Quantifying sensitivity and uncertainty analysis of a new mathematical model for the evaluation of greenhouse gas emissions from membrane bioreactors

Reducing biosolids from a membrane bioreactor system: Assessing the effects on carbon and nutrient removal, membrane fouling and greenhouse gas emissions

This study presents the effects on carbon and nutrient removal, membrane fouling and greenhouse gas (GHG) emissions of an Oxic-Settling-Anaerobic (OSA) - Membrane Bioreactor (MBR) pilot plant fed with real wastewater. The influence of three sludge return internal ratios (IR) was investigated by testing 45, 75 and 100%. The results showed that with the increase of IR, the biological sludge production substantially decreased by 85.8% due to the combination of cell lysis and endogenous metabolism. However, a worsening of ammonia removal efficiencies occurred (from 94.5 % to 84.7 with an IR value of 45 and 100%, respectively) mostly due to the ammonia release caused by cell lysis under anaerobic conditions. The N2O emission factor increased with the rise of IR (namely, from 2.17% to 2.54% of the total influent nitrogen). In addition, a variation of carbon footprint (CF) (0.78, 0.62 and 0.75 kgCO2eq m-3 with 45, 75 and 100% IR, respectively) occurred with IR mainly due to the different energy consumption and carbon oxidation during the three periods. The study's relevance is to address the optimal operating conditions in view of reducing sludge production. In this light, the need to identify a trade-off between the advantages of reducing sludge production and the disadvantages of increasing membrane fouling and GHG emissions must be identified in the future.

Modelling greenhouse gas emissions from biological wastewater treatment by GPS-X: The full-scale case study of Corleone (Italy)

Greenhouse gas (GHG) emissions from wastewater treatment plants (WWTPs) can affect climate change and must be measured and reduced. Mathematical modelling is an attractive solution to get a tool for GHG mitigation. However, although many efforts have been made to create reliable tools that can simulate "sustainable" full-scale WWTP operation, these studies are not considered complete enough to include GHG emissions and energy consumption of biological processes under long-term dynamic conditions. In this study, activated sludge model no. 1 (ASM1) was modified to model nitrous oxide (N2O) emissions with a plant-wide modelling approach. The model is novel compared to the state of the art since it includes three steps denitrification, all N2O production pathways and its stripping in an ASM1. The model has been calibrated and validated through long-term water quality and short-term N2O emissions data collected from Corleone (Italy) WWTP. Different dissolved oxygen (DO) concentrations and return sludge (RAS) ratios were tested with dynamic simulations to optimise the full-scale WWTP. The scenarios have been compared synergistically with effluent quality, direct GHG emissions, and energy footprint by the water-energy‑carbon coupling index (WECCI). This modelling study is novel as it fully covers long-term calibration/validation of the model with N2O measurements and tests the dynamic optimisation. Decision-makers and operators can use this new model to optimise GHG emissions and treatment costs.

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.

Minimizing membrane bioreactor environmental footprint by multiple objective optimization

This paper presents a modelling study aimed at minimizing the environmental foot print of a membrane bioreactor (MBR) for wastewater treatment. Specifically, an integrated model for MBR was employed in view of the management optimization of an MBR biological nutrient removal (BNR) pilot plant in terms of operational costs and direct greenhouse gases emissions. The influence of the operational parameters (OPs) on performance indicators (PIs) was investigated by adopting the Extended-FAST sensitivity analysis method. Further, a multi-objective analysis was performed by applying the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The results show-up that the sludge retention time is the OP mostly affecting all the investigated PIs. By applying the set of optimal OPs, there was a reduction of 48% and 10% of the operational costs and direct emissions, respectively.

Aeration control in membrane bioreactor for sustainable environmental footprint

In this study different scenarios were scrutinized to minimize the energy consumption of a membrane bioreactor system for wastewater treatment. Open-loop and closed-loop scenarios were investigated by two-step cascade control strategies based on dissolved oxygen, ammonia and nitrite concentrations. An integrated MBR model which includes also the greenhouse gas formation/emission processes was applied. A substantial energy consumption reduction was obtained for the closed-loop scenarios (32% for Scenario 1 and 82% for Scenario 2). The air flow control based on both ammonia and nitrite concentrations within the aerobic reactor (Scenario 2) provided excellent results in terms of reduction of operating cost reduction (64%), direct (10%) and indirect (81%) emissions.

