The EAWAG Bio-P module for activated sludge model No. 3

Digitalization of phosphorous removal process in biological wastewater treatment systems: Challenges, and way forward

Phosphorus in wastewater poses a significant environmental threat, leading to water pollution and eutrophication. However, it plays a crucial role in the water-energy-resource recovery-environment (WERE) nexus. Recovering Phosphorus from wastewater can close the phosphorus loop, supporting circular economy principles by reusing it as fertilizer or in industrial applications. Despite the recognized importance of phosphorus recovery, there is a lack of analysis of the cyber-physical framework concerning the WERE nexus. Advanced methods like automatic control, optimal process technologies, artificial intelligence (AI), and life cycle assessment (LCA) have emerged to enhance wastewater treatment plants (WWTPs) operations focusing on improving effluent quality, energy efficiency, resource recovery, and reducing greenhouse gas (GHG) emissions. Providing insights into implementing modeling and simulation platforms, control, and optimization systems for Phosphorus recovery in WERE (P-WERE) in WWTPs is extremely important in WWTPs. This review highlights the valuable applications of AI algorithms, such as machine learning, deep learning, and explainable AI, for predicting phosphorus (P) dynamics in WWTPs. It emphasizes the importance of using AI to analyze microbial communities and optimize WWTPs for different various objectives. Additionally, it discusses the benefits of integrating mechanistic and data-driven models into plant-wide frameworks, which can enhance GHG simulation and enable simultaneous nitrogen (N) and Phosphorus (P) removal. The review underscores the significance of prioritizing recovery actions to redirect Phosphorus from effluent to reusable products for future considerations.

A combined process model for wastewater treatment based on hydraulic retention time and toxicity inhibition

Hydraulic retention time (HRT), as an important parameter in the wastewater treatment process, has a great impact on water quality and energy consumption. With the rapid advances in computer technology and deepened understanding of in microbial metabolism, a series of activated sludge models (ASMs) have been developed and applied in wastewater treatment. However, ASMs simulation based on the nexus of HRT, water treatment process, water quality and energy consumption has yet to be verified. In this study, HRT was creatively linked to water treatment process variation. And a novel combined process model (CPM) was developed based on the operational data and treatment performance data from 4 full-scale coking wastewater treatment processes. In the CPM, an array of biological treatment processes were represented by setting the HRT in respective treatment units of the anaerobic-oxic-hydrolytic & denitrification-oxic (A/O/H/O) process. The relationships between HRT, effluent quality and energy consumption were systematically analyzed. Results showed that: (i) for A/O/H/O process, the HRT of first oxic (O1) reactor has a key effect on the effluent water quality and energy consumption, while the impact of the anaerobic (A) reactor HRT was limited; (ii) the O/H/O process has a clear advantage in treating coking wastewater due to the carbon removal and detoxification function of O1 reactor; (iii) the lowest energy consumption (with the total system HRT below 210 h) to meet the biological effluent quality requirements (COD = 200 mg/L, TN = 50 mg/L) is 4.429 kWh/m³. Since the CPM could effectively work out the optimal process configuration and break the boundaries between HRT and process variation, it has enormous potential to be extended to the design of other wastewater treatment processes.

Model-based fractionation of biomass in a biological nutrient removal system and its effect on the removal efficiencies

Fractionation of active biomass in a five-stage Bardenpho process was accomplished using an MS Excel wastewater treatment plant modeling tool based on Activated Sludge Model No. 3 extended with a bio-P module. The biomass fractions within the treatment system were predicted as autotrophs, ordinary heterotrophs, and phosphorus accumulating organisms (PAOs). Several simulations were performed in a Bardenpho process using various C/N/P ratios in primary effluent. Biomass fractionation was obtained from steady-state simulation results. The results suggest that the mass percentage of autotrophs, heterotrophs, and PAOs in active biomass range from 1.7 to 7.8%, 5.7-69.0%, and 23.2-92.6%, respectively, depending on characteristics of primary effluent. Results of principal component analysis showed that TKN/COD ratio in primary effluent determines the population of autotrophs and ordinary heterotrophs whereas PAO population is mainly a function of TP/COD ratio.

Impact of the anaerobic feeding mode on substrate distribution in aerobic granular sludge

There is a growing interest to implement aerobic granular sludge (AGS) in existing conventional activated sludge (CAS) systems with a continuous flow-through configuration. The mode of anaerobic contact of raw sewage with the sludge is an important aspect in the adaptation of CAS systems to accommodate AGS. It remains unclear how the distribution of substrate over the sludge by a conventional anaerobic selector compares to the distribution via bottom-feeding applied in sequencing batch reactors (SBRs). This study investigated the effect of the anaerobic contact mode on the substrate (and storage) distribution by operating two lab-scale SBRs; one with the traditional bottom-feeding through a settled sludge bed similar to full-scale AGS systems, and one where the synthetic wastewater was fed as a pulse at the start of the anaerobic phase while the reactor was mixed through sparging of nitrogen gas (mimicking a plug-flow anaerobic selector in continuous flow-through systems). The distribution of the substrate over the sludge particle population was quantified via PHA analysis, combined with the obtained granule size distribution. Bottom-feeding was found to primarily direct substrate towards the large granular size classes (i.e. large volume and close to the bottom), while completely mixed pulse-feeding gives a more equal distribution of substrate over all granule sizes (i.e. surface area dependant). The anaerobic contact mode directly controls the substrate distribution over the different granule sizes, irrespective of the solids retention time of a granule as an entity. Preferential feeding of the larger granules will enhance and stabilise the granulation compared to pulse-feeding, certainly under less advantageous conditions imposed by real sewage.

Advanced nitrogen and phosphorus removal by the symbiosis of PAOs, DPAOs and DGAOs in a pilot-scale A2O/A+MBR process with a low C/N ratio of influent

Cooperating in harmony to avoid competition with dominant functional microbial symbiosis is an efficient way in advanced nitrogen and phosphorus removal in wastewater treatment processes. In this study, a niche-based coordinating strategy was implemented to cooperate in harmony with phosphorus-accumulating organisms (PAOs), denitrifying phosphorus-accumulating organisms (DPAOs) and denitrifying glycogen-accumulating organisms (DGAOs) to advance nitrogen and phosphorus removal based on an anaerobic-anoxic-oxic-anoxic-membrane bioreactor (A²O/A+MBR) under low C/N in municipal wastewater influent. The niche-based strategy was conducted based on the ORP change during the process as an indicator combined with the adjustment of recirculation and anoxic zone shifting. The results indicated that the strategy of the post-anoxic unit could enable significant enhancement of biological nitrogen and phosphorus removal (BNPR) by 9.9% and 16.3%, respectively, with low effluent concentrations of 7.0 ± 2.2 mg N/L and 0.36±0.32 mg P/L. The satisfactory performance was dominated along with the shift in the microbial community: the relative abundance of Tetrasphaera (PAO genus) increased from 0.14±0.08% to 0.32±0.12%, while the relative abundance of Decchloromonas (DGAO genus) and Candidatus Competibacter (DGAO genus) also increased. The advanced combination of anaerobic phosphorus release, anoxic denitrification, denitrifying phosphorus removal and endogenous denitrification was qualified by the modeling simulation of the biochemical kinetics mechanism of activated sludge in the A²O+MBR and A²O/A+MBR processes, which means that cooperation in the harmony of PAOs, DPAOs and DGAOs could be efficiently realized by a promising control strategy to enhance BNPR in an A²O+MBR with a post-anoxic unit. This study provides an efficient and simple novel control strategy to overcome the limitation of traditional nitrogen and phosphorus removal under an insufficient carbon source.

