Internal Combustion Engine Vehicles Research Articles

Greening the roads: Assessing the role of electric and hybrid vehicles in curbing CO[formula omitted] emissions

The transportation sector is the largest contributor to greenhouse gas (GHG) emissions, and electric and hybrid vehicles (EHVs) are among many solutions that can help reduce the consumption of fossil fuels and their resulting GHG emissions. This study addresses the significant and understudied question of how EHVs’ adoption influences CO2 emissions using panel U.S. state-level data over the 2016-2019 period and fixed effects. The study finds no statistically significant relationship between the adoption of hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles (PHEVs), and plug-in electric vehicles (PEVs) and CO2 emissions. These findings could be explained by adoption rates of HEVs and PHEVs that are too low to manifest statistically significant reductions in CO2 emissions from the potential displacement of internal-combustion engine vehicles (ICEVs). The findings also align with observations indicating that PEVs, although emission-free, are frequently adopted as supplementary rather than primary vehicles by multi-vehicle households in the U.S. The complexities surrounding EHVs and their impact on CO2 emissions highlight the importance of further research in understanding the role these vehicles play in the larger context of sustainable transportation as well as more nuanced research into adoption patterns, potential policy interventions, and broader environmental implications.

Historical and prospective lithium-ion battery cost trajectories from a bottom-up production modeling perspective

Lithium-ion batteries (LiBs) are pivotal in the shift towards electric mobility, having seen an 85 % reduction in production costs over the past decade. However, achieving even more significant cost reductions is vital to making battery electric vehicles (BEVs) widespread and competitive with internal combustion engine vehicles (ICEVs). Recent trends indicate a slowdown, including a slight cost increase in LiBs in 2022. This study employs a high-resolution bottom-up cost model, incorporating factors such as manufacturing innovations, material price fluctuations, and cell performance improvements to analyze historical and projected LiB cost trajectories. Our research predicts potential cost reductions of 43.5 % to 52.5 % by the end of this decade compared to 2020. Furthermore, reaching cost parity between BEVs and ICEVs is expected in the latter half of this decade, contingent on a total installed capacity of 3500 to 4100 GWh.year−1 across giga-factories. The determinants influencing these cost reductions evolve over time, with historical significance placed on savings in cathode materials and anticipated future importance on minimizing scrap rates. This research offers valuable insights for policymakers and investors in the LiB industry, aiding informed decision-making.

CanmetMINING battery electric vehicle field test series: Relay utility vehicle

ABSTRACT Battery electric vehicles (BEVs) have been used increasingly in Canadian mines to replace conventional internal combustion engine vehicles due to their high efficiency, low heat production, and zero emissions locally. To help understand BEV technology, performance, and energy consumed under different work conditions, CanmetMINING and CanmetENERGY conducted a series of tests on the Miller Technology Relay BEV at Vale’s North Mine site in Ontario, Canada. The 1.25-km test route comprises uphill and downhill sections with flat (0%), 5%, 10%, and 20% inclination grades. The BEV was driven through the route in both directions to complete multiple 2.5-km laps at 5 and 15 km/h while loaded and empty. This paper presents test results normalized by distance, including energy consumed and captured tabulated by inclination grade, speed, and load. The consumed and captured energy ranged from −1.4 to 4.5 kWh/km at 5 km/h and from −2.0 to 3.7 kWh/km at 15 km/h. The battery charging data and variation in state of charge are also presented to describe the energy balance during BEV operation. A vehicle energy model calibrated against the field test data was used to estimate the energy consumption of a utility BEV operated in an underground mine.

Electrifying Green Logistics: A Comparative Life Cycle Assessment of Electric and Internal Combustion Engine Vehicles

