This chapter provides a comprehensive review of techniques, instruments, and methods suitable for mine residue sampling and characterization, using the potential recovery of critical raw materials (CRMs) from bauxite residues as an example. The sampling methods address diverse strategies for assessing the suitability of CRMs recovery, including screening, detailed characterization, determination of acid rock drainage generation and wastewater, and the implementation of a geometallurgical approach. The methods for characterizing mine residues are a selection of geochemical, mineralogical, and other techniques that can be used either in field environments (e.g., portable X-ray fluorescence, infrared spectroscopy) or in the laboratory (e.g., inductively coupled plasma-based techniques, scanning electron microscopy) to study the main properties of the waste material. Other techniques used for the remote characterization, such as earth observation are also addressed. Approaches for data analytics and the impact of digitalization in the characterization of mine residues are briefly discussed. Overall, this chapter aims to help practitioners and researchers to implement better practices in the sampling and characterization for the revalorization of mine residues.

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This chapter addresses the general properties and characteristics of the following residue categories: mining wastes, mineral processing wastes or tailings, metallurgical wastes (slags, dusts, slimes, and muds), and wastewaters. Residue origin, storage, disposal, and a brief indication of associated environmental impacts are discussed; concrete examples are given for illustration purposes.

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TRIM4Post-Mining is a H2020/RFCS-funded project that brings together a consortium of European experts from industry and academia to develop an integrated information modelling system. This is designed to support decision making and planning during the transition from coal exploitation to a revitalized post-mining landscape, enabling infrastructure development for agricultural and industrial utilization, and contributing to the recovery of energy and materials from coal mining dumps. The smart system will be founded upon a high-resolution spatiotemporal database, utilizing state-of-the-art multi-scale and multi-sensor monitoring technologies that characterize dynamic processes in coal waste dumps related to timely, dependent deformation and geochemical processes. It will integrate efficient methods for operational and post-mining monitoring, comprehensive spatiotemporal data analytics, feature extraction, and predictive modelling; this will allow for the identification of potential contamination areas and the forecasting of geotechnical risks and ground conditions. For the interactive exploration of alternative land-use planning scenarios—in terms of residual risks, technical feasibility, environmental and social impact, and affordability—up-to-date data and models will be embedded in an interactive planning system based on Virtual Reality and Augmented Reality technology, forming a TRIM—a Transition Information Modelling System. This contribution presents the conceptual approach and main constituents, and describes the state-of-the-art and detailed anticipated methodological approach for each of the constituents. This is supported by the presentation of the first results and a discussion of future work. An anticipated second contribution will focus on the main findings, technology readiness and a discussion of future work.@en

The recent Circular Economy Action Plan for Europe1 considers mine waste a secondary source of minerals. These deposits contain potentially economic concentrations of Critical Raw Materials (CRMs), such as Al, Li, Co and REE, which are strategic for the global economy and energy transition. However, there are significant knowledge and technological gaps that hinder their successful recovery. The INCO-Piles 2020 project2 is currently working on the recapitulation, establishment and development of innovative technologies for the sustainable extraction of CRMs from the residuals of mining activities, focusing on Regional Innovation Scheme (RIS) strategic areas. The project includes the definition of potential applications, best practices, and the promotion of technology transfer through round tables that count with international experts' participation.The first Round Table, a hybrid event held in December 2020 with 73 experts from 23 countries, addressed the challenges in recovering CRMs from tailings. The discussions were based on three topics: (1) challenges in sampling and characterisation from mining residue, (2) extraction and processing challenges, and (3) economic and environmental challenges. Regarding the first topic, one of the most significant issues is the inherent heterogeneity of mine waste deposits, which is a product of the mine processing and deposition methods, and the post-depositional weathering reactions. The lack of historical data, particularly for old deposits, hampers the understanding of such processes. A second challenge concerns the specific type of information required for assessing the CRMs potential. Representative geochemical and mineralogical data must be collected and interpreted at different scales (i.e., from individual minerals to tens of meters tall waste rock piles and tailings). The collection of representative samples faces issues related to the accessibility to the mine waste sites, the coverage and the sample contamination (i.e., material mixing) related to sample recovery methods. The scalability can be addressed by a combination of laboratory analyses, in-the-field surveys and remote sensing techniques. Current innovations in the combination of modern analytical instruments for geochemistry and mineralogy (e.g., pXRF, LIBS and portable infrared spectrometers) and the implementation of machine learning and artificial intelligence techniques will contribute to closing the knowledge and technology gaps.Lastly, the discussions included the potential hazards faced during the characterisation and re-intervention of old-sites. Well-known mine wastes issues related to human health, environment and license to operate that can hinder a characterisation campaign must be properly considered before the commencement of a CRMs recovery project. The participants also identified transversal challenges for the three discussion topics, such as the need for regulation and professionals with an appropriate background.All the insights discussed during this First Round Table will serve as a baseline for defining the best practices for characterisation and sampling of CRMs in mine wastes and contributing to increasing the sustainability in the supply of mineral resources and improving old mining sites' environmental quality. 1 EU Circular Economy Action Plan https://ec.europa.eu/environment/circular-economy/ 2 INCO-Piles is a two-year project funded by EIT RawMaterials. More information: https://site.unibo.it/inco-piles-2020/en@en

