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Sampling and blending in geoenvironmental campaigns – current practice and future opportunities


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Author A Parbhakar-Fox and S C Dominy


The prediction of acid and metalliferous drainage (AMD) from mine waste materials is critically important during all stages of the mine value chain. However, to determine such geoenvironmental characteristics static and kinetic testing of individual waste units must be performed on representative samples. The importance of sample selection cannot be underestimated; it is the single most critical aspect of any geoenvironmental investigation. Poor sampling techniques and inadequate sample selection will contribute to excessive variance, difficulties in interpretation and incorrect assessment. By undertaking mesotextural characterisation based on hyperspectral mineralogical data (with sulfur assay data if available), opportunities to improve sampling strategies are presented. Such data will inform the selection of samples for low-cost total sulfur, paste pH and geoenvironmental logging, which collectively will allow for accurate AMD forecasting and improved sampling practices to be achieved. Once sampled, robust quality assurance/quality control (QA/QC) protocols must be developed where the use of international certified reference standards become obligatory. This is currently not practised, resulting in inter-laboratory discrepancies when undertaking waste classification. Further improvements in geoenvironmental characterisation testing lies in the adoption of blended static testing protocols, whereby blends of waste materials can be efficiently tested so as to give an early forecast as to whether they will produce acidic or metal-laden drainage. Such information is integral in developing a waste schedule that will allow for a non-acid forming waste landform to be constructed right from the start of the operational phase. Ultimately, improvements in this discipline lie in technological innovations with regards to mineralogical characterisation, and by offering geoscience and minerals engineering students a competent education in the discipline. Collectively, this will empower a step-change in AMD prediction and waste handling, and will make the realisation of the United Nations Sustainable Development Goals a reality, rather than a dream.


Parbhakar-Fox, A and Dominy, S C, 2017. Sampling and
blending in geoenvironmental campaigns – current practice and future
opportunities, in Proceedings Eighth World Conference on Sampling and
, pp 45–54 (The Australasian Institute of Mining and Metallurgy: Melbourne).