用多元线性回归分析法定量判别PCBs污染物类型

应用多元线性回归分析法处理多氯联苯(PCBs)标准样品和实际样品的气相色谱数据,定量判别PCBs污染物类型,该法简便易行,可以避免由主观判断引入的偏差.对于PCBs标准样品Aroclor 1248及PCBs配制样品,污染物组成计算结果与实际值吻合,绝对误差小于2%.实际土壤样品的分析计算结果表明:北京土壤样品PCBs污染物是Aroclor 1242;兰州土壤样品PCBs污染物是49.0%的Aroclor 1242和51.0%的Aroclor 1254的混合物.应用多元线性回归分析法处理气相色谱分析数据,还可以作为一种质量控制的手段来识别干扰物. 

Identification and Estimate of Polychlorinated Biphenyls Mixture by Multiple Linear Regression Analysis

The multiple linear regression analysis was applied to process the gas chromatographic data of Polychlorinated Biphenyls (PCBs) standard samples and actual soil samples, in order to quantitatively and objectively estimate the PCBs composition in the soil. It is shown that the calculated compositions of standard PCBs sample (Aroclor 1248) and the mixture of two standard samples prepared in laboratory are in line with those from labels. The absolute analysis error is smaller than 2%. Two soil samples polluted by PCBs from two cities of China, Beijing and Lanzhou, are analyzed by this method. The soil sample from Beijing is polluted by Aroclor 1242. The soil sample from Lanzhou is polluted by 49.0% of Aroclor 1242 and 51.0% of Aroclor 1254. The method described also provides a quality control approach to distinguish the interference compounds in the samples.