Quantification of nitrous oxide (N2O) emissions and soluble microbial product (SMP) production by a modified AOB-NOB-N2O-SMP model

Establishment of nitrous oxide (N2O) dynamics model based on ASM3 model during biological nitrogen removal via nitrification

Nitrous oxide (N₂O), as one of the six greenhouse gases, is mainly produced in the biological nitrogen removal process of wastewater treatment plants (WWTPs). Establishing the N₂O kinetic model can provide insight into the N₂O generation mechanism and regulate its production. This work uses Activated Sludge Model NO.3 (ASM3) as the basic framework, combines organic storage with endogenous respiration theory, and couples ammonia-oxidizing bacteria (AOB) denitrification pathway and the NH₂OH/NOH model to establish a kinetic model. Meanwhile, the Sequencing Batch Reactor (SBR) process with artificial simulated urban domestic sewage was used as the carrier; MATLAB and EXCEL software were used as tools to establish a model calculation programme. The simulated values obtained by substituting the operating conditions of the SBR process into the model and the measured values of the SBR process were analysed. The correlation coefficient (R²) between the experimental values and simulated values obtained for the 5 components of COD, ammonia, nitrite, nitrate and total N₂O is 0.952, 0.996, 0.902, 0.991 and 0.956, respectively, which indicates that the N₂O kinetic model has great consistency, this further shows that the established model modelling mechanism is clear and accurate, and provides a new method for the N₂O dynamic model.

A plant-wide modelling comparison between membrane bioreactors and conventional activated sludge

A comprehensive plant-wide mathematical modelling comparison between conventional activated sludge (CAS) and Membrane bioreactor (MBR) systems is presented. The main aim of this study is to highlight the key features of CAS and MBR in order to provide a guide for an effective plant operation. A scenario analysis was performed to investigate the influence on direct and indirect greenhouse gas (GHG) emissions and operating costs of (i) the composition of inflow wastewater (scenario 1), (ii) operating conditions (scenario 2) and (iii) oxygen transfer efficiency (scenario 3). Scenarios show higher indirect GHG emissions for MBR than CAS, which result is related to the higher energy consumption in MBR. The simultaneous variation of the investigated factors (scenario 4) exacerbates direct and indirect GHG emissions for both CAS and MBR. Indeed, during scenario 4 a maximum direct GHG emissions of 0.94 kgCO_2eq m^-3 and 1.56 kgCO_2eq m^-3 for CAS and MBR, respectively, was obtained.

Nitrogen removal in a combined aerobic granular sludge and solid-phase biological denitrification system: System evaluation and community structure

In the present study, the feasibility of treating high ammonia wastewater was evaluated in a combination of aerobic granular sludge nitrification reactor (AGS-SBR) and poly(butylene succinate) solid denitrification reactor (PBS-SBR). After 90 days operation, the effluent NH₄⁺-N and total nitrogen (TN) removal efficiencies were high of 99.6% and 99.7%, respectively. According to typical cycle, N₂O emission rate in AGS nitrification process was much higher than PBS denitrification process. It was found from EEM-PARAFAC that the fluorescence intensity scores (protein-like and humic like substances) of soluble microbial products (SMP) in AGS-SBR were the significant higher than in PBS-SBR. Microbial community analysis showed that Thauera was main genus in AGS-SBR and Hydrogenophaga Simplicispira and Thiomonas were dominant genus in PBS-SBR. The obtained result implied that the combined technology is feasible to remove nitrogen compounds from wastewater to meet the stringent emission standards.

Calibration of the comprehensive NDHA-N2O dynamics model for nitrifier-enriched biomass using targeted respirometric assays

The NDHA model comprehensively describes nitrous oxide (N₂O) producing pathways by both autotrophic ammonium oxidizing and heterotrophic bacteria. The model was calibrated via a set of targeted extant respirometric assays using enriched nitrifying biomass from a lab-scale reactor. Biomass response to ammonium, hydroxylamine, nitrite and N₂O additions under aerobic and anaerobic conditions were tracked with continuous measurement of dissolved oxygen (DO) and N₂O. The sequential addition of substrate pulses allowed the isolation of oxygen-consuming processes. The parameters to be estimated were determined by the information content of the datasets using identifiability analysis. Dynamic DO profiles were used to calibrate five parameters corresponding to endogenous, nitrite oxidation and ammonium oxidation processes. The subsequent N₂O calibration was not significantly affected by the uncertainty propagated from the DO calibration because of the high accuracy of the estimates. Five parameters describing the individual contribution of three biological N₂O pathways were estimated accurately (variance/mean < 10% for all estimated parameters). The NDHA model response was evaluated with statistical metrics (F-test, autocorrelation function). The 95% confidence intervals of DO and N₂O predictions based on the uncertainty obtained during calibration are studied for the first time. The measured data fall within the 95% confidence interval of the predictions, indicating a good model description. Overall, accurate parameter estimation and identifiability analysis of ammonium removal significantly decreases the uncertainty propagated to N₂O production, which is expected to benefit N₂O model discrimination studies and reliable full scale applications.

Reduction and prediction of N2O emission from an Anoxic/Oxic wastewater treatment plant upon DO control and model simulation

In order to make a better understanding of the characteristics of N₂O emission in A/O wastewater treatment plant, full-scale and pilot-scale experiments were carried out and a back propagation artificial neural network model based on the experimental data was constructed to make a precise prediction of N₂O emission. Results showed that, N₂O flux from different units followed a descending order: aerated grit tank>oxic zone≫anoxic zone>final clarifier>primary clarifier, but 99.4% of the total emission of N₂O (1.60% of N-load) was monitored from the oxic zone due to its big surface area. A proper DO control could reduce N₂O emission down to 0.21% of N-load in A/O process, and a two-hidden-layers back propagation model with an optimized structure of 4:3:9:1 could achieve a good simulation of N₂O emission, which provided a new method for the prediction of N₂O emission during wastewater treatment.