Fractional-order models identification and control within a supervisory control framework for efficient nutrients removal in biological wastewater treatment plants

Wastewater treatment plants (WWTPs) are highly non-linear processes that must be optimized to meet rigorous environmental water regulations. In this context, efficiency and costs are equally important terms. The ASM3bioP framework is employed in this study to enable simultaneous nitrogen and phosphorus removal using an activated sludge process model with seven-reactor configurations. The activated sludge process is the most complicated and energy-intensive phase of a WWTP. To control dissolved oxygen in aerobic reactors and nitrate levels in anoxic reactors, two robust PI controllers - a classical PI and a non-integer (fractional)-order PI - with both integer-order and fractional-order models are designed. The controllers are created and simulated with the use of a mathematical model that has been developed based on the input data. The lower level fractional controller with a fractional-order model improves both the effluent quality (EQI) and operational cost (OCI) indices significantly. For such biological WWTP, a hierarchical fuzzy logic controller is designed to adjust the dissolved oxygen in the seventh reactor (DO₇) to control ammonia. The implemented supervisory layer control strategy improves effluent quality EQI while increasing OCI marginally.

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.

Expanding ASM models towards integrated processes for short-cut nitrogen removal and bioplastic recovery

In next-generation water resource recovery facilities (WRRFs), it is becoming increasingly important to save energy costs and promote resource recovery of valuable products. One way of reducing the substantial aeration energy costs at WRRFs is to employ shortcut N removal, while polyhydroxyalkanoate (PHA) production and recovery as bioplastic is a promising means of recovering a valuable product from biosolids. Both objectives can be achieved simultaneously through the Short-Cut Enhanced Phosphorus and PHA Recovery (SCEPPHAR) process. However, current mathematical models have not previously been employed to describe the behavior of such a process, which limits engineering design and optimisation of process operation. This work focusses on extending the ASM3 model towards the description of short-cut nitrogen removal and simultaneous PHA recovery in a sidestream treatment process. The calibrated and validated model described very well the nitritation process coupled with the aerobic feast/anoxic famine process for the selection of PHA producing organisms at a pilot-scale facility operated in Carbonera, Italy, where the normalised root mean squared error (NRMSE) was consistently <20%. Furthermore, the model applied to the PHA selection stage could effectively describe the PHA accumulation stage without recalibration. A simulation study was performed using the modified ASM3 model to assess the relative benefits of the SCEPPHAR process strategy as compared to the fully aerobic selection process for mixed culture PHA production. While the level of PHA production was found to be 34% lower with SCEPPHAR, a 43% savings in volatile fatty acids (VFAs) demand, a 15% decrease in Total suspended solids (TSS) production and a 28% decrease in oxygen demand were also achievable, which could lead to savings in operational costs. This study facilitates the design and optimisation of WRRFs that integrate short-cut N removal with PHA production, saving aeration energy costs while achieving resource recovery.

Modeling, simulation and control of biological and chemical P-removal processes for membrane bioreactors (MBRs) from lab to full-scale applications: State of the art

Phosphorus (P) removal from the domestic wastewater is required to counter the eutrophication in receiving water bodies and is mandated by the regulatory frameworks in several countries with discharge limits within 1-2mgPL-1. Operating at higher sludge retention time (SRT) and higher biomass concentration than the conventional activated sludge process (CASP), membrane bioreactors (MBRs) are able to remove 70-98% phosphorus without addition of coagulant. In full-scale facilities, enhanced biological phosphorus removal (EBPR) is assisted by the addition of metal coagulant to ensure >95% P-removal. MBRs are successfully used for super-large-scale wastewater treatment facilities (capacity >100,000 m3d-1). This paper documents the knowledge of P-removal modeling from lab to full-scale submerged MBRs and assesses the existing mathematical models for P-removal from domestic wastewater. There are still limited studies involving integrated modeling of the MBRs (full/super large-scale), considering the complex interactions among biology, chemical addition, filtration, and fouling. This paper analyses the design configurations and the parameters affecting the biological and chemical P-removal in MBRs to understand the P-removal process sensitivity and their implications for the modeling studies. Furthermore, it thoroughly reviews the applications of bio-kinetic and chemical precipitation models to MBRs for assessing their effectiveness with default stoichiometric and kinetic parameters and the extent to which these parameters have been calibrated/adjusted to simulate the P-removal successfully. It also presents a brief overview and comparison of seven (7) chemical precipitation models, along with a quick comparison of commercially available simulators. In addition to advantages associated with chemical precipitation for P-removal, its role in changing the relative abundance of the microbial community responsible for P-removal and denitrification and the controversial role in fouling mitigation/increase are discussed. Lastly, it encompasses several coagulant dosing control systems and their applications in the pilot to full-scale facilities to save coagulants and optimize the P-removal performance.

Integrated anaerobic and algal bioreactors: A promising conceptual alternative approach for conventional sewage treatment

Conventional sewage treatment applying activated sludge processes is energy-intensive and requires great financial input, hampering widespread implementation. The introduction of anaerobic membrane bioreactors (AnMBR) followed by an algal reactor growing species of commercial interest, may present an alternative, contributing to the envisaged resource recovery at sewage treatment plants. AnMBRs can be applied for organic matter removal with energy self-sufficiency, provided that effective membrane fouling management is applied. Haematococcus pluvialis, an algal species with commercial value, can be selected for ammonium and phosphate removal. Theoretical analysis showed that good pollutant removal, positive financial output, as well as a significant reduction in the amount of hazardous activated sludge can be achieved by applying the proposed process, showing interesting advantages over current sewage treatment processes. Microbial contamination to H. pluvialis is a challenge, and technologies for preventing the contamination during continuous sewage treatment need to be applied.

