The deployment of water reuse in a safe scenario, in terms of environmental and health impacts, introduces the need for wastewater treatment pltants (WWTPs) to release effluents fulfilling quality criteria set by law that must be timely and accurately monitored. This poses the challenge of overcoming, as much as possible, laboratory-based control and move to a real time monitoring approach. Indeed, while a wide variety of sensors are already available for parameters like pH, dissolved oxygen, temperature, conductivity, suspended solids, and metals, the analytical controls of microbiological pollutants and of Contaminants of Emerging Concern (CECs), and related transformation products, are still mostly performed at laboratory scale and in many cases requires sophisticated and expensive instrumentation. On the other hand, the current impressive growth of advanced soft-sensing techniques and the Internet of Things (IoT), coupled with machine learning (ML) and artificial intelligence (AI), allows to foresee an upcoming possible transition from the laboratory-based approach to the real time one.

Analytical Challenges in the Water Reuse Scenario

Flores Garcia, Jenny
First
;
Palma, Davide;Sciscenko, Iván
;
Bianco Prevot, Alessandra
Last
2024-01-01

Abstract

The deployment of water reuse in a safe scenario, in terms of environmental and health impacts, introduces the need for wastewater treatment pltants (WWTPs) to release effluents fulfilling quality criteria set by law that must be timely and accurately monitored. This poses the challenge of overcoming, as much as possible, laboratory-based control and move to a real time monitoring approach. Indeed, while a wide variety of sensors are already available for parameters like pH, dissolved oxygen, temperature, conductivity, suspended solids, and metals, the analytical controls of microbiological pollutants and of Contaminants of Emerging Concern (CECs), and related transformation products, are still mostly performed at laboratory scale and in many cases requires sophisticated and expensive instrumentation. On the other hand, the current impressive growth of advanced soft-sensing techniques and the Internet of Things (IoT), coupled with machine learning (ML) and artificial intelligence (AI), allows to foresee an upcoming possible transition from the laboratory-based approach to the real time one.
2024
Water Reuse and Unconventional Water Resources. A Multidisciplinary Perspective
Springer
367
391
9783031677380
9783031677397
Flores Garcia, Jenny; Palma, Davide; Sciscenko, Iván; Bianco Prevot, Alessandra
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/2069333
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