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By C. N. Eze, C. K. Ezeh, O. Nnabuife, N. M. Ugwoju, S. C. Enemuor, V. Okechukwu

In this study, the efficacy of Providencia vermicola KUBT-1 in the leaching and beneficiation of Agbaja iron ore was evaluated under varying conditions of temperature, ore particle size, and pH. Agbaja iron ore is a Nigerian low-grade ore containing about 43%–52% iron and a high amount of gangue materials, including phosphorus (1.4%–2.0%) and sulphur (0.12%). The study was organised in triplicate in shake flasks with 48 samples. One millilitre of washed cells of Providencia vermicola KUBT-1 suspended in normal saline at 0.5 McFarland standard (108 cells ml-1) was introduced into each flask containing 50 g of sterilised ore in 100 ml of bioleaching medium, and the samples incubated at room temperature for eight weeks. The levels of upgraded iron, mobilised sulphur, and phosphorus were determined by atomic absorption and ultraviolet spectrophotometric analyses, respectively. Results showed that a particle size of 0.8 mm was optimal for iron upgrading and sulphur mobilisation while 1.0 mm ore size was optimal for phosphorus mobilisation. Up to 89.60% of the iron was upgraded while phosphorus and sulphur were mobilised, leaving residual values of 0.223% and 0.02%, in the ore, respectively. The organism produced best beneficiation results at a pH of 2.5 and a temperature of 3ºC. Correlation analysis with the Pearson’s correlation model showed a positive correlation between iron upgrading and sulphur-phosphorus removal (r =1.000, and r =0.967), respectively. These results present Providencia vermicola KUBT-1 as a promising candidate for large scale leaching and beneficiation of Agbaja iron ore.

Dec 15, 2025

By T. C. Maswanganyi, G. L. Smith, R. C. A. Minnitt

This paper identifies the strategic gaps and opportunities for the South African mining industry’s contribution towards advancing sustainable development. Mineral resources companies are confronted by a range of complex social performance challenges, which largely manifest in sporadic community and labour unrest, undermining the sustainability and profitability of these companies. Integrating supply chain management, strategic long-term planning and sustainability planning is identified as a strategic gap that can contribute towards the sustainability of mining companies, if effectively implemented. Contributing towards sustainable development by the South African mining industry is not merely a voluntary requirement on the industry but a legal requirement in terms of the Minerals and Petroleum Resources Development Act No. 28 of 2002. This Act is legislation aimed at advancing socioeconomic development in communities that host mining operations and in areas that provide labour to the South African mining industry. In contributing towards the advancement of sustainable development in mining host communities, not only will mining companies fulfil a legal requirement in terms of the Minerals and Petroleum Resources Development Act, but they will also prevent negative social and economic impacts in those communities. This paper identifies innovative and cost-effective ways of advancing sustainable development by integrating strategic supply chain management, strategic long-term planning, and sustainability planning.

Dec 15, 2025

By B. Genc, P. Malepfane

This study proposes a new approach to reduce the environmental impact during surface mining by improving environmental factors through the incorporation of carbon footprint into strategic mine planning. Two key variables were analysed by contrasting and comparing the baseline and optimised models generated. These variables include net present value, which helps determine the financial feasibility of the mining models and their carbon emissions. The variables were analysed by using linear regression, Spearman’s correlation, a P-value hypothesis, and an exponential decay test. Results show that at Mine A the projected net present value was 62% higher than when running a baseline model. Furthermore, the net present value from the baseline model portrayed a high rate of decay at 0.667 versus 0.118 from the optimised model. This indicates the baseline model’s sensitivity to long-term project timelines and fluctuating markets. The optimised method presents an opportunity to manage emissions during the high operational costs phases. It is represented by a 31% improvement in carbon emissions during the periods of high operational costs, whilst maintaining a positive net present value when compared with the baseline model. It was shown that the optimised model presents a better chance of achieving financial feasibility and balancing environmental impact, thereby ensuring that Mine A can align with the environmental aspect of economic, social, and governance principles through lowering the carbon footprint resulting from its hauling operations.

Jan 30, 2026

By L. Diko-Makia, N. Rembuluwani

Artisanal and small-scale mining is crucial for the mineral sector in South Africa, but it also presents both opportunities and challenges. This paper presents an overview of the South African artisanal and small-scale mining sector, the socio-economic significance of artisanal and smallscale mining, the regulatory environment, and the environmental impacts, which are currently the status quo of this sector in South Africa. The paper identified ways in which artisanal and small-scale mining can support local development, create employment opportunities, and reduce poverty. The case of informatisation, ecological damage, and social insecurity has shown social conflicts, potential land degradation, and criminal behaviour. Finally, the paper discusses the future of artisanal and small-scale mining in South Africa, which will largely depend on improved legislation, enhanced personnel capacity, and more sustainable practices to ensure that the positive outcomes of the industry outweigh the negative ones. These propositions include recommendations to all stakeholders, including the government, industry, and civil society, such as stricter environmental regulations, improved working conditions for miners, and the promotion of responsible mining practices.

