Authors: Preeti Mishra, Sayali Apte, Vaishnavi Dhok
Categories: Environmental Science, Risk Matrix, End-of-life (EOL) battery disposal, Soil conditions, Cause-consequence analysis, Scenario-based impact assessment, Network diagram
Source: MethodsX
Authors: Preeti Mishra, Sayali Apte, Vaishnavi Dhok
The growing use of electric vehicles (EVs) has led to a sharp increase in battery waste, particularly from end-of-life (EOL) lithium-ion batteries (LiBs). A significant portion of this waste is not properly recycled but instead ends up being incinerated, landfilled, or processed through informal channels. Such practices contribute to environmental degradation by releasing potentially toxic elements into the air, soil, and water. This study presents a method for quantifying ecological risks from the leaching of these elements. The risk assessment considers different scenarios involving weather conditions, soil types, and groundwater levels, and presents outcomes through a risk matrix. A detailed cause-consequence analysis and quantitative risk evaluation are conducted. Laboratory testing on soil samples contaminated with LiB waste, compared against control samples, revealed marked degradation in the soil's index and engineering properties. The findings indicate that improper LiB disposal not only degrades soil quality but also poses serious threats to human health and surrounding ecosystems. Additionally, a scenario-based focused group discussion corroborated these risks. The research underscores the urgent need for effective LiB waste management practices and regulatory oversight to mitigate long-term environmental and health impacts.•Quantified environmental risks of EOL lithium-ion battery waste through scenario-based analysis.•Laboratory testing confirmed soil degradation due to improper LiB disposal.•Highlights the need for regulatory action and improved waste management strategies.
Specifications tableSubject areaMore specific subject areaRisk Assessment, Environmental sustainability, Soil contaminationName of your methodScenario-Based Risk Assessment: Network Diagram and Cause-Consequence AnalysisName and reference of the original methodNAResource availabilityNA
The increasing use of Lithium-ion Batteries (LiBs) in Electric Vehicles (EVs) has raised concerns about their environmental impact, especially during the End-of-Life (EOL) disposal phase. As LiBs are essential to the shift towards electric transportation, safe disposal and recycling are critical to preventing long-term environmental harm. According to ISO 2015 [1], industries must minimize environmental impacts, including those from the disposal of EOL LiBs. Proper disposal strategies are vital to avoid significant environmental risks such as contamination of soil, water, and air. Several studies have explored the environmental risks linked to LiB disposal, particularly regarding hazardous substances like lithium, cobalt, and nickel, which, when improperly disposed of, can leach into the environment and cause severe ecological damage [2]. Additionally, improper disposal in landfills or inadequate recycling facilities can lead to fire or explosion hazards, directly threatening human health and the environment [3]. These findings highlight the urgent need for a comprehensive risk assessment framework to address the environmental risks associated with EOL LiB disposal [4].
While much of the research has focused on safety risks, such as fire and mechanical failures, limited attention has been given to environmental impacts and the subsequent health risks [5]. Some studies have examined circular economy (CE) approaches using methods like the Best-Worst Method (BWM) and TOPSIS to rank safety risks [2]. However, there is still a gap in research concerning the broader environmental effects of improper LiB disposal, especially on soil, water, and air quality, and the long-term health risks from exposure to toxic substances.
Recent research emphasizes the need for life cycle assessments (LCA) that consider not only the operational phase but also the EOL phase of LiBs (Li, J. et al., 2023). This research gap, especially regarding soil and water contamination, calls for studies to address environmental impacts, quantify risks, and propose best practices for disposal and recycling. To understand these risks, models have been developed to simulate the behavior of LiBs during disposal. For example, Jiapeng Li et al. [3] created a simulation model to quantify the self-heating risk during transportation. Similarly, studies have examined the long-term effects of LiB disposal on soil properties and the potential contamination of soil and water [[2], [4]]. Scanty literature is available on developing a generalised methodology for the quantification of environmental risk posed by EOL-LIB. The major objective of the present study is to assess and quantify the environmental risks associated with EOL LiBs, focusing on their impact on soil, water, and air quality. To validate these findings, experimental investigations have been conducted to evaluate soil degradation due to contaminants from EOL LiBs. These lab results provide empirical evidence supporting the risk model, which quantifies the severity, probability, and vulnerability of various disposal scenarios. The outcomes will contribute to developing sustainable LiB disposal and recycling strategies, addressing the environmental impact of EOL LiBs amid the growing EV market.
