The efficient applications of native flora for phytorestoration of mine tailings: a pan-global survey

Mine tailings are the discarded materials resulting from mining processes after minerals have been extracted. They consist of leftover mineral fragments, excavated land masses, and disrupted ecosystems. The uncontrolled handling or discharge of tailings from abandoned mine lands (AMLs) poses a threat to the surrounding environment. Numerous untreated mine tailings have been abandoned globally, necessitating immediate reclamation and restoration efforts. The limited feasibility of conventional reclamation methods, such as cost and acceptability, presents challenges in reclaiming tailings around AMLs. This study focuses on phytorestoration as a sustainable method for treating mine tailings. Phytorestoration utilizes existing native plants on the mine sites while applying advanced principles of environmental biotechnology. These approaches can remediate toxic elements and simultaneously improve soil quality. The current study provides a global overview of phytorestoration methods, emphasizing the specifics of mine tailings and the research on native plant species to enhance restoration ecosystem services.

Estimation of radon diffusivity tensor for fractured rocks in cave mines using a discrete fracture network model

This study develops a numerical model for predicting radon effective diffusivity tensor for fractured rocks using a two dimensional discrete fracture network (DFN) model. This is motivated by the limitations of existing techniques in predicting the radon diffusion coefficient for the fractured zones of cave mines. These limitations include access to the fractured zones for the purpose of conducting field studies as well as replication of the degree of fracturing in these zones for laboratory studies. The caving of a rock mass involves the fracturing and breaking of intact and naturally fractured rock, which creates migration pathways for radon gas trapped within uranium-rich rock. Therefore, this study develops a stochastic DFN model with equations derived from radon transport to predict diffusivity. Our simulation results reveal the establishment of a representative elementary volume (REV) for diffusivity tensor; approximately equal principal and cross diffusivity magnitudes for each of the DFN domain; a range of diffusivity with porosity (calculated based on the fractures in the domain); and a significant effect of fracture density on diffusivity tensor. These results are essential in developing proactive measures for mitigation of radon gas in cave mines.