Mine waste dump planning with focus on arsenic risk mitigation based on uncertainty analysis

Mine waste dumps represent significant sources of toxic and hazardous elements, posing long-term environmental risks such as acid rock drainage and heavy metal migration, particularly over extended periods. The inherent uncertainty in the chemical composition of waste rocks, particularly for less-studied elements such as arsenic, complicates long-term waste dump management. This study investigates the uncertainty in waste rock characteristics, with a focus on arsenic, to enhance waste dump design and provide recommendations for managing the dispersion of this toxic element. Initially, the uncertainty in arsenic grade is quantified using the Sequential Gaussian Simulation method. Subsequently, a waste dump optimization model, building upon our previously developed deterministic model, is adapted to incorporate arsenic content into the design and construction of the waste dump. This approach is implemented at a gold mine. The results indicate that, while the mathematical model achieves a more homogeneous arsenic distribution within the waste dump, some cells still contain elevated concentrations due to the overall high arsenic content. The uncertainty analysis reveals that, in an optimistic scenario, approximately 557,197 tons of arsenic would be deposited, whereas, in a pessimistic scenario, this amount could reach 747,254 tons. Finally, several strategies are proposed and discussed to reduce arsenic levels in waste dumps, aiding decision-makers.