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2017 | OriginalPaper | Buchkapitel

Predicting Waste Properties Using the Geochemistry-Mineralogy-Texture-Geometallurgy Approach

verfasst von : Anita Parbhakar-Fox

Erschienen in: Environmental Indicators in Metal Mining

Verlag: Springer International Publishing

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Abstract

Established protocols for predicting acid rock drainage (ARD) principally utilise geochemical testwork for classifying waste materials. However, ARD formation is dictated by the mineralogy of the sampled material, and indeed textural relationships of both acid forming and neutralizing mineral phases present. In order for such characteristics to be understood, a logical and structured approach to ARD prediction must be adopted. Motivated by this, the three-stage geochemistry-mineralogy-texture-geometallurgy (GMTG) approach was developed. This integrates a range of techniques, with the resulting sample classification based on diverse analyses. This intends to eradicate the possibility of identifying samples as ‘uncertain’ as is the case with established protocols. At stage one, termed ‘pre-screening’ simple tools including paste pH, portable XRF, measurement of sulfur, environmental logging and geometallurgical techniques are used. Samples identified as inert (non-acid forming, non-metalliferous) are not prioritized for further testing. At stage-two termed ‘screening’, established screening tools are used including net acid producing potential (NAPP) and net acid generation (NAG) tests with samples classified by establish criteria. At stage three, termed ‘defining’, only samples identified as acid forming are subjected to in-depth characterization to identify controls on oxidation, as well as advanced geochemical tests to confirm classifications assigned at the conclusion of stage-two. The GMTG approach has potential applications at operations that are at the early life-of-mine (e.g. prefeasibility) and also post-closure phase (e.g. abandoned sites).

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Metadaten
Titel
Predicting Waste Properties Using the Geochemistry-Mineralogy-Texture-Geometallurgy Approach
verfasst von
Anita Parbhakar-Fox
Copyright-Jahr
2017
DOI
https://doi.org/10.1007/978-3-319-42731-7_5