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<p>Fresh water aquifers adjoining the geothermal resources are often vulnerable to trace metal contamination and associated risks to human health. Realistic assessment of health hazard as well as source apportionment play a vital role in designing suitable remedial actions, which can be better achieved through application of probabilistic methods using Monte Carlo Simulations (MCS) and multivariate based Absolute Principal Component Score-Multiple Linear Regression (APCS-MLR) methods. In this study, a comprehensive analysis of groundwater quality was performed using multiple pollution indices (HPI, HEI, Cd, IWPI), MCS and APCS-MLR methods. Chemical results indicate that TDS, F<sup>−</sup> and NO<sub>3</sub><sup>−</sup> showed exceedances in 19%, 38% and 23% of the samples respectively while trace metals (Fe, Mn, Pb, and As) showed higher exceedances compared to WHO limits. Pollution indices suggest that 73% of the samples fall under low contamination and the rest (27%) in high risk category. MCS infers both non-carcinogenic and carcinogenic health risks to different age groups mainly due to arsenic and lead. Sensitivity analysis indicates body weight, ingestion rate as most influential followed by arsenic concentration. High geochemical mobility is noticed for Zn and Co while Al and Ni are largely immobile. Both relative mobility index and APCS-MLR model output point to rock weathering and geothermal sources as the key contributors accounting for 19.8% of the trace metal load in this region. This integrative approach underscores the need for regular monitoring and implementation of policies for safeguarding public health in this region.</p>

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Geochemical study of trace metals and health risk assessment in Indian geothermal aquifer using health indices, MCS and APCS-MLR

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月5日

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  • Tirumalesh Keesari,
  • Bhumika Kumari,
  • Saha Dauji,
  • Annadasankar Roy,
  • Asmita Maitra,
  • Saibal Gupta,
  • Banajarani Panda,
  • Diksha Pant,
  • Diana Anoubam Sharma

摘要

Fresh water aquifers adjoining the geothermal resources are often vulnerable to trace metal contamination and associated risks to human health. Realistic assessment of health hazard as well as source apportionment play a vital role in designing suitable remedial actions, which can be better achieved through application of probabilistic methods using Monte Carlo Simulations (MCS) and multivariate based Absolute Principal Component Score-Multiple Linear Regression (APCS-MLR) methods. In this study, a comprehensive analysis of groundwater quality was performed using multiple pollution indices (HPI, HEI, Cd, IWPI), MCS and APCS-MLR methods. Chemical results indicate that TDS, F− and NO3− showed exceedances in 19%, 38% and 23% of the samples respectively while trace metals (Fe, Mn, Pb, and As) showed higher exceedances compared to WHO limits. Pollution indices suggest that 73% of the samples fall under low contamination and the rest (27%) in high risk category. MCS infers both non-carcinogenic and carcinogenic health risks to different age groups mainly due to arsenic and lead. Sensitivity analysis indicates body weight, ingestion rate as most influential followed by arsenic concentration. High geochemical mobility is noticed for Zn and Co while Al and Ni are largely immobile. Both relative mobility index and APCS-MLR model output point to rock weathering and geothermal sources as the key contributors accounting for 19.8% of the trace metal load in this region. This integrative approach underscores the need for regular monitoring and implementation of policies for safeguarding public health in this region.