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The concentration of domestic slurry has two advantages, it promotes resource recovery (nutrients and biomass) and saves water. But the design of a relevant sewerage requires a clear understanding of the frictional losses incurred during the transport of the slurry. This abstracts describes numerical & CFD-based methods to estimate losses while the concentrated slurry flows through circular pipes in a fully-turbulent flow. To model turbulent flows through circular pipes, one can rely on either the Newtonian Moody Charts appropriate for engineering applications or a computational fluid dynamics (CFD)-based analysis, made possible through the Newtonian universal law of the wall. However, our studies reveal that concentrated domestic slurry behaves like a non-Newtonian fluid, of the Herschel-Bulkley type. Therefore, the analysis of such a slurry would require modifications to both, existing engineering models and CFD methods. This abstract summarises a modified law of the wall suitable for Herschel-Bulkley fluids, which has been validated against experiments on concentrated domestic slurry. It further details possible non-Newtonian numerical engineering models that could be modified to assess frictional losses incurred by Herschel-Bulkley fluids. The latter will be a quicker and perhaps reliable alternative to computationally expensive CFD-analyses.

Due to the ageing of our underground wastewater infrastructure, leakage of sewers and pressure mains and subsequent infiltration or exfiltration are becoming an increasingly important issue. Herein, we present a novel method to detect and potentially quantify exfiltration from sewer systems under variable flow conditions; the DEST method. The DEST method is based on the principle of setting up a mass balance of a tracer substance. At an upstream point a tracer is injected in a sewer with a constant rate for a certain period, subsequently downstream high frequent time discrete grab samples are combined with discharge measurements to complete the mass balance. The method is applied on a sewer section in Loenen (NL) to investigate its feasibility. Two different tracers are used; Lithium chloride and Deuterium. Preliminary results indicate that both tracers show similar behaviour at the downstream measurement point. Final lab results are expected at the end of March, allowing in depth analysis of the experimental results with a focus on the measurement uncertainty.

The use of decision support systems (DSS) allows integrating all the issues related with sustainable development in view of providing a useful support to solve multi-scenario problems. In this work an extensive review on the DSSs applied to wastewater treatment plants (WWTPs) is presented. The main aim of the work is to provide an updated compendium on DSSs in view of supporting researchers and engineers on the selection of the most suitable method to address their management/operation/design problems. Results showed that DSSs were mostly used as a comprehensive tool that is capable of integrating several data and a multi-criteria perspective in order to provide more reliable results. Only one energy-focused DSS was found in literature, while DSSs based on quality and operational issues are very often applied to site-specific conditions. Finally, it would be important to encourage the development of more user-friendly DSSs to increase general interest and usability., This work is part of a research project supported by grant of the Italian Ministry of Education, University and Research (MIUR) through the Research project of national interest PRIN2012 (D.M. 28 December 2012 n. 957/Ric – Prot. 2012PTZAMC) entitled “Energy consumption and Greenhouse Gas (GHG) emissions in the wastewater treatment plants: a decision support system for planning and management – http://ghgfromwwtp.unipa.it” in which the first author is the Principal Investigator. In addition, some coauthors acknowledge the partial support of the Industrial Doctorate Programme (2017-DI-006) and the Research Consolidated Groups/Centres Grant (2017 SGR 574) from the Catalan Agency of University and Research Grants Management (AGAUR), from Catalan Government.

An integrated membrane bioreactor (MBR) model was previously proposed and tested. The model provides a comprehensive and detailed description of the nitrogen biological removal processes with respect to up-to-date literature. This paper presents a sensitivity and uncertainty analysis aimed at identifying the key factors affecting the variability of the model predictions. The Standardized Regression Coefficients (SRC) method was adopted for the sensitivity analysis. The uncertainty analysis was employed by running Monte Carlo simulations by varying only the value of the key factors affecting the model outputs. The sensitivity analysis combined with the uncertainty analysis applied here enabled to gain useful insights about the robustness of the model. By means of the SRC method 45 model factors (of 122) were selected as important. The results obtained here allowed to investigate the advantage of a detailed description of the nitrogen transformation bioprocesses (nitrification/denitrification) in terms of model accuracy and uncertainty bandwidth. The model allows to simulate the intermediate product during nitrification/denitrification, thus providing the possibility to control the nitrogen compounds that favour the formation of nitrous oxide.