Integrated supervisory and override control strategies for effective biological phosphorus removal and reduced operational costs in wastewater treatment processes

A novel control strategy is developed for a municipal wastewater treatment plant (WWTP) consisting of anaerobic-anoxic-aerobic reactors. The idea is to generate more organic matter with a reduction of nitrate concentration in the anoxic section so that more biological phosphorus (P) removal happens. For this, the Supervisory and Override Control Approach (SOPCA) is designed based on the benchmark simulation model (BSM1-P) and is evaluated by considering dynamic influent. In the supervisory layer, proportional integral (PI) and fuzzy controllers are designed. Additionally, dissolved oxygen (S_o) control loops in the aerobic reactors are designed. PI controller is designed for control of nitrate levels in the anoxic reactors and is integrated with override control and supervisory layer. It is found that the novel SOPCA approach gave better nutrient removal with slightly higher operating costs when S_o control is not put in place. With three S_o control loops in place, the WWTP showed better effluent quality and lower cost. Here, the improved removal efficiency of 28.5% and 20.5% are obtained when Fuzzy and PI control schemes respectively are used in the supervisory layer. Therefore, the application of SOPCA is recommended for a better P removal rate.

Organic matter parameters in WWTP - a critical review and recommendations for application in activated sludge modelling

This paper includes a comprehensive literature review of sludge composition data from wastewater treatment plants. 722 data sets from 249 sources were used to establish typical ratios between COD and solids-based parameters and to verify rule-of-thumb values, respectively. Confirmation of these typical ratios can also be accomplished by using biochemical composition data. It is shown that a correlation between data from proteins, lipids and carbohydrates analysis can be related to COD/VSS ratios. Finally, using the findings from the literature review, the organic and inorganic conversion factors of COD fractions in activated sludge models are adjusted to solids-based parameters. It was shown that with the adjustments of the factors and a partition of the particulate inert fraction into a fraction assigned to the influent and a fraction assigned to the endogenous products, a better agreement with the ratios of COD/VSS in the individual sludge streams can be established.

Design of Feedback Control Strategies in a Plant-Wide Wastewater Treatment Plant for Simultaneous Evaluation of Economics, Energy Usage, and Removal of Nutrients

Simultaneous removal of nitrogen and phosphorous is a recommended practice while treating wastewater. In the present study, control strategies based on proportional-integral (PI), model predictive control (MPC), and fuzzy logic are developed and implemented on a plant-wide wastewater treatment plant. Four combinations of control frameworks are developed in order to reduce the operational cost and improve the effluent quality. As a working platform, a Benchmark simulation model (BSM2-P) is used. A default control framework with PI controllers is used to control nitrate and dissolved oxygen (DO) by manipulating the internal recycle and oxygen mass transfer coefficient (KLa). Hierarchical control topology is proposed in which a lower-level control framework with PI controllers is implemented to DO in the sixth reactor by regulating the KLa of the fifth, sixth, and seventh reactors, and fuzzy and MPC are used at the supervisory level. This supervisory level considers the ammonia in the last aerobic reactor as a feedback signal to alter the DO set-points. PI-fuzzy showed improved effluent quality by 21.1%, total phosphorus removal rate by 33.3% with an increase of operational cost, and a slight increase in the production rates of greenhouse gases. In all the control design frameworks, a trade-off is observed between operational cost and effluent quality.

Supervisory control configurations design for nitrogen and phosphorus removal in wastewater treatment plants

Model predictive control (MPC) and Fuzzy controllers are designed in a two-level hierarchical supervisory control framework for control of activated sludge-based wastewater treatment plants (WWTP) in order to efficiently remove nitrogen and phosphorus. Benchmark simulation model No.3 with a bio-phosphorus (ASM3bioP) module is used as a working platform. The hierarchical control framework is used to alter the dissolved oxygen in the seventh reactor (DO₇ ) to control ammonia. Lower-level PI, MPC, and Fuzzy are used to control the nitrate levels in the fourth reactor (S_NO4 ) by manipulating internal recycle (Q_intr ) and DO₇ in the seventh tank by manipulating mass transfer coefficient (K_L a₇ ). MPC and Fuzzy are designed in the supervisory layer to alter the DO₇ set-point based on the ammonia composition in the seventh reactor (NH₇ ). From the analysis, it is observed that the effluent quality is improved with a decrease in ammonia, TN, and TP. Though a little difference was observed in the cost for all the control strategies, a trade-off is maintained between cost and percentage improvement of effluent quality. MPC-MPC combination showed significant removal in ammonia and better effluent quality when compared to other control strategies. PRACTITIONER POINTS: Developed novel strategies in hierarchical configurations for better nutrient removal with optimal costs in an A² O process. Lower level control strategies deals with dissolved oxygen in last aeration tank and nitrate in fourth anoxic tank (PI/MPC) Higher level control strategy deals with ammonia in the last aeration tank (MPC/Fuzzy). Average and violations of nutrient removal, economy and overall effluent quality for three weather conditions (Dry, Rain and Strom) are studied. A trade-off is observed between EQI and OCI.

Design of control strategies for nutrient removal in a biological wastewater treatment process

Wastewater treatment plants (WWTP) are highly non-linear operations concerned with huge disturbances in flow rate and concentration of pollutants with uncertainties in the composition of influent wastewater. In this work, the activated sludge process model with seven reactor configuration in the ASM3bioP framework is used to achieve simultaneous removal of nitrogen and phosphorus. A total of 8 control approaches are designed and implemented in the advanced simulation framework for assessment of the performance. The performance of the WWTP (effluent quality index and global plant performance) and the operational costs are also evaluated to compare the control approaches. Additionally, this paper reports a comparison among proportional integral (PI) control, fuzzy logic control, and model-based predictive control (MPC) configurations framework. The simulation outcomes indicated that all three control approaches were able to enhance the performance of WWTP when compared with open loop operation.

Denitrification kinetics indicates nitrous oxide uptake is unaffected by electron competition in Accumulibacter

Denitrifying phosphorus removal is a cost and energy efficient treatment technology that relies on polyphosphate accumulating organisms (DPAOs) utilizing nitrate or nitrite as terminal electron acceptor. Denitrification is a multistep process, but many organisms do not possess the complete pathway, leading to the accumulation of intermediates such as nitrous oxide (N₂O), a potent greenhouse gas and ozone depleting substance. Candidatus Accumulibacter organisms are prevalent in denitrifying phosphorus removal processes and, according to genomic analyses, appear to vary in their denitrification abilities based on their lineage. Denitrification kinetics and nitrous oxide accumulation in the absence of inhibition from free nitrous acid is a strong indicator of denitrification capabilities of Accumulibacter exposed long-term to nitrate or nitrite as electron acceptor. Thus, we investigated the preferential use of the nitrogen oxides involved in denitrification and nitrous oxide accumulation in two enrichments of Accumulibacter and a competitor - the glycogen accumulating organism Candidatus Competibacter. We modified a metabolic model to predict phosphorus removal and denitrification rates when nitrate, nitrite or N₂O were added as electron acceptors in different combinations. Unlike previous studies, no N₂O accumulation was observed for Accumulibacter in the presence of multiple electron acceptors. Electron competition did not limit denitrification kinetics or lead to N₂O accumulation in Accumulibacter or Competibacter. Despite the presence of sufficient internal storage polymers (polyhydroxyalkanoates, or PHA) as energy source for each denitrification step, the extent of denitrification observed was dependent on the dominant organism in the enrichment. Accumulibacter showed complete denitrification, whereas Competibacter denitrification was limited to reduction of nitrate to nitrite. These findings indicate that DPAOs can contribute to lowering N₂O emissions in the presence of multiple electron acceptors under partial nitritation conditions.

