Reinventing the wheel - predicting acidic outflow from mines
Anita Parbhakar-Fox, Research Fellow for CRC ORE, based at the University of Tasmania, argues that new approaches to predicting the outflow of acidic water from mines are needed to reduce the significant management costs of this environmental hazard.
Ore stockpiles, exposed pit walls and mine wastes often contain abundant sulphide minerals, such as pyrite (FeS2), which can oxidise and dissolve to generate acid rock drainage (ARD) water, with the oxidation products potentially impacting on ecosystems and human health. The historic mine site of Rio Tinto in southwest Spain is a world famous example of ARD. Mining activities began in Tartessian times, around 9,000 years ago, and continued into the 19th and 20th Centuries, producing 1,600Mt of mine waste from which ARD has emanated, contributing to the environmental degradation of the downstream rivers and estuaries.
Despite the many visual examples of mine waste mismanagement, predicting ARD is usually not an aspect that is strongly embedded in the development of mineral deposits. Other aspects, such as resource evaluation and testing for beneficiation, mineral processing, and recovery attributes of ores and different ore types, take priority. However, published evidence for the consequences of failing to predict and manage ARD – for both individual operations and for the mining industry as a whole – is abundant, with costs for total worldwide liability estimated at £60bln. For large mines located in settings favourable to the generation of ARD, unplanned closure costs have frequently been in the range of £30–60m, and sometimes beyond. Failure to predict ARD leads to long-term impacts on ecosystem and human health, and substantial financial consequences and reputational damage to operators.
The status quo
Current approaches to ARD prediction either directly use or are modifications of the wheel approach. This recommends the use of several categories of tests, such as acid-base-accounting, whole-rock geochemistry, field and kinetic tests. Limitations of these tests are often discussed in the scientific literature, with questions raised, such as, how relevant is it for the mining industry to heavily use costly geochemical tests first developed in the 1970s? The wheel approach and its derivatives provide basic information on how best to use the tests concurrently, and while mineralogy is identified as a test category, few guidelines are given as to what type of mineralogical work is required. Furthermore, mineral texture, a factor known to significantly impact on ARD formation, is not even considered in its own right.
Another challenge is, how can best-practice ARD sampling, as recommended by the Australian Government, be achieved and accurately predicted when using costly tests and outdated protocols?
First, a logical and integrated approach must be adopted. Second, accurate small-scale, low-cost tests must be used, allowing for best practice sampling and the geological variability of the future mine waste to be examined. Based on this requirement, the geochemistry-mineralogy-texture (GMT) approach was developed. This approach comprises three stages following an initial grouping of samples based on lithological ARD characteristics.
Stage one is a mandatory pre-screening stage, which focuses on using small-scale, inexpensive geochemical and mineralogical tests as well as textural evaluations. These tests are suitable for a number of samples. Data from these are concurrently used for waste classification, allowing for samples identified as potentially acid forming or as having an acid neutralising capacity. Non-acid forming samples are not tested further, saving costs.
At stage two, the acid forming, or neutralising potential is quantified using standard geochemical tests. At stage three, the controls on sulphide oxidation are realised using advanced analytical techniques including laser-ablation, inductively coupled plasma mass spectrometry (ICPMS) and mineral liberation analysis (MLA).
Through understanding the controls, detailed ARD predictive models can be developed and their long-term geochemical behaviour understood. This approach has been tested at several mine sites in Australia, where improved waste characterisation was demonstrated. While this approach is a significant improvement to the wheel, further opportunities to improve ARD prediction and waste characterisation can be realised by integrating geometallurgical datasets.
Geometallurgy, a team-based approach performed during early life-of-mine stages, documents variability within an orebody and provides key quantitative data on the impact of geology and mineralogy on grinding, metallurgical response and metal recovery processes. Operational improvements are delivered based on increased orebody knowledge, allowing for more effective mine planning and optimisation and, overall, a more holistic approach to maximising economic returns and managing risks. The philosophy of geometallurgy can be taken further and applied to environmental characterisation, specifically for predicting and managing the risks associated with ARD.
I believe an integrated environmental geometallurgy and GMT approach should be established. This should be adopted where geometallurgical data has been collected, adding value to existing datasets and allowing for conservative ARD domaining. The challenge presented to the environmental geochemist is to examine geometallurgical data and ascertain which particular characteristics could be of use to determine ARD characteristics. Examples of applications include the use of hyperspectral data (as collected by instruments such as a HyLogger) for determining effective acid neutralisation capacity by examining carbonate mineralogy. Additionally, using mineral hardness data can provide an insight into the weathering potential of waste materials, allowing for the determination of lag-time to acid formation.
Further ARD domaining can be achieved by using these data in conjunction with sulphur assay values. Such geometallurgical methods are suitable for use on waste drill holes and will allow for a basic ARD deposit model to be compiled. Environmental geometallurgy domaining facilitates decision-making regarding that samples require in-depth GMT testing, a decision which cannot be made based on sulphur values alone (as is often attempted).
Ultimately, the mining industry needs and wants simple and accurate field ARD tests with waste classification results rapidly determined in the core shed or rock face. This requires site geologists to have an understanding of the parameters that control ARD, and to examine these as part of their routine observations.
One example of an environmental logging code is the acid rock drainage index (ARDI) that is now starting to be used by industry. It is imperative that site geologists contribute to the ARD prediction campaign in this manner. Their knowledge and observations of both the orebody and the sulphide/carbonate mineralogy can greatly assist in the selection of samples for in-depth ARD testing, and the ARDI is a simple manner by which they can collect ARD relevant data for the mines database.
To assist environmental logging, field-based tools and tests can be used, such as handheld-XRF and pH tests. However, their application has to be optimised and proven before they can be routinely implemented, and should be the focus of the industries research and development activities.
It is often said that ‘you can’t reinvent the wheel’. I disagree – we must, and we now have the opportunity to do so by using an integrated GMT and geometallurgy approach, alongside improved field tests, to bring ARD prediction into the 21st Century.