In this study a University of Cape Town (UCT) Integrated Fixed Film Activated Sludge (IFAS) Membrane BioReactor (MBR) wastewater treatment plant was monitored in terms of nitrous oxide (N2O) emissions. The short term effect on the N2O emission due to the influent carbon-to-nitrogen (C/N) ratio variation (C/N ratios of 2, 5 and 10 gCOD/gN) was evaluated. Since in a previous study, the effect of the C/N ratio was studied in the same system without biofilm (UCT-MBR configuration) the main aim here was to investigate the role of biofilms on N2O emissions. Under all the investigated C/N ratios, the N2O fluxes and the average emission factors were lower than that of previous studies with no biofilm presence. The total average N2O emission was 0.5% of the influent nitrogen with biofilm (IFAS system) and 3.5% without biofilm. This result emphasizes the potential role of the biofilms in attenuating the N2O emissions especially in the case of stress conditions (i.e., low C/N influent ratios). An increase of N2O flux from the anoxic reactor (till 28 mgN2O m−2h−1) occurred at the lowest influent C/N tested (2 gCOD/gN - phase III). At C/N equal to 2 gCOD/gN the anoxic reactor was the main source of N2O, contributing 45% of all produced N2O. This result was attributed to an incomplete denitrification caused by a lack of organic carbon and a slight increase of dissolved oxygen concentration.

A comprehensive integrated membrane bioreactor (MBR) model for wastewater treatment is here proposed. The model quantifies the main biological and physical processes. The model describes the biological removal of organic matter, nitrogen and phosphorus including greenhouse gases (carbon dioxide, CO 2 and nitrous oxide, N 2 O). The model takes into account the following main innovative aspects jointly: i. Two-step nitrification process; ii. N 2 O formation due to ammonia-oxidizing bacteria as a product of the hydroxylamine oxidation (NH 2 OH) and of the nitrite (NO 2 − ) reduction; iii. Soluble microbial product (SMP) formation/degradation due to microbial growth and endogenous respiration; iv. Interlink between SMP and membrane fouling. The model was calibrated by employing a detailed calibration protocol and data from a University Cape Town (UCT) – MBR pilot plant. The key processes contributing to the N 2 O formation were properly described (total efficiency related to the calibrated model equal to 0.55). Results suggested that the incomplete hydroxylamine oxidation and the heterotrophic denitrification were the predominant processes influencing the N 2 O production. The model was able to describe the membrane fouling as demonstrated by the high efficiency (0.92) for the resistance state variable. This result confirms the importance in the modelling approach of considering both biological and physical processes jointly.

The aim of the present paper was to investigate the effect of solids (SRT) and hydraulic (HRT) retention time on Integrated Fixed Film Activated Sludge (IFAS) University of Cape Town (UCT) membrane Bioreactor (MBR). In particular, three different pairs of SRT and HRT values were analysed, namely, Phase I 56 d/30 h, Phase II 31 d/15 h and Phase III 7 d/13 h. The short-term effect of these three SRT/HRT conditions was assessed by analysing several system performance indicators: organic carbon and biological nutrient (nitrogen and phosphorus) removal, biomass respiratory activity, activated sludge filtration properties and membrane fouling. The results showed that the decrease of SRT/HRT had a positive influence on system performance. Specifically, the IFAS-UCT-MBR showed excellent removal of organic matter - highest value (99%) at the shortest SRT/HRT (7 d/13 h). Also, the increase in organic loading rate resulting from the decrease of SRT and HRT led to improved nitrogen removal due to higher N removal by sludge wasting requiring less N removal (as N2) by denitrification. Complete nitrification of influent ammonia was achieved at all three SRT/HRT phases, guaranteed by the presence of biofilm carriers in the aerobic reactor, which ensured a higher media SRT than suspended biomass SRT. The increase of the organic loading rate and decrease in SRT led also to a higher heterotrophic activity as demonstrated by the respirometric batch tests, which is due to the increasing active biomass fraction of the volatile suspended solids as SRT decreases. The SRT/HRT decrease over the three phases resulted in an overall increase of the Extracellular Polymeric Substance concentration, which caused an increase in membrane fouling.

