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河流水体中砷和重金属污染的途径与风险分析:多元统计和美国环境保护局推荐的风险评估模型的应用

Pathways and risk analysis of arsenic and heavy metal pollution in riverine water: Application of multivariate statistics and USEPA-recommended risk assessment models.

作者信息

Khan Kifayatullah, Khan Muhammad Sajawal, Younas Muhammad, Yaseen Muhammad, Al-Sehemi Abdullah G, Kavil Yasar N, Su Chao, Ali Niaz, Maryam Afsheen, Liang Ruoyu

机构信息

Department of Environmental and Conservation Sciences, University of Swat, Swat 19120, Pakistan; State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.

Department of Environmental and Conservation Sciences, University of Swat, Swat 19120, Pakistan.

出版信息

J Contam Hydrol. 2025 Feb;269:104483. doi: 10.1016/j.jconhyd.2024.104483. Epub 2024 Dec 7.

Abstract

This study analyzed surface water from the River Swat, Pakistan, using inductively coupled plasma mass spectrometry, multivariate statistical techniques, and US-EPA risk assessment models to evaluate the concentrations, distribution, pathways, and potential risks of arsenic (As) and heavy metals, including chromium (Cr), manganese (Mn), cobalt (Co), nickel (Ni), copper (Cu), zinc (Zn), cadmium (Cd), mercury (Hg), and lead (Pb). The results revealed significant correlations (p ≤ 0.01) among metals that indicated common pollution sources, likely influenced by anthropogenic point and non-point activities. Along the monitored sites (S1-S10), the mass flow of ∑metals showed a dynamic pattern: progressively increasing downstream, decreasing at S6-S7, rising again at S7-S8, and then steadily declining toward S10, with Ni being the most abundant metal, followed by Cr > As> Cu > Mn > Co > Zn > Hg > Cd > Pb. The As and Heavy Metal Pollution Index (HPI), As and Heavy Metal Evaluation Index (HEI), and Pollution Index (PI) revealed variations in pollution levels, ranking the metals in the orders of Co > As> Cr > Cd > Mn > Hg > Ni > Pb > Cu > Zn, As> Cr > Ni > Hg > Cd > Co > Mn > Cu > Zn > Pb, and Hg > Ni > As> Co > Cu > Cd > Mn > Zn > Pb, respectively. However, according to the risk assessment, overall individual metal contamination in the River Swat water was below the ecological risk threshold (ERI 〈110). Where, the Chronic Daily Intakes (CDIs), Hazard Quotients (HQs), Hazard Indices (HIs), Cancer Risks (CRs), and Total Cancer Risks (TCRs) of Cr, Mn, Co, Ni, Cu, Zn, As, Cd, Hg, and Pb associated with daily river water intake and dermal contact indicate that long-term exposure to untreated river water may pose both carcinogenic and non-carcinogenic health risks to residents.

摘要

本研究采用电感耦合等离子体质谱法、多元统计技术和美国环境保护局风险评估模型,对巴基斯坦斯瓦特河的地表水进行分析,以评估砷(As)和重金属(包括铬(Cr)、锰(Mn)、钴(Co)、镍(Ni)、铜(Cu)、锌(Zn)、镉(Cd)、汞(Hg)和铅(Pb))的浓度、分布、迁移途径及潜在风险。结果显示,金属之间存在显著相关性(p≤0.01),表明存在共同污染源,可能受到人为点源和非点源活动的影响。在所监测的站点(S1 - S10)中,∑金属的质量流量呈现动态变化模式:向下游逐渐增加,在S6 - S7处减少,在S7 - S8处再次上升,然后向S10稳定下降,其中镍是含量最丰富的金属,其次是铬>砷>铜>锰>钴>锌>汞>镉>铅。砷和重金属污染指数(HPI)、砷和重金属评价指数(HEI)以及污染指数(PI)显示出污染水平的差异,金属排序分别为钴>砷>铬>镉>锰>汞>镍>铅>铜>锌、砷>铬>镍>汞>镉>钴>锰>铜>锌>铅以及汞>镍>砷>钴>铜>镉>锰>锌>铅。然而,根据风险评估,斯瓦特河水中总体单个金属污染低于生态风险阈值(ERI<110)。其中,与每日河水摄入和皮肤接触相关的铬、锰、钴、镍、铜、锌、砷、镉、汞和铅的慢性日摄入量(CDIs)、危害商数(HQs)、危害指数(HIs)、癌症风险(CRs)和总癌症风险(TCRs)表明,长期接触未经处理的河水可能对居民造成致癌和非致癌健康风险。

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