Towards one-step design of tailored enzymatic nanobiosensors.

The manufacturing of conventional enzymatic biosensors produced via a layer-by-layer (LbL) approach requires expensive instrumentation, and in most cases involves a complex, resource and time-consuming fabrication process. Moreover, LbL assemblies are prone to mechanical instability that leads to irreversible changes in sensor architecture and morphology resulting in degradation of enzymatic activities and insufficient signal reproducibility. Hence, novel fabrication techniques for the production of enzymatic biosensors that are instrumentally controlled and allow reproducible, simultaneous multi-analyte detection with high specificity, temporal and spatial resolution are greatly required. Herein, we report on the development of a novel, fully instrumentally controlled, one-step synthesis approach for the production of nanoparticle-based enzymatic biosensors. The approach relies on a simultaneous encapsulation of the enzyme (glucose and alcohol oxidases), a fluoropolymer (Nafion) and noble metal nanoparticles via co-deposition from a phosphate multiple electrolyte on top of the sensor surface. Remarkably, electrochemical studies revealed that nanoparticle-based biosensors produced by this novel fabrication approach display a significantly enhanced mechanical stability (more than several orders of magnitude higher) without loss of biological activity or leakage of the enzyme or Nafion, and advanced synthesis reproducibility (40 times higher) in comparison to LbL analogues.

Assessing the effects of intra-granule precipitation in a full-scale industrial anaerobic digester.

In this paper, a multi-scale model is used to assess the multiple mineral precipitation potential in a full-scale anaerobic granular sludge system. Reactor behaviour is analysed under different operational conditions (addition/no addition of reject water from dewatering of lime-stabilized biomass) and periods of time (short/long term). Model predictions suggest that a higher contribution of reject water promotes the risk of intra-granule CaCO3 formation as a result of the increased quantity of calcium arriving with that stream combined with strong pH gradients within the biofilm. The distribution of these precipitates depends on: (i) reactor height; and (ii) granule size. The study also exposes the potential undesirable effects of the long-term addition of reject water (a decrease in energy recovery of 20% over a 100-day period), caused by loss in biomass activity (due to microbial displacement), and the reduced buffer capacity. This demonstrates how both short-term and long-term operational conditions may affect the formation of precipitates within anaerobic granules, and how it may influence methane production and consequently energy recovery.

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

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

Plant-wide model-based analysis of iron dosage strategies for chemical phosphorus removal in wastewater treatment systems.

Stringent phosphorus discharge standards (i.e. 0.15-0.3 g P.m-3) in the Baltic area will compel wastewater treatment practice to augment enhanced biological phosphorus removal (EBPR) with chemical precipitation using metal salts. This study examines control of iron chemical dosing for phosphorus removal under dynamic loading conditions to optimize operational aspects of a membrane biological reactor (MBR) pilot plant. An upgraded version of the Benchmark Simulation Model No. 2 (BSM2) with an improved physico-chemical framework (PCF) is used to develop a plant-wide model for the pilot plant. The PCF consists of an equilibrium approach describing ion speciation and pairing, kinetic minerals precipitation (such as hydrous ferric oxides (HFO) and FePO4) as well as adsorption and co-precipitation. Model performance is assessed against data sets from the pilot plant, evaluating the capability to describe water and sludge lines across the treatment process under steady-state operation. Simulated phosphorus differed as little as 5-10% (relative) from measured phosphorus, indicating that the model was representative of reality. The study also shows that environmental factors such as pH, as well operating conditions such as Fe/P molar ratios (1, 1.5 and 2), influence the concentration of dissolved phosphate in the effluent. The time constant of simultaneous precipitation in the calibrated model, due to a step change decrease/increase in FeSO4 dosage, was found to be roughly 5 days, indicating a slow dynamic response due to a multi-step process involving dissolution, oxidation, precipitation, aging, adsorption and co-precipitation. The persistence effect of accumulated iron-precipitates (HFO particulates) in the activated sludge seemed important for phosphorus removal, and therefore solids retention time plays a crucial role according to the model. The aerobic tank was deemed to be the most suitable dosing location for FeSO4 addition, due to high dissolved oxygen levels and good mixing conditions. Finally, dynamic model-based analyses show the benefits of using automatic control when dosing chemicals.

