A comprehensive, open-source data model for wastewater-based epidemiology.

The recent SARS-COV-2 pandemic has sparked the adoption of wastewater-based epidemiology (WBE) as a low-cost way to monitor the health of populations. In parallel, the pandemic has encouraged researchers to openly share their data to serve the public better and accelerate science. However, environmental surveillance data are highly dependent on context and are difficult to interpret meaningfully across sites. This paper presents the second iteration of the Public Health Environmental Surveillance Open Data Model (PHES-ODM), an open-source dictionary and set of data tools to enhance the interoperability of environmental surveillance data and enable the storage of contextual (meta)data. The data model describes how to store environmental surveillance program data, metadata about measurements taken on various specimens (water, air, surfaces, sites, populations) and data about measurement protocols. The model provides software tools that support the collection and use of PHES-ODM formatted data, including performing PCR calculations and data validation, recording data into input templates, generating wide tables for analysis, and producing SQL database definitions. Fully open-source and already adopted by institutions in Canada, the European Union, and other countries, the PHES-ODM provides a path forward for creating robust, interoperable, open datasets for environmental public health surveillance for SARS-CoV-2 and beyond.

Assessing the equivalence of WRRF regulations using dynamic model simulations.

A wide diversity of regulatory practices for wastewater resource recovery plants exists throughout the world. This contribution aims to highlight the implications of choosing particular permitting structures and investigate the equivalence of effluent standards in terms of limit values and compliance assessment specifications. These factors heavily affect the true performance that a treatment plant has to attain and thus the required plant capacity and operation. The dynamic simulations executed in this work, based on a realistic case study and three selected permits from China, The Netherlands and the USA, show the impact of certain compliance specifications like sampling frequency, averaging and tolerable permit exceedances leading to differences in the required design capacity of more than 250% for the same wastewater to be treated. The results also reveal clear differences between permits in their capacity to handle excess variability. The latter is important to avoid overdesign, i.e., when further investment in treatment capacity would result only in marginal effluent quality gains, as well as to create a safe space for testing innovative technologies or ways of operation that might otherwise trigger compliance issues.

Wastewater-based epidemiology: the crucial role of viral shedding dynamics in small communities.

Background: Wastewater surveillance (WWS) of pathogens is a rapidly evolving field owing to the 2019 coronavirus disease pandemic, which brought about a paradigm shift in public health authorities for the management of pathogen outbreaks. However, the interpretation of WWS in terms of clinical cases remains a challenge, particularly in small communities where large variations in pathogen concentrations are routinely observed without a clear relation to clinical incident cases. Methods: Results are presented for WWS from six municipalities in the eastern part of Canada during the spring of 2021. We developed a numerical model based on viral kinetics reduction functions to consider both prevalent and incident cases to interpret the WWS data in light of the reported clinical cases in the six surveyed communities. Results: The use of the proposed numerical model with a viral kinetics reduction function drastically increased the interpretability of the WWS data in terms of the clinical cases reported for the surveyed community. In line with our working hypothesis, the effects of viral kinetics reduction modeling were more important in small communities than in larger communities. In all but one of the community cases (where it had no effect), the use of the proposed numerical model led to a change from a +1.5% (for the larger urban center, Quebec City) to a +48.8% increase in the case of a smaller community (Drummondville). Conclusion: Consideration of prevalent and incident cases through the proposed numerical model increases the correlation between clinical cases and WWS data. This is particularly the case in small communities. Because the proposed model is based on a biological mechanism, we believe it is an inherent part of any wastewater system and, hence, that it should be used in any WWS analysis where the aim is to relate WWS measurement to clinical cases.

The future of WRRF modelling - outlook and challenges.

