Deciphering stone mining-induced hazardous heavy metal contamination in agricultural soils using source attribution, health-dietary risk analysis, and machine learning-driven insights

Clinical Snapshot

Key Findings

• P Value: Not reported in abstract

• Effect Size: Zone 1 vs Zone 2: Cr 308.95 vs 60.24 mg/kg (5.1-fold increase), Ni 117.11 vs 31.61 mg/kg (3.7-fold increase), Cd 4.21 vs 0.66 mg/kg (6.4-fold increase)

• Primary Outcome: Heavy metal concentrations significantly elevated in Zone 1 compared to Zone 2, with Cr, Ni, and Cd exceeding WHO/FAO thresholds

• Nnt Or Sensitivity: Hazard quotient exceeded threshold for Pb (1.59) and Cd (0.632), indicating significant health risk

• Confidence Interval: Standard deviations provided: Cr ±23.03 mg/kg (Zone 1), Ni ±16.21 mg/kg (Zone 1), Cd ±1.26 mg/kg (Zone 1)

Clinical Application

Requires sophisticated analytical capabilities and risk assessment expertise; applicable to environmental health monitoring programs Relevant to Australian mining regions, though regulatory frameworks differ; could inform TGA food safety assessments and state environmental health programs Communities living near mining operations, particularly those consuming locally grown agricultural products

Abstract

Mining activities significantly contribute to the release of hazardous heavy metals (HHMs) into agricultural soils, especially where stone extraction is intensive. This study assessed metal content, source identification, and possible health risks associated with HHMs (Cd, Pb, Cr, Cu, Ni) in stone mines affected agricultural soils of India. The results revealed that Zone 1 exhibited higher concentrations of Cr (308.95 ± 23.03 mg/kg), Ni (117.11 ± 16.21 mg/kg), and Cd (4.21 ± 1.26 mg/kg), surpasses the threshold limit set by WHO/FAO for agricultural soils. In contrast, Zone 2 had considerably lower HHMs concentrations for Cr (60.24 ± 10.68 mg/kg), Ni (31.61 ± 7.52 mg/kg) and Cd (0.66 ± 0.13 mg/kg). Geospatial distribution and self-organizing map (SOM) indicated spatial clustering of HHMs, with elevated concentrations centered in the southern part of the study area. Positive matrix factorization showed that geogenic sources and mining activities affect significantly to HHMs pollution. Monte Carlo simulation revealed that children are more prone to exposure to HHMs than adults, with ingestion identified as the primary exposure route. Hazard quotient values calculated from free ion activity model exceeded the threshold limit for Pb (1.59E+00) and Cd (6.32E-01). Severity adjustment margin of exposure highlighted severe human health risk for Cr and Ni. Random forest analysis indicated that bioavailable HHMs significantly influence the accumulation of metals in rice tissues which elevating dietary risk. The integration of robust statistical tools offers insights into the dynamics of HHMs contamination and provide policymakers and environmental scientists with useful information to mitigate the potential risks caused by mining on nearby agricultural lands.

References

1. 1.Acharya, A., Tunga, C., Banerjee, S., Basu, R., Ghosh, S., Mondal, G., Kumar, S., Chakraborty, S., Gorai, G., Tripathi, S., & Bhattacharyya, P. (2026). Deciphering stone mining-induced hazardous heavy metal contamination in agricultural soils using source attribution, health-dietary risk analysis, and machine learning-driven insights. Environmental Geochemistry and Health. https://doi.org/10.1002/ieam.4230