Exploring the potential of electroless and electroplated noble metal-semiconductor hybrids within bio- and environmental sensing.

Over the last two decades, the rapid development and widespread application of nanomaterials has significantly influenced research in various fields, including analytical chemistry and biosensing technologies. In particular, the simple functionalization and tuning of noble metal nanoparticle (NP) surface chemistry resulted in the development of a series of novel biosensing platforms with quick read-out and enhanced capabilities towards specific analyte detection. Moreover, noble metal NPs possess a number of unique properties, viz. high surface-to-volume ratio and excellent spectral, optical, thermal, electrical and catalytic characteristics. This manuscript provides an elaborate review on galvanic noble metal NPs deposited onto semiconductor surfaces, from the preparation stage towards their application in biosensors and gas sensing. Two types of deposition approaches, viz. galvanic displacement/electroless and conventional electroplating, are introduced and compared. Furthermore, the analytical merit of hybrid nanomaterials towards the improvement of sensing abilities is highlighted. Finally, some limitations and challenges related to progress in the development and application of analytical devices based on electroless and electroplated noble metal NPs-semiconductor hybrids (NMNPsHs) in biochemical and environmental sensing are discussed.

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

The objective of this paper is to show the results of an industrial project dealing with modelling of anaerobic digesters. A multi-scale mathematical approach is developed to describe reactor hydrodynamics, granule growth/distribution and microbial competition/inhibition for substrate/space within the biofilm. The main biochemical and physico-chemical processes in the model are based on the Anaerobic Digestion Model No 1 (ADM1) extended with the fate of phosphorus (P), sulfur (S) and ethanol (Et-OH). Wastewater dynamic conditions are reproduced and data frequency increased using the Benchmark Simulation Model No 2 (BSM2) influent generator. All models are tested using two plant data sets corresponding to different operational periods (#D1, #D2). Simulation results reveal that the proposed approach can satisfactorily describe the transformation of organics, nutrients and minerals, the production of methane, carbon dioxide and sulfide and the potential formation of precipitates within the bulk (average deviation between computer simulations and measurements for both #D1, #D2 is around 10%). Model predictions suggest a stratified structure within the granule which is the result of: 1) applied loading rates, 2) mass transfer limitations and 3) specific (bacterial) affinity for substrate. Hence, inerts (XI) and methanogens (Xac) are situated in the inner zone, and this fraction lowers as the radius increases favouring the presence of acidogens (Xsu,Xaa, Xfa) and acetogens (Xc4,Xpro). Additional simulations show the effects on the overall process performance when operational (pH) and loading (S:COD) conditions are modified. Lastly, the effect of intra-granular precipitation on the overall organic/inorganic distribution is assessed at: 1) different times; and, 2) reactor heights. Finally, the possibilities and opportunities offered by the proposed approach for conducting engineering optimization projects are discussed.

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

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

Generation of synthetic influent data to perform (micro)pollutant wastewater treatment modelling studies.

The use of process models to simulate the fate of micropollutants in wastewater treatment plants is constantly growing. However, due to the high workload and cost of measuring campaigns, many simulation studies lack sufficiently long time series representing realistic wastewater influent dynamics. In this paper, the feasibility of the Benchmark Simulation Model No. 2 (BSM2) influent generator is tested to create realistic dynamic influent (micro)pollutant disturbance scenarios. The presented set of models is adjusted to describe the occurrence of three pharmaceutical compounds and one of each of its metabolites with samples taken every 2-4h: the anti-inflammatory drug ibuprofen (IBU), the antibiotic sulfamethoxazole (SMX) and the psychoactive carbamazepine (CMZ). Information about type of excretion and total consumption rates forms the basis for creating the data-defined profiles used to generate the dynamic time series. In addition, the traditional influent characteristics such as flow rate, ammonium, particulate chemical oxygen demand and temperature are also modelled using the same framework with high frequency data. The calibration is performed semi-automatically with two different methods depending on data availability. The 'traditional' variables are calibrated with the Bootstrap method while the pharmaceutical loads are estimated with a least squares approach. The simulation results demonstrate that the BSM2 influent generator can describe the dynamics of both traditional variables and pharmaceuticals. Lastly, the study is complemented with: 1) the generation of longer time series for IBU following the same catchment principles; 2) the study of the impact of in-sewer SMX biotransformation when estimating the average daily load; and, 3) a critical discussion of the results, and the future opportunities of the presented approach balancing model structure/calibration procedure complexity versus predictive capabilities.

