Realisation of a Multi-sensor System for Real-time Monitoring of Odour Emissions at a Waste Treatment Plant
Panzitta, Alessandra
Bax, Carmen
Lotesoriere, Beatrice J.
Ratti, Christian
Capelli, Laura
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How to Cite

Panzitta A., Bax C., Lotesoriere B.J., Ratti C., Capelli L., 2022, Realisation of a Multi-sensor System for Real-time Monitoring of Odour Emissions at a Waste Treatment Plant, Chemical Engineering Transactions, 95, 139-144.
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Abstract

Currently, there is a growing interest in the development of Instrumental Odour Monitoring Systems (IOMS) for the real-time monitoring of odour emissions. They can be used at sensitive receptors for assessing the odour impact of the plant, or at plant fenceline or emission sources for process control purposes. The present work describes a research project, currently ongoing, concerning the realisation of an innovative IOMS network for the real-time measurement of odour concentration at the fenceline of a plant for the treatment of organic waste. More in detail, the IOMS, after a specific training phase, provides an output correlated to the odour concentration measured by dynamic olfactometry. As final goal, this project aims to define specific thresholds for the odour concentration at the plant fenceline, capable to effectively provide information about the probability of occurrence of odour episodes at sensitive receptors located in the surroundings of the plant. The research has been structured in five phases: 1) Parametric modelling study, aimed at correlating the odour concentration at the plant fenceline and the potential impact on the nearest sensitive receptors. 2) IOMS training for the specific application 3) IOMS performance verification in the field 4) Real-time monitoring of ambient air at the fenceline. 5) Definition of variable “alarm” thresholds for the odour concentration on the basis of meteorological data. Results achieved until now concerning the performance verification of the instrument in the field proved, with an accuracy of 82% (CI95% 68-94), the capability of the IOMS to detect and recognize odours from the plant. The preliminary evaluation of the quantification performance highlighted that the IOMS can provide an estimation of the odour concentration within the confidence interval by dynamic olfactometry.
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