Evaluation and reduction of the analytical uncertainties in GC-MS analysis using a boundary regression model

Miao Yu; Xingwang Hou; Qian Liu; Yawei Wang; Jiyan Liu; Guibin Jiang

doi:10.1016/j.talanta.2016.11.046

Evaluation and reduction of the analytical uncertainties in GC-MS analysis using a boundary regression model

Talanta. 2017 Mar 1:164:141-147. doi: 10.1016/j.talanta.2016.11.046. Epub 2016 Nov 21.

Authors

Miao Yu¹, Xingwang Hou¹, Qian Liu¹, Yawei Wang¹, Jiyan Liu², Guibin Jiang¹

Affiliations

¹ State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, P.O. Box 2871, Beijing 100085, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China.
² State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, P.O. Box 2871, Beijing 100085, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China. Electronic address: liujy@rcees.ac.cn.

PMID: 28107908
DOI: 10.1016/j.talanta.2016.11.046

Abstract

The uncertainties in analysis of trace environmental pollutants may come from sample matrix and sample pretreatment process. In this study, a boundary model was developed based on the visualized data of mass spectrometry to evaluate the influences from sample matrix and pretreatment process. The factors affecting the pretreatment procedures, such as the solvents, the extraction sorbents and the extraction process had limited influences compared with matrix effects. Using such boundary model, we found that selecting suitable qualitative and quantitative ions for MS detector is more important for reducing the matrix effect in GC-MS analysis than the traditionally used methods of optimizing the pretreatment process since some clean up sorbents might be useless to reduce the matrix effects. As for 2,2',4,4',5-pentabromodiphenyl ether (BDE-99), the fragmental ions were usually used for qualitative and quantitative analysis, which however was easily affected by the matrix effects. While, molecular ions would eliminate the influences from the sample matrix. Such a model could be used to decrease the uncertainty and increase the accuracy of environmental trace analysis.

Keywords: Data visualization; Environmental analysis; GC-MS; Regression model.