Challenges encountered when expanding activated sludge models: a case study based on N2O production.

It is common practice in wastewater engineering to extend standard activated sludge models (ASMs) with extra process equations derived from batch experiments. However, such experiments have often been performed under conditions different from the ones normally found in wastewater treatment plants (WWTPs). As a consequence, these experiments might not be representative for full-scale performance, and unexpected behaviour may be observed when simulating WWTP models using the derived process equations. In this paper we want to highlight problems encountered using a simplified case study: a modified version of the Activated Sludge Model No. 1 (ASM1) is upgraded with nitrous oxide (N2O) formation by ammonia-oxidizing bacteria. Four different model structures have been implemented in the Benchmark Simulation Model No. 1 (BSM1). The results of the investigations revealed two typical difficulties: problems related to the overall mathematical model structure and problems related to the published set of parameter values. The paper describes the model implementation incompatibilities, the variability in parameter values and the difficulties of reaching similar conditions when simulating a full-scale activated sludge plant. Finally, the simulation results show large differences in oxygen uptake rates, nitritation rates and consequently the quantity of N2O emission (GN2O) using the different models.

Instrumentation, control and automation in wastewater--from London 1973 to Narbonne 2013.

Key developments of instrumentation, control and automation (ICA) applications in wastewater systems during the past 40 years are highlighted in this paper. From the first ICA conference in 1973 through to today there has been a tremendous increase in the understanding of the processes, instrumentation, computer systems and control theory. However, many developments have not been addressed here, such as sewer control, drinking water treatment and water distribution control. It is hoped that this review can stimulate new attempts to more effectively apply control and automation in water systems in the coming years.

Benchmark simulation models, quo vadis?

As the work of the IWA Task Group on Benchmarking of Control Strategies for wastewater treatment plants (WWTPs) is coming to an end, it is essential to disseminate the knowledge gained. For this reason, all authors of the IWA Scientific and Technical Report on benchmarking have come together to provide their insights, highlighting areas where knowledge may still be deficient and where new opportunities are emerging, and to propose potential avenues for future development and application of the general benchmarking framework and its associated tools. The paper focuses on the topics of temporal and spatial extension, process modifications within the WWTP, the realism of models, control strategy extensions and the potential for new evaluation tools within the existing benchmark system. We find that there are major opportunities for application within all of these areas, either from existing work already being done within the context of the benchmarking simulation models (BSMs) or applicable work in the wider literature. Of key importance is increasing capability, usability and transparency of the BSM package while avoiding unnecessary complexity.

Experimental methods and modeling techniques for description of cell population heterogeneity.

With the continuous development, in the last decades, of analytical techniques providing complex information at single cell level, the study of cell heterogeneity has been the focus of several research projects within analytical biotechnology. Nonetheless, the complex interplay between environmental changes and cellular responses is yet not fully understood, and the integration of this new knowledge into the strategies for design, operation and control of bioprocesses is far from being an established reality. Indeed, the impact of cell heterogeneity on productivity of large scale cultivations is acknowledged but seldom accounted for. In order to include population heterogeneity mechanisms in the development of novel bioprocess control strategies, a reliable mathematical description of such phenomena has to be developed. With this review, we search to summarize the potential of currently available methods for monitoring cell population heterogeneity as well as model frameworks suitable for describing dynamic heterogeneous cell populations. We will furthermore underline the highly important coordination between experimental and modeling efforts necessary to attain a reliable quantitative description of cell heterogeneity, which is a necessity if such models are to contribute to the development of improved control of bioprocesses.

