There are significant tin reserves in the dumps and tailings from Llallagua. Currently, this waste is being processed using gravity concentration or a combination of gravity concentration with a final stage of froth flotation. A process mineralogy study of the tailings and their products after processing in Llallagua was carried out to determine the failings of the processing system in order to contribute to designing an improved new processing scheme. The mineralogy of the feed tailings, concentrate, and final tailings was determined by X-ray diffraction, scanning electron microscopy, and mineral liberation analysis. The tailings were composed of quartz, tourmaline, illite, K-feldspar, plagioclase, cassiterite, rutile, zircon, and monazite. The concentrate essentially contains cassiterite (57.4 wt.%), tourmaline, quartz, hematite, rutile and rare earth minerals, mainly monazite and minor amounts of xenotime and florencite. The concentrate contained 52–60 wt.% of SnO2 and 0.9–1.3 wt.% REE. The final tailings contained 0.23–0.37 wt.% SnO2 and 0.02 wt.% of Rare Earth Elements (REE). Only 57.6 wt.% of cassiterite from the concentrate was liberated. The non-liberated cassiterite was mainly associated with quartz, tourmaline, and rutile. The average grain size of monazite was 45 µm and 57.5 wt.% of this was liberated. In other cases, it occurs in mixed particles associated with tourmaline, quartz, cassiterite, and muscovite. To improve the sustainability of this mining activity, the concentrate grade and the metal recovery must be improved. Reducing the particle size reduction of the processed tailings would increase the beneficiation process rates. In addition, the recovery of the REE present in the concentrate as a by-product should be investigated.

No abstract

Subsidence is an important environmental and safety issue in the mining sector, yet there remain voids in knowledge in terms of management and prediction. This study aims to improve knowledge on the impact of mining operations on the surface, reducing their effect on the environment, increasing the safety of mining operations, monitoring stress behavior and predicting rock mass. Therefore, an analysis was carried out to process and analyze the measured subsidence data and, subsequently, create a numerical model to predict the surface subsidence of a case study mine. The model was developed based on a finite element method (FEM). It was achieved by considering the geological characteristics of the area, the design features of the mine, the surface subsidence measured over twelve years and the time-dependent behavior of the geological layers. The correlation obtained between the measured subsidence and the modelling results was very satisfactory, with a 90% confidence level, over the years analyzed. Hence, the efficiency of the system was confirmed, enabling the evaluation and the prediction of potential surface effects, and therefore improving the safety and environmental levels of the mining area.

No abstract