Environmental pollution and depth distribution of metal(loid)s and rare earth elements in mine tailing

The concern about the environmental impacts of mining waste due to its high concentrations of heavy metals is a widespread aspect worldwide, however, the presence and relationship of these metals with rare earth elements (REEs) has been little studied. In addition, the evaluation of the degree of contamination by REEs and their distribution in mining waste has not been widely evaluated. Therefore, the objective of this study is to evaluate the depth distribution, relationship and pollution of metal(loid)s and REEs in a mine tailing composed by sludge and gravimetric waste, which was divided in four units according their morphology and location. For this purpose, twenty-two surface samples were collected in two depths according with the waste layers (sludge on surface and gravimetric waste in deep), also two mechanical drills (6-10 m depth) were performed. Total concentration of 29 metal(loid)s and REEs, and physicochemical properties of the wastes were determined. Principal component analysis and cluster analysis were used to evaluate the elements association and relationship, and enrichment factors of elements were calculated to determine the degree of pollution. The results indicated that all waste materials have a high acidity and low or medium salinity. Moreover, the acidity decreases with increasing depth, which resulted in the precipitation of studied elements and reduction of their mobility, however the most predominant particle sizes were the coarsest ones (sand) promoting water infiltration. There were no significant differences in total concentrations of metal(loid)s and REEs between the sludge and gravimetric waste, indicating that the treatment process of the ore is not a key factor in metals and REEs concentrations in the wastes. Results showed that concentrations of As, Cd, Cu, Pb, Fe, Al, Mn, Mo and Zn exceeded the limits to consider soil as contaminated, and therefore control and management actions should be implemented to decrease the potential environmental and health risks. Finally, results showed that multivariate analysis, either PCA or cluster analysis, is a good tool to study the relationships between heavy metals and REEs, since allowed to identify mine activity and natural enrichment as the main sources of these elements.