Long-term simulation of a full-scale EBPR plant with a novel metabolic-ASM model and its use as a diagnostic tool

This study evaluates the predictive capacity of the META-ASM model, a new integrated metabolic activated sludge model, in describing the long-term performance of a full-scale enhanced biological phosphorus removal (EBPR) system that suffers from inconsistent performance. In order to elucidate the causes of EBPR upsets and troubleshoot the process accordingly, the META-ASM model was tested as an operational diagnostic tool in a 1336-day long-term dynamic simulation, while its performance was compared with the ASM-inCTRL model, a version based on the Barker & Dold model. Overall, the predictions obtained with the META-ASM without changing default parameters were more reliable and effective at describing the active biomass of polyphosphate accumulating organisms (PAOs) and the dynamics of their storage polymers. The primary causes of the EBPR upsets were the high aerobic hydraulic retention times (HRTs) and low organic loading rates (OLRs) of the plant, which led to periods of starvation. The impact of these factors on EBPR performance were only identified with the META-ASM model. Furthermore, the first signs of process upsets were predicted by variations in the aerobic PAO maintenance rates, suggesting that the META-ASM model has potential to provide an early warning of process upset. The simulation of a new viable operational strategy indicated that troubleshooting the process could be achieved by reducing the aerated volume by switching off air in the first half of the aeration tank. In this new strategy, the META-ASM model predicted a simultaneous improvement in the biological phosphorus (P) and nitrogen (N) removal due to the enhancement of the hydrolysis and fermentation of the mixed liquor sludge in the new unaerated zone, which increased the availability of volatile fatty acids (VFAs) for PAOs. This study demonstrates that the META-ASM model is a powerful operational diagnostic tool for EBPR systems, capable of predicting and mitigating upsets, optimising performance and evaluating new process designs.

Effects of heavy metals and metal (oxide) nanoparticles on enhanced biological phosphorus removal

With the rapid growth of economics and nanotechnology, a significant portion of the anthropogenic emissions of heavy metals and nanoparticles (NPs) enters wastewater streams and discharges to wastewater treatment plants, thereby potentially posing a risk to the bacteria that facilitate the successful operation of the enhanced biological phosphorus (P) removal (EBPR) process. Although some efforts have been made to obtain detailed insights into the effects of heavy metals and metal (oxide) nanoparticles [Me(O)NPs], many unanswered questions remain. One question is whether the toxicity of Me(O)NPs originates from the released metal ions. This review aims to holistically evaluate the effects of heavy metals and Me(O)NPs. The interactions among extracellular polymeric substances, P, and heavy metals [Me(O)NPs] are presented and discussed for the first time. The potential mechanisms of the toxicity of heavy metals [Me(O)NPs] are summarized. Additionally, mathematical models of the toxicity and removal of P, heavy metals, and Me(O)NPs are overviewed. Finally, knowledge gaps and opportunities for further study are discussed to pave the way for fully understanding the inhibition of heavy metals [Me(O)NPs] and for reducing their inhibitory effect to maximize the reliability of the EBPR process.

A novel metabolic-ASM model for full-scale biological nutrient removal systems

This study demonstrates that META-ASM, a new integrated metabolic activated sludge model, provides an overall platform to describe the activity of the key organisms and processes relevant to biological nutrient removal (BNR) systems with a robust single-set of default parameters. This model overcomes various shortcomings of existing enhanced biological phosphorous removal (EBPR) models studied over the last twenty years. The model has been tested against 34 data sets from enriched lab polyphosphate accumulating organism (PAO)-glycogen accumulating organism (GAO) cultures and experiments with full-scale sludge from five water resource recovery facilities (WRRFs) with two different process configurations: three stage Phoredox (A2/O) and adapted Biodenitro™ combined with a return sludge sidestream hydrolysis tank (RSS). Special attention is given to the operational conditions affecting the competition between PAOs and GAOs, capability of PAOs and GAOs to denitrify, metabolic shifts as a function of storage polymer concentrations, as well as the role of these polymers in endogenous processes and fermentation. The overall good correlations obtained between the predicted versus measured EBPR profiles from different data sets support that this new model, which is based on in-depth understanding of EBPR, reduces calibration efforts. On the other hand, the performance comparison between META-ASM and literature models demonstrates that existing literature models require extensive parameter changes and have limited predictive power, especially in the prediction of long-term EBPR performance. The development of such a model able to describe in detail the microbial and chemical transformations of BNR systems with minimal adjustment to parameters suggests that the META-ASM model is a powerful tool to predict and mitigate EBPR upsets, optimise EBPR performance and to evaluate new process designs.

Aeration Process in Bioreactors as the Main Energy Consumer in a Wastewater Treatment Plant. Review of Solutions and Methods of Process Optimization

Due to the key role of the biological decomposition process of organic compounds in wastewater treatment, a very important thing is appropriate aeration of activated sludge, because microorganisms have to be supplied with an appropriate amount of oxygen. Aeration is one of the most energy-consuming processes in the conventional activated sludge systems of wastewater treatment technology (may consume from 50% to 90% of electricity used by a plant), which makes it the most cost-generating process incurred by treatment plants. The paper presents the construction of aeration systems, their classification as well as parameters and factors that significantly affect the aeration process e.g., oxygen transfer efficiency, diffuser fouling, methods of dealing with diffuser fouling, diffuser selection. Additionally, there are briefly presented “smart control” systems in wastewater treatment and effect of application control strategy based on Supervisory Control and Data Acquisition system connected with the decrease in the energy consumption for aeration of bioreactors with activated sludge. It is noted that before the process is optimized, the system should be equipped with suitable metering devices. Only when relevant data is available, the improvements can be carried out. However, it’s important, that the operator should regularly maintain good condition and high efficiency of diffusers.

