e, battery passports with circularity information\u003csup\u003e44\u003c/sup\u003e, and International Organization for Standardization policies (e.g. TC323, TC333) show progress, but stronger negotiation frameworks are needed. We suggest prioritizing international consensus and cooperative rule-making, which would allow diverse national strategies while avoiding excessive costs and ensuring a fair and effective transition toward circularity.\u003c/p\u003e \u003cp\u003eUnder relatively lenient international rules, an economy can enjoy path dependence in technology development without precluding balanced circular strategies. Japan has established strength in NMC and solid-state batteries\u003csup\u003e45\u003c/sup\u003e and the relative weakness in LFP technologies\u003csup\u003e46\u003c/sup\u003e illustrates the risks of abrupt chemical shifts on national research and development\u003csup\u003e47\u003c/sup\u003e. A forced shift to LFP could undermine domestic capabilities. However, our analysis shows that even NMC-oriented strategies can halve total primary critical mineral demand and achieve 50\u0026ndash;80% circulation by 2050 under interventions (see Figure S39). In contrast, in the case of maximizing user value, all secondary-use strategies can also potentially halve the demand while remaining an acceptable circularity (see Figure S40). Combining these measures offers a feasible pathway toward both reduced input and enhanced circularity, suggesting that transitions must be adaptive to industrial legacies rather than prescriptive toward one chemistry. Such path dependence will support a wider public acceptance towards EVs and stimulate the enterprises\u0026rsquo; investment enthusiasm. Our simulator enables a nation/region to evaluate and investigate customized policy combinations that align with the established technology roadmap.\u003c/p\u003e \u003cp\u003eOur simulation also supports, different minerals respond very differently to circular economy interventions, requiring tailored policy mixes. Under most intensive policy intervention, Co primary demand can be almost eliminated by 2040 (Figure S29), while Ni primary demand accordingly declines but slower due to the substitution of Co in battery chemical shifts (Figure S30), which is consistent with previous studies\u003csup\u003e21\u003c/sup\u003e. Li is far more resistant: that is, only expedited recycling or breakthroughs such as Li-S/Air achieve substantial reductions (Figure S28). Thus, the lithium supply chain will still be dominated by several exportors\u003csup\u003e48\u003c/sup\u003e in the near future. Additional analysis on Cu flow proves even less flexible with demand continuing to rise until 2050 under all scenarios (Figure S31), which verifies the concerns from the International Energy Agency (IEA) report\u003csup\u003e36\u003c/sup\u003e. These contrasting trajectories highlight that circularity is not a uniform challenge. Effective policy design will depend on mineral-specific strategies aligned with both technological potential and market dynamics.\u003c/p\u003e"},{"header":"4 Materials and methods","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Modelling, definitions, and research boundary\u003c/h2\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e(a), we developed a scenario-based dynamic material flow\u003csup\u003e49,50\u003c/sup\u003e simulator to simulate the demand and circularity of lithium, cobalt, nickel, and manganese in Japan\u0026rsquo;s automotive LIB supply chain from 2025 to 2050. The model integrates projections of passenger car ownership, battery technology adoption, material composition, and end-of-life recycling. Vehicle fleet size and powertrain composition are projected under demographic, economic, and mobility scenarios using an econometric stock model calibrated to Japanese transport data. Battery technology configurations (e.g. NMC, NCA, LFP, Li\u0026ndash;S/Air) are assigned according to scenario-specific technological trajectories drawn from literature and policy outlooks. End-of-life flows are modelled for both domestic and exported vehicles using a Weibull distribution calibrated to 2020 fleet data. Closed-loop recycling is tracked through a mass balance framework, while open-loop flows and cross-border returns are conservatively excluded in the baseline. Three indicators (i.e. inflow circulation rate, outflow circulation rate, and weighted average circulation rate) quantify circularity outcomes annually and cumulatively. Nine integrated scenarios explore interactions between battery strategies and circular economy policies, including extended producer responsibility, direct recycling, and domestic production support. Full methodological details are provided in the Supplementary Document.\u003c/p\u003e \u003cp\u003eThe system boundary excludes buses, trucks, and special vehicles, which are in a small proportion or are expected to favour fuel cell technologies. The simulation focuses on LIBs originally installed in passenger EVs for the Japanese market or for export. Directly exported new LIBs (OEM) are excluded due to their unclear market share and limited data. The extraction phase of virgin raw materials is not modelled. Several key assumptions also apply. First, all spent automotive LIBs for potential secondary use are assumed to be collected and controlled by companies and are 100% collected after retirement, though losses occur during dismantling and used-car trading due to weak regulatory oversight. Second, the secondary-use market is assumed to have unlimited capacity to accept spent LIBs from Japan. Third, all passenger vehicles follow a common survival curve, and battery refurbishment is treated as a service-life extension. Fourth, all first-use stationary energy storage systems are assumed to employ LFP batteries.