摘要
本文尝试利用主成分分析方法对农田土壤污染物进行识别,并对土壤环境质量进行分级。结果表明,利用主成分分析可以有效地识别土壤污染物中的主要成分,揭示土壤污染物的数据结构和相互间的关系。主成分分析方法可用于定量化的土壤复合污染研究或对历史数据较为缺乏的地区进行土壤环境质量评价。在污染物检测指标数量较大时,可以在一定程度上简化农田土壤重点污染物的定量化识别过程。
Principal components analysis （PCA） is a statistical technique used to investigate the structure of a data set, in an effort to identify the procedures controlling the scores of the variables in the data. PCA produces several linear combinations of observed variables, each linear combination being a component or factor. The factors summarize the patterns of the correlations in the observed correlation matrix and can in fact be used to reproduce the observed correlation matrix. Since the number of factors is usually far fewer than the number of the observed variables, there is a considerable parsimony in factor analysis. Furthermore, when scores on factors are estimated for each subject, they are often more reliable than scores on individual observed variables. The advantages of PCA are particularly useful in soil complex contamination studies, especially in poorly recorded areas historically, and could be further used for the spatial assessment. Now PCA has been used in the fields of resource exploitation and protection, environmental degradation and quantitative soil contamination assessment.
In this paper, data structure of soil contaminations, relationships and differences of soil pollutions were discovered, and the major components of soil pollutions were identified. The result of agriculture field quality classified with component scores showed that paddy field irrigated with clean water was on the top of the six types of land, and soil environment of sewage irrigated paddy field had worst quality. The relationships with and contribution to contamination of soil pollutants were reflected well. The effect of heavy metals inputting was higher than organic pesticide, and is the major factor of soil contamination.
The study implied that PCA is advantageous in the assessment on complex soil contamination and classification of soil environmental quality, and could be used in soil pollutants identify ication and soil environment assessment as well. The method could simplify the process of major soil pollutants identification, especially in cases of complex or poorly recorded contamination.
出处
《地理研究》
CSCD
北大核心
2006年第5期836-842,共7页
Geographical Research
基金
国家环保总局"中意合作典型区生态环境调查"项目
