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.

Acid Mine Drainage Sources and Impact on Groundwater at the Osarizawa Mine, Japan

“…Multivariate principal component analysis (PCA) was undertaken to examine major trends and interrelationships in the analysis results for each sample. The approach has been applied in many studies comparing the qualities of AMD, groundwater, and river water in mine areas [38][39][40]. Here, PCA was performed using the multivariate analysis software IBM SPSS Statistics 25 (IBM Japan, Ltd., Tokyo, Japan), and it was applied to four variables measured in situ (temperature, pH, EC, and Eh), the concentrations of seven major ions (Na + , K + , Ca 2+ , Mg 2+ , Cl − , HCO 3 − , SO 4 2− , and NO 3 − ), Si, three heavy metals (total Fe, Cu, Zn), and the isotopic ratios of δD and δ 18 O.…”

Geoecological situation in the region of the Erdenet mining and processing facility (Mongolia)

“…These technogenic elements are persistent, non-degradable and, as a rule, toxic pollutants that cause degradation of ecosystems and pose a threat to public health [6][7][8][9][10][11][12][13]. Their impact is manifested not only during the period of exploitation of mineral deposits, but also after its termination [14][15][16][17][18][19][20].…”

The Scale Effect of Coarse‐Grained Materials by Triaxial Test Simulation

“…After CA was proposed, researchers have been trying to apply it to their research and achieved many reliable results. However, most of them focused on rock bursts and rock fractures [20], soil particle size distribution [21], element migration in the soil [22], and other aspects, and only a few scholars [23][24][25] applied CA into the numerical simulation research of coarse-grained materials.…”