In a nutshell, Lithium-ion batteries (LiBs) are widely adopted in electric vehicles due to their high energy density and long cycle life. However, concerns over resource scarcity and environmental risks at their end-of-life stage have prompted the exploration of alternatives, such as zinc-ion batteries (ZIBs) and sodium-ion batteries (SIBs). ZIBs, utilizing bio-based electrolytes such as those developed by Xu et al. [6], provide safer and more sustainable options. Similarly, SIBs, as demonstrated by Massaro et al. [7], show promise with lower cost, thermal stability, and suitability for lightweight EVs. Despite their advantages, spent LiBs can leach heavy metals into the soil, degrading its properties. Mishra and Apte [8] reported significant geotechnical impacts from LiB disposal, reinforcing the need for improved recycling techniques, such as those reviewed by Zhang et al. [9].
The methodology adopted and the sequenced steps are being followed for the risk assessment study and are shown in Figure 1. The steps are described in detail in the following section.Fig 1Methodology adopted for the study.Fig 1
The very first step is to understand the impact of the disposal of spent LiB, which involves addressing the risk and its identification through an extensive literature review. A literature review study is conducted, and through existing studies, the various undesirable conditions due to LiB waste disposal are identified. The major literature is presented in Table 1 below. It becomes evident through these studies that the EoL LiB disposal routes cause environmental degradation, i.e., to soil, air, and water resources.Table 1Existing literature review study in the area of battery waste disposal.Table 1Disposal MethodEnvironmental Medium AffectedKey Contributing FactorsUndesirable ConditionsReferencesLandfillingSoil, groundwater- Electrolyte leakage- Heavy metal leaching (Li, Co, Ni)- Poor landfill lining- Long-term corrosion of casings- Groundwater contamination- Soil acidification and metal toxicitySiddiqua et al. [10]; Zhang et al. [11]IncinerationAir- Incomplete combustion- Emission of HF, CO, dioxins- No gas scrubbing systems- Air pollution (PM2.5, VOCs)- Respiratory health hazardsBeall [12]; Chen et al. [13]Informal Recycling / Open BurningAir, water, and soil- Open burning of plastics and electrolytes- Acid leaching without containment- Lack of worker protection- Release of POPs and toxic fumes- Soil and water contamination- Human health risksMrozik et al. [14]; Jayaraman et al. [15]Open dumpingSoil, water, air- Weathering and corrosion- Fire hazards due to thermal runaway- Fire, explosion risks- Heavy metal leachate generationZhang et al. [11]; Gaines et al. [16]**All Methods (Cross-cutting issues)**Multiple- Lack of standardized EoL management- Absence of legislation/enforcement- Poor public awareness- Systemic pollution risk- Accumulation of hazardous substances in ecosystemsGuelfo et al. [17]; Jayaraman et al. [15]
To understand the impact of undesirable events under different scenarios on the air, water, and soil environment at different locations of disposal, a detailed impact assessment is performed using the network method as shown in Figure 2. The primary (direct), secondary (indirect), and tertiary (cumulative) impacts are also presented through the network diagram as per the guidelines outlined in ISO 2015 Environmental Management Systems, which facilitates the identification, classification, and ranking of environmental impacts based on severity, frequency, and spatial distribution.Fig 2Network diagram of causes and impacts of EOL LiBs.Fig 2
The probable destinations of waste lithium-ion batteries (LiBs) suggest that, irrespective of the disposal or recycling method, be it incineration, landfilling, or hydrometallurgical processes, the resulting end materials commonly include metal-rich ash, airborne emissions, slag, and leachate. These by-products pose significant environmental risks due to their toxic constituents, as evidenced by studies on pyrometallurgical and hydrometallurgical recycling processes, acid leaching methods, and the formation of hazardous slag and emissions during recycling efforts ([[14], [18], [19]]; Jin et al., 2006; [20,21]).
The network diagram indicates that the major impacts of open dumping of EOL LiBs are the flow of toxic substances through leachate into the soil. This has subsequent impacts such as soil contamination, contamination of water bodies through surface discharge, and alterations in the soil structure. Landfilling leads to degradation of soil physical and chemical properties, making it sterile and unfit for future construction. Similarly, recycling and/ or incineration lead to the production of slag, metal-rich ash, and air emissions, which can lead to adverse environmental consequences if not disposed of properly.
