Benchmark simulation models, quo vadis?

Deep learning in wastewater treatment: a critical review

Modeling wastewater processes supports tasks such as process prediction, soft sensing, data analysis and computer assisted design of wastewater systems. Wastewater treatment processes are large, complex processes, with multiple controlling mechanisms, a high degree of disturbance variability and non-linear (generally stable) behavior with multiple internal recycle loops. Semi-mechanistic biochemical models currently dominate research and application, with data-driven deep learning models emerging as an alternative and supplementary approach. But these modeling approaches have grown in separate communities of research and practice, and so there is limited appreciation of the strengths, weaknesses, contrasts and similarities between the methods. This review addresses that gap by providing a detailed guide to deep learning methods and their application to wastewater process modeling. The review is aimed at wastewater modeling experts who are familiar with established mechanistic modeling approach, and are curious about the opportunities and challenges afforded by deep learning methods. We conclude with a discussion and needs analysis on the value of different ways of modeling wastewater processes and open research problems.

A plant-wide model describing GHG emissions and nutrient recovery options for water resource recovery facilities

In this study, a plant-wide model describing the fate of C, N and P compounds, upgraded to account for (on-site/off-site) greenhouse gas (GHG) emissions, was implemented within the International Water Association (IWA) Benchmarking Simulation Model No. 2 (BSM2) framework. The proposed approach includes the main biological N₂O production pathways and mechanistically describes CO₂ (biogenic/non-biogenic) emissions in the activated sludge reactors as well as the biogas production (CO₂/CH₄) from the anaerobic digester. Indirect GHG emissions for power generation, chemical usage, effluent disposal and sludge storage and reuse are also included using static factors for CO₂, CH₄ and N₂O. Global and individual mass balances were quantified to investigate the fluxes of the different components. Novel strategies, such as the combination of different cascade controllers in the biological reactors and struvite precipitation in the sludge line, were proposed in order to obtain high plant performance as well as nutrient recovery and mitigation of the GHG emissions in a plant-wide context. The implemented control strategies led to an overall more sustainable and efficient plant performance in terms of better effluent quality, reduced operational cost and lower GHG emissions. The lowest N₂O and overall GHG emissions were achieved when ammonium and soluble nitrous oxide in the aerobic reactors were controlled and struvite was recovered in the reject water stream, achieving a reduction of 27% for N₂O and 9% for total GHG, compared to the open loop configuration.

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.

A framework for model-based assessment of resilience in water resource recovery facilities against power outage

Current practice to enhance resilience in Water Resource Recovery Facilities (WRRFs) is to ensure redundancy or back-up for most critical equipment (e.g. pumps or blowers). Model-based assessment allows evaluation of different strategies for quantitatively and efficiently enhancing resilience and justifying the allocation of resources. The goal of this study is to provide guidance for the development of tailored deterministic models of full-scale WRRFs. A framework for model-based resilience assessment is proposed that provides guidance on data collection, model selection, model calibration and scenario analysis. The framework is embedded into the Good Modeling Practice (GMP) Unified Protocol, providing a new application for resilience assessment and an initial set of stressors for WRRFs. The usefulness of the framework is illustrated through a resilience assessment of the WRRF of Girona against power outage. Results show that, for the Girona facility, limited energy back-up can cause non-compliance of WRRF discharge limits in the case of a blower power shut-down of 6 h, and around 12 h when the blower shut-down is also combined with a shut-down of the recirculation pumps. The best option to enhance resilience would be increasing the power back-up by 218%, which allows the plant to run with recirculation pumps and blowers at minimum capacity. In such a case, resilience can be further enhanced by manipulating the air supply valves to optimise the air distribution, to balance oxygen needs in each reactor with the overall system pressure. We conclude that, with industry consensus on what is considered an acceptable level of resilience, a framework for resilience assessment would be a useful tool to enhance the resilience of our current water infrastructure. Further research is needed to establish if the permit structure should accommodate levels sof functionality to account for stress events.

