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.

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.

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.

A comprehensive evaluation of process kinetics: A plant-wide approach for nutrient removal and biogas production.

The present study investigated the deviations of operational parameters of a large-scale wastewater treatment plant (WWTP) from design basis through combining dedicated batch experiments with full-scale dynamic modeling results. The long-term process performance of a full-scale biological nutrient removal (BNR) plant equipped with anaerobic sludge digestion system was monitored to evaluate the process kinetics of both carbon and nutrient removal and anaerobic sludge digestion. In this respect, plant-specific characterization; chemical oxygen demand (COD) fractionation, batch kinetic studies and sludge settling velocity tests were performed together with plant-wide SUMO model simulation. Results showed that nitrification and anaerobic hydrolysis were found to be 30% and 70% lower than literature values, respectively. The anaerobic digestion test coupled with plant-wide model calibration showed that anaerobic hydrolysis was the bottleneck in biogas production. Correspondingly, performance of the anaerobic digestion in the full-scale plant was poor as low biogas production yields were observed. In addition, the degradation rate via anaerobic hydrolysis of primary sludge was found to be higher (∼2-2.5) compared to anaerobic hydrolysis of biological sludge. The results of this study provide insight into model-based experimental characterization as well as plant-wide modeling approach. Coupling model-based batch experiments with full-scale modeling enabled to reduce the number of kinetic parameters to be fine-tuned. Moreover, the information gathered from kinetic batch tests to the simulation platform yielded a satisfying prediction of long-term performance of the plant operation.

Dynamic alpha factors: Prediction in time and evolution along reactors.

The performance of aeration - one of the most costly processes at water resource recovery facilities - is heavily impacted by actual wastewater characteristics which are commonly taken into account using the alpha factor (α). This factor varies depending on hydraulic and organic loading; such variance includes both time and spatial fluctuations. In standard design practice, it is often considered as a fixed number, or at best, a predefined time series. The objective of this paper is to propose a new method of predicting plantwide trends in the α factor through the use of process modelling which can accommodate diurnal and seasonal variations. The authors' concept takes into account the dependence of α on sludge retention time in the form of degradation kinetics, the effects of organic loading (influent filtered COD), the presence or absence of anoxic zones, diffuser depth, and the impact of high MLSS found in certain, e.g., MBR, technologies. The developed model was calibrated using data from numerous facilities, relying on off-gas measurements and tests in clean and process water. Model validation was carried out against averaged α factor gradient data from one plant, and against diurnal air flow measurements from another. The Benchmark Simulation Model 1 configuration was used to demonstrate the applicability of the proposed model - in estimation of blower energy consumption and peak air flow requirements - comparing it with constant and scheduled α factor-based approaches.

A proof-of-concept experimental study for vacuum-driven anaerobic biosolids fermentation using the IntensiCarb technology.

This study demonstrates the potential of an innovative anaerobic treatment technology for municipal biosolids (IntensiCarb), which relies on vacuum evaporation to decouple solids and hydraulic retention times (SRT and HRT). We present proof-of-concept experiments using primary sludge and thickened waste activated sludge (50-50 v/v mixture) as feed for fermentation and carbon upgrading with the IntensiCarb unit. IntensiCarb fully decoupled the HRT and SRT in continuously stirred anaerobic reactors (CSAR) to achieve two intensification factors, that is, 1.3 and 2, while keeping the SRT constant at 3 days (including in the control fermenter). The intensified CSARs were compared to a conventional control system to determine the yields of particulate hydrolysis, VFA production, and nitrogen partitioning between fermentate and condensate. The intensified CSAR operating at an intensification factor 2 achieved a 65% improvement in particulate solubilization. Almost 50% of total ammonia was extracted without pH adjustment, while carbon was retained in the fermentate. Based on these results, the IntensiCarb technology allows water resource recovery facilities to achieve a high degree of plant-wide intensification while partitioning nutrients into different streams and thickening solids. PRACTITIONER POINTS: The IntensiCarb reactor can decouple hydraulic (HRT) and solids (SRT) retention times in anaerobic systems while also increasing particulate hydrolysis and overall plant capacity. Using vacuum as driving force of the IntensiCarb technology, the system could achieve thickening, digestion, and partial dewatering in the same unit-thus eliminating the complexity of multi-stage biosolids treatment lines. The ability to partition nutrients between particulate, fermentate, and condensate assigns to the IntensiCarb unit a key role in recovery strategies for value-added products such as nitrogen, phosphorus, and carbon, which can be recovered separately and independently.

Investigating the dynamics of volatile sulfur compound emission from primary systems at a water resource recovery facility.