To explore and understand the environmental impacts of End-of-Life (EOL) lithium-ion battery (LiB) disposal, a series of Focus Group Discussions (FGDs) were conducted with stakeholders, including community members, informal waste handlers, and local environmental authorities. These discussions are structured around key themes derived from the prior impact assessment study and aimed to capture perceptions related to the probability and severity of risk events associated with various LiB disposal practices.
FGDs are widely recognized as an effective qualitative method for eliciting diverse perspectives, especially on complex or sensitive topics such as environmental risk [22,23]. The major focus is on the severity (negligible, low, medium, significant, and severe) of a consequence and on the probability (Rare, Unlikely, Possible, Likely, Almost Certain) of occurrence of such a consequence, and the discussion is shared as Supplementary Material-2. The following steps are shown below for carrying out the FGD:•Triangulation: This method involves using multiple methods or data sources to validate the findings of the focus group discussion. For the same, FGD results are compared with data from other sources, such as surveys, interviews, or secondary data. The findings are cross-checked by comparing the outcomes across multiple groups or stakeholders to identify common themes and discrepancies. Also, a different set of researchers/observers is being used to analyse the same FGD transcripts to cross-verify if similar conclusions are drawn.•Member Checking: This step involved returning to the participants to check if the findings or interpretations made from the FGD align with their intended meanings. After analyzing the FGD outcomes, findings are shared with the participants (or a representative sample) to ensure that their views are accurately captured and interpreted. This is done through follow-up interviews, email feedback, or during another round of discussion.•Peer Review: This method involves seeking validation from others who have expertise in the subject or qualitative research methodology. The FGD findings are presented to the peers, colleagues, or academic advisors for their feedback and critique. This ensured that the interpretations and conclusions are reasonable, valid, and grounded in the data.•Consistency with Existing Literature: The FGD outcomes are compared with existing research and literature in the field to see if the findings align or contradict with prior studies. For the same, similar studies or reports are studied to see if FGD outcomes correspond to established knowledge or if there are any new insights that support or challenge existing theories to confirm the relevance and significance of the findings.•Clear and Transparent Reporting: This step includes providing a detailed and transparent account of the FGD process and outcomes to allow for external verification. To make sure that the context, participants, methodology, and findings of the FGD are clearly documented in the final paper.•Validation with Stakeholders: The findings are presented to stakeholders to see if they recognize the themes or if they suggest any corrections or additions. This step ensures that the outcomes are grounded in real-world applications and have practical relevance.•Follow-up and Observation: Follow-up discussions are being conducted to see if the themes identified in the FGD hold true over time. Conduct follow-up FGDs with different groups or the same group after a period to validate whether the findings remain consistent. In some cases, longitudinal studies or observations can help ensure that the conclusions drawn from the FGD are sustainable and applicable over time.•**Risk Matrix **•Under different scenarios, the occurrence of risk would have a different magnitude, i.e., in some scenarios, the risk posed is low, and in other scenarios, the risk posed has a higher magnitude. The various scenarios considered include weather conditions (Non-Rainy Season(NRS) and Rainy Season (RS), underground water table conditions (High Water Table (HWT) and Low Water Table (LWT)), terrain conditions, type of disposal of S-LiB (Open Dumping (OD) or Landfill disposal (LF) on which transfer mechanism of EOL lithium-ion battery waste into the environment depends on. Based on these influencing parameters, a total of 64 different scenarios are defined and provided in the supplementary material. Out of the total 64 risk scenarios, a total of 20 worst-case scenarios (as shown in Table 2) are considered for the quantification of risk using the risk matrix. The detailed risk matrix is provided in Supplementary Material 3.Table 2Probable Worst-case Scenarios based on the Combinations of Influencing Parameters.Table 2Rain ConditionGroundwater conditionSoil typeTerrain conditionType of Disposal of S-LiB1NRSHWTCGSlopyOD2NRSHWTCGSlopyLF3NRSHWTCGFlatOD4NRSHWTCGFlatLF5NRSHWTFGSlopyOD6NRSHWTFGSlopyLF7NRSLWTCGSlopyOD8NRSLWTCGSlopyLF9RSHWTCGSlopyOD10RSHWTCGSlopyLF11RSHWTCGFlatOD12RSHWTCGFlatLF13RSHWTFGSlopyOD14RSHWTFGSlopyLF15RSHWTFGFlatOD16RSHWTFGFlatLF17RSLWTCGSlopyOD18RSLWTCGSlopyLF19RSLWTCGFlatOD20RSLWTCGFlatLFNote: NRS- Non-Rainy Season, RS: Rainy Season, HWT- High water table, LWT-Low water table, CG- Coarse grained, FG- Fine grained, OD-Open dumping, LF- LF-Landfilling