Modeling interspecific competition of the microbial community during anaerobic digestion based on cellular automata and ADM1

Interspecific competition for substrate and space gives rise to considerable variation in biomass distribution within the microbial community. To study microbial community in depth, we used several research methods as sampling and analytical measurements, and developed a cellular automata (CA) model that would facilitate a description of the microbial growth process based on Anaerobic Digestion Model No. 1 (ADM1) of the International Water Association (IWA). Using the CA model, we aimed to determine whether interspecific competition occurs among acidogens, acetogens and methanogens, and to examine the influence of interspecific competition on the spatial structure of microbial communities. We found that acetogens and methanogens competed for core space, resulting in a multi-layer structure. Butyrate-degrading acetogens increased in number, resulting in inhibition of propionate-degrading acetogens. Hydrogenotrophic methanogens showed stronger competitive advantage than acetotrophic methanogens. The simulation showed that the multi-layer structure of the microbial community was formed by interspecific competition.

Model-Based Solution for Upgrading Nitrogen Removal for a Full-Scale Municipal Wastewater Treatment Plant with CASS Process

Aiming at providing cost-effective approach for upgrading the existing municipal wastewater treatment plants in the cold region of China to meet more stringent discharge standards of nitrogen removal, a full-scale sewage treatment plant with the CASS process was selected through focusing on biological process, key equipment and hydrodynamics in bioreactors by the activated sludge model 1 (ASM1) and computational fluid dynamics (CFD) model. Influent COD fractions and the key characteristic parameters (YH and bH) of the activated sludge were determined through the respirometry at temperatures of 10 °C and 20 °C, respectively. The layout of submerged agitator installation in the bioreactor of the CASS process was optimized through CFD simulation. The calculation of the average relative deviation (less than 20%) between simulated data and the operation data, demonstrated that the ASM1 model could be reasonably used in the wastewater treatment plant simulation. The upgrade solution based on modelling of ASM1 and CFD was successfully applied in practice, which not only made the effluent COD, NH4+-N and TN concentrations meet with the discharge standard of Grade I-A, but also reduced the energy consumption by 25% and 16.67% in summer and winter, respectively. After upgrading, microbial diversity increased in both summer and winter, with an especially significant increase of the relative abundance of denitrifying bacteria.

Assessment of sludge management strategies in wastewater treatment systems using a plant-wide approach

The objective of this paper is to use plant-wide modeling to assess the net impacts of varying sludge management strategies. Special emphasis is placed on effluent quality, operational cost and potential resource recovery (energy, nutrients). The study is particularly focused on a centralized bio-solids beneficiation facility (BBF), which enables larger, more capital intensive sludge management strategies. Potential barriers include the ability to process reject streams from multiple donor plants in the host plant. Cape Flats (CF) wastewater treatment works (WWTW) (Cape Town, South Africa) was used as a relevant test case since it is currently assessing to process sludge cake from three nearby facilities (Athlone, Mitchells Plain and Wildevoelvlei). A plant-wide model based on the Benchmark Simulation Model no 2 (BSM2) extended with phosphorus transformations was adapted to the CF design / operational conditions. Flow diagram and model parameters were adjusted to reproduce the influent, effluent and process characteristics. Historical data between January 2014 and December 2019 was used to compare full-scale measurements and predictions. Next, different process intensification / mitigation technologies were evaluated using multiple criteria. Simulation values for COD, TSS, VSS/TSS ratio, TN, TP, NH₄⁺/NH₃, H_xPO4^3-x, NO_x alkalinity and pH fall within the interquartile ranges of measured data. The effects of the 2017 severe drought on influent variations and biological phosphorus removal are successfully reproduced for the entire period with dynamic simulations. Indeed, 80% of all dynamically simulated values are included within the plant measurement uncertainty ranges. Sludge management analysis reveals that flow diagrams with thermal hydrolysis pre-treatment (THP) result in a better energy balance in spite of having higher heat demands. The flow diagram with THP is able to i) increase biodegradability/solubility, ii) handle higher sludge loads, iii) change methanogenic microbial population and iv) generate lower solids volumes to dispose by improving sludge dewaterability. The study also reveals the importance of including struvite precipitation and harvesting (SPH) technology, and the effect that pH in the AD and the use of chemicals (NaOH, MgO) may have on phosphorus recovery. Model-based results indicate that the current aerobic volume in the water line (if properly aerated) would be able to handle the returns from the sludge line and the contribution of a granular partial nitritation/Anammox (PN/ANX) reactor on the overall nitrogen removal would be marginal. However autotrophic N denitrification generates a much lower sludge production and therefore increases AD treatment capacity. The study shows for the very first time in Africa how the use of a (calibrated) plant-wide model could assist water utilities to decide between competing plant layouts when upgrading a WWTW.