This study quantifies volatile sulfur compound (VSC) emissions from primary settling tanks and investigates their mechanisms of generation. Hydrogen sulfide (H2 S) and methyl mercaptan (MM) concentrations in the off-gas were dominant among the VSCs analyzed, while dimethyl sulfide (DMS) and dimethyl disulfide (DMDS) were under their odor threshold for most sampling dates. H2 S emission in primary settling tanks was mainly the result of the stripping of dissolved sulfide (64%) generated in the sewers. Results indicate that MM emission was more dependent on the conditions in the primary clarifiers (only 16% stripping). Prevention of odor emission in primary settling tanks can be achieved by managing biofilms and microbial reactions in the sewer network. Controlling the biomass seeding and fermentation product availability in the primary settling tanks is essential to significantly minimize the kinetics of H2 S and MM generation. Overall, the management of sludge blanket heights and thus avoiding time at low oxidation-reduction potential minimized odor emission independent of sewer conditions. PRACTITIONER POINTS: H2 S emission from primary clarifiers mainly originated from the stripping of the dissolved sulfide formed in the sewers. MM emission contributed for 89% to overall odor emitted from primary clarifiers. Seeding of active biomass from the sewer into the primary clarifiers was be the main driver for both MM and H2 S formation. Increased availability of fermentation products or fermenters increased MM production.

Towards more predictive clarification models via experimental determination of flocculent settling coefficient value.

Improved settleability has become an essential feature of new wastewater treatment innovations. To accelerate adoption of such new technologies, improved clarifier models are needed to help with designing and predicting improvement in settleability. In general, the level of mathematics of settling clarifier models has gone far beyond the level of existing experimental methods available to support these models. To date, even for simple one-dimensional (1D) clarifier models, no experimental method has been described for flocculent settling coefficient (rp). As a consequence, rp cannot be considered as a sludge characteristic and is used as a calibration parameter to achieve observed effluent quality. In this study, we focused on the development of an empirical function based on a simple and practical experimental approach for the calculation of the rp value from sludge characteristics. This approach provided a similar approach as currently taken for hindered settling coefficient calculations (Veslind equation) and allowed for the model to predict effluent quality, thus increasing the power of the 1D model. The threshold of flocculation (TOF), which describes the collision efficiency of particles, directly correlated with the effluent quality of the five tested activated sludge systems and was selected as experimental method. The proposed empirical function between TOF and rp was validated for four years of validating data with five different sludge types operated under different operational conditions and configurations. The good effluent quality prediction with this approach brings us one step closer in making the clarification models more predictive towards effluent quality and clarifier performance.

Operational and structural A-stage improvements for high-rate carbon removal.

Biosorption of organics is investigated at two sites in order to optimize operation and infrastructure for carbon removal and redirection in upstream, high-rate processes. Sufficient process temperature and stable mixed liquor solids concentration were established as the key impact parameters for the process performance. Improved COD removal was achieved by either substantially enhanced aeration (elevated metabolic state) or by enhanced flocculation capability (dosed chemicals). Separation and thickening of organics are typically operated as continuous-flow processes. The optimization of performance parameters led to a new A-stage process named alternating activated adsorption. The AAA process is presented as a novel configuration linking biosorption and thickening capabilities in an alternating scheme without mechanical equipment. The performance data from its first trial indicate benefits from process dynamics including high organics capture rates and thickening capabilities reaching solid concentrations higher than 40 g(TSS)/L. COD removal could be increased further by adding biologically generated polymer, that is waste sludge from B-stage. © 2020 Water Environment Federation PRACTITIONERS POINTS: Enhanced preliminary treatment helps to increase capacity and energy efficiency. Low RAS rates, SRT control, aeration, high temperatures, and metal dosing are key performance parameters for removal rates and energy efficiency. The Triple-A process offers new possibilities for A-stage in terms of performance increase and flexibility showing similar or better results compared with conventional A-stage. Adding B-sludge improved COD and nutrient removal rates. High preliminary removal rates of COD and N foster sidestream processes.

Survey of full-scale sidestream enhanced biological phosphorus removal (S2EBPR) systems and comparison with conventional EBPRs in North America: Process stability, kinetics, and microbial populations.

