Quantifying, predicting, and mitigating nitrous oxide emissions in a full-scale partial nitritation/anammox reactor treating reject water

作     者：Flores-Alsina, Xavier Vangsgaard, Anna Katrine Uri-Carreno, Nerea Nielsen, Per H. Gernaey, Krist V. 

作者机构：Tech Univ Denmark PROSYS Res Ctr Dept Chem & Biochem Engn Soltofts Plads Bldg 228A DK-2800 Lyngby Denmark EnviDan A S Fuglebaekvej 1A DK-2770 Kastrup Denmark Vandcenter Syd A S Vandvaerksvej 7 DK-5000 Odense Denmark N118 Consulting Skt Jorgens Gade 44K DK-5000 ODENSE Denmark 

出 版 物：《WATER RESEARCH》 (Water Res.)

年 卷 期：2025年第278卷

页      面：123200页

核心收录：

学科分类：0830[工学-环境科学与工程（可授工学、理学、农学学位）] 08[工学] 0815[工学-水利工程] 

基　　金：MUDP (Miljoteknologisk Udviklingsog Demonstrationsprogram) [2021-20015] University of Queensland (School of Chemical Engineering) 

主　　题：Climate change mitigation Data science Digital twins GHG emissions Modeling Net zero 

摘      要：In this paper, a set of mathematical tools are developed and assembled to quantify, predict and virtually assess N2O 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 (NHx, NO2-, NO3-, N2O) 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 N2O production pathway. The model revealed that the system was suffering from low ANX activity leading to NO2- 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 N2O emission rates that are in line with wh