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Policy options and the parameter settings\u003c/h2\u003e \u003cp\u003eThe dynamic material flow simulator accounts for annual changes in stock, usage, recycling, and disposal flows of LIBs under varying policy conditions. Key parameters are calibrated based on literature and national statistics. For instance, the predicted market shares of battery chemistries under the \u0026lsquo;Battery Chemistry Shift\u0026rsquo; option were derived from Xu, et al. \u003csup\u003e20\u003c/sup\u003e. The potential doubling of LIB service life is based on projected technology roadmaps\u003csup\u003e51\u003c/sup\u003e. The collection rates for spent LIBs in domestic regions are informed by METI surveys\u003csup\u003e52\u003c/sup\u003e, while overseas collection rates consider local regulations\u003csup\u003e29\u003c/sup\u003e and the proportion of passenger cars sent to these regions\u003csup\u003e53\u003c/sup\u003e. Critical mineral recovery rates are set based on the latest assessments\u003csup\u003e17\u003c/sup\u003e. EV penetration trajectories and the share of PHEVs using CNF follow estimates from \u003cem\u003eJAMA\u003c/em\u003e\u003csup\u003e54\u003c/sup\u003e. The trade-off between secondary use and expedited recycling is modelled by adjusting delay times before recycling\u003csup\u003e28\u003c/sup\u003e. Export restrictions are reflected through reduced outflows of used vehicles and improved traceability, while traffic demand shifts are modelled via reductions in car stock per capita, aligned with demographic trends. As summarized in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e(b) and Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, these options are ordered from \u0026lsquo;a\u0026rsquo; to \u0026lsquo;b\u0026rsquo; to \u0026lsquo;c\u0026rsquo;, based on the regulatory intensity of resource conservation and circulation.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePolicy options in the LIB supply chain and parameter settings.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFactors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePolicy options\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDescriptions\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e① Battery chemistry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ea. NCX-oriented\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNMC batteries dominate the automobile market. Figure S24(a).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eb. LFP-oriented\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLFP batteries dominate the automobile market. Figure S24(b).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ec. Li-S/Air-oriented\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLi-S/Air batteries dominate the automobile market. Figure S24(c).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e② Battery service life\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ea. Current situation unchanged\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe guarantee periods of LIBs for BEVs, PHEVs, and stationary energy storage are set at 7, 8, and 10 years, respectively\u003csup\u003e13\u003c/sup\u003e.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eb. Extended scenario\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe above guarantee periods are extended to 11, 12, and 15 years, respectively (average during 2025\u0026ndash;2050)\u003csup\u003e51\u003c/sup\u003e (Table S8).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e③ Tracing \u0026amp; mandatory collection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ea. Current situation unchanged\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75% of spent LIBs domestically and 10% overseas are collected in closed-loop systems\u003csup\u003e52\u003c/sup\u003e.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eb. Strengthened via sales network\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% of spent LIBs domestically and 40% overseas are collected in closed-loop systems.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ec. Strengthened via international rule-making\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% of spent LIBs domestically and 90% overseas are collected in closed-loop systems (Table S11).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e④ Recycling progress\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ea. Low level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLFP batteries are not recycled; the recycling rate for Li is 50%, and for Ni, Co, and Mn it reaches 90%\u003csup\u003e17\u003c/sup\u003e.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eb. Moderate level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLFP batteries are recycled; the recycling rate for Li, Ni, Co, and Mn reaches 90%.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ec. Ambitious level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLFP batteries are recycled; the recycling rate for Li, Ni, Co, and Mn reaches 99% (Table S10).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e⑤ EV penetration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ea. BEV-oriented\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eICEVs exit the domestic new sales market by 2035, while BEVs dominate by 2050. Overseas market share changes follow IEA projections\u003csup\u003e8\u003c/sup\u003e (Figure S19(a)).