A Fast and Automated Strategy for the Identification and Risk Assessment of Unknown Substances (IAS/NIAS) in Plastic Food Contact Materials by GC-Q-Orbitrap HRMS: Recycled LDPE as a Proof-of-Concept
Pablo Miralles, Vicent Yusà, Adriana Pineda, Clara Coscollà
Abstract
A fast and automated approach has been developed for the tentative identification and risk assessment of unknown substances in plastic food contact materials (FCM) by GC-Q-Orbitrap HRMS. The proposed approach combines GC-HRMS full scan data acquisition coupled to Compound Discoverer™ 3.2 software for automated data processing and compound identification. To perform the tentative identification of the detected features, a restrictive set of identification criteria was used, including matching with the NIST Mass Spectral Library, exact mass of annotated fragments, and retention index calculation. After the tentative identification, a risk assessment of the identified substances was performed by using the threshold of toxicological concern (TTC) approach. This strategy has been applied to recycled low-density polyethylene (LDPE), which could be used as FCM, as a proof-of-concept demonstration. In the analyzed sample, 374 features were detected, of which 83 were tentatively identified after examination of the identification criteria. Most of these were additives, such as plasticizers, used in a wide variety of plastic applications, oligomers of LDPE, and substances with chemical, industrial, or cosmetic applications. The risk assessment was performed and, according to the TTC approach, the obtained results showed that there was no risk associated with the release of the identified substances. However, complementary studies related to the toxicity of the unidentified substances and the potential mixture toxicity (cocktail effects) should be conducted in parallel using bioassays.