New framework for automated article selection applied to a literature review of Enhanced Biological Phosphorus Removal

AIMS

Enhanced Biological Phosphorus Removal (EBPR) is a technology widely used in wastewater treatment to remove phosphorus (P) and prevent eutrophication. Establishing its operating efficiency and stability is an active research field that has generated almost 3000 publications in the last 40 years. Due to its size, including over 119 review articles, it is an example of a field where it becomes increasingly difficult to manually recognize its key research contributions, especially for non-experts or newcomers. Therefore, this work included two distinct but complementary objectives. First, to assemble for the first time a collection of bibliometric techniques into a framework for automating the article selection process when preparing a literature review (section 2). Second, to demonstrate it by applying it to the field of EBPR, producing a bibliometric analysis and a review of the key findings of EBPR research over time (section 3).

FINDINGS

The joint analysis of citation networks, keywords, citation profiles, as well as of specific benchmarks for the identification of highly-cited publications revealed 12 research topics. Their content and evolution could be manually reviewed using a selection of articles consisting of approximately only 5% of the original set of publications. The largest topics addressed the identification of relevant microorganisms, the characterization of their metabolism, including denitrification and the competition between them (Clusters A-D). Emerging and influential topics, as determined by different citation indicators and temporal analysis, were related to volatile fatty acid production, P-recovery from waste activated sludge and aerobic granules for better process efficiency and stability (Clusters F-H).

CONCLUSIONS

The framework enabled key contributions in each of the constituent topics to be highlighted in a way that may have otherwise been biased by conventional citation-based ranking. Further, it reduced the need for manual input and a priori expertise compared to a traditional literature review. Hence, in an era of accelerated production of information and publications, this work contributed to the way that we are able to use computer-aided approaches to curate information and manage knowledge.

The evaluation of COD fractionation and modeling as a key factor for appropriate optimization and monitoring of modern cost-effective activated sludge systems

A study was conducted to characterize the raw wastewater entering a modern cost effective municipal WWTP in Poland using two approaches; 1) a combination of modeling and carbonaceous oxygen demand (COD) fractionation using respirometric test coupled with model estimation (RT-ME) and 2) flocculation/filtration COD fractionation method combined with BOD measurements (FF-BOD). It was observed that the particulate fractions of COD obtained using FF-BOD method was higher than those estimated by RT-ME approach. Contrary to the above, the values of inert soluble fraction evaluated by FF-BOD method was significantly lower than RT-ME approach (2.4% and 3.9% respectively). Furthermore, the values for low colloidal and particulate fractions as well as soluble inert fractions were different than expected from a typical municipal wastewater. These observations suggest that even at low load (10% of the total wastewater treatment inflow), the industrial wastewater composition can significantly affect the characteristics of municipal wastewater which could also affect the performance and accuracy of respirometric tests. Therefore, in such cases, comparison of the respirometric tests with flocculation/filtration COD/BOD measurements are recommended. Oxygen uptake rate profile with settled wastewater and/or after coagulation-flocculation, however, could still be recommended as a "rapid" control method for monitoring/optimising modern cost-effective wastewater treatment plants.

Improve the performance of full-scale continuous treatment of municipal wastewater by combining a numerical model and online sensors

Mathematical models based on instant environmental inputs are increasingly applied to optimize the operation of wastewater treatment plants (WWTPs) for improving treatment efficiency. This study established a numerical model consisting of the activated sludge module ASM3 and EAWAG bio-P module, and calibrated the model using data from a full-scale experiment conducted in a WWTP in Nanjing, China. The calibrated model was combined with online sensors for water temperature, chemical oxygen demand, NH⁺ ₄-N and PO^3- ₄-P to optimize and dynamically adjust the operation of the WWTP. The results showed that, compared to the original default operation mode, the effluent water quality was significantly improved after optimization even without supplementation of external carbon or alkalinity, and the required aeration rate in spring, summer, autumn, and winter was reduced by 15, 41, 33 and 11%, respectively. The study indicated that there was the potential for application of closed-loop automatic control to regulate operating parameters to improve wastewater treatment processes through the integration of data on influent characteristics and environmental conditions from sensors, and results from simulation models.

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.

Modeling the Effect of External Carbon Source Addition under Different Electron Acceptor Conditions in Biological Nutrient Removal Activated Sludge Systems

The aim of this study was to expand the International Water Association Activated Sludge Model No. 2d (ASM2d) to predict the aerobic/anoxic behavior of polyphosphate accumulating organisms (PAOs) and "ordinary" heterotrophs in the presence of different external carbon sources and electron acceptors. The following new aspects were considered: (1) a new type of the readily biodegradable substrate, not available for the anaerobic activity of PAOs, (2) nitrite as an electron acceptor, and (3) acclimation of "ordinary" heterotrophs to the new external substrate via enzyme synthesis. The expanded model incorporated 30 new or modified process rate equations. The model was evaluated against data from several, especially designed laboratory experiments which focused on the combined effects of different types of external carbon sources (acetate, ethanol and fusel oil) and electron acceptors (dissolved oxygen, nitrate and nitrite) on the behavior of PAOs and "ordinary" heterotrophs. With the proposed expansions, it was possible to improve some deficiencies of the ASM2d in predicting the behavior of biological nutrient removal (BNR) systems with the addition of external carbon sources, including the effect of acclimation to the new carbon source.

A plant-wide aqueous phase chemistry module describing pH variations and ion speciation/pairing in wastewater treatment process models

There is a growing interest within the Wastewater Treatment Plant (WWTP) modelling community to correctly describe physico-chemical processes after many years of mainly focusing on biokinetics. Indeed, future modelling needs, such as a plant-wide phosphorus (P) description, require a major, but unavoidable, additional degree of complexity when representing cationic/anionic behaviour in Activated Sludge (AS)/Anaerobic Digestion (AD) systems. In this paper, a plant-wide aqueous phase chemistry module describing pH variations plus ion speciation/pairing is presented and interfaced with industry standard models. The module accounts for extensive consideration of non-ideality, including ion activities instead of molar concentrations and complex ion pairing. The general equilibria are formulated as a set of Differential Algebraic Equations (DAEs) instead of Ordinary Differential Equations (ODEs) in order to reduce the overall stiffness of the system, thereby enhancing simulation speed. Additionally, a multi-dimensional version of the Newton-Raphson algorithm is applied to handle the existing multiple algebraic inter-dependencies. The latter is reinforced with the Simulated Annealing method to increase the robustness of the solver making the system not so dependent of the initial conditions. Simulation results show pH predictions when describing Biological Nutrient Removal (BNR) by the activated sludge models (ASM) 1, 2d and 3 comparing the performance of a nitrogen removal (WWTP1) and a combined nitrogen and phosphorus removal (WWTP2) treatment plant configuration under different anaerobic/anoxic/aerobic conditions. The same framework is implemented in the Benchmark Simulation Model No. 2 (BSM2) version of the Anaerobic Digestion Model No. 1 (ADM1) (WWTP3) as well, predicting pH values at different cationic/anionic loads. In this way, the general applicability/flexibility of the proposed approach is demonstrated, by implementing the aqueous phase chemistry module in some of the most frequently used WWTP process simulation models. Finally, it is shown how traditional wastewater modelling studies can be complemented with a rigorous description of aqueous phase and ion chemistry (pH, speciation, complexation).