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eb. CNF-oriented\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eICEVs exit the domestic new sales market by 2035, while BEVs and PHEVs each account for about half of the market by 2050. Overseas market share changes follow IEA projections\u003csup\u003e8\u003c/sup\u003e (Figure S19(b)).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e⑥ Secondary use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ea. All to secondary use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAll spent LIBs are accepted for stationary energy storage and used worldwide.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eb. LFP\u0026ndash;only secondary use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOnly LFP batteries are accepted for stationary energy storage and used worldwide.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ec. All to immediate recycling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAll spent LIBs are immediately recycled. Instead, stationary energy storage demand is met by new LFP batteries. The substitution ratio of spent LIBs for new LIBs is set at 80% (State of health\u0026thinsp;=\u0026thinsp;80%) (Table S29).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e⑦ Used-car export\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ea. Export with LIB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLIBs are exported with used cars as usual.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eb. Export without LIB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLIBs are prohibited from being exported with used cars (Figure S27).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e⑧ Traffic demand management\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ea. Current situation unchanged\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo reduction in road infrastructure or promotion of car-sharing domestically.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eb. Car-sharing \u0026amp; compact city\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRoad infrastructure is reduced due to depopulation, and car-sharing is promoted domestically (Figure S10).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Vehicle fleet and market projections\u003c/h2\u003e \u003cp\u003eWe first estimate the size and composition of Japan\u0026rsquo;s passenger car fleet. Total domestic passenger car ownership (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:S\\)\u003c/span\u003e\u003c/span\u003e) is projected using a modified econometric model adapted from Nakamura et al.\u003csup\u003e55\u003c/sup\u003e, incorporating the number of households (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:N\\)\u003c/span\u003e\u003c/span\u003e), annual household income (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\stackrel{-}{I}\\)\u003c/span\u003e\u003c/span\u003e), average vehicle purchase price (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\stackrel{-}{P}\\)\u003c/span\u003e\u003c/span\u003e), and car-sharing trends:\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:S=\\frac{N\u0026middot;\\gamma\\:\u0026middot;(1-\\eta\\:\u0026middot;\\delta\\:)}{1+\\alpha\\:\u0026middot;\\text{e}\\text{x}\\text{p}(-\\beta\\:\u0026middot;\\frac{\\stackrel{-}{I}}{\\stackrel{-}{P}})}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eHere, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\eta\\:\\)\u003c/span\u003e\u003c/span\u003e is the car-sharing membership rate, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\delta\\:\\)\u003c/span\u003e\u003c/span\u003e is the reduction in car ownership per membership, based on findings from a report by the ECOMO\u003csup\u003e56\u003c/sup\u003e. The parameter \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\gamma\\:\\)\u003c/span\u003e\u003c/span\u003e, representing mobility demand, is estimated as a function of paved road length per capita (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:r\\)\u003c/span\u003e\u003c/span\u003e) and population density in densely inhabited districts (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{D}_{DID}\\)\u003c/span\u003e\u003c/span\u003e):\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\:\\gamma\\:={\\epsilon\\:}_{1}\u0026middot;{r}^{{\\epsilon\\:}_{2}}\u0026middot;{{D}_{DID}}^{-{\\epsilon\\:}_{3}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eCoefficients \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\alpha\\:\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\beta\\:\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\epsilon\\:}_{1}\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\epsilon\\:}_{2}\\)\u003c/span\u003e\u003c/span\u003e, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\epsilon\\:}_{3}\\)\u003c/span\u003e\u003c/span\u003e are calibrated using Japanese transport data (see Table S4). A compact city scenario assumes constant population density in DIDs and proportional decline in local road infrastructure (accounting for 80% of the total) after 2025. Vehicle usage intensity will be reduced by compact city policies, but it should be partially offset by car-sharing services.