Estimating Phosphorus and COD Concentrations Using a Hybrid Soft Sensor: A Case Study in a Norwegian Municipal Wastewater Treatment Plant

Abstract

Online monitoring of wastewater quality parameters is vital for an efficient and stable operation of wastewater treatment plants (WWTP). Several WWTPs rely on daily/weekly analysis of water samples rather than online automated wet-analyzers due to their high capital and maintenance costs. Soft-sensors are emerging as a viable alternative for real-time monitoring of parameters that either lack a reliable measuring principle or are measured using expensive online sensors. This paper presents the development, implementation, and validation of a hybrid soft sensor used to estimate Total Phosphorus (TP) and Chemical Oxygen Demand (COD) in the influent and effluent streams of a full-scale WWTP. A systematic method for cleaning and processing sensor data, identifying statistically significant correlations, and developing a mathematical model, is discussed. A non-intrusive Industrial Internet of Things (IIoT) infrastructure for soft-sensor deployment and a web-based GUI for data visualization are also presented in this work. The values of TP and COD estimated by the soft sensor are validated by comparing the estimated values to the daily average of their corresponding lab measurements. The data validation results demonstrate the potential of soft sensors in providing real-time values of essential wastewater quality parameters with an acceptable degree of accuracy.

Artificial Intelligence-Assisted Prediction of Effluent Phosphorus in a Full-Scale Wastewater Treatment Plant with Missing Phosphorus Input and Removal Data

“…Most water quality variables were measured manually using standardized lab analyses, including chlorine residue (Cl 2 ), ammonia nitrogen (NH 3 ), phosphorus, five-day biological oxygen demand (BOD 5 ), and suspended solids (SS). However, compared to the previous study for TP prediction in a coagulation/flocculation process, several essential variables were not monitored in the SIUE WWTP, including influent phosphorus and alum dosage. The liquid alum was diluted in units of mix% before dosing, and the concentration was determined on the basis of the assumed influent P load (i.e., the result of multiplying the influent phosphorus concentration by the influent flow rate).…”

“…In particular, some small-scale WWTPs lack the use of real-time sensors and do not monitor all of the key parameters such as the influent phosphorus concentration, making it challenging to establish ML/DL models . Therefore, applying ML/DL algorithms can be difficult in small-scale WWTPs via “big data”, which are generally characterized by five dimensions: volume (quantity and amount of data), velocity (speed of data generation), variety (type, nature, and format of data), veracity (trustworthiness and quality of captured data), and value (insights and impact). , For example, the ML models were applied to the coagulation/flocculation process in a WWTP equipped with online sensors, and the essential variables, such as influent total phosphorus (TP), effluent TP, coagulant dose, and flocculant dose, were collected to predict the effluent TP with a maximum R 2 of 0.76; however, this kind of data collection seems to be unachievable for some small-scale WWTPs. Thus, when the data set is incomplete, feature selection matters for the exploration of the correlated variables for output prediction.…”

IoT Innovations in Sustainable Water and Wastewater Management and Water Quality Monitoring: A Comprehensive Review of Advancements, Implications, and Future Directions

“…The reviewed literature can be categorized into two primary groups based on the use of sensors in wastewater management. The first set of studies primarily focuses on creating sensors specifically designed to monitor various wastewater parameters [94], [95], [96], [97]. For example, Depari et al…”

Design of a Soft Sensor for Monitoring Phosphorous Uptake in an EBPR Process

“…12,13 For instance, a recent study demonstrated real-time controls of dosing in a chemically driven phosphorous removal process using a soft sensor (comprised of pH, total suspended solids, electrical conductivity, oxidation reduction potential, level, and flow sensors) at a full-scale WWT plant. 14 Building on prior work using soft sensors for characterization of minority and/or difficult-to-measure constituents in natural waters and wastewaters, 15,16 this work assesses the feasibility of designing a soft sensor for phosphorus removal monitoring in relatively more sustainable biological processes such as EBPR with the goal of providing data at higher accuracy, higher resolution, lower lag time, and lower cost than existing solutions. Successfully applying online monitoring and control strategies like those above requires an understanding of both (1) the chemistry of the target process and (2) the expected interferences on candidate sensors, which can then be used to appropriately design the hardware backbone of a soft sensor solution.…”

“…These challenges have limited the development of sophisticated controls for advanced processes designed for phosphorus removal, for example, enhanced biological phosphate removal (EBPR), forcing these processes to be operated under conservative (i.e., over-treatment) regimes that may be inefficient in both cost and energy usage. Yet, the use of arrays of sensors for direct and indirect (proxy) measurement of chemical constituents has been proven successful in related applications. − Soft sensors, that is, systems that utilize a tuned algorithm to estimate the concentration of a target analyte from readings of multiple individual sensing devices, − may provide a promising alternative to expensive and sometimes unreliable analyzers and probes for wastewater process monitoring and control. , For instance, a recent study demonstrated real-time controls of dosing in a chemically driven phosphorous removal process using a soft sensor (comprised of pH, total suspended solids, electrical conductivity, oxidation reduction potential, level, and flow sensors) at a full-scale WWT plant . Building on prior work using soft sensors for characterization of minority and/or difficult-to-measure constituents in natural waters and wastewaters, , this work assesses the feasibility of designing a soft sensor for phosphorus removal monitoring in relatively more sustainable biological processes such as EBPR with the goal of providing data at higher accuracy, higher resolution, lower lag time, and lower cost than existing solutions.…”