Thermodynamic Analysis of Intermediary Metabolic Steps and Nitrous Oxide Production by Ammonium-Oxidizing Bacteria.

Nitrous oxide (N2O) is a greenhouse gas emitted from wastewater treatment, soils, and agriculture largely by ammonium-oxidizing bacteria (AOB). While AOB are characterized by being aerobes that oxidize ammonium (NH4+) to nitrite (NO2-), fundamental studies in microbiology are revealing the importance of metabolic intermediates and reactions that can lead to the production of N2O. These findings about the metabolic pathways for AOB were integrated with thermodynamic electron-equivalents modeling (TEEM) to estimate kinetic and stoichiometric parameters for each of the AOB's nitrogen (N)-oxidation and -reduction reactions. The TEEM analysis shows that hydroxylamine (NH2OH) oxidation to nitroxyl (HNO) is the most energetically efficient means for the AOB to provide electrons for ammonium monooxygenation, while oxidations of HNO to nitric oxide (NO) and NO to NO2- are energetically favorable for respiration and biomass synthesis. The respiratory electron acceptor can be O2 or NO, and both have similar energetics. The TEEM-predicted value for biomass yield, maximum-specific rate of NH4+ utilization, and maximum specific growth rate are consistent with empirical observations. NO reduction to N2O is thermodynamically favorable for respiration and biomass synthesis, but the need for O2 as a reactant in ammonium monooxygenation likely precludes NO reduction to N2O from becoming the major pathway for respiration.

Modelling of aerobic granular sludge reactors: the importance of hydrodynamic regimes, selective sludge removal and gradients.

Hydraulic selection is a key feature of aerobic granular sludge (AGS) systems but existing aerobic granular sludge (AGS) models neglect those mechanisms: gradients over reactor height (Hreactor), selective removal of slow settling sludge, etc. This study aimed at evaluating to what extent integration of those additional processes into AGS models is needed, i.e., at demonstrating that model predictions (biomass inventory, microbial activities and effluent quality) are affected by such additional model complexity. We therefore developed a new AGS model that includes key features of full-scale AGS systems: fill-draw operation, selective sludge removal, distinct settling models for flocs/granules. We then compared predictions of our model to those of a fully mixed AGS model. Our results demonstrate that hydraulic selection can be predicted with an assembly of four continuous stirred tank reactors in series together with a correction code for plug-flow. Concentration gradients over the reactor height during settling/plug-flow feeding strongly impact the predictions of aerobic granular sludge models in terms of microbial selection, microbial activities and ultimately effluent quality. Hydraulic selection is a key to predict selection of storing microorganisms (phosphorus-accumulating organisms (PAO) and glycogen-accumulating organisms (GAO)) and in turn effluent quality in terms of total phosphorus, and for predicting effluent solid concentration and dynamic during plug-flow feeding.

Incorporating sulfur reactions and interactions with iron and phosphorus into a general plant-wide model.

Sulfur causes many adverse effects in wastewater treatment and sewer collection systems, such as corrosion, odours, increased oxygen demand, and precipitate formation. Several of these are often controlled by chemical addition, which will impact the subsequent wastewater treatment processes. Furthermore, the iron reactions, resulting from coagulant addition for chemical P removal, interact with the sulfur cycle, particularly in the digester with precipitate formation and phosphorus release. Despite its importance, there is no integrated sulfur and iron model for whole plant process optimization/design that could be readily used in practice. After a detailed literature review of chemical and biokinetic sulfur and iron reactions, a plant-wide model is upgraded with relevant reactions to predict the sulfur cycle and iron cycle in sewer collection systems, wastewater and sludge treatment. The developed model is applied on different case studies.

Colloids, flocculation and carbon capture - a comprehensive plant-wide model.

