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Chemosphere


Title:Smart instrumental Odour Monitoring Station for the efficient odour emission management and control in wastewater treatment plants
Author(s):Zarra T; Galang MGK; Oliva G; Belgiorno V;
Address:"Sanitary Environmental Engineering Division (SEED), Department of Civil Engineering, University of Salerno, Via Giovanni Paolo II 132, 84084, Fisciano, SA, Italy. Electronic address: tzarra@unisa.it. Sanitary Environmental Engineering Division (SEED), Department of Civil Engineering, University of Salerno, Via Giovanni Paolo II 132, 84084, Fisciano, SA, Italy. Electronic address: mgalang@unisa.it. Sanitary Environmental Engineering Division (SEED), Department of Civil Engineering, University of Salerno, Via Giovanni Paolo II 132, 84084, Fisciano, SA, Italy. Electronic address: goliva@unisa.it. Sanitary Environmental Engineering Division (SEED), Department of Civil Engineering, University of Salerno, Via Giovanni Paolo II 132, 84084, Fisciano, SA, Italy. Electronic address: v.belgiorno@unisa.it"
Journal Title:Chemosphere
Year:2022
Volume:20220930
Issue:Pt 1
Page Number:136665 -
DOI: 10.1016/j.chemosphere.2022.136665
ISSN/ISBN:1879-1298 (Electronic) 0045-6535 (Linking)
Abstract:"Odour emission assessment in wastewater treatment plants (WWTP) is a key aspect that needs to be improved in the plant management to avoid complaints and guarantee a sustainable environment. The research presents a smart instrumental odour monitoring station (SiOMS) composed of an advanced instrumental odour monitoring system (IOMS) integrated with other measurement units, for the continuous characterization and measurement of the odour emissions, with the aim of managing the potential odour annoyance causes in real time, in order to avoid negative effects. The application and on-site validation procedure of the trained IOMS is discussed. Experimental studies have been conducted at a large-scale WWTP. Fingerprint analysis has been applied to analyze and identify the principal gaseous compounds responsible for the odour annoyance. The artificial neural network has been adopted to elaborate and dynamically update the odour monitoring classification and quantification models (OMMs) of the IOMS. The results highlight the usefulness of a real-time measurement and control system to provide continuous and different information to the plant operators, thus allowing the identification of the odour sources and the most appropriate mitigation actions to be implemented. The paper provides important information for WWTP operators, as well as for the regulating bodies, authorities, manufacturers and end-users of odour monitoring systems involved in environmental odour impact management"
Keywords:*Odorants/prevention & control Environmental Monitoring/methods *Water Purification Environment Gases Backward analysis Dynamic olfactometry Fingerprint analysis Odour monitoring model Process control Volatile organic compounds;
Notes:"MedlineZarra, Tiziano Galang, Mark Gino K Oliva, Giuseppina Belgiorno, Vincenzo eng England 2022/10/04 Chemosphere. 2022 Dec; 309(Pt 1):136665. doi: 10.1016/j.chemosphere.2022.136665. Epub 2022 Sep 30"

 
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Citation: El-Sayed AM 2024. The Pherobase: Database of Pheromones and Semiochemicals. <http://www.pherobase.com>.
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