某焦化场地土壤多环芳烃污染数据的统计特征  

Statistical characteristic analysis of soil PAHs in a coking contaminated site of China

作　　者：刘庚[1,2] 毕如田[1] 王世杰[2] 魏文侠 李发生[2] 郭观林[2] 

机构地区：[1]山西农业大学资源环境学院,山西太谷030801 [2]中国环境科学研究院环境基准与风险评估国家重点实验室,北京100012 [3]轻工业环境保护研究所,北京100012

出　　处：《应用生态学报》2013年第6期1722-1728,共7页Chinese Journal of Applied Ecology

基　　金：国家环境保护公益性行业科研专项(201009015);国家自然科学基金青年科学基金项目(40901249)资助

摘　　要：分析污染场地调查数据的统计特征能够帮助判别污染物在场地中的空间变异特征以及污染来源和成因.本文以我国某焦化场地为对象,对采集的表层土壤114个样点16种多环芳烃(PAHs)含量数据进行多元统计和空间特征分析.结果表明:每种污染物的含量范围差异显著,具有高度的偏倚性;多元统计分析提取的前2个主成分可以有效代表原场地污染数据信息.选择苯并(a)蒽、苯并(b,k)荧蒽、苯并(a)芘和茚并(1,2,3-cd)芘4种污染物进行趋势分析和空间局部变异分析,在场地的东西和南北方向的污染物含量均表现出由低到高再到低的变化趋势,空间变异系数在场地的中部、西北及西南较高,其他区域变异系数较低.Statistical characteristic analysis of pollutants in contaminated sites can help identify the origin, generation, and spatial variation of different pollutants, and can reduce the uncertainty of site survey data. Taking a large and abandoned contaminated coking site of China as the object, 114 surface （0-50 cm） soil samples were collected, with the statistical and spatial characteristics of 16 priority PAHs （ΣPAHs） analyzed. The descriptive statistical analysis indicated that the ΣPAH levels varied significantly, and the data were severely skewed. The correlation matrix （CM） and principal component analysis （PCA） showed that the extracted first two principal components （PCs） could effectively represent the whole site pollution data. Four pollutants, i.e., Baa, BbfBkf, Bap, and Inp, were selected for trend analysis and spatial local variance analysis. In the east-west and north-south directions of the site, the pollution showed a low-high-low trend. The variation coefficient of pollution for the site was higher in the central, northwest, and southwest regions, while lower in the other regions.

关 键 词：污染场地 趋势分析 多元统计分析 空间变异 

分 类 号：X53[环境科学与工程—环境工程]