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.

Raman spectroscopy and one-dimensional convolutional neural network modeling as a real-time monitoring tool for in vitro transaminase-catalyzed synthesis of a pharmaceutically relevant amine precursor.

Raman spectroscopy has been used to measure the concentration of a pharmaceutically relevant model amine intermediate for positive allosteric modulators of nicotinic acetylcholine receptor in a ω-transaminase-catalyzed conversion. A model based on a one-dimensional convolutional neural network was developed to translate raw data augmented Raman spectra directly into substrate concentrations, with which the conversion from ketone to amine by ω-transaminase could be determined over time. The model showed very good predictive capabilities, with R2 values higher than 0.99 for the spectra included in the modeling and 0.964 for an independent dataset. However, the model could not extrapolate outside the concentrations specified by the model. The presented work shows the potential of Raman spectroscopy as a real-time monitoring tool for biocatalytic reactions.

Handheld FTIR outperforms total organic carbon swab in pharmaceutical cleaning validation.

Cleaning Validation is a crucial process in pharmaceutical manufacturing, as it verifies that cross-contamination levels are below acceptable limits. The use of Mid-Infrared (IR) spectroscopy has long been proposed as a rapid method enabling real-time release, but only with the recent emergence of a handheld Fourier-Transform IR (FTIR) does a feasible solution exist for practical implementation in pharmaceutical manufacturing plants. This paper address the model development challenges for multi-product plants without complete traceability of production equipment and produced product. This is done by developing a partial least squares discriminant analysis model determining if the sample is clean or not clean compared to a residual acceptance limit, based on total organic carbon (TOC) measurements. The model is built and tested on artificial samples printed with a chemical printer for multiple products with different spectral peaks based on 91 samples in the calibration set and tested on 30 samples in the validation set. Furthermore, the model also incorporates spectra from surfaces with different surface roughness. The evaluation of the model is based on sensitivity, specificity and class error. The model outperforms or performs equally well as TOC swab with sampling error, dependent on the sampling error distribution for the TOC swab.

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.

Data-based dynamic compartment model: Modeling of E. coli fed-batch fermentation in a 600 m3 bubble column.

Mathematical modeling is a powerful and inexpensive approach to provide a quantitative basis for improvements that minimize the negative effects of bioreactor heterogeneity. For a model to accurately represent a heterogeneous system, a flow model that describes how mass is channeled between different zones of the bioreactor volume is necessary. In this study, a previously developed compartment model approach based on data from flow-following sensor devices was further developed to account for dynamic changes in volume and flow rates and thus enabling simulation of the widely used fed-batch process. The application of the dynamic compartment model was demonstrated in a study of an industrial fermentation process in a 600 m3 bubble column bioreactor. The flow model was used to evaluate the mixing performance by means of tracer simulations and was coupled with reaction kinetics to simulate concentration gradients in the process. The simulations showed that despite the presence of long mixing times and significant substrate gradients early in the process, improving the heterogeneity did not lead to overall improvements in the process. Improvements could, however, be achieved by modifying the dextrose feeding profile.

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.

Digital models in biotechnology: Towards multi-scale integration and implementation.

Industrial biotechnology encompasses a large area of multi-scale and multi-disciplinary research activities. With the recent megatrend of digitalization sweeping across all industries, there is an increased focus in the biotechnology industry on developing, integrating and applying digital models to improve all aspects of industrial biotechnology. Given the rapid development of this field, we systematically classify the state-of-art modelling concepts applied at different scales in industrial biotechnology and critically discuss their current usage, advantages and limitations. Further, we critically analyzed current strategies to couple cell models with computational fluid dynamics to study the performance of industrial microorganisms in large-scale bioprocesses, which is of crucial importance for the bio-based production industries. One of the most challenging aspects in this context is gathering intracellular data under industrially relevant conditions. Towards comprehensive models, we discuss how different scale-down concepts combined with appropriate analytical tools can capture intracellular states of single cells. We finally illustrated how the efforts could be used to develop digitals models suitable for both cell factory design and process optimization at industrial scales in the future.

Sampling Error of TOC swab in Pharmaceutical Cleaning Verification.

Cleaning verification is a critical process for patient safety in pharmaceutical manufacturing in order to keep cross-contamination below acceptable limits. A common cleaning verification method is the total organic carbon (TOC) swab. Others have studied the variances of different factors on the TOC swab in order to establish the best swab method. This paper attempts to quantify the sampling error of the TOC swab in the actual sampling situation using simulation. The study investigates the variability on the drug product recovery due to different analysts, concentration, steel finish and position, as well as the estimation of the given swab area. The results demonstrate that the sampling error leads to a large variation in TOC results. For areas estimated in the laboratory, it leads to an increase in limit of detection, LOD, with 60%, while for areas estimated in a tank, the LOD cannot be determined due to the large heteroscedasticity. Thus, this paper is also to be considered as an invitation to discuss and further investigate the TOC sampling error in the pharmaceutical industry.

