Mathematical modelling of greenhouse gas emissions from membrane bioreactors: A comprehensive comparison of two mathematical models

Modeling nitrous oxide emissions in membrane bioreactors: Advancements, challenges and perspectives

Membrane bioreactors (MBRs) have become a well-established wastewater treatment technology owing to their extraordinary efficiency and low space advantage over conventional activated sludge processes. Although the extended activated sludge models can predict the general trend of nitrous oxide (N₂O) emissions in MBRs, the simulation results usually deviate from the actual values. This review critically evaluates the recent advances in the modeling of N₂O emissions in MBRs, and proposes future directions for the development and improvement of models that better match the MBR characteristics. The quantitative impact of MBR characteristics on N₂O emissions is identified as a key knowledge gap demanding urgent attention. Accurately clarification of the N₂O emission pathways governed by MBR characteristics is essential to improve the reliability and practicability of existing models. This article lays a momentous foundation for the optimization of N₂O models in MBRs, and proposes new demands for the next-generation model. The contents will assist academics and engineers in developing N₂O production models for accurate prediction.

Greenhouse gas emission estimation from municipal wastewater using a hybrid approach of generative adversarial network and data-driven modelling

Greenhouse gas (GHG) emissions including carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O) created via wastewater treatment processes are not easily modeled given the non-linearity and complexity of biological processes. These factors are also impacted by limited data availability making the development of artificial data generation algorithms, such as a generative adversarial network (GAN), useful for determination of GHG emission rate estimates (EREs). The main objective of this study was to develop a hybrid approach of using GAN and regression modelling to determine GHG EREs from a cold-region biological nutrient removal (BNR) municipal wastewater treatment plant (MWTP) in which the aerobic reactor has previously been established as the main GHG emission source. To our knowledge, this is the first application of GAN used for MWTP modelling purposes. The EREs were generated from laboratory-scale reactors used in conjunction with facility-monitored operating parameters to develop the GAN and regression models. Results showed that regression models provided reasonable EREs using parameters including hydraulic retention time (HRT), temperature, total organic carbon, and dissolved oxygen (DO) concentrations for CO₂ EREs; HRT, temperature, DO and phosphate (PO₄^3-) concentrations for CH₄ EREs; and temperature, DO, and nitrogen (nitrite, nitrate, and ammonium) concentrations for N₂O EREs. Additionally, the addition of 100 GAN-created virtual data points improved regression model metrics including increased correlation coefficient and index agreement values, and decreased root mean square error values. Clearly, virtual data augmentation using GAN is a valuable resource in supplementation of limited data for improved modelling outcomes. Genetic algorithm optimization was also used to determine operating parameter modifications resulting in potential for minimization (or maximization) of GHG emissions.

Development of a double-layer EPS-ASM2d model to illustrate the effect on mainstream biological phosphorus system in side-stream phosphorus recovery process

In order to deeply investigate the influences of side-stream phosphorus (P) recovery operation on mainstream biological P removal system, an improved activated sludge model no. 2 (ASM2d) was established to illuminate the metabolic processes of P in a side-stream P recovery reactor. The improved ASM2d (named D-EPS-ASM2d) was established by extending of the P metabolic processes of double-layer extracellular polymeric substances (EPS) into conventional ASM2d model. The predicted effluent concentrations of COD, NH₄, and TP by the D-EPS-ASM2d had good fits with measured values in the side-stream P recovery process. Comparing with conventional ASM2d, the likelihood values of D-EPS-ASM2d related to COD, NH₄, and TP effluents were increased from 0.694, 0.837 and 0.762 to 0.868, 0.904 and 0.920, respectively, implying the simulation performances of D-EPS-ASM2d on nutrient removal processes were significantly improved. Besides, the calibrated values of f_PP,TEPS was 0.09, 0.102 and 0.123 as side-stream volume (SSV) increasing from 0.3 to 0.9, implying the fraction of P removal by tightly-bound EPS was enhanced with the increase of SSV.

Integrated membrane bioreactors modelling: A review on new comprehensive modelling framework

Integrated Membrane Bioreactor (MBR) models, combination of biological and physical models, have been representing powerful tools for the accomplishment of high environmental sustainability. This paper, produced by the International Water Association (IWA) Task Group on Membrane Modelling and Control, reviews the state-of-the-art, identifying gaps for future researches, and proposes a new integrated MBR modelling framework. In particular, the framework aims to guide researchers and managers in pursuing good performances of MBRs in terms of effluent quality, operating costs (such as membrane fouling, energy consumption due to aeration) and mitigation of greenhouse gas emissions.