A modified oxic-settling-anaerobic activated sludge process using gravity thickening for excess sludge reduction

Oxic-settling-anaerobic process (OSA) was known as a cost-effective way to reduce the excess sludge production with simple upgrade of conventional activated sludge process (CAS). A low oxidation-reduction potential (ORP) level was the key factor to sludge decay and lysis in the sludge holding tank of the OSA process. However, the ORP control with nitrogen purge or chemical dosing in the OSA process would induce extra expense and complicate the operation. Hence, in this study, a sludge holding tank using gravity thickening was applied to OSA process to reduce the excess sludge production without any ORP control. Results showed that the modified OSA process not only reduced the excess sludge production effectively but also improved the sludge settleability without affected the treatment capacity. The reduction of the excess sludge production in the modified OSA process resulted from interactions among lots of factors. The key element of the process was the gravity thickening sludge holding tank.

Mathematical Modeling of Nitrous Oxide Production during Denitrifying Phosphorus Removal Process

A denitrifying phosphorus removal process undergoes frequent alternating anaerobic/anoxic conditions to achieve phosphate release and uptake, during which microbial internal storage polymers (e.g., Polyhydroxyalkanoate (PHA)) could be produced and consumed dynamically. The PHA turnovers play important roles in nitrous oxide (N2O) accumulation during the denitrifying phosphorus removal process. In this work, a mathematical model is developed to describe N2O dynamics and the key role of PHA consumption on N2O accumulation during the denitrifying phosphorus removal process for the first time. In this model, the four-step anoxic storage of polyphosphate and four-step anoxic growth on PHA using nitrate, nitrite, nitric oxide (NO), and N2O consecutively by denitrifying polyphosphate accumulating organisms (DPAOs) are taken into account for describing all potential N2O accumulation steps in the denitrifying phosphorus removal process. The developed model is successfully applied to reproduce experimental data on N2O production obtained from four independent denitrifying phosphorus removal study reports with different experimental conditions. The model satisfactorily describes the N2O accumulation, nitrogen reduction, phosphate release and uptake, and PHA dynamics for all systems, suggesting the validity and applicability of the model. The results indicated a substantial role of PHA consumption in N2O accumulation due to the relatively low N2O reduction rate by using PHA during denitrifying phosphorus removal.

A novel protocol for model calibration in biological wastewater treatment

Activated sludge models (ASMs) have been widely used for process design, operation and optimization in wastewater treatment plants. However, it is still a challenge to achieve an efficient calibration for reliable application by using the conventional approaches. Hereby, we propose a novel calibration protocol, i.e. Numerical Optimal Approaching Procedure (NOAP), for the systematic calibration of ASMs. The NOAP consists of three key steps in an iterative scheme flow: i) global factors sensitivity analysis for factors fixing; ii) pseudo-global parameter correlation analysis for non-identifiable factors detection; and iii) formation of a parameter subset through an estimation by using genetic algorithm. The validity and applicability are confirmed using experimental data obtained from two independent wastewater treatment systems, including a sequencing batch reactor and a continuous stirred-tank reactor. The results indicate that the NOAP can effectively determine the optimal parameter subset and successfully perform model calibration and validation for these two different systems. The proposed NOAP is expected to use for automatic calibration of ASMs and be applied potentially to other ordinary differential equations models.

Modelling the metabolic shift of polyphosphate-accumulating organisms

Enhanced biological phosphorus removal (EBPR) is one of the most important methods of phosphorus removal in municipal wastewater treatment plants, having been described by different modelling approaches. In this process, the PAOs (polyphosphate accumulating organisms) and GAOs (glycogen accumulating organisms) compete for volatile fatty acids uptake under anaerobic conditions. Recent studies have revealed that the metabolic pathways used by PAOs in order to obtain the energy and the reducing power needed for polyhydroxyalkanoates synthesis could change depending on the amount of polyphosphate stored in the cells. The model presented in this paper extends beyond previously developed metabolic models by including the ability of PAO to change their metabolic pathways according to the content of poly-P available. The processes of the PAO metabolic model were adapted to new formulations enabling the change from P-driven VFA uptake to glycogen-driven VFA uptake using the same process equations. The stoichiometric parameters were changed from a typical PAO coefficient to a typical GAO coefficient depending on the internal poly-P with Monod-type expressions. The model was calibrated and validated with seven experiments under different internal poly-P concentrations, showing the ability to correctly represent the PAO metabolic shift at low poly-P concentrations. The sensitivity and error analysis showed that the model is robust and has the ability to describe satisfactorily the change from one metabolic pathway to the other one, thereby encompassing a wider range of process conditions found in EBPR plants.

Variance-based sensitivity analysis for wastewater treatment plant modelling

Global sensitivity analysis (GSA) is a valuable tool to support the use of mathematical models that characterise technical or natural systems. In the field of wastewater modelling, most of the recent applications of GSA use either regression-based methods, which require close to linear relationships between the model outputs and model factors, or screening methods, which only yield qualitative results. However, due to the characteristics of membrane bioreactors (MBR) (non-linear kinetics, complexity, etc.) there is an interest to adequately quantify the effects of non-linearity and interactions. This can be achieved with variance-based sensitivity analysis methods. In this paper, the Extended Fourier Amplitude Sensitivity Testing (Extended-FAST) method is applied to an integrated activated sludge model (ASM2d) for an MBR system including microbial product formation and physical separation processes. Twenty-one model outputs located throughout the different sections of the bioreactor and 79 model factors are considered. Significant interactions among the model factors are found. Contrary to previous GSA studies for ASM models, we find the relationship between variables and factors to be non-linear and non-additive. By analysing the pattern of the variance decomposition along the plant, the model factors having the highest variance contributions were identified. This study demonstrates the usefulness of variance-based methods in membrane bioreactor modelling where, due to the presence of membranes and different operating conditions than those typically found in conventional activated sludge systems, several highly non-linear effects are present. Further, the obtained results highlight the relevant role played by the modelling approach for MBR taking into account simultaneously biological and physical processes.