Benchmark Simulation Model No 2: finalisation of plant layout and default control strategy.

The COST/IWA Benchmark Simulation Model No 1 (BSM1) has been available for almost a decade. Its primary purpose has been to create a platform for control strategy benchmarking of activated sludge processes. The fact that the research work related to the benchmark simulation models has resulted in more than 300 publications worldwide demonstrates the interest in and need of such tools within the research community. Recent efforts within the IWA Task Group on "Benchmarking of control strategies for WWTPs" have focused on an extension of the benchmark simulation model. This extension aims at facilitating control strategy development and performance evaluation at a plant-wide level and, consequently, includes both pretreatment of wastewater as well as the processes describing sludge treatment. The motivation for the extension is the increasing interest and need to operate and control wastewater treatment systems not only at an individual process level but also on a plant-wide basis. To facilitate the changes, the evaluation period has been extended to one year. A prolonged evaluation period allows for long-term control strategies to be assessed and enables the use of control handles that cannot be evaluated in a realistic fashion in the one week BSM1 evaluation period. In this paper, the finalised plant layout is summarised and, as was done for BSM1, a default control strategy is proposed. A demonstration of how BSM2 can be used to evaluate control strategies is also given.

New framework for standardized notation in wastewater treatment modelling.

Many unit process models are available in the field of wastewater treatment. All of these models use their own notation, causing problems for documentation, implementation and connection of different models (using different sets of state variables). The main goal of this paper is to propose a new notational framework which allows unique and systematic naming of state variables and parameters of biokinetic models in the wastewater treatment field. The symbols are based on one main letter that gives a general description of the state variable or parameter and several subscript levels that provide greater specification. Only those levels that make the name unique within the model context are needed in creating the symbol. The paper describes specific problems encountered with the currently used notation, presents the proposed framework and provides additional practical examples. The overall result is a framework that can be used in whole plant modelling, which consists of different fields such as activated sludge, anaerobic digestion, sidestream treatment, membrane bioreactors, metabolic approaches, fate of micropollutants and biofilm processes. The main objective of this consensus building paper is to establish a consistent set of rules that can be applied to existing and most importantly, future models. Applying the proposed notation should make it easier for everyone active in the wastewater treatment field to read, write and review documents describing modelling projects.

Wastewater treatment modelling: dealing with uncertainties.

This paper serves as a problem statement of the issues surrounding uncertainty in wastewater treatment modelling. The paper proposes a structure for identifying the sources of uncertainty introduced during each step of an engineering project concerned with model-based design or optimisation of a wastewater treatment system. It briefly references the methods currently used to evaluate prediction accuracy and uncertainty and discusses the relevance of uncertainty evaluations in model applications. The paper aims to raise awareness and initiate a comprehensive discussion among professionals on model prediction accuracy and uncertainty issues. It also aims to identify future research needs. Ultimately the goal of such a discussion would be to generate transparent and objective methods of explicitly evaluating the reliability of model results, before they are implemented in an engineering decision-making context.

Benchmark simulation model no 2: general protocol and exploratory case studies.

Over a decade ago, the concept of objectively evaluating the performance of control strategies by simulating them using a standard model implementation was introduced for activated sludge wastewater treatment plants. The resulting Benchmark Simulation Model No 1 (BSM1) has been the basis for a significant new development that is reported on here: Rather than only evaluating control strategies at the level of the activated sludge unit (bioreactors and secondary clarifier) the new BSM2 now allows the evaluation of control strategies at the level of the whole plant, including primary clarifier and sludge treatment with anaerobic sludge digestion. In this contribution, the decisions that have been made over the past three years regarding the models used within the BSM2 are presented and argued, with particular emphasis on the ADM1 description of the digester, the interfaces between activated sludge and digester models, the included temperature dependencies and the reject water storage. BSM2-implementations are now available in a wide range of simulation platforms and a ring test has verified their proper implementation, consistent with the BSM2 definition. This guarantees that users can focus on the control strategy evaluation rather than on modelling issues. Finally, for illustration, twelve simple operational strategies have been implemented in BSM2 and their performance evaluated. Results show that it is an interesting control engineering challenge to further improve the performance of the BSM2 plant (which is the whole idea behind benchmarking) and that integrated control (i.e. acting at different places in the whole plant) is certainly worthwhile to achieve overall improvement.