Membrane processes

This literature review provides a review for publications in 2018 and 2019 and includes information membrane processes findings for municipal and industrial applications. This review is a subsection of the annual Water Environment Federation literature review for Treatment Systems section. The following topics are covered in this literature review: industrial wastewater and membrane. Bioreactor (MBR) configuration, membrane fouling, design, reuse, nutrient removal, operation, anaerobic membrane systems, microconstituents removal, membrane technology advances, and modeling. Other sub-sections of the Treatment Systems section that might relate to this literature review include the following: Biological Fixed-Film Systems, Activated Sludge, and Other Aerobic Suspended Culture Processes, Anaerobic Processes, and Water Reclamation and Reuse. This publication might also have related information on membrane processes: Industrial Wastes, Hazardous Wastes, and Fate and Effects of Pollutants.

Recent advances in nitrous oxide production and mitigation in wastewater treatment

Nitrous oxide (N₂O) emitted from wastewater treatment plants has caused widespread concern. Over the past decade, people have made tremendous efforts to discover the microorganisms responsible for N₂O production, elucidate metabolic pathways, establish production models and formulate mitigation strategies. The ultimate goal of all these efforts is to shed new light on how N₂O is produced and how to reduce it, and one of the best ways is to find key opportunities by integrating the information obtained. This review article critically evaluates the knowledge gained in the field within a decade, especially in N₂O production microbiology, biochemistry, models and mitigation strategies, with a focus on denitrification. Previous research has greatly deepened the understanding of the N₂O generation mechanism, but further efforts are still needed due to the lack of standardized methodology for establishing N₂O mitigation strategies in full-scale systems. One of the challenges seems to be to convert the denitrification process from a net N₂O source into an effective sink, which is recommended as a key opportunity to reduce N₂O production in this review.

Uncertainty and sensitivity analysis for reducing greenhouse gas emissions from wastewater treatment plants

This paper presents the sensitivity and uncertainty analysis of a plant-wide mathematical model for wastewater treatment plants (WWTPs). The mathematical model assesses direct and indirect (due to the energy consumption) greenhouse gases (GHG) emissions from a WWTP employing a whole-plant approach. The model includes: (i) the kinetic/mass-balance based model regarding nitrogen; (ii) two-step nitrification process; (iii) N₂O formation both during nitrification and denitrification (as dissolved and off-gas concentration). Important model factors have been selected by using the Extended-Fourier Amplitude Sensitivity Testing (FAST) global sensitivity analysis method. A scenario analysis has been performed in order to evaluate the uncertainty related to all selected important model factors (scenario 1), important model factors related to the influent features (scenario 2) and important model factors related to the operational conditions (scenario 3). The main objective of this paper was to analyse the key factors and sources of uncertainty at a plant-wide scale influencing the most relevant model outputs: direct and indirect (DIR,CO_2eq and IND,CO_2eq, respectively), effluent quality index (EQI), chemical oxygen demand (COD) and total nitrogen (TN) effluent concentration (COD_OUT and TN_OUT, respectively). Sensitivity analysis shows that model factors related to the influent wastewater and primary effluent COD fractionation exhibit a significant impact on direct, indirect and EQI model factors. Uncertainty analysis reveals that outflow TN_OUT has the highest uncertainty in terms of relative uncertainty band for scenario 1 and scenario 2. Therefore, uncertainty of influential model factors and influent fractionation factors has a relevant role on total nitrogen prediction. Results of the uncertainty analysis show that the uncertainty of model prediction decreases after fixing stoichiometric/kinetic model factors.

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.

Position paper - progress towards standards in integrated (aerobic) MBR modelling

Membrane bioreactor (MBR) models are useful tools for both design and management. The system complexity is high due to the involved number of processes which can be clustered in biological and physical ones. Literature studies are present and need to be harmonized in order to gain insights from the different studies and allow system optimization by applying a control. This position paper aims at defining the current state of the art of the main integrated MBR models reported in the literature. On the basis of a modelling review, a standardized terminology is proposed to facilitate the further development and comparison of integrated membrane fouling models for aerobic MBRs.