Step Quantification of Severity and Probability of an event through FGD
FGD facilitated in defining the limits of severity (S) and probability (P) of an event, i.e., Table 3 shown below. Enlisting different scenariosTable 3Range for Severity and Probability.Table 3Sr. No.SlimitsPlimits1Negligible0-2Rare0-22Low2-4Unlikely2-43Medium4-6Possible4-64Significant6-8Likely6-85Severe8-10Almost Certain8-10
The ranges/ limits represent the degree of severity and likelihood. For instance, if the event's severity is negligible, it is rated between 0 and 2; similarly, low severity ranges from 2 to 4, medium from 4 to 6, significant from 6 to 8, and severe from 8 to 10. A similar approach is used to assess the probability of a Rare is rated from 0 to 2, Unlikely from 2 to 4, Possible from 4 to 6, Likely from 6 to 8, and Almost Certain from 8 to 10. The collected responses are recorded in Excel, and after analyzing the results, conclusions are drawn.
Step Vulnerability based on different scenarios (network diagram):
The network diagram formed helps in identifying the different scenarios under which EoL LiBs would affect the environment. For instance, different scenarios such as dumping the waste LiBs, Recycling, or Incinerating would lead to different consequences, having primary, secondary, and tertiary impacts on the environment (soil, air, and groundwater). After enlisting different scenarios, a combination of worst-case scenarios is taken up, and vulnerability is then rated. Hence, we get probability and severity ratings through FGD and Vulnerability through identifying 20 worst-case scenarios.
The calculation for vulnerability is based on assuming different ranges for different cases. Table No. 4 depicts the vulnerability rating based on different scenarios.
Based on these ranges, a table is formed to determine the vulnerability for all 20 scenarios. The table is shown in the supplementary material as S1.
Step Risk Matrix formation
The risk matrix is created by analysing various scenarios as mentioned above. The magnitude of risk is calculated by multiplying the probability of an event, the associated vulnerability, and the severity of the consequence, represented by the formula R∑(P × V × S). where, P is defined as the probability of a hazard occurring in a location or region, V as the vulnerability that increases the likelihood of a negative event depending on the scenario, and S as the severity that identifies the extent of the impact on the environment and human health. Based on these risk values, the high-risk scenarios are identified.
Table 4 shows a list of various critical scenario combinations, focusing only on the worst-case scenarios out of a total of 64. The calculations done for probability, severity, and vulnerability for the 20 worst-case scenarios are provided in the comprehensive risk table in supplementary material S2. The maximum risk values for the worst-case scenarios are presented in the risk matrix (Table 5).Table 4Scenario-Based Vulnerability Ratings for End-of-Life LiB Disposal Under Varying Environmental and Site Conditions.Table 4Sr. No.ConditionsWorst-case ScenarioVulnerability RangeSr. No.ScenarioVulnerability Range1Weather conditionRainy0.66Non Rainy0.42Ground conditionHWT0.77LWT0.33Underlying soil typeCoarse Grained0.88Fine Grained0.24Geographical conditionSloppy Terrain0.59Flat Terrain0.55LocationOpen Dumping0.710Landfill0.3Table 5Risk Matrix.Table 5ProbabilitySeverityS1S2S3S4S5246810P10.20.2640.5280.7921.0561.32P20.40.5281.0561.5842.1122.64P30.60.7921.5842.3763.1683.96P40.81.0562.1123.1684.2245.28P511.322.643.965.286.6Table 6Classification of risk associated with EOL-LiB waste flow.Table 6Sr. No.Risk classScale1Extreme (RE)5.01-102High (RH)3.50-5.003Moderate (RM)2.00-3.494Low (RL)0.25-1.99
The experimental study is carried out in order to study the effect of EOL EV Battery disposal on soil. Various soil properties, such as soil index (Specific Gravity and Atterberg's Limit) and Soil Engineering (Permeability and Shear strength) properties, are obtained. The results obtained for open dumping and landfill conditions are compared, and the magnitude of risk obtained through risk matrix formation is then compared.