The wastewater industry is currently facing dramatic changes, shifting away from energy-intensive wastewater treatment towards low-energy, sustainable technologies capable of achieving energy positive operation and resource recovery. The latter will shift the focus of the wastewater industry to how one could manage and extract resources from the wastewater, as opposed to the conventional paradigm of treatment. Debatable questions arise: can the more complex models be calibrated, or will additional unknowns be introduced? After almost 30 years using well-known International Water Association (IWA) models, should the community move to other components, processes, or model structures like 'black box' models, computational fluid dynamics techniques, etc.? Can new data sources - e.g. on-line sensor data, chemical and molecular analyses, new analytical techniques, off-gas analysis - keep up with the increasing process complexity? Are different methods for data management, data reconciliation, and fault detection mature enough for coping with such a large amount of information? Are the available calibration techniques able to cope with such complex models? This paper describes the thoughts and opinions collected during the closing session of the 6th IWA/WEF Water Resource Recovery Modelling Seminar 2018. It presents a concerted and collective effort by individuals from many different sectors of the wastewater industry to offer past and present insights, as well as an outlook into the future of wastewater modelling.

How well-mixed is well mixed? Hydrodynamic-biokinetic model integration in an aerated tank of a full-scale water resource recovery facility.

Current water resource recovery facility (WRRF) models only consider local concentration variations caused by inadequate mixing to a very limited extent, which often leads to a need for (rigorous) calibration. The main objective of this study is to visualize local impacts of mixing by developing an integrated hydrodynamic-biokinetic model for an aeration compartment of a full-scale WRRF. Such a model is able to predict local variations in concentrations and thus allows judging their importance at a process level. In order to achieve this, full-scale hydrodynamics have been simulated using computational fluid dynamics (CFD) through a detailed description of the gas and liquid phases and validated experimentally. In a second step, full ASM1 biokinetic model was integrated with the CFD model to account for the impact of mixing at the process level. The integrated model was subsequently used to evaluate effects of changing influent and aeration flows on process performance. Regions of poor mixing resulting in non-uniform substrate distributions were observed even in areas commonly assumed to be well-mixed. The concept of concentration distribution plots was introduced to quantify and clearly present spatial variations in local process concentrations. Moreover, the results of the CFD-biokinetic model were concisely compared with a conventional tanks-in-series (TIS) approach. It was found that TIS model needs calibration and a single parameter set does not suffice to describe the system under both dry and wet weather conditions. Finally, it was concluded that local mixing conditions have significant consequences in terms of optimal sensor location, control system design and process evaluation.

Dynamic modelling of solids in a full-scale activated sludge plant preceded by CEPT as a preliminary step for micropollutant removal modelling.

The presence of micropollutants in the environment has triggered research on quantifying and predicting their fate in wastewater treatment plants (WWTPs). Since the removal of micropollutants is highly related to conventional pollutant removal and affected by hydraulics, aeration, biomass composition and solids concentration, the fate of these conventional pollutants and characteristics must be well predicted before tackling models to predict the fate of micropollutants. In light of this, the current paper presents the dynamic modelling of conventional pollutants undergoing activated sludge treatment using a limited set of additional daily composite data besides the routine data collected at a WWTP over one year. Results showed that as a basis for modelling, the removal of micropollutants, the Bürger-Diehl settler model was found to capture the actual effluent total suspended solids (TSS) concentrations more efficiently than the Takács model by explicitly modelling the overflow boundary. Results also demonstrated that particular attention must be given to characterizing incoming TSS to obtain a representative solids balance in the presence of a chemically enhanced primary treatment, which is key to predict the fate of micropollutants.

Fate and mass balance of contaminants of emerging concern during wastewater treatment determined using the fractionated approach.

Contaminants of emerging concern (CECs) are often poorly removed from wastewater using conventional treatment technologies and there is limited understanding of their fate during treatment. Inappropriate sampling strategies lead to inaccuracies in estimating removals of CECs. In this study, we used the "fractionated approach" that accounts for the residence time distribution (RTD) in treatment units to investigate the fate of 26 target CECs in a municipal wastewater treatment plant (WWTP) that includes primary, secondary and tertiary treatment steps. Prior hydraulic calibration of each treatment unit was performed. Wastewater and sludge samples were collected at different locations along the treatment train and the concentrations of target CECs were measured by liquid chromatography mass spectrometry. The most substantial aqueous removal occurred during activated sludge treatment (up to 99%). Removals were <50% in the primary clarifier and tertiary rotating biological contactors (RBCs) and up to 70% by sand filtration. Mass balance calculations demonstrated that (bio)degradation accounted for up to 50% of the removal in the primary clarifier and 100% in activated sludge. Removal by sorption to primary and secondary sludge was minimal for most CECs. Analysis of the selected metabolites demonstrated that negative removals obtained could be explained by transformations between the parent compound and their metabolites. This study contributes to the growing literature by applying the fractionated approach to calculate removal of different types of CECs across each wastewater treatment step. An additional level of understanding of the fate of CECs was provided by mass balance calculations in primary and secondary treatments.

