Benchmarking Soft Sensors for Remote Monitoring of On-Site Wastewater Treatment Plants

Abstract

On-site wastewater treatment plants are usually unattended, so undetected failures often lead to prolonged periods of reduced performance. To stabilize the good performance of unattended plants, soft-sensors could expose faults and failures to the operator. In a previous study, we developed softsensors and showed that soft-sensors with data from unmaintained physical sensors can be as accurate as soft-sensors with data from maintained ones. The quantities sensed were pH and dissolved oxygen (DO), and soft-sensors were used to predict nitrification performance. In the present study, we use synthetic data and monitor three plants to test these soft-sensors. We find that a long sludge age and a moderate aeration rate improve the pH soft-sensor accuracy, and that the aeration regime is the main operational parameter affecting the accuracy of the DO soft-sensor. We demonstrate that integrated design, monitoring, and control are necessary to achieve robust accuracy and to obviate case-specific fine-tuning. Additionally, we provide a unique labelled dataset for further feature and data-driven soft-sensor development. Our approach is limited to sequencing batch reactors. Moreover, nitrite accumulation and alkalinity limitation cannot be detected. The strength of the approach is that unmaintained sensors drastically reduce monitoring costs, enabling the monitoring of plants hitherto unchecked. AbbreviationsASM activated sludge model COD chemical oxygen demand DO dissolved oxygen DOC dissolved organic carbon SL standard-liter OST on-site wastewater treatment plant (small, unstaffed wastewater treatment plant) PE population equivalent SA sludge age SAC254 spectral absorption coefficient at 254 nanometers SBR sequencing batch reactor WWTP wastewater treatment plant

How well can inaccurate sensors quantify and improve the performance of a fleet of on-site wastewater treatment plants?

“…48 Thirdly, the inflow concentrations of ammonium to OSTs can be very high. 14,25 We therefore argue that the focus on high treatment performance of one unit (instead of system performance) underestimates the comparative advantage that distributed systems can have over centralised systems. These untreated losses indicate that centralised systems only exceed 90% elimination performance in exceptional situations.…”

“…Hug and Maurer (2012) 24 showed that a discrepancy between real and measured performance can be expected when monitoring OSTs. Schneider et al 25 suggested a soft sensor based on signals from unmaintained physical sensors, which solves the issue of labor-intensive maintenance on the costs of measurement accuracy. Soft-sensor accuracy (all true classifications divided by the total) has been identified to be 0.83-0.85 based on four pH sensors, as well as 0.80 and 0.85 for two dissolved oxygen sensors.…”

Forward-Looking Roadmaps for Long-Term Continuous Water Quality Monitoring: Bottlenecks, Innovations, and Prospects in a Critical Review

“… 222 However, a study exploring benchmark sensors for on-site monitoring in a WW treatment plant reveals that proper operation setups (e.g., solid retention time and aeration rate) can maintain and even improve the sensor accuracy, and integration of a sensor surveillance network and control can enhance the robustness of remote monitoring systems. 223 In conventional centralized water systems, water network distribution depends on a centralized cloud model that has a potential risk of exposure to cyberattack with the growing number of network nodes. 224 From the standpoint of security and privacy, each end-user may act as a bottleneck or a failure point to disrupt the entire water network.…”

“…With data accumulating over time, its collection and storage could lead to an unexpected burden for data transmission and processing . However, a study exploring benchmark sensors for on-site monitoring in a WW treatment plant reveals that proper operation setups (e.g., solid retention time and aeration rate) can maintain and even improve the sensor accuracy, and integration of a sensor surveillance network and control can enhance the robustness of remote monitoring systems . In conventional centralized water systems, water network distribution depends on a centralized cloud model that has a potential risk of exposure to cyberattack with the growing number of network nodes .…”

Combination of Microscopic Tests of the Activated Sludge and Effluent Quality for More Efficient On-Site Treatment

“…Treatment efficiency of chemical oxygen demand (COD), biochemical oxygen demand (BOD), total solids (TS), nitrogen (N), and phosphorus (P) is a manufacturer's declaration and should be equal to, or higher than the regulations of the country of distribution. The real efficiency of container on-site wastewater treatment systems, however, often deviates from the assumed values [4] and can be a source of contamination of the environment [5][6][7]. The insufficient degree of wastewater treatment in on-site plants was widely reported.…”