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基于受体模型的孟加拉国受工业影响河流系统沉积物中金属的来源和风险评估。

Receptor model-oriented sources and risks evaluation of metals in sediments of an industrial affected riverine system in Bangladesh.

机构信息

Key Laboratory of Mountain Surface Processes and Ecological Regulation, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, Sichuan, China; University of Chinese Academy of Sciences, Beijing 100049, China.

School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China.

出版信息

Sci Total Environ. 2022 Sep 10;838(Pt 1):156029. doi: 10.1016/j.scitotenv.2022.156029. Epub 2022 May 17.

Abstract

Toxic metals in river sediments may represent significant ecological concerns, although there has been limited research on the source-oriented ecological hazards of metals in sediments. Surface sediments from an industrial affected Rupsa River were utilized in this study to conduct a complete investigation of toxic metals with source-specific ecological risk assessment. The findings indicated that the average concentration of Ni, Cr, Cd, Zn, As, Cu, Mn and Pb were 50.60 ± 10.97, 53.41 ± 7.76, 3.25 ± 1.73, 147.76 ± 36.78, 6.41 ± 1.85, 59.78 ± 17.77, 832.43 ± 71.56 and 25.64 ± 7.98 mg/kg, respectively and Cd, Ni, Cu, Pb and Zn concentration were higher than average shale value. Based on sediment quality guidelines, the mean effective range median (ERM) quotient (1.29) and Mean probable effect level (PEL) quotient (2.18) showed medium-high contamination in sediment. Ecological indexes like toxic risk index (20.73), Nemerow integrated risk index (427.59) and potential ecological risk index (610.66) posed very high sediment pollution. The absolute principle component score-multiple linear regression (APCS-MLR) and positive matrix factorization (PMF) model indicated that Zn (64.21%), Cd (51.58%), Cu (67.32%) and Ni (58.49%) in APCS-MLR model whereas Zn (49.5%), Cd (52.7%), Cu (57.4%) and Ni (44.6%) in PMF model were derived from traffic emission, agricultural activities, industrial source and mixed sources. PMF model-based Nemerow integrated risk index (NIRI) reported that industrial emission posed considerable and high risks for 87.27% and 12.72% of sediment samples. This work will provide a model-based guidelines for identifying and assessing metal sources which would be suitable for mitigating future pollution hazards in Riverine sediments in Bangladesh.

摘要

河流沉积物中的有毒金属可能是一个重大的生态问题,但对于沉积物中金属的基于源的生态危害,研究还很有限。本研究利用受工业影响的鲁普萨河的表层沉积物,对有毒金属进行了全面调查,并进行了基于源的生态风险评估。研究结果表明,镍、铬、镉、锌、砷、铜、锰和铅的平均浓度分别为 50.60 ± 10.97、53.41 ± 7.76、3.25 ± 1.73、147.76 ± 36.78、6.41 ± 1.85、59.78 ± 17.77、832.43 ± 71.56 和 25.64 ± 7.98mg/kg,镉、镍、铜、铅和锌的浓度高于平均页岩值。根据沉积物质量指南,平均有效范围中位数 (ERM) 商 (1.29) 和平均可能效应水平 (PEL) 商 (2.18) 表明沉积物中存在中高水平的污染。生态指数如毒性风险指数 (20.73)、内梅罗综合风险指数 (427.59) 和潜在生态风险指数 (610.66) 表明沉积物受到很高的污染。绝对主成分得分多元线性回归 (APCS-MLR) 和正矩阵因子分解 (PMF) 模型表明,APCS-MLR 模型中 Zn(64.21%)、Cd(51.58%)、Cu(67.32%)和 Ni(58.49%)以及 PMF 模型中 Zn(49.5%)、Cd(52.7%)、Cu(57.4%)和 Ni(44.6%)主要来自交通排放、农业活动、工业源和混合源。基于 PMF 模型的内梅罗综合风险指数 (NIRI) 报告称,工业排放对 87.27%和 12.72%的沉积物样本造成了相当大的和高的风险。这项工作将为识别和评估金属来源提供一个基于模型的指南,这将有助于减轻孟加拉国河流沉积物未来的污染危害。

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