From the affinity constant to the half-saturation index: understanding conventional modeling concepts in novel wastewater treatment processes.

The "affinity constant" (KS) concept is applied in wastewater treatment models to incorporate the effect of substrate limitation on process performance. As an increasing number of wastewater treatment processes rely on low substrate concentrations, a proper understanding of these so-called constants is critical in order to soundly model and evaluate emerging treatment systems. In this paper, an in-depth analysis of the KS concept has been carried out, focusing on the different physical and biological phenomena that affect its observed value. By structuring the factors influencing half-saturation indices (newly proposed nomenclature) into advectional, diffusional and biological, light has been shed onto some of the apparent inconsistencies present in the literature. Particularly, the importance of non-ideal mixing as a source of variability between observed KS values in different systems has been illustrated. Additionally, discussion on the differences existent between substrates that affect half-saturation indices has been carried out; it has been shown that the observed KS for some substrates will reflect transport or biological limitations more than others. Finally, potential modeling strategies that could alleviate the shortcomings of the KS concept have been provided. These could be of special importance when considering the evaluation and design of emerging wastewater treatment processes.

CFD study to determine the optimal configuration of aerators in a full-scale waste stabilization pond.

Aerated lagoons (ALs) are important variants of the pond wastewater treatment technology that have not received much attention in the literature. The hydraulic behaviour of ALs and especially the Facultative aerated lagoons (FALs) is very complex since the aeration in these systems is designed for oxygen transfer but not necessarily to create complete mixing. In this work, the energy expenditure of the aerators was studied by means of a scenario analysis. 3D CFD models (one phase and multiphase) of a 3 ha FAL in a waste stabilization pond system in Cuenca (Ecuador) were built for different configurations of aerators. The thrust produced by the aerators was modelled by an external momentum source applied as velocity vectors into the pond fluid. The predictions of a single phase model were in satisfactory agreement with experimental results. Subsequently, a scenario analysis assessing several aeration schemes with different numbers of aerators in operation were tested with respect to velocity profiles and residence time distribution (RTD) curves. This analysis showed that the aeration scheme with all 10 aerators switched on produces a similar hydraulic behaviour compared to using only 6 or 8 aerators. The current operational schemes comprise of switching off some aerators during the peak hours of the day and operating all 10 aerators during night. This current practice could be economically replaced by continuously operating 4 or 6 aerators without significantly affecting the overall mixing. Furthermore, a continuous mixing regime minimises the sediment oxygen demand enhancing the oxygen levels in the pond.

Membrane bioreactor fouling behaviour assessment through principal component analysis and fuzzy clustering.

Adequate membrane bioreactor operation requires frequent evaluation of the membrane state. A data-driven approach based on principal component analysis (PCA) and fuzzy clustering extracting the necessary monitoring information solely out of transmembrane pressure data was investigated for this purpose. Out of three tested PCA techniques the two functional methods proved useful to cope with noise and outliers as opposed to the common standard PCA, while all of them presented similar capabilities for revealing data trends and patterns. The expert functional PCA approach enabled linking the two major trends in the data to reversible fouling and irreversible fouling. The B-splines approach provided a more objective way for functional representation of the data set but its complexity did not appear justified by better results. The fuzzy clustering algorithm, applied after PCA, was successful in recognizing the data trends and placing the cluster centres in meaningful positions, as such supporting data analysis. However, the algorithm did not allow a correct classification of all data. Factor analysis was used instead, exploiting the linearity of the observed two dimensional trends, to completely split the reversible and irreversible fouling effects and classify the data in a more pragmatic approach. Overall, the tested techniques appeared useful and can serve as the basis for automatic membrane fouling monitoring and control.