Hindered and compression solid settling functions - Sensor data collection, practical model identification and validation

Secondary settling tanks (SSTs) are the most hydraulically sensitive unit operations in activated sludge water resource recovery facilities (WRRF). Mathematical models for predicting activated sludge solids settling velocity include parameters that show irreducible epistemic uncertainty. Therefore, reliable and periodic calibration of the settling velocity model is key for predicting activated sludge process capacity, thus averting possible failures under wet-weather flow- and filamentous bulking conditions. The two main knowledge gaps addressed here are: (1) Do constitutive functions for hindered and compression settling exist, for which all velocity parameters can be uniquely estimated? (2) What is the optimum sensor data requirement of developing reliable settling velocity functions? Innovative settling column sensor and full-scale data were used to identify and validate amended Vesilind function for hindered settling and a new exponential function for compression settling velocity using one-dimensional and computational fluid dynamics simulations. Results indicate practical model identifiability under well-settling and filamentous bulking conditions.

Predicting wastewater treatment plant performance during aeration demand shifting with a dual-layer reaction settling model

Demand response (DR) programmes encourage energy end users to adjust their consumption according to energy availability and price. Municipal wastewater treatment plants are suitable candidates for the application of such programmes. Demand shedding through aeration control, subject to maintaining the plant operational limits, could have a large impact on the plant DR potential. Decreasing the aeration intensity may promote the settling of the particulate components present in the reactor mixed liquor. The scope of this study is thus to develop a mathematical model to describe this phenomenon. For this purpose, Benchmark Simulation Model No.1 was extended by implementing a dual-layer settling model in one of the aerated tanks and combining it with biochemical reaction kinetic equations. The performance of this extended model was assessed in both steady-state and dynamic conditions, switching the aeration system off for 1 hour during each day of simulation. This model will have applications in the identification of potential benefits and issues related to DR events, as well as in the simulation of the plant operation where aerated tank settling is implemented.

Reliability Analysis of Activated Sludge Process by Means of Biokinetic Modelling and Simulation Results

Analysis of wastewater treatment plant reliability is a difficult process, therefore it is often limited to selected aspects, e.g., mechanical reliability of equipment or technological availability of the process. The research presents a method of combining the above mentioned aspects in order to determine the complex operational availability index (CAVO). A hypothetical technological system with activated sludge (AS) in a typical layout (denitrification-nitrification) was selected for the studies. A number of operational scenarios have been developed, taking into account the possible mechanical failures of system components. Computer simulations with the use of Activated Sludge Model No.1 (ASM1), performed for selected scenarios allowed the determination of a complex operational availability of the system. Obtained results confirm high reliability of AS system in terms of biochemical oxygen demand (BOD), chemical oxygen demand (COD) and total suspended solids (TSS) removal (CAVO > 0.96) and indicate the necessity of further research in order to determine representative value of reliability of total nitrogen removal (from the study, CAVO-Ntot < 0.4) and to evaluate other technological solutions in terms of their complex reliability.

Quantifying the sources of uncertainty when calculating the limiting flux in secondary settling tanks using iCFD

Solids-flux theory (SFT) and state-point analysis (SPA) are used for the design, operation and control of secondary settling tanks (SSTs). The objectives of this study were to assess uncertainties, propagating from flow and solids loading boundary conditions as well as compression settling behaviour to the calculation of the limiting flux (J_L) and the limiting solids concentration (X_L). The interpreted computational fluid dynamics (iCFD) simulation model was used to predict one-dimensional local concentrations and limiting solids fluxes as a function of loading and design boundary conditions. A two-level fractional factorial design of experiments was used to infer the relative significance of factors unaccounted for in conventional SPA. To move away from using semi-arbitrary safety factors, a systematic approach was proposed to calculate the maximum SST capacity by employing a factor of 23% and a regression meta-model to correct values of J_L and X_L, respectively - critical for abating hydraulic effects under wet-weather flow conditions.