Application of multivariable statistical techniques in plant-wide WWTP control strategies analysis.

The main objective of this paper is to present the application of selected multivariable statistical techniques in plant-wide wastewater treatment plant (WWTP) control strategies analysis. In this study, cluster analysis (CA), principal component analysis/factor analysis (PCA/FA) and discriminant analysis (DA) are applied to the evaluation matrix data set obtained by simulation of several control strategies applied to the plant-wide IWA Benchmark Simulation Model No 2 (BSM2). These techniques allow i) to determine natural groups or clusters of control strategies with a similar behaviour, ii) to find and interpret hidden, complex and casual relation features in the data set and iii) to identify important discriminant variables within the groups found by the cluster analysis. This study illustrates the usefulness of multivariable statistical techniques for both analysis and interpretation of the complex multicriteria data sets and allows an improved use of information for effective evaluation of control strategies.

On-line estimation and detection of abnormal substrate concentrations in WWTPs using a software sensor: a benchmark study.

In this paper, a new approach for on-line monitoring and detection of abnormal readily biodegradable substrate (S(s)) and slowly biodegradable substrate (X(s)) concentrations, for example due to input of toxic loads from the sewer, or due to influent substrate shock load, is proposed. Considering that measurements of S(s) and X(s) concentrations are not available in real wastewater treatment plants, the S(s) / X(s) software sensor can activate an alarm with a response time of about 60 and 90 minutes, respectively, based on the dissolved oxygen measurement. The software sensor implementation is based on an extended Kalman filter observer and disturbances are modelled using fast Fourier transform and spectrum analyses. Three case studies are described. The first one illustrates the fast and accurate convergence of the extended Kalman filter algorithm, which is achieved in less than 2 hours. Furthermore, the difficulties of estimating X(s) when off-line analysis is not available are depicted, and the S(s) / X(s) software sensor performances when no measurements of S(s) and X(s) are available are illustrated. Estimation problems related to the death-regeneration concept of the activated sludge model no.1 and possible application of the software sensor in wastewater monitoring are discussed.

Benchmark simulation Model no 2 in Matlab-simulink: towards plant-wide WWTP control strategy evaluation.

In this paper, implementation of the Benchmark Simulation Model No 2 (BSM2) within Matlab-Simulink is presented. The BSM2 is developed for plant-wide WWTP control strategy evaluation on a long-term basis. It consists of a pre-treatment process, an activated sludge process and sludge treatment processes. Extended evaluation criteria are proposed for plant-wide control strategy assessment. Default open-loop and closed-loop strategies are also proposed to be used as references with which to compare other control strategies. Simulations indicate that the BM2 is an appropriate tool for plant-wide control strategy evaluation.

Plant-wide (BSM2) evaluation of reject water treatment with a SHARON-Anammox process.

In wastewater treatment plants (WWTPs) equipped with sludge digestion and dewatering systems, the reject water originating from these facilities contributes significantly to the nitrogen load of the activated sludge tanks, to which it is typically recycled. In this paper, the impact of reject water streams on the performance of a WWTP is assessed in a simulation study, using the Benchmark Simulation Model no. 2 (BSM2), that includes the processes describing sludge treatment and in this way allows for plant-wide evaluation. Comparison of performance of a WWTP without reject water with a WWTP where reject water is recycled to the primary clarifier, i.e. the BSM2 plant, shows that the ammonium load of the influent to the primary clarifier is 28% higher in the case of reject water recycling. This results in violation of the effluent total nitrogen limit. In order to relieve the main wastewater treatment plant, reject water treatment with a combined SHARON-Anammox process seems a promising option. The simulation results indicate that significant improvements of the effluent quality of the main wastewater treatment plant can be realized. An economic evaluation of the different scenarios is performed using an Operating Cost Index (OCI).