Sidestream EBPR (S2EBPR) is an emerging alternative process to address common challenges in EBPR related to weak wastewater influent and may improve EBPR process stability. A systematic evaluation and comparison of the process performance and microbial community structure was conducted between conventional and S2EBPR facilities in North America. The statistical analysis suggested higher performance stability in S2EBPR than conventional EBPR, although possible bias associated with other plant-specific factors might have affected the comparison. Variations in stoichiometric values related to EBPR activity and discrepancies between the observed values and current model predictions suggested a varying degree of metabolic versatility of PAOs in S2EBPR systems that warrant further investigation. Microbial community analysis using various techniques suggested comparable known candidate PAO relative abundances in S2EBPR and conventional EBPR systems, whereas the relative abundance of known candidate GAOs seemed to be consistently lower in S2EBPR facilities than conventional EBPR facilities. 16S rRNA gene sequencing analysis revealed differences in the community phylogenetic fingerprints between S2EBPR and conventional facilities and indicated statistically higher microbial diversity index values in S2EBPR facilities than those in conventional EBPRs. PRACTITIONER POINTS: Sidestream EBPR (S2EBPR) can be implemented with varying and flexible configurations, and they offer advantages over conventional configurations for addressing the common challenges in EBPR related to weak wastewater influent and may improve EBPR process stability. Survey of S2EBPR plants in North America suggested statistically more stable phosphorus removal performance in S2EBPR plants than conventional EBPRs, although possible bias might affect the comparison due to other plant-specific factors. The EBPR kinetics and stoichiometry of the S2EBPR facilities seemed to vary and are associated with metabolic versatility of PAOs in S2EBPR systems that warrant further investigation. The abundance of known candidate PAOs in S2EBPR plants was similar to those in conventional EBPRs, and the abundance of known candidate GAOs was generally lower in S2EBPR than conventional EBPR facilities. Further finer-resolution analysis of PAOs and GAOs, as well as identification of other unknown PAOs and GAOs, is needed. Microbial diversity is higher in S2EBPR facilities compared with conventional ones, implying that S2EBPR microbial communities could show better resilience to perturbations due to potential functional redundancy.

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.

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.

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.

Overcoming floc formation limitations in high-rate activated sludge systems.

High-rate activated sludge (HRAS) is an essential cornerstone of the pursuit towards energy positive sewage treatment through maximizing capture of organics. The capture efficiency heavily relies on the degree of solid separation achieved in the clarifiers. Limitations in the floc formation process commonly emerge in HRAS systems, with detrimental consequences for the capture of organics. This study pinpointed and overcame floc formation limitations present in full-scale HRAS reactors. Orthokinetic flocculation tests were performed with varying shear, sludge concentration, and coagulant or flocculant addition. These were analyzed with traditional and novel settling parameters and extracellular polymeric substances (EPS) measurements. HRAS was limited by insufficient collision efficiency and occurred because the solids retention time (SRT) was short and colloid loading was high. The limitation was predominantly caused by impaired flocculation rather than coagulation. In addition, the collision efficiency limitation was driven by EPS composition (low protein over polysaccharide ratio) instead of total EPS amount. Collision efficiency limitation was successfully overcome by bio-augmenting sludge from a biological nutrient removal reactor operating at long SRT which did not show any floc formation limitations. However, this action brought up a floc strength limitation. The latter was not correlated with EPS composition, but rather EPS amount and hindered settling parameters, which determined floc morphology. With this, an analysis toolkit was proposed that will enable design engineers and operators to tackle activated solid separation challenges found in HRAS systems and maximize the recovery potential of the process.

Pinpointing wastewater and process parameters controlling the AOB to NOB activity ratio in sewage treatment plants.

Even though nitrification/denitrification is a robust technology to remove nitrogen from sewage, economic incentives drive its future replacement by shortcut nitrogen removal processes. The latter necessitates high potential activity ratios of ammonia oxidizing to nitrite oxidizing bacteria (rAOB/rNOB). The goal of this study was to identify which wastewater and process parameters can govern this in reality. Two sewage treatment plants (STP) were chosen based on their inverse rAOB/rNOB values (at 20 °C): 0.6 for Blue Plains (BP, Washington DC, US) and 1.6 for Nieuwveer (NV, Breda, NL). Disproportional and dissimilar relationships between AOB or NOB relative abundances and respective activities pointed towards differences in community and growth/activity limiting parameters. The AOB communities showed to be particularly different. Temperature had no discriminatory effect on the nitrifiers' activities, with similar Arrhenius temperature dependences (ΘAOB = 1.10, ΘNOB = 1.06-1.07). To uncouple the temperature effect from potential limitations like inorganic carbon, phosphorus and nitrogen, an add-on mechanistic methodology based on kinetic modelling was developed. Results suggest that BP's AOB activity was limited by the concentration of inorganic carbon (not by residual N and P), while NOB experienced less limitation from this. For NV, the sludge-specific nitrogen loading rate seemed to be the most prevalent factor limiting AOB and NOB activities. Altogether, this study shows that bottom-up mechanistic modelling can identify parameters that influence the nitrification performance. Increasing inorganic carbon in BP could invert its rAOB/rNOB value, facilitating its transition to shortcut nitrogen removal.

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.