Depression is considered to be one of the most prevalent mental disorders in humans. Antidepressant drugs are released in large concentrations and cause adverse effects on the environment and/or human health. Fabric Phase Sorptive Extraction (FPSE), a contemporary solid sorbent-handling technique, is a quick, sensitive, and simple analytical process. This paper describes a micro-extraction FPSE procedure coupled with High-Performance Liquid-Chromatography–Photodiode Array Detection (FPSE-HPLC–DAD) for the simultaneous extraction and analysis of five antidepressants, namely citalopram, clozapine, mirtazapine, bupropion and sertraline. Three fabric media (Whatman Cellulose filter, Whatman Microfiber Glass filter and Polylactic acid disks) and two different sol–gel sorbents (polyethylene glycol (PEG 300), alongside poly(ethylene glycol)-block-poly(propylene glycol)-block-poly(ethylene glycol) (PEG-PPG-PEG 5.800)) were tested. The best FPSE device was observed to be the microfiber glass filter coated with PEG 300 sol–gel sorbent. In addition, the parameters that affect the efficiency of the process (FPSE media and sorbents, sample pH, extraction time, elution time, etc.) were optimized. The proposed methodology displays a linear range with absolute recovery values higher than 60%, RSD% of less than 13% and LOQs in the range between 1.9–10.7 μg·L−1. Finally, the method was applied in hospital and urban effluents and lake water samples, but none of the analytes were detected.

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Aside from the classical residues of persistent organic pollutants (POPs), the occurrence of emerging contaminants (ECs) in the environment has become a subject of increasing concern due to their harmful impact on the aquatic environment. Wastewater treatment plant (WWTP) effluents are major sources of environmental pollution. Therefore, data concerning their existence is required. In this study, twenty compounds representative of different drug groups considered ECs and belonging to antibiotics, antipsychotics, anti-inflammatory drugs plus acesulfame K were selected to be accurately detected and quantified with UHPLC–LTQ-Orbitrap MS in hospital and urban WWTP effluents. Chromatographic parameters (column efficiency, mobile phase, etc.), as well as mass spectrometry conditions concerning ionization mode and Orbitrap analysis (ESI options, mass resolving power, AGC target, tube lens, injection time), were evaluated. Moreover, a novel fabric phase sorptive extraction (FPSE) method based on fiber glass coated with PEG300 was employed as sample preparation process. Experimental parameters affecting extraction and desorption steps such as sample pH, extraction time, ionic strength, elution time and solvent have been optimized. The optimized methodology was validated providing excellent linearity (R2 > 0.99), and low detection and quantification limits up to 3.1 and 9.3 ng/L, for carbamazepine, respectively. Relative recoveries ranged from 81.1% to 114.0%, while a medium matrix effect for most of the target compounds occurred. Applying the above analytical method in effluents of WWTPs from NW Greece, nine compounds were quantified with concentrations that varied from 55.4 to 728.4 ng/L.

This study proposes a simple approach for the recognition of polyamide 6.9 samples differing in impurity amounts and viscosities (modulated during the synthesis), which are parameters plausibly variable in polymers’ manufacturing processes. Infrared spectroscopy (ATR-FTIR) was combined with chemometrics, applying statistical methods to experimental data. Both non-supervised and supervised methods have been used (PCA and PLS-DA), and a predictive model that could assess the polyamide type of unknown samples was created. Chemometric tools led to a satisfying degree of discrimination among samples, and the predictive model resulted in a great classification of unknown samples with an accuracy of 88.89%. Traditional physical-chemical characterizations (such as thermal and mechanical tests) showed their limits in the univocal identification of sample types, and additionally, they resulted in time-consuming procedures and specimen destruction. The spectral modifications have been investigated to understand the main signals that are more likely to affect the discrimination process. The proposed hybrid methodology represents a potential support for quality control activities within the production sector, especially when the spectra of compounds with the same nominal composition show almost identical signals.

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