Making waves: Power-to-X for the Water Resource Recovery Facilities of the future.

The wastewater industry and the energy system are undergoing significant transformations to address climate change and environmental pollution. Green hydrogen, which will be mainly obtained from renewable electricity water electrolysis (Power-to-Hydrogen, PtH), has been considered as an essential energy carrier to neutralize the fluctuations of renewable energy sources. PtH, or Power-to-X (PtX), has been allocated to multiple sectors, including industry, transport and power generation. However, considering its large potential for implementation in the wastewater sector, represented by Water Resource Recovery Facilities (WRRFs), the PtX concept has been largely overlooked in terms of planning and policymaking. This paper proposes a concept to implement PtX at WRRFs, where sourcing of water, utilization of the oxygen by-product, and PtX itself can be sustainable and diversified strategies. Potential value chains of PtX are presented and illustrated in the frame of a WWRF benchmark simulation model, highlighting the applications of oxygen from PtX through pure oxygen aeration and ozone disinfection. Opportunities and challenges are highlighted briefly, and so is the prospective outlook to the future. Ultimately, it is concluded that 'coupling PtX to WRRFs' is a promising solution, which will potentially bring sustainable opportunities for both WRRFs and the energy system. Apart from regulatory and economic challenges, the limitations in coupling PtX to WRRFs mainly come from energy efficiency concerns and the complexity of the integration of the water framework and the energy system.

Modelling the impacts of operational conditions on the performance of a full-scale membrane aerated biofilm reactor.

Membrane Aerated Biofilm Reactors (MABR) are gaining more and more acceptance in the plethora of wastewater process intensification technologies. Mathematical modelling has contributed to show their feasibility in terms of reduced energy consumption and footprint. Nevertheless, most simulation studies published until now are still focused on analyzing MABR as single units and not fully integrated within the flow diagram of the water treatment plant (WWTP). In this paper, the prediction capabilities of an integrated modelling approach is tested using full-scale data from Ejby Mølle WWTP+MABR site (Odense, Denmark). Mass balances, data reconciliation methods, process simulation and the different evaluation criteria were used to adjust influent, effluent and process indicators. Results show 10 % mismatch between flow, COD, N and P predictions and measurements in different plant locations. Using the adopted hydraulic retention time (HRT), nitrogen load (NL), membrane surface area (MA) and oxygen transfer rate (OTR), it was possible to predict nitrification rates (NR) within the interquartile range. This has been done under two different MABR operational conditions: with (#S2) and without (#S1) external aeration (EA) in the bulk liquid. The model provides additional process insights about biofilm structure, substrate gradients, weak acid base chemistry and precipitation potential. More specifically, simulations suggest the potential undesirable effects of sulfate (SRB) and iron reducing bacteria (IRB) on both microbial activity and composition of the biofilm. The latter may have a strong impact on ammonium (NHx), sulfate (SOx) and ferrous ion (Fe+2) conversion processes. The change of operational strategy in the scenario analysis highlights that the denitrifying activity of phosphorus accumulating organisms (PAOs) can enhance nutrient removal in MABR tanks. In addition, it was possible to assess the chance of success (in terms of energetic cost of nitrogen removal) of adding several MABR units in one tank of the WWTP under study before full-scale implementation.

Using plant data to estimate biodegradable COD fractions - case study kwaMashu WWTP.

A modelling study is under way in preparation for a planned upgrade of the capacity of the kwaMashu WWTP in eThekwini, South Africa, from 50 to 80 ML/d. When the configuration of an existing plant is to be changed, the most critical part of the model calibration is the influent wastewater fractionation. However, the constantly varying characteristics of wastewater make experimental determination of an adequately representative set of components difficult, time-consuming and expensive, which constitutes significant barriers to the adoption of modelling by many municipalities. Compliance and process monitoring generate large sets of influent measurements of chemical oxygen demand (COD), free and saline ammonia (FSA), total suspended solids (TSS), etc., but these are insufficient for modelling purposes. In particular, biodegradability is not routinely measured. However, since influent fractionation is designed to predict the fate of material in the wastewater treatment process, it should be possible to infer the fractionation from a combination of influent and plant measurements. This case study demonstrates the application of a pair of modelling tools, a probabilistic influent fractionator and a simplified steady­state plant­wide model, to estimate the influent fractionation, together with certain unmeasured or unreliable operational parameters.

