Evaluation of soil heavy metals in Raniganj open-cast coal mines in India: Spatial distribution, Positive Matrix Factorization and Monte Carlo Simulation
Silvia Dutta, Manish Kumar Jain & Dheeraj Kumar.
Process Safety and Environmental Protection, 194, 1038-1055 (2025);
DOI: https://doi.org/10.1016/j.psep.2024.12.039
Abstract
Surface mining and its associated industries exhibits substantial risks to both ecosystems and human health. This study employed multiple statistical analyses, interpolation techniques, Positive Matrix Factorization model, pollution indices, and Monte Carlo Simulations. This demonstrates source identification, spatial distribution of heavy metals (Cd, Zn, Cr, Hg, As, Cu, Co, Mn, Ni, and Pb), and their consequences on native ecosystem and human environment in the Raniganj, India. During the hot and dry summer season, 108 soil samples were collected from active and inactive overburden dumps, reclaimed areas, agricultural soils, and ground control points across 11 mines. The high variance and wide concentration ranges suggest that heavy metals were introduced into the soil primarily through mining activities. PMF model revealed various heavy metal sources i. e., coal mining (69.4 %): Cr; dust settlement (1.8 %): Zn; anthropogenic sources (11.6 %): Cu; emissions from coal conveyor belts and vehicle (12 %): Pb; natural sources (4.9 %): Mn; industrial sources (37.3 %): Hg. Monte Carlo Simulation model demonstrated probabilities of carcinogenic health risks as 97.6 % (Cd), 86.1 % (Cr), and 69.9 % (As), in children but not in adults. This study uniquely help in managing pollution sources, protecting the environment, and promoting sustainable practices in industrial region.
KEYWORDS: Surface mining, Soil heavy metal, Source identification, Spatial distribution, Pollution indices, Probabilistic health risk.
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