文献类型：期刊文献

中文题名：基于稳健统计学确定高潜在污染土壤CU、Pb基线值

英文题名：DEFINING Cu AND Pb GEOCHEMICAL BASELINES FOR SOILS HIGH IN POLLUTION RISK WITH ROBUST STATISTICS

作者：王志刚[1,2,3] 赵永存[1] 孙维侠[1] 黄标[1,3] 邵学新[4] Jeremy L.Darilek[1]

第一作者：王志刚

机构：[1]中国科学院土壤环境与污染修复重点实验室(中国科学院南京土壤研究所);[2]长江科学院水土保持研究所;[3]中国科学院研究生院;[4]中国林业科学研究院亚热带林业研究所

年份：2011

卷号：48

期号：2

起止页码：246-254

中文期刊名：土壤学报

外文期刊名：Acta Pedologica Sinica

收录：CSTPCD;;北大核心:【北大核心2008】；CSCD:【CSCD2011_2012】；

基金：国家自然科学基金项目(40773075);江苏省自然科学基金项目(BK2009340)资助

语种：中文

中文关键词：土壤重金属;稳健统计学;稳健回归;基线值;污染评价

外文关键词：Soil heavy metals; Robust statistics; Robust regression; Geochemical baseline; Pollution assessment

分类号：X825

摘要：土壤重金属基线值的确定对于评价重金属积累现状具有重要意义。在存在人为污染的情况下,土壤重金属数据经常强烈地偏离正态分布和对数正态分布,影响统计分析结果的可信度,而稳健统计方法可以降低离群值对统计分析结果的影响。本研究以张家港为研究区域,采用稳健回归方法,建立表层和底层土壤Cu、Pb的回归关系,通过底层土壤Cu、Pb含量计算表层土壤Cu、Pb基线值,并对土壤Cu、Pb积累状况进行评价。结果表明,稳健回归方法确定的表层土壤Cu、Pb基线值可以反映出不同样点间,土壤Cu、Pb背景含量的自然变异。与稳健统计学方法相比,使用国家土壤环境质量标准值,或大区域(江苏省)的土壤背景值,评价自然背景本身存在变异区域的土壤重金属积累状况时,可能会产生较大的误差。
It is of great practice significance to define baselines for soil heavy metals in the Yangtze River Delta Region to evaluation of status quo of the heavy metal accumulation in the soil. In the presence of anthropogenic heavy metal pollution, soil heavy metal data always significantly deviate from normal or lognormal distribution, which affects reliability of the results of classical statistics. In contrast, robust statistics is aimed at lowering the effect of outliers on statistical analysis. With the robust regression method regression relationships between Cu and Pb concentrations in topsoil and in subsoil were established for the study region of Zhangjiagang, which has thousands of years of agricultural history and has recently been developing rapidly in industry. Based on the topsoil Cu and Pb concentration baselines calculated through robust regression of their subsoil concentrations, the status of soil Cu and Pb accumulations were evaluated. Results show that the calculated geochemical baselines can reflect natural variation of soil Cu and Pb background values between different sampling sites. Compared with the robust statistical method, the evaluation of soil heavy metal accumulation in a region that has spatial variation of natural background values on the basis of the national standard for soil environmental quality or regional soil background values would generate bigger errors.