Economic, technical, and environmental evaluation of retrofitting scenarios in a full-scale industrial wastewater treatment system.

The use of mathematical models is a well-established procedure in the field of (waste) water engineering to "virtually" evaluate the feasibility of novel process modifications. In this way, only options with the highest chance of success are further developed to be implemented at full-scale, while less interesting proposals can be disregarded at an early stage. Nevertheless, there is still lack of studies, where different plant-wide model predictions (effluent quality, process economics, and technical aspects) are comprehensibly verified in the field with full-scale data. In this work, a set of analysis/evaluation tools are used to assess alternative retrofitting options in the largest industrial wastewater treatment plant in Northern Europe. A mechanistic mathematical model is simulated to reproduce process behavior (deviation < 11%). Multiple criteria are defined and verified with plant data (deviation < 5%). The feasibility of three types of scenarios is tested: (1) stream refluxing, (2) change of operational conditions and (3) the implementation of new technologies. Experimental measurements and computer simulations show that the current plant´s main revenues are obtained from the electricity produced by the biogas engine (54%) and sales of the inactivated bio-solids for off-site biogas production (33%). The main expenditures are the discharge fee (39%), and transportation and handling of bio-solids (30%). Selective treatment of bio-solid streams strongly modifies the fate of COD and N compounds within the plant. In addition, it increases revenues (+3%), reduces cost (-9%) and liberates capacity in both activated sludge (+25%) and inactivation reactors (+50%). Better management of the buffer tank promotes heterotrophic denitrification instead of dissimilatory nitrate conversion to ammonia. In this way, 11% of the incoming nitrogen is removed within the anaerobic water line and does not overload the activated sludge reactors. Only a marginal increase in process performance is achieved when the anaerobic granular sludge reactor operates at full capacity. The latter reveals that influent biodegradability is the main limiting factor rather than volume. Usage of either NaOH or heat (instead of CaO) as inactivation agents allows anaerobic treatment of the reject water, which substantially benefits revenues derived from higher electricity recovery (+44%). However, there is a high toll paid on chemicals (+73%) or heat recovery (-19%) depending on the inactivation technology. In addition, partial nitration/Anammox and a better poly-aluminum chloride (PAC) dosage strategy is necessary to achieve acceptable (< 2%) N and P levels in the effluent. The scenarios are evaluated from a sustainability angle by using life cycle impact assessment (LCIA) in form of damage stressors grouped into three categories: human health, ecosystems quality, and resource scarcity. The presented decision support tool has been used by the biotech company involved in the study to support decision-making on how to handle future expansions.

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.

Plant-wide assessment of alternative activated sludge configurations for biological nutrient removal under uncertain influent characteristics.

This study presents an extensive plant-wide model-based assessment of four alternative activated sludge (AS) configurations for biological nitrogen (N) and phosphorus (P) removal under uncertain influent loads and characteristics. Zeekoegat wastewater treatment plant (WWTP) in South Africa was chosen as case study due to its flexible design that enables operation in four different AS configurations: 3-stage Bardenpho (A2O), University of Cape Town (UCT), UCT modified (UCTM), and Johannesburg (JHB). A metamodeling based global sensitivity analysis was performed on a steady-state plant-wide simulation model using Activated Sludge Model No. 2d with the latest extension of physico-chemical processes describing the plant-wide P transformations. The simulation results showed that the predictions of effluent chemical oxygen demand (COD), N and P using the proposed approach fall within the interquartile range of measured data. The study also revealed that process configuration can affect: 1) how influent uncertainty is reflected in model predictions for effluent quality and cost related performances, and 2) the parameter rankings based on variance decomposition, particularly for effluent phosphate, sludge disposal and methane production. The results identified UCT and UCTM as more robust configurations for P removal (less propagated uncertainty and less sensitivity to N load) in the expense of incomplete denitrification. Moreover, based on the results of Monte-Carlo based scenario analysis, the balanced SRT for N and P removal is more sensitive to influent load variation/uncertainty for the A2O and JHB configurations. This gives a more operational flexibility to UCT and UCTM, where a narrow SRT range can ensure both N and P removal.