\u003c/p\u003e \u003cp\u003ePassenger vehicle survival rate at age \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:t\\)\u003c/span\u003e\u003c/span\u003e (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:F\\left(t\\right)\\)\u003c/span\u003e\u003c/span\u003e) is modelled using a Weibull distribution calibrated to 2020 fleet data\u003csup\u003e57\u003c/sup\u003e:\u003cdiv id=\"Equ3\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ3\" name=\"EquationSource\"\u003e\n$$\\:F\\left(t\\right)=1-{e}^{-{\\left(\\frac{t}{}\\right)}^{m}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e3\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eParameters \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:m\\)\u003c/span\u003e\u003c/span\u003e and \u003cem\u003e\u0026micro;\u003c/em\u003e are calibrated to 1.93 and 16.02, respectively. Passenger car exports are assumed to remain constant at the 2017\u0026ndash;2023 average: that is, 3.82\u0026nbsp;million new and 25% of deregistered vehicles annually exported. Market shares for new vehicle sales follow the IEA\u0026rsquo;s Announced Pledges Scenarios\u003csup\u003e8\u003c/sup\u003e: 48% BEVs and PHEVs in 2030, 67% in 2035, and 98% in 2050.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Battery technology configurations\u003c/h2\u003e \u003cp\u003eWe model four major LIB types: LFP, NCA, NMC, and Li-S/Air, and tentatively exclude sodium-ion and magnesium batteries, etc\u003csup\u003e58\u003c/sup\u003e. The market share trajectory of each battery type is dependent on the scenario. The baseline assumes continued dominance of NMC and NCA in EVs, with LFP adoption limited by Japan\u0026rsquo;s cost disadvantage and reliance on imports. Li-S and Li-Air represent high-performance post-Li-ion technologies with potential for domestic leadership. Battery parameters (e.g. energy density, material content per kWh, cycle life, and vehicle range) are derived from peer-reviewed literature and industry reports as mentioned before, with values summarized in Tables S6 and S7. Advanced configurations assume Li-S/Air batteries reach technical maturity after 2035 under certain scenarios. A unified battery design is assumed for each technology per scenario. Annual material demand for new Evs is calculated by multiplying projected EV sales by battery capacity per vehicle and per-kWh material intensities.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e4.5 End-of-life flows and circularity indicators\u003c/h2\u003e \u003cp\u003eConsidering service life of battery mismatches with vehicles\u003csup\u003e59\u003c/sup\u003e, we track LIBs from both domestic and exported vehicles according to their usage abroad and potential return or recycling in foreign markets. Exported used vehicles are assumed to serve their full lifespan overseas. As shown in Figure S4, material flows include closed-loop recycling (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:e\\)\u003c/span\u003e\u003c/span\u003e) (i.e. recovered LIB materials reused within Japan\u0026rsquo;s automotive battery production), and final disposal (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:c\\)\u003c/span\u003e\u003c/span\u003e) (i.e. uncollected or unrecoverable LIB materials). Open-loop recycling (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:b\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:d\\)\u003c/span\u003e\u003c/span\u003e), which represents flows to/from other industries or countries, is excluded due to insufficient data. Recycling yields and collection efficiencies are parameterized by battery chemistry and recovery technology, drawing from prior studies and updated projections mentioned before (Table S8\u0026ndash;S11). Delamination and direct recycling processes are ranged for advanced scenarios.\u003c/p\u003e \u003cp\u003eThe Indicators for evaluating the Impact on critical mineral circularity IIe the cumulative Input of critical minerals, the annual input of virgin raw critical minerals, and the circulation rate. We adopt three indicators to evaluate circularity outcomes for critical minerals. The inflow circulation rate is defined as the proportion of recycled materials in total resource input. The outflow circulation rate indicates the share of recovered materials in the post-consumer waste flow. The weighted average circulation rate combines these two, capturing both supply- and demand-side effects. These are calculated as follows:\u003c/p\u003e \u003cp\u003eInflow circulation rate \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{R}_{in}=\\frac{e}{a+b+e}\\)\u003c/span\u003e\u003c/span\u003e (4)\u003c/p\u003e \u003cp\u003eOutflow circulation rate \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{R}_{out}=\\frac{e}{c+d+e}\\)\u003c/span\u003e\u003c/span\u003e (5)\u003c/p\u003e \u003cp\u003eWeighted average circulation rate \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\stackrel{-}{R}=\\frac{{R}_{in}\u0026middot;(a+b+e)+{R}_{out}\u0026middot;(c+d+e)}{(a+b+e)+(c+d+e)}\\)\u003c/span\u003e\u003c/span\u003e (6)\u003c/p\u003e \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:a\\)\u003c/span\u003e\u003c/span\u003e denotes the inflow of virgin material input. These indicators are computed annually and cumulatively from 2025 to 2050, aligned with definitions by WBCSD\u003csup\u003e60\u003c/sup\u003e. More details can be found in the Supplementary Document.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e4.6 Limitations and uncertainties\u003c/h2\u003e \u003cp\u003eOur scenario-based simulation inevitably involves uncertainties stemming from assumptions about EV adoption, battery technology evolution, and vehicle longevity. Future EV adoption in Japan and worldwide may diverge from current projections due to shifting consumer preferences\u003csup\u003e61\u003c/sup\u003e and evolving domestic and international tendencies\u003csup\u003e62\u003c/sup\u003e. Rapid battery innovation may also lead to more diverse application scenarios\u003csup\u003e63\u003c/sup\u003e and higher efficiency, energy densities and stability than anticipated\u003csup\u003e64\u003c/sup\u003e. The service life of EVs remains uncertain compared to conventional cars, with studies showing much shorter lifespans in China\u003csup\u003e65\u003c/sup\u003e compared to parity in Great Britain\u003csup\u003e66\u003c/sup\u003e. We also assume fixed battery capacities, although trends suggest increasing demand for high-capacity batteries, particularly for heavy-duty transport. To address these uncertainties, we conducted sensitivity analyses on key parameters; detailed results are available in the Supplementary Information (Figure S41). Given these constantly evolving conditions, further parameter adjustments and validation of results are necessary.