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基于 AVS-SEM 和多元统计分析的滨海河口湿地沉积物质量综合评价—以马銮湾为例。

Integrated assessment of sediment quality in a coastal lagoon (Maluan Bay, China) based on AVS-SEM and multivariate statistical analysis.

机构信息

School of Resource and Environment Engineering, Jiangxi University of Science and Technology, 86 Hongqi Boulevard, Ganzhou, Jiangxi 341000, China.

School of Resource and Environment Engineering, Jiangxi University of Science and Technology, 86 Hongqi Boulevard, Ganzhou, Jiangxi 341000, China.

出版信息

Mar Pollut Bull. 2019 Sep;146:476-487. doi: 10.1016/j.marpolbul.2019.07.005. Epub 2019 Jul 9.

DOI:10.1016/j.marpolbul.2019.07.005
PMID:31426183
Abstract

Total metal concentrations and acid-volatile sulfide (AVS) measurements coupled with simultaneously extracted metals (SEM) were determined in heterogeneous sediments from Maluan Bay, China. Zn was the predominant component of SEM, while Cd was the least. In sediment cores, AVS increased with sediment depth, followed by a decrease with large variation, while SEM fluctuated. Multiple empirical sediment quality guidelines (SQGs) and equilibrium partitioning (EqP) approaches were applied to assess the contamination degree, sediment quality and potential risks associated with bioavailable metals, indicating that not all sediments with [SEM]-[AVS] > 0 were capable of causing toxicity because TOC is also an important metal-binding phase. In order to screen out the physicochemical variability and the complexity and large variance of datasets, multivariate statistical techniques were utilized to comprehensively reveal pollution status by visualized factor scores. Collectively, this study favors the integrative utilization of multifarious methods to scientifically diagnose the pollution characterization for sustainable coastal management.

摘要

采用总金属浓度和酸可挥发性硫化物(AVS)测量以及同时提取金属(SEM)的方法,对中国马銮湾的非均相沉积物进行了研究。SEM 中的主要成分是 Zn,而 Cd 的含量最少。在沉积物岩芯中,AVS 随深度增加而增加,随后波动下降,而 SEM 则波动变化。多种经验性沉积物质量指南(SQGs)和平衡分配(EqP)方法被用于评估与生物可利用金属相关的污染程度、沉积物质量和潜在风险,这表明并非所有 [SEM]-[AVS] > 0 的沉积物都具有毒性,因为 TOC 也是一种重要的金属结合相。为了筛选出物理化学变异性以及数据集的复杂性和大方差,利用多元统计技术通过可视化因子得分全面揭示污染状况。总的来说,这项研究有利于综合利用多种方法,科学诊断污染特征,以实现沿海地区的可持续管理。

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