Evaluation of anaerobic digestion post-treatment options using an integrated model-based approach

The objective of this paper is to present the main results of an engineering-research project dealing with model-based evaluation of waste streams treatment from a biotech company. This has been extensively done in domestic treatment systems, but is equally important, and with different challenges in industrial wastewater treatment. A new set of biological (activated sludge, anaerobic digestion), physicochemical (aqueous phase, precipitation, mass transfer) process models and model interfaces are required to describe removal of organics in an upflow anaerobic sludge blanket (UASB) reactor plus either traditional nitrification/denitrification (A₁) or partial nitritation (PN)/anammox (ANX) (A₂) processes. Model-based analysis shows that option A₁ requires a decrease in digestion energy recovery (E_recovery) in order to have enough organic substrate for subsequent post NO₃ reduction treatment (95 kWh.kg N^-1). In contrast, A₂ in an aerobic granular sludge reactor allows for higher UASB conversion since N removal is carried out autotrophically. The study also reveals that the addition of an aerated pre-treatment unit prior to the PN/ANX (A₂) reactor promotes COD and H₂S oxidation, CO₂ and CH₄ stripping, a pH increase (up to 8.5) and a reduction of the risk of intra-granular precipitation as well as sulfide inhibition. Simulations indicate clear differences regarding the microbial distribution/abundance within the biofilm in A₂ when comparing the two operational modes. Final results show the effects of different loading and operational conditions; dissolved oxygen (DO), Total Suspended Solids (TSS_op), energy recovery (E_recovery); on the overall process performance; N removal, aeration energy (E_aeration), net energy production (E_recovery); using response surfaces, highlighting the need of integrated approaches to avoid sub-optimal outcomes. The study shows the benefits of virtual plant simulation and demonstrates the potential of model-based evaluation when process engineers in industry have to decide between competing options.

Operation performance of an A/O process combined sewage sludge treatment and phosphorus recovery using human urine

A novel sewage sludge treatment process is developed in which sludge anaerobically phosphorus (P) released with the temperature control/ultrasonic treatment and recovery with human urine are incorporated to a conventional anaerobic/aerobic (A/O) process. The results showed that temperature affected the anaerobic P release and the maximum orthophosphate (PO₄ ^3-P) release rate was 21.68 mg PO₄ ^3-P/(g MLVSS^.h) at 20 °C. The optimal specific energy of ultrasonic treatment was 15,000 kJ/kg TS, at which the solubilization degree of soluble chemical oxygen demand (SCOD) was 37.93%, which verified that the anaerobic sludge flocs were broken and the organic matter was obviously released. Human urine and P-rich sludge stream could be verified as a feasible way of P recovery in the form of struvite. The output of P in the combined A/O treatment process consisted of three pathways (i.e., effluent wastewater, sewage sludge, and P recovery). The influent P could be recovered by 22.84% and about 1.48 g/d potential struvite could be recovered from the anaerobic sludge flow using 0.27 L/d-human urine. The mass balances of COD and nitrogen (N) indicated that the combined A/O process also improved the organic mineralization and the removal of N.

Modelling an industrial anaerobic granular reactor using a multi-scale approach

The objective of this paper is to show the results of an industrial project dealing with modelling of anaerobic digesters. A multi-scale mathematical approach is developed to describe reactor hydrodynamics, granule growth/distribution and microbial competition/inhibition for substrate/space within the biofilm. The main biochemical and physico-chemical processes in the model are based on the Anaerobic Digestion Model No 1 (ADM1) extended with the fate of phosphorus (P), sulfur (S) and ethanol (Et-OH). Wastewater dynamic conditions are reproduced and data frequency increased using the Benchmark Simulation Model No 2 (BSM2) influent generator. All models are tested using two plant data sets corresponding to different operational periods (#D1, #D2). Simulation results reveal that the proposed approach can satisfactorily describe the transformation of organics, nutrients and minerals, the production of methane, carbon dioxide and sulfide and the potential formation of precipitates within the bulk (average deviation between computer simulations and measurements for both #D1, #D2 is around 10%). Model predictions suggest a stratified structure within the granule which is the result of: 1) applied loading rates, 2) mass transfer limitations and 3) specific (bacterial) affinity for substrate. Hence, inerts (X_I) and methanogens (X_ac) are situated in the inner zone, and this fraction lowers as the radius increases favouring the presence of acidogens (X_su,X_aa, X_fa) and acetogens (X_c4,X_pro). Additional simulations show the effects on the overall process performance when operational (pH) and loading (S:COD) conditions are modified. Lastly, the effect of intra-granular precipitation on the overall organic/inorganic distribution is assessed at: 1) different times; and, 2) reactor heights. Finally, the possibilities and opportunities offered by the proposed approach for conducting engineering optimization projects are discussed.

