Environmental and closure costs in strategic mine planning, models, regulations, and policies

Academic Editor: Jun Liu Received: 23 January 2025 Revised: 19 February 2025 Accepted: 25 February 2025 Published: 27 February 2025 Citation: Oliveros-Sepúlveda, D.; Bascompta-Massanés, M.; Franco-Sepúlveda, G. Environmental and Closure Costs in Strategic Mine Planning, Models, Regulations, and Policies. Resources 2025,14, 41. https://doi.org/10.3390/ resources14030041 Copyright: © 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/ licenses/by/4.0/). Review Environmental and Closure Costs in Strategic Mine Planning, Models, Regulations, and Policies David Oliveros-Sepúlveda 1,* , Marc Bascompta-Massanés 1and Giovanni Franco-Sepúlveda 2 1Escola Politècnica Superior d’Enginyeria de Manresa, Universitat Politècnica de Catalunya, 08242 Manresa, Spain; [email protected] 2Grupo de Investigación en Planeamiento Minero–GIPLAMIN, Facultad de Minas, Universidad Nacional de Colombia, Medellín 050034, Colombia; [email protected] *Correspondence: doliver[email protected]; Tel.: +34-667521713 Abstract: This study explores the evolution of mine planning, with particular emphasis on the integration of environmental and social factors in alignment with the sustainable development. Traditionally, mine planning emphasized technical and economic variables, often overlooking environmental and social impacts. However, the increasing need to align with the Sustainable Development Goals (SDGs) has prompted a shift toward broader definitions that incorporate these factors into resource planning. This paradigm change is crucial for managing risks related to project profitability, which now include environmental considerations. The article also examines how government policies and corporate strategies, including Corporate Social Responsibility (CSR) and Environmental, Social, and Governance (ESG) frameworks have evolved to address these impacts. A review of the literature published over the last 25 years identifies four main thematic areas: (1) inclusion of environmental costs in mine planning, (2) quantitative models for calculating environmental and closure costs, (3) legal frameworks in mining, and (4) innovations in public policies. This study underscores the need for a comprehensive approach in mine planning that balances economic, social, and environmental considerations to ensure sustainability and mitigate risks associated with mine closure and environmental remediation. Keywords: environmental costs; mine planning; public policy of mining 1. Introduction Mine planning, like the mining industry as a whole, has undergone significant evolution over the past decades. It is now evident that there is a paradigm shift in the conception of a mineral deposit, aligning with SDGs established at the Rio de Janeiro Summit [ 1 ] and reaffirmed in the 2030 Agenda of the United Nations [ 2 ]. Traditionally, the classical definition of a mineral deposit focused on maximizing economic profitability by considering a limited set of technical variables that directly influenced financial indicators. These variables primarily addressed geological factors such as the genesis and morphology of mineralization, geomechanics, concentrations, and the distribution of the ore body, among others [ 3 ]. However, environmental and social factors were often overlooked or treated as externalities. The necessity of meeting the SDGs (as shown in Figure 1) and overcoming environmental and social challenges has led to new definitions that better reflect the realities of extractive and mining projects [ 4 ]. These definitions encompass not only the previously mentioned variables but also the environmental, ecological, and socio-economic factors faced by mining projects. Consequently, mineral resources and reserves are Resources 2025,14, 41 https://doi.org/10.3390/resources14030041 Resources 2025,14, 41 2 of 29 now directly influenced by these factors, which were historically considered external to technical planning. Resources 2025, 14, x FOR PEER REVIEW 2 of 30 mentioned variables but also the environmental, ecological, and socio-economic factors faced by mining projects. Consequently, mineral resources and reserves are now directly influenced by these factors, which were historically considered external to technical planning. Figure 1. SDGs. Source: Modified of UN [2]. Strategic mine planning plays a critical role in managing uncertainties associated with projects to mitigate risks in the calculations of Net Present Value (NPV) and Internal Rate of Return (IRR) [5,6]. Environmental factors carry associated risks that must be addressed in alignment with the interests and needs of the state, the mining company, and local communities [7]. Premature project termination poses a significant risk to sustainability, often resulting in higher closure costs compared to well-planned or ongoing closure efforts [8]. This underscores the importance of considering and adequately planning these activities from the project’s inception or early stages [9]. Mining companies must comply with environmental and social standards dictated by the legal frameworks of the jurisdictions where their projects are located. Governments have approached the challenge of sustainable extractive industry development through various strategies tailored to their historical, economic, and environmental contexts [10]. These strategies include taxation, centralized mining authorities, and regulatory measures to oversee the industry. Examples of such regulations include mine rehabilitation and recovery obligations, environmental compensation payments, and the procurement of mining–environmental insurance policies to cover unanticipated impacts [11]. Despite these measures, many projects encounter environmental and social challenges, necessitating the implementation or enhancement of Corporate Social Responsibility (CSR) campaigns and Environment, Social, and Governance (ESG) frameworks [12,13]. Strategic planning, particularly corporate policies adopted by mining companies, has evolved alongside the extractive sector [14]. In response to operational challenges, companies have introduced sustainability and corporate social development policies driven by corporate values and voluntary initiatives [15,16]. While international and national regulations mandate environmental and mine closure standards, many companies strive to exceed these requirements [17]. These initiatives help prevent negative impacts and potential conflicts among stakeholders (company, state, and communities) [18] or alleviate existing tensions in ongoing projects, such as disputes over land, mineral, or water use. Although environmental and social factors have been considered in operational planning, they have not been integrated directly into block models and are treated as externalities or accounting liabilities incurred at the end of a mine’s life. This approach often leads to cost overruns, as remediation efforts are generally more expensive than early Figure 1. SDGs. Source: Modified of UN [2]. Strategic mine planning plays a critical role in managing uncertainties associated with projects to mitigate risks in the calculations of Net Present Value (NPV) and Internal Rate of Return (IRR) [ 5 , 6 ]. Environmental factors carry associated risks that must be addressed in alignment with the interests and needs of the state, the mining company, and local communities [ 7 ]. Premature project termination poses a significant risk to sustainability, often resulting in higher closure costs compared to well-planned or ongoing closure efforts [ 8 ]. This underscores the importance of considering and adequately planning these activities from the project’s inception or early stages [9]. Mining companies must comply with environmental and social standards dictated by the legal frameworks of the jurisdictions where their projects are located. Governments have approached the challenge of sustainable extractive industry development through various strategies tailored to their historical, economic, and environmental contexts [ 10 ]. These strategies include taxation, centralized mining authorities, and regulatory measures to oversee the industry. Examples of such regulations include mine rehabilitation and recovery obligations, environmental compensation payments, and the procurement of mining–environmental insurance policies to cover unanticipated impacts [ 11 ]. Despite these measures, many projects encounter environmental and social challenges, necessitating the implementation or enhancement of Corporate Social Responsibility (CSR) campaigns and Environment, Social, and Governance (ESG) frameworks [12,13]. Strategic planning, particularly corporate policies adopted by mining companies, has evolved alongside the extractive sector [ 14 ]. In response to operational challenges, companies have introduced sustainability and corporate social development policies driven by corporate values and voluntary initiatives [ 15 , 16 ]. While international and national regulations mandate environmental and mine closure standards, many companies strive to exceed these requirements [ 17 ]. These initiatives help prevent negative impacts and potential conflicts among stakeholders (company, state, and communities) [ 18 ] or alleviate existing tensions in ongoing projects, such as disputes over land, mineral, or water use. Although environmental and social factors have been considered in operational planning, they have not been integrated directly into block models and are treated as externalities or accounting liabilities incurred at the end of a mine’s life. This approach often leads to cost overruns, as remediation efforts are generally more expensive than Resources 2025,14, 41 3 of 29 early mitigation [ 19 , 20 ]. Evaluating, quantifying, and incorporating impacts enables companies to