Quantifying, predicting, and mitigating nitrous oxide emissions in a full-scale partial nitritation/anammox reactor treating reject water
Xavier Flores‐Alsina, Anna Katrine Vangsgaard, Nerea Uri-Carreño, Per H. Nielsen, Krist V. Gernaey
Abstract
• Data pre-treatment reduces noise, fills gaps, and is crucial for accurate process simulations. • Model predicts NH x , NO 2 - , NO 3 - , N 2 O, DO, and pH with high accuracy (RMSE <1). • Biofilm simulations predict substrate gradients, microbial stratification with inactive inner granule parts. • N 2 O emission peaks linked to NO 2 - accumulation and low DO due to ANX limitations. • Adjusting aeration patterns, VSS concentration and granule size can reduce N 2 O emissions. • Study supports development of digital twins for real-time wastewater process monitoring. In this paper, a set of mathematical tools are developed and assembled to quantify, predict and virtually assess N 2 O emission mitigation strategies in partial nitritation (PN) / anammox (ANX) granular based reactors. The proposed approach is constructed upon a set of data pre-treatment methods, process simulation models, control tools (and algorithms) and key performance indicators to analyze, reproduce, and forecast the behavior of multiple operational variables within aerobic granular sludge systems. All these elements are tested on two full-scale data sets (#D1, #D2) collected over a period of four months (Sept-Dec 2023). Results show that data pretreatment is essential for noise reduction, filling data gaps, and ensuring smooth process simulations. The model accurately predicts (normalized RMSE< 1) multiple N oxidation states (NH x , NO 2 - , NO 3 - , N 2 O) and dissolved oxygen (DO), demonstrating its capability to describe bacterial behavior within the studied system. Special emphasis is placed on weak acid-base chemistry where pH is reliably reproduced, and it can be used for control purposes. Both biological and physico-chemical aspects are predicted at different time scales (months, days, minutes). While nitritation mainly occurred in the bulk, biofilm distribution showed inactive inner granule parts and increasing biomass (mostly ANX) towards the surface, with distinct organic concentrations. Gradients for multiple soluble compounds could also be reflected. Nitrifier denitrification (ND) is identified as the main N 2 O production pathway. The model revealed that the system was suffering from low ANX activity leading to NO 2 - accumulation. This in combination with low DO levels resulted in an unusually high emission factor (EF). The validation data set also yielded satisfactory results (normalized RMSE< 1). The scenario analysis revealed that modification of the operational parameters could improve the ANX activity and lead to N 2 O emission rates that are in line with what is normally expected from similar systems. The study includes a discussion on transitioning from process models to digital shadows/ twins for real-time process monitoring. Additionally, it emphasizes the necessity of evaluating reject water technologies from a plant-wide perspective.