The implementation of carbon capture technologies such as high-rate activated sludge (HRAS) systems are gaining interests in water resource and recovery facilities (WRRFs) to minimize carbon oxidation and maximize organic carbon recovery and methane potential through biosorption of biodegradable organics into the biomass. Existing activated sludge models were developed to describe chemical oxygen demand (COD) removal in activated sludge systems operating at long solids retention times (SRT) (i.e. 3 days or longer) and fail to simulate the biological reactions at low SRT systems. A new model is developed to describe colloidal material removal and extracellular polymeric substance (EPS) generation, flocculation, and intracellular storage with the objective of extending the range of whole plant models to very short SRT systems. In this study, the model is tested against A-stage (adsorption) pilot reactor performance data and proved to match the COD and colloids removal at low SRT. The model was also tested on longer SRT systems where effluents do not contain much residual colloids, and digestion where colloids from decay processes are present.

Modelling gas-liquid mass transfer in wastewater treatment: when current knowledge needs to encounter engineering practice and vice versa.

Gas-liquid mass transfer in wastewater treatment processes has received considerable attention over the last decades from both academia and industry. Indeed, improvements in modelling gas-liquid mass transfer can bring huge benefits in terms of reaction rates, plant energy expenditure, acid-base equilibria and greenhouse gas emissions. Despite these efforts, there is still no universally valid correlation between the design and operating parameters of a wastewater treatment plant and the gas-liquid mass transfer coefficients. That is why the current practice for oxygen mass transfer modelling is to apply overly simplified models, which come with multiple assumptions that are not valid for most applications. To deal with these complexities, correction factors were introduced over time. The most uncertain of them is the α-factor. To build fundamental gas-liquid mass transfer knowledge more advanced modelling paradigms have been applied more recently. Yet these come with a high level of complexity making them impractical for rapid process design and optimisation in an industrial setting. However, the knowledge gained from these more advanced models can help in improving the way the α-factor and thus gas-liquid mass transfer coefficient should be applied. That is why the presented work aims at clarifying the current state-of-the-art in gas-liquid mass transfer modelling of oxygen and other gases, but also to direct academic research efforts towards the needs of the industrial practitioners.

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.

A framework for good biofilm reactor modeling practice (GBRMP).

A researcher or practitioner can employ a biofilm model to gain insight into what controls the performance of a biofilm process and for optimizing its performance. While a wide range of biofilm-modeling platforms is available, a good strategy is to choose the simplest model that includes sufficient components and processes to address the modeling goal. In most cases, a one-dimensional biofilm model provides the best balance, and good choices can range from hand-calculation analytical solutions, simple spreadsheets, and numerical-method platforms. What is missing today is clear guidance on how to apply a biofilm model to obtain accurate and meaningful results. Here, we present a five-step framework for good biofilm reactor modeling practice (GBRMP). The first four steps are (1) obtain information on the biofilm reactor system, (2) characterize the influent, (3) choose the plant and biofilm model, and (4) define the conversion processes. Each step demands that the model user understands the important components and processes in the system, one of the main benefits of doing biofilm modeling. The fifth step is to calibrate and validate the model: System-specific model parameters are adjusted within reasonable ranges so that model outputs match actual system performance. Calibration is not a simple 'by the numbers' process, and it requires that the modeler follows a logical hierarchy of steps. Calibration requires that the adjusted parameters remain within realistic ranges and that the calibration process be carried out in an iterative manner. Once each of steps 1 through 5 is completed satisfactorily, the calibrated model can be used for its intended purpose, such as optimizing performance, trouble-shooting poor performance, or gaining deeper understanding of what controls process performance.

Recent advances in bio-P modelling - a new approach verified by full-scale observations.

This paper summarizes recent developments in biological phosphorus removal modelling, with special attention to side-stream enhanced biological phosphorus removal (S2EBPR) systems on which previous models proved to be ineffective without case-by-case parameter adjustments. Through the research and experience of experts and practitioners, a new bio-kinetic model was developed including an additional group of biomass (glycogen accumulating organisms - GAOs) and new processes (such as aerobic and anoxic maintenance for PAO and GAO; enhanced denitrification processes; fermentation by PAOs which - along with PAO selection - is driven by oxidation-reduction potential (ORP)). This model successfully described various conditions in laboratory measurements and full plant data. The calibration data set is provided by Clean Water Services from Rock Creek Facility (Hillsboro, OR) including two parallel trains: conventional A2O and Westbank configurations, allowing the model to be verified on conventional and side-stream EBPR systems as well.

