利用机器学习方法评估潜在有毒元素对人类健康造成的风险并预测地下水污染情况

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC ACS Applied Electronic Materials Pub Date : 2024-02-01 DOI:10.1016/j.jconhyd.2024.104307
Md Galal Uddin , Md Hasan Imran , Abdul Majed Sajib , Md Abu Hasan , Mir Talas Mahammad Diganta , Tomasz Dabrowski , Agnieszka I. Olbert , Md Moniruzzaman
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引用次数: 0

摘要

位于孟加拉国 Ishwardi 的 Rooppur 核电厂(RNPP)计划于 2024 年投入运行,因此,RNPP 附近地区的环境监测,尤其是水资源管理方面的环境监测,正得到科学界的充分重视。然而,由于在 RNPP 建设初期所做的工作很少,因此大量缺乏文献资料以及早些年的环境数据集。因此,本研究旨在评估 2014-2015 年期间地下水中的潜在有毒元素 (PTE) 污染及其对 RNPP 附近居民的相关健康风险。为实现研究目的,研究人员按季节(旱季和雨季)从 9 个采样点采集地下水样本,然后分析水质指标,如温度 (Temp.)、pH 值、电导率 (EC)、溶解固体总量 (TDS)、总硬度 (TH) 以及 PTEs,包括铁 (Fe)、锰 (Mn)、铜 (Cu)、铅 (Pb)、铬 (Cr)、镉 (Cd) 和砷 (As)。本研究采用新开发的均方根水质指数模型来评估地下水中 PTEs 的污染情况,并利用人类健康风险评估模型来量化 PTEs 的毒性风险。在大多数采样点,雨季的 PTEs 浓度高于旱季,铁、锰、镉和砷的浓度超过了饮用水指导限值。RMS 评分大多将地下水的 PTEs 污染情况归类为 "一般"。非致癌风险(以危害指数-HI 表示)显示,在旱季和雨季,分别约有 44% 和 89% 的成人样本以及 67% 和 100% 的儿童样本超过了美国环保局设定的阈值限值(HI >1),具有经口途径的风险。此外,在整个研究期间,计算得出的儿童累积 HI 分数均高于成人。就持久性有机污染物的致癌风险(CR)而言,风险程度按照铬、砷、镉的模式下降。虽然目前的研究是基于旧的数据集,但研究结果可作为监测的基线,以减少发电厂未来的有害影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Assessment of human health risk from potentially toxic elements and predicting groundwater contamination using machine learning approaches

The Rooppur Nuclear Power Plant (RNPP) at Ishwardi, Bangladesh is planning to go into operation within 2024 and therefore, adjacent areas of RNPP is gaining adequate attention from the scientific community for environmental monitoring purposes especially for water resources management. However, there is a substantial lack of literature as well as environmental datasets for earlier years since very little was done at the beginning of the RNPP's construction phase. Therefore, this study was conducted to assess the potential toxic elements (PTEs) contamination in the groundwater and its associated health risk for residents at the adjacent part of the RNPP during the year of 2014–2015. For the purposes of achieving the aim of the study, groundwater samples were collected seasonally (dry and wet season) from nine sampling sites and afterwards analyzed for water quality indicators such as temperature (Temp.), pH, electrical conductivity (EC), total dissolved solid (TDS), total hardness (TH) and for PTEs including Iron (Fe), Manganese (Mn), Copper (Cu), Lead (Pb), Chromium (Cr), Cadmium (Cd) and Arsenic (As). This study adopted the newly developed Root Mean Square water quality index (RMS-WQI) model to assess the scenario of contamination from PTEs in groundwater whereas the human health risk assessment model was utilized to quantify the risk of toxicity from PTEs. In most of the sampling sites, PTEs concentration was found higher during the wet season than the dry season and Fe, Mn, Cd and As exceeded the guideline limit for drinking water. The RMS score mostly classified the groundwater in terms of PTEs contamination into “Fair” condition. The non-carcinogenic risks (expressed as Hazard Index-HI) revealed that around 44% and 89% of samples for adults and 67% and 100% of samples for children exceeded the threshold limit set by USEPA (HI > 1) and possessed risks through the oral pathway during dry and wet season, respectively. Furthermore, the calculated cumulative HI score was found higher for children than the adults throughout the study period. In terms of carcinogenic risk (CR) from PTEs, the magnitude of risk decreased following the pattern of Cr > As > Cd. Although the current study is based on old dataset, the findings might serve as a baseline for monitoring purposes to reduce future hazardous impact from the power plant.

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