Towards Sustainable Mining and Mineral Processing of Metals: Assessment to Implementation

A special issue of Minerals (ISSN 2075-163X).

Deadline for manuscript submissions: 30 April 2025 | Viewed by 3113

Special Issue Editors


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Guest Editor
Business School, University of Western Australia, Perth, Australia
Interests: mineral economics; mining finance; resource sector management; mining sustainability; gold mining; base metals mining; critical minerals; new energy metals; mineral exploration; mineral policy
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
The Minerals Research Institute of Western Australia, East Perth, Australia
Interests: mineral exploration; critical minerals; low-carbon steel production and value chain; the challenge of net-zero emissions mining and mineral processing; precision and low-impact mining; innovation in the mining equipment, technology and services (METS) sector; mineral carbonation; alternative uses of tailings and waste
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to launch a new Special Issue focusing on recent and emerging developments that will ensure a sustainable minerals industry to facilitate the energy transition, as well as the concurrent achievement of net zero emissions mining.

The minerals sector faces an exciting yet extremely challenging future. There is a dual requirement to discover and develop significant new sources of raw materials to process into metals, including critical minerals for the energy transition, but to do so in a manner that is sustainable, incurring minimal environmental externalities.

Mineral production remains a cornerstone of present and future societal needs, underpinning economic growth and thus affecting citizens’ quality of life.

Solutions for a cleaner future for the minerals industry are diverse, varying between commodities and geographies.

New methods of mining are needed where waste streams are minimized, as well as new processing technologies, both requiring cleaner energy sources, energy-efficient equipment, and fit-for-purpose chemical reagents and other consumables.

Sustainability challenges exist along the entire value chain from discovery through to economic assessment, financing, capital development, clean production, and in supply chain management.

Ethical, environmental, social, and governance expectations are heightened, as is the expectation that new production can be delivered safely.

This Special Issue will contain new research in the broad area of sustainable mining and will form a unique and valuable reference source for researchers and industry practitioners.

A list of potential topics of interest is reported below:

  • New frontiers in innovative mineral exploration and discovery.
  • Non-invasive mining, including in situ leaching of metals.
  • Productivity technologies in open pit and underground mining.
  • Mineral resources life cycle impact assessment.
  • Towards net zero emissions mining.
  • Energy efficiency in mining and processing.
  • New methods and emerging technologies for mineral processing and recovery.
  • Efficient recovery of by-product metals from smelting and refining.
  • Novel uses for mining sector waste streams.
  • Mining closure strategies and land repurposing.
  • Energy efficient transport of minerals products.
  • New demand segments for metals, for example in energy storage technologies.
  • Novel mineral policy initiatives for mining sustainability.
  • Community engagement in minerals developments.
  • Social and environmental sustainability of mining and mineral processing.

You may choose our Joint Special Issue in Sustainability.

Prof. Dr. Allan Trench
Dr. Geoffrey E. Batt
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Minerals is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • mining sustainability
  • cleaner mineral production
  • future of mining
  • minerals demand
  • critical minerals
  • emissions reduction
  • reusing mining waste
  • circular economy
  • mining value-chains
  • metals recycling
  • mining rehabilitation
  • socioeconomic impacts of mining
  • sustainable supply chains

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Published Papers (3 papers)

