| 运用多元统计方法识别浙北海域两个典型港湾的水质状况 |
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| 引用本文： | 叶然,刘莲,王琼,叶仙森,曹维,何琴燕,蔡燕红.运用多元统计方法识别浙北海域两个典型港湾的水质状况[J].海洋学报(英文版),2017,36(2):1-10. |
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| 作者姓名： | 叶然 刘莲 王琼 叶仙森 曹维 何琴燕 蔡燕红 |
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| 作者单位： | 国家海洋局宁波海洋环境监测中心站, 宁波 315012;宁波大学海洋学院, 宁波 315211,国家海洋局宁波海洋环境监测中心站, 宁波 315012,国家海洋局宁波海洋环境监测中心站, 宁波 315012,国家海洋局宁波海洋环境监测中心站, 宁波 315012;宁波大学海洋学院, 宁波 315211,国家海洋局宁波海洋环境监测中心站, 宁波 315012,国家海洋局宁波海洋环境监测中心站, 宁波 315012,国家海洋局宁波海洋环境监测中心站, 宁波 315012 |
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| 基金项目： | The National Marine Ecoenvironment Assessment Program of State Oceanic Administration. |
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| 摘 要： | 浙北海域两个典型港湾，杭州湾与象山港的水体污染状况日趋严重。本文运用多元统计方法，对分析了研究海域水体的物理及生物地球化学要素进行了量化分析。结果表明，根据物理及生物地球化学特性，层次聚类分析可将研究海域划分为两个不同的子区域；主成分分析分别在杭州湾和象山港识别出3个潜在的污染源，且陆源径流的输入、沿岸工业排污以及自然演化过程为主要源头。因此，研究海域的生态环境保护刻不容缓，应该立即采取相关措施。
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| 关 键 词： | 近岸水质 杭州湾 象山港 层次聚类分析 主成分分析 潜在污染源 |
| 收稿时间： | 2016/2/3 0:00:00 |
| 修稿时间： | 2016/3/22 0:00:00 |
Identification of coastal water quality by multivariate statistical techniques in two typical bays of northern Zhejiang Province, East China Sea |
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| YE Ran,LIU Lian,WANG Qiong,YE Xiansen,CAO Wei,HE Qinyan and CAI Yanhong.Identification of coastal water quality by multivariate statistical techniques in two typical bays of northern Zhejiang Province, East China Sea[J].Acta Oceanologica Sinica,2017,36(2):1-10. |
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| Authors: | YE Ran LIU Lian WANG Qiong YE Xiansen CAO Wei HE Qinyan and CAI Yanhong |
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| Institution: | 1.Marine Environmental Monitoring Centre of Ningbo, State Oceanic Administration(SOA), Ningbo 315012, China;School of Marine Sciences, Ningbo University, Ningbo 315211, China2.Marine Environmental Monitoring Centre of Ningbo, State Oceanic Administration(SOA), Ningbo 315012, China |
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| Abstract: | The Hangzhou Bay (HZB) and Xiangshan Bay (XSB), in northern Zhejiang Province and connect to the East China Sea (ECS) were considerably affected by the consequence of water quality degradation. In this study, we analyzed physical and biogeochemical properties of water quality via multivariate statistical techniques. Hierarchical cluster analysis (HCA) grouped HZB and XSB into two subareas of different pollution sources based on similar physical and biogeochemical properties. Principal component analysis (PCA) identified three latent pollution sources in HZB and XSB respectively and emphasized the importance of terrestrial inputs, coastal industries as well as natural processes in determining the water quality of the two bays. Therefore, proper measurement for the protection of aquatic ecoenvironment in HZB and XSB were of great urgency. |
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| Keywords: | coastal water quality Hangzhou Bay Xiangshan Bay hierarchical cluster analysis principal component analysis latent pollution sources |
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