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.

Soft-sensors application for automated feeding control in high-throughput mammalian cell cultures.

The ever-increasing demand for biopharmaceuticals has created the need for improving the overall productivity of culture processes. One such operational concept that is considered is fed-batch operations as opposed to batch operations. However, optimal fed-batch operations require complete knowledge of the cell culture to optimize the culture conditions and the nutrients feeding. For example, when using high-throughput small-scale bioreactors to test multiple clones that do not behave the same, depletion or overfeeding of some key components can occur if the feeding strategy is not individually optimized. Over the recent years, various solutions for real-time measuring of the main cell culture metabolites have been proposed. Still, the complexity in the implementation of these techniques has limited their use. Soft-sensors present an opportunity to overcome these limitations by indirectly estimating these variables in real-time. This manuscript details the development of a new soft-sensor-based fed-batch strategy to maintain substrate concentration (glucose and glutamine) at optimal levels in small-scale multiparallel Chinese Hamster Ovary Cells cultures. Two alternatives to the standard feeding strategy were tested: an OUR soft-sensor-based strategy for glucose and glutamine (Strategy 1) and a dual OUR for glutamine and CO2 /alkali addition for glucose soft-sensor strategy (Strategy 2). The results demonstrated the applicability of the OUR soft-sensor-based strategy to optimize glucose and glutamine feedings, which yielded a 21% increase in final viable cell density (VCD) and a 31% in erythropoietin titer compared with the reference one. However, CO2 /alkali addition soft-sensor suffered from insufficient data to relate alkali addition with glucose consumption. As a result, the culture was overfed with glucose resulting in a 4% increase on final VCD, but a 9% decrease in final titer compared with the Reference Strategy.

Exceptionally rich keratinolytic enzyme profile found in the rare actinomycetes Amycolatopsis keratiniphila D2T.

The non-spore forming Gram-positive actinomycetes Amycolatopsis keratiniphila subsp. keratiniphila D2T (DSM 44,409) has a high potential for keratin valorization as demonstrated by a novel biotechnological microbial conversion process consisting of a bacterial growth phase and a keratinolytic phase, respectively. Compared to the most gifted keratinolytic Bacillus species, a very large number of 621 putative proteases are encoded by the genome of Amycolatopsis keratiniphila subsp. keratiniphila D2T, as predicted by using Peptide Pattern Recognition (PPR) analysis. Proteome analysis by using LC-MS/MS on aliquots of the supernatant of A. keratiniphila subsp. keratiniphila D2T culture on slaughterhouse pig bristle meal, removed at 24, 48, 96 and 120 h of growth, identified 43 proteases. This was supplemented by proteome analysis of specific fractions after enrichment of the supernatant by anion exchange chromatography leading to identification of 50 proteases. Overall 57 different proteases were identified corresponding to 30% of the 186 proteins identified from the culture supernatant and distributed as 17 metalloproteases from 11 families, including an M36 protease, 38 serine proteases from 4 families, and 13 proteolytic enzymes from other families. Notably, M36 keratinolytic proteases are prominent in fungi, but seem not to have been discovered in bacteria previously. Two S01 family peptidases, named T- and C-like proteases, prominent in the culture supernatant, were purified and shown to possess a high azo-keratin/azo-casein hydrolytic activity ratio. The C-like protease revealed excellent thermostability, giving promise for successful applications in biorefinery processes. Notably, the bacterium seems not to secrete enzymes for cleavage of disulfides in the keratinous substrates. KEY POINTS: • A. keratiniphila subsp. keratiniphila D2T is predicted to encode 621 proteases. • This actinomycete efficiently converts bristle meal to a protein hydrolysate. • Proteome analysis identified 57 proteases in its secretome.

Particle-Scale Modeling to Understand Liquid Distribution in Twin-Screw Wet Granulation.

Experimental characterization of solid-liquid mixing for a high shear wet granulation process in a twin-screw granulator (TSG) is very challenging. This is due to the opacity of the multiphase system and high-speed processing. In this study, discrete element method (DEM) based simulations are performed for a short quasi-two-dimensional simulation domain, incorporating models for liquid bridge formation, rupture, and the effect of the bridges on inter-particular forces. Based on the knowledge gained from these simulations, the kneading section of a twin-screw wet granulation process was simulated. The time evolution of particle flow and liquid distribution between particles, leading to the formation of agglomerates, was analyzed. The study showed that agglomeration is a rather delayed process that takes place once the free liquid on the particle surface is well distributed.