Novel Stokesian Metrics that Quantify Collision Efficiency, Floc Strength, and Discrete Settling Behavior.

Novel parameters were developed to predict the effluent quality and settling behavior in clarifiers that cannot conventionally be achieved using either the conventional flux theory or overflow rates. Simple batch experiments based on the critical settling velocity (CSV) selection were used as the basis for the development of three novel parameters: intrinsic settling classes (ISC), threshold of flocculation/flocculation limitation (TOF/α), and floc strength. ISC was proven to accurately (±2%) determine the granule fraction and discrete particle distribution. TOF quantified the minimum solids concentration needed to form large flocs and was directly linked to collision efficiency. In hybrid systems, an exponential fitting on a CSV matrix was proposed to quantify the collision efficiency of flocs (α). Shear studies were conducted to quantify floc strength. The methods were applied to a wide spectrum of sludge types to show the broad applicability and sensitivity of the novel methods.

Evaluation of the information content of long-term wastewater characteristics data in relation to activated sludge model parameters.

A parameter estimation framework was used to evaluate the ability of observed data from a full-scale nitrification-denitrification bioreactor to reduce the uncertainty associated with the bio-kinetic and stoichiometric parameters of an activated sludge model (ASM). Samples collected over a period of 150 days from the effluent as well as from the reactor tanks were used. A hybrid genetic algorithm and Bayesian inference were used to perform deterministic and parameter estimations, respectively. The main goal was to assess the ability of the data to obtain reliable parameter estimates for a modified version of the ASM. The modified ASM model includes methylotrophic processes which play the main role in methanol-fed denitrification. Sensitivity analysis was also used to explain the ability of the data to provide information about each of the parameters. The results showed that the uncertainty in the estimates of the most sensitive parameters (including growth rate, decay rate, and yield coefficients) decreased with respect to the prior information.

Rethinking growth and decay kinetics in activated sludge - towards a new adaptive kinetics approach.

Growth kinetics in activated sludge modelling (ASM) are typically assumed to be the result of intrinsic growth and decay properties and thus process parameters are deemed to be constant. The activity change in a microbial population is expressed in terms of variance of the active biomass fraction and not actual shifts in bacterial cellular activities. This approach is limited, in that it does not recognise the reality that active biomass is highly physiologically adaptive. Here, a strong correlation between maximum specific growth rate (µmax) and decay rate (be) of ordinary heterotrophic organisms was revealed in both low solids retention times (SRT) and high SRT activated sludge systems. This relationship is indicative of physiological adaptation either for growth (high µmax and be) or survival optimization (low µmax and be). Further, the nitrifier decay process was investigated using molecular techniques to measure decay rates of ammonia oxidizing bacteria and nitrite oxidizing bacteria over a range of temperatures. This approach revealed decay rates 10-12% lower than values previously accepted and used in ASM. These findings highlight potential benefits of incorporating physiological adaptation of heterotrophic and nitrifying populations in future ASM.

Assessment of the endogenous respiration rate and the observed biomass yield for methanol-fed denitrifying bacteria under anoxic and aerobic conditions.

