Modelling the Transference of Trace Elements between Environmental Compartments in Abandoned Mining Areas

Area of Science:

• Environmental Science
• Geochemistry
• Computational Modeling

Background:

• Abandoned mining sites pose risks of contaminant migration.
• Surface runoff is a key pathway for contaminant dispersal.
• Predictive models are needed to assess and mitigate mining-related pollution.

Purpose of the Study:

• To develop and validate an openly accessible cellular automaton for predicting contaminant migration pathways.
• To assess the risk of soil and element transfer from mining areas to downstream environments.
• To provide a tool for managing environmental risks in abandoned mining regions.

Main Methods:

• Development of the Contaminant Mass Transfer Cellular Automaton (CMTCA).
• Field validation using soil, water, and sediment sampling in an abandoned mining area.
• Analysis of 12 elements (including Cu, Co, Ni, As) using ICP-OES and ICP-MS.
• Spatial analysis of model predictions against measured pollution indexes and trace element concentrations.

Main Results:

• The CMTCA successfully identified areas with higher pollution indexes.
• Model predictions of soil mass transfer into streams were corroborated by increased trace element concentrations (5-9 fold) in stream sediments.
• Downstream river concentrations showed significant increases (up to 700% for Cu) due to stream discharge.

Conclusions:

• The CMTCA is an effective tool for predicting contaminant migration pathways from abandoned mines.
• The model aids in identifying areas vulnerable to soil erosion and element mobilization.
• Findings highlight the environmental impact of mining activities on surface and river water quality.