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Updated: Nov 17, 2025

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Published on: July 1, 2017
Identification and quantification of plastic additives using pyrolysis-GC/MS: A review
Fleurine Akoueson1, Chaza Chbib2, Sébastien Monchy2
1ANSES - Laboratoire de Sécurité des Aliments, Boulevard du Bassin Napoléon, F-62200 Boulogne-sur-Mer, France; Univ. Littoral Côte d'Opale, UMR 1158 BioEcoAgro, EA 7394, Institut Charles Viollette, USC ANSES, INRAe, Univ. Lille, Univ. Artois, Univ. Picardie Jules Verne, Uni. Liège, F-62200, Boulogne-sur-Mer, France.
Pyrolysis coupled with gas chromatography-mass spectrometry (Py-GC/MS) is a promising technique for identifying and semi-quantifying organic plastic additives (OPAs) in polymers. This method simplifies sample preparation and allows for simultaneous analysis of additives and the plastic matrix.
Area of Science:
- Analytical Chemistry
- Polymer Science
- Environmental Science
Background:
- Analysis of organic plastic additives (OPAs) in plastic polymers is an area of increasing scientific interest.
- Traditional methods for OPA analysis often involve extensive sample preparation and risk contamination.
Purpose of the Study:
- To review the characteristics and development of multi-step pyrolysis coupled with gas chromatography-mass spectrometry (Py-GC/MS) for OPA identification and semi-quantification.
- To highlight the advantages of Py-GC/MS over conventional analytical techniques for OPA analysis.
Main Methods:
- The review focuses on (multi-step) pyrolysis coupled with gas chromatography-mass spectrometry (Py-GC/MS).
- It examines various aspects of sample preparation, including particle weight and size, and calibration strategies.
Main Results:
- Py-GC/MS offers advantages such as reduced sample preparation, minimized solvent contamination, and the ability to analyze minute particles.
- The technique allows for the successive analysis of OPAs and the polymeric matrix from the same sample.
- Numerous methods for OPA identification and semi-quantification have been reported, though a gold standard is yet to be established due to OPA diversity and potential interferences.
Conclusions:
- Py-GC/MS is a valuable tool for the analysis of OPAs in plastic polymers.
- Future methodological developments should aim to better characterize the limits of Py-GC/MS for quantifying specific OPAs in different polymer matrices.
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