In this study, the endogenous respiration rate and the observed biomass yield of denitrifying methylotrophic biomass were estimated through measuring changes in denitrification rates (DNR) as a result of maintaining the biomass under methanol deprived conditions. For this purpose, activated sludge biomass from a full-scale wastewater treatment plant was kept in 10-L batch reactors for 8 days under fully aerobic and anoxic conditions at 20 °C without methanol addition. To investigate temperature effects, another biomass sample was placed under starvation conditions over a period of 10 days under aerobic conditions at 25 °C. A series of secondary batch tests were conducted to measure DNR and observed biomass yields. The decline in DNR over the starvation period was used as a surrogate to biomass decay rate in order to infer the endogenous respiration rates of the methylotrophs. The regression analysis on the declining DNR data shows 95% confidence intervals of 0.130 ± 0.017 day-1 for endogenous respiration rate under aerobic conditions at 20 °C, 0.102 ± 0.013 day-1 under anoxic conditions at 20 °C, and 0.214 ± 0.044 day-1 under aerobic conditions at 25 °C. Results indicated that the endogenous respiration rate of methylotrophs is 20% slower under anoxic conditions than under aerobic conditions, and there is a significant temperature dependency, with an Arrhenius coefficient of 1.10. The observed biomass yield value showed an increasing trend from approximately 0.2 to 0.6 when the starvation time increased from 0 to 10 days.

Biofilm carrier migration model describes reactor performance.

The accuracy of a biofilm reactor model depends on the extent to which physical system conditions (particularly bulk-liquid hydrodynamics and their influence on biofilm dynamics) deviate from the ideal conditions upon which the model is based. It follows that an improved capacity to model a biofilm reactor does not necessarily rely on an improved biofilm model, but does rely on an improved mathematical description of the biofilm reactor and its components. Existing biofilm reactor models typically include a one-dimensional biofilm model, a process (biokinetic and stoichiometric) model, and a continuous flow stirred tank reactor (CFSTR) mass balance that [when organizing CFSTRs in series] creates a pseudo two-dimensional (2-D) model of bulk-liquid hydrodynamics approaching plug flow. In such a biofilm reactor model, the user-defined biofilm area is specified for each CFSTR; thereby, Xcarrier does not exit the boundaries of the CFSTR to which they are assigned or exchange boundaries with other CFSTRs in the series. The error introduced by this pseudo 2-D biofilm reactor modeling approach may adversely affect model results and limit model-user capacity to accurately calibrate a model. This paper presents a new sub-model that describes the migration of Xcarrier and associated biofilms, and evaluates the impact that Xcarrier migration and axial dispersion has on simulated system performance. Relevance of the new biofilm reactor model to engineering situations is discussed by applying it to known biofilm reactor types and operational conditions.

Toward Universal Half-Saturation Coefficients: Describing Extant K(s) as a Function of Diffusion.

Observed (extant) K(s) is not a constant and it is strongly influenced by diffusion. This paper argues that diffusion can be used to describe bacterial kinetic effects that are sometimes attributed to "K-strategists" and, in fact, the physics of the system is the dominant mechanism affecting the apparent (extant) Ks--not intrinsic biological characteristics--in real water resource recovery facility systems. Four different biological processes have been modeled using the "porter-diffusion" model that was originally developed by Pasciak and Gavis (1974) for aquatic systems. The results demonstrate that diffusion is the dominant mechanism affecting K(s) in all four biological processes. Therefore, the authors argue that for treatment processes in which substrate concentrations are low, it is important to consider shifting to variable extant K(s) values or explicitly modeling the effects of diffusion.

Modeling of organic substrate transformation in the high-rate activated sludge process.

