Valorisation of mine waste - Part II: Resource evaluation for consolidated and mineralised mine waste using the Central African Copperbelt as an example.

J Environ Manage

Bavarian Georesources Centre, Dept. of Geodynamics & Geomaterials Research, Institute of Geography and Geology, University of Würzburg, Am Hubland, D, 97074, Würzburg, Germany; Department of Geological Sciences, University of Cape Town, Rondebosch, 7700, South Africa.

Published: December 2021

Mine waste can create long-term and occasionally catastrophic environmental degradation. Due diligence of mine waste in the form of monitoring and maintenance requires a constant supply of societal resources. Furthermore, mine waste is unlikely to disappear with current mining methods and instead, it is more likely to accumulate at a faster rate due to decreasing primary ore grades and increasing societal demands. However, mine waste can be a societal asset, as it can offer an alternative source of partly critical raw materials (CRMs) that can augment primary sources and provide an opportunity to mitigate supply-risk while ensuring sustainability and easing geopolitical tensions. Cobalt is a critical raw material that is largely a by-product of mining of copper, nickel and platinum-group element ores. It is an element that the renewable energy and high-tech sectors critically depend on and for which no reasonable substitutes currently exist. The majority of the global cobalt production stems from the Central African Copperbelt. Published cobalt production figures for the Central African Copperbelt were used to evaluate cobalt tailings from the Central African Copperbelt. As part of a waste valorisation framework that focuses on primarily on the technical aspects of mine waste valorisation, this study assesses the application of key geostatistical methods, such as kriging and conditional simulation, followed by uniform conditioning, to evaluate the resource potential in a hypothetical copper-cobalt tailing deposit from the Central African Copperbelt. The results indicate that methods such as traditional algorithmic kriging, sequential Gaussian simulation and uniform conditioning are highly effective tools in resource modelling of mine waste. The resource assessment framework component developed in this study makes it possible to systematically characterise, profile and model any mine waste storage facility and thus supplements other framework components discussed in an accompanying paper to maximise mine waste utilization.

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http://dx.doi.org/10.1016/j.jenvman.2021.113553DOI Listing

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