EXPERIMENTAL AND NUMERICAL ASSESSMENT OF MULTI-SOURCE PM EMISSIONS DURING ORE MUCKING IN A POLYMETALLIC UNDERGROUND MINE ENVIRONMENT

Abstract

Particulate matter (PM) emissions during load-haul-dump (LHD) operations in underground polymetallic mines pose significant health risks to miners and contribute to environmental pollution. This study investigates the PM dispersion from various emission sources during ore handling in a polymetallic underground mine. A combined approach of field experimentation and numerical simulation was employed to evaluate the airflow dynamics and PM diffusion characteristics in the operational drift of mine, situated in East Kazakhstan. For numerical simulation, ANSYS Fluent was used to model and analyze the scenarios. Two primary operating conditions (OC-1 and OC-2) were examined. In OC-1 the airflow and PM2.5 dispersion characteristics were evaluated based on existing and simulating volumetric airflows during LHD handling ore, including condition 1 (C1) loading at the working face, condition 2 (C2) dumping at a temporary dumpsite, and condition (C3) dumping into an underground mine truck (UMT). The existing volumetric airflow in the mine drift was Q = 13 m3/s, and the simulated volumetric airflows were Q = 15, 17, and 20 m3/s to assess the impact of increased ventilation rate on PM dispersion. In OC-2 airflow patterns and PM mitigation strategies were investigated under four auxiliary ventilation system (AVS) designs. The four AVS designs were categorized based on the positioning of AVS ducts’ outlets and all four AVS designs were assessed under scenario 1 (S1) loading near the working face, and scenario 2 (S2) unloading inside the temporary dumpsite. The numerical simulation was compared with the data collected during the field experimentation to validate the results. The comparative analysis revealed the difference between experimental and simulation results for both airflow and PM was less than 10% in OC-1 and OC-2. The research delineates complex airflow patterns characterized by backflow, vortex, unsteady, and steady flow regions. Findings indicate that C2 exposes LHD operators to the highest PM concentrations, followed by C1, while C3 results in greater PM exposure for UMT operators compared to LHD operators. The study further evaluates PM diffusion characteristics across the experimental and simulated volumetric airflows and AVS designs in both OC-1 and OC-2. The analysis of the novel combination of spatial-temporal model and multiple sources of PM revealed that Q = 17 m3/s was able to reduce PM concentrations to 28%, 29%, and 20% in C1, C2, and C3, respectively. Similarly, AVS 2 showed 15% and 27% reduction of PM concentrations in S1 and S2, respectively. Moreover, correlation equations, with high coefficient values (R2), were proposed between the PM concentrations and length of the mine drift to predict the PM concentrations for similar operating conditions in underground mines. These findings provide valuable insights for developing strategies to reduce elevated PM concentrations in the mine drifts. Implementing the recommended AVS designs, and volumetric airflows can significantly enhance air quality management in underground mining environments, promoting miner health and operational efficiency.