Microbiome-guided strategies to reduce nitrous oxide emissions from municipal wastewater treatment: Insights from laboratory and full-scale systems

Research Project, 2026 – 2031

Nitrogen removal from municipal wastewater relies on nitrification and denitrification. These processes also emit nitrous oxide (N2O) - a potent greenhouse gas responsible for a major share of the climate impact of wastewater treatment plants (WWTPs). However, the causes of the emissions from WWTPs are poorly understood, tools for prediction lack precision, and effective mitigation strategies are not yet in place. Research about N2O emissions from WWTPs has focused on conventional treatment with activated sludge. Seasonal N2O emission patterns have been identified, but the underlying mechanisms remain unresolved. In biofilm reactors, which are increasingly used at WWTPs, long-term studies are still lacking. Here, diffusion limitations and stratification of microbial guilds throughout the biofilm add complexity to the N2O production pathways but also entail possibilities to mitigate emissions that are not yet explored.This project aims to uncover the causes of N2O emissions in both activated sludge and biofilm and develop effective mitigation strategies. We will do this by combining measurements of nitrogen turnover resulting in N2O emissions with microbial studies based on metagenomics and metatranscriptomics, and model-based predictions.In long-term studies of WWTPs with activated sludge and biofilm, we will continuously measure N2O emission together with turnover of the various wastewater components (dissolved nitrogen species, organic matter) and at the same time analyze microbial composition, metabolic potential and activity. With this approach, we will map seasonal variations in emissions and identify underlying causes. In lab-scale studies, the opportunities to mitigate emissions will be identified by kinetic and microbial studies at well-defined conditions. Here, we will investigate how various environmental factors affect the turnover rates resulting in N2O emissions in activated sludge and biofilm. In modelling studies, the results from the full-scale studies and the laboratory experiments will be used to develop and calibrate a hybrid model combining mechanistic and machine learning approaches. The model will be used to predict emissions and evaluate mitigation strategies. By this approach, we will generate new knowledge for use in N2O mitigation at WWTPs, which we reach by collaboration and close communication in already existing networks.