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用于地下水评估的地理空间映射和基于熵的分析,同时估计硝酸盐和氟化物暴露导致的潜在健康风险。

Geospatial mapping and entropy-based analysis for groundwater evaluation with estimation of potential health risks due to nitrate and fluoride exposure.

作者信息

Kumar Amit, Singh Anshuman

机构信息

Department of Civil Engineering, National Institute of Technology Patna, Bihar, 800005, India.

出版信息

Environ Sci Pollut Res Int. 2024 Dec;31(59):66953-66976. doi: 10.1007/s11356-024-35691-8. Epub 2024 Dec 9.

Abstract

Groundwater is a vital source of freshwater, but its quality is often compromised by various physiochemical factors. In the Mid-Gangetic Plains, there is a concerning escalation in the degradation of groundwater quality due to anthropogenic interventions. However, there remains a paucity of comprehensive knowledge concerning groundwater quality and the associated health hazards it poses. In response to this gap, the current study focuses on Nalanda district (Bihar), where 78 groundwater samples were collected across district in the month of May 2022 and their various water quality parameters were quantified as per standard methods. The adequacy of groundwater for human use was assessed using an entropy-based water quality index (EWQI), which also evaluated the potential human health risk stemming from nitrate and fluoride contamination. Furthermore, an empirical Bayesian kriging (EBK) driven geostatistical approach was utilized to predict water quality parameters at ungauged sites. The analysis of results disclosed that the ionic dominance in groundwater followed the sequence as cations Ca  > Mg, and anions HCO > SO > Cl > NO > F > PO. The concentration of NO and F exceeded the permissible BIS levels by 11.5% and 6.5% of the samples respectively. The analysis of EBK models suggested K-Bessel as the best-fit model for pH, Mg, TH, F, NO, and SO spatial interpolation while exponential EBK model for EC, Cl, and PO and whittle EBK model for TDS, Ca, and HCO spatial interpolation. Spearman's correlation analysis revealed that elevated TDS and EC levels, coupled with correlations between NO, SO, and Cl, suggest anthropogenic influences. The EWQI of the groundwater samples ranged from 36.28 to 180.80. The analysis of EWQI values revealed predominantly fair to good groundwater quality across the study area, suitable for drinking purposes. The hazard quotients for NO and F indicate that non-carcinogenic health risks are more significant with nitrate pollution. The combined health impact was assessed using total hazard index (HI), ranging from 0.20 to 3.29 for children, 0.19 to 3.05 for males, and 0.17 to 2.70 for females. The cumulative probability distribution revealed total hazard index (HI) > 1 in 41.56%, 34.62%, and 28.21% of samples for children, males, and females. The HI analysis indicated a substantially higher risk for children compared to adults within the study area. This study offers a novel combination of entropy-based water quality assessment and geostatistical EBK modeling to evaluate groundwater quality and health risks in ungauged areas. The findings provide valuable insights for improved groundwater management and health risk mitigation.

摘要

地下水是重要的淡水资源,但其质量常常受到各种物理化学因素的影响。在恒河中游平原,由于人为干预,地下水质量退化问题令人担忧地不断升级。然而,关于地下水质量及其所带来的相关健康危害,目前仍缺乏全面的认识。针对这一空白,本研究聚焦于比哈尔邦的那烂陀区,于2022年5月在全区采集了78个地下水样本,并按照标准方法对其各种水质参数进行了量化。采用基于熵的水质指数(EWQI)评估地下水供人类使用的适宜性,该指数还评估了硝酸盐和氟化物污染所带来的潜在人类健康风险。此外,利用经验贝叶斯克里金(EBK)驱动的地质统计方法来预测未测量站点的水质参数。结果分析表明,地下水中离子的主导顺序为阳离子Ca  > Mg,阴离子HCO > SO > Cl > NO > F > PO。硝酸盐和氟化物的浓度分别超过了印度标准局(BIS)规定水平的样本占比为11.5%和6.5%。对EBK模型的分析表明,K - 贝塞尔模型最适合用于pH值、镁、总硬度(TH)、氟、硝酸盐、硫酸盐的空间插值;指数EBK模型适用于电导率(EC)、氯化物和磷酸盐的空间插值;惠特尔EBK模型适用于总溶解固体(TDS)、钙和碳酸氢盐的空间插值。斯皮尔曼相关性分析显示,总溶解固体和电导率水平升高,以及硝酸盐、硫酸盐和氯化物之间的相关性,表明存在人为影响。地下水样本的EWQI值在36.28至180.80之间。对EWQI值的分析表明,研究区域内的地下水质量总体上处于中等偏上水平,适合饮用。硝酸盐和氟化物的危害商表明,非致癌健康风险中硝酸盐污染更为显著。使用总危害指数(HI)评估综合健康影响,儿童的HI范围为0.20至3.29,男性为0.19至3.05,女性为0.17至2.70。累积概率分布显示,儿童、男性和女性样本中总危害指数(HI)> 1的占比分别为41.56%、34.62%和28.21%。HI分析表明,研究区域内儿童面临的风险明显高于成年人。本研究提供了一种基于熵的水质评估和地质统计EBK建模相结合的新方法,用于评估未测量区域的地下水质量和健康风险。研究结果为改善地下水管理和减轻健康风险提供了有价值的见解。

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