BSM-MBR: a benchmark simulation model to compare control and operational strategies for membrane bioreactors.

A benchmark simulation model for membrane bioreactors (BSM-MBR) was developed to evaluate operational and control strategies in terms of effluent quality and operational costs. The configuration of the existing BSM1 for conventional wastewater treatment plants was adapted using reactor volumes, pumped sludge flows and membrane filtration for the water-sludge separation. The BSM1 performance criteria were extended for an MBR taking into account additional pumping requirements for permeate production and aeration requirements for membrane fouling prevention. To incorporate the effects of elevated sludge concentrations on aeration efficiency and costs a dedicated aeration model was adopted. Steady-state and dynamic simulations revealed BSM-MBR, as expected, to out-perform BSM1 for effluent quality, mainly due to complete retention of solids and improved ammonium removal from extensive aeration combined with higher biomass levels. However, this was at the expense of significantly higher operational costs. A comparison with three large-scale MBRs showed BSM-MBR energy costs to be realistic. The membrane aeration costs for the open loop simulations were rather high, attributed to non-optimization of BSM-MBR. As proof of concept two closed loop simulations were run to demonstrate the usefulness of BSM-MBR for identifying control strategies to lower operational costs without compromising effluent quality.

The cost of a large-scale hollow fibre MBR.

A cost sensitivity analysis was carried out for a full-scale hollow fibre membrane bioreactor to quantify the effect of design choices and operational parameters on cost. Different options were subjected to a long term dynamic influent profile and evaluated using ASM1 for effluent quality, aeration requirements and sludge production. The results were used to calculate a net present value (NPV), incorporating both capital expenditure (capex), based on costs obtained from equipment manufacturers and full-scale plants, and operating expenditure (opex), accounting for energy demand, sludge production and chemical cleaning costs. Results show that the amount of contingency built in to cope with changes in feedwater flow has a large impact on NPV. Deviation from a constant daily flow increases NPV as mean plant utilisation decreases. Conversely, adding a buffer tank reduces NPV, since less membrane surface is required when average plant utilisation increases. Membrane cost and lifetime is decisive in determining NPV: an increased membrane replacement interval from 5 to 10 years reduces NPV by 19%. Operation at higher SRT increases the NPV, since the reduced costs for sludge treatment are offset by correspondingly higher aeration costs at higher MLSS levels, though the analysis is very sensitive to sludge treatment costs. A higher sustainable flux demands greater membrane aeration, but the subsequent opex increase is offset by the reduced membrane area and the corresponding lower capex.

Model-based energy optimisation of a small-scale decentralised membrane bioreactor for urban reuse.

The energy consumption of a small-scale membrane bioreactor, treating high strength domestic wastewater for community level wastewater recycling, has been optimised using a dynamic model of the plant. ASM2d was chosen as biological process model to account for the presence of phosphate accumulating organisms. A tracer test was carried out to determine the hydraulic behaviour of the plant. To realistically simulate the aeration demand, a dedicated aeration model was used incorporating the dependency of the oxygen transfer on the mixed liquor concentration and allowing differentiation between coarse and fine bubble aeration, both typically present in MBRs. A steady state and dynamic calibration was performed, and the calibrated model was able to predict effluent nutrient concentrations and MLSS concentrations accurately. A scenario analysis (SCA) was carried out using the calibrated model to simulate the effect of varying SRT, recirculation ratio and DO set point on effluent quality, MLSS concentrations and aeration demand. Linking the model output with empirically derived correlations for energy consumption allowed an accurate prediction of the energy consumption. The SCA results showed that decreasing membrane aeration and SRT were most beneficial towards total energy consumption, while increasing the recirculation flow led to improved TN removal but at the same time also deterioration in TP removal. A validation of the model was performed by effectively applying better operational parameters to the plant. This resulted in a reduction in energy consumption by 23% without compromising effluent quality, as was accurately predicted by the model. This modelling approach thus allows the operating envelope to be reliably identified for meeting criteria based on energy demand and specific water quality determinants.