Validation of Dissolved Oxygen Instability as a 12-Hour Precursor to Ammonia Events: Analysis of the Shafdan WWTP Dataset

Background and Objective: Efficient nitrogen removal is a critical challenge in Wastewater Treatment Plant (WWTP) operations, where sudden ammonia breakthroughs (events) can lead to environmental non-compliance and increased energy costs. This research investigates the validity of using Dissolved Oxygen (DO) instability as an operational proxy for the early detection of such ammonia events. The study specifically evaluates whether high-frequency fluctuations in DO levels can serve as a reliable precursor with a significant lead time for preventive intervention. Methodology: The analysis was conducted using the open-source Shafdan WWTP dataset, comprising over 135,000 observations at 10-minute intervals spanning from 2017 to 2020. An "instability proxy" (DO_dynamic_std) was engineered by calculating the 1-hour rolling standard deviation of the resampled DO time series. Ammonia events were defined based on the 95th percentile threshold (Ammonia Stage B > 15.2 mg/L). Lead-time analysis was performed across horizons ranging from 3 to 48 hours to identify the optimal predictive window. Results: The findings demonstrate a statistically significant correlation between pre-event DO instability and subsequent ammonia spikes. The predictive signal peaks at a 12-hour horizon, where the instability ratio (ratio of volatility in pre-event vs. normal operation) reaches 1.713× after outlier clipping. The univariate baseline achieved an Area Under the Curve (AUC) of 0.670. Crucially, the signal proved robust across multiple operating years (2018–2020), with the strongest precursor signal observed in 2019 (2.075× ratio). Conclusion: This research confirms that DO dynamics contain vital information regarding the impending loss of process stability. A 12-hour lead time provides a sufficient window for plant operators to adjust aeration strategies or return sludge flows. The proposed DO_dynamic_std metric offers a simple, sensor-based early warning proxy that can be integrated into automated control systems without the need for expensive additional hardware Wastewater Treatment (WWTP) Ammonia Breakthrough Prediction Dissolved Oxygen (DO) Dynamics Operational Instability Early Warning System (EWS) Time-series Analysis Shafdan WWTP Dataset Process Control Optimization Sensor-based Monitoring Environmental Data Science Lead-time Analysis Nitrogen Removal Efficiency