Water resource recovery facilities (WRRFs) are increasingly focusing on reducing process emissions such as nitrous oxide (N2O), while extracting greater value and resilience from existing assets. Aeration is the dominant driver of energy use and process emissions, accounting for 50% - 75% of total plant electricity consumption. Significant gaps remain regarding long-term monitoring and implementation of resource efficient control strategies. This paper presents a case-study from a municipal WRRF in Ireland, treating a population equivalent of 26,000, connected to a combined storm/sewer network with variable influent loads. The case-study integrates long-term (ongoing) process and N2O monitoring, digital tools and anomaly detection to support emission control strategies, demonstrating improved efficiency without major upgrades. The analysis shows seasonal and day-to-day variability of N2O and influent loads, alongside operational anomalies, impact emission profiles. The current aeration control strategy uses high/low DO setpoints creating periods of low DO, where N2O accumulated and subsequently stripped when aeration resumed. Tiered DO control has the potential to mitigate transient N2O emissions, reduce aeration energy demand, while maintaining compliance with regulatory effluent limits. This work demonstrates how data-driven control, connected monitoring, and process modelling can maximise asset performance, reduce emissions, and inform design guidelines for resilient, low-carbon WRRFs.