Modelling biofilm development: The importance of considering the link between EPS distribution, detachment mechanisms and physical properties.

In industry, treatments against biofilms need to be optimized and, in the wastewater treatment field, biofilm composition needs to be controlled. Therefore, describing the biochemical and physical structures of biofilms is now required to better understand the influence of operating parameters and treatment on biofilms. The present study aims to investigate how growth conditions influence EPS composition, biofilm physical properties and volume detachment using a 1D biofilm model. Two types of EPS are considered in the present model, proteins and polysaccharides. The main hypotheses are that: (i) the production of polysaccharides occurs mainly under strong nutrient limitation(s) while the production of proteins is coupled to both the substrate uptake rate and the lysis process; (ii) the local biofilm porosity depends on the local biofilm composition. Both volume and surface detachment occur in biofilms and volume detachment extent depends on the biofilm local cohesion and thus on the local composition of biofilms for a given shear stress. The model is based on experimental trends and aims to represent these observations on the basis of biochemical and physical processes. Four case studies covering a wide range of contrasting growth conditions such as different COD/N ratios, applied SOLR and shear stresses are investigated. The model predicts how the biochemical and physical biofilm structures change as a result of contrasting growth conditions. More precisely simulation results are in good agreement with the main experimental observations reported in the literature, such as: (i) a strong nitrogen limitation of growth induces an important accumulation of polysaccharides leading to a more porous and homogenous biofilm, (ii) a high applied surface organic loading load allows to obtain a high biofilm thickness, (iii) a strong shear stress applied during the biofilm growth leads to a reduction of the biofilm thickness and to a consolidation of the biofilm structure. Overall, this model represents a relevant decision tool for the selection of appropriate enzymatic treatments in the context of negative biofilm control. From our results, it appears that protease based treatments should be more appropriate for biofilms developed under low COD/N ratios (about 20 gCOD/gN) whereas both glucosidases and proteases based treatments should be more appropriate for biofilms developed under high COD/N ratio (about 70 gCOD/gN). In addition, the model could be useful for other applications such as resource recovery in biofilms or granules, and help to better understand biological membrane fouling.

A two pathway model for N2O emissions by ammonium oxidizing bacteria supported by the NO/N2O variation.

In this work, a new model for nitritation combining two N2O emission pathways was confronted with both NO and N2O measurements during nitrification. The model was calibrated with batch experiments and validated with long-term data collected in a sequencing batch reactor (SBR). A good prediction of the evolution of N2O emissions for a varying level of nitrite was demonstrated. The NO/N2O ratio was shown to vary during nitritation depending on the nitrite level. None of the models based on a single pathway could describe this variation of the NO/N2O ratio. In contrast, the 2 pathway model was capable of describing the trends observed for the NO/N2O ratio and gave better predictions of N2O emission factors. The model confirmed that the decrease of the NO/N2O ratio can be explained by an increase of the ND pathway to the detriment of the NN pathway. The ND pathway was systematically the predominant pathway during nitritation. The combined effect of nitrite (or free nitrous acid) and dissolved oxygen (DO) on the contribution of each pathway was in agreement with practical observations and the literature.

Robust control of the activated sludge process.

In this work, a robust control strategy is proposed for maintaining the oxygