Evaluating the Global Processability of Anthropogenic Metals from Mining Waste

Abstract

Natural resource depletion and increased mining waste pose significant challenges to global sustainability efforts. This study investigates the processability of mining waste during the metal recovery stage to evaluate its potential contribution to anthropogenic circularity. The mining industry, abundant in valuable metals that are crucial for a carbon-neutral economy, plays a pivotal role in this context. We determine the grades of metals by looking at their chemical makeup, and then we use statistical entropy to model how easy it is to process certain waste materials. This provides us with processability measures that range from 0.19 bit to 1.18 bit. Our findings highlight that while some waste contains “abundant” metals, its complexity may diminish its economic value, raising concerns about its environmental impacts and resource availability at the end-of-life stages. Estimating potential revenue involves multiplying processed amounts by commodity prices, revealing a maximum value of 8.73 USD/metric ton for processed waste. This assessment underscores the importance of integrating circular economy principles, aiming to mitigate environmental damage and promote industrial ecology. By advancing our understanding of mining waste management through rigorous scientific inquiry, this study contributes to sustainable resource utilization strategies that are essential for future industrial practices and environmental stewardship.

1. Introduction

The mining industry, a leading producer of industrial solid waste globally, generates approximately 25 billion tons annually [1,2,3]. In China, 8840 state-owned and 260,000 collectively and privately owned metal mines produce mine waste. These mines are responsible for 70% of the total solid waste produced in China, with 30% (300 Mt) tailings. These wastes not only occupy significant land areas but also pose substantial environmental risks, such as contributing to greenhouse gas emissions and deforestation [4,5].

Due to economic activity, the EU-28 countries generated waste in the following proportions: in 2016, construction accounted for 36.4% of the total, followed by manufacturing (10.3%), mining and quarrying (25.3%), water services (10.0%), and households (8.5%); the remaining 9.5% was waste created by other economic activities, primarily services (4.6%) and energy (3.5%) [6]. Mining accounts for 4–7% of global greenhouse gas (GHG) emissions [7]. Mine waste is a complex and significant environmental issue that is widely acknowledged to have a global impact. For instance, mining activity has been responsible for nine percent of all Amazon rainforest losses from 2005 to 2015 [8].

A rising demand for metals is one of modern society’s main issues. Low metal recycling rates and rising demand for high-tech items require more mining, with environmental, health, energy, water, and CO₂ impacts [9,10]. Metals are not “going out” or being destroyed; they are scattered across the technosphere, making recuperation difficult and expensive. Due to global economic fluctuation and quick technological advancement, the recycling potential does not account for the total processing cost and hence cannot consistently reflect the nature of recycling technology [11,12,13].

In addition to dealing with metal depletion and waste management, the concept of responsible sourcing has developed as an important component in fostering sustainable growth. Responsible sourcing attempts to ensure that resource extraction and processing are carried out in an environmentally and socially responsible manner. This is especially important in the context of the global energy transition, where metal demand is increasing while new operations may put further strain on ecosystems and populations [14]. Our work corresponds with responsible sourcing methods by measuring the processability of mining waste, which supports the long-term use of existing resources and reduces the need for additional extraction.

Processing current or historic mining waste repositories is necessary to prevent hazards and serve as a potential source of elements for industry [12,15,16]. The efficient management of mining waste through recycling is crucial for mitigating these impacts and supporting the principles of a circular economy [17,18,19]. Here, we define processability (P) as the theoretical probability of processing a selected mine waste, considering the challenges of processing (recycling) metals [20] through physical treatment and chemical recovery.

Mining operations produce substantial waste and place significant strain on ecosystems, as evidenced by the ecosystem service costs linked to metal extraction [21]. Effective waste processing and recycling can help alleviate these pressures, minimizing the adverse effects on ecosystems and encouraging the adoption of more sustainable mining methods. Our analysis of mining waste’s processability contributes to these efforts by providing a practical approach to minimize environmental harm and maximize resource recovery.

Finding effective and long-term solutions for mine waste management is essential to changing the perception of mine waste as a potential source for recycling and accomplishing Sustainable Development Goals (SDGs) 12 and 13. For example, SDG 12 indicates that sustainable consumption and production focus on improving the usage of our overstressed and crucial materials, doing more with less, and adopting circular economies instead of linear ones. Increasing consumer demands from a growing population, with increased hopes for a brighter future, have prompted concerns about the security of supply and accessibility of numerous elements in the periodic table that are used in chemical processes and manufacturing [22]. To address these challenges, this study focuses on evaluating the processability of mining waste during the metal recovery stage. By assessing the theoretical probability of processing selected mine wastes, we aim to identify the economic and environmental feasibility of recycling various types of mining waste. This approach is grounded in thermodynamic principles, specifically entropy, which measures the disorder within waste materials and their potential for recovery [23]. This model can recover all recyclables (metals), increase material availability, moderate prices, process all anticipated chemicals, and reduce energy and environmental impacts.

The purpose of this study is to assess the processability of mining waste in the context of responsible sourcing and environmental sustainability, as well as its potential for resource recovery. By using entropy-based models to evaluate the feasibility of waste processing, we help to build methods that improve metal circularity, reduce environmental pressures, and support circular economy concepts. This article stands out due to its unique perspective.

• Mining waste’s processability is evaluated using Shannon entropies.
• A conceptually integrated processability map for mine waste is developed across ten countries. Waste is categorized based on its material mixing and processability.
• A global policy framework is developed to enhance the efficiency of mine waste management services.

2. Methodology

Our study focuses on evaluating the processability of mining waste during metal recovery to assess its contribution to circular economy principles. We have selected a few countries based on the available literature and mining activity, including those mentioned in Kügerl et al. (2023) [14] and Tost et al. (2020) [21], which discuss responsible sourcing and the ecosystem service costs associated with metal mining. These references provide a valuable context for our study, emphasizing the broader implications of mining waste management for sustainability and environmental justice. The countries include the USA [24,25,26,27,28], China [29], European Union [30], KSA [31,32], Australia [33], Mexico [34,35], Portugal [36], Malaysia [37], Poland [38], and Morocco [2,39]. The methodology was derived and modified from Kanwal et al., 2021 [3], and incorporates these considerations to assess the contribution of mining waste processability to circular economy principles.

2.1. Basis for Using Thermodynamic Entropy and Grade

2.1.1. Entropy in Waste Recycling

We use the concept of entropy to measure the level of uncertainty or disorder within a given system. Both Shannon entropy and thermodynamic entropy provide insightful information on the material distribution and processing difficulties in mining waste recycling.

Thermodynamic entropy quantifies the disorder within mining waste, which impacts the difficulty of separating and recovering valuable materials. This study employs entropy calculations to measure the dispersal of material components, providing a basis for evaluating the feasibility of material recovery [40].

Shannon Information Entropy is used to evaluate the degree of variability and unpredictability in the composition of materials found within the waste stream. This tool facilitates the evaluation of waste material’s diversity and aids in making informed decisions regarding sorting and processing strategies.

The entropy formula (Equation (1)) is used to express the statistical uncertainty in material distribution, which is directly related to the energy required for processing:

$$H=-{\sum }_{i=1}^n\left(p_i{log}_i{p}_i\right)$$

(1)

where $p_i$ is the probability of event $i$, and it is replaced by the concentration of $i$ material; $n$ is the total number of materials in an industrial waste sample, and $H$ denotes entropy (the unit of entropy is bit).

By utilizing entropy, we gain insights into how material dispersion affects recovery efforts. This measure helps in understanding the inherent challenges in processing different types of mining waste, aligns with established thermodynamic principles, and has been effectively utilized in various studies to evaluate material recovery potential [41,42,43,44].

2.1.2. Grade

The grade indicates the concentration and purity of materials, which are essential for assessing the economic viability of recycling processes [44,45,46]. The grade formula (Equation (2)) quantifies the concentration of materials, providing a clear metric for assessing the economic potential of recycling different types of waste [45].

$$D={\sum }_{i=1}^m{D}_i=\left\{\begin{array}{c}\sum _i^m{P}_i (\mathrm{P}\mathrm{h}\mathrm{y}\mathrm{s}\mathrm{i}\mathrm{c}\mathrm{a}\mathrm{l}\mathrm{l}\mathrm{y} \mathrm{m}\mathrm{i}\mathrm{x}\mathrm{e}\mathrm{d} \mathrm{w}\mathrm{a}\mathrm{s}\mathrm{t}\mathrm{e})\\ \sum _i^m\left[{\displaystyle \frac{1-\left(j_i-1\right)}{N}}\right] (\mathrm{Chemically} \mathrm{mixed} \mathrm{waste})\end{array}\right.$$

(2)

where $D_i$ is material $i^{\prime }s \mathrm{g}\mathrm{r}\mathrm{a}\mathrm{d}\mathrm{e}$; $m$ is the number of materials in a given waste sample ($m$ = $n$); $j$ is the valence ranking of metals from low to high; $N$ is the total number of all the valences of a given metal; and $D$ is the total grade of industrial waste (the unit of grade is dimensionless).

The grade metric is crucial for understanding the economic feasibility of recycling processes. Higher grade values indicate a higher concentration of valuable materials, making the recovery process more economically viable.

2.2. Processability Calculation

Processability combines the metrics of grade and entropy to evaluate the feasibility of processing mining waste. The processability formula (Equation (3)) incorporates both the grade and entropy to determine how practical it is to recover valuable materials from waste. This calculation helps in identifying which types of mining waste are more suitable for recycling based on their processability value [45].

$$P={\displaystyle \frac{D}{n·H}}$$

(3)

where P is processability (bit). D is the total grade, n is the number of materials, and H is the entropy.

2.3. Observations

The entropy is different if we only consider the components we want to recycle. For example, we only consider one recyclable component with probability p_i.

• For a single, pure component, p_i = 1, H = 0.
• For p_i = 0.1, H = 0.1.
• For pi = 0.01, H = 0.02.
• For p_i = 0.001, H = 0.003.

This calculation shows how the entropy changes with the concentration of recyclable components, demonstrating the relationship between material dispersal and recovery feasibility.

Our methodology leverages the thermodynamic entropy and grade to provide a comprehensive evaluation of the processability of industrial waste. These metrics are grounded in thermodynamic principles and offer a robust framework for assessing the potential for material recovery in line with circular economy goals. This ensures a thorough evaluation of material recovery potential, supporting the principles of a circular economy.

3. Results

3.1. Mining Waste Processability

Mining is becoming a bottleneck for the future of the Earth, and it plays a central role in the energy transition. Therefore, we calculated processability using Equations (1)–(3); the results are reported in

Table 1. Mining wastes’ processability, grade, and entropy.

Country	Location	Mining Waste Type	H (bit)	D	P (bit)
KSA	Al Amar Maaden Gold Mining	Gold tailings	0.00031–0.53	6.85	0.33
	KSA	Copper tailings	0.01–0.50	9.09	0.37
European Union	Global review	Sulfidic tailings	0.07–0.53	6.56	0.34
USA	Idaho, Western Wyoming, and Northern Utah	Phosphate mines Utah	0.00024–0.50	8.12	0.29
	Washington	Midnite Uranium mine	0.02–0.48	4.68	0.21
	Tennessee and North Carolina	Sulfidic shale and copper mine waste	0.03–0.53	4.12	0.25
	Orange County, Vermont	Elizabeth copper mine	0.01–0.19	4.12	1.18
	Central Virginia	Kyanite mine	0.0012–0.52	8.32	0.34
China	Jincheng, Shanxi Province	Coal gangue	0.08–0.46	3.95	0.54
	National Average	Fly ash	0.08–0.52	3.95	0.52
Portugal	Sao Pedro Da Cova	Coal mine waste	0.0007–0.53	7.68	0.22
Malaysia	Selinsing, Pahang	Gold mine waste	0.19–0.50	4.01	0.49
Poland	Olkusz Zn–Pb ore District	Zn–Pb ore	0.04–0.53	3.56	0.19
Morocco	Zgounder Millennium Silver Mining	Silver mine tailings	0.01–0.41	5.36	0.75
	Blieda Mining Site	Copper Mine Waste Rocks (CMWRs)	0.02–0.49	7.35	0.39
	Agadir region	Moroccan Solid Mining Wastes	0.02–0.47	7.35	0.41
Mexico	Pachuca, Mining Waste	Metallurgical waste	0.000098–0.28	10.05	0.85
Australia	Geo Discoveries, West Gosford, New South Wales	Pyritic Mine Waste	0.05–0.28	3.42	0.64

. Processability depends on the composition and grade of the contained metals. The entropy of selected wastes ranges from 0.0007 to 0.53 bit, while the grades range from 3.42 to 10.05. A higher grade indicates greater purity and a more intricate composition of each waste metal.

The results of our study demonstrate a notable range of processability, with values ranging from 0.19 to 1.18 bit. This variation underscores disparities in metals’ concentration and complexity. In a study conducted by Kügerl et al. (2023) [14], responsible sourcing is described as a thorough assessment of the waste management effectiveness, encompassing recycling methods. The processability of wastes with higher metal contents and lower entropy values is in line with this idea, highlighting the potential for more responsible recycling practices.

Figure 1 displays a processability ladder for various mining wastes. The results show that the processability spans from 0.19 to 1.18 bit. This variability reflects differences in metal concentration and the complexity of the material composition. For example, metallurgical waste, Elizabeth copper mine, silver tailings, phosphate mines, coal gangue, and fly ash lie in the high-processability zone (p > 0.5 bit) due to their high metal contents and lower entropy values. Moroccan solid mining wastes, copper mine waste rocks, gold tailings, copper mine tailings, sulfidic mine tailings, and coal gangue showed moderate processability (0.3 < p < 0.5). Zn–Pb ore, coal mine waste, sulfidic shale and copper mine, midnite uranium mine waste, and pyritic mine waste (p < 0.1) fall into a low-processability zone.

Kanwal et al., 2021 [3], stated that the Earth’s crust’s theoretical processability averages about 0.18 bit, and most of the waste samples also showed a processability above 0.18 bit [the amplification constant (100) is not considered in our study]. Less efficient metal recovery is associated with a lower grade of processability (D); however, a greater degree of material mixing (H) makes the processability more achievable and cost-effective. The lower processability suggests that the leaching agent makes metal recovery less effective.

In contrast, a lower entropy with a greater P is preferable economically. For instance, the processability rates of copper tailings, phosphate mines in Utah, coal mine waste, silver mine tailings, copper mine waste rocks, Moroccan solid mining wastes, and metallurgical waste are higher than those of coal gangue, fly ash, Zn-Pb ore, and pyritic mine waste. Coal gangue, which has a lower metal processability and is often used in road building, is a similar example. Fly ash-containing recycled waste is an example of a sustainable construction material. One can use the magnetic part for producing iron and the non-magnetic part for construction purposes [47,48].

3.2. Processability Efficiency

The relationship between processability and entropy is crucial for understanding the economic feasibility of recycling. Lower entropy with higher processability indicates more efficient recycling processes, as it reduces the complexity of material separation [36].

Figure 2 depicts the correlation between processability efficiency and entropy reduction in waste treatment operations. The data reveal that mechanical and thermal pre-treatment procedures become more efficient when the entropy (measured in bit) is lowered by 0.45 bit. This modest entropy decrease simplifies the pre-treatment, resulting in reduced energy consumption and improved material processing. A further entropy reduction, while initially more expensive, improves the overall efficiency by allowing for greater material separation and recovery over time.

The graphic also shows that the cost of separating material mixes, including different metals, increases with the minimal recycling entropy. The dashed line represents single recycled metal values, while the material mixing entropy is represented by the recycling rates. The “apparent recycling boundary” establishes the barrier for effective mechanical and thermal recycling. Recycling is easier at lower entropy levels, whereas higher entropy requires more sophisticated and costly separation methods. Overall, Figure 2 emphasizes the necessity of entropy management in improving the recycling efficiency and cost-effectiveness in material recovery.

3.3. Global Processability and Revenue Potential

Calculating the potential revenue from recycling mining waste provides valuable insights into the economic benefits of different waste types. The results show significant variations in potential revenue, with high-processability wastes like silver mine tailings offering greater economic returns. This analysis underscores the importance of considering both processability and economic factors when evaluating the feasibility of recycling different types of mining waste.

Table 1 details the grade and thermodynamic entropy of recyclable metals. Comparing processability values allows for valuable conclusions to be drawn. The Elizabeth copper mine tops the list, mainly due to its high copper content and more significant metal fractions. The second most important is metallurgical waste, which contains many valuable raw metals. Upon adequate dismantling, the metallurgical waste exhibits excellent processability, with over 0.85 bit. However, when measured in terms of grading, the processability significantly decreases due to the loss of grade, specifically in the case of pyritic mine waste. Although their processability in grade is very low due to the grade loss, the processability is high (1.18 bit), given that copper mine waste is not lost in the recycling process.

In addition to the processability results, it is essential to calculate the potential economic revenue by adequately treating the metal content. Aiming at this, the potential revenue for each waste category is calculated by multiplying the recycled quantities obtained based on the economic value of the different commodities. For instance, silver mine tailings show a high potential revenue of 8.73 USD/metric ton, while coal mine waste exhibits a lower potential revenue of 0.84 USD/metric ton (

Table 2. The revenue potential for chosen mining wastes.

Mining Waste	Potential Revenue (USD/metric ton)
Gold tailings	1.24
Copper tailings	4.33
Sulfidic tailings	3.98
Phosphate mines in Utah	3.38
Midnite uranium mine	6.88
Sulfidic shale and copper mine waste	0.94
Elizabeth copper mine	4.49
Kyanite mine	3.99
Coal gangue	6.28
Fly ash	6.08
Coal mine waste	0.84
Gold mine waste	5.70
Zn–Pb ore	0.74
Silver mine tailings	8.73
Copper mine waste rocks (CMWRs)	4.50
Moroccan solid mining wastes	4.79
Metallurgical waste	3.82
Pyritic mine waste	2.45

).

3.4. Analyzing Costs and Benefits

The cost–benefit analysis examines the economic viability of recycling various types of mining waste. Factors such as the metal concentration, recycling infrastructure, and market demand play a critical role in determining the overall cost-effectiveness of recycling efforts. This analysis helps in making informed decisions about which wastes are the most suitable for recycling based on their economic and environmental benefits. This study presents some of the costs and benefits of metal recycling from mining waste (Table S1 in Supplementary Materials).

3.5. Sensitivity Analysis

To manage and optimize mining waste operations, it is critical to understand how different factors affect processability. We applied sensitivity analysis to check the result’s credibility because there is no similar mining waste information to compare with. Tornado diagrams are a valuable tool for conducting deterministic sensitivity analysis, which assesses the relative importance of input variables on the outcome. A tornado diagram is employed in our investigation to demonstrate the degree of sensitivity of mining waste’s processability to critical parameters.

In Figure 3A, the tornado diagram illustrates the sensitivity of waste processability to variations in input parameters. Each bar represents the range of percentile deviation from the base case, quantitatively indicating the level of variation for each parameter. The length of the bars correlates with the degree of sensitivity, with longer bars signifying a greater impact on the processability. The diagram includes labels denoting the exact percentile deviation values, providing a clear measure of how each parameter affects the processability. This enables a thorough comparison of the relative influence of different parameters. Parameters with longer bars, such as “Elizabeth copper mine”, have the highest sensitivity ratings, indicating a significant effect on processability. Conversely, variables with shorter bars, such as “Zn-Pb ore”, have a minimal influence. Figure 3A thus helps prioritize the variables that are necessary for substantial processability improvements.

In Figure 3B, the scatterplot illustrates the correlation between the potential revenue (USD/metric ton) and processability (P) for a variety of mining waste categories. We plot the data points on a graph, representing processability on the x-axis and potential revenue on the y-axis. The red line represents the linear regression fit, indicating a positive correlation between processability and potential revenue. The regression equation y = 0.055x + 0.313y = 0.055x + 0.313y = 0.055x + 0.313, as well as the correlation coefficient of 0.375, indicate a moderately positive association. The statement suggests that there is a positive correlation between increased processability and higher revenue potential. This emphasizes the significance of economic factors when it comes to optimizing waste management strategies.

Kanwal et al., 2021 [3], observed that the potential revenue contribution affects waste processability, making this economic element crucial to waste management system development. The scatterplot shows the following equations:

Regression equation: y = 0.055x + 0.313

(4)

Correlation coefficient = 0.375

(5)

The positive association suggests that a greater processability relates to greater revenue potential.

4. Discussion

4.1. Optimization of the Processability System

Despite the substantial losses experienced during material separation and recycling operations, the effort is frequently well worth it. The existence of profitable separation and recycling systems can economically support this assumption. However, it should be emphasized that not all recycling enterprises are profitable. Recycling conserves energy (or exergy) and has a minor impact on the environment. These positive findings are frequently attributed to some measure of reuse potentials, such as the prospective ability to supplant virgin production or the accessible energy stored in these materials as exergy.

Systems that cannot be quantitatively characterized cannot be optimized. Thermodynamics provides the basic tools and a value system for achieving defined objectives. Several scholars have developed thermodynamic frameworks for defining recycling systems globally, primarily by analogy and at the molecular scale for specific material systems, where strict thermodynamic approaches apply [3,23,47].

Kügerl et al. (2023) emphasize the importance of incorporating responsible sourcing practices to enhance the efficiency of recycling systems [14]. By aligning processability metrics with responsible sourcing, the efficiency and sustainability in recycling can be enhanced. The aforementioned perspective is consistent with the findings of our study, which indicate that enhanced processability plays a significant role in improving resource recovery efficiency and minimizing environmental consequences. Tost et al. (2020) [21] point out that comprehending the wider environmental effects of mining and recycling necessitates taking ecosystem service prices into account. Our study supports this idea by demonstrating that enhancing the processability not only enhances financial gains but also aids in reducing the overall environmental impacts. This underscores the significance of integrating processability with ecosystem considerations to attain sustainability objectives.

Consequently, our research posits that a comprehensive strategy for optimizing recycling systems should encompass both processability enhancements and the costs of ecosystem services. This comprehensive viewpoint guarantees that recycling initiatives are both environmentally responsible and economically viable, thereby promoting the long-term sustainability of waste management.

Figure 4 illustrates systematic pathways for enhancing processability in the mining waste management sector. It highlights strategies such as increasing anthropogenic deposits, refining recycling policies, and minimizing environmental costs. This diagram supports our study’s proposal of using thermodynamic entropy as a “prototype for recycling”, aligning with our approach of optimizing processability systems through innovative recycling frameworks.

4.2. Entropy Cycling and SDG Achievement

Processability helped to achieve a circular economy by reducing waste production and boosting secondary resource recovery. Our approach is in line with SDG 12 (Responsible Consumption and Production) and SDG 13 (Climate Action), as it focuses on waste reduction and resource recovery. As highlighted by Tost et al. (2020) [21] the inclusion of ecosystem service costs is of the utmost importance in achieving sustainable development. The findings presented in our study provide evidence that implementing efficient recycling practices can play a crucial role in reducing these expenses, thereby fostering a more environmentally friendly industrial system. To achieve a “closed” material cycle, waste management must convert high-entropy wastes into low-entropy recovered resources (so-called “entropy cycling”). This study enhances sustainable development by highlighting key stages of metal recycling by utilizing the processability model. To the best of our knowledge, it is the first to assess and compare mining waste processability considering multiple sustainability aspects, i.e., environmental, social, and economic.

