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Pollution and health risk assessment of mine tailings contaminated soils in India from toxic elements with statistical approaches.
Chemosphere. 2023 May; 324:138267.C

Abstract

The rapid mining activities of mica mines in Giridih district, India, have led to toxic metal pollution of agricultural soil. This is a key concern for environmental risk and human health. 63 top soil samples were collected at a distance of 10 m (Zone 1), 50 m (Zone 2), and 100 m (Zone 3) from near 21 mica mines with agriculture fields. The mean concentration of total and bio-available toxic elements (TEs - Cr, Ni, Pb, Cu, Zn, and Cd) was higher in zone 1 across three zones. The Positive matrix factorization model (PMF) and Pearson Correlation analysis were used to identify waste mica soils with TEs. Based on PMF results, Ni, Cr, Cd, and Pb were the most promising pollutants and carried higher environmental risks than the other TEs. Using the self-organizing map (SOM), zone 1 was identified as a high-potential source of TEs. Soil quality indexes for TEs risk zone 1 were found to be higher across three zones. Based on the health risk index (HI), children are more adversely affected than adults. Monte Carlo simulations (MCS) model and sensitivity analysis of total carcinogenic risk (TCR), children were more affected by Cr and Ni than adults through ingestion exposure pathways. Finally, a geostatistical tool was developed to predict the spatial distribution patterns of TEs contributed by mica mines. In a probabilistic assessment of all populations, non-carcinogenic risks appeared to be negligible. The fact that there is a TCR can't be ignored, and children are more likely to develop it than adults. Mica mines with TEs contamination were found to be the most significant anthropogenic contributor to health risks based on source-oriented risk assessment.

Authors+Show Affiliations

Agricultural and Ecological Research Unit, Indian Statistical Institute, Giridih, Jharkhand, 815301, India.Agricultural and Ecological Research Unit, Indian Statistical Institute, Giridih, Jharkhand, 815301, India.Agricultural and Ecological Research Unit, Indian Statistical Institute, Giridih, Jharkhand, 815301, India; Department of Mathematics, Institute of Chemical Technology, Mumbai, India.School of Science, Engineering & Environment, University of Sulford, Manchester, M5 4WT, UK.Agricultural and Ecological Research Unit, Indian Statistical Institute, Giridih, Jharkhand, 815301, India.Agricultural and Ecological Research Unit, Indian Statistical Institute, Giridih, Jharkhand, 815301, India. Electronic address: pradip.bhattacharyya@gmail.com.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

36871802

Citation

Ghosh, Saibal, et al. "Pollution and Health Risk Assessment of Mine Tailings Contaminated Soils in India From Toxic Elements With Statistical Approaches." Chemosphere, vol. 324, 2023, p. 138267.
Ghosh S, Banerjee S, Prajapati J, et al. Pollution and health risk assessment of mine tailings contaminated soils in India from toxic elements with statistical approaches. Chemosphere. 2023;324:138267.
Ghosh, S., Banerjee, S., Prajapati, J., Mandal, J., Mukherjee, A., & Bhattacharyya, P. (2023). Pollution and health risk assessment of mine tailings contaminated soils in India from toxic elements with statistical approaches. Chemosphere, 324, 138267. https://doi.org/10.1016/j.chemosphere.2023.138267
Ghosh S, et al. Pollution and Health Risk Assessment of Mine Tailings Contaminated Soils in India From Toxic Elements With Statistical Approaches. Chemosphere. 2023;324:138267. PubMed PMID: 36871802.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Pollution and health risk assessment of mine tailings contaminated soils in India from toxic elements with statistical approaches. AU - Ghosh,Saibal, AU - Banerjee,Sonali, AU - Prajapati,Jyoti, AU - Mandal,Jajati, AU - Mukherjee,Abhishek, AU - Bhattacharyya,Pradip, Y1 - 2023/03/03/ PY - 2022/11/28/received PY - 2023/02/09/revised PY - 2023/02/26/accepted PY - 2023/3/6/pubmed PY - 2023/3/6/medline PY - 2023/3/5/entrez KW - GIS KW - Health risk assessment KW - MCS KW - PMF KW - SOM KW - TEs SP - 138267 EP - 138267 JF - Chemosphere JO - Chemosphere VL - 324 N2 - The rapid mining activities of mica mines in Giridih district, India, have led to toxic metal pollution of agricultural soil. This is a key concern for environmental risk and human health. 63 top soil samples were collected at a distance of 10 m (Zone 1), 50 m (Zone 2), and 100 m (Zone 3) from near 21 mica mines with agriculture fields. The mean concentration of total and bio-available toxic elements (TEs - Cr, Ni, Pb, Cu, Zn, and Cd) was higher in zone 1 across three zones. The Positive matrix factorization model (PMF) and Pearson Correlation analysis were used to identify waste mica soils with TEs. Based on PMF results, Ni, Cr, Cd, and Pb were the most promising pollutants and carried higher environmental risks than the other TEs. Using the self-organizing map (SOM), zone 1 was identified as a high-potential source of TEs. Soil quality indexes for TEs risk zone 1 were found to be higher across three zones. Based on the health risk index (HI), children are more adversely affected than adults. Monte Carlo simulations (MCS) model and sensitivity analysis of total carcinogenic risk (TCR), children were more affected by Cr and Ni than adults through ingestion exposure pathways. Finally, a geostatistical tool was developed to predict the spatial distribution patterns of TEs contributed by mica mines. In a probabilistic assessment of all populations, non-carcinogenic risks appeared to be negligible. The fact that there is a TCR can't be ignored, and children are more likely to develop it than adults. Mica mines with TEs contamination were found to be the most significant anthropogenic contributor to health risks based on source-oriented risk assessment. SN - 1879-1298 UR - https://www.unboundmedicine.com/medline/citation/36871802/Pollution_and_health_risk_assessment_of_mine_tailings_contaminated_soils_in_India_from_toxic_elements_with_statistical_approaches_ DB - PRIME DP - Unbound Medicine ER -