Appraisal of pollution and health risks associated with coal mine contaminated soil using multimodal statistical and Fuzzy-TOPSIS approaches.

Abstract

The present study assesses the concentration, probabilistic risk, source classification, and dietary risk arising from heavy metal (HMs) pollution in agricultural soils affected by coal mining in eastern part of India. Analyses of soil and rice plant indicated significantly elevated levels of HMs beyond the permissible limit in the contaminated zones (zone 1: PbSoil: 108.24 ± 72.97, CuSoil: 57.26 ± 23.91, CdSoil: 8.44 ± 2.76, CrSoil: 180.05 ± 46.90, NiSoil: 70.79 ± 25.06 mg/kg; PbGrain: 0.96 ± 0.8, CuGrain: 8.6 ± 5.1, CdGrain: 0.65 ± 0.42, CrGrain: 4.78 ± 1.89, NiGrain: 11.74 ± 4.38 mg/kg. zone 2: PbSoil: 139.56 ± 69.46, CuSoil: 69.89 ± 19.86, CdSoil: 8.95 ± 2.57, CrSoil: 245.46 ± 70.66, NiSoil: 95.46 ± 22.89 mg/kg; PbGrain: 1.27 ± 0.84, CuGrain: 7.9 ± 4.57, CdGrain: 0.76 ± 0.43, CrGrain: 8.6 ± 1.58, NiGrain: 11.50 ± 2.46 mg/kg) compared to the uncontaminated zone (zone 3). Carcinogenic and non-carcinogenic health risks were computed based on the HMs concentration in the soil and rice grain, with Pb, Cr, and Ni identified as posing a high risk to human health. Monte Carlo simulation, the solubility-free ion activity model (FIAM), and severity adjusted margin of exposure (SAMOE) were employed to predict health risk. FIAM hazard quotient (HQ) values for Ni, Cr, Cd, and Pb were > 1, indicating a significant non-carcinogenic risk. SAMOE (risk thermometer) results for contaminated zones ranged from low to moderate risk (CrSAMOE: 0.05, and NiSAMOE: 0.03). Fuzzy-TOPSIS and variable importance plots (from random forest) showed that Ni and Cr were mostly responsible for the toxicity in the rice plant, respectively. A self-organizing map for source classification revealed common origin for the studied HMs with zone 2 exhibiting the highest contamination. The positive matrix factorization model for the source apportionment identified coal mining and transportation as the predominant sources of HMs. Spatial distribution analysis indicated higher contamination near mining sites as compared to distant sampling sites. Consequently, this study will aid environmental scientists and policymakers controlling HM pollution in agricultural soils near coal mines.