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.

Mechanisms, status, and challenges of thermal hydrolysis and advanced thermal hydrolysis processes in sewage sludge treatment.

Sewage sludge management has garnered interest in both academia and industry due to the challenges of overpopulation and its potential as a bioenergy source. Thermal hydrolysis is a promising technology for sludge pre-treatment prior to anaerobic digestion to enhance biogas production. However, the technology is facing two main problems; the dark colour of sludge can affect UV disinfection and the formation of methanogenesis inhibitors such as free ammonia and refractory compounds have a significant impact on methane production in anaerobic digestion processes. Advanced thermal hydrolysis, which is an oxidative thermal hydrolysis process, has been introduced to overcome these challenges. This study provides a comprehensive review of the mechanisms and reactions which occur during the hydrothermal hydrolysis and advanced thermal hydrolysis processes. Technical and implementation challenges of both technologies are discussed. Additionally, the prospects of the technologies are assessed through their technology readiness levels. An assessment of the relevant literature is also provided to illuminate the aspects in which research gaps exist and areas where additional studies could be performed.

Analysis of the response of the cell membrane of Saccharomyces cerevisiae during the detoxification of common lignocellulosic inhibitors.

Gaining an in-depth understanding of the response of Saccharomyces cerevisiae to the different inhibitors generated during the pretreatment of lignocellulosic material is driving the development of new strains with higher inhibitor tolerances. The objective of this study is to assess, using flow cytometry, how three common inhibitors (vanillin, furfural, and acetic acid) affect the membrane potential, the membrane permeability and the concentration of reactive oxygen species (ROS) during the different fermentations. The membrane potential decreased during the detoxification phase and reflected on the different mechanisms of the toxicity of the inhibitors. While vanillin and furfural caused a metabolic inhibition and a gradual depolarization, acetic acid toxicity was related to fast acidification of the cytosol, causing an immediate depolarization. In the absence of acetic acid, ethanol increased membrane permeability, indicating a possible acquired tolerance to ethanol due to an adaptive response to acetic acid. The intracellular ROS concentration also increased in the presence of the inhibitors, indicating oxidative stress. Measuring these features with flow cytometry allows a real-time assessment of the stress of a cell culture, which can be used in the development of new yeast strains and to design new propagation strategies to pre-adapt the cell cultures to the inhibitors.

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.

Transforming data to information: A parallel hybrid model for real-time state estimation in lignocellulosic ethanol fermentation.

Operating lignocellulosic fermentation processes to produce fuels and chemicals is challenging due to the inherent complexity and variability of the fermentation media. Real-time monitoring is necessary to compensate for these challenges, but the traditional process monitoring methods fail to deliver actionable information that can be used to implement advanced control strategies. In this study, a hybrid-modeling approach is presented to monitor cellulose-to-ethanol (EtOH) fermentations in real-time. The hybrid approach uses a continuous-discrete extended Kalman filter to reconciliate the predictions of a data-driven model and a kinetic model and to estimate the concentration of glucose (Glu), xylose (Xyl), and EtOH. The data-driven model is based on partial least squares (PLS) regression and predicts in real-time the concentration of Glu, Xyl, and EtOH from spectra collected with attenuated total reflectance mid-infrared spectroscopy. The estimations made by the hybrid approach, the data-driven models and the internal model were compared in two validation experiments showing that the hybrid model significantly outperformed the PLS and improved the predictions of the internal model. Furthermore, the hybrid model delivered consistent estimates even when disturbances in the measurements occurred, demonstrating the robustness of the method. The consistency of the proposed hybrid model opens the doors towards the implementation of advanced feedback control schemes.

Towards the Development of Digital Twins for the Bio-manufacturing Industry.

The bio-manufacturing industry, along with other process industries, now has the opportunity to be engaged in the latest industrial revolution, also known as Industry 4.0. To successfully accomplish this, a physical-to-digital-to-physical information loop should be carefully developed. One way to achieve this is, for example, through the implementation of digital twins (DTs), which are virtual copies of the processes. Therefore, in this paper, the focus is on understanding the needs and challenges faced by the bio-manufacturing industry when dealing with this digitalized paradigm. To do so, two major building blocks of a DT, data and models, are highlighted and discussed. Hence, firstly, data and their characteristics and collection strategies are examined as well as new methods and tools for data processing. Secondly, modelling approaches and their potential of being used in DTs are reviewed. Finally, we share our vision with regard to the use of DTs in the bio-manufacturing industry aiming at bringing the DT a step closer to its full potential and realization.

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.