Applications of Acid Mine Drainage Prediction Data

As discussed previously, all mine wastes should be characterised to predict the potential, rate and timing of AMD formation, and likely metals in leachates from sulphide oxidation. This forms the basis for developing waste management plans where AMD risk is evident. Therefore, the control and safe disposal of waste materials to minimise AMD formation may involve prediction for AMD potential, classification and confinement of any materials at risk of AMD. Consequently, any material classified as PAF from prediction tests have high AMD risk that must be properly identified. The material must be selectively disposed and encapsulated with benign materials, that is, those that are classified as NAF mine wastes with high ANC and low AMD risk (Jones et al., 2016). Thus, the integrated and sustainable AMD management through prediction dictates the use of source control technologies for AMD in order to prevent, minimise or reduce AMD formation through the following measures, some of which are discussed in Chapter 6:

  • • Identification of AMD risk and early integration of AMD issue in the life cycle of the mine,
  • • Blending of acid-generating wastes with acid-consuming materials,
  • • Encapsulation of PAF waste dumps by dry covers, caps, seals, etc.,
  • • Flooding/sealing underground mines (with water) after closure to stop oxygen ingress and thus, prevent further AMD generation,
  • • Underwater storage of tailings, and
  • • Application of cleaner production principles.

The awareness, adoption and use of AMD prediction tools by the mining industry is evident, however, post mine closure incidents of AMD continue to occur at many mine sites despite improved understanding of AMD prediction tests. Consequently, failure to predict AMD has resulted in environmental destruction, unplanned remediation costs and reputational damage to the industry. Lottermoser (2015) provides a comprehensive discussion on why some mine sites remain AMD liabilities after mine closure. For example, from a practical perspective, the mining industry puts too much emphasis on reactive or end-of-pipe approaches to manage environmental impacts through legal compliance, mine site rehabilitation and monitoring, etc., as opposed to the use of AMD prediction tests to prevent AMD formation at source which is regarded as a sustainable option and best practice. In addition, the industry often uses static tests to make major waste management plans rather than the more realistic, long-term, field-based kinetic tests that have not received much attention. Furthermore, mine waste dump facilities are susceptible to AMD partly because they tend to be constructed without strictly following the design and mine closure plans (e.g., capping, etc.).

Although AMD prediction tests are well established and have predicted AMD formation correctly in many case studies, they have also failed in many others due to their inherent limitations. For example, the simple waste classification criteria of PAF, NAF and uncertain (UC) are limited in that it does not account for parameters like the mobility of metal ions of interest at neutral pFl, effects of microorganisms, reaction rates of individual minerals, particle size, texture, climate and many others (Lottermoser, 2015).

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