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Monitoring of a Broad Set of Pharmaceuticals in Wastewaters by High-Resolution Mass Spectrometry and Evaluation of Heterogenous Catalytic Ozonation for Their Removal in a Pre-Industrial Level Unit

Authors :
Christina Nannou
Efthimia Kaprara
Savvina Psaltou
Maria Salapasidou
Panagiota-Aikaterini Palasantza
Panagiotis Diamantopoulos
Dimitra A. Lambropoulou
Manassis Mitrakas
Anastasios Zouboulis
Source :
Analytica, Vol 3, Iss 2, Pp 195-212 (2022)
Publication Year :
2022
Publisher :
MDPI AG, 2022.

Abstract

The removal of contaminants of emerging concern (CECs) occurring in wastewater effluents, such as pharmaceutically active substances (PhACs) and personal care products, pose a big research challenge since they can be a major source of pollution for water bodies and a danger to public health. The objective of this work was to perform a comprehensive monitoring of a broad set of PhACs (>130) in a wastewater treatment plant (WWTP) close to Thessaloniki (Greece), as well as to evaluate the potential of heterogeneous catalytic ozonation for the removal of CECs from wastewater through a continuous flow system. The high-resolution mass spectrometry analysis revealed the highest average concentrations for irbesartan (1817 ng/L). Antihypertensives along with antibiotics, psychiatrics, and β-blockers were found to aggravate the effluents. Removal efficiency after conventional treatment was >30%. The results from catalytic ozonation unit operation indicate that the introduction of a proper solid material that acts as catalyst can enhance the removal of CECs. A preliminary risk assessment using the risk quotient (RQ) revealed that irbesartan and telmisartan entail high acute risk. The overall results underline the urgent need to incessantly monitor PhACs and expand the toxicological studies to establish the sublethal and chronic effects on aquatic organisms.

Details

Language :
English
ISSN :
26734532
Volume :
3
Issue :
2
Database :
Directory of Open Access Journals
Journal :
Analytica
Publication Type :
Academic Journal
Accession number :
edsdoj.03a7c2e2e63f439ba40ab1b71dd58362
Document Type :
article
Full Text :
https://doi.org/10.3390/analytica3020014