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研究安扎利沿海湿地沉积物中的重金属污染:一种源识别的统计方法。

Investigating heavy metal pollution in Anzali coastal wetland sediments: A statistical approach to source identification.

机构信息

Faculty of Environment, College of Engineering, University of Tehran, P.O. Box 1417853111, Tehran, Iran.

Faculty of Environment, College of Engineering, University of Tehran, P.O. Box 1417853111, Tehran, Iran.

出版信息

Mar Pollut Bull. 2023 Sep;194(Pt B):115376. doi: 10.1016/j.marpolbul.2023.115376. Epub 2023 Aug 5.

Abstract

In this study, the pollution and bioavailability of heavy metals in the sediments of Anzali Wetland were measured by analyzing data from sequential chemical extraction of sediments, risk assessment code (RAC), and sediment pollution indices. The average RAC results indicated that the risk from Zn, Cr, Cu, and Hg was low, while the risk from Pb, Ni, As, and Cd was moderate. To identify the sources of heavy metal pollution in the sediments of Anzali Wetland, multivariate statistical techniques such as Pearson correlation analysis, cluster analysis (CA), and principal component analysis (PCA) were employed. The results of the statistical analyses at a high significance level revealed that Zn, Cr, Cu, Pb, Ni, and As were attributed to natural sources. Additionally, the statistical analyses demonstrated that the concentrations of Cd and Hg in the sediments of Anzali Wetland were influenced by non-oil organic sources and atmospheric deposition, respectively.

摘要

本研究通过对沉积物进行连续化学提取、风险评估码(RAC)和沉积物污染指数分析,测量了安扎利湿地沉积物中重金属的污染和生物可利用性。平均 RAC 结果表明,Zn、Cr、Cu 和 Hg 的风险较低,而 Pb、Ni、As 和 Cd 的风险为中等。为了确定安扎利湿地沉积物中重金属污染的来源,采用了多元统计技术,如 Pearson 相关分析、聚类分析(CA)和主成分分析(PCA)。在高显著性水平下的统计分析结果表明,Zn、Cr、Cu、Pb、Ni 和 As 来源于自然源。此外,统计分析表明,安扎利湿地沉积物中 Cd 和 Hg 的浓度分别受到非石油有机源和大气沉降的影响。

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