摘要
本文以准东地区不同区域为研究对象,共采集168个表层土壤样品测定了Zn、Cu、Cr、Hg、Pb和As等6种重金属含量,运用内梅罗综合污染指数和污染负荷指数法对该地区进行了总体污染评价,并利用多元统计学方法解析了其污染来源。研究表明:Cr、Pb、Hg和As等元素均值都超出了新疆土壤背景值,超标率在30%~100%之间,存在较严重的污染,主要受自然和人为因子的共同影响;Zn和Cu元素污染处在警戒水平,而As、Cr、Pb和Hg元素污染贡献较大,不同区域污染程度依次为A区>B区>C区;多元统计分析可知,Zn、Cu、Cr和As元素存在较高的相关性,Pb与其他元素均没有显著相关关系;Zn和Cu元素污染来自成土母质,Pb元素污染源可能与交通尾气排放和轮胎磨损有关,Cr和As元素受到了煤炭开采、工业生产和农业活动等人为污染的影响,应引起重视。
This paper takes different regions of Zhundong area as the research site,and collects the 168 soil samples for measuring the content of heavy metals including Zn、Cu、Cr、Hg、As and Pb.For evaluating soil pollution characteristics,the Nemerow pollution index(P N)and pollution load index(PLI)are calculated,and based on the multivariable statistics pollution sources of the heavy metals are analyzed.The research results indicate that the average contents of Cr,Pb,Hg and As exceed the background value,exceeding standard rate between 30%and 100%,and have the heavy pollution trend,predominantly get the influences of anthropogenic and natural pollution sources;the places where affect by Zn and Cu are under the alert level,and Cr,Pb,Hg and As contributes more for pollution,regions contamination degree in the order of region A>region B>region C;the multivariable statistical analysis showes that there are significant correlation between Zn、Cu、Cr and As,and Pb have low correlation with the other elements;Zn and Cu may originate from parent materials,and Pb may derive from emission gases and tier wear,and As and Cr may affect by anthropogenic activities such as coal mining activities,industrial production and agricultural activity.
作者
阿卜杜萨拉木·阿布都加帕尔
王宏卫
杨胜天
刘香云
ABDUSALAM Abdujappar;WANG Hongwei;YANG Shengtian;LIU Xiangyun(College of Resources and Environmental Science,Xinjiang University,Urumqi 830046,China;School of Geography and Remote Sensing,Beijing Normal University,Beijing 100875,China)
出处
《中国矿业》
北大核心
2019年第11期168-174,共7页
China Mining Magazine
基金
国家自然科学基金项目资助(编号:U1603241
51704259)
国家科技支撑计划项目资助(编号:2014BAC15B01)
关键词
土壤重金属
污染特征
多元统计学
来源解析
soil heavy metal
pollution characteristics
multivariate statistics
source analysis