TITLE:
Use of Multivariate Statistics in Order to Understand the Flow of Acid Rock Drainage from an Abandoned Mining Site
AUTHORS:
Mattias Bäckström, Lotta Sartz
KEYWORDS:
PCA, PHREEQC, Metals, ARD, Flowpath
JOURNAL NAME:
Journal of Environmental Protection,
Vol.7 No.3,
February
26,
2016
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.