anticipate the costs of repair and mitigation and provides a foundation for economically comparing the environmental and social advantages and disadvantages of mining projects [21,22]. Environmental impact assessments are mandatory for any project. However, when complemented with additional methodologies and mining designs, they can serve as essential tools for achieving a social, environmental, and economic balance. These methodologies suggest mechanisms that facilitate the implementation of control and preventive measures [ 23 , 24 ]. Identifying potential impacts in advance allows for informed decisionmaking regarding intervention strategies and opens opportunities to evaluate alternative mining methods [25,26]. Despite the mandatory nature of environmental considerations, holistic project planning remains inadequate [ 27 ]. While many studies have explored global and regional economic analyses related to mineral depletion, detailed engineering and designs for sustainable resource management require further development [ 28 , 29 ]. Incorporating these variables could not only improve environmental and social performance [ 30 ] but also yield economic and commercial benefits for companies, warranting greater attention. This study aims to review the most relevant research and contributions in this area, allowing readers to identify promising trends or strategies that can be integrated and improved by companies or governments to enhance the environmental performance of the mining sector and its operations. Using the ScienceDirect and Springer databases, key works published between 2000 and late 2024 were identified through searches using terms such as “environmental costs in mining”, “quantification of environmental costs in mining”, “mine planning and environment”, “mine planning and mine closure”, “public policies in mining”, “mine closure legislation”, and “public policies and extractive industry.” Finally, we used the ChatGPT-4 tool to improve the writing style and translation of the text. The analysis identified four main themes for a comprehensive literature review: (1) inclusion of environmental costs in mine planning, (2) quantitative models or methodologies for calculating environmental and closure costs, (3) legal frameworks for mining in selected countries, and (4) innovation in public policies adopted by specific administrations. The existing literature includes numerous studies examining the environmental or social impacts of mining activities worldwide, describing and quantifying liabilities and proposing strategies to improve environmental performance in specific processes. Examples include substituting chemical compounds with organic substances in metallurgical processes and using technologies to reduce CO 2 emissions. However, such studies are outside the scope of this review, which focuses on the inclusion of environmental and mine closure variables. Additionally, this study does not address the qualification or identification of negative mining impacts, detailed mine closure projects, or CSR initiatives in specific cases. 2. Inclusion of Environmental Costs in Mine Planning As previously mentioned, the mine planning process has also evolved to optimize environmentally friendly practices. Although research in this area is not as extensive as studies on cut-off grade optimization, the inclusion of geomechanical variables, metallurgical optimization, risk management associated with mineral prices, or geological uncertainty, among others [ 6 , 31 – 39 ], there is a growing body of work focusing on incorporating environmental, mine closure, or social factors into mine planning. Given that a significant portion of environmental costs stem directly from waste generated during mineral exploitation and processing, Osanloo et al. [ 40 ] proposed a methodology to reduce such waste by optimizing the cut-off grade for porphyry deposits. Resources 2025,14, 41 4 of 29 Adrien Rimélé et al. [ 41 ] optimized the Net Present Value (NPV) and Life of Mine (LoM), incorporating variables aimed at minimizing tailings in a copper operation. Their mathematical formulation integrated geological uncertainty and aimed to define the optimal sequence of block extraction, categorizing blocks as reserves or waste for disposal. Kumral [ 42 ] utilized Simulated Annealing to minimize the amount of tailings and waste generated in mine production plans. This mathematical model introduced flexibility in extraction rates, leveraging feedback from mined blocks to estimate waste from future blocks, enabling short-term profitability projections while meeting production requirements. Seredkin et al. [ 43 ] reformulated mineral processing techniques for certain deposits, drawing from the success of in situ recovery in uranium extraction. According to the authors, this method enhances both environmental and economic performance by eliminating the need for material removal, processing, and waste disposal, thus avoiding many conventional costs. Other studies addressed environmental concerns through unconventional planning algorithms: Adiansyah et al. [ 44 ] tackled tailing management and treatment, while [ 45 – 47 ] focused on minimizing CO 2 emissions or air pollutants. These efforts used multi-objective optimization functions for decision-making in block sequencing operations. Li et al., Ullah et al., Anderson & Razaie [ 48 – 50 ] explored alternatives to optimize projects by minimizing the production of acid mine drainage. However, these studies typically addressed specific parameters rather than providing a comprehensive integration of environmental variables. Holistic approaches to environmental factors in mining include X. C. Xu et al. [ 51 ], who proposed a detailed methodology for calculating ecological costs—accounting for over 40 parameters—associated with a polymetallic project. These costs were internalized within a 2D optimization algorithm that conducted iterative simulations to create a final 3D envelope. Adibi et al. [ 26 ] calculated ultimate pit limits (UPLs) and qualitatively evaluated environmental, social, and mine closure factors to select the pit with the best performance and economic relationship using multi-attribute decision-making techniques. Similarly, Moradi and Osanloo [ 52 ] addressed 77 sustainability indicators present in mining projects, providing a qualitative assessment that quantified and weighted each criterion. Narrei and Osanloo [ 53 ] optimized the cut-off grade using Lane’s traditional algorithm [ 54 ] while incorporating mine closure costs and potential future income from productive activities in the project area. Rahimi and Ghasemzadeh [ 55 ] employed the same algorithm but included environmental costs from various metallurgical methods. In both cases, costs were assumed rather than calculated. Assuming it is more beneficial for a company to extend the operational life of a project by extracting and processing low-grade ore, Nehring and Cheng [ 56 ] selected a 2D optimal pit with the highest NPV among calculated pushbacks. They proposed seven scenarios extending the mine life from 10 to 17 years while respecting mining and processing constraints. Closure costs were calculated for each scenario using Australia’s “Asset Retirement Obligation Estimates” methodology [ 57 ]. The study concluded that extending LoM by four years increased mineral recovery, offset closure costs, and enhanced NPV. Paricheh and Osanloo [ 58 ] modified Hutchison’s [ 59 ] approach to estimate mine closure costs, using Monte Carlo simulation and decision tree analysis to probabilistically estimate closure costs and LoM. They generated 2D block models and final pits with a 100% price occurrence probability, creating additional pits for positive price scenarios. Closure costs for these pits were calculated following X. C. Xu et al. [51]. Rahmanpour and Osanloo [ 60 ] determined several final pits and calculated their associated NPVs. Environmental performance was measured using Impact Factors (IFs)—e.g., land use, mineral recovery, alignment with local development plans—and Environmental Components (ECs)—e.g., safety, community relations, air and water quality. These fac- Resources 2025,14, 41 5 of 29 tors were analyzed through matrix methods. However, the methodology relied on expert judgment, introducing subjectivity in determining indicator magnitudes. X. Xu et al. [ 61 ] applied a case study where the selected optimal pit was associated with higher environmental costs compared to pushbacks. Factoring in restoration costs and the economic value of ecosystem services—such as land opportunity costs and carbon emissions—revealed other scenarios with superior economic outcomes. Expanding on these findings, X. Chuan Xu et al. [ 62 ] applied their methodology to a real polymetallic mine. They demonstrated that integrating calculated costs into the block model produced a scenario with 2.5% higher NPV, despite initially appearing less favorable. Notably, this research focused on block sequencing rather than ultimate pits. Jafarpour and Khatami [ 63 ] employed expert valuation systems to weigh environmental costs in mining projects. These valuations were adjusted through coefficients across seven scenarios sequenced using dynamic system-based software. However, this study did not quantify environmental costs. Meanwhile, Badakhshan et al. [ 64 ] developed a mixed-integer programming model to maximize NPV by incorporating mitigation, prevention, and compensation costs for transitioning from open-pit to block-caving mining. These costs were derived from expert input and international guidelines but lacked specific calculation methodologies. Liu et al. [ 65 ] presented an innovative perspective by incorporating mine closure planning from early project stages. They proposed designing a UPL that includes future revenues from building a small hydropower plant (SHP) within the mined-out pit. Although challenging to replicate due to unique case study characteristics, this approach offers promising alternatives for planning sustainable and productive mine closures. Table 1summarizes the reviewed studies, categorizing them by publication year, included variables (environmental or closure), and project type. Table 1. Summary table of environmental or mine closure cost research in mine planning. Reference Year Minerals Partial or Total Inclusion of Variables Parameters Included Application Environmental Costs Closure Costs Open-Pit Project Underground Project [40] 2008 Copper Partial (acid drainage) ✓ ✓ [42] 2013 Gold Partial (tailings) ✓ ✓ [44] 2014 Polymetallic Partial (tailings) ✓ ✓ [45] 2014 Coal Partial (CO2)✓ ✓ [51] 2014 Polymetallic Total ✓ ✓ ✓ [26] 2015 Copper Total ✓ ✓ [52] 2015 - Total ✓ ✓ [53] 2015 Iron Partial (tailings) ✓ ✓ [55] 2015 Copper Total ✓ ✓ [43] 2016 Uranium Partial (process) ✓ ✓ [56] 2016 Copper Total ✓ ✓ [46] 2016 Coal Partial (CO2)✓ ✓ Resources 2025,14, 41 6 of 29 Table 1. Cont. Reference Year Minerals Partial or Total Inclusion of Variables Parameters Included Application Environmental Costs Closure Costs Open-Pit Project Underground Project [58] 2017 Copper Total ✓ ✓ [60] 2017 Copper Total ✓ ✓ [61] 2017 Not specified Total ✓ ✓ [41] 2018 Not specified Partial (waste) ✓ ✓ [62] 2018 Polymetallic Total ✓ ✓ ✓ [49] 2020 Polymetallic Partial (acid drainage) ✓ ✓ [63] 2021 Copper Partial ✓ ✓ ✓ [50] 2023 Copper Partial (ESG) ✓ ✓ [64] 2024 Copper Total ✓ ✓ ✓ [65] 2024 Iron Total ✓ ✓ ✓ [47] 2024 Coal Partial (CO2)✓ ✓ The studies analyzed in this section share a common need to quantify environmental or mine closure aspects. Some employ qualitative methods, subsequently evaluated to establish indices, others use methodologies or equations to quantify costs, and some simply assume economic values to integrate them into sequencing, scheduling, or ultimate pit calculations. It is noteworthy that few studies focus on underground mining projects, and no research specifically addressing mining clusters or districts in this area was identified. In the following Section 3, the most prominent works aimed at quantifying costs associated with environmental variables in mining projects are discussed. 3. Quantitative Approaches for the Evaluation of Environmental and Mine Closure Costs In the literature on quantitative models or methodologies for calculating environmental and mine closure costs, three significant subgroups can be identified. The first subgroup comprises studies that propose equations for calculating environmental costs (primarily academic or research works). The second subgroup involves methodologies for calculating closure costs, particularly regulatory frameworks from various countries and strategies developed by private companies. The third subgroup includes methodologies that, while not directly quantifying costs, propose quantitative models to evaluate the environmental performance of mining projects through the creation of indices. For brevity and clarity, we will highlight the most relevant works and explain the most comprehensive methodology from each of these groups. The economic valuation of environmental variables has been extensively studied in engineering projects. Various methodologies exist that allow the quantification of these variables in monetary terms. From a legislative perspective, some countries have implemented regulations requiring a thorough and guided valuation of costs associated with closure and abandonment activities, as is the case in Chile, certain U.S. states, and Australia. However, considering the nature and magnitude of the impacts caused by mining projects, there remains a gap in research and information on the quantification of environmental costs specific to this field. Proper valuation of these aspects would not Resources 2025,14, 41 7 of 29 only help determine the investments required to mitigate, prevent, and remediate potential impacts [ 66 ] but could also offer new approaches to comprehensive economic evaluation and project feasibility analyses [ 67 ] and assess the profitability for a nation in pursuing projects of this nature [68]. Ex-post evaluations of case studies suggest that the closure costs calculated at the end of operations are generally higher than those incurred through progressive closures [ 69 ]. Environmental impact assessments must be integrated with these closure plans, which should also be included in mine planning throughout the entire life of the mine [ 70 , 71 ] [ 72 ]. Research has proposed methodologies for calculating rehabilitation costs in areas affected by illegal or irregular mining activities. These studies are based on the costs of individual tasks required for the proper recovery of such areas [ 73 – 75 ] and the intended future use of the recovered land. However, these methodologies fall short of anticipating impacts and advocating for progressive closures that enhance both environmental and economic performance. Geographic Information Systems (GISs) provide a valuable alternative for understanding and monitoring the outcomes of progressive closures. These systems supply information on the condition of affected areas and serve as tools for mine planning by providing area-based data that can be integrated into the planning process [ 76 , 77 ]. Furthermore, the costs associated with these systems are typically related to production rates, extraction scales, and the dimensions and areas of operations [78]. From a sustainable development perspective, it is crucial to conduct economic evaluations of productive projects planned for post-closure operations and to outline the necessary transitions [79,80]. Documented cases in some studies reveal that post-closure productive activities for open-pit coal mining projects often include agriculture (over 50% of cases), forestry projects (17% to 96%), and aquatic recreation (9% to 26%) [ 81 ]. Additionally, some researchers suggest that the highest costs are associated with open-pit operations, followed by waste dumps and industrial facilities. The lowest costs, albeit not insignificant, are those near waste dumps and pits that are indirectly affected [82]. Among the noteworthy works, Kosinskiy et al. [ 83 ] proposed a methodology for environmental economic analysis based on the loss of Gross Regional Product (GRP), including labor time lost due to negative environmental impacts. Delgado and Romero [ 84 ] analyzed environmental conflicts using an integrated method of gray clustering and entropy weighting (the IGCEW method). Field data, gathered through interviews, indicated that conflicts are more likely to arise from issues such as access to potable water, poverty, GDP per capita, and employment. The IGCEW method employs weighting functions to rank observation indices perceived by different stakeholders, making it highly applicable to the analysis of environmental conflicts. Gulley [ 85 ] addressed costs related to mercury discharge in various countries, caused either indirectly (e.g., mercury sulfide emissions from mineral deposits) or directly (e.g., illegal or small-scale metallurgical recovery methods), and calculated costs per ton for each scenario. Narrei and Ataee-pour [ 86 ] proposed the choice experiment method (based on stated preference approaches), which was used to survey individuals affected by mining operations about their perceptions of the project and the monthly costs they would be willing to bear to achieve high, medium, or low environmental, social, and economic outcomes. Five possible scenarios were presented, from which respondents had to choose one based on their perceptions. The results indicated that affected individuals believe the company should pay an additional USD 11.3 per extracted ton. Vergara et al. & Kitula [ 87 , 88 ] employed the contingent valuation method (CVM) to estimate the costs that those impacted by mining projects felt they should receive annually as compensation for lost environmental services. This method estimates the value of non-market goods by simulating a market Resources 2025,14, 41 8 of 29 through consumer surveys—in this case, the population affected by mining operations [ 89 ]. Vergara Tamayo et al. [ 87 ] found that residents were willing to receive approximately USD 1,500 annually for the implementation of the project. According to Badakhshan et al. [ 64 ], six factors influence the environmental costs of mining: the Human Development Index (HDI), mining scale, proximity to populated areas, mining type, mineral type, and the ecosystem where the project is located. By consulting experts and drawing from the authors’ experiences, they established costs per ton for open-pit and block-caving projects. Similarly, Rodríguez-Zapata et al. [ 90 ] conducted a contingent valuation using surveys among residents of a mining district with five openpit coal projects. Although this study aligns with research using contingent valuation to determine environmental costs, it stands out for focusing on a mining district or cluster rather than a single project. Gu et al. [ 91 ] proposed a methodology for calculating total environmental and ecological costs through simple summations. They argued that environmental costs result from the combined damages to an ecosystem’s functions and the restoration value of these functions. Their first measurement, the ecological footprint, links local resource demand (in this case, mineral resources) to the regenerative capacity of the soils where mining activities occur. Considering the variety of soil types and environmental impacts within a mining project, their approach incorporates impact types, soil types, and contamination levels in each area. While the aforementioned works provide valuable approaches for estimating environmental and mine closure costs, the most precise and deterministic methodologies are those proposed by X. C. Xu et al. [ 51 ] and by Chile’s National Geology and Mining Service [ 92 ]. These methodologies will be discussed in Sections 3.1 and 3.2, respectively. 