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首页> 外文期刊>Journal of Environment and Earth Science >Identification of heavy metals contamination by multivariate statistical analysis methods in Pondicherry mangroves, India
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Identification of heavy metals contamination by multivariate statistical analysis methods in Pondicherry mangroves, India

机译:通过多元统计分析方法在印度本地治里红树林中鉴定重金属污染

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摘要

Pondicherry mangroves received a heavy influx of sewage, industrial effluents; domestic and agricultural waste which consists of varying hazardous chemical and causing deleterious effects on fish and other aquatic organisms. Surface water and sediments (0-5 cm) were collected in two locations from the Pondicherry mangroves, India. Fractionation of the metals in Zn, Cu, Fe, Mn, Cd & Hg was investigated. Cluster analysis, principal componenent analysis and multidimensional scale plot were employed to evaluate tropic status of pollution for monitoring the present study stations. This study confirmed that source of water and sediment heavy metals concentration followed the hierarchy; Fe>Zn>Mn>Cu>Cd>Hg in estuary. An important observation is that, in general lowest heavy metal concentrations are found during summer, compared Post, pre and monsoon. Enrichment factor values of station 2; sediments reveal unpolluted nature and the positive correlation among Fe, Mn and other heavy metals indicate the influence of early diagnostic process.
机译:朋迪榭里红树林的污水,工业废水大量涌入。家庭和农业废物,由各种有害化学物质组成,对鱼类和其他水生生物造成有害影响。在印度本地治里红树林的两个地方收集了地表水和沉积物(0-5厘米)。研究了锌,铜,铁,锰,镉和汞中金属的分馏。采用聚类分析,主成分分析和多维比例尺图来评估热带污染状况,以监测目前的研究站。这项研究证实,水和沉积物中重金属的来源遵循层次结构。河口Fe> Zn> Mn> Cu> Cd> Hg。一个重要的观察结果是,与后期,早期和季风相比,夏季通常发现最低的重金属浓度。站2的富集系数值;沉积物显示出未受污染的性质,铁,锰和其他重金属之间的正相关性表明了早期诊断过程的影响。

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