Cost minimization in a full-scale conventional wastewater treatment plant: associated costs of biological energy consumption versus sludge production

Energy consumption and sludge production minimization represent rising challenges for wastewater treatment plants (WWTPs). The goal of this study is to investigate how energy is consumed throughout the whole plant and how operating conditions affect this energy demand. A WWTP based on the activated sludge process was selected as a case study. Simulations were performed using a pre-compiled model implemented in GPS-X simulation software. Model validation was carried out by comparing experimental and modeling data of the dynamic behavior of the mixed liquor suspended solids (MLSS) concentration and nitrogen compounds concentration, energy consumption for aeration, mixing and sludge treatment and annual sludge production over a three year exercise. In this plant, the energy required for bioreactor aeration was calculated at approximately 44% of the total energy demand. A cost optimization strategy was applied by varying the MLSS concentrations (from 1 to 8 gTSS/L) while recording energy consumption, sludge production and effluent quality. An increase of MLSS led to an increase of the oxygen requirement for biomass aeration, but it also reduced total sludge production. Results permit identification of a key MLSS concentration allowing identification of the best compromise between levels of treatment required, biological energy demand and sludge production while minimizing the overall costs.

Generalised approach to modelling a three-tiered microbial food-web

The complexity of the anaerobic digestion process has motivated the development of complex models, such as the widely used Anaerobic Digestion Model No. 1. However, this complexity makes it intractable to identify the stability profile coupled to the asymptotic behaviour of existing steady-states as a function of conventional chemostat operating parameters (substrate inflow concentration and dilution rate). In a previous study this model was simplified and reduced to its very backbone to describe a three-tiered chlorophenol mineralising food-web, with its stability analysed numerically using consensus values for the various biological parameters of the Monod growth functions. Steady-states where all organisms exist were always stable and non-oscillatory. Here we investigate a generalised form of this three-tiered food-web, whose kinetics do not rely on the specific kinetics of Monod form. The results are valid for a large class of growth kinetics as long as they keep the signs of their derivatives. We examine the existence and stability of the identified steady-states and find that, without a maintenance term, the stability of the system may be characterised analytically. These findings permit a better understanding of the operating region of the bifurcation diagram where all organisms exist, and its dependence on the biological parameters of the model. For the previously studied Monod kinetics, we identify four interesting cases that show this dependence of the operating diagram with respect to the biological parameters. When maintenance is included, it is necessary to perform numerical analysis. In both cases we verify the discovery of two important phenomena; i) the washout steady-state is always stable, and ii) a switch in dominance between two organisms competing for hydrogen results in the system becoming unstable and a loss in viability. We show that our approach results in the discovery of an unstable operating region in its positive steady-state, where all three organisms exist, a fact that has not been reported in a previous numerical study. This type of analysis can be used to determine critical behaviour in microbial communities in response to changing operating conditions.

Plant-wide modelling of phosphorus transformations in wastewater treatment systems: Impacts of control and operational strategies