Dissolved oxygen regulation by logarithmic/antilogarithmic control to improve a wastewater treatment process

This paper presents the automation of a real activated sludge wastewater treatment plant, which is located at San Antonio Ajijic in Jalisco, Mexico. The main objective is to create an on-line automatic supervision system, and to regulate the dissolved oxygen concentration in order to improve the performances of the process treating municipal wastewater. An approximate mathematical model is determined in order to evaluate via simulations different control strategies: proportional integral (PI), fuzzy PI and PI Logarithm/Antilogarithm (PI L/A). The controlled variable is dissolved oxygen and the control input is the injected oxygen. Based on this evaluation, the PI L/A controller is selected to be implemented in the real process. After that, the implementation, testing and fully operation of the plant automation are described. With this system, the considered wastewater treatment plant save energy and improves the effluent quality; also, the process monitoring is done online and it is easily operated by the plant users.

Including Life Cycle Assessment for decision-making in controlling wastewater nutrient removal systems

This paper focuses on the use of Life Cycle Assessment (LCA) to evaluate the performance of seventeen control strategies in wastewater treatment plants (WWTPs). It tackles the importance of using site-specific factors for nutrient enrichment when decision-makers have to select best operating strategies. Therefore, the LCA evaluation is repeated for three different scenarios depending on the limitation of nitrogen (N), phosphorus (P), or both, when evaluating the nutrient enrichment impact in water bodies. The LCA results indicate that for treated effluent discharged into N-deficient aquatic systems (e.g. open coastal areas) the most eco-friendly strategies differ from the ones dealing with discharging into P-deficient (e.g. lakes and rivers) and N&P-deficient systems (e.g. coastal zones). More particularly, the results suggest that strategies that promote increased nutrient removal and/or energy savings present an environmental benefit for N&P and P-deficient systems. This is not the case when addressing N-deficient systems for which the use of chemicals (even for improving N removal efficiencies) is not always beneficial for the environment. A sensitivity analysis on using weighting of the impact categories is conducted to assess how value choices (policy decisions) may affect the management of WWTPs. For the scenarios with only N-limitation, the LCA-based ranking of the control strategies is sensitive to the choice of weighting factors, whereas this is not the case for N&P or P-deficient aquatic systems.

Enhanced biological phosphorus removal and its modeling for the activated sludge and membrane bioreactor processes

A modified activated sludge process (ASP) for enhanced biological phosphorus removal (EBPR) needs to sustain stable performance for wastewater treatment to avoid eutrophication in the aquatic environment. Unfortunately, the overall efficiency of the EBPR in ASPs and membrane bioreactors (MBRs) is frequently hindered by different operational/system constraints. Moreover, although phosphorus removal data from several wastewater treatment systems are available, a comprehensive mathematical model of the process is still lacking. This paper presents a critical review that highlights the core issues of the biological phosphorus removal in ASPs and MBRs while discussing the inhibitory process requirements for other nutrients' removal. This mini review also successfully provided an assessment of the available models for predicting phosphorus removal in both ASP and MBR systems. The advantages and limitations of the existing models were discussed together with the inclusion of few guidelines for their improvement.

Effect of nitrite, limited reactive settler and plant design configuration on the predicted performance of simultaneous C/N/P removal WWTPs

This paper describes a modelling study where five new benchmark plant design configurations for biological nutrient removal (A(2)/O, UCT, JHB, MUCT and BDP-5 stage) are simulated and evaluated under different model assumptions. The ASM2d including electron dependent decay rates is used as the reference model (A1). The second case (A2) adds nitrite as a new state variable, describing nitrification and denitrification as two-step processes. The third set of models (A3 and A4) considers different reactive settlers types (diffusion-limited/non limited). This study analyses the importance of these new model extensions to correctly describe the nitrification behaviour and the carbon source competition between ordinary heterotrophic organisms (OHO) and polyphosphate accumulating organisms (PAO) under certain operation conditions. The economic and environmental aspects when meeting the P discharge limits by adding an external carbon source are also studied.

Comparison of conventional and inverted A2/O processes: phosphorus release and uptake behaviors

Two full-scale systems operated in parallel, a conventional A2/O system consisting of anaerobic, anoxic and oxic compartments in succession and an inverted system consisting of anoxic, anaerobic and oxic compartments without internal recycle, were compared in terms of their phosphorus removal performance, with an emphasis on phosphate (P) release behaviors, using both operational data and simulation results. The inverted system exhibited better long-term phosphorus removal performance (0.2 +/- 0.3 vs. 0.7 +/- 0.7 mg/L), which should be attributed to the higher P release rate (0.79 vs. 0.60 kg P/(kg MLSS x day)) in the non-aerated compartments. The P release occurred in both the anoxic and anaerobic compartments of the inverted system, resulting in more efficient P release. Although the abundances of the 'Candidatus Accumulibacter phosphatis' population in the two systems were quite similar ((19.1 +/- 3.27)% and (18.4 +/- 4.15)% of the total microbe (DAPI stained particles) population in the inverted and conventional systems, respectively, by fluorescence in situ hybridization (FISH)), the high-concentration DAPI staining results show that the abundances of the whole polyphosphate accumulating organisms (PAOs) in the aerobic ends were quite different (the average ratios of the poly-P granules to total microbes (DAPI stained particles) were (45 +/- 4.18)% and (35 +/- 5.39)%, respectively). Both the operational data and simulation results showed that the inverted system retained more abundant PAO populations due to its special configuration, which permitted efficient P release in the non-aerated compartment and better P removal.

Evaluating sludge minimization caused by predation and viral infection based on the extended activated sludge model No. 2d

The Activated Sludge Model No. 2d (ASM2d) was extended to incorporate the processes of both predation and viral infection. The extended model was used to evaluate the contributions of predation and viral infection to sludge minimization in a sequencing batch reactor (SBR) system enriching polyphosphate-accumulating organisms (PAOs). Three individual decay processes formulated according to the general model rules were used in the extended model. The model was firstly calibrated and validated by different experimental results. It was used to evaluate the potential extent of predation and viral infection on sludge minimization. Simulations indicate that predation contributes roughly two times more to sludge minimization than viral infection in the SBR system enriching PAOs. The sensitivity analyses of the selected key parameters reveal that there are thresholds on both predation and viral infection rates, if they are too large a minimal sludge retention time is obtained and the effluent quality is deteriorating. Due to the thresholds, the contributions of predation and viral infection to sludge minimization are limited to a maximal extent of about 21% and 9%, respectively. However, it should be noted that the parameters concerning predation and viral infection were not calibrated separately by independent experiment in our study due to the lack of an effective method, especially for the parameters regarding viral infection. Therefore, it is essential to better evaluate these parameters in the future.

