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.

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.

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.

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.

Promoting the co-utilisation of glucose and xylose in lignocellulosic ethanol fermentations using a data-driven feed-back controller.

BACKGROUND: The diauxic growth of Saccharomyces cerevisiae on glucose and xylose during cellulose-to-ethanol processes extends the duration of the fermentation and reduces productivity. Despite the remarkable advances in strain engineering, the co-consumption of glucose and xylose is still limited due to catabolite repression. This work addresses this challenge by developing a closed-loop controller that is capable of maintaining the glucose concentration at a steady set-point during fed-batch fermentation. The suggested controller uses a data-driven model to measure the concentration of glucose from 'real-time' spectroscopic data. The concentration of glucose is then automatically controlled using a control scheme that consists of a proportional, integral, differential (PID) algorithm and a supervisory layer that manipulates the feed-rates to the reactor accounting for the changing dynamics of fermentation. RESULTS: The PID parameters and the supervisory layer were progressively improved throughout four fed-batch lignocellulosic-to-ethanol fermentations to attain a robust controller able of maintaining the glucose concentration at the pre-defined set-points. The results showed an increased co-consumption of glucose and xylose that resulted in volumetric productivities that are 20-33% higher than the reference batch processes. It was also observed that fermentations operated at a glucose concentration of 10 g/L were faster than those operated at 4 g/L, indicating that there is an optimal glucose concentration that maximises the overall productivity. CONCLUSIONS: Promoting the simultaneous consumption of glucose and xylose in S. cerevisiae is critical to increase the productivity of lignocellulosic ethanol processes, but also challenging due to the strong catabolite repression of glucose on the uptake of xylose. Operating the fermentation at low concentrations of glucose allows reducing the effects of the catabolite repression to promote the co-consumption of the two carbon sources. However, S. cerevisiae is very sensitive to changes in the glucose concentration and deviations from a set-point result in notable productivity losses. The controller structure developed and implemented in this work illustrates how combining data-driven measurements of the glucose concentration and a robust yet effective PID-based supervisory control allowed tight control of the concentration of glucose to adjust it to the metabolic requirements of the cell culture that can unlock tangible gains in productivities.

Electrochemical tuning of alcohol oxidase and dehydrogenase catalysis via biosensing towards butanol-1 detection in fermentation media.

A novel approach for electrochemical tuning of alcohol oxidase (AOx) and alcohol dehydrogenase (ADH) biocatalysis towards butanol-1 oxidation by incorporating enzymes in various designs of amperometric biosensors is presented. The biosensors were developed by using commercial graphene oxide-based screen-printed electrodes and varying enzyme producing strains, encapsulation approaches (layer-by-layer (LbL) or one-step electrodeposition (EcD)), layers composition and structure, operating conditions (applied potential values) and introducing mediators (Meldola Blue and Prussian Blue) or Pd-nanoparticles (Pd-NPs). Simultaneous analysis/screening of multiple crucial system parameters during the enzyme engineering process allowed to identify within a period of one month that four out of twelve proposed designs demonstrated a good signal reproducibility and linear response (up to 14.6 mM of butanol) under very low applied potentials (from -0.02 to -0.32 V). Their mechanical stability was thoroughly investigated by multi-analytical techniques prior to butanol determination in cell-free samples from an anaerobic butanol fermentation. The EcD-based biosensor that incorporates ADH, NAD+, Pd-NPs and Nafion showed no loss of enzyme activity after preparation and demonstrated capabilities towards low potential (-0.12 V) detection of butanol-1 in fermentation medium (4 mM) containing multiple electroactive species with almost 15 times enhanced sensitivity (0.2282 µA/mM ± 0.05) when compared to the LbL design. Furthermore, the ADH-Nafion bonding for the S. cerevisiae strain was confirmed to be 3 times higher than for E. coli.

Towards smart biomanufacturing: a perspective on recent developments in industrial measurement and monitoring technologies for bio-based production processes.

The biomanufacturing industry has now the opportunity to upgrade its production processes to be in harmony with the latest industrial revolution. Technology creates capabilities that enable smart manufacturing while still complying with unfolding regulations. However, many biomanufacturing companies, especially in the biopharma sector, still have a long way to go to fully benefit from smart manufacturing as they first need to transition their current operations to an information-driven future. One of the most significant obstacles towards the implementation of smart biomanufacturing is the collection of large sets of relevant data. Therefore, in this work, we both summarize the advances that have been made to date with regards to the monitoring and control of bioprocesses, and highlight some of the key technologies that have the potential to contribute to gathering big data. Empowering the current biomanufacturing industry to transition to Industry 4.0 operations allows for improved productivity through information-driven automation, not only by developing infrastructure, but also by introducing more advanced monitoring and control strategies.

