Mining, Volume 4, Issue 2 (June 2024) – 7 articles

This research applies remote sensing methodologies for the first time to comprehensively explore the geological and mineralogical characteristics of the Jbel Bou Dahar region. An integrated approach with multi-sensor satellite images, including ASTER, Landsat-8, and Sentinel-2 was applied with the aim to discriminate the different lithological units in the study area. We implemented a suite of well-established image processing techniques, including Band Ratios, Principal Component Analysis, and Spectral Angle Mapper, to successfully identify, classify, and map the spatial distribution of carbonate minerals, OH-bearing minerals, and iron oxide minerals. Due to its high spectral resolution in the short-wave infrared region (SWIR), the ASTER sensor provided the most accurate results for mapping carbonate and OH-bearing minerals compared to the Sentinel-2 and Landsat-8 sensors. Conversely, Sentinel-2 offers high spectral and spatial resolution in visible and near-infrared (VNIR) corresponding to the regions where iron oxide minerals exhibit their characteristic absorption peaks. The results confirm the advantages of remote sensing technologies in the geological and mineralogical exploration of the study area and the importance of selecting the appropriate sensors for specific mapping objectives. Full article

Arsenic and antimony are impurities that reduce the economic value of concentrates due to the environmental problems they cause. The removal of these impurities by hydrometallurgical means has been highly studied for sulfide copper concentrates using different leaching agents in an alkaline medium (NaClO, H₂O₂, NaOH, Na₂S, NaHS, and S). For a lead–silver concentrate consisting of galena, sphalerite, and pyrite, it was possible to selectively reduce the arsenic content from 1.10% to 0.55% and antimony from 2.41 to 1.04% through the digestion-leaching technique that uses elemental sulfur as a leaching agent in alkaline medium. The adequate powdered sulfur and sodium hydroxide dosage were 336 and 342 kg/t, respectively. The process was carried out at 120 °C with a liquid/solid ratio of 2 in digestion and 5.67 in leaching; the appropriate digestion and leaching time were 20 and 30 min, respectively. The thermodynamics and kinetics of this process turned out to be very complex due to the great variety of simultaneous leaching and precipitation reactions. The digestion process exhibited a mixed kinetic control, where diffusion through the boundary layer and the chemical reaction were the controlling steps with an activation energy of 11.05 kcal/mol. Full article

The mining industry is the leading supplier of raw materials in modern society. This sector of human activity has experienced a severe crisis due to the energy transition and has been revived in recent years due to the need for critical metals that are essential in the post-coal era. In underground and open pit mining, processes such as extraction, transportation, safety, underground ventilation, waste management, and rehabilitation are of major importance, and their “design” is critical to the economic survival of the mine. All the above processes required to operate a mine are strongly reminiscent of an example of nature’s workman: the ant. The sympatric insect uses the same processes as the ones aforementioned during the creation of its nest. The ants dig to “extract material from the ground”, and they transport this material from the nest‘s site to the waste deposition location. The ants ensure the safety of the underground opening and the proper ventilation needed for them to live there for a long time. This article attempts to identify the relations between all the above processes and sub-processes, and how human mining and ant colony development correlate with each other. Furthermore, we examine how an ant colony has aided in the development of mining technology, and what more humans can learn and adopt from a “miner” that is 66 million years old, in order to improve their processes. Full article

This article describes a part of the POTENTIALS project promoted by the Research Fund for Coal and Steel (RFCS) of the EU, which, in general, has aimed to develop business models for the reuse of former industrial and mining sites in different European regions. The goal of this project focused on the creation of so-called eco-industrial parks to enable sustainable energy production and reduce waste and pollution on coal sites in transition. A key aspect was the development of a suitable territorial impact assessment (TIA), a new and complex policy tool for the assessment of the territorial impacts of EU policies and projects on territorial cohesion. Therefore, the special TEQUILA (Territorial Efficiency, Quality and Identity Layer Assessment) approach is used to describe the TIA for this case and emphasizes its application in assessing ex ante the impacts of the transition from a coal site to an eco-industrial park. It underlines the need for a differentiated understanding of the regional characteristics and potential impacts of transition policies or projects. Furthermore, the process and results of applying the TEQUILA methodology, a multicriteria analysis, in the context of regionalized impact models has shown how important it is to select well-defined, expert-based criteria, but at the same time, to establish a system that is flexible and adaptable to the needs of political decision makers and stakeholders considering the normative weights of the criteria. This has been illustrated by some examples. Full article

Integrated geo- and environmental monitoring in mining represents a high-dimensional challenge (location, altitude/depth, time and sensors). This is challenging for experts but poses great problems for a multitude of participants and stakeholders in building up a complete process understanding. The Epe research cooperation aims to elucidate the ground movement at the Epe cavern storage facility with a public participation process. The research cooperation was founded by the city of Gronau, the citizens’ initiative cavern field Epe, the company EFTAS, Münster, and the Research Center of Post-Mining at the Technische Hochschule Georg Agricola, Bochum. This research cooperation is the first in Germany to involve direct collaboration between science and the public. In the cavern field, which has been in operation since the 1970s, brine is extracted, and at the same time natural gas, crude oil and helium, as well as hydrogen in the future, are stored in the subsurface. The technical focus of this work was the development of a high-resolution spatiotemporal analysis of ground movements. The area is monitored annually by the mining company’s mine surveyor. The complexity of the monitoring issue lies in the fact that the western part is a bog area and a former bog area. Furthermore, the soils in the eastern part are very humus-rich and show strong fluctuations in the groundwater and therefore complex hydraulic conditions. At the same time, there are few fixed scatterers or prominent points in the area that allow high-resolution spatiotemporal monitoring using simple radar interferometry methods. Therefore, the SBAS method (Small Baseline Subset), which is based on an aerial method, was used to analyze the radar interferometric datasets. Using an SBAS analysis, it was possible to evaluate a time series of 760 scenes over the period from 2015 to 2023. The results were integrated with the mine survey maps on the ground movement and other open geodata on the surface, the soil layers and the overburden. The results show complex forms of ground movement. The main influence is that of mining. Nevertheless, the influence of organic soils with drying out due to drought years and uplift in wet years is great. Thus, in dry years, ground subsidence accelerates, and in wet years, ground subsidence not only slows down but in some cases also causes uplift. This complexity of ground movements and the necessary understanding of the processes involved has been communicated to the interested public at several public information events as part of the research cooperation. In this way, an understanding of the mining process was built up, and transparency was created in the subsurface use, also as a part of the energy transition. In technical terms, the research cooperation also provides a workflow for developing the annual mine survey maps into an integrated geo- and environmental monitoring system with the development of a transparent participatory geomonitoring process to provide resilience management to a mining location. Full article

Direct and indirect effects after mine operations cease operating must ideally be subjected to perpetual monitoring routines in order to detect possible risks or avoid adverse effects on the surrounding ecosystems at an early stage. In this contribution, mining subsidence lakes created inside the nature reserve Kirchheller Heide and Hilsfeld Forest are subjected to analysis for a long-term monitoring scheme. For this purpose, we employ high-resolution unmanned aerial system (UAS)-based multispectral and thermal mapping tools to provide a fast, non-invasive and multitemporal environmental monitoring method. Specifically, we propose to monitor vegetation evolution through multispectral analysis, biotypes identification using machine learning algorithms, and water surface extent detection, together with their thermal behavior. The aim of this contribution is to present the proposed workflow and first results to establish a baseline for future analyses and subsequent surveys for long-term multi-temporal monitoring. Full article

This study investigated the application of machine learning to optimise the pumping load shift of a complex dewatering system in a deep-level mine, aiming to reduce energy costs associated with the dewatering process, which consumes an average of 14% of the mine’s electricity. Traditional practices, reliant on human control and simulations, often lead to inconsistent savings and occasional losses. The study employed multivariate linear regression (MLR) and extreme gradient boosting (XGBoost) on a mine dewatering system, to identify important parameters influencing the pumping load shift performance. Critical parameters significantly impacting the energy consumption of the dewatering system were identified by the best-performing model, XGBoost. Implementing a pumping schedule based on XGBoost insights resulted in consistent load shifting and enhanced energy cost savings. These findings highlight the potential of machine learning in comprehending and optimising complex systems in deep-level mines, with the case study approach proving effective in quantifying and validating real-world impacts. This approach could offer substantial energy savings through data-driven decision-making. Full article