Microbial biofilms in biorefinery - Towards a sustainable production of low-value bulk chemicals and fuels.

Harnessing the potential of biocatalytic conversion of renewable biomass into value-added products is still hampered by unfavorable process economics. This has promoted the use of biofilms as an alternative to overcome the limitations of traditional planktonic systems. In this paper, the benefits and challenges of biofilm fermentations are reviewed with a focus on the production of low-value bulk chemicals and fuels from waste biomass. Our study demonstrates that biofilm fermentations can potentially improve productivities and product yields by increasing biomass retention and allowing for continuous operation at high dilution rates. Furthermore, we show that biofilms can tolerate hazardous environments, which improve the conversion of crude biomass under substrate and product inhibitory conditions. Additionally, we present examples for the improved conversion of pure and crude substrates into bulk chemicals by mixed microbial biofilms, which can benefit from microenvironments in biofilms for synergistic multi-species reactions, and improved resistance to contaminants. Finally, we suggest the use of mathematical models as useful tools to supplement experimental insights related to the effects of physico-chemical and biological phenomena on the process. Major challenges for biofilm fermentations arise from inconsistent fermentation performance, slow reactor start-up, biofilm carrier costs and carrier clogging, insufficient biofilm monitoring and process control, challenges in reactor sterilization and scale-up, and issues in recovering dilute products. The key to a successful commercialization of the technology is likely going to be an interdisciplinary approach. Crucial research areas might include genetic engineering combined with the development of specialized biofilm reactors, biofilm carrier development, in-situ biofilm monitoring, model-based process control, mixed microbial biofilm technology, development of suitable biofilm reactor scale-up criteria, and in-situ product recovery.

Assessment of alkaline stabilization processes in industrial waste streams using a model-based approach.

Chemical conditioning prior to disposal is a common practice in biotech companies to stabilize the biological waste generated during production. Nevertheless, the state of the art models used to analyze management strategies in water treatment systems (WTS) do not include the effect of high alkaline conditions during bio-solids processing. In this paper, the prediction capabilities of a novel model-based approach describing the effect of quicklime addition (CaO) on the waste streams of an industrial WTS is assessed. Two measuring campaigns were carried out taking samples of TSS, VSS and total/soluble COD, N, P, S and multiple metals before and after chemical stabilization, and dewatering under and overflow. Mass balances were set up and Sankey diagrams were generated to represent the occurrence, transformation and fate of the major compounds within the studied facility. A simulation model was used to predict plant at different locations. Next, a scenario analysis was carried out in order to assess potential alternatives to the current operational practice. The resulting mass balances show a mismatch between the system's input and output up to 17%. It was also possible to identify different types of compound-behavior depending on the effect that high pH induced on the soluble and particulate fractions: hydrolysis, precipitation and unaltered. Model predictions and measurements differed 9.6% (steady state) and 12.4% (dynamic state) respectively. Finally, in the scenario analysis, the model suggested that the change from quicklime to sodium hydroxide (NaOH) would increase the quantity of organics in the dewatered cake (+23%), but with a considerable increase in chemical consumption (+50%). The selective stabilization of the incoming streams has the lowest use of chemicals (-30%) and reduces the load of CODsol (-13%) and TNsol (-14%) recirculated to the water line of the WWTP.

Long-term operation assessment of a full-scale membrane-aerated biofilm reactor under Nordic conditions.