3.1. Quantification Methodology for Environmental and Ecological Costs in Mining Although this methodology has not been expanded or modified by other researchers, it has been widely used by various authors to develop works related to mine planning and the economic quantification of environmental variables. The methodology proposed by X. C. Xu et al. [ 51 ] involves optimizing the design of the final pit while considering the quantification of ecological costs. The calculations used to define these costs include four main components related to the type and area of soil impacted by mining. These components are the following: (i) loss of the ecological value of direct services, (ii) loss of the ecological value of indirect services, (iii) prevention and repair costs, and (iv) ecological costs of carbon emissions due to energy consumption. The parameters suggested by X. C. Xu et al. for estimating environmental and ecological costs take the following into account: value lost from direct eco-services, Cd ; value lost from indirect eco-services, Ci ; and CO 2 emission costs, Cpr . These equations are presented in detail below, from Equation (1) to Equation (7): Vs=s v 104ρshm (1) where s is the soil retention capacity, ρs is the soil density, hm is the soil thickness minimum for cultivation, and vis the annual net income from local crop cultivation. Va=1.62 q fc cC+yscs+ydcd(2) where q is the net primary productivity, fc is the carbon (C) to (CO 2 ) mass conversion factor, cC is the cost of carbon capture and storage, ys is the forest capacity to absorb SO 2 , cs is the Resources 2025,14, 41 9 of 29 SO 2 removal and control cost, yd is the forest capacity to absorb dust, and cd is the dust removal and control cost. Vo=1.2 q co(3) where q is the net primary productivity, co is the cost f oxygen production, and 1,2 corresponds to the oxygen release factor. Vr=10 p k frcr(4) where p is the average precipitation, k is the proportion of rain causing runoff, fr is the runoff reduction coefficient caused by the forest, and cr is the cost of storing water in a reservoir. Vn=qkNPN+fpkpPp+kKPK(5) where q is the net primary productivity, kN is the nitrogen content in the soil, PN is the nitrogen fertilizer cost, fp is the phosphorus mass conversion factor to P 2 O 5 , kp is the phosphorus content in the soil, Pp is the phosphorus fertilizer cost, kK is the potassium content in the soil, and PKis the potassium fertilizer cost. The value of the total lost indirect ecological services ( Ci ) is calculated by considering the time period from soil and vegetation removal to complete restoration: Ci=Qo Po +N(Vs+Va+Vo+Vn+Vr)(6) where Qo is the ore in the pit, Po is the annual ore extracted, and N is the period from removal to soil recovery. Cpr =edfd+egfg+eebacfccC 1000 (7) where ed is the average diesel consumption per ton of material removed, fd is the carbon emission factor for diesel, eg is the average gasoline consumption per ton of material removed, fg is the carbon emission factor for gasoline, ee is the average electricity consumption per unit mass of extracted material, b is the proportion of total electricity generated from coal, ac is the amount of thermal coal required to generate one unit of electricity, fc is the carbon emission factor for coal, and cCis the cost of carbon capture and storage. To determine the total ecological costs, a simple summation of Cd , Ci , and Cpr is developed, which represents what a company should invest as compensation for direct and indirect ecosystem services and CO 2 emissions to the atmosphere. In this example, the Cd variable is not presented because it is exclusively dependent on the yields that a productive project of another type (e.g., livestock, agriculture, aquaculture, etc.) can have in the area where the project is located. This methodology does not calculate closure and abandonment costs, and therefore, the next section will present this information. 3.2. Methodology for Calculating Mine Closure Costs (Servicio Nacional de Geología y Minería Sernageomin) This regulation allows for addressing mining regulation with a strategic planning approach, sustainability, and financial guarantees that do not exist in other countries, and it also provides a point of comparison and reference for other legislations that still lack a detailed framework for calculating these guarantees. Law 20.551 [ 92 ] regulates mine closure and the associated costs. This methodology proposes a series of calculations to determine an exact value that mining projects must allocate for mine abandonment in Chile. The methodology includes the following: (i) direct closure costs, (ii) indirect closure costs, Resources 2025,14, 41 16 of 29 As for royalties and taxes, it is important to clarify that taxes can reach up to 37.5% of the total profits recorded from the projects, plus a maximum of 5% of the total recorded income [133]. 4.5. Canada While there is a legal framework governing the entire country, as in all federal or similar models, the Canadian provinces have more freedom to define their own mining and taxation policies. The Canadian Mining Certification Program establishes an integrated approach for mine closure, which involves active participation from social groups. It also requires concessionaires to present a financial guarantee ensuring funds are available to carry out closure tasks once a project is finished [133]. Tax rates in Canada depend on the province where the project takes place. For instance, in British Columbia, the total tax rate only reaches 23% based on the company’s income, there are no royalties, and everything is taxed under the income tax model [127,128]. 4.6. Spain Directive 2006/21/EC [ 134 ] establishes criteria for the closure and abandonment of hazardous mine waste deposits within the European Union. It requires mining concessionaires to submit technical reports and closure plans detailing investments to be made. National state entities approve or disapprove these plans or reach agreements with companies [ 135 ]. It is worth noting that Autonomous Communities in each region have the authority to monitor and supervise mining projects. In Catalonia, for example, the Directorate General for Energy, Mines, and Industrial Safety [ 136 ] sets the value of the bonds covering mine closure and rehabilitation of areas affected by mining [137]. In terms of taxation, Spain does not have a royalty payment policy. All mining companies must pay the Corporate Tax, which taxes company profits at 25%, and a VAT (21%). Additionally, Autonomous Communities can decide whether to charge an extra tax on mining activities. In Catalonia, for instance, this surcharge is between 1% and 3% of the mineral sales, making the total tax burden approximately 48% [138]. 4.7. Sweden In Sweden, the Mineral Ordinance [ 139 ] focuses on risk management and a rigorous follow-up to ensure compliance with requirements for mine restoration and closure. Mining companies must make a bond payment at the start of the project, which is agreed upon between the company, the state, and impacted communities. This bond must cover the total cost of remediation and mine closure tasks. It is important to mention that the state receives and manages these resources. Regarding the fiscal burden of mining projects, it is necessary to clarify that there are no royalties, and from a tax perspective, mining is considered just another business. However, tax rates in Scandinavian countries are among the highest in the OECD [ 140 ], with Sweden’s tax rate at 29%. The only additional fee mining companies pay is 0.02% of total sales, which is allocated to a fund for mining research, innovation, and compensation for landowners affected by the project [141]. 4.8. Australia As in the United States, Australia delegates the responsibility for legislating and regulating mine closure to each of its states. Two prominent regulatory frameworks are those of Western Australia (WA) [ 142 ] and Queensland [ 143 ]. In WA, a cost calculator is used to estimate the responsibility and annual levy payable into the WA Mine Rehabilitation Fund. In Queensland, another cost calculator was developed to determine the basis for the Resources 2025,14, 41 17 of 29 financial guarantee to be paid. The literature includes studies using both calculators for the same case, finding similar calculated amounts [80]. Likewise, the total tax burdens for mining projects depend on the state where the project takes place. In Northern Territory, for example, a constant rate of 18% is paid as royalty, while in other states, it varies depending on commodity value, type, and amount extracted. In Western Australia, it can reach a maximum of 52% of total income [127,128]. As mentioned, while there is common concern for mine rehabilitation and closure, some regulatory frameworks are more rigorous in determining costs related to this process. This not only increases the environmental risks associated with the projects but also suggests that social pressures may increase in the future due to lax regulations that do not promote early or correct investment in environmental impact control [ 144 ]. On the other hand, having legal methodologies for calculating environmental costs helps reduce the approval or denial times of permits for the implementation of projects. When clear and concise guidelines are established for evaluating closure plans and their costs, it is possible to eliminate bureaucratic negotiation processes between state entities and companies. Table 2below summarizes the fiscal burden, closure cost methodologies used in each country, and whether royalties are paid as a result of mineral exploitation. It also mentions the level of governmental centralization in the mining sector in each country. Table 2. Comparative table of methodologies to calculate closure costs, tax burden, royalty payments, and level of centralization of the mining sector. Country Law Methodology for Calculating Closure Costs Maximum Tax Burden Royalties Payment Management Level Chile Ley 20.551, 2014 ✓47% ✓Central Peru Ley N◦28090, 2003 exttimes 35% ✓Central Colombia Ley 685, 2001 exttimes 70% ✓Central Bolivia Ley Minería y Metalurgia, 2014 exttimes 43% ✓Central Canada (BC) * RSBC, 1996 exttimes 23% exttimes Federal Spain (Cat) * Decret Legislatiu 14/1994 exttimes 48% exttimes Autonomous ** Sweden Mineral Ordinance, 1992 exttimes 29% exttimes State domain Australia (WA) * Mining Act, 978 ✓52% ✓State domain * BC: British Columbia; Cat: Catalonia; WA: Western Australia; ** Autonomous corresponds to Autonomous Community (CCAA), equivalent at the state level. 