Evaluation of Spectroscopic and Hyperspectral Imaging methodologies for the study of emerging contaminants and microplastics in wastewater

The increasing release of microplastics (MPs) and emerging contaminants (ECs) into aquatic environments has raised growing concerns regarding their potential impact on ecosystems and human health. Wastewater treatment plants (WWTPs) represent both an important barrier against the release of these pollutants and a potential pathway for their dissemination into receiving waters. Consequently, the development of rapid, reliable and sustainable analytical methodologies for their detection and monitoring has become a priority in environmental research. The present thesis investigates the application of spectroscopic techniques coupled with chemometric data analysis for the characterization of MPs and ECs in environmental matrices associated with wastewater treatment processes. The experimental work was carried out through a collaboration between the University of Modena and Reggio Emilia and the University of the Basque Country (UPV/EHU). The first part of the study focused on the identification and characterization of microplastics collected along the treatment lines of the Galindo and Crispijana wastewater treatment plants, located in the Basque Country. Samples were subjected to dedicated preparation procedures including filtration, organic matter digestion and density separation. The resulting metallic filters were analysed by Raman spectroscopy, combining optical microscopy, point-by-point spectral acquisition and Raman mapping. This approach enabled the identification of the main polymeric families present in the samples and the evaluation of their distribution throughout the treatment process. The second part of the work was dedicated to the investigation of emerging contaminants using Polar Organic Chemical Integrative Samplers (POCIS) deployed at the influent and effluent sections of the Modena wastewater treatment plant. The collected samples were analysed through Raman spectroscopy and near-infrared hyperspectral imaging (HSI) in order to assess the capability of spectroscopic techniques to detect spectral variations associated with contaminant accumulation on the sorbent material. To complement the environmental study, laboratory-prepared samples were produced using the same sorbent phase spiked with known concentrations of caffeine, hydrochlorothiazide, diclofenac, metoprolol and atenolol according to a dedicated Design of Experiments (DoE). These samples were analysed using benchtop and portable spectroscopic instruments, including Raman and MicroNIR systems. Spectral data were processed through dedicated MATLAB routines and subsequently analysed using chemometric methods. Preprocessing procedures included noise reduction, baseline correction and spectral normalization, while exploratory and multivariate analyses were performed through Principal Component Analysis (PCA) and Multivariate Curve Resolution (MCR). Overall, the results demonstrate the potential of spectroscopic techniques, particularly when combined with chemometric tools, for the rapid characterization of complex environmental samples. Furthermore, the study highlights the opportunities and limitations associated with the use of portable spectroscopic devices for environmental screening applications, providing useful insights for the development of fast and non-destructive monitoring strategies for wastewater-related contaminants.