The influence of the main operational variables on N2O emissions from an Integrated Fixed Film Activated Sludge University of Cape Town membrane Bioreactor pilot plant was studied. Nine operational cycles (total duration: 340 days) were investigated by varying the value of the mixed liquor sludge retention time (SRT) (Cycles 1–3), the feeding ratio between carbon and nitrogen (C/N) (Cycles 4–6) and simultaneously the hydraulic retention time (HRT) and the SRT (Cycles 7–9). Results show a huge variability of the N2O concentration in liquid and off-gas samples (ranged from 10−1μg N2O-N L−1to 103μg N2O-N L−1). The maximum N2O concentration (1228 μg N2O-N L−1) in the off-gas samples occurred in the anoxic reactor at the lowest C/N value confirming that unbalanced C/N promotes the N2O emission during denitrification. The aerated reactors (aerobic and MBR) have been the major N2O emitters during all the three Phases.

Sensitivity and uncertainty assessment of integrated urban drainage water quality models are crucial steps in the evaluation of the reliability of model results. Indeed, the assessment of the reliability of the results of complex water quality models is crucial in understanding their significance. In the case of integrated urban drainage water quality models, due to the fact that integrated approaches are basically a cascade of sub-models (simulating the sewer system, wastewater treatment plant and receiving water body), uncertainty produced in one sub-model propagates to the following ones in a manner dependent on the model structure, the estimation of parameters and the availability and uncertainty of measurements in the different parts of the system. Uncertainty basically propagates throughout a chain of models in which the simulation output from upstream models is transferred to the downstream ones as input. The paper presents the uncertainty assessment of an integrated urban drainage model developed in previous studies by means of the Generalized Likelihood Uncertainty Estimation (GLUE) methodology. A straightforward approach based on the analysis of the coefficient of variation (Rxy). Rxy is defined as the ratio between the standard deviation (α) and the average (μ) value of the model output of reference taken into account. The analysis has been applied to an experimental catchment in Bologna (Italy) which consists of a part of the Bologna sewer network and a reach of the Savena river. The results showed that the method can be a useful tool for uncertainty analysis and for guiding the operator in the choice of the modelling approach.

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.

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 N 2 O production only during denitrification. Model II takes into account the ammonia-oxidizing bacteria (AOB) formation pathways for N 2 O. 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 N 2 O 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.

A University of Cape Town Integrated Fixed-Film Activated Sludge Membrane Bioreactor (UCT-IFAS-MBR) pilot plant was operated at different values of the sludge retention time (SRT). Three SRTs were investigated at different durations: indefinitely, 30 and 15 days. The organic carbon, nitrogen and phosphorus removal, kinetic/stoichiometric parameters, membrane fouling tendency and sludge filtration properties were assessed. The findings showed that by decreasing the SRT, the pilot plant could maintain excellent carbon removal efficiencies throughout the experiments. In contrast, the biological carbon removal showed a slight nitrification and was slightly affected by the decrease of the SRT, showing high performance (approximately 91%, on average). Thus, the biofilm might have helped sustain the nitrification throughout the experiments. The average phosphorus removal performance increased slightly with a decrease in SRT, achieving the maximum efficiency (61.5%) at a SRT of 15 days. After a 30-day SRT, an increase in resistance due to pore blocking and a general worsening of the membrane filtration properties occurred.