5. Innovation in Public Policies Adopted by Some Governments In recent years, the extractive sector has posed one of the greatest challenges in terms of public policy for countries that generate part of their fiscal revenue from the development of this activity. The growing demand for mineral resources, driven by the transition to renewable energy, technological development, and demographic growth, has intensified the need for innovative public policies that integrate sustainability into mining practices [145,146]. Beyond the commitments made by companies to achieve environmentally friendly and socially sustainable projects, the responsibility for ensuring a sustainable mining sector falls on the states, as they are the ones responsible for setting the rules of the game [ 147 ]. Many of the objectives established in international climate agreements (signed by countries) aim at stricter industrial activity regulations, including the mining sector [ 148 ]. Although countries are part of these treaties, it is common for them not to modify their regulations, Resources 2025,14, 41 18 of 29 often maintaining a more extractive approach that moves away from sustainability [ 149 , 150 ]. As a result, research efforts have focused on the development of subnational or local policies that allow for the design of tailored strategies depending on the characteristics and needs of each territory [ 151 ]. Some countries have opted to restrict mining projects in specific areas to preserve and conserve ecosystems, such as the cases of Argentina and Chile with glaciers or Colombia with páramos [ 152 ]. However, such decisions are sometimes driven more by political motivations than by technical or scientific foundations. Traditional regulatory approaches have often been insufficient to address the complexity of current challenges, leading to a search for adaptive and participatory models [ 68 ]. The implementation of clean technologies and the adoption of responsible mining practices require regulatory frameworks that integrate environmental and social criteria from planning to execution [ 153 ]. Innovation in public policies can provide more flexible regulatory frameworks that facilitate the implementation of these technologies and practices necessary to achieve better economic, social, and environmental outcomes. Based on the definition of sustainable development, it is essential to have active community participation in decision-making for economic growth in their territories [ 154 ]. This may present challenges due to the lack of technical knowledge in certain areas, especially in rural areas with conditions such as limited access to education, healthcare, and employment opportunities [ 146 , 155 ]. Despite this, as [ 156 ] suggest in their case study in Poland, urban or rural zoning tools and planning instruments can serve as a starting point for residents to directly influence future land use before and after mining projects. In these cases, achieving collaborative development among all stakeholders requires starting from principles of reciprocity [13]. One of the most successful cases documented is in northern Finland, where, as a solution to the question of socially responsible mining, social management plans (SIMPs) have been proposed, in which communities actively participate in decision-making and collaborative planning of the mining project. Involved companies can learn to understand the issues that may generate social conflicts if not addressed, local administrations can use them to plan services and infrastructure, and local residents can use them as a channel to express their interests and ideas [ 157 ]. The SIMP was successful in Finland and was established as a public policy for mining activities that are in the feasibility stages in the country. However, in other parts of the world, new environmental conflicts persist, where there are no agreements between communities and companies on how to achieve sustainable project development [158]. Part of the strategies employed by public administrations focus on incentives and disincentives for the development of mining projects. This can be a double-edged sword, as increasing the fiscal burden could deter investment in the sector (especially harmful for commodity-dependent countries) [ 159 ], while decreasing it may result in diminished governance credibility and increased risks of environmental and community pressures in case production levels rise and auditing institutions are unprepared [ 155 ]. The tax issue remains complex, not only due to the revenue models (whether a royalty model exists, taxes are levied on income or profits, etc.) [ 160 ], but also because of its redistribution across different levels of public administration and society. In China, for example, a fiscal policy change was implemented in 2017, which, in addition to giving local administrations greater involvement in revenue collection, introduced a reform on mining company taxation with ad valorem taxes and automatic fiscal adjustment mechanisms [ 161 ]. In 2017, another proposed change in the Chinese government was the implementation of the “Action Plan for Soil Pollution Prevention and Control” (APSPPC), which introduced punitive measures, not only economically through fines but also by affecting companies’ credit reports and lowering their credit ratings for non-compliance with regulations [ 162 ], representing signif- Resources 2025,14, 41 19 of 29 icant pressure for mining companies, especially those listed on the stock exchange or on the verge of obtaining loans. In addition to the challenges posed by sustainable mining development in recent years, new issues have emerged that were not previously addressed. Pepper et al. [ 163 ] examine public policies governing the care and maintenance of mines that have not yet closed but had to temporarily suspend operations due to exogenous factors like market conditions. If they have not closed but are not in the production stage, how is sustainability guaranteed during this period? They identify legal gaps [ 164 ] and suggest possible solutions, such as requiring progressive closures and periodically recalculating closure bonds and guarantees considering already closed areas, environmental performance indicators, and the companies’ economic performance. The increase in technological capabilities and the rise of technocratic models have become essential for better understanding projects, conducting proper monitoring, and negotiating project terms. Public administrations’ adoption of new technologies and tools enables more accurate data and figures necessary for decision-making and tax imposition [ 165 ]. The use of drones to assess stocks, progress, and the size of rehabilitated and intervened areas may be a good option [ 166 ]; however, it requires significant investment in equipment acquisition and professional training. Despite the high costs, studies suggest that stronger institutional capacity is crucial for building credibility, enhancing environmental performance, and ensuring effective tax collection and reinvestment from companies [ 167 ]. This could also be a key factor in avoiding or falling into economic problems like the “resource curse” [ 168 ]. Policies like those outlined in the previous section (Section 4) in countries such as Sweden or Colombia are important for promoting best practices in the extractive industry, especially in mining, where a small percentage of fiscal revenues is reinvested in science, technology, and innovation for the mining sector, fostering increased interest and tools for environmental optimization and more environmentally friendly processes within the industry [10]. Vertical integration and the decentralization of entities responsible for overseeing, controlling, collecting, and sanctioning the mining industry are additional factors that correlate with better sustainable mining practices [ 169 ]. Numerous studies have focused on deepening the relationship between governance models in which local or state authorities play an active role and better environmental outcomes in mining territories (districts, states, autonomous communities, departments, etc.) [ 170 – 178 ]. These studies demonstrate that decentralizing financial powers and giving local governments (environmental and mining authorities) a more prominent role can positively impact local economic development and control the primary risks faced by territories due to mining activities [ 179 , 180 ]. The implementation of mixed governance models that employ technocracy and agency models may be an important step for nations still lagging behind centralized models [ 181 ]. However, research on such organizational reforms in public institutions is scarce and outdated, and there is also a lack of political will to implement them. Toward Global Approaches? The mining industry stands at a sustainability crossroads, where it must balance the enhancement