Membrane-aerated biofilm reactor (MABR) technology is an exciting alternative to conventional activated sludge, with promising results in bench and pilot-scale systems. Nevertheless, there is still a lack of long-term and full-scale data under different operational conditions. This study aims to report the performance of a full-scale hybrid MABR located in the North of Europe. Influent, effluent, and exhaust data were collected for 1 year (September 2019 to September 2020) using online sensors/gas-analyzers and off-line laboratory analysis. Next, oxygen transfer rate (OTR), oxygen transfer efficiency (OTE), and nitrification rates (NR) were quantified as process indicators. Finally, multivariate methods were used to find patterns among monitored variables. Observations revealed that lower airflows achieved higher OTE at the same values of OTR and OTR was strongly correlated to ammonia/um concentration in the MABR tank (NHx,eff). The dynamics between oxygen concentration in the exhaust (O2,exh) and NHx,eff indicated that a nitrifying biofilm was established within 3 weeks. Average NR were calculated using four different methods and ranged between 1 and 2 g N m-2d-1. Principal component analysis (PCA) explained 81.4% of the sample variance with the first three components and cluster analysis (CA) divided the yearly data into five distinctive periods. Hence, it was possible to identify typical Nordic episodes with high frequency of heavy rain, low temperature, and high variations in pollution load. The study concludes that nitrification capacity obtained with MABR is robust during cold weather conditions, and its volumetric value is comparable to other well-established biofilm-based technologies. Moreover, the aeration efficiency (AE) obtained in this study, 5.8 kg O2 kW h-1, would suppose an average reduction in energy consumption of 55% compared to fine pore diffused aeration and 74% to the existing surface aeration at the facility.

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, HxPO43-x, NOx 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.

Incremental design of water symbiosis networks with prior knowledge: The case of an industrial park in Kenya.

Industrial parks have a high potential for recycling and reusing resources such as water across companies by creating symbiosis networks. In this study, we introduce a mathematical optimization framework for the design of water network integration in industrial parks formulated as a large-scale standard mixed-integer non-linear programming (MINLP) problem. The novelty of our approach relies on i) developing a multi-level incremental optimization framework for water network synthesis, ii) including prior knowledge of water demand growth and projected water scarcity to evaluate the significance of water-saving solutions, iii) incorporating a comprehensive formulation of the water network synthesis problem including multiple pollutants and different treatment units and iv) performing a multi-objective optimization of the network including freshwater savings and relative cost of the network. The significance of the proposed optimization framework is illustrated by applying it to an existing industrial park in a water-scarce region in Kenya. Firstly, we illustrated the benefits of including prior knowledge to prevent an over-design of the network at the early stages. In the case study, we achieved a more flexible and expandable water network with 36% lower unit cost at the early stage and 15% lower unit cost at later stages for overall maximum freshwater savings of 25%. Secondly, multi-objective analysis suggests an optimum freshwater savings of 14% to reduce the unit cost of the network by half. Moreover, the significance of symbiosis networks is highlighted by showing that intra-company connections can only achieve a maximum freshwater savings of 17% with significantly higher unit cost (+45%). Finally, we showed that the values of symbiosis connectivity index in the Pareto front correspond to higher freshwater savings, indicating the significant role of the symbiosis network in the industrial park under study. This is the first study, where all the above elements have been taken into account simultaneously for the design of a water reuse network.

Monitoring and modelling of influent patterns, phase distribution and removal of 20 elements in two primary wastewater treatment plants in Norway.

