This paper describes the procedure adopted for implementing a monitoring system based on an electronic nose (EN) to continuously monitor odour emissions from a wastewater treatment plant (WWTP), with the purpose of identifying odour peaks related to the incoming wastewaters. The paper focuses on the methodology related to the instrument training, the implementation of a suitable model to classify the odour peaks, and then the validation procedure. In the specific case, the EN was installed at the arrival tank of the plant, which is characterized by anomalously intense odours and high variability of the incoming wastewater, with the purpose of identifying the origin of the odour peaks. To do this, the EN was equipped with automatic sampling systems to collect both the liquid effluent and gaseous samples at the arrival tank for further olfactometric and chemical characterizations. The paper limits its focus on the illustration of the EN training to identify the anomalous odour peaks related to unpredictable changes in the incoming wastewater, and the validation of the implemented model based on principal component analysis and support vector machine. Results achieved show that the EN can be effectively used for process control: the alarm set on EN signals proved effective in detecting alterations of the incoming effluent potentially responsible for odour events in the surroundings of the plant, thereby allowing plant managers prompt intervention to limit odour impacts.