The pulp and paper industry is the third-largest global consumer of freshwater and faces mounting pressure to optimize water usage. This study addresses limitations in existing aerated stabilization basin (ASB) models by developing an advanced approach for ultimate oxygen demand (UOD) prediction. We implemented variable temperature correction factors, significantly enhancing prediction accuracy for UOD, carbonaceous biochemical oxygen demand, and ammonia across seasonal variations. The models effectively simulated microbial activity, organic matter degradation, and phosphorus dynamics including benthal feedback effects. A digital twin was developed integrating these models with real-time data for dynamic optimization. Analysis revealed that comparable removal efficiencies could be achieved through various operational strategies depending on temperature conditions. This research provides a robust framework enhancing treatment efficiency and supporting regulatory compliance, offering valuable decision-making tools for industrial wastewater management.
