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Updated: Jan 14, 2026

Gas Chromatography-Mass Spectrometry Paired with Total Vaporization Solid-Phase Microextraction as a Forensic Tool
Published on: May 25, 2021
Automated vortex-assisted-liquid-liquid microextraction with injector-based derivatization for GC-MS/MS analysis of
Malte Hübschen1,2, Fabrian Brenz3, Torsten C Schmidt4
1Faculty of Chemistry, Instrumental Analytical Chemistry, University of Duisburg-Essen, Universitätsstraße 5, 45141, Essen, Germany.
Abstract:
The analysis of 1,3-dichloropropan-2-ol (1,3-DCP) and 3-chloropropane-1,2-diol (3-MCPD) in paper products and cardboard boxes used as food contact materials is of great importance due to the potential health risks associated with the intake of these contaminants. Both compounds, which originate from wet strength agents used in paper production, pose significant health concerns: 1,3-DCP and 3-MCPD are classified as possibly carcinogenic to humans and suspected to be carcinogenic in humans, respectively. This study presents a novel, automated analytical method for the analysis of a cold water extract-a widely used procedure for isolating these analytes from paper products and cardboard boxes. Method development included the implementation of vortex-assisted liquid-liquid microextraction (VALLME) with a focus on reducing solvent consumption and improving environmental sustainability and the systematic investigation of derivatization techniques. Optimization of the extraction solvent, extraction time, and derivatization parameters using vial-based and injector-based approaches resulted in a lean and rapid method with low limits of detection (0.01 µg/L for 1,3-DCP and 0.16 µg/L for 3-MCPD). The method showed good precision with intra-day repeatabilities of 3.6-3.7% for 1,3-DCP and 3.6-5.9% for 3-MCPD and inter-day repeatabilities of 2.6-3.6% and 4.0-7.6%, respectively. Recoveries ranged from 100 to 102% for 1,3-DCP and from 90 to 99% for 3-MCPD. Comparative assessment with a reference method confirmed good precision and comparability of the method. Improved environmental performance was quantified by the analytical greenness metric for sample preparation.
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