This study describes the development of a modified activated sludge model No.1 framework to describe the organic substrate transformation in the high-rate activated sludge (HRAS) process. New process mechanisms for dual soluble substrate utilization, production of extracellular polymeric substances (EPS), absorption of soluble substrate (storage), and adsorption of colloidal substrate were included in the modified model. Data from two HRAS pilot plants were investigated to calibrate and to validate the proposed model for HRAS systems. A subdivision of readily biodegradable soluble substrate into a slow and fast fraction were included to allow accurate description of effluent soluble chemical oxygen demand (COD) in HRAS versus longer solids retention time (SRT) systems. The modified model incorporates production of EPS and storage polymers as part of the aerobic growth transformation process on the soluble substrate and transformation processes for flocculation of colloidal COD to particulate COD. The adsorbed organics are then converted through hydrolysis to the slowly biodegradable soluble fraction. Two soluble substrate models were evaluated during this study, i.e., the dual substrate and the diauxic models. Both models used two state variables for biodegradable soluble substrate (SBf and SBs) and a single biomass population. The A-stage pilot typically removed 63% of the soluble substrate (SB) at an SRT <0.13 d and 79% at SRT of 0.23 d. In comparison, the dual substrate model predicted 58% removal at the lower SRT and 78% at the higher SRT, with the diauxic model predicting 32% and 70% removals, respectively. Overall, the dual substrate model provided better results than the diauxic model and therefore it was adopted during this study. The dual substrate model successfully described the higher effluent soluble COD observed in the HRAS systems due to the partial removal of SBs, which is almost completely removed in higher SRT systems.

A comprehensive floc model for simulating simultaneous nitrification, denitrification, and phosphorus removal.

A comprehensive floc model for simultaneous nitrification, denitrification, and phosphorus removal (SNDPR) was designed, incorporating polyphosphate-accumulating organisms (PAOs), glycogen-accumulating organisms (GAOs), intrinsic half-saturation coefficients, and explicit external mass transfer terms. The calibrated model was able to effectively describe experimental data over a range of operating conditions. The estimated intrinsic half-saturation coefficients of oxygen values for ammonia-oxidizing bacteria, nitrite-oxidizing bacteria, ordinary heterotrophic organisms (OHOs), PAOs, and GAOs were set at 0.08, 0.18, 0.03, 0.07, and 0.1 mg/L, respectively. Simulation suggested that low dissolved oxygen (DO) environments favor K-strategist nitrifying bacteria and PAOs. In SNDPR, virtually all influent and fermentation-generated volatile fatty acids were assimilated as polyhydroxyalkanoates by PAOs in the anaerobic phase. In the aerobic phase, PAOs absorbed 997 % and 171 % of the benchmark influent total phosphorus mass loading through aerobic growth and denitrification via nitrite. These high percentages were because they were calculated relative to the influent total phosphorus, rather than total phosphorus at the end of the anaerobic period. When considering simultaneous nitrification and denitrification, about 23.1 % of influent total Kjeldahl nitrogen was eliminated through denitrification by PAOs and OHOs via nitrite, which reduced the need for both oxygen and carbon in nitrogen removal. Moreover, the microbial and DO profiles within the floc indicated a distinct stratification, with decreasing DO and OHOs, and increasing PAOs towards the inner layer. This study demonstrates a successful floc model that can be used to investigate and design SNDPR for scientific and practical purposes.

Restructuring anaerobic hydrolysis kinetics in plant-wide models for accurate prediction of biogas production.

In this study, the effect of anaerobic hydrolysis rate on biogas production was investigated with mesophilic digesters in seven large-scale wastewater treatment plants. A linear correlation was determined between the percentage of primary sludge mass in the total sludge fed to the digester and the overall anaerobic hydrolysis rate. The anaerobic hydrolysis rate of primary sludge was determined to be three times higher than that of biological sludge. The reduction factors for anaerobic hydrolysis (ηHYD,ana) were identified in the range of 0.11-0.30 which is lower compared to the recommended range (0.30-0.50) given in the literature. This study proposes a new model approach where anaerobic degradation kinetics of influent originated (XB) and decay originated (XB,E) particulate biodegradable organics are separated. Current plant-wide models with a single kinetic expression required recalibration of the model for calculating biogas flowrate for each treatment facility with different primary and secondary sludge ratios fed to the digesters. The new model structure is able to predict biogas production of all wastewater treatment plants without any recalibration effort by segregating degradation kinetics of two particulate biodegradable organic fractions (XB, XB,E).

Modeling versatile and dynamic anaerobic metabolism for PAOs/GAOs competition using agent-based model and verification via single cell Raman Micro-spectroscopy.

