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Updated: Sep 16, 2025

Gas Chromatography-Mass Spectrometry Paired with Total Vaporization Solid-Phase Microextraction as a Forensic Tool
Published on: May 25, 2021
Validation of a novel approach for quantification of short-chain chlorinated paraffins by gas chromatography-mass
Xin Wang1, Wenkai Chang2, Chongcheng Chen1
1Research Center for Differentiated Fibers and Functional Fabrics, Liming Vocational University, Quanzhou, Fujian 362000, PR China.
Abstract:
Gas chromatography electron capture negative ionization mass spectrometry (GC-ECNI-MS) coupling is often used for the detection and analysis of short-chain chlorinated paraffins (SCCPs). However, due to the complex composition, variable chain lengths and chlorination degrees, the accurate quantification of SCCPs remains a major analytical challenge. In this work, a novel analytical method for the quantification of SCCPs by GC-ECNI-MS was developed. Taking fully into account the combined influence of the chlorine content and concentration on the response of SCCPs, the response of the m/z 70 [Cl2]⁻• ion and the total response of specific quantitative ions were taken as the two dependent variables. Within the range of five degrees of chlorination, 24 appropriate concentrations were used to plot inverse nonlinear calibration surface of the relative areas versus concentration. The regression equation was fitted on the surface within a three-dimensional coordinate system and then used for the quantification of SCCPs in the samples. Spiked samples with SCCPs of different chlorination degrees at different concentration levels were determined, and the overall quantitative recovery reached in the range of 80-120 % for different chlorine contents. A total of five types of footwear material samples, including the collected positive samples and simulated actual samples prepared by adding SCCPs, were analyzed to assess and validate the applicability and reliability of the optimized quantitative method. Compared with the linear regression calibration, this developed method significantly improves the quantitative accuracy of SCCPs and has excellent applicability in all material matrices analyzed.
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