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Despite water being a significant output of water and resource recovery facilities (WRRFs), tertiary wastewater treatment processes are often underrepresented in integrated WRRF models. This study critically reviews the approaches used in comprehensive models for ozone (O 3 ) and biological activated carbon (BAC) operation units for wastewater tertiary treatment systems. The current models are characterised by limitations in the mechanisms that describe O 3 disinfection and disinfection by-product formation, and BAC adsorption in multi-component solutes. Drawing from the insights from the current O 3 , BAC, and WRRF modelling approaches, we propose an integrated O 3 -BAC model suitable for simulating dissolved organic carbon (DOC) and micropollutants removal in the O 3 -BAC systems. We recommend a hybrid modelling approach in which data-driven models can be integrated to compensate for structural limitations in mechanistic models. The model is developed within the activated sludge model (ASM) framework for flexibility in coupling with other WRRF models and hence facilitates developing system-wide WRRF models for wastewater reclamation and reuse systems., Competing Interests: The authors declare there is no conflict., (© 2024 The Authors This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY 4.0), which permits copying, adaptation and redistribution, provided the original work is properly cited (http://creativecommons.org/licenses/by/4.0/).)

Emission of N 2 O represents an increasing concern in wastewater treatment, in particular for its large contribution to the plant's carbon footprint (CFP). In view of the potential introduction of more stringent regulations regarding wastewater treatment plants' CFP, there is a growing need for advanced monitoring with online implementation of mitigation strategies for N 2 O emissions. Mechanistic kinetic modelling in full-scale applications, are often represented by a very detailed representation of the biological mechanisms resulting in an elevated uncertainty on the many parameters used while limited by a poor representation of hydrodynamics. This is particularly true for current N 2 O kinetic models. In this paper, a possible full-scale implementation of a data mining approach linking plant-specific dynamics to N 2 O production is proposed. A data mining approach was tested on full-scale data along with different clustering techniques to identify process criticalities. The algorithm was designed to provide an applicable solution for full-scale plants' control logics aimed at online N 2 O emission mitigation. Results show the ability of the algorithm to isolate specific N 2 O emission pathways, and highlight possible solutions towards emission control., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

The choice of the spatial submodel of a water resource recovery facility (WRRF) model should be one of the primary concerns in WRRF modelling. However, currently used mechanistic models are limited by an over-simplified representation of local conditions. This is illustrated by the general difficulties in calibrating the latest N 2 O models and the large variability in parameter values reported in the literature. The use of compartmental model (CM) developed on the basis of accurate hydrodynamic studies using computational fluid dynamics (CFD) can take into account local conditions and recirculation patterns in the activated sludge tanks that are important with respect to the modelling objective. The conventional tanks in series (TIS) configuration does not allow this. The aim of the present work is to compare the capabilities of two model layouts (CM and TIS) in defining a realistic domain of parameter values representing the same full-scale plant. A model performance evaluation method is proposed to identify the good operational domain of each parameter in the two layouts. Already when evaluating for steady state, the CM was found to provide better defined parameter ranges than TIS. Dynamic simulations further confirmed the CM's capability to work in a more realistic parameter domain, avoiding unnecessary calibration to compensate for flaws in the spatial submodel.

Aeration is the largest energy consumer in most water and resource recovery facilities, which is why oxygen transfer optimization is fundamental to improve energy efficiency. Although oxygen transfer is strongly influenced by the bubble size distribution dynamics, most aeration efficiency models currently do not include this influence explicitly. In few cases, they assume a single average bubble size. The motivation of this work is to investigate this knowledge gap, i.e. a more accurate calculation of the impact of bubble size distribution dynamics on oxygen transfer. Experiments were performed to study bubble size distribution dynamics along the height of a bubble column at different air flow rates for both tap water and solutions that mimic the viscosity of activated sludge at different sludge concentrations. Results show that bubble size is highly dynamic in space and time since it is affected by hydrodrynamics and the viscosity of the liquid. Consequently, oxygen transfer also has a dynamic character. The concept of a constant overall volumetric oxygen transfer coefficient, K L a, can thus be improved. A new modeling approach to determine the K L a locally based on bubble size distribution dynamics is introduced as an alternative. This way, the K L a for the entire column is calculated and compared to the one measured by a traditional method. Results are in good agreement for tap water. The modeled K L a based on the new approach slightly overestimates the experimental K L a for solutions that mimic the viscosity of activated sludge. The difference appears to be lower when the air flow rate increases. This work can be considered as a first step towards more accurate and rigorous mechanistic aeration efficiency models which are based on in-depth mechanism knowledge. This is key for oxygen transfer optimization and consequently energy savings., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

The large global warming potential of nitrous oxide (N 2 O) is currently of general concern for the water industry, especially in view of a new regulatory framework concerning the carbon footprint of water resource recovery facilities (WRRFs). N 2 O can be generated through different biological pathways and from different treatment steps of a WRRF. The use of generic emission factors (EF) for quantifying the emissions of WRRFs is discouraged. This is due to the number of different factors that can affect how much, when and where N 2 O is emitted from WRRFs. The spatial and temporal variability of three WRRFs in Europe using comparable technologies is presented. An economically feasible and user-friendly method for accounting for the contribution of anoxic zones via direct gas emission measurements was proven. The investigation provided new insights into the contribution from the anoxic zones versus the aerobic zones of biological WRRF tanks and proved the unsuitability of the use of a single EF for the three WRRFs. Dedicated campaigns for N 2 O emissions assessment are to be advised. However, similarities in the EF magnitude can be found considering treatment strategy and influent water composition.

The efficiency of aeration systems should be monitored to guarantee suitable biological processes. Among the available tools for evaluating the aeration efficiency, the off-gas method is one of the most useful. Increasing interest towards reducing greenhouse gas (GHG) emissions from biological processes has resulted in researchers using this method to quantify N 2 O and CO 2 concentrations in the off-gas. Experimental measurements of direct GHG emissions from aerobic digesters (AeDs) are not available in literature yet. In this study, the floating hood technique was used for the first time to monitor AeDs. The floating hood technique was used to evaluate oxygen transfer rates in an activated sludge (AS) tank of a medium-sized municipal wastewater treatment plant located in Italy. Very low values of oxygen transfer efficiency were found, confirming that small-to-medium-sized plants are often scarcely monitored and wrongly managed. Average CO 2 and N 2 O emissions from the AS tank were 0.14 kg CO2 /kg bCOD and 0.007 kg CO2,eq /kg bCOD , respectively. For an AeD, 3 × 10 -10  kg CO2 /kg bCOD direct CO 2 emissions were measured, while CO 2,eq emissions from N 2 O were 4 × 10 -9  kg CO2,eq /kg bCOD . The results for the AS tank and the AeD were used to estimate the net carbon and energy footprint of the entire plant.