The objective of this paper is to report the effects that control/operational strategies may have on plant-wide phosphorus (P) transformations in wastewater treatment plants (WWTP). The development of a new set of biological (activated sludge, anaerobic digestion), physico-chemical (aqueous phase, precipitation, mass transfer) process models and model interfaces (between water and sludge line) were required to describe the required tri-phasic (gas, liquid, solid) compound transformations and the close interlinks between the P and the sulfur (S) and iron (Fe) cycles. A modified version of the Benchmark Simulation Model No. 2 (BSM2) (open loop) is used as test platform upon which three different operational alternatives (A₁, A₂, A₃) are evaluated. Rigorous sensor and actuator models are also included in order to reproduce realistic control actions. Model-based analysis shows that the combination of an ammonium ( [Formula: see text] ) and total suspended solids (X_TSS) control strategy (A₁) better adapts the system to influent dynamics, improves phosphate [Formula: see text] accumulation by phosphorus accumulating organisms (X_PAO) (41%), increases nitrification/denitrification efficiency (18%) and reduces aeration energy (E_aeration) (21%). The addition of iron ( [Formula: see text] ) for chemical P removal (A₂) promotes the formation of ferric oxides (X_HFO-H, X_HFO-L), phosphate adsorption (X_HFO-H,P, X_HFO-L,P), co-precipitation (X_HFO-H,P,old, X_HFO-L,P,old) and consequently reduces the P levels in the effluent (from 2.8 to 0.9 g P.m^-3). This also has an impact on the sludge line, with hydrogen sulfide production ( [Formula: see text] ) reduced (36%) due to iron sulfide (X_FeS) precipitation. As a consequence, there is also a slightly higher energy production (E_production) from biogas. Lastly, the inclusion of a stripping and crystallization unit (A₃) for P recovery reduces the quantity of P in the anaerobic digester supernatant returning to the water line and allows potential struvite ( [Formula: see text] ) recovery ranging from 69 to 227 kg.day^-1 depending on: (1) airflow (Q_stripping); and, (2) magnesium ( [Formula: see text] ) addition. All the proposed alternatives are evaluated from an environmental and economical point of view using appropriate performance indices. Finally, some deficiencies and opportunities of the proposed approach when performing (plant-wide) wastewater treatment modelling/engineering projects are discussed.

Short-sludge age EBPR process - Microbial and biochemical process characterisation during reactor start-up and operation

The new paradigm for used water treatment suggests the use of short solid retention times (SRT) to minimize organic substrate mineralization and to maximize resource recovery. However, little is known about the microbes and the underlying biogeochemical mechanisms driving these short-SRT systems. In this paper, we report the start-up and operation of a short-SRT enhanced biological phosphorus removal (EBPR) system operated as a sequencing batch reactor (SBR) fed with preclarified municipal wastewater, which is supplemented with propionate. The microbial community was analysed via 16S rRNA amplicon sequencing. During start-up (SRT = 8 d), the EBPR was removing up to 99% of the influent phosphate and completely oxidized the incoming ammonia. Furthermore, the sludge showed excellent settling properties. However, once the SRT was shifted to 3.5 days nitrification was inhibited and bacteria of the Thiothrix taxon proliferated in the reactor, thereby leading to filamentous bulking (sludge volume index up to SVI = 1100 mL/g). Phosphorus removal deteriorated during this period, likely due to the out-competition of polyphosphate accumulating organisms (PAO) by sulphate reducing bacteria (SRB). Subsequently, SRB activity was suppressed by reducing the anaerobic SRT from 1.2 day to 0.68 day, with a consequent rapid SVI decrease to ∼200 ml/g. The short-SRT EBPR effectively removed phosphate and nitrification was mitigated at SRT = 3 days and oxygen levels ranging from 2 to 3 mg/L.

Modelling phosphorus (P), sulfur (S) and iron (Fe) interactions for dynamic simulations of anaerobic digestion processes

