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丰水期巢湖水体砷和重金属污染调查 被引量:2

Arsenic and heavy metals contamination in Chaohu Lake during wet season
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摘要 目的了解巢湖表层水体中砷和重金属的污染状况。方法于2017年9月,采集巢湖表层水样,检测Cu、Pb、Cd、Hg和As的浓度,利用单因子污染评价法和美国EPA健康风险评价模型对巢湖表层水体砷和重金属污染进行评估,并进行主成分分析。结果巢湖表层水体中Cu、Pb、Cd、Hg和As浓度的中位数分别为1.55、1.21、0.08、0.15和3.83μg/L,Cu、Pb、Cd和As均达到GB 3838—2002《地表水环境质量标准》的I类指标,Hg为Ⅲ~Ⅳ类。单因子污染评价结果显示主要污染因子为Hg,超标率达86.54%。致癌物质As和Cd的年健康风险分别为5.48×10^(-6)和0.28×10^(-6),非致癌物质Cu、Pb和Hg的年健康风险分别为0.73×10^(-10)、2.03×10^(-10)和2.51×10^(-10)。第一、二、三主成分中载荷值>0.7的元素分别为Cu和As,Pb和Cd,Hg。结论本次调查的巢湖表层水体中As和Hg的污染应引起关注,As的健康风险最高。 Objective To explore the contamination characteristics of arsenic and heavy metals in Chaohu Lake. Methods The surface water samples were collected in September 2017 and the concentrations of Cu, Pb, Cd, Hg and As were determined.The single factor contamination evaluation,health risk assessment recommended by USEPA and principal component analysis were performed. Results The median concentrations of Cu,Pb,Cd,Hg and As were 1.55,1.21,0.08,0.15 and 3.83 μg/L respectively; Hg met the requirement of Grade Ⅲ-Ⅳ ruled by GB3838-2002 Environmental Quality Standard for Surface Water,the others Grade Ⅰ.The main contamiantion factor was Hg with over substandard rate of 86.54%. The annual carcinogenic risks of As and Cd were 5.48×10^(-6) and 0.28×10^(-6) respectively; The annual non-carcinogenic risk of Cu, Pb and Hg were 0.73×10^(-10), 2.03×10^(-10) and 2.51×10^(-10) respectively.The elements with factor loading〉0.7 were Cu and As in the first principal component, Pb and Cd in the second, Hg in the third. Conclusion Arsenic, with the highest health risk, and mercury as the dominant contaminats in Chaohu Lake, should be paid more attention to.
作者 施阳 彭宇豪 吴源 SHI Yang;PENG Yu-hao;WU Yuan(Department of Occupational and Environmental Health,School of Public Health,Anhui Medical University,Hefei,A nhui 230032,China)
出处 《环境与健康杂志》 CAS 北大核心 2018年第4期333-336,共4页 Journal of Environment and Health
基金 安徽高校自然科学研究重点项目(KJ2015A021) 安徽医科大学博士科研启动基金(XJ201016)
关键词 金属 健康风险评价 主成分分析法 水污染 Arsenic Metal,heavy Health risk assessment Princial component analysis Water pollution
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