Green logistics is an approach aimed at reducing the environmental impact of transport, storage, and distribution practices, through low-emission vehicles, optimized routes, clean energy tech in warehouses, and efficient waste management. These solutions can contribute to achieving the sustainable development goals of the European Green Deal. The main research question of this paper is whether an electric vehicle has a lower environmental impact compared to a gasoline vehicle. This study presents a life cycle assessment (LCA) of an electric vehicle using lithium-ion battery technology (BEV) and compares it to an internal combustion engine vehicle (ICEV), considering the transportable load within the context of Italy. Through a gate-to-grave approach, both vehicles’ life cycle use and disposal phases were evaluated to identify the hotspots of environmental impact. The LCA methodology allows for an objective comparison and the results show that BEV emits slightly less kgCO2eq than ICEVs. The primary contributor to the vehicles’ impact is the dependency of the electric energy primary source from fossil fuels. Therefore, a second analysis was conducted to analyse the benefit of photovoltaic panels to generate the electric energy, showing that it can result in a significant 50% reduction in impact, making the electric vehicle a valid solution for achieving green logistics objectives. However, the questions of electric energy production, management, and distribution together with the supply of raw material and disposal of lithium batteries remain open. This issue raises a concern regarding the BEV in a country like Italy where the lack of recharging points limits the adoption of electric vehicles in green logistics.

Analysis on the Thermal Behavior of Lithium-Ion Battery with Nickel-Rich Cathode and Silicon-Carbon Composite Anode

<div>Compared with traditional internal combustion engine vehicles, electric vehicles still have shortfall in driving range and energy replenishment time. In order to continuously improve the driving range of electric vehicles, the high-nickel/silicon-carbon lithium-ion battery with high energy density is a promising industrialized application route. However, with the increase of battery energy density, the heat generation of battery usually increases, which will inevitably bring greater heat dissipation problems to the battery thermal management system. To design a good thermal management system, the first thing is to accurately measure and deeply understand the heat generation characteristics of the battery. In this work, the heat generation behavior of a high-nickel LiNi<sub>0.8</sub>Co<sub>0.1</sub>Mn<sub>0.1</sub>O<sub>2</sub>/silicon-carbon pouch-type battery under different operating conditions were tested by an isothermal battery calorimeter. The influence of current rate, current direction, and operating temperature on the heat generation characteristics of the battery was systematically analyzed. A comparison between heat generation power of batteries with different cathode/anode materials was provided. The research results of this article can deepen the understanding of the heat generation behavior of LiNi<sub>0.8</sub>Co<sub>0.1</sub>Mn<sub>0.1</sub>O<sub>2</sub>/silicon-carbon battery and provide guideline for the design of thermal management system.</div>

The economic aspects of vehicle operation in the context of electromobility strategies

The transformation of the automotive industry towards electromobility is a key step in achieving a sustainable transportation system. To analyze the economic feasibility of electric vehicles (EVs) compared to internal combustion engine vehicles (ICEs), this study assessed the operating costs of both types of vehicles, including fueling and charging costs on a selected theoretical route. The analysis of economic aspects also examined the development of fueling and charging infrastructure and the impact of government programs promoting electromobility. The study employs a comparative analysis of ICE and EV based on fuel and electricity prices, insurance costs, and servicing expenses. The results of the analysis indicate that adopting EVs can lead to significant economic benefits, especially when coupled with government incentives and well-developed charging infrastructure. The network of charging stations and fuel infrastructure serves as an indicator of the market conditions for vehicles equipped with either internal combustion engines or electric powertrains, and forecasts help anticipate their future directions. The decreased pace of new petrol stations being established may indicate a weakening market for internal combustion engine vehicles compared to previous periods. This study highlights the economic aspects of electromobility strategies aimed at accelerating the transition towards a sustainable transportation system.

The application challenge of electric vehicles

The growing demand for sustainable transportation has prompted an accelerated transition toward electric vehicles (EVs) as a promising solution to mitigate the environmental impact of conventional internal combustion engine (ICE) vehicles. This research analyzes the key challenges and technologies associated with EVs, aiming to produce insights into this rapidly evolving field. The challenges surrounding EVs encompass various aspects, including limited driving range, lack of access to electric vehicle charging stations (EVCS), charging times for EVs, and safety considerations. To overcome these challenges, several technological advancements have emerged. Battery technology has advanced to extend the driving range per charge of an electric vehicle. Various models and algorithms to study the EVs charging station placement problem (EVCSPP) have been proposed to find the optimal location to build the charging stations. The advancement of extreme fast charging (XFC) technology and the intelligent transport system (ITS) shorten the charging time to improve the practicality of EVs adoption. Furthermore, the EVs charging standard and risk management have been introduced to ensure a secure charging system. By addressing these challenges and leveraging innovative technologies, a comprehensive and sustainable charging network can be realized, facilitating the transition towards a cleaner and greener transportation system.

Optimization of battery swapping stations with heterogeneity, charging degradation and PV-option

Greenhouse gas emissions-related issues have been extensively discussed in the past years, with over 70 countries already committed to a carbon-neutral economy by 2050. The electrification of transportation modals has increased following these goals, where Electric Vehicles (EVs) are starting to take Internal Combustion Engine Vehicles (ICEV) market share all over the globe. Besides the particular complexity in comparing EVs and ICEVs, challenges involving the nature of EVs and their integration with cities, such as the lack of public locals for charging, are also critical and interfere with their development. In this context, this work aims at studying the problem of a Battery Swapping Station (BSS), a structure where the EVs users swap their depleted batteries for fully or partially charged ones. In order to simulate the BSS daily operations and battery charging schedule, a novel Mixed Integer Linear Programming (MILP) model is proposed, taking into account battery heterogeneity, the use of local photovoltaic (PV) production, and battery degradation based on charging profile. A collection of BSS operation metrics are designed to evaluate the solution quality of the proposed scheduling model. A numerical experiment comprising four case studies based on real data from the US power and transportation systems is presented, with insights and analyses on the PV and grid power use, as well as a BSS financial comparison against close-related benchmark scheduling approaches, together with sensitivity analyses on BSS sizing plan and costumers service. Results highlight the importance of battery degradation in the optimization model, since its consideration as an operational cost brought a reduction of 16%.

Tribological evaluation of electric vehicle driveline lubricants in an electrified environment

Electrification continues to permeate the automotive industry, with future projections showing an exponential growth in the market share for both light and heavy-duty applications. Existing test methods for automotive applications were developed to model internal combustion engine vehicles and drivelines and are not appropriate for electric drivelines that experience stray electric currents. Tribometers can be used to evaluate friction and wear on modeled surfaces simulating in-vehicle operation. In this work, a commercially available tribometer was modified to isolate an electrical input into a tribological contact. After necessary modifications to the tribometer, a test matrix was completed for investigating different temperatures, load conditions, speed conditions, voltage input types, frequencies of AC signal, and shapes of AC signal. These parameters were tested on three lubricants—two typical automatic transmission fluid formulations and gear oil used in differential applications. Friction was measured throughout the tests, and wear scar width was measured at the end of each test. Results indicated that temperature, DC voltage, AC frequency, lubricant, and test profile had statistically significant differences in wear scar width. For electrical parameters, AC frequency produced different results from DC voltage when no voltage was applied. This significance applied to only one lubricant, with the other two lubricants having mixed results.

Four-color fiber-coupled mid-infrared laser-absorption sensor for temperature, CO, CO2, and NO at 5 kHz in internal combustion engine vehicle exhaust

A mid-infrared (MIR) laser absorption spectroscopy (LAS) sensor was developed for temperature, CO, NO, and CO2 measurements at 5 kHz in engine-out exhaust. It used fiber-coupled quantum cascade lasers (QCLs) for measuring CO and NO, and an interband cascade laser (ICL) for measuring CO2. Validation tests in a heated gas cell confirmed that the LAS measurements of CO, CO2, NO, and temperature are accurate to within 4.8%, 5.1%, 4.6%, and 3.1%, respectively, at 1–2 atm and 300–1000 K. The LAS sensor was applied to characterize the engine-out exhaust gas of an 8-cylinder gasoline engine in a light-duty truck at operating conditions where commercial instruments lack sufficient time response to quantify important emission dynamics.

A REVIEW ON INTEGRATION OF ELECTRIC VEHICLES AND OPTIMAL POWER MANAGEMENT STRATEGY FOR SUSTAINABLE DEVELOPMENT

The integration of electric vehicles (EVs) into our transportation system is a pivotal step towards sustainable development. EVs are gaining traction as a cleaner and more energy-efficient alternative to traditional internal combustion engine vehicles. Their adoption holds the promise of reducing greenhouse gas emissions and decreasing our reliance on fossil fuels, contributing significantly to environmental sustainability .One of the critical aspects of effective EV integration is the development and implementation of optimal power management strategies. These strategies play a pivotal role in ensuring that the charging and discharging of EV batteries are not only efficient but also seamlessly integrated with the existing power grid infrastructure. An optimal power management system takes into consideration factors such as load balancing, peak demand management, and the integration of renewable energy sources, making it a key component of a sustainable and resilient energy ecosystem. By efficiently scheduling when and how EVs charge or discharge, these strategies can reduce the strain on the electrical grid during peak periods, lower electricity costs, and minimize the carbon footprint associated with charging. Moreover, they can contribute to grid stability and reliability, making the entire energy system more sustainable. This research explores the synergistic potential of EVs and smart grid technologies, aiming to create a harmonious relationship between transportation and energy systems. Key Words: Electric Vehicles, Sustainable Development, Optimal Power Management, greenhouse gas emissions, fossil fuels, clean environment, smart grid technology.