Many small- or medium-sized communities in Northern Europe employ only primary wastewater treatment plants (WWTPs) and effluent discharges can be a relevant source of pollution. The current study combines monitoring and modelling approaches to investigate concentrations, influent patterns, size distribution and removal of 20 elements for the two primary WWTPs (Ladehammeren, LARA; Høvringen, HØRA) serving Trondheim, the third largest city in Norway. Element concentrations were determined in raw influent wastewater, effluents and biosolids, and diurnal inflow patterns were assessed. The elemental distribution in particulate, colloidal and dissolved fractions of untreated wastewater was characterized using filtration separation and electron microscopy. An influent generator model and multivariate statistical analyses were used to determine release patterns and to predict the (co-)occurrence of selected elements. Raw influent wastewater concentrations for most elements were similar in the two WWTPs, with only Ca, Mn, Fe, Co and Ba being significantly higher (p < 0.05) in HØRA (which receives more household and hospital discharges). Removal efficiencies varied between elements, but in most cases reflected their association with particulates. Nanosized particles of several elements were detected, with Cu/Zn being most common. Measured concentrations of most elements followed typical diurnal wastewater discharge patterns and enrichment factors calculated for biosolids confirmed the importance of anthropogenic sources for P, Cu, Zn, Cd, As, Cr, Ni, Pb, V, Co and Fe. Elemental concentrations generally correlated well with total suspended solid (TSS) concentrations at HØRA, while this was less pronounced in LARA (possibly due to higher industrial contributions). In one of its first applications for WWTP influent pattern examination, principal component analysis was found to be instrumental for source identification of target elements, showing significant differences between LARA and HØRA influents. The combined experimental, statistical and modelling approaches used herein allowed for improved understanding of element sources, patterns of discharge and fate in primary WWTPs.

Model-based analysis and optimization of a full-scale industrial high-rate anaerobic bioreactor.

The objective of this paper is to present the model-based optimization results of an anaerobic granular sludge internal circulation reactor. The International Water Association Anaerobic Digestion Model No. 1 extended with phosphorus (P), sulfur (S), and ethanol is used to describe the main biological and physico-chemical processes. The high-rate conditions within the reactor are simulated using a flow + reactor model comprised of a series of continuous stirred tank reactors followed by an ideal total suspended solids separation unit. Following parameter estimation by least squares on the measured data, the model had a relative mean error of 13 and 15% for data set #1 and data set #2, respectively. Response surfaces show that the reactor performance index (a metric combining energy recovery in the form of heat and electricity, as well as chemicals needed for pH control) could be improved by 45% when reactor pH is reduced down to 6.8. Model-based results reveal that influent S does not impose sufficient negative impacts on energy recovery (+5.7%, in MWh/day,+0.20 M€/year when influent S is removed) to warrant the cost of its removal (3.58 M€/year). In fact, the process could handle even higher S loads (ensuring the same degree of conversion) as long as the pH is maintained above 6.8. Nevertheless, a higher S load substantially increases the amount of added NaOH to maintain the desired operational pH (>25%) due to the acidic behavior of HS - . CO 2 stripping decreases the buffer capacity of the system and hence use of chemicals for pH control. Finally, the paper discusses the possibilities and limitations of the proposed approach, and how the results of this study will be put into practice.

Occurrence, characterisation and fate of (nano)particulate Ti and Ag in two Norwegian wastewater treatment plants.

Due to their widespread application in consumer products, elemental titanium (e.g., titanium dioxide, TiO2) and silver (Ag), also in nanoparticulate form, are increasingly released from households and industrial facilities to urban wastewater treatment plants (WWTPs). A seven-day sampling campaign was conducted in two full-scale WWTPs in Trondheim (Norway) employing only primary treatment. We assessed the occurrence and elimination of Ti and Ag, and conducted size-based fractionation using sequential filtration of influent samples to separate particulate, colloidal and dissolved fractions. Eight-hour composite influent samples were collected to assess diurnal variations in total Ti and Ag influx. Measured influent Ti concentrations (up to 290 µg L-1) were significantly higher than Ag (<0.15-2.1 µg L-1), being mostly associated with suspended solids (>0.7 µm). Removal efficiencies ≥70% were observed for both elements, requiring for one WWTP to account for the high Ti content (∼2 g L-1) in the flocculant. Nano- and micron-sized Ti particles were observed with scanning transmission electron microscopy (STEM) in influent, effluent and biosolids, while Ag nanoparticles were detected in biosolids only. Diurnal profiles of influent Ti were correlated to flow and pollutant concentration patterns (especially total suspended solids), with peaks during the morning and/or evening and minima at night, indicating household discharges as predominant source. Irregular profiles were exhibited by influent Ag, with periodic concentration spikes suggesting short-term discharges from one or few point sources (e.g., industry). Influent Ti and Ag dynamics were reproduced using a disturbance scenario generator model, and we estimated per capita loads of Ti (42-45 mg cap-1 d-1) and Ag (0.11 mg cap-1 d-1) from households as well as additional Ag load (14-22 g d-1) from point discharge. This is the first study to experimentally and mathematically describe short-term release dynamics and dry-weather sources of emissions of Ti and Ag in municipal WWTPs and receiving environments.

