
基于主成分综合模型的矿区农田重金属污染评价
王从陆1、吴超2、段瑜3
Research of mine farmland heavy metal pollution assessment basedon synthetic principal component analysis model
Wang Conglu1、Wu Chao2、Duan Yu3
文章尝试利用变量聚类分析方法对矿区附近农田土壤重金属污染的主要污染物进行辨识,并采用 综合主成分分析法对矿区附近农田土壤重金属污染情况进行评价和分级。分析结果表明:利用变量聚类分 析法可以有效地辨识矿区附近农田土壤重金属污染中的主要成分;运用综合主成分分析法,确定样本的综合 主成分,并对其排序和聚类,可以有效揭示矿区附近农田土壤重金属污染物的数据结构、相互关系和不同样 品点的污染程度。采用主成分分析方法对矿区附近农田土壤重金属污染情况的评价结果,反映了矿区主要 重金属污染物的影响,同时又定量化了土壤复合重金属污染研究。辨识和评价结果可为矿区附近农田土壤 重金属污染治理对策的提出和重点治理区域的确定提供参考和指导。
Referring to GB5618 — 1995 about heavy metal pollution,and using statistical analysis SPSS,the major pollutants of mine area farmland heavy metal pollution were identified by variable clustering analysis.Assessment and classification were done to the mine area farmland heavy metal pollution situation by synthetic principal components analysis (PCA) . The study result implied that variable clustering analysis is efficient to identify the principal components of mine area farmland heavy metal pollution.Sort and clustering were done to the synthetic principal components scores of soil sample, which is given by synthetic principal components analysis. In this paper, data structure of soil heavy metal contaminations, relationships and pollution level of different soil samples were discovered. The results of mine area farmland heavy metal pollution quality assessed and classified with synthetic component scores reflect the influence of both the major and compound heavy metal pollutants. Identification and assessment results of mine area farmland heavy metal pollution can provide reference and guide to propose control measures of mine area farmland heavy metal pollution and focus on the key treatment region.
synthetic principal components analysis model / mine region soils / heavy metal pollution / assessment
/
〈 |
|
〉 |