Use of Multivariate Statistics in Order to Understand the Flow of Acid Rock Drainage from an Abandoned Mining Site

Abstract

Pathways for acid rock drainage from an abandoned mining site (sulphidic ore) were investigated by analysing ground, seepage and surface waters. It was found that in affected ground and seepage waters pH was lower (average pH 5.0); sulphate higher (average 350 mg/L) and trace element concentrations were significantly increased (4330 µg/L copper and 7700 µg/L zinc) compared to surrounding waters. Multivariate statistics (principal component analysis) were used on the data set. Obtained loading plot showed a clear negative correlation between pH and parameters found at high concentrations, indicating that these parameters are found at the source term (acid rock drainage). Lead was also found in close proximity to iron and turbidity indicating that lead might be associated with particles. The score plot presented almost all samples from high concentrations to low concentrations along the first principal component (explaining 63% of the variation in the data set) indicating that dilution was an important mechanism for the decrease in concentrations as opposed to immobilisation on surfaces along the flowpath. Decrease in fluoride and sulphate along one of the suspected flowpath coincided with an increase in calcium. Through geochemical calculations it was concluded that calcite (CaCO3) dissolved along the flowpath and thus induced precipitation of gypsum (CaSO4) and fluorite (CaF2). Through a combination of PCA and geochemical calculations the most likely flowpaths for contaminated water from the abandoned mining site were presented, making it possible to prevent further negative effects on the surface water.