Remote Monitoring of On-Site Wastewater Treatment Plants by Means of Low-Maintenance Sensors: Data Collection and Interpretation from a SBR in Operation

Abstract

Decentralized sanitation systems, where wastewater is treated on-site, is playing an important role to cover present and future sanitation demands due to their low investment costs and infrastructure requirements. Yet, on-site wastewater treatment plants (WWTP) suffer from bad reputation due to their high failure rate. However, the poor performance is by a great deal caused by the insuffcient monitoring and maintenance system and not by lack of appropriate technologies. A possibility to improve the monitoring proceeding is to remotely monitor a whole system of on-site WWTPs with the aid of low-maintenance sensors, installed at each unit, which deliver real-time information about the treatment performance. Methods are needed, that translate those sensor signals into performance parameters such as efluent concentration of certain substances. A method exists that predicts the ammonium efluent concentration based on the pH signal in the case of a pilot scale sequencing batch reactor (SBR). In this thesis, this method is tested on its applicability at an on-site SBR in operation. Moreover, the potential of an additional low-maintenance sensor, which measures the CO2 in the off-gas of a plant, was tested regarding remote monitoring of the bacterial activity. The results show, that the existing method based on the pH sensor can be applied at plants in operation, when they meet certain requirements regarding aeration pattern and inflow characteristics (ratio of alkalinity:ammonium > 2:1). In this thesis it is further illustrated, which possibilities exist to enlarge the application range of the method. Moreover, it could be demonstrated that the CO2 sensor represents a promising alternative for monitoring the biological activity. Yet, this method needs to be optimized in order to increase the information content of the model output.