This paper proposes a series of extensions to functionally upgrade the IWA Anaerobic Digestion Model No. 1 (ADM1) to allow for plant-wide phosphorus (P) simulation. The close interplay between the P, sulfur (S) and iron (Fe) cycles requires a substantial (and unavoidable) increase in model complexity due to the involved three-phase physico-chemical and biological transformations. The ADM1 version, implemented in the plant-wide context provided by the Benchmark Simulation Model No. 2 (BSM2), is used as the basic platform (A0). Three different model extensions (A1, A2, A3) are implemented, simulated and evaluated. The first extension (A1) considers P transformations by accounting for the kinetic decay of polyphosphates (XPP) and potential uptake of volatile fatty acids (VFA) to produce polyhydroxyalkanoates (XPHA) by phosphorus accumulating organisms (XPAO). Two variant extensions (A2,1/A2,2) describe biological production of sulfides (SIS) by means of sulfate reducing bacteria (XSRB) utilising hydrogen only (autolithotrophically) or hydrogen plus organic acids (heterorganotrophically) as electron sources, respectively. These two approaches also consider a potential hydrogen sulfide ( [Formula: see text] inhibition effect and stripping to the gas phase ( [Formula: see text] ). The third extension (A3) accounts for chemical iron (III) ( [Formula: see text] ) reduction to iron (II) ( [Formula: see text] ) using hydrogen ( [Formula: see text] ) and sulfides (SIS) as electron donors. A set of pre/post interfaces between the Activated Sludge Model No. 2d (ASM2d) and ADM1 are furthermore proposed in order to allow for plant-wide (model-based) analysis and study of the interactions between the water and sludge lines. Simulation (A1 - A3) results show that the ratio between soluble/particulate P compounds strongly depends on the pH and cationic load, which determines the capacity to form (or not) precipitation products. Implementations A1 and A2,1/A2,2 lead to a reduction in the predicted methane/biogas production (and potential energy recovery) compared to reference ADM1 predictions (A0). This reduction is attributed to two factors: (1) loss of electron equivalents due to sulfate [Formula: see text] reduction by XSRB and storage of XPHA by XPAO; and, (2) decrease of acetoclastic and hydrogenotrophic methanogenesis due to [Formula: see text] inhibition. Model A3 shows the potential for iron to remove free SIS (and consequently inhibition) and instead promote iron sulfide (XFeS) precipitation. It also reduces the quantities of struvite ( [Formula: see text] ) and calcium phosphate ( [Formula: see text] ) that are formed due to its higher affinity for phosphate anions. This study provides a detailed analysis of the different model assumptions, the effect that operational/design conditions have on the model predictions and the practical implications of the proposed model extensions in view of plant-wide modelling/development of resource recovery strategies.

iCFD: Interpreted Computational Fluid Dynamics - Degeneration of CFD to one-dimensional advection-dispersion models using statistical experimental design - The secondary clarifier

The present study aims at using statistically designed computational fluid dynamics (CFD) simulations as numerical experiments for the identification of one-dimensional (1-D) advection-dispersion models - computationally light tools, used e.g., as sub-models in systems analysis. The objective is to develop a new 1-D framework, referred to as interpreted CFD (iCFD) models, in which statistical meta-models are used to calculate the pseudo-dispersion coefficient (D) as a function of design and flow boundary conditions. The method - presented in a straightforward and transparent way - is illustrated using the example of a circular secondary settling tank (SST). First, the significant design and flow factors are screened out by applying the statistical method of two-level fractional factorial design of experiments. Second, based on the number of significant factors identified through the factor screening study and system understanding, 50 different sets of design and flow conditions are selected using Latin Hypercube Sampling (LHS). The boundary condition sets are imposed on a 2-D axi-symmetrical CFD simulation model of the SST. In the framework, to degenerate the 2-D model structure, CFD model outputs are approximated by the 1-D model through the calibration of three different model structures for D. Correlation equations for the D parameter then are identified as a function of the selected design and flow boundary conditions (meta-models), and their accuracy is evaluated against D values estimated in each numerical experiment. The evaluation and validation of the iCFD model structure is carried out using scenario simulation results obtained with parameters sampled from the corners of the LHS experimental region. For the studied SST, additional iCFD model development was carried out in terms of (i) assessing different density current sub-models; (ii) implementation of a combined flocculation, hindered, transient and compression settling velocity function; and (iii) assessment of modelling the onset of transient and compression settling. Furthermore, the optimal level of model discretization both in 2-D and 1-D was undertaken. Results suggest that the iCFD model developed for the SST through the proposed methodology is able to predict solid distribution with high accuracy - taking a reasonable computational effort - when compared to multi-dimensional numerical experiments, under a wide range of flow and design conditions. iCFD tools could play a crucial role in reliably predicting systems' performance under normal and shock events.

Effects of ionic strength and ion pairing on (plant-wide) modelling of anaerobic digestion

