The use of predictive tools to prevent AMD formation has historically been driven by the application of increasingly unacceptable end-of-pipe approaches to address the destructive nature of AMD and its huge remediation costs. It is now a regulatory requirement in most mining countries, as part of EIA process, to predict the potential of AMD formation for all solid waste materials at mine sites and to proactively develop plans for waste management and mitigation facilities for unavoidable AMD.
Amongst the many methods used, the ABA method is widely used to predict AMD formation from mine wastes by measuring sulphur species, the calculation of AP and the determination of the acid NP. The difference between AP and NP values indicates the NAPP of the waste material. It is, thus, a quantitative estimate of the balance between the acid generated from mainly the oxidation of sulphide minerals and the acid consumption by carbonate minerals. The other tests that complement the ABA method are the mineralogy, elemental composition, paste pH and the NAG test. The results from all these tests are useful to identify waste materials with potential to form AMD and to classify and segregate the mine wastes for separate disposal and mitigation. However, ABA methods do not predict the time when acid generation would occur and provide no information about effluent quality and rates for acid generation and neuralisation. Thus, several kinetic tests (e.g., humidity cells, leach columns, etc.) have been developed to complement ABA static tests in the prediction of AMD formation. They are aimed at determining the sulphide oxidation kinetics, rates of acid formation and neutralisation, assess water quality and predict when AMD is likely to occur.
Some of the recent developments in AMD prediction include the acid rock drainage index (ARDI) tool that was proposed by Parbhakar-Fox et al (2011). This tool addresses some limitations in the waste characterisation criteria using an integrated geochemistry-mineralogy-texture (GMT) approach to generate detailed and accurate prediction data at a relatively low cost. Other new tests have been developed such as the computed acid rock drainage (CARD) risk protocol that uses the automated mineralogy data to calculate surface area of minerals that form or neutralise acid. In addition, the existing testing tools are being validated, for example, the paste pH method by ASTM has been found to be the best paste pH procedure on drill cores (Lottermoser, 2015).
It is recommended that a site-specific approach in predicting the potential for AMD formation is developed and that all mine waste materials are considered. To obtain a reliable prediction, a combined data interpretation from the mineralogy, static tests, kinetic tests, drainage chemistry and water quality is necessary to fully understand and predict the potential of AMD formation in the future. Waste materials that are PAF may be blended with acid-consuming materials or encapsulated with benign materials to minimise AMD formation at source.
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