摘要
重金属来源解析是防止或减少土壤重金属污染的必要前提。为此,采集并分析了环巢湖典型农业区408个表层土壤样品中As、Cd、Cr、Cu、Ni、Pb、Zn等7种重金属元素含量。地积累指数评价结果表明土壤重金属污染总体处于0~1级。综合相关性分析、主成分分析和聚类分析结果可知:(1)Cd、Cu、Pb、Zn主要来源于大气沉降、畜禽粪肥和化肥等人类活动;(2)成土母质是Cr和Ni的主要来源;(3)As有人类活动和成土母质双重来源。用绝对主成分得分-多元线性回归模型(APCS-MLR)对土壤中重金属来源进行了定量解析,解析结果与主成分分析和聚类分析结果相符。可见,多元统计分析结合APCS-MLR模型能很好地应用于土壤重金属来源解析。
Source apportionment of heavy metals is the crucial step for prevention or reduction of heavy metal pollution in soils. Thus,408 topsoil samples were collected from typically agricultural region around Chaohu Lake,and contents of As,Cd,Cr,Cu,Ni,Pb and Zn in those samples were measured. Geo-accumulation index show that the pollution level of soil heavy metals is characterized by 0-1degree. Synthesizing the results of correlation analysis,principal component analysis（ PCA） and cluster analysis（ CA）,we can conclude that（ 1） Cd,Cu,Pb and Zn mainly associate with and controlled by anthropogenic activities,such as atmospheric deposition,livestock manures and inorganic fertilizers;（ 2） Soil parent material is the main source of Cr and Ni; and（ 3） As originates from not only anthropogenic activities but also soil parent material. Then,the absolute principal component scores-multiple linear regression（ APCSMLR） was used for apportioning the source of heavy metals. Results were perfectly accordance with the results of PCA and CA. The combination of multivariate statistic approaches with APCS-MLR model could be well applied in the source apportionment of heavy metals in soils.
出处
《地球与环境》
CAS
CSCD
2017年第4期455-463,共9页
Earth and Environment
基金
安徽省公益性地质调查项目(2012-g-32)
关键词
巢湖
地积累指数
主成分分析
聚类分析
APCS-MLR
Chaohu
geo-accumulation index
principal component analysis
cluster analysis
Absolute Principal Component Scores-Multiple Linear Regression