Dec 15, 2025

By C. Musingwini, G. Njowa, M. Burnett, C. C. Birch

From 2022 to 2040, the global demand for mineral commodities is projected to increase by fourfold to six-fold, largely due to traditional drivers such as population growth and urbanisation compounded by the adoption of decarbonisation technologies that are more mineral intensive than fossil fuel technologies. To meet this projected demand, companies operating in the minerals industry should accelerate the development of mineral projects. Since most of the companies generally operate in multiple geographical, regulatory or legislative jurisdictions, it is critical that the information on Mineral Resources and Mineral Reserves they report on in the public domain should be comparable and consistent across different jurisdictions. The Committee for Mineral Reserves International Reporting Standards fosters alignment of national and regional mineral reporting codes through an internationally accepted template that creates common technical understanding of definitions, classification, estimation processes and the Public Reporting of Exploration Results, Mineral Resources, and Mineral Reserves. The Committee for Mineral Reserves International Reporting Standards Template-based codes guide reporting at respective national and regional levels. Since mine planning is critical in the conversion of mineral resources to mineral reserves, a shared technical understanding should aid comparability of mine planning results. However, differences persist in the way mine planning results are reported. Unlike most previous studies, which have primarily focused on comparing mineral reporting codes, this paper updates and extends such comparisons by exploring how similarities or differences in reporting should influence the mine planning process. It also recommends some principle and process changes to assist mine planning professionals to improve consistency and comparability in reporting mine planning results.

Mar 30, 2026

By C. Aldı, O. Yaral

For the more economical excavation of tunnels in underground mining activities, the selection of mechanised excavation machines (such as roadheaders, electro-hydraulic drills, etc.) and the analysis of performance prediction that can be used in estimating machine energy consumption have been subjects of research from past to present. One of the parameters to be considered in studies examining these methods, is the grinding process. The success of increasing efficiency in grinding is expressed by a reduction in energy consumption. The goal of a grinding process is to maximise the grinding amount at the appropriate grinding size while minimising the energy consumption per tonne of the fragmented material. Today, the depletion of high-grade ore deposits has largely directed the mining industry towards low-grade but large reserve ore deposits. This shift has particularly increased the importance of the grinding process, as it is dependent on particle liberation. Grinding is a critical step in reducing the mineral to the appropriate size, and energy consumption poses a significant challenge in this process. As a result, researchers have conducted various studies focusing on energy efficiency and cost optimisation in this field. In this study, the grindability of 7 different coal environment rocks (sandstone, siltstone) from the Zonguldak Basin, Uzulmez Region was investigated. For this, Hardgrove Grindability Index and Bond Work Index tests were conducted. While determining the relationships between grindability and other parameters, the results obtained from the Hardgrove Grindability Index (HGI) test were used. The energy values found in the Bond Work Index (BWI) test were used to evaluate the excavatability of the rocks. Additionally, tests for strength, hardness, drillability, and abrasiveness were conducted to observe the impact of other parameters on grindability. Considering the results obtained from the experiments, significant relationships were found between the grindability of the rocks and other parameters.

Mar 30, 2026

By K. L. Morton

This technical note reviews the status quo of mud rushes and flooding, which have claimed them lives of many people in underground mines in South Africa and globally. Given that the causes are well known and can be managed, the note calls for the development of a national and global standard on flood and mud rush prevention in order to save lives.

Mar 30, 2026

By R. C. A. Minnitt, A. Akpabio

This study presents a rigorous comparison between ordinary kriging and commonly used machine learning algorithms, those being, linear regression, support vector regression, decision trees, random forests (RF), and k-nearest neighbours for spatial interpolation of platinum grade estimates in a complex ore body within the Bushveld Igneous Complex. Using only X and Y coordinates as predictors, both ordinary kriging and machine learning models were evaluated at point and block supports under traditional and spatial block cross validation frameworks. While naive validation results suggested superior performance for k-nearest neighbour and random forest (R² = 0.92 and 0.86, respectively), these were revealed to be overly optimistic under spatial dependence. Spatial block cross validation results demonstrated substantial declines in model performance, with R² often falling below zero, particularly for decision trees and k-nearest neighbour, indicating strong overfitting and limited generalisability. Ordinary kriging exhibited more stable, albeit modest, performance under spatial validation, reflecting its strength in geostatistical interpolation when contextual geological variables are unavailable. The study underscores the critical importance of spatially aware validation in resource estimation and highlights that machine learning models constrained to spatial coordinates behave as interpolators rather than true learners of geological variability. Recommendations are provided for future work incorporating geological information to enhance predictive robustness.

Mar 30, 2026