4.4 Article

Authentication of recycled and virgin polyethylene terephthalate based on UPLC-Q-TOF-MS using non-volatile organic compounds and chemometrics

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TAYLOR & FRANCIS LTD
DOI: 10.1080/19440049.2023.2227732

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UPLC-Q-TOF-MS; chemometrics; recycled polyethylene terephthalate; non-volatile organic compounds; >

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Plastic packaging waste, especially PET, has increased significantly, causing serious concerns about the environment, economy, and policy. Recycling is an effective tool to address this issue. In this study, a feasible method using UPLC-Q-TOF-MS combined with chemometrics was developed to distinguish between virgin and recycled PET based on 202 NVOCs. The method achieved a high discrimination rate and successfully identified marker compounds. The method showed 100% accuracy using a decision tree and improved prediction accuracy through cross-discrimination. This method provides a quick and accurate way to detect fraud in PET recycling.
Plastic packaging waste, such as polyethylene terephthalate (PET) has increased significantly in recent decades, arousing a considerable and serious public concern regarding the environment, economy, and policy. Plastic recycling is a useful tool to mitigate this issue. Here, a feasible study was performed to investigate the potential of a novel method for identifying virgin and recycled PET. Ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) was combined with various chemometrics, as a simple and reliable method that achieved a high discrimination rate for 105 batches of virgin PET (v-PET) and recycled PET (r-PET) based on 202 non-volatile organic compounds (NVOCs). Making use of orthogonal partial least-squares discrimination analysis (OPLS-DA) together with non-parametric tests, 26 marker compounds (i.e. 12 intentionally added substances (IAS) and 14 non-intentionally added substances (NIAS) as well as 31 marker compounds (i.e. 11 IAS and 20 NIAS) obtained from positive and combination of positive and negative ionization modes of UPLC-Q-TOF-MS, respectively, were successfully identified. Moreover, 100% accuracy was obtained using a decision tree (DT). Cross-discrimination based on misclassified samples using various chemometrics allowed the prediction accuracy to be improved and to identify a large sample set, thus greatly enhancing the application scope of this method. The possible origins of these detected compounds can be the plastic itself, as well as contamination from food, medicine, pesticides, industry-related substances, and degradation and polymerization products. As many of these compounds are toxic, especially those pesticide related, this indicates an urgent requirement for closed loop recycling. Overall, this analytical method provides a quick, accurate, and robust way to distinguish virgin from recycled PET and thus addresses the issue of potential virgin PET adulteration thereby detecting fraud in the area of PET recycling.

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