Automated Electrochemical Glucose Biosensor Platform as an Efficient Tool Toward On-Line Fermentation Monitoring: Novel Application Approaches and Insights.

Monitoring and control of fermentation processes remain a crucial challenge for both laboratory and industrial-scale experiments. Reliable identification and quantification of the key process parameters in on-line mode allow operation of the fermentation at optimal reactor efficiency, maximizing productivity while minimizing waste. However, state-of-the-art fermentation on-line monitoring is still limited to a number of standard measurements such as pH, temperature and dissolved oxygen, as well as off-gas analysis as an advanced possibility. Despite the availability of commercial biosensor-based platforms that have been established for continuous monitoring of glucose and various biological variables within healthcare, on-line glucose quantification in fermentation processes has not been implemented yet to a large degree. For the first time, this work presents a complete study of a commercial flow-through-cell with integrated electrochemical glucose biosensors (1st generation) applied in different media, and importantly, at- and on-line during a yeast fed-batch fermentation process. Remarkably, the glucose biosensor-based platform combined with the developed methodology was able to detect glucose concentrations up to 150 mM in the complex fermentation broth, on both cell-free and cell-containing samples, when not compromised by oxygen limitations. This is four to six-fold higher than previously described in the literature presenting the application of biosensors predominately toward cell-free fermentation samples. The automated biosensor platform allowed reliable glucose quantification in a significantly less resource and time (<5 min) consuming manner compared to conventional HPLC analysis with a refractive index (RI) detector performed as reference measurement. Moreover, the presented biosensor platform demonstrated outstanding mechanical stability in direct contact with the fermentation medium and accurate glucose quantification in the presence of various electroactive species. Coupled with the developed methodology it can be readily considered as a simple, robust, accurate and inexpensive tool for real-time glucose monitoring in fermentation processes.

Monitoring yeast fermentations by nonlinear infrared technology and chemometrics-understanding process correlations and indirect predictions.

Fermentation processes are still compromised by a lack of monitoring strategies providing integrated process data online, ensuring process understanding, control, and thus, optimal reactor efficiency. The crucial demand for online monitoring strategies, not only encouraged by the PAT initiative but also motivated by modern paradigms such as circular economy and sustainability, has driven research and industry to provide "next-generation process technology": in other words, technology tailored toward industrial needs. Mid-infrared (MIR) spectroscopy as such is superior to near-infrared (NIR) spectroscopy since it provides significantly enhanced selectivity. However, due to high costs and a lack of instrumental robustness, MIR spectroscopy is outcompeted by NIR when it comes to industrial application. The lack of chemometric expertise, model understanding, and practical guidance might add to the slow acceptance of industrial MIR application. This work demonstrates the use of novel MIR, so-called non-linear infrared (NLIR) technology and the importance of model understanding, exemplarily investigated on a lab-scale yeast fermentation process. The six analytes glucose, ethanol, glycerol, acetate, ammonium, and phosphate were modeled by partial least squares (PLS) based on spectral data, demonstrating the potential of the novel technology facilitating online data acquisition and the necessity of investigating indirect predictions. KEY POINTS: • NLIR spectra were acquired online during a yeast fermentation process • PLS models were constructed for six components based on uncorrelated samples • Glucose, ethanol, ammonium, and phosphates were modeled with errors of less than 15% • Acetate and glycerol were shown to rely on indirect predictions.

Comment on "A compilation and bioenergetic evaluation of syntrophic microbial growth yields in anaerobic digestion" by Patón, M. and Rodríguez, J. [Water Research 162 (2019), 516-517].

Recent efforts have focused on providing a systematic analysis of syntrophic microbial growth yields. These biokinetic parameters are key to developing an accurate mathematical description of the anaerobic digestion process. The agreement between experimentally determined growth yields and those obtained from bioenergetic estimations is therefore of great interest. Considering five important syntrophic groups, including acetoclastic and hydrogenotrophic methanogens, as well as propionate, butyrate and lactate oxidizers, previous findings suggest that measured and estimated growth yields were consistent only for acetoclastic methanogens. A re-analysis revealed that data are also consistent for lactate oxidizers and hydrogenotrophic methanogens, whereas the limited data available for propionate and butyrate oxidizers are unsupportive of firm conclusions. These results highlight pertinent challenges in the analysis of microbial syntrophy and encourage more accurate measurements of syntrophic microbial growth yields in the future.