Calibration of a complex activated sludge model for the full-scale wastewater treatment plant

In this study, the results of the calibration of the complex activated sludge model implemented in BioWin software for the full-scale wastewater treatment plant are presented. Within the calibration of the model, sensitivity analysis of its parameters and the fractions of carbonaceous substrate were performed. In the steady-state and dynamic calibrations, a successful agreement between the measured and simulated values of the output variables was achieved. Sensitivity analysis revealed that upon the calculations of normalized sensitivity coefficient (S_i,j) 17 (steady-state) or 19 (dynamic conditions) kinetic and stoichiometric parameters are sensitive. Most of them are associated with growth and decay of ordinary heterotrophic organisms and phosphorus accumulating organisms. The rankings of ten most sensitive parameters established on the basis of the calculations of the mean square sensitivity measure (δ_j^msqr) indicate that irrespective of the fact, whether the steady-state or dynamic calibration was performed, there is an agreement in the sensitivity of parameters.

Modeling of the Contact-Adsorption-Regeneration (CAR) activated sludge process

Contact-Adsorption-Regeneration (CAR) process is a cost-effective system for wastewater treatment and has a potential for application in less-developed regions. To offer a better understanding of this process, a mathematical model was established on the basis of Activated Sludge Model No. 1 (ASM1) and by incorporating the adsorption and different hydrolysis processes. The model predictions were compared with the measured data in terms of effluent concentrations and removals of both chemical oxygen demand (COD) and NH(4)(+)-N. A good agreement between the predicted and measured data was observed, indicating that the model was capable of predicting the rapid adsorption, COD removal and nitrification processes in the CAR system. This work provides an experimental and theoretical basis for the application of the CAR process in less-developed regions.

Calibration of denitrifying activity of polyphosphate accumulating organisms in an extended ASM2d model

This paper presents the results of an experimental study for the modelling and calibration of denitrifying activity of polyphosphate accumulating organisms (PAOs) in full-scale WWTPs that incorporate simultaneous nitrogen and phosphorus removal. The convenience of using different yields under aerobic and anoxic conditions for modelling biological phosphorus removal processes with the ASM2d has been demonstrated. Thus, parameter η(PAO) in the model is given a physical meaning and represents the fraction of PAOs that are able to follow the DPAO metabolism. Using stoichiometric relationships, which are based on assumed biochemical pathways, the anoxic yields considered in the extended ASM2d can be obtained as a function of their respective aerobic yields. Thus, this modification does not mean an extra calibration effort to obtain the new parameters. In this work, an off-line calibration methodology has been applied to validate the model, where general relationships among stoichiometric parameters are proposed to avoid increasing the number of parameters to calibrate. The results have been validated through a UCT scheme pilot plant that is fed with municipal wastewater. The good concordance obtained between experimental and simulated values validates the use of anoxic yields as well as the calibration methodology. Deterministic modelling approaches, together with off-line calibration methodologies, are proposed to assist in decision-making about further process optimization in biological phosphate removal, since parameter values obtained by off-line calibration give valuable information about the activated sludge process such as the amount of DPAOs in the system.

Using a carbon-based ASM3 EAWAG Bio-P for modelling the enhanced biological phosphorus removal in anaerobic/aerobic activated sludge systems

Modelling of activated sludge processes is a commonly used technique to design and optimize wastewater treatment processes. Since wastewater and activated sludge is characterized by chemical oxygen demand (COD) measurements, units of state variables describing organic matter are expressed as equivalent amounts of COD. However, current procedures for measuring it have several drawbacks, including the production of hazardous wastes, so the utility of other variables for characterizing the organic load in modelling, such as total organic carbon (TOC), warrant re-evaluation. Other advantages of TOC over COD are that it provides matrix-independent analytical results and it can be readily measured online. Proposals for TOC-based models were made in the 1990s, but they seem to have sunk into obscurity. To re-assess the value of TOC for this purpose, we have recalculated the EAWAG module for Bio-P removal coupled to the Activated Sludge Model No. 3 on a TOC basis, and tested it against data acquired in batch experiments with four single carbon sources (acetate, glucose, citrate and casein). The batch test-based calibrations showed a good match with experimental data, following modifications of the model to account for the anaerobic volumes and retention times applied in the tests.

Activated sludge model (ASM) based modelling of membrane bioreactor (MBR) processes: a critical review with special regard to MBR specificities

Membrane bioreactors (MBRs) have been increasingly employed for municipal and industrial wastewater treatment in the last decade. The efforts for modelling of such wastewater treatment systems have always targeted either the biological processes (treatment quality target) as well as the various aspects of engineering (cost effective design and operation). The development of Activated Sludge Models (ASM) was an important evolution in the modelling of Conventional Activated Sludge (CAS) processes and their use is now very well established. However, although they were initially developed to describe CAS processes, they have simply been transferred and applied to MBR processes. Recent studies on MBR biological processes have reported several crucial specificities: medium to very high sludge retention times, high mixed liquor concentration, accumulation of soluble microbial products (SMP) rejected by the membrane filtration step, and high aeration rates for scouring purposes. These aspects raise the question as to what extent the ASM framework is applicable to MBR processes. Several studies highlighting some of the aforementioned issues are scattered through the literature. Hence, through a concise and structured overview of the past developments and current state-of-the-art in biological modelling of MBR, this review explores ASM-based modelling applied to MBR processes. The work aims to synthesize previous studies and differentiates between unmodified and modified applications of ASM to MBR. Particular emphasis is placed on influent fractionation, biokinetics, and soluble microbial products (SMPs)/exo-polymeric substances (EPS) modelling, and suggestions are put forward as to good modelling practice with regard to MBR modelling both for end-users and academia. A last section highlights shortcomings and future needs for improved biological modelling of MBR processes.

Experimental evaluation of decrease in the activities of polyphosphate/glycogen-accumulating organisms due to cell death and activity decay in activated sludge

Decrease in bacterial activity (biomass decay) in activated sludge can result from cell death (reduction in the amount of active bacteria) and activity decay (reduction in the specific activity of active bacteria). The goal of this study was to experimentally differentiate between cell death and activity decay as the cause of decrease in bacterial activity. By means of measuring maximal anaerobic phosphate release rates, verifying membrane integrity by live/dead staining and verifying presence of 16S rRNA with fluorescence in situ hybridization (FISH), the decay rates and death rates of polyphosphate-accumulating organisms (PAOs) in a biological nutrient removal (BNR) system and a laboratory phosphate removing sequencing batch reactor (SBR) system were determined, respectively, under famine conditions. In addition, the decay rate and death rate of glycogen-accumulating organisms (GAOs) in a SBR system with an enrichment culture of GAOs were also measured under famine conditions. Hereto the maximal anaerobic volatile fatty acid uptake rates, live/dead staining, and FISH were used. The experiments revealed that in the BNR and enriched PAO-SBR systems, activity decay contributed 58% and 80% to the decreased activities of PAOs, and that cell death was responsible for 42% and 20% of decreases in their respective activities. In the enriched GAOs system, activity decay constituted a proportion of 74% of the decreased activity of GAOs, and cell death only accounted for 26% of the decrease of their activity.