of social and environmental outcomes with the economic viability of projects, all within a unified regulatory and methodological framework [ 182 ]. While previous research has highlighted the complexity of designing a universally accepted method for quantifying environmental and closure costs in mining, the question remains whether a consensus can be reached to standardize these calculations [ 183 ]. Public sector initiatives across various countries demonstrate that regulatory advancements and adaptive governance are converging toward similar objectives [ 184 ]; however, significant disparities Resources 2025,14, 41 20 of 29 persist among nations with varying degrees of economic dependence on mining and differing social contexts [185,186]. One of the main challenges in developing a universal model lies in the heterogeneity of mining operations worldwide. Geological conditions, extraction technologies, regulatory frameworks, and socio-economic contexts vary significantly across regions, making the establishment of a one-size-fits-all methodology impractical [ 187 ]. Nevertheless, efforts to harmonize environmental impact assessments and closure cost calculations are gaining momentum, particularly through international standards and the creation of financial assurance mechanisms in countries with mature and developed mining sectors [ 188 ]. These examples suggest that while full standardization may not be feasible, a structured framework with adaptable parameters could help bridge the gap between local regulations and global best practices [189]. From a public policy perspective, achieving consensus within the industry requires not only regulatory alignment but also financial and technological incentives that promote the adoption of sustainable practices by companies. Integrating environmental costs into financial models—through risk-adjusted project valuations and progressive closure bonds— could serve as a stepping stone toward broader acceptance of sustainability-driven mine planning [ 190 ]. In this regard, governments play a critical role in facilitating collaboration among industry stakeholders, enforcing stricter environmental accountability, and funding research to improve cost estimation methodologies. Moreover, the role of countries that demand these raw materials is equally crucial, as downstream industries can drive responsible sourcing decisions by prioritizing suppliers that meet high sustainability standards [191]. The feasibility of a universally accepted approach also hinges on the political will of nations to prioritize long-term environmental stewardship over short-term economic gains [ 192 ]. While some countries have adopted decentralized governance models to enhance oversight and public participation, others continue to operate under extractivist policies that hinder sustainable transitions [ 185 ]. Lessons from Finland’s Social Impact Management Plans (SIMPs) illustrate how participatory governance can mitigate conflicts and establish more resilient regulatory frameworks, potentially serving as a reference for broader adoption in other regions [ 12 ]. Although a fully standardized global methodology for calculating environmental and closure costs in mining may remain an elusive goal, progress can be achieved through incremental regulatory convergence, cross-border collaboration, and the adoption of flexible yet comprehensive frameworks. The future of the mining industry, from a public policy perspective, will depend on the ability of states to balance resource exploitation with sustainability imperatives, ensuring that mining activities contribute to economic development without compromising environmental and social well-being. 6. Conclusions The evolution of mine planning has led to a holistic approach that not only considers economic profitability but also environmental and social aspects, aligning with the SDGs. In response to the growing demand for sustainable processes, strategic planning has become an essential tool to mitigate risks associated with negative impacts and ensure the longterm viability of projects. The inclusion of environmental costs and the implementation of Corporate Social Responsibility policies are crucial to balancing the interests of businesses, communities, and governments. Despite progress, gaps in holistic planning persist, highlighting the need to effectively incorporate environmental variables into mining models and strengthen regulation and public policies to achieve truly sustainable development in the sector. Resources 2025,14, 41 21 of 29 While most research has focused on maximizing traditional economic indicators, such as Net Present Value (NPV) and cut-off grades, methodologies that incorporate environmental and mine closure costs into optimization algorithms are being explored [58,63] . This approach not only mitigates the negative impact of mining activities but also improves long-term profitability by considering sustainability from the early stages of the project. As the industry moves toward more responsible practices, it is essential to continue developing and implementing strategies that comprehensively assess the costs and benefits associated with mining, ensuring a more balanced development that benefits businesses, communities, and the environment. There are quantitative methodologies applied in mining to calculate environmental and closure costs, with three main approaches standing out: equations for environmental costs, regulatory frameworks for closure costs, and environmental performance evaluation models. While regulatory frameworks exist in countries like Chile, the U.S., and Australia, methodologies for quantifying environmental costs in mining remain limited. Proper valuation could improve the profitability and sustainability of these projects. Additionally, methodologies such as Geographic Information Systems (GISs) for monitoring progressive closures and multi-criteria methods like AHP and TOPSIS are useful for creating sustainability indices. More comprehensive models include the quantification of ecological impacts, considering the loss of environmental services and carbon emissions, along with specific methodologies, such as the Chilean SERNAGEOMIN regulations, which calculate closure costs based on reference rates and correction factors. These methodologies are crucial for responsible mining and for making informed decisions about the costs derived from environmental impacts and the economic sustainability of mining operations. While there is no international standard for mine closure, countries like Chile and Australia have advanced legislation that requires financial guarantees and calculation methodologies to ensure the environmental and social restoration of affected areas. The experiences of countries such as Canada, Sweden, and Australia highlight the value of clear regulations that allow for greater collaboration between governments, businesses, and communities to mitigate environmental impacts and facilitate the transition of land use in mining-affected areas. As evidenced in this review, in addition to many research studies or methodologies originating from these countries, the EJAtlas—Global Atlas of Environmental Justice [ 193 ] records show a higher concentration of conflicts in countries with lax or unclear legislation. The comparison suggests that stricter regulations not only benefit the environment and communities but also reduce the risk of social conflicts by ensuring that companies assume financial responsibility from the early stages of the project. Differences in fiscal burdens and royalty policies reflect the diversity of approaches to sustainability in mining. However, it is evident that having well-defined closure costs and methodologies improves the permitting process, the economic evaluation of projects by state entities, and transparency in the mining sector, promoting a balance between economic development and environmental responsibility. Innovation in public policies for the extractive sector is crucial to addressing contemporary challenges related to environmental and social sustainability. With the growing demand for mineral resources, countries must adopt more stringent legal approaches while being flexible and participatory in processes involving local communities in decisionmaking. The implementation of regulatory frameworks that integrate environmental and social criteria from planning to execution is key to achieving sustainable development. Successful cases, such as the social management model in Finland, demonstrate that community participation can reduce conflicts and foster more harmonious development. However, the challenge of balancing fiscal incentives and disincentives, along with the need for technological capacities and institutional robustness, highlights the complexity Resources 2025,14, 41 22 of 29 of governance in the mining sector. To avoid falling into the resource curse, it is essential for states to modernize and innovate their regulatory frameworks, prioritize decentralization, and promote reinvestment in science and technology, ensuring the responsible and sustainable management of mineral resources. Author Contributions: Conceptualization, D.O.-S.; methodology, D.O.-S.; investigation, D.O.-S.; resources, M.B.-M. and G.F.-S.; writing—original draft preparation, D.O.-S.; review and editing, M.B.-M. and G.F.-S.; visualization, D.O.-S.; supervision, M.B.-M. and G.F.-S.; project administration, G.F.-S.; funding acquisition, D.O.