Validation of a plant-wide phosphorus modelling approach with minerals precipitation in a full-scale WWTP.

The focus of modelling in wastewater treatment is shifting from single unit to plant-wide scale. Plant-wide modelling approaches provide opportunities to study the dynamics and interactions of different transformations in water and sludge streams. Towards developing more general and robust simulation tools applicable to a broad range of wastewater engineering problems, this paper evaluates a plant-wide model built with sub-models from the Benchmark Simulation Model No. 2-P (BSM2-P) with an improved/expanded physico-chemical framework (PCF). The PCF includes a simple and validated equilibrium approach describing ion speciation and ion pairing with kinetic multiple minerals precipitation. Model performance is evaluated against data sets from a full-scale wastewater treatment plant, assessing capability to describe water and sludge lines across the treatment process under steady-state operation. With default rate kinetic and stoichiometric parameters, a good general agreement is observed between the full-scale datasets and the simulated results under steady-state conditions. Simulation results show differences between measured and modelled phosphorus as little as 4-15% (relative) throughout the entire plant. Dynamic influent profiles were generated using a calibrated influent generator and were used to study the effect of long-term influent dynamics on plant performance. Model-based analysis shows that minerals precipitation strongly influences composition in the anaerobic digesters, but also impacts on nutrient loading across the entire plant. A forecasted implementation of nutrient recovery by struvite crystallization (model scenario only), reduced the phosphorus content in the treatment plant influent (via centrate recycling) considerably and thus decreased phosphorus in the treated outflow by up to 43%. Overall, the evaluated plant-wide model is able to jointly describe the physico-chemical and biological processes, and is advocated for future use as a tool for design, performance evaluation and optimization of whole wastewater treatment plants.

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.

A systematic study of multiple minerals precipitation modelling in wastewater treatment.

Mineral solids precipitation is important in wastewater treatment. However approaches to minerals precipitation modelling are varied, often empirical, and mostly focused on single precipitate classes. A common approach, applicable to multi-species precipitates, is needed to integrate into existing wastewater treatment models. The present study systematically tested a semi-mechanistic modelling approach, using various experimental platforms with multiple minerals precipitation. Experiments included dynamic titration with addition of sodium hydroxide to synthetic wastewater, and aeration to progressively increase pH and induce precipitation in real piggery digestate and sewage sludge digestate. The model approach consisted of an equilibrium part for aqueous phase reactions and a kinetic part for minerals precipitation. The model was fitted to dissolved calcium, magnesium, total inorganic carbon and phosphate. Results indicated that precipitation was dominated by the mineral struvite, forming together with varied and minor amounts of calcium phosphate and calcium carbonate. The model approach was noted to have the advantage of requiring a minimal number of fitted parameters, so the model was readily identifiable. Kinetic rate coefficients, which were statistically fitted, were generally in the range 0.35-11.6 h(-1) with confidence intervals of 10-80% relative. Confidence regions for the kinetic rate coefficients were often asymmetric with model-data residuals increasing more gradually with larger coefficient values. This suggests that a large kinetic coefficient could be used when actual measured data is lacking for a particular precipitate-matrix combination. Correlation between the kinetic rate coefficients of different minerals was low, indicating that parameter values for individual minerals could be independently fitted (keeping all other model parameters constant). Implementation was therefore relatively flexible, and would be readily expandable to include other minerals.