The validation of focused group discussion and the Risk matrix formed specifically for soil contamination is discussed in the present section. Various steps involved in validating the FGD are shown below, followed by depicting the experimental results for contaminated and non-contaminated soil samples for open dumping and landfill conditions in tabular form.
**Focused group ** To validate the sample sufficiency of the focused group discussion, factor analysis is performed.Table 7Factor analysis for sample size and adequacy.Table 7Factor AnalysisCut-off ValueSourceKaiser-Meyer-Olkin Measure of Sampling Adequacy..921Meritorious: ≥0.80,Middling: ≥0.70,Mediocre: ≥0.60,Miserable: ≥0.50,Unacceptable: <0.50Recommended value of 0.6or aboveHair et al. (2010)Bartlett's Test of SphericityApprox. Chi-Square5645.830Significant at α < .05Hair et al. (2010)df171Sig..000
To assess the impact of lithium-ion battery (LiB) contamination on soil and to validate the findings of the risk matrix, an experimental investigation is conducted focusing on the degradation of soil properties. Among several influencing factors, such as weather conditions, groundwater table levels, soil type, and the location of LiB waste disposal, the present study specifically considers two open dumping and landfill conditions. These two disposal methods are examined to evaluate how they affect soil degradation. Given that soil contamination is a critical concern in the disposal of end-of-life (EoL) LiBs, laboratory tests are carried out on both uncontaminated samples and samples exposed to contamination under the selected conditions.•Soil Properties Studied: Index properties and engineering characteristics of the soil are evaluated, including parameters such as specific gravity, Atterberg limits, Strength characteristics, Settlement characteristics, and permeability.•Experimental The experimental setup was done in the laboratory for both conditions, i.e., open dumping and landfilling. The prototype construction and sample collection were done following the study by Mishra, P., & Apte, S. D. (2025) wherein they have simulated the landfill condition in the laboratory through constructing a prototype and a detailed laboratory investigation was performed on the control and contaminated samples at different time intervals, i.e. 15,30,45,69,75, and 90 days. To simulate the open dumping condition in the laboratory, again the samples were mixed with 3%, 6% and 9% heavy metal powders present in LiBs as per definite reference values shown by Joan Mwihaki Nyika et al., (2019) and Perry et al., (2018). The samples were collected using sample collection methodology presented by Mishra, P. & Apte, S.D (2025).•Quality Assurance and Quality Control (QA/QC):•To ensure the reliability and accuracy of the experimental results, standard QA/QC procedures are implemented throughout the study. This •Sample Integrity: All soil samples are collected, labelled, and stored using standardized protocols to prevent cross-contamination.•Calibration of Equipment: Laboratory instruments and equipment are regularly calibrated as per manufacturer guidelines and ASTM standards.•Repetition of Tests: The tests are triplicated, and average or concordant values are reported to avoid errors. The tests are repeated to confirm the consistency and repeatability of results.•Use of Certified Reference Materials: Where applicable, certified materials are being used to validate test procedures. The study follows the ASTM codes for sample analysis.•Documentation and Traceability: All test procedures, observations, and outcomes are being thoroughly documented to maintain transparency and traceability.Table 8Experimental result summary for non-contaminated and contaminated samples under open dumping and landfill conditions.Table 8Sr. No.Soil PropertiesASTM CodeNon-contaminated condition (1)Degradation during open dumping (2)ƍo(Delta= 2-1)(3)% change = (3)100/(1)Degradation during landfilling (4)ƍl(Delta)= (1)-(4)(5)% Change= (5100/(1)1Plasticity characteristics (PI)D43182268713961.51537332.32Specific Gravity (G)D8542.762.8-0.04-1.452.81-0.05**-1.813Settlement Characteristics (Cv, 10^-06^ cm^2^ /s)D47675.56.65-1.15-216.1-0.6-114Strength Characteristics (C and Ø)(kPa)D2850C= 90.22Ø= 11.87Ƭ= 121.11C= 43.13Ø= 14.1Ƭ= 80.0541.0634C= 72.1Ø= 14Ƭ= 108.7612.3510.25Permeability (K, 10^-09^ cm/s)D585628.3-6.3-3157.5-5.5-2756Swelling Characteristics (FSI)D589023510912653.611558034.047Micro-structural alterationsFE-SEM AnalysisAppears smooth, compact, and well-defined stacked sheet structuresIncreased flocculation and particle size––Presence of micro cracks, irregular voids, and fragmented structure—****–**ƍo = Delta for Open dumping condition, ƍl = Delta for Landfill conditionTable 9Comparative Assessment of Geotechnical and Microstructural Impacts of EoL LiB Disposal Methods on Soil Properties.Table 9AspectOpen Dumping ImpactLandfilling ImpactBetter disposal methodPlasticity (PI)High degradationModerateLandfillStrength (τ)Severe dropSlight dropLandfillPermeability (K)Highly increasedIncreasedLandfillCompressibility (Cv)IncreasedSlightly increasedLandfillSwelling (FSI)Large dropModerate dropLandfillMicrostructureHighly disturbedModerately disturbedLandfill
It can be observed from the above table that the open dumping of LiB waste severely degrades soil properties, making it more compressible, weaker, and more permeable, posing high environmental risks. Landfilling, while not ideal, shows significantly less damage across all tested parameters and is a comparatively safer disposal method. Similarly, a risk pattern is observed in the risk matrix developed in the present study.