In response to the growing demand for sustainable products and services, the kaolin calcination industry is developing practices that optimise the use of resources. The main challenges include more efficient use of raw materials and a reduction in the energy consumed by the calcination furnace. An opportunity to achieve this lies in the optimisation of the calcination process. This can be done by giving real-time feedback on the quality parameters of the generated calcined kaolin. This study proposes the use of infrared spectroscopy as a monitoring technique to determine the chemical properties of the calcined kaolin product. The basis of the monitoring system is the measurement of the kaolin soluble alumina content as one of the most important quality parameters; this property is an indicator of the over- or under-use of raw materials and energy during the calcination process and can advise the operations regarding the optimisation of the working conditions of the furnace. The implementation of an infrared-based monitoring system would lead to increased efficiency in the production of calcined kaolin.

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Industrial minerals are essential to human activity. The products derived from them make an integral part of a wide range of materials that are ubiquitously present in our daily lives. The performance and attributes of these materials depend significantly on the properties and quality of the industrial minerals and the products generated from them. These characteristics are ensured by the selection and mining of adequate ores, and by using various beneficiation and processing strategies to modify or enhance the original properties of the minerals.
One example of these strategies is calcination, in which the minerals are subject to thermal treatment. The success of the generation of high-quality products by using this technique partly depends on the capability of the plant to detect the factors that can degrade the quality of the raw ore, feed for calcination and final product. It also depends on its ability to inform and adapt the operations according to the presence of such factors. A possible approach for doing this is to characterise the minerals and materials with sensor technologies that can generate information on-site and in real-time, focusing on the identification of the degrading factors. Their timely detection can give operational feedback to the process and aid in the generation of high-quality products.
This Thesis aims to develop methods for the detection of factors that determine the quality of industrial mineral products by using data derived from infrared sensors, which have the potential to be implemented in mining and process control. For doing this, kaolin, perlite and diatomite have been selected as commodities that are relevant to the market and that represent different applications. This research shows the capacity of infrared sensor-based technologies to retrieve information, directly or indirectly, about the factors that affect the quality of industrial minerals at a lower cost and with comparable efficiency to other analytical methods.
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In the production of calcined kaolin, the on-line monitoring of the calcination reaction is becoming more relevant for the generation of optimal products. In this context, this study aimed to assess the suitability of using infrared (IR) spectroscopy as a potential technique for the on-line characterization of the
calcination of kaolin. The transformation of kaolin samples calcined at different temperatures were characterized in the short-wave (SWIR) spectra using the kaolinite crystallinity (Kx) index and the depth of the water spectral feature (1900D). A high correlation between the standard operational procedure
for the quality control of calcined kaolin and the Kx index was observed (r = -0.89), as well as with the 1900D parameter (r = -0.96). This study offers a new conceptual approach to the use of SWIR spectroscopy for the characterization the calcination of kaolin, withdrawing the need of using extensive laboratory techniques.@en

In the production of calcined kaolin, the soluble Al2O3 content is used as a quality control criterion for some speciality applications. The increasing need for automated quality control systems in the industry has brought the necessity of developing techniques that provide (near) real-time data. Based on the understanding that the presence of water in the calcined kaolin detected using infrared spectroscopy can be used as a proxy for the soluble Al2O3 measurement, in this study, a hand-held infrared spectrometer was used to analyse a set of calcined kaolin samples obtained from a production plant. The spectra were used to predict the amount of soluble Al2O3 in the samples by implementing Partial Least Squares regression (PLS-R) and Support Vector Regression (SVR) as multivariate calibration methods. The presence of non-linearities in the dataset and the different types of association between water and the calcined kaolin represented the main challenges for developing a good calibration. In general, SVR showed a better performance than PLS-R, with Root Mean Squared Error of the cross-validation (RMSECV) = 0.046 wt.% and R2 = 0.87 for the best-achieved prediction. This accuracy level is adequate for detecting variation trends in the production of calcined kaolin which could be used not only as a quality control strategy but also for the optimisation of the calcination process.@en

