摘要
采集青草沙水库上游水闸、垦区南北水道、库中以及库尾5个代表性区域的30个表层沉积物样品,分析了沉积物中7种重金属(Cu、Zn、Pb、Cr、Cd、As和Hg)含量和赋存形态,并评价了其潜在生态风险.结果显示,青草沙水库中部表层沉积物的重金属含量相对较高,而垦区南北水道附近重金属含量最低.表层沉积物重金属以残渣态为主,可交换态含量低.基于重金属污染的生态风险评价可知,水库表层沉积物的潜在生态风险指数值(ERI)介于55~113,属于低风险或不具潜在生态风险水平,其中上游水闸附近的生态风险相对最高,而南北水道和库尾附近的生态风险最低.
Surface sediments were collected from five representative areas—the floodgate entrance,the north and south sides of the reclamation area,and the central and downstream sections—of Qingcaosha Reservoir;the pollution characteristics and potential ecological risk of seven heavy metals(Cu,Zn,Pb,Cr,Cd,As and Hg)in these sediments were subsequently investigated.Results showed that the heavy metal content in the surface sediments showed spatial variations:the content was relatively higher in the center of the reservoir and was low in the north and south sides of the reclamation area.Heavy metals in the surface sediments,in addition,were mainly in the residual fraction;the content of heavy metals in the exchangeable fraction was extremely low.A potential ecological risk assessment indicated that the comprehensive potential ecological risk index(ERI)of the investigated heavy metals ranged from 55 to 113.The maximum ERI value was observed around the floodgate of the reservoir entrance,and low ERI values were observed at the north and south sides of the reclamation area.The ERI was lower than the threshold for low ecological risk,indicating that heavy metals in the surface sediments of the Qingcaosha Reservoir have low potential ecological risk.
作者
朱宜平
李小飞
梁霞
ZHU Yiping;LI Xiaofei;LIANG Xia(Shanghai Chengtou Raw Water Limited Company,Shanghai 200125,China;School of Geographical Sciences,Fujian Normal University,Fuzhou 350007,China;State Key Laboratory of Estuarine and Coastal Research,East China Normal University,Shanghai 200241,China)
出处
《华东师范大学学报（自然科学版）》
CAS
CSCD
北大核心
2021年第2期54-62,共9页
Journal of East China Normal University(Natural Science)
基金
国家重点研发计划(2016YFA0600900)。
关键词
重金属
沉积物
生态风险
水库
饮用水水源地
heavy metal
sediment
ecological risk
reservoir
drinking water source
