摘要
有效识别海州湾海域水质特征,可为其海洋环境的保护和管理提供决策参考。依据2009年12月33个站位的环境调查数据,采用聚类分析划分调查站位类别并识别其空间相似性,通过因子分析探讨海水主要污染源组成和空间分布特征。空间聚类分析显示,海州湾南北两侧污染状况存在区域差异性(南高北低),各入海河口影响区域可划分为不同类型,连云港滨海新区北侧和龙王河口北侧的污染类型与其他站位具有明显差异。因子分析表明,影响海州湾水质的主成分有4类,包括来自临洪河口的陆域污染影响(营养盐类、铜、锌),海洋工程活动对沉积物的扰动(铅、铜、锌),临洪河口和岚山港区的组合影响(溶解氧、汞)和特定区域污染(铬),其方差贡献率分别为47.4%、16.4%、13.9%和9.1%。分析结果表明,海州湾水质具有明显空间分布特性,海洋环境调查站位的布设需兼顾到不同类型区域,方能全面反映海洋水质环境现状。
This article aims at identifying the characteristics of water quality in Haizhou Bay and providing a reference for protection and management. Based on the data of environmental investigation carried out in 33 stations in December 2009,the stations were categorized according to the result of cluster analysis which was used to identify the similarities of the stations. The main pollution components and distribution characteristics of the sea water were examined with factor analysis. Spatial clustering analysis showed that the pollution status was greatly different in the northern and southern parts of Haizhou Bay. The stations could be divided into different types due to the influence from estuaries. The pollution types on the north side of Lianyungang Binhai New Area and the north side of Longwang estuary obviously differed from the other stations. Factor analysis showed that the first four components accounted for 47. 4%,16. 4%,13. 9% and9. 1% of the total variance respectively,including Linhong estuary pollution impact( nutrient salts,copper,zinc),sediment disturbance of marine engineering activities( lead,copper,zinc),the combined effect of Linhong estuary and Lanshan harbor(dissolved oxygen,mercury)and certain regional pollution impact(chromium). The results indicated that the water quality of Haizhou Bay has an obvious spatial distribution. Therefore,for the station arrangement of marine environmental survey it should take into account the regional difference in order to fully reflect the environmental status of marine water quality.
出处
《生态学杂志》
CAS
CSCD
北大核心
2014年第7期1888-1894,共7页
Chinese Journal of Ecology
基金
海洋公益性行业科研专项(201205005)资助
关键词
因子分析
聚类分析
营养盐
重金属
factor analysis
cluster analysis
nutrient
heavy metals