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

This paper compares two mathematical models (Model I and Model II) to predict greenhouse gases emission from a University Cape Town (UCT) - membrane bioreactor (MBR) plant. Model I considers N₂O production only during denitrification. Model II takes into account the ammonia-oxidizing bacteria (AOB) formation pathways for N₂O. Both models were calibrated adopting real data. Model comparison was performed in terms of (i) sensitivity analysis (ii) best fit and (iii) model prediction uncertainty. On average 6% of factors of Model I and 9% of Model II resulted to be important. In terms of best fit, Model II had a better capability of reproducing the measured data. The average efficiency related to the N₂O model outputs was equal to 0.33 and 0.38 for Model I and Model II, respectively. On average, 73% (Model I) and 86% (Model II) of measured data lay inside the uncertainty bands.

Greenhouse gas emissions and the links to plant performance in a fixed-film activated sludge membrane bioreactor - Pilot plant experimental evidence

The present study explores the interlinkages among the operational variables of a University of Cape Town (UCT) Integrated Fixed Film Activated Sludge (IFAS) membrane bioreactor (MBR) pilot plant. Specifically, dedicated experimental tests were carried out with the final aim to find-out a constitutive relationship among operational costs (OCs), effluent quality index (EQI), effluent fines (EF). Greenhouse gas (GHG) emissions were also included in the study. Results showed that the EQI increases at low flow rate likely due to the dissolved oxygen (DO) limitation in the biological processes. Direct GHGs increase with the increasing of the air flow due to the anoxic N₂O contribution. Irreversible membrane fouling reduce from 98% to 85% at the air flow rate of 0.57m³h^-1 and 2.56m³h^-1, respectively. However, the increase of the air flow rate leads to the increase of the N₂O-N flux emitted from the MBR (from 40% to 80%).

Greenhouse gases from membrane bioreactors: Mathematical modelling, sensitivity and uncertainty analysis

In this study a new mathematical model to quantify greenhouse gas emissions (namely, carbon dioxide and nitrous oxide) from membrane bioreactors (MBRs) is presented. The model has been adopted to predict the key processes of a pilot plant with pre-denitrification MBR scheme, filled with domestic and saline wastewater. The model was calibrated by adopting an advanced protocol based on an extensive dataset. In terms of nitrous oxide, the results show that an important role is played by the half saturation coefficients related to nitrogen removal processes and the model factors affecting the oxygen transfer rate in the aerobic and MBR tanks. Uncertainty analysis showed that for the gaseous model outputs 88-93% of the measured data lays inside the confidence bands showing an accurate model prediction.

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

A modified AOB-NOB-N₂O-SMP model able to quantify nitrous oxide (N₂O) emissions and soluble microbial product (SMP) production during wastewater treatment is proposed. The modified AOB-NOB-N₂O-SMP model takes into account: (1) two-step nitrification by ammonia-oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB), (2) N₂O production by AOB denitrification under oxygen-limited conditions and (3) SMP production by microbial growth and endogenous respiration. Validity of the modified model is demonstrated by comparing the simulation results with experimental data from lab-scale sequencing batch reactors (SBRs). To reliably implement the modified model, a model calibration that adjusts model parameters to fit the model outputs to the experimental data is conducted. The results of this study showed that the modeling accuracy of the modified AOB-NOB-N₂O-SMP model increases by 19.7% (NH₄), 51.0% (NO₂), 57.8% (N₂O) and 16.7% (SMP) compared to the conventional model which does not consider the two-step nitrification and SMP production by microbial endogenous respiration.

Greenhouse gases from wastewater treatment - A review of modelling tools

Nitrous oxide, carbon dioxide and methane are greenhouse gases (GHG) emitted from wastewater treatment that contribute to its carbon footprint. As a result of the increasing awareness of GHG emissions from wastewater treatment plants (WWTPs), new modelling, design, and operational tools have been developed to address and reduce GHG emissions at the plant-wide scale and beyond. This paper reviews the state-of-the-art and the recently developed tools used to understand and manage GHG emissions from WWTPs, and discusses open problems and research gaps. The literature review reveals that knowledge on the processes related to N2O formation, especially due to autotrophic biomass, is still incomplete. The literature review shows also that a plant-wide modelling approach that includes GHG is the best option for the understanding how to reduce the carbon footprint of WWTPs. Indeed, several studies have confirmed that a wide vision of the WWPTs has to be considered in order to make them more sustainable as possible. Mechanistic dynamic models were demonstrated as the most comprehensive and reliable tools for GHG assessment. Very few plant-wide GHG modelling studies have been applied to real WWTPs due to the huge difficulties related to data availability and the model complexity. For further improvement in GHG plant-wide modelling and to favour its use at large real scale, knowledge of the mechanisms involved in GHG formation and release, and data acquisition must be enhanced.