-S. All authors have read and agreed to the published version of the manuscript. Funding: This work was funded by resources from the Ministry of Science, Technology, and Innovation of Colombia and by the Francisco José de Caldas Fund, within the framework of “Convocatoria 937—Investigación Fundamental” for the year 2023. Acknowledgments: The authors acknowledge the use of ChatGPT for assisting in language editing and translation to improve the clarity and readability of the manuscript. Conflicts of Interest: The authors declare no conflicts of interest. References 1. ONU. Informe de la Conferencia de las Naciones Unidas Sobre el Medio Ambiente y el Desarrollo: Rio de Janeiro, 3 a 14 de Junio de 1992, Organización de las Naciones Unidas; Naciones Unidas: Rio de Janeiro, Brasil, 1993. 2. ONU. La Agenda 2030 y los Objetivos de Desarrollo Sostenible: Una Oportunidad para América Latina y el Caribe. Organización de las Naciones Unidas. 2018. [En línea]. Available online: https://repositorio.cepal.org/server/api/core/bitstreams/cb30a4de-7d874e79-8e7a-ad5279038718/content (accessed on 16 September 2024). 3. Oyarzún, J.; Oyarzún, R. Léxico de Geología Económica: Términos de uso Común en España e Iberoamérica, 1.ª ed. La Serena, Chile: GEMM—Aula2puntonet. 2014. [En línea]. Available online: https://www.aulados.net/Libros_Aula2puntonet_GEMM/ Libro_Lexico_Geologia_Economica.pdf (accessed on 16 September 2024). 4. Tost, M.; Hitch, M.; Chandurkar, V.; Moser, P.; Feiel, S. The state of environmental sustainability considerations in mining. J. Clean. Prod. 2018,182, 969–977. [CrossRef] 5. Franco, S.G.; Jaramillo, A.P.; Branch, B.J. Stochastic optimization in mine planning scheduling. Comput. Oper. Res. 2020, 115, 104823. [CrossRef] 6. Lamghari, A.; Dimitrakopoulos, R. Network-flow based algorithms for scheduling production in multi-processor open-pit mines accounting for metal uncertainty. Eur. J. Oper. Res. 2016,250, 273–290. [CrossRef] 7. Eerola, T.; Komnitsas, K. Preliminary Assessment of Social License to Operate (SLO) and Corporate Communication in Four European Lithium Projects. Mater. Proc. 2023,15, 35. [CrossRef] 8. Laurence, D. Establishing a sustainable mining operation: An overview. J. Clean. Prod. 2011,19, 278–284. [CrossRef] 9. Lyytimäki, J.; Peltonen, L. Mining through controversies: Public perceptions and the legitimacy of a planned gold mine near a tourist destination. Land Use Policy 2016,54, 479–486. [CrossRef] 10. Bashir, M.A.; Qing, L.; Syed, Q.R.; Barwi´nska-Małajowicz, A.; Hashmi, S.M. Resources policy from extraction to innovation: The interplay of minerals, geothermal energy, technological advancements, and ecological footprint in high-ecological footprint economies. Resour. Policy 2024,95, 105182. [CrossRef] 11. Murguía, D.I.; Bastida, A.E. The elephant in the mine: Why voluntary sustainability standards are insufficient to ensure responsible mining. Extr. Ind. Soc. 2024,19, 101485. [CrossRef] 12. Tuulentie, S.; Halseth, G.; Kietäväinen, A.; Ryser, L.; Similä, J. Local community participation in mining in Finnish Lapland and Northern British Columbia, Canada—Practical applications of CSR and SLO. Resour. Policy 2019,61, 99–107. [CrossRef] 13. Baba, S.; Mohammad, S.; Young, C. Managing project sustainability in the extractive industries: Towards a reciprocity framework for community engagement: Managing Project Sustainability in the Extractive Industries. Int. J. Proj. Manag. 2021,39, 887–901. [CrossRef] 14. Bascompta, M.; Sanmiquel, L.; Vintró, C.; Yousefian, M. Corporate Social Responsibility Index for Mine Sites. Sustainability 2022, 14, 13570. [CrossRef] 15. Murguía, D.I.; Böhling, K. Sustainability reporting on large-scale mining conflicts: The case of Bajo de la Alumbrera, Argentina. J. Clean. Prod. 2013,41, 202–209. [CrossRef] Resources 2025,14, 41 23 of 29 16. Wagner, M.; Wellmer, F.W. A Hierarchy of Natural Resources with Respect to Sustainable Development—A Basis for a Natural Resources Efficiency Indicator. In Mining, Society, and a Sustainable World; Richards, J., Ed.; Springer: Berlin/Heidelberg, Germany, 2009. [CrossRef] 17. Isacowitz, J.J.; Schmeidl, S.; Tabelin, C. The operationalisation of Corporate Social Responsibility (CSR) in a mining context. Resour. Policy 2022,79, 103012. [CrossRef] 18. Garcia-Zavala, C.; Ordens, C.M.; Pagliero, L.; Lèbre, É.; Aitken, D.; Stringer, M. An approach for prioritising environmental, social and governance (ESG) water-related risks for the mining industry: The case of Chile. Extr. Ind. Soc. 2023,14, 101259. [CrossRef] 19. Borregaard, N. Valorización económica de los impactos ambientales en la minería Chilena. Ambiente Desarro. 2001,XVII, 50–58. 20. Moran, R. Aproximaciones al costo económico de impactos ambientales en la minería. Ambiente Desarro. 2001,17, 59–66. 21. Juan David, O.; Francisco, C. VALORACIÓN ECONÓMICA DE COSTOS AMBIENTALES: MARCO CONCEPTUAL Y MÉTODOS DE ESTIMACIÓN. Semest. Económico 2004,7, 159–193. 22. Ouoba, Y. Gold companies and local economic sustainability: The case of Kalsaka Mining SA in Burkina Faso. J. Environ. Econ. Policy 2023,12, 79–95. [CrossRef] 23. Moia, G.C.M.; Matlaba, V.J.; dos Santos, J.F. Evaluation of the impact of mining royalties on socio-environmental indicators in Parauapebas, Pará, the Eastern Amazon. Extr. Ind. Soc. 2024,19, 101512. [CrossRef] 24. Andía Valencia, W. Los Estudios de Impacto Ambiental y su Implicancia en las Inversiones de los Proyectos. Prod. Gest. 2012,15, 17–20. 25. Galo, D.d.B.; dos Anjos, J.Â.S.A.; Sánchez, L.E. Are mining companies mature for mine closure? An approach for evaluating preparedness. Resour. Policy 2022,78, 102919. [CrossRef] 26. Adibi, N.; Ataee-Pour, M.; Rahmanpour, M. Integration of sustainable development concepts in open pit mine design. J. Clean. Prod. 2015,108, 1037–1049. [CrossRef] 27. Vymazal, J.; Sklenicka, P. Restoration of areas affected by mining. Ecol. Eng. 2012,43, 1–4. [CrossRef] 28. Laurence, D. Optimisation of the mine closure process. J. Clean. Prod. 2006,14, 285–298. [CrossRef] 29. Mancini, L.; Sala, S. Social impact assessment in the mining sector: Review and comparison of indicators frameworks. Resour. Policy 2018,57, 98–111. [CrossRef] 30. Sheveleva, O.; Slesarenko, E.; Kudrevatykh, N.; Mamzina, T. The unity of the trajectory of sustainable development of the mining region and ensuring its environmental safety. In E3S Web of Conferences; EDP Sciences: Essonne, France, 2019. [CrossRef] 31. Espinoza, R.D.; Rojo, J. Towards sustainable mining (Part I): Valuing investment opportunities in the mining sector. Resour. Policy 2017,52, 7–18. [CrossRef] 32. Upadhyay, S.P.; Askari-Nasab, H. Simulation and optimization approach for uncertainty-based short-term planning in open pit mines. Int. J. Min. Sci. Technol. 2018,28, 153–166. [CrossRef] 33. Del Castillo, M.F.; Dimitrakopoulos, R. Dynamically optimizing the strategic plan of mining complexes under supply uncertainty. Resour. Policy 2019,60, 83–93. [CrossRef] 34. Armstrong, M.; Lagos, T.; Emery, X.; Homem-de-Mello, T.; Lagos, G.; Sauré, D. Adaptive open-pit mining planning under geological uncertainty. Resour. Policy 2021,72, 102086. [CrossRef] 35. Jélvez, E.; Morales, N.; Nancel-Penard, P.; Cornillier, F. A new hybrid heuristic algorithm for the Precedence Constrained Production Scheduling Problem: A mining application. Omega 2020,94, 102046. [CrossRef] 36. Gilani, S.-O.; Sattarvand, J.; Hajihassani, M.; Abdullah, S.S. A stochastic particle swarm based model for long term production planning of open pit mines considering the geological uncertainty. Resour. Policy 2020,68, 101738. [CrossRef] 37. Morales, N.; Mancilla, D.; Miranda, R.; Vallejos, J. A fast method to develop an optimal operational sublevel stope design. Resour. Policy 2022,77, 102670. [CrossRef] 38. Tabesh, M.; Moradi Afrapoli, A.; Askari-Nasab, H. A two-stage simultaneous optimization of NPV and throughput in production planning of open pit mines. Resour. Policy 2023,80, 103167. [CrossRef] 39. Yaakoubi, Y.; Dimitrakopoulos, R. Decision-focused neural adaptive search and diving for optimizing mining complexes. Eur. J. Oper. Res. 2024,320, 699–719. [CrossRef] 40. Osanloo, M.; Rashidinejad, F.; Rezai, B. Incorporating environmental issues into optimum cut-off grades modeling at porphyry copper deposits. Resour. Policy 2008,33, 222–229. [CrossRef] 41. Rimélé, M.A.; Dimitrakopoulos, R.; Gamache, M. A stochastic optimization method with in-pit waste and tailings disposal for open pit life-of-mine production planning. Resour. Policy 2018,57, 112–121. [CrossRef] 42. Kumral, M. Optimizing ore-waste discrimination and block sequencing through simulated annealing. Appl. Soft Comput. J. 2013, 13, 3737–3744. [CrossRef] 43. Seredkin, M.; Zabolotsky, A.; Jeffress, G. In situ recovery, an alternative to conventional methods of mining: Exploration, resource estimation, environmental issues, project evaluation and economics. Ore Geol. Rev. 2016,79, 500–514. [CrossRef] 44. Adiansyah, J.S.; Rosano, M.; Vink, S.; Keir, G. A framework for a sustainable approach to mine tailings management: Disposal strategies. J. Clean. Prod. 2015,108, 1050–1062. [CrossRef] Resources 2025,14, 41 24 of 29 45. Canales-Bustos, L.; Santibañez-González, E.; Candia-Véjar, A. A multi-objective optimization model for the design of an effective decarbonized supply chain in mining. Int. J. Prod. Econ. 2017,193, 449–464. [CrossRef] 46. Yu, S.; Zheng, S.; Gao, S.; Yang, J. A multi-objective decision model for investment in energy savings and emission reductions in coal mining. Eur. J. Oper. Res. 2017,260, 335–347. [CrossRef] 47. Mirzehi, M.; Moradi Afrapoli, A. A novel framework for integrating environmental costs and carbon pricing in open-pit mine plans: Towards sustainable and green mining. J. Clean. Prod. 2024,468. [CrossRef] 48. Li, L.; Lei, Y.; Wu, S.; He, C.; Yan, D. Study on the coordinated development of economy, environment and resource in coal-based areas in Shanxi Province in China: Based on the multi-objective optimization model. Resour. Policy 2018,55, 80–86. [CrossRef] 49. Rezaie, B.; Anderson, A. Sustainable resolutions for environmental threat of the acid mine drainage. Sci. Total Environ. 