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).

Effects of influent fractionation, kinetics, stoichiometry and mass transfer on CH4, H2 and CO2 production for (plant-wide) modeling of anaerobic digesters.

This paper examines the importance of influent fractionation, kinetic, stoichiometric and mass transfer parameter uncertainties when modeling biogas production in wastewater treatment plants. The anaerobic digestion model no. 1 implemented in the plant-wide context provided by the benchmark simulation model no. 2 is used to quantify the generation of CH4, H2and CO2. A comprehensive global sensitivity analysis based on (i) standardized regression coefficients (SRC) and (ii) Morris' screening's (MS's) elementary effects reveals the set of parameters that influence the biogas production uncertainty the most. This analysis is repeated for (i) different temperature regimes and (ii) different solids retention times (SRTs) in the anaerobic digester. Results show that both SRC and MS are good measures of sensitivity unless the anaerobic digester is operating at low SRT and mesophilic conditions. In the latter situation, and due to the intrinsic nonlinearities of the system, SRC fails in decomposing the variance of the model predictions (R² < 0.7) making MS a more reliable method. At high SRT, influent fractionations are the most influential parameters for predictions of CH4and CO2emissions. Nevertheless, when the anaerobic digester volume is decreased (for the same load), the role of acetate degraders gains more importance under mesophilic conditions, while lipids and fatty acid metabolism is more influential under thermophilic conditions. The paper ends with a critical discussion of the results and their implications during model calibration and validation exercises.

A generalised chemical precipitation modelling approach in wastewater treatment applied to calcite.

Process simulation models used across the wastewater industry have inherent limitations due to over-simplistic descriptions of important physico­chemical reactions, especially for mineral solids precipitation. As part of the efforts towards a larger Generalized Physicochemical Modelling Framework, the present study aims to identify a broadly applicable precipitation modelling approach. The study uses two experimental platforms applied to calcite precipitating from synthetic aqueous solutions to identify and validate the model approach. Firstly, dynamic pH titration tests are performed to define the baseline model approach. Constant Composition Method (CCM) experiments are then used to examine influence of environmental factors on the baseline approach. Results show that the baseline model should include precipitation kinetics (not be quasi-equilibrium), should include a 1st order effect of the mineral particulate state (Xcryst) and, for calcite, have a 2nd order dependency (exponent n = 2.05 ± 0.29) on thermodynamic supersaturation (σ). Parameter analysis indicated that the model was more tolerant to a fast kinetic coefficient (kcryst) and so, in general, it is recommended that a large kcryst value be nominally selected where insufficient process data is available. Zero seed (self nucleating) conditions were effectively represented by including arbitrarily small amounts of mineral phase in the initial conditions. Both of these aspects are important for wastewater modelling, where knowledge of kinetic coefficients is usually not available, and it is typically uncertain which precipitates are actually present. The CCM experiments confirmed the baseline model, particularly the dependency on supersaturation. Temperature was also identified as an influential factor that should be corrected for via an Arrhenius-style correction of kcryst. The influence of magnesium (a common and representative added impurity) on kcryst was found to be significant but was considered an optional correction because of a lesser influence as compared to that of temperature. Other variables such as ionic strength and pH were adequately captured by the quasi-equilibrium description of the aqueous-phase and no further kinetic corrections were required. The baseline model is readily expandable to include other precipitation reactions. For simple representations, large values for kcryst with n = 2 (or n = 2 or 3 for other minerals, as appropriate) should be selected without corrections to kcryst. Where accuracy is required (e.g., in mechanistic studies), machine estimation of kcryst should be performed with robust process data and kcryst should at least be corrected for temperature.