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Research

22 pages, 23363 KiB  
Article
3D Geostatistical Modeling and Metallurgical Investigation of Cu in Tailings Deposit: Characterization and Assessment of Potential Resources
by M’hamed Koucham, Yassine Ait-Khouia, Saâd Soulaimani, Mariam El-Adnani and Abdessamad Khalil
Minerals 2024, 14(9), 893; https://doi.org/10.3390/min14090893 - 30 Aug 2024
Viewed by 954
Abstract
The management of mine tailings presents a global challenge. Re-mining these tailings to recover remaining metals could play a crucial role in reducing the volume of stored tailings, as historical mining methods were less efficient than those used today. Consequently, mine wastes have [...] Read more.
The management of mine tailings presents a global challenge. Re-mining these tailings to recover remaining metals could play a crucial role in reducing the volume of stored tailings, as historical mining methods were less efficient than those used today. Consequently, mine wastes have the potential to become unconventional resources for critical minerals. To assess this potential, critical minerals and metals in the mine tailings were investigated through sampling, characterization, and 3D geostatistical modeling. The Bleïda copper mine tailings in Morocco were modeled, and residual copper resources were estimated using ordinary kriging (OK). Tailings were systematically sampled at a depth of 1.8 m using a triangular grid and tubing method. The metallic and mineralogical content of the samples was analyzed, and a numerical 3D model of the tailing’s facility was created using topographic drone surveys, geochemical data, and geostatistical modeling. The results from the 3D block model of the Bleïda tailings facility reveal that the volume of deposited tailings is 3.73 million cubic meters (mm3), equivalent to 4.85 million tonnes (Mt). Furthermore, based on the average copper grade (~0.3% by weight) in the studied part of the tailings pond, the copper resources are estimated at 2760 tonnes. Mineralogical characterization indicates that this metallic content is mainly associated with sulfide and carbonate minerals, which exhibit a low degree of liberation. This study aims to serve as a reference for assessing the reprocessing feasibility of tailings in both abandoned and active mines, thereby contributing to the sustainable management of mine tailings facilities. Geostatistical modeling has proven effective in producing tonnage estimates for tailings storage facilities and should be adopted by the industry to reduce the technical and financial uncertainties associated with re-mining. Full article
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12 pages, 1141 KiB  
Article
Assessing Mining Performance Indicators in Relation to the SDGs: Development of a Guided Methodology and Its Application in an Iron Ore Mine
by Rhaymá do Carmo Silva and Anna Luiza Marques Ayres da Silva
Minerals 2024, 14(9), 887; https://doi.org/10.3390/min14090887 - 30 Aug 2024
Viewed by 974
Abstract
The concept of sustainability has gained significant recognition across all industrial sectors, particularly in response to the potential global environmental crisis. In mining, sustainability ensures responsible operations by addressing environmental, social, and economic aspects. Performance indicators, categorized into environmental, social, economic, and governance [...] Read more.
The concept of sustainability has gained significant recognition across all industrial sectors, particularly in response to the potential global environmental crisis. In mining, sustainability ensures responsible operations by addressing environmental, social, and economic aspects. Performance indicators, categorized into environmental, social, economic, and governance groups, are monitored to oversee these aspects. In 2015, the UN established 17 Sustainable Development Goals (SDGs) as a global agenda for achieving equitable economic and social development. This study presents a methodology to evaluate performance indicators in an iron ore mine in southeast Pará, Brazil, to understand whether and how these indicators guide the mine’s operations toward fulfilling the SDGs. This study was based on the application of a methodology specifically developed for this purpose, where a seven-step application was defined, with each step involving an activity to be carried out to verify the correlation performance indicators with the SDGs. By applying the proposed methodology, the assessment of 286 performance indicators was conducted, revealing that 55.24% aligned the mine’s operation with the SDGs. Furthermore, the developed methodology may be applied to other mining enterprises, supporting their sustainability reports and compliance with the sector’s regulatory standards and mine closure plan requirements. Full article
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21 pages, 9335 KiB  
Article
Predictive Insight into Tailings Flowability at Their Disposal Using Operating Data-Driven Artificial Neural Network (ANN) Technique
by Nelson Herrera, Raul Mollehuara, María Sinche Gonzalez and Jarkko Okkonen
Minerals 2024, 14(8), 737; https://doi.org/10.3390/min14080737 - 23 Jul 2024
Viewed by 669
Abstract
This study investigates the application of artificial neural networks (ANNs) in predicting the flowability of mining tailings based on operational variables. As the mining industry seeks to enhance operations with complex ores, the constant improvement and optimization of mineral waste management are crucial. [...] Read more.
This study investigates the application of artificial neural networks (ANNs) in predicting the flowability of mining tailings based on operational variables. As the mining industry seeks to enhance operations with complex ores, the constant improvement and optimization of mineral waste management are crucial. The flowability of tailings was investigated with data driven by properties such as particle-size distribution, water content, compaction capacity, and viscoelastic characteristics that can directly affect stacking, water recovery capabilities, and stability at disposal, influencing storage capacity, operational continuity, and work safety. There was a strong correlation between water content and tailings flowability, emphasising its importance in operational transport and deposition. Three ANN models were evaluated to predict tailings flowability across three and five categories, where a model based on thickening operational variables, including yield stress and turbidity, demonstrated the highest accuracy, achieving up to 94.4% in three categories and 88.9% in five categories. Key variables such as flocculant dosage, water content, yield stress, and solid concentration were identified as crucial for prediction accuracy The findings suggest that ANN models, even with limited datasets, can provide reliable flowability predictions, supporting tailings management and operational decision-making. Full article
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