Non-Intentionally Added Substances (NIAS): analysis of migration from Food Contact Materials and assessment of human exposure.

Food Contact Materials (FCMs) play a fundamental role in ensuring food safety and quality; however, they also represent a potential source of human exposure to chemical contaminants. In recent years, increasing attention has been devoted to non-intentionally added substances (NIAS), a complex and largely unknown class of compounds that may originate from impurities, degradation processes, or interactions occurring during manufacturing and use. The identification and assessment of NIAS remain a major analytical and toxicological challenge due to their unknown nature and the lack of regulatory limits and toxicological data. The present thesis aims to provide an integrated evaluation of chemical safety in FCMs by combining advanced analytical methodologies for the characterization of NIAS with human biomonitoring approaches for the assessment of real exposure. In the first part of the work, a multi-technique analytical strategy was developed and optimized for the comprehensive screening of NIAS in FCMs. Complementary techniques, including headspace gas chromatography–mass spectrometry (HS–GC–MS), gas chromatography–mass spectrometry (GC–MS), and liquid chromatography coupled with high-resolution mass spectrometry (LC–HRMS), were applied to cover a wide range of compounds with different physicochemical properties. This approach enabled the identification and semi-quantitative evaluation of volatile, semi-volatile, and non-volatile substances in different types of materials, including plastics, paper and board, and multimaterial structures. Particular attention was given to the occurrence and distribution of NIAS across matrices and to the identification of recurrent chemical classes. The second part of the thesis focused on the development of targeted analytical methods for compounds of high toxicological relevance, specifically bisphenols and styrene. A new method based on LC–HRMS was developed for the determination of bisphenol A (BPA) in FCMs, in line with recent European regulatory requirements. In parallel, a specific method for paper and board materials was optimized to address matrix-related analytical challenges. In addition, a GC–MS/MS method was developed and validated for the determination of styrene migration, including the evaluation of different testing conditions using food simulants and real food matrices. The results highlighted the importance of selecting appropriate testing conditions, as simulants may overestimate migration compared to real food scenarios. The final part of the work addressed human exposure through biomonitoring studies. Urinary biomarkers of bisphenols, styrene metabolites, phthalates, triclosan, and parabens were determined using a multi-analyte GC–MS/MS method, specifically developed and optimized. This approach allowed the simultaneous quantification of compounds belonging to different chemical classes, improving analytical efficiency and enabling a more comprehensive assessment of exposure. The biomonitoring results revealed a marked variability in exposure levels across the study population. While a large proportion of samples showed concentrations below the limit of quantification, indicating limited or no detectable exposure, quantifiable levels were observed, in some cases reaching relatively elevated concentrations. This pattern suggests the presence of heterogeneous exposure sources and highlights the importance of identifying specific determinants of exposure, such as lifestyle factors, dietary habits, or contact with particular materials. Overall, this thesis provides a comprehensive framework linking the characterization of chemical contaminants in FCMs with the assessment of human exposure. The integration of advanced analytical techniques with biomonitoring approaches represents a powerful strategy to better understand the contribution of food packaging to chemical exposure and to support more effective risk assessment and regulatory decision-making.