2020, 717, 137211. [CrossRef] 50. Ullah, G.M.W.; Nehring, M.; Kizil, M.; Knights, P. Environmental, Social, and Governance Considerations in Production Scheduling Optimisation for Sublevel Stoping Mining Operations: A Review of Relevant Works and Future Directions. Min. Metall. Explor. 2023,40, 2167–2182. [CrossRef] 51. Xu, X.C.; Gu, X.W.; Wang, Q.; Liu, J.P.; Wang, J. Ultimate pit optimization with ecological cost for open pit metal mines. Trans. Nonferrous Met. Soc. China Engl. Ed. 2014,24, 1531–1537. [CrossRef] 52. Moradi, G.; Osanloo, M. Prioritizing Sustainable Development Criteria Affecting Open Pit Mine Design: A Mathematical Model. Procedia Earth Planet. Sci. 2015,15, 813–820. [CrossRef] 53. Narrei, S.; Osanloo, M. Optimum cut-off grade’s calculation in open pit mines with regard to reducing the undesirable environmental impacts. Int. J. Min. Reclam. Environ. 2015,29, 226–242. [CrossRef] 54. Lane, K. Choosing the optimum cut-off grade. In Choosing the Optimum Cut-Off Grade; Colorado School of Mines: Golden, CO, USA, 1964; pp. 5–492. 55. Rahimi, E.; Ghasemzadeh, H. A new algorithm to determine optimum cut-off grades considering technical, economical, environmental and social aspects. Resour. Policy 2015,46, 51–63. [CrossRef] 56. Nehring, M.; Cheng, X. An investigation into the impact of mine closure and its associated cost on life of mine planning and resource recovery. J. Clean. Prod. 2016,127, 228–239. [CrossRef] 57. Environmental Protection Authority and Department of Mines and Petroleum (EPA/DMP). Guidelines for Preparing Mine Closure Plans; Government of Western Australia: Perth, Australia, 2011. 58. Paricheh, M.; Osanloo, M. A simulation-based framework for estimating probable open-pit mine closure time and cost. J. Clean. Prod. 2017,167, 337–345. [CrossRef] 59. Hutchison, I.; Dettore, R. Statistical and probabilistic closure cost estimating. In Proceedings of the 15th International Conference on Tailings and Mine Waste, Vancouver, BC, Canada, 9 November 2011; University of British Columbia Institute of Mining Engineering: Vancouver, BC, Canada, 2011. 60. Rahmanpour, M.; Osanloo, M. A decision support system for determination of a sustainable pit limit. J. Clean. Prod. 2017,141, 1249–1258. [CrossRef] 61. Xu, X.; Guo, X.; Wang, Q.; Liu, J.; Zhu, Q. Production Scheduling of Open Pit Metal Mine with Ecological Cost. Geo-Resour. Environ. Eng. 2017,2, 59–63. [CrossRef] 62. Xu, X.C.; Cu, X.; Wang, Q.; Gao, X.; Liu, J.; Wang, Z.; Wang, X. Production scheduling optimization considering ecological costs for open pit metal mines. J. Clean. Prod. 2018,180, 210–221. [CrossRef] 63. Jafarpour, A.; Khatami, S. Analysis of Environmental Costs’ Effect in Green Mining Strategy Using a System Dynamics Approach: A Case Study. Math. Probl. Eng. 2021,18. [CrossRef] 64. Badakhshan, N.; Shahriar, K.; Afraei, S.; Bakhtavar, E. Optimization of transition from open-pit to underground mining considering environmental costs. Resour. Policy 2024,95, 105178. [CrossRef] 65. Liu, F.; Yang, K.; Yang, T.; Deng, W.; Li, H.; Yang, L. Open pit limit optimization considering the pumped storage benefit after mine closure: A case study. Geomech. Geophys. Geo-Energy Geo-Resour. 2024,10, 44. [CrossRef] 66. Oblasser, A.; Chaparro, E. Estudio comparativo de la gestión de los pasivos ambientales mineros en Bolivia, Chile, Perú y Estados Unidos. Arbor 2008,17, 3. [CrossRef] 67. Martinez-Alier, J. Mining conflicts, environmental justice, and valuation. J. Hazard. Mater. 2001,86, 153–170. [CrossRef] 68. Vela-Almeida, D. Territorial partitions, the production of mining territory and the building of a post-neoliberal and plurinational state in Ecuador. Polit. Geogr. 2018,62, 126–136. [CrossRef] 69. Getty, R.; Morrison-Saunders, A. Evaluating the effectiveness of integrating the environmental impact assessment and mine closure planning processes. Environ. Impact Assess. Rev. 2020,82, 106366. [CrossRef] 70. Gała´s, S.; Gała´s, A. The qualification process of mining projects in environmental impact assessment: Criteria and thresholds. Resour. Policy 2016,49, 204–212. [CrossRef] 71. Lechner, A.M.; Baumgartl, T.; Matthew, P.; Glenn, V. The Impact of Underground Longwall Mining on Prime Agricultural Land: A Review and Research Agenda. Land Degrad. Dev. 2016,27, 1650–1663. [CrossRef] Resources 2025,14, 41 25 of 29 72. McCullough, C.D.; Harvey, B.; Unger, C.J.; Winchester, S.; McCarthy, B.; Coetzee, J. From start to finish—A perspective on improving sustainable development aspects of life-of-mine practices. In From Start to Finish: Life of Mine Perspective, Spectrum 24; AusIMM: Carlton Victoria, Australia, 2018. 73. Centro de Investigación y Desarrollo—PUCESE. Economic Valuation of the Environmental Assessments of Gold Mining Activity in the North of Ecuador; Ministerio del Ambiente: Esmeraldas, Ecuador, 2011. [CrossRef] 74. Yupari, A. Pasivos Ambientales Mineros en Sudamérica; Report prepared for the CEPAL; Instituto Federal de Geociencias y Recursos Naturales—BGR and Servicio Nacional de Geología y Minería—SERNAGEOMIN: Santiago de Chile, Chile, 2003. 75. Arango Aramburo, M. Requerimientos Para el Diseño de una Metodología que Permita Estimar el Valor de Pasivos Ambientales Mineros; Universidad Nacional de Colombia: Bogotá, Colombia, 2011. Available online: https://repositorio.unal.edu.co/bitstream/ handle/unal/8766/43869159.2011.pdf?sequence=1&isAllowed=y (accessed on 9 October 2024). 76. Liao, X.; Li, W.; Hou, J. Application of GIS Based Ecological Vulnerability Evaluation in Environmental Impact Assessment of Master Plan of Coal Mining Area. Procedia Environ. Sci. 2013,18, 271–276. [CrossRef] 77. Wu, Z.; Lei, S.; Lu, Q.; Bian, Z.; Ge, S. Spatial distribution of the impact of surface mining on the landscape ecological health of semi-arid grasslands. Ecol. Indic. 2020,111, 105996. [CrossRef] 78. Glaister, B.J.; Mudd, G.M. The environmental costs of platinum-PGM mining and sustainability: Is the glass half-full or halfempty? Miner. Eng. 2010,23, 438–450. [CrossRef] 79. Pietrzyk-Sokulska, E.; Uberman, R.; Kulczycka, J. Minería e impactos ambientales en Polonia. Gospod. Surowcami Miner. Miner. Resour. Manag. 2015,31, 45–64. [CrossRef] 80. Lechner, A.M.; Kassulke, O.; Unger, C. Spatial assessment of open cut coal mining progressive rehabilitation to support the monitoring of rehabilitation liabilities. Resour. Policy 2016,50, 234–243. [CrossRef] 81. Kasztelewicz, Z.; Szwed, L. Directions of Reclamation in Polish Lignite Mines on Selected Examples. Min. Geoengin. 2010,66, 86–102. 82. Feng, Z.; Hu, Z.; Li, G.; Zhang, Y.; Zhang, X.; Zhang, H. Improving mine reclamation efficiency for farmland sustainable use: Insights from optimizing mining scheme. J. Clean. Prod. 2022,379, 134615. [CrossRef] 83. Kosinskiy, P.; Merkuriev, V.; Medvedev, A. Approaches to evaluation of environmental and economic damage to the Kuzbass agglomeration caused by coal mining industry development. E3S Web Conf. 2019,134, 03009. [CrossRef] 84. Delgado, A.; Romero, I. Environmental conflict analysis using an integrated grey clustering and entropy-weight method: A case study of a mining project in Peru. Environ. Model. Softw. 2016,77, 108–121. [CrossRef] 85. Gulley, A.L. Valuing environmental impacts of mercury emissions from gold mining: Dollar per troy ounce estimates for twelve open-pit, small-scale, and artisanal mining sites. Resour. Policy 2017,52, 266–272. [CrossRef] 86. Narrei, S.; Ataee-pour, M. Estimations of utility function and values of sustainable mining via the choice experiment method. J. Clean. Prod. 2020,267, 121938. [CrossRef] 87. Vergara Tamayo, C.; González Quesada, A.; González Coronado, C. Evaluación de impacto ambiental y estudios previos a una valoración contingente. Caso La Colosa, Cajamarca, Tolima, Colombia. Ens. Econ. 2013,23, 191–222. 88. Kitula, A.G.N. The environmental and socio-economic impacts of mining on local livelihoods in Tanzania: A case study of Geita District. J. Clean. Prod. 2006,14, 405–414. [CrossRef] 89. Willis, K.G.; Garrod, G.D. Valuing landscape: A contingent valuation approach. J. Environ. Manag. 1993,37, 1–22. [CrossRef] 90. Rodríguez-Zapata, M.A.; Ruíz-Agudelo, C.A.; Ahrens, M.J. Analysis of social perception and field verification as a route to evaluation of environmental liabilities in Colombia: Case study Cesar (Colombia). World Dev. Sustain. 2024,4, 100133. [CrossRef] 91. Gu, X.W.; Xu, X.C.; Wang, Q.; Wang, R. Ecological Cost of Mining. J. Northeast. Univ. Nat. Sci. 2013,34, 594–597. 92. Servicio Nacional de Geología y Minería (SERNAGEOMIN). Guía Metodológica para la Presentación de Planes de Cierre Sometidos al Procedimiento de Aplicación General; Ministerio de Minería, Gobierno de Chile: Santiago, Chile, 2014. 93. Valdebenito, L.M. Estimación de Costos de Cierre de Pasivos Ambientales Mineros Identificados en Chile de Acuerdo a los Requerimientos de la Ley 20.551; Universidad de Chile: Santiago, Chile, 2015. 94. Dialga, I. A mining industry sustainability index: Experiences from gold and uranium sectors. In Environmental Footprints and Eco-Design of Products and Processes; Springer: Berlin/Heidelberg, Germany, 2019; pp. 27–63. [CrossRef] 95. Global Reporting Initiative. GRI 14: Mining Sector 2024; GRI: Amsterdam, The Netherlands, 2024. Available online: https: //www.globalreporting.org/ (accessed on 19 February 2025). 96. Taoufikallah, A. Capítulo 5. Aplicación de la Metodología AHP; Escuela Técnica Superior de Ingenieros de Sevilla, Universidad de Sevilla: Sevilla, Spain, 2010. Available online: https://biblus.us.es/bibing/proyectos/abreproy/70496/fichero/Capitulo+5+ Aplicaci%C3%B3n+de+la+metodologia+AHP.pdf (accessed on 23 March 2024). 97. Hwang, C.-L. Multiple Attribute Decision Making: An Introduction; Sage Publications: Thousand Oaks, CA, USA, 1995; Volume 104. 98. Saaty, T.L. The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation, 2nd ed.; McGraw-Hill International Book Company: New York, NY, USA, 1980.