Data-driven modeling of downwind toxic gas dispersion in lithium-ion battery failures using computational fluid dynamics

Understanding the toxicity hazard associated with lithium-ion battery systems (electric vehicles, e-mobility devices, energy storage systems, etc.) is critical due to their increasing prevalence in densely populated areas. In this work, a meta-analysis of literature data on the main toxic gas species emitted by lithium-ion batteries was conducted. The aggregated data were used as inputs to computational fluid dynamics simulations to characterize the universe of potential toxic gas concentration profiles. These simulations were run for various ambient conditions and battery characteristics. Results are reported in terms of estimated minimum safety distances based on immediately dangerous to life or health (IDLH) values, which could help inform decisions regarding effective firefighting and evacuation recommendations. A sensitivity analysis was also run to identify the key factors that influence safety distances as well as the combination of factors that led to the largest and shortest safety distances. Additionally, using toxicity data from the literature, the downwind toxicity of an internal combustion engine vehicle fire was compared to that of an electric vehicle fire. A relatively simple simulation setup was used for all simulations to make the results as general as possible.

Signal pre-processing techniques for fault signature enhancement in a bearing health monitoring system used in the automotive industry

Traditional internal combustion engine vehicles have low transmission bearing failure rates in their lifespans. However, the prolonged lifespan of electric and autonomous vehicles can surpass the reliable life of bearing designs, which poses a risk of bearing failure and loss of propulsion. Compared to replacing bearings on a fixed schedule to ensure reliability, a bearing health monitoring system is a more cost-effective solution. Despite extensive research on bearing condition monitoring, implementing well-known methods such as vibration spectrum analysis in vehicles can be challenging due to vibrations from vehicle components and the road. This paper explores and compares the effect of various pre-processing techniques on the spectrum of a faulty bearing with various fault levels. To achieve this objective, faults with the width size of 0.1 mm (mild), 0.5 mm (moderate) and 2 mm (severe) were injected into the inner race of a ball bearing. A bench setup was then used to capture the vibrations of multiple vehicle components including the faulty ball bearing under various speed/ load conditions. Phase domain transform, envelope and Fourier transform were used as the core signal processing steps, and advanced signal processing methods for removing discrete frequencies from other components and enhancing the fault signature were explored. 4 health indicators were then developed from the vibration spectrum of the vibration signals and calculated for the captured data. Next, for each fault level, the area under Receiver operating characteristic (ROC) curve was calculated and used as a metric to compare the performance of our health monitoring system for classification of faulty and healthy bearings. For our best health indicator, the results show that applying minimum entropy deconvolution, and spectral kurtosis-based band pass filtering increases the ROC area from 0.40, 0.99, 1.0 to 0.86, 1.0 and 1.0 for the mild, moderate, and severe inner race faults, respectively. This implies that although applying only phase domain transform, envelope and Fourier transform might be enough for moderate and severe faults, advanced signal processing is needed to enhance the fault signature for early detection of mild faults.

Electric vehicle (EV) and driving towards sustainability: Comparison between EV, HEV, PHEV, and ICE vehicles to achieve net zero emissions by 2050 from EV