The sustainable management of end-of-life lithium-ion batteries (LiBs) requires a systemic approach that includes not only treatment technologies but also the proper handling, collection, and distribution infrastructure. Currently, many countries rely on informal or fragmented collection systems, leading to uncontrolled disposal and environmental hazards, especially in developing regions [24]. To mitigate this, extended producer responsibility (EPR) frameworks are gaining traction globally, mandating manufacturers to take accountability for post-consumer battery recovery and ensuring traceability throughout the supply chain [25].
Collection and segregation of LiB waste remain critical challenges. Safe handling requires proper classification, labeling, and temporary storage to avoid short-circuiting, thermal runaway, or leakage. Existing guidelines recommend transportation under UN 3480 standards; however, implementation remains inconsistent [26]. In response, smart logistics and digital tracking systems using blockchain and IoT are being developed to monitor battery location, health, and ownership, ensuring safer and more efficient reverse logistics. On the treatment side, while traditional pyrometallurgical and hydrometallurgical methods dominate current recycling practices, they come with high energy demands and environmental costs. In contrast, biological recovery, solvent extraction, and electrochemical separation (e.g., electrodialysis) are emerging as low-impact alternatives for recovering critical metals such as Li, Co, Ni, and Mn [[9], [27]]. For soil, biochar-amended barriers and in-situ immobilization techniques are being researched to limit heavy metal mobility. For water, membrane-based filtration and chemical precipitation remain effective, though scalability and cost-efficiency continue to evolve. For air emissions, safer thermal treatment systems and dry processes are replacing acid-intensive methods to reduce toxic off-gassing [7]. Looking ahead, integrating design-for-recycling principles during battery manufacturing, along with digitized return systems and regional processing hubs, can significantly improve the circularity and environmental safety of LiB waste management.
The proposed approach enables the quantification of environmental risks associated with the disposal of End-of-Life (EoL) Lithium-ion Batteries (LiBs), an area with limited existing research. Few studies to date have developed methodologies for assessing and quantifying such risks, despite the growing urgency to address the environmental and health hazards posed by improper LiB disposal. This study addresses this gap by introducing a novel framework involving Focus Group Discussions (FGDs) and scenario-based vulnerability ratings to construct a risk matrix. However, the study has certain limitations. The formation of the risk matrix is inherently influenced by the knowledge and perspectives of the selected FGD participants, which introduces the possibility of subjectivity or bias. Furthermore, validation of the framework is carried out through laboratory-scale testing of a single case scenario under controlled conditions. These findings, while valuable, may not fully capture the complexities and dynamic nature of real-world disposal environments, where variables such as heterogeneous battery composition, climatic factors, and local disposal practices may significantly alter risk outcomes.
Additionally, field-level validation under actual disposal conditions should be pursued to test and refine the model's applicability in varied geographic and socio-economic contexts. Integration of geospatial data, real-time monitoring, and machine learning techniques could further enhance risk prediction and provide dynamic decision-support tools for regulators and waste management authorities. Cross-country comparisons may also be beneficial in identifying context-specific as well as universal risk factors associated with EoL LiB disposal.
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.