Application of Event-Based Real-Time Analysis for Long-Term N2O Monitoring in Full-Scale WWTPs

Abstract

Nitrous oxide (N2O) emissions from wastewater treatment plants (WWTPs) are gaining increased attention globally. Several operating parameters, the configuration, environmental conditions and microbiological diversity of the biological processes affect significantly nitrous oxide (N2O) formation in WWTPs. However there are still uncertainties regarding the exact triggering mechanisms and the dependancies between the N2O emissions and main performance parameters of the plant. The aim of this work is to apply an event-based sensitivity analysis (EventTracker) to investigate dependencies and potential patterns between the operating parameters monitored online in wastewater treatment processes and N2O emissions. The complete dataset from long-term N2O monitoring in a full-scale plug-flow and two Carrousel reactors published by Daelman et al. (2015) was used for the analysis. The event-based sensitivity analysis indicated significant dependencies between the system parameters (i.e. nitrite, nitrate, ammonia) and N2O emissions. Spearman’s rank correlation coefficient was applied using monthly datasets indicating significant correlations between nitrite and nitrate sensor signals with the N2O emissions. The latter was mainly observed in cases characterised by high N2O emission fluxes supporting the event-based sensitivity analysis. The examined method enabled the grouping of the system parameters based on the identified dependencies. The results indicated that N2O emissions can provide information for the state of the examined biological processes.