Plant-wide models of wastewater treatment (such as the Benchmark Simulation Model No. 2 or BSM2) are gaining popularity for use in holistic virtual studies of treatment plant control and operations. The objective of this study is to show the influence of ionic strength (as activity corrections) and ion pairing on modelling of anaerobic digestion processes in such plant-wide models of wastewater treatment. Using the BSM2 as a case study with a number of model variants and cationic load scenarios, this paper presents the effects of an improved physico-chemical description on model predictions and overall plant performance indicators, namely effluent quality index (EQI) and operational cost index (OCI). The acid-base equilibria implemented in the Anaerobic Digestion Model No. 1 (ADM1) are modified to account for non-ideal aqueous-phase chemistry. The model corrects for ionic strength via the Davies approach to consider chemical activities instead of molar concentrations. A speciation sub-routine based on a multi-dimensional Newton-Raphson (NR) iteration method is developed to address algebraic interdependencies. The model also includes ion pairs that play an important role in wastewater treatment. The paper describes: 1) how the anaerobic digester performance is affected by physico-chemical corrections; 2) the effect on pH and the anaerobic digestion products (CO2, CH4 and H2); and, 3) how these variations are propagated from the sludge treatment to the water line. Results at high ionic strength demonstrate that corrections to account for non-ideal conditions lead to significant differences in predicted process performance (up to 18% for effluent quality and 7% for operational cost) but that for pH prediction, activity corrections are more important than ion pairing effects. Both are likely to be required when precipitation is to be modelled.

Biodegradability of wastewater and activated sludge organics in anaerobic digestion

The investigation provides experimental evidence that the unbiodegradable particulate organics fractions of primary sludge and waste activated sludge calculated from activated sludge models remain essentially unbiodegradable in anaerobic digestion. This was tested by feeding the waste activated sludge (WAS) from three different laboratory activated sludge (AS) systems to three separate anaerobic digesters (AD). Two of the AS systems were Modified Ludzack - Ettinger (MLE) nitrification-denitrification (ND) systems and the third was a membrane University of Cape Town (UCT) ND and enhanced biological P removal system. One of the MLE systems and the UCT system were fed the same real settled wastewater. The other MLE system was fed raw wastewater which was made by adding a measured constant flux (gCOD/d) of macerated primary sludge (PS) to the real settled wastewater. This PS was also fed to a fourth AD and a blend of PS and WAS from settled wastewater MLE system was fed to a fifth AD. The five ADs were each operated at five different sludge ages (10-60d). From the measured performance results of the AS systems, the unbiodegradable particulate organic (UPO) COD fractions of the raw and settled wastewaters, the PS and the WAS from the three AS systems were calculated with AS models. These AS model based UPO fractions of the PS and WAS were compared with the UPO fractions calculated from the performance results of the ADs fed these sludges. For the PS, the UPO fraction calculated from the AS and AD models matched closely, i.e. 0.30 and 0.31. Provided the UPO of heterotrophic (OHO, fE_OHO) and phosphorus accumulating (PAO, fE_PAO) biomass were accepted to be those associated with the death regeneration model of organism "decay", the UPO of the WAS calculated from the AS and AD models also matched well - if the steady state AS model fE_OHO = 0.20 and fE_PAO = 0.25 values were used, then the UPO fraction of the WAS calculated from the AS models deviated significantly from those calculated with the AD models. Therefore in plant wide wastewater treatment models the characterization of PS and WAS as defined by the AS models can be applied without modification in AD models. The observed rate limiting hydrolysis/acidogenesis rates of the sludges are listed.

Calibration and validation of a phenomenological influent pollutant disturbance scenario generator using full-scale data

The objective of this paper is to demonstrate the full-scale feasibility of the phenomenological dynamic influent pollutant disturbance scenario generator (DIPDSG) that was originally used to create the influent data of the International Water Association (IWA) Benchmark Simulation Model No. 2 (BSM2). In this study, the influent characteristics of two large Scandinavian treatment facilities are studied for a period of two years. A step-wise procedure based on adjusting the most sensitive parameters at different time scales is followed to calibrate/validate the DIPDSG model blocks for: 1) flow rate; 2) pollutants (carbon, nitrogen); 3) temperature; and, 4) transport. Simulation results show that the model successfully describes daily/weekly and seasonal variations and the effect of rainfall and snow melting on the influent flow rate, pollutant concentrations and temperature profiles. Furthermore, additional phenomena such as size and accumulation/flush of particulates of/in the upstream catchment and sewer system are incorporated in the simulated time series. Finally, this study is complemented with: 1) the generation of additional future scenarios showing the effects of different rainfall patterns (climate change) or influent biodegradability (process uncertainty) on the generated time series; 2) a demonstration of how to reduce the cost/workload of measuring campaigns by filling the gaps due to missing data in the influent profiles; and, 3) a critical discussion of the presented results balancing model structure/calibration procedure complexity and prediction capabilities.