This study explores the environmental and economic implications of Internal Combustion Engine (ICE) vehicles, Hybrid Electric Vehicles (HEVs), Plug-in Hybrid Electric Vehicles (PHEVs), and Electric Vehicles (EVs). A case study in Indonesia is selected, focusing to achieve net zero emissions by 2050 and improve air quality. The research compares key factors such as emission costs, fueling time costs, maintenance costs, and vehicle selection for a comprehensive understanding of each vehicle type's viability in the automotive landscape. The analysis reveals that EVs exhibit the lowest CO and CO2 emissions of about 20 %, while HEVs and PHEVs demonstrate significant reductions compared to ICE vehicles. However, EVs produce higher NOx and N2O emissions of more than 70 %, indicating a dependence on fossil fuels for electricity generation. Air quality-related emissions, including SOx and PM10, are 90 % and 85 % higher in EVs, emphasizing the need for enhanced emission control technologies and the adoption of renewable energy sources. Despite their higher selling price and emission costs, EVs possess the lowest maintenance costs among the evaluated vehicles at only 0.00419 USD/km. Ultimately, HEVs present the most balanced combination of selling price, emission cost, and maintenance cost, making them an appealing option for the market. This study provides valuable insights for policymakers, automotive manufacturers, and consumers in transitioning towards more sustainable transportation solutions.

National-scale bi-directional EV fleet control for ancillary service provision

Deploying real-time control on large-scale fleets of electric vehicles (EVs) is becoming pivotal as the share of EVs over internal combustion engine vehicles increases. In this paper, we present a Vehicle-to-Grid (V2G) algorithm to simultaneously schedule thousands of EVs charging and discharging operations, that can be used to provide ancillary services. To achieve scalability, the monolithic problem is decomposed using the alternating direction method of multipliers (ADMM). Furthermore, we propose a method to handle bilinear constraints of the original problem inside the ADMM iterations, which changes the problem class from Mixed-Integer Quadratic Program (MIQP) to Quadratic Program (QP), allowing for a substantial computational speed up. We test the algorithm using real data from the largest carsharing company in Switzerland and show how our formulation can be used to retrieve flexibility boundaries for the EV fleet. Our work thus enables fleet operators to make informed bids on ancillary services provision, thereby facilitating the integration of electric vehicles.

Using Driving-Cycle Data to Retrofit and Electrify Sub-Saharan Africa’s Existing Minibus Taxis for a Circular Economy

The nascent electrification of transport has heralded a new chapter in the driving force of mobility. Developing regions such as sub-Saharan Africa already lag in this transformative transport transition. A potential transitional step towards full-scale electric mobility is the retrofitting of the existing fleet of internal combustion-based vehicles. This paper proposes a novel approach to the design of a retrofit electric drivetrain for an internal combustion engine vehicle. Specifically, a minibus taxi, which dominates the region’s informal paratransit industry, is electrified. This retrofit is the first formal research presented with a focus on sub-Saharan Africa and its unique challenges. A generic methodology is presented to systematically specify and select drivetrain components and assess the suitability and characteristics of those components. Unique about the presented methodology is the application of driving-cycle data of internal combustion engine vehicles, which provides quantitative insights into the performance and characteristics of the selected components for a retrofit. Finally, a real-world use case is presented to provide a tangible example and to validate the feasibility of the presented approach.

Towards BitCO2, an individual consumption-based carbon emission reduction mechanism

Human activities, such as burning fossil fuels for electricity generation, heating, and transport, are the primary drivers of a large amount of greenhouse gases emission. The individual consumers, able to influence the supply-chains behind the commodities their chose to fulfil their needs is the driver behind production and, consequently, its impacts. Thus, the active and willing participation of citizens in combatting climate change may be pivotal to address this issue. The present work is aimed at presenting and modelling a novel market-based carbon emission reduction mechanism, called BitCO2, designed to incentivize individual consumption choices toward lower carbon footprints. This mechanism is tested for the Italian private transportation sector thanks to an ad hoc developed System Dynamics model. The Battery Electric Vehicle (BEV) adoption, if compared with the Internal Combustion Engine Vehicle (ICEV) one, cause less CO2 emissions per km travelled. After a certain number of travelled km, a BitCO2 token is assigned to BEV owners for each ton of avoided CO2. This token can be exchanged in a dedicated market and used to get a discount on insurance services. Assuming a Social Cost of Carbon of 9.22 [2.13–22.3] €/tonCO2eq, model results show that the BitCO2 mechanism would allow for a cumulated CO2 emission reduction of 973 [68.9–5’230] ktonCO2eq over 20 years of operation with a peak of 39.3 [5.34–189] thousand additional BEV registration per year.

