High-fidelity profiling and modeling of heterogeneity in wastewater systems using milli-electrode array (MEA): Toward high-efficiency and energy-saving operation

Abstract

High energy consumption is a critical problem for wastewater treatment systems currently monitored using conventional "single point" probes and operated with manual or automatic open-loop control strategies, exhibiting significant time lag. This challenge is addressed in this study by profiling the variation of three critical water quality parameters (conductivity, temperature and pH) along the depth of a reactor at high spatiotemporal resolution in a real-time mode using flat thin milli-electrode array (MEA) sensors. The profiling accurately captured the heterogeneous status of the reactor under transient shocks (conductivity and pH) and slow lingering shock (temperature), providing an effective dataset to optimize the chemical dosage and energy requirement of wastewater treatment systems. Transient shock models were developed to validate the MEA profiles and calculate mass transfer coefficients. Monte Carlo simulation revealed high-resolution MEA profiling combined with fast closed-loop control strategies can save 59.50% of energy consumption (Temperature and oxygen consumption controls) and 45.29% of chemical dosage, and reach 16.28% performance improvement over the benchmark (defined with ideal conditions), compared with traditional "single-point" sensors that could only monitor the entire system through a single process state. This study demonstrated the capability of MEA sensors to profile reactor heterogeneity, visualize the variation of water quality at high resolution, provide complete datasets for accurate control, and ultimately lead to energy-saving operation with high resilience.

Keywords: Energy-saving and performance enhancement; High-fidelity profiling; Milli-electrode array (MEA); Navier-Stokes equations; Real time in situ monitoring; Wastewater treatment.