Limitation of syntrophic coculture growth by the acetogen.

The syntrophic cooperation between hydrogen-producing acetogens and hydrogenotrophic methanogens relies on a critical balance between both partners. A recent study, provided several indications for the dependence of the biomass-specific growth rate of a methanogenic coculture on the acetogen. Nevertheless, final experimental proof was lacking since biomass-specific rates were obtained from a descriptive model, and not from direct measurement of individual biomass concentrations. In this study, a recently developed quantitative PCR approach was used to measure the individual biomass concentrations in the coculture of Desulfovibrio sp. G11 and Methanospirillum hungatei JF1 on lactate, formate or both. The model-derived growth yields and biomass-specific rates were successfully validated. Experimental findings identified the acetogen as the growth-limiting partner in the coculture on lactate. While the acetogen was operating at its maximum biomass-specific lactate consumption rate, the hydrogenotrophic methanogen showed a significant overcapacity. Furthermore, this study provides experimental evidence for different growth strategies followed by the syntrophic partners in order to maintain a common biomass-specific growth rate. During syntrophic lactate conversion, the biomass-specific electron transfer rate of Methanospirillum hungatei JF1 was three-fold higher compared to Desulfovibrio sp. G11. This is to compensate for the lower methanogenic biomass yield per electron-mole of substrate, which is dictated by the thermodynamics of the underlying reaction.

Absolute quantification of individual biomass concentrations in a methanogenic coculture.

Identification of individual biomass concentrations is a crucial step towards an improved understanding of anaerobic digestion processes and mixed microbial conversions in general. The knowledge of individual biomass concentrations allows for the calculation of biomass specific conversion rates which form the basis of anaerobic digestion models. Only few attempts addressed the absolute quantification of individual biomass concentrations in methanogenic microbial ecosystems which has so far impaired the calculation of biomass specific conversion rates and thus model validation. This study proposes a quantitative PCR (qPCR) approach for the direct determination of individual biomass concentrations in methanogenic microbial associations by correlating the native qPCR signal (cycle threshold, Ct) to individual biomass concentrations (mg dry matter/L). Unlike existing methods, the proposed approach circumvents error-prone conversion factors that are typically used to convert gene copy numbers or cell concentrations into actual biomass concentrations. The newly developed method was assessed and deemed suitable for the determination of individual biomass concentrations in a defined coculture of Desulfovibrio sp. G11 and Methanospirillum hungatei JF1. The obtained calibration curves showed high accuracy, indicating that the new approach is well suited for any engineering applications where the knowledge of individual biomass concentrations is required.

Plasticicumulans lactativorans sp. nov., a polyhydroxybutyrate-accumulating gammaproteobacterium from a sequencing-batch bioreactor fed with lactate.

A bacterial consortium that accumulated more than 90 % (w/w) polyhydroxybutyrate (PHB) from lactate was selected in a laboratory-scale bioreactor with a 'feast-famine' regime. Bacterial strain YD(T), representing a dominant species in this enrichment, was isolated and characterized. Analysis of the 16S rRNA gene sequence revealed that the isolate is a member of the class Gammaproteobacteria, forming an independent phylogenetic lineage. The closest relative of the isolate was Plasticicumulans acidivorans TUD-YJ37(T), with 94 % 16S rRNA gene sequence similarity. Strain YD(T) was an obligate aerobe with large, ovoid, Gram-negative cells, motile by means of a polar flagellum. It utilized a relatively broad spectrum of substrates (e.g. carbohydrates, fatty acids) as carbon and energy sources. The temperature range for growth was 20-45 °C, with an optimum at 40 °C; the pH range was pH 6.0-8.0, with an optimum at pH 7.0. The major respiratory lipoquinones were Q-8 (91 %) and Q-7 (9 %). The polar lipids consisted of diphosphatidylglycerol, phosphatidylglycerol, phosphatidylethanolamine, phosphatidylmonomethylethanolamine and an unidentified aminolipid. The predominant fatty acids in the membrane polar lipids were C16 : 1ω7c, C16 : 0 and C18 : 1ω7c. The G+C content of the genomic DNA was 68.5 mol%. On the basis of the phenotypic, chemotaxonomic and phylogenetic data, the isolate is proposed to represent a novel species in the genus Plasticicumulans, for which the name Plasticicumulans lactativorans sp. nov. is proposed. The type strain is YD(T) ( = DSM 25287(T) = NCCB 100398(T)).