Our results help optimize the treatment conditions and minimize the recycling costs while maintaining the correctness of ecological aspects. The entropy approach helps us understand industrial metabolism and aids decision-making and design by quantifying complicated systems with a single metric per element. Nonetheless, our results might provide helpful policy insights for management sectors, allowing them to develop their policies to increase the processability efficiency of their waste by considering their realities.

4.3. Policy Implications and Prospects

The policy implications of our study underscore the need for improved recycling infrastructure and regulations that support responsible sourcing and sustainable waste management. By integrating principles from Kügerl et al. (2023) [14] and considering the ecosystem service costs discussed by Tost et al. (2020) [21], policymakers can enhance the recycling efficiency and reduce environmental impacts. Effective policies should focus on increasing processability through better recycling technologies, supporting research and development, and implementing regulations that encourage the use of recycled materials.

Metal recycling has some potential policy implications that could be discussed:

• Developing recycling infrastructure: Investing in recycling infrastructure boosts recycling rates and reduces landfill waste. Advanced systems like San Francisco have high diversion rates [49]. Governments should improve recycling centers and technologies.
• Supporting research and development: Research and development (R&D) investments lead to technological innovations that improve recycling processes, such as robotic sorting and chemical recycling methods. Policymakers should support R&D efforts to foster innovation in recycling technologies, as demonstrated by the European Union’s Horizon 2020 program [50].
• Implementing regulations and standards: The EU WEEE Directive and Extended Producer Responsibility programs in Japan and South Korea have significantly improved recycling rates and waste management, highlighting the importance of effective regulations and standards in promoting recycling practices [51]. Enforcing similar standards can drive further improvements in recycling practices.
• Educating the public: Public education campaigns, such as the UK’s “Recycle Now” campaign, have been proven to boost recycling participation, with household recycling rates increasing by 15% over five years [50]. Policymakers should invest in public education to enhance recycling behaviors and community engagement.
• Encouraging international cooperation: The Basel Convention and the International Resource Panel promote global best practices in recycling and resource management, promoting international cooperation to improve processes and standards worldwide, thereby facilitating the transboundary movement of hazardous wastes [51].

By addressing these policy implications, policymakers can promote sustainable metal recycling practices that conserve natural resources, reduce environmental pollution, and support economic growth.

5. Conclusions

Mining is becoming a bottleneck for the future of the Earth, and it plays a central role in the transition toward energy and recycling. This study highlights the importance of evaluating the processability of mining waste to support sustainable resource utilization. By applying thermodynamic entropy and grade metrics, we provide a comprehensive assessment of the feasibility and economic potential of recycling various types of mining waste. The processability values for various types of mining waste across different countries range from 0.19 to 1.18, indicating varying degrees of potential for resource recovery and processability efforts, with notable examples including the high processability of gold mine waste in Malaysia (0.49) and the exceptionally high processability of copper mine waste in the USA (1.18). The resource and technology index exhibits significant interdependence, influencing recycling entities’ decision-making during waste resource selection. Generally, high values of the resource index indicate that waste is important from an economic perspective and has significant potential as a resource. A higher technology index indicates that the waste is well suited for metal recovery processes compared to those with lower values, and it requires less technology investment. The significance of mining waste processability in promoting responsible sourcing practices and reducing ecosystem service costs is highlighted by our findings. This research promotes sustainable and ethical resource utilization strategies by integrating circular economy principles, thereby contributing to the achievement of global sustainability goals. The findings emphasize the need for effective recycling strategies and policies to enhance resource recovery and minimize environmental impacts. This research contributes to advancing circular economy principles and supports the achievement of sustainable development goals by improving mining waste management practices.