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cb\u003eLead contact\u003c/b\u003e \u003c/p\u003e \u003cp\u003eFurther information and requests for resources should be directed to the lead contact, Yi Dou ([email protected]), Yasunori Kikuchi ([email protected]).\u003c/p\u003e \u003cp\u003e \u003ch2\u003eDeclaration of interests\u003c/h2\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor contributions\u003c/h2\u003e \u003cp\u003eConceptualization, Y.D.; methodology, Y.D.; investigation, Y.D.; writing\u0026mdash;original draft, Y.D.; writing\u0026mdash;review \u0026amp; editing, Y.D., A.H., and Y.K.; funding acquisition, Y.D., A.H., and Y.K.; resources, Y.D. and A.H.; supervision, Y.D., A.H., and Y.K. All authors contributed to writing this paper.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eThis work was supported by the MEXT/JSPS KAKENHI Grant No. JP21H03660, JP21K14276 and JP20K20016, JST COI-NEXT Program Grant No. JPMJPF2003, as well as NISSAN Motor Co., Ltd., Ltd. The activities of the Presidential Endowed Chair for \u0026ldquo;Platinum Society\u0026rdquo; at the University of Tokyo are supported by Mitsui Fudosan Corporation, Sekisui House, Ltd., East Japan Railway Company, and Toyota Tsusho Corporation.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eCrabtree, G. The coming electric vehicle transformation. \u003cem\u003eScience\u003c/em\u003e\u003cstrong\u003e366\u003c/strong\u003e, 422-424 (2019). https://doi.org/10.1126/science.aax0704\u003c/li\u003e\n\u003cli\u003eOlivetti, E. A., Ceder, G., Gaustad, G. G. \u0026amp; Fu, X. K. 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The closing longevity gap between battery electric vehicles and internal combustion vehicles in Great Britain. \u003cem\u003eNature Energy\u003c/em\u003e\u003cstrong\u003e10\u003c/strong\u003e, 354-364 (2025). https://doi.org/10.1038/s41560-024-01698-1\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"critical mineral, lithium-ion battery, material flow analysis, electric mobility, supply chain, circular economy, decarbonization","lastPublishedDoi":"10.21203/rs.3.rs-7959887/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7959887/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe rapid electrification of transport is driving soaring demand for lithium-ion batteries (LIBs), straining critical mineral supply chains. While policy efforts increasingly emphasize circularity, the diverse and uncertain impacts of supply chain interventions remain poorly understood. We develop a globally applicable scenario-based dynamic material flow simulator incorporating eight drivers with 20 policy options to assess their individual and combined effects on resource conservation and circularity in automotive LIBs. Using the world\u0026rsquo;s largest car exporter, Japan, as a case, we show that even late EV adopters can rapidly close critical mineral loops through intensive policy measures, though results depend strongly on policy combinations. Supplier-side policies can at best reduce mineral demand, while user-side actions more strongly boost circularity. Accelerated recycling of end-of-life LIBs is most influential, followed by advanced battery design. Cross-border traceability, mandatory collection, recycling infrastructure, carbon-neutral fuels, and compact urban design moderately reduce demand but contribute less to circularity. Extending battery life presents trade-offs while restricting the export of used vehicles has a limited effect. We reveal strong synergies among coordinated policies and trade-offs between short-term resource efficiency and long-term circularity. Our results stress the need for integrated, stage-specific strategies that align resource security with circular economy goals. Openly accessible online, the simulator enables nations to craft tailored policies and support international negotiation.\u003c/p\u003e","manuscriptTitle":"From Demand to Circularity: Rethinking National Strategy on Automobile Battery Supply Chain for Sustainability","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-04 07:05:50","doi":"10.21203/rs.3.rs-7959887/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9dbb9e25-1c36-4ed8-9246-0d96850e03a9","owner":[],"postedDate":"February 4th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":60052297,"name":"Earth and environmental sciences/Environmental sciences/Environmental impact"},{"id":60052298,"name":"Scientific community and society/Business and industry/Industry"},{"id":60052299,"name":"Scientific community and society/Energy and society/Energy security"},{"id":60052300,"name":"Earth and environmental sciences/Environmental social sciences/Sustainability"},{"id":60052301,"name":"Earth and environmental sciences/Environmental social sciences/Climate-change mitigation"}],"tags":[],"updatedAt":"2026-02-04T07:05:50+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-04 07:05:50","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7959887","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7959887","identity":"rs-7959887","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}