• 关键词：南黄海  重金属环境风险  多元统计  重金属来源  相关性分析

• 基金项目：中国地质调查局海洋地质保障工程专项资助项目(No.GZH201200506);国家重点基础研究发展计划(No.2013CB956500)

• 彭修强
• 江苏省有色金属华东地质勘查局, 地球化学勘查与海洋地质调查研究院, 南京 210007

• 项立辉
• 江苏省有色金属华东地质勘查局, 地球化学勘查与海洋地质调查研究院, 南京 210007

• 郭娜
• 江苏省有色金属华东地质勘查局, 地球化学勘查与海洋地质调查研究院, 南京 210007

• 孙祝友
• 江苏省有色金属华东地质勘查局, 地球化学勘查与海洋地质调查研究院, 南京 210007

• 张鹏程
• 江苏省有色金属华东地质勘查局, 地球化学勘查与海洋地质调查研究院, 南京 210007

• 摘要：基于2012年夏季对南黄海南部海域的调查资料,分析了表层沉积物中7种重金属元素的含量分布特征;采用多元统计分析,揭示了研究区表层沉积物重金属污染的主要来源及各元素之间的相关性;应用地质累积指数法和Hakanson潜在生态风险指数法对重金属元素进行了污染及风险分析.结果表明:Cd、Pb的含量均符合国标规定的一类沉积物标准,Zn、Cu、Cr在绝大部分站位也都低于国标规定的一类沉积物的最高标准,仅在个别站位处达到二类或三类沉积物标准;除Cr、Cd、Mn外,其余各重金属与Al₂O₃、平均粒径之间有显著的相关性,表明它们均以自然来源为主,并受到沉积物粒度的控制,遵循"元素的粒度控制律";Cr、Cd、Mn与Al₂O₃的相关系数较小,表明其可能受到人为污染源的影响.通过主成分分析和聚类分析可将7种重金属元素辨识为2个主成分,PC1(Zn、Cu、Pb、Fe、Mn)为自然源因子,PC2(Cr、Cd)为工农业源因子;其中,Cr、Cd 在PC1和PC2上均具有一定的正载荷,受自然地质背景和人类活动的共同控制.地质累积指数法评价结果表明,Zn、Cu、Cd、Pb整体均处于清洁级别,而Cr则处于轻微污染水平,污染程度排序依次为Cr >Pb >Cd >Zn >Cu;潜在生态风险评价结果表明,各元素潜在生态危害等级排序依次为Cd >Pb >Cu >Cr >Zn,Cr、Zn、Cu和Pb均为低生态危害等级,Cd以低中等生态危害等级为主,局部出现较重生态危害等级,综合潜在生态风险评价为低度.

• Abstract：Spatial distribution characteristics of heavy metals (Cu, Pb, Zn, Cr, Cd, Fe, Mn) were analyzed in 414 surface sediments of the southern of the South Yellow Sea based on the summer cruise in 2012. Sources of these heavy metals and the correlation among these heavy metals and Al₂O₃, mean grain size (M_z) were revealed by multivariate analysis. Meanwhile, the ecological risk of the heavy metals in surface sediments were studied by using the methods of geoaccumulation index and Hakanson potential ecological risk assessment. The results are shown as follows: 1) The contents of Cd and Pb accord with the first type marine sedimentary evaluation criterion request in the sedimentary in every station location of study area; the contents of heavy metals of Zn, Cu and Cr in most of the areas accord with the first type marine sedimentary evaluation criterion request, except the ones from few areas are belonging to the second even third type marine sedimentary evaluation criterion request; all these heavy metals had prominent correlation with Al₂O₃ and mean grain size (M_z) except for Cr, Cd and Mn, showing that they mainly derived from natural sources, and controlled by sediment grain size. The contents and distributions of heavy metals correspond to "the rule of the granularity controlling", i.e., the finer the sediment grain size, the higher the heavy metal content. The correlation between Cr, Cd, Mn and Al₂O₃ was weak, suggesting that they were affected by anthropogenic pollution sources. 2) A total of 7 heavy metals could be classified as 2 Principal Components (PCs) by the methods of principal component analysis and cluster analysis, including PC1 (Zn, Cu, Pb, Fe and Mn), PC2 (Cr, Cd). PC1 was the factors dominated by natural sources, PC2 represented the factors from industrial and agricultural sources. Cr and Cd with a high load in different PCs might originate from the mixed sources including anthropogenic and natural sources. 3) The assessment by Geoaccumulation Index indicates that Zn, Cu, Cd and Pb are at the unpolluted level, Cr at the slightly polluted level. The pollution level of the heavy metals is: Cr >Pb >Cd >Zn >Cu. The assessment by the Potential Ecological Risk Index indicates that the potential ecological risk of study area caused by heavy metals is: Cd >Pb >Cu >Cr >Zn. The potential ecological risk of Cr, Zn, Cu and Pb is at the low level, and Cd is generally at the moderate risk level while it presents high or relatively high risk level in some parts of the study area. The integrated potential ecological risk of the heavy metals in study area is low.

• Key words：South Yellow Sea  environmental risk of heavy metals  multivariate analysis  heavy metals sources identification  correlation analysis

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