An attempt to estimate the appropriate oxidation-reduction potential and dissolved oxygen within the aeration tank of an activated sludge method livestock wastewater treatment facility using time series analysis and machine learning

Abstract

To maintain a low concentration of nitrogenous compounds in the effluent of a swine wastewater treatment facility using activated sludge method, pH and EC sensors were installed in the discharge tank, while a temperature sensor, ORP sensor, and DO sensor were installed in the aeration tank. At first, it was confirmed that monitoring the nitrogenous compounds is possible through pH and EC measurements. Next, by analyzing the time series data of the nitrogenous compounds along with water temperature, ORP, and DO, the trend components of the changes were identified. Additionally, a rate of change series with a 48-hour time lag was created for the nitrogenous compounds concentration based on the trend series. Finally, decision tree analysis was conducted using the rate of change as the dependent variable and the trend components of water temperature, ORP, and DO as independent variables. As a result, the range of ORP and DO values where the rate of change in nitrogenous compounds becomes negative could be identified.