Agricultural and Ecological Research Unit, Indian Statistical Institute, Giridih, Jharkhand, 815301, India.
Department of Plant Pathology, The Ohio State University, Columbus, OH, 43210, USA.
Environ Geochem Health. 2024 Aug 27;46(10):400. doi: 10.1007/s10653-024-02177-y.
The contribution of mica mining activities to fluoride (F) contamination in groundwater has been chased in this study. For the purpose, groundwater samples (n = 40, replicated thrice) were collected during the post-monsoons (September-October) from a mica mining area in the Tisri block of Giridih district, Jharkhand. The study has employed a synergy of classical aquifer chemistry, statistical approaches, different indices, Self-Organising Maps (SOM), and Sobol sensitivity index (SSI) to unveil the underlying aquifer chemistry, identify the impacts of mining activities on groundwater quality and its associated health hazard. Fluoride levels varied from 0.34 to 2.8 ppm, with 40% of samples exceeding the World Health Organization's permissible limit (1.5 ppm). Physicochemical analysis revealed significant differences in electrical conductivity (EC), total dissolved solids (TDS), total hardness (TH) and major ion concentrations (Na, HCO, Ca) between fluoride-contaminated (FC) and fluoride-uncontaminated (FU) groups. Higher Na and HCO associated with F contaminated samples, were indicative of silicate weathering and carbonate dissolution as primary geogenic sources for this ion. Health risk assessment (HRA) revealed hazard quotient (HQ) values exceeding unity, indicating non-carcinogenic risks, particularly for children in most samples from group FC. The mean Water Quality Index (WQI) of FC group (156.76 ± 7.30) was significantly higher (p < 0.05) than group FU indicating of its unsuitability. SOM could accurately (80%) predict presence of fluoride in water samples based on other major ions. Sobol sensitivity analysis successfully identified fluoride concentration and body weight as most impactful parameters affecting human health. The integration of advanced modelling techniques and geospatial analysis as Inverse Distance Weightage (IDW) maps has provided a robust framework for ongoing groundwater quality monitoring in mining-affected regions and can help proactive intervention in risk-prone areas. Overall, this comprehensive study takes us a step ahead towards ensuring safe drinking water access for the global community.
本研究探讨了云母开采活动对地下水氟（F）污染的贡献。为此，在印度恰尔肯德邦吉里迪区蒂斯里区块的云母开采区，在后季风期（9 月至 10 月）采集了 40 个地下水样本（重复 3 次）。该研究采用了经典含水层化学、统计方法、不同指数、自组织映射（SOM）和 Sobol 敏感性指数（SSI）的协同作用，揭示了含水层化学的潜在特征，确定了采矿活动对地下水质量及其相关健康危害的影响。氟化物含量从 0.34 到 2.8ppm 不等，有 40%的样本超过了世界卫生组织规定的限值（1.5ppm）。理化分析表明，受氟污染（FC）和不受氟污染（FU）组之间的电导率（EC）、总溶解固体（TDS）、总硬度（TH）和主要离子浓度（Na、HCO3、Ca）有显著差异。与氟污染样本相关的较高 Na 和 HCO3表明，硅酸盐风化和碳酸盐溶解是该离子的主要地球成因来源。健康风险评估（HRA）显示，危险商数（HQ）值超过 1，表明存在非致癌风险，尤其是 FC 组中大多数样本中的儿童。FC 组的平均水质指数（WQI）（156.76±7.30）显著高于 FU 组（p<0.05），表明其不适合饮用。SOM 可以根据其他主要离子准确（80%）预测水样中氟的存在。Sobol 敏感性分析成功确定了氟浓度和体重是影响人类健康的最具影响力的参数。先进建模技术和地理空间分析（如反距离权重（IDW）图）的整合为受采矿影响地区的地下水质量监测提供了一个强大的框架，并有助于在高风险地区进行主动干预。总的来说，这项综合研究使我们朝着确保全球社区获得安全饮用水的目标迈进了一步。
