Conference Agenda

Acid mine drainage (AMD) is widely recognized as one of the most significant environmental challenges in the mining industry. AMD is characterized by higher concentrations of metals and sulfate and an acidic pH.

Several techniques are commonly employed to treat AMD, including raising the pH by adding alkaline materials, precipitating dissolved metals by introducing sulfide reagents, and using biological processes.

Superabsorbent polymers (SAPs), known for their high water absorption and retention capacity, offer a promising alternative for treating mining effluents due to their unique properties. In this study, synthetic metal solutions were used to assess the effectiveness of SAPs in effluent treatment.

Investigation results demonstrate the effectiveness of SAPs in sequestering heavy metal ions. The sequestration capacity of metals is influenced by pH, the ionic radius of the element, and the availability of binding sites in the SAPs.

To better understand the relationship between metal ion absorption rates and these chemical factors, an equation has been proposed that considers both ionic radii and the concentrations of the elements analyzed. This equation provides highly accurate predictions of the metallic ion absorption rate. However, further validation using data not included in the equation's development is required to generalize its applicability.

Mine waters exhibit variable compositions with a range of pH and dissolved solutes. Waters with pH less than six are referred to as acid mine drainage (AMD), and waters with pH greater than six are classified as saline drainage (SD) or neutral mine drainage (NMD) depending on the concentration of dissolved solutes. Plumlee et al., (1999) developed a set of trace elements that when compared with pH, enabled definition of mine waters into twelve categories and later developed this into a geo-environmental model using mine sites from a limited geography within North America. This study uses a wider international sample-set of surface water drainage from mines to assess whether this model has global applicability.

Hydrochemical data from thirty-eight mines located on four continents were plotted onto the Plumlee model to assess the boundaries of each field. Early geology-based classification schemes (e.g. Cox and Singer, 1986) have evolved into mineral deposit models that classify deposits using geologic, geophysical and geochemical characteristics that consider the overall ‘geodynamic’ context of ore deposits (Gessner et al., 2018).

The results of this study correlate well with the fields set out in the original Ficklin diagrams from the 1990s. This approach helps move towards more refined mine water quality predictions early on in a project development and allows easy revision of the model throughout the project life cycle. These models can be used as an improved predictive tool by researchers including consultants, mining professionals, regulators and other stakeholders.