Modelling the transference of trace elements between environmental compartments in abandoned mining areas

Abstract

An openly accessible cellular automaton has been developed to predict the preferential migration pathways of contaminants by surface runoff in abandoned mining areas. The site where the validation of the results of the Contaminant Mass Transfer Cellular Automaton (CMTCA) has been carried out is situated on the steep flank of a valley in the Spanish northwestern region of Asturias, at the foot of which there is a village with 400 inhabitants, bordered by a stream that flows into a larger river just outside the village. Soil samples were collected from the steep valley flank where the mine adits and spoil heaps are situated, at the foot of the valley, and in the village, including private orchards. Water and sediment samples were also collected from both surface water courses. The concentration of 12 elements, including those associated with the Cu-Co-Ni ore, were analyzed by ICP-OES (Perkin Elmer Optima 3300DV, Waltham, MA, USA) and ICP-MS (Perkin Elmer NexION 2000, Waltham, MA, USA). The spatial representation of the model’s results revealed that those areas most likely to be crossed by soil material coming from source zones according to the CMTCA exhibited higher pollution indexes than the rest. The model also predicted where the probabilities of soil mass transfer into the stream were highest. The accuracy of this prediction was corroborated by the results of trace element concentrations in stream sediments, which, for elements associated with the mineral paragenesis (i.e., Cu, Co, Ni, and also As), increased between five-and nine-fold downstream from the predicted main transfer point. Lastly, the river into which the stream discharges is also affected by the mobilization of mined materials, as evidenced by an increase of up to 700% (in the case of Cu), between dissolved concentrations of those same elements upstream and downstream of the confluence of the river and the stream.