Proactive early-warning of effluent through OUR process feedback: An innovative intelligent prediction framework for wastewater treatment as a substitute for end-point monitoring

The implementation of intelligent regulations in wastewater treatment requires timely and reliable data. The existing end-point feedback control technique employed in most wastewater treatment systems is hindered by inadequate timeliness due to its intrinsic latency, while process feedback can markedly diminish this lag. The Oxygen Uptake Rate (OUR) is a robust process indicator for characterizing activated sludge physiological status and metabolic activity in wastewater treatment. Therefore, investigating the information about the wastewater treatment process contained in OUR becomes crucial for obtaining such data. This study focuses on the key process parameter of OUR, systematically elucidating its intrinsic mechanisms in response to temperature, sludge concentration (MLSS), and substrate concentration. The results indicate that the maximum OUR follows an exponential relationship with temperature and exhibits a significant linear correlation with Mixed Liquor Suspended Solids (MLSS). The real-time OUR of Ammonia-Oxidizing Bacteria (AOB) in response to NH 3 -N conforms to the Monod kinetic model. Then, based on the above understanding of the mechanism, a novel K-value method (KPR) for effluent NH 3 -N compliance assessment was introduced. Furthermore, a Random Forest (RF) algorithm was developed to predict effluent NH 3 -N based on OUR. This model achieved excellent predictive performance (R 2 = 0.9532). The result was interpreted by variable importance measures and microbial community. Subsequently, a combined KPR-RF strategy was formulated for compliance determination, achieving a precision for compliance prediction of 100% and a precision for exceedance prediction of 100%. This study introduces an innovative theoretical framework and technical tools for executing “process feedback-based intelligent regulation” in wastewater treatment.