Abatement of photochemical smog precursors through complete hydrocarbon oxidation over commercial Pd catalysts under fuel-lean conditions with NO promoting effect

Currently, severe environmental issues have led to a great transition in the automotive industry from internal combustion engine vehicles to electric vehicles, but this transition will take time more than 10 years, which still requires the use of internal combustion engine vehicles. However, these vehicles emit a significant amount of hydrocarbons, in addition to nitrogen oxides (NOx), due to incomplete fuel combustion. They contribute to the formation of photochemical smog when they react with NOx in the presence of sunlight. To effectively remove these hydrocarbons from the exhaust gas of turbo-gasoline engines or diesel engines, we investigated the abatement of propane and iso-pentane, two typical hydrocarbons. In particular, we studied commercial Pd catalysts and revealed how the Pd loading and aging process simulating 4k and 100k mileage affected hydrocarbon abatement abilities, and their phases were identified using characterization technique, including CO chemisorption, X-ray diffraction (XRD), and high-resolution transmission electron microscopy (HR-TEM). We also suggested the reaction pathway for the complete oxidation of propane over Pd catalyst based on the reaction orders of propane and oxygen: Propane adsorbs on O atoms of PdO, and the kinetically relevant C–H bond cleavage step occurs by the interaction with abundant neighboring O atoms of PdO. Finally, the propane and iso-pentane abatement ability of the Pd catalyst aged for 100k mileage were evaluated under realistic exhaust gas conditions, and the effect of each gas component in the realistic exhaust gas was identified; water inhibits the catalytic reaction of hydrocarbons by occupying the active sites, whereas NO catalyzes the hydrocarbon oxidation reaction by either changing the reaction pathway or active sites under fuel-lean conditions. These findings enable us to effectively reduce environmental pollution and facilitate a smoother transition from internal combustion engine vehicles to electric vehicles.

Life cycle climate performance evaluation (LCCP) of electric vehicle heat pumps using low-GWP refrigerants towards China's carbon neutrality

The environmental-friendly heat pump with low global warming potential (GWP), such as R1234yf, CO2, R290, and several potentially promising refrigerant mixtures, is increasingly essential for the electric vehicle (EV) to save energy consumption and extend the driving range. It is beneficial to achieve carbon neutrality by reducing both direct and indirect carbon emissions. Previously, the life cycle climate performance (LCCP) was a widely accepted metric to evaluate the carbon footprint of mobile air conditioning systems “from cradle to grave” for the internal combustion engine vehicle (ICEV), however, such LCCP analyses about EV heat pumps can hardly be found. To facilitate the EV industry and policymakers' better understanding of the environmental impacts of those low-GWP refrigerants, this study provided a comprehensive LCCP analysis for the EV heat pumps based on the system bench test results, local climates, local power supply characteristics, real-world driving patterns, vehicle cabin thermal sensation, and climate control load. Five low-GWP refrigerants, i.e., R1234yf, CO2, R290, binary blends of CO2 and R41 (with GWP values of 49), M2(R410A substitute with GWP values of 137), were compared against R134a and R410A in 31 provinces of mainland China. We also considered the impacts of electric vehicle adoption rates and the carbon intensity of electricity from 2020 to 2060. Results show that the total life-cycle emissions per vehicle are highly related to climate conditions in different provinces, while R290 shows the lowest emission on the national average. The national mean life-cycle emissions per vehicle are projected to decrease 14% by 2030 and 45.4% by 2060 under the current technological trajectory of electricity generation. By using low-GWP heat pump systems in EVs, the cumulative emissions counting all vehicles can be saved up to 1450 Mt. CO2e from 2020 to 2060.

Tracing the multiregional evolution of the global dysprosium demand-supply chain

Dysprosium (Dy) is a critical rare earth element, indispensable for realizing low-carbon technologies. A holistic understanding of global Dy supply-demand chains is essential for ensuring its future sustainable supply and use. This study conducts the first multiregional analysis of Dy flows and stocks to comprehensively trace the global Dy cycle from 1988 to 2021. Results show a rising demand for Dy-comprising intermediate and final products with complex trade fluctuations since 2000. In total, 22,009 tons of intermediate products, primarily as neodymium-based permanent magnets (NdFeB), accumulatively entered the global manufacturing phase, of which China accounted for approximately 55%. Dy use was notable in the United States and Japan for internal combustion engine (ICE) vehicles manufacturing and for industrial machinery production in the European Union. Less than 3% of globally mined Dy was recycled. Considering the growing global demand for Dy, alternate supply sources, and regional efforts to promote recycling and circular economy strategies are required.