Side-stream enhanced biological phosphorus removal process (S2EBPR) has been demonstrated to improve performance stability and offers a suite of advantages compared to conventional EBPR design. Design and optimization of S2EBPR require modification of the current EBPR models that were not able to fully reflect the metabolic functions of and competition between the polyphosphate-accumulating organisms (PAOs) and glycogen-accumulating organisms (GAOs) under extended anaerobic conditions as in the S2EBPR conditions. In this study, we proposed and validated an improved model (iEBPR) for simulating PAO and GAO competition that incorporated heterogeneity and versatility in PAO sequential polymer usage, staged maintenance-decay, and glycolysis-TCA pathway shifts. The iEBPR model was first calibrated against bulk batch testing experiment data and proved to perform better than the previous EBPR model for predicting the soluble orthoP, ammonia, biomass glycogen, and PHA temporal profiles in a starvation batch testing under prolonged anaerobic conditions. We further validated the model with another independent set of anaerobic testing data that included high-resolution single-cell and specific population level intracellular polymer measurements acquired with single-cell Raman micro-spectroscopy technique. The model accurately predicted the temporal changes in the intracellular polymers at cellular and population levels within PAOs and GAOs, and further confirmed the proposed mechanism of sequential polymer utilization, and polymer availability-dependent and staged maintenance-decay in PAOs. These results indicate that under extended anaerobic phases as in S2EBPR, the PAOs may gain competitive advantages over GAOs due to the possession of multiple intracellular polymers and the adaptive switching of the anaerobic metabolic pathways that consequently lead to the later and slower decay in PAOs than GAOs. The iEBPR model can be applied to facilitate and optimize the design and operations of S2EBPR for more reliable nutrient removal and recovery from wastewater.

Improving nutrient removal while reducing energy use at three Swiss WWTPs using advanced control.

Aeration consumes about 60% of the total energy use of a wastewater treatment plant (WWTP) and therefore is a major contributor to its carbon footprint. Introducing advanced process control can help plants to reduce their carbon footprint and at the same time improve effluent quality through making available unused capacity for denitrification, if the ammonia concentration is below a certain set-point. Monitoring and control concepts are cost-saving alternatives to the extension of reactor volume. However, they also involve the risk of violation of the effluent limits due to measuring errors, unsuitable control concepts or inadequate implementation of the monitoring and control system. Dynamic simulation is a suitable tool to analyze the plant and to design tailored measuring and control systems. During this work, extensive data collection, modeling and full-scale implementation of aeration control algorithms were carried out at three conventional activated sludge plants with fixed pre-denitrification and nitrification reactor zones. Full-scale energy savings in the range of 16-20% could be achieved together with an increase of total nitrogen removal of 40%.

Towards a generalized physicochemical framework.

Process models used for activated sludge, anaerobic digestion and in general wastewater treatment plant process design and optimization have traditionally focused on important biokinetic conversions. There is a growing realization that abiotic processes occurring in the wastewater (i.e. 'solvent') have a fundamental effect on plant performance. These processes include weak acid-base reactions (ionization), spontaneous or chemical dose-induced precipitate formation and chemical redox conversions, which influence pH, gas transfer, and directly or indirectly the biokinetic processes themselves. There is a large amount of fundamental information available (from chemical and other disciplines), which, due to its complexity and its diverse sources (originating from many different water and process environments), cannot be readily used in wastewater process design as yet. This position paper outlines the need, the methods, available knowledge and the fundamental approaches that would help to focus the effort of research groups to develop a physicochemical framework specifically in support of whole-plant process modeling. The findings are that, in general, existing models such as produced by the International Water Association for biological processes are limited by omission of key corrections such as non-ideal acid-base behavior, as well as major processes (e.g., ion precipitation). While the underlying chemistry is well understood, its applicability to wastewater applications is less well known. This justifies important further research, with both experimental and model development activities to clarify an approach to modeling of physicochemical processes.