Diatomite, a rock formed by the accumulation of opaline diatom frustules, is a preferred raw material for the manufacturing of filters. Its uniqueness relies on the high porosity and inertness of the frustules. The presence of carbonates in some diatomite ores hinders these properties. The~purpose of this study was to identify the type of carbonates and their association with the ore in a diatomite deposit, and to assess the suitability of determining the quality of the ore using techniques with potential for in-pit implementation. For this, run-of-mine samples were analysed using environmental scanning electron microscopy (ESEM) and infrared spectroscopy. The ESEM images showed that carbonate is present as cement and laminae. The infrared data revealed that the carbonate minerals correspond to aragonite and calcite, and that their occurrence is linked to the total amount of carbonate in the sample. By using a portable spectral instrument that uses diffuse reflectance, it was possible to classify the spectra of the ore samples based on the carbonate content. These results indicate that {infrared} technology could be used on-site for determining the quality of the ore, thus providing relevant information to assist the optimisation of mining and beneficiation~activities.@en

For industrial applications, highly refined kaolin is calcined at temperatures above 1000ºC, triggering chemical, morphological and mineralogical changes. The aim of the calcination process is to create a white, non-abrasive and chemically inert product. In order to control these properties, the Standard Operating Procedure (SOP) in the industry is the extraction of soluble aluminium. This parameter measures the reactivity of the calcined kaolin and estimates on its abrasiveness. However, this procedure has a long turn-around time that prohibits operational feedback. As a consequence, there is a strong industrial interest on the development of an on-line and automated measurement of soluble aluminium. This study proposes a methodology based on diffuse reflectance infrared (IR) spectroscopy that serves as a proxy for the measurement of soluble aluminium. The technique was chosen based on its capabilities for implementation as an on-line and automated tool, and because it can detect the mineralogical changes associated to the crystallinity of the calcined kaolin, which are linked to the soluble aluminium content. For this, feed and products collected from a calcined kaolin processing plant were characterised using diffuse reflectance IR spectroscopy in the mid- and long-wave ranges (MWIR and LWIR, respectively) using a portable instrument. The spectral features that explain the transformation in the calcined kaolin reaction were identified, and the IR spectra were used as input for a Partial Least Squares (PLS)-based regression model for the prediction of soluble aluminium. In the IR spectra, the amorphous and highly reactive phase was characterised by broad Al-OH, Si-O and Al-O absorption features. The transition towards a crystalline phase was evidenced in the spectra by changes in the shape and wavelength position of the absorption features. These variations describe the stability of the mineral structure, which is related to the reactivity of the material, and the formation of crystals that influence the abrasiveness. The input for the PLS model was restricted to the wavelength ranges where the relevant absorption features occur, thus avoiding the influence of environmental factors. The resulting model has a good performance for the prediction of the soluble aluminium values, showing that the IR spectra can be used as a proxy for the measurement of the SOP. In a mineral processing environment, portable IR instruments can record spectra from the calcined kaolin production on-site and periodically. The short time required for the data collection and processing enables the generation of results in near real-time. These data can be integrated to the plant’s monitoring system giving timely feedback to operators for adjusting the parameters for calcination. As a consequence, reduction of energy and costs can be expected, thus increasing the efficiency of the operations. @en

Calcined kaolin is an industrial minerals product used in the production of paper, paint, rubber and other specialty applications. It is produced from kaolinite through a series of refinement steps and final calcination at temperatures of above 900°C, with the aim of generating a whiter and more abrasive material. The raw kaolin ore is a mixture of clay minerals, quartz and feldspars, where kaolinite is the main constituent. The optimal kaolin ores to feed the processing plant should ideally have high kaolinite abundance, be free in Fe-bearing mineralogy (to avoid influence in the colour of the product), and the kaolinite itself should be of high crystallinity (to ensure the correct abrasiveness after calcination). This work presents a case study from the kaolin deposits in the St. Austell Granite (South-West England), which are known for their high quality and world-class size. In this area, the kaolin is of primary-hydrothermal origin, with mineral associations that are related to the genetic history. The eventual depletion of the high-quality reserves is bringing now the attention to the lower grade zones, where the amount of impurities increases. As a consequence, it is critical to developing strategies that ensure the supply of high-quality ore to the processing plant. For this, it is necessary to acquire a thorough knowledge of the ore, including relative abundance of the minerals and their textural relationships. Hyperspectral images in the visible-near infrared (VNIR) and short-wave infrared (SWIR) ranges were collected from drill cores and run-off-mine (ROM) samples, obtained from one of the kaolin pits in the St. Austell area, where the kaolin quality is known to be lower than in the rest of the deposit. A series of mineral maps were generated to assess the distribution, texture and abundance of the Fe-bearing mineralogy and the other kaolin-associated minerals, as well as the variations in the crystallinity of kaolinite. The mineral maps enabled the identification of tourmaline, biotite and hematite as the Fe-bearing mineralogy. Tourmaline was found mainly in veins and sometimes as phenocrysts; biotite was rather scarce, which suggest the advanced alteration degree of the deposit; hematite was present as coating and concentrated along quartz veins. Most of the mineral associations were represented by kaolinite, halloysite, muscovite, illite and montmorillonite. The ground mass was mostly kaolinite, although transition zones from kaolinite to halloysite and kaolinite to mica and montmorillonite were detected. Regarding the kaolinite crystallinity, the pure kaolinite graded from high to very high crystallinity. For the mineral mixtures of kaolinite with montmorillonite or halloysite, the crystallinity could not be determined with confidence. These findings raise the possibility of using hyperspectral imaging as a tool for assisting selective mining, by identifying the areas in the deposit with the highest kaolin quality, thus reducing the amount of waste. In scenarios where selective mining is not possible, the spectral characterisation might provide robust mineralogical information about the content of the ore that can support the decision-making process in higher levels of the kaolin value chain.@en

Diatomaceous Earth (DE) is commonly used in the industry for the manufacturing of filters, where diatomite is preferred due to its low chemical reactivity and high porosity. Diatomite deposits with major amounts of mineral impurities, such as carbonates, present a problem in the production DE. In this study, samples from a diatomite deposit with known presence of carbonate were analysed. With the aim of estimating the carbonate content, the samples were analysed with infrared (IR) spectroscopy. The association between the carbonate and diatomite was characterised using thin sections and Environmental Scanning Electron Microscopy (ESEM). Based on the infrared spectra, the diatomite ore was classified according to the carbonate content. The microscopy images showed laminae, cement and coating of carbonate around the diatomite. These findings indicate that the IR classification along with the type of carbonate association can optimise the production of DE. @en

In the mining of perlite deposits, controlling the generation of fine particles and the concentration of metals is of outstanding importance to meet the environmental and market requirements. Particle size and chemical purity are conventionally manipulated during the processing of the ore to achieve high product specifications. However, the current practices do not consider a proactive approach that focuses in the in-pit characterisation of the ore that would minimise the environmental impact and optimise the mining process since its early stages. This paper presents a method for the in-pit detection of the perlite ore variability that is related to the generation of fine particles and the elevated concentration of metals. Particle size and chemical purity showed to be dependent on the mineralogical variations of the ore, specifically opal and montmorillonite. Using a portable infrared spectrometer, an index that establishes the relative proportions of these minerals in the perlite ore was created. Such index provided insight into the correlation between mineralogy, fine particles and concentration of metals. Consequently, the index could be used not only for mineralogical determination but also as a predictor of the presence of the main impurities in the perlite ore. These results can be implemented in perlite mining to reduce the generation of waste and can influence the production of high-quality perlite products.@en

Perlite products are used as a filter aid in the food industry. For such applications, the purity of the material is one of the most significant parameters of control. Early detection of heavy metals is therefore of great industrial interest. In this study, a sensor-based approach for chemical and mineralogical characterization enabled the identification of patterns in the distribution of heavy metals in the perlite ore. Integration of Laser-Induced Breakdown Spectroscopy (LIBS) and Near Infrared Spectroscopy (NIR) was used to determine the presence of heavy metals in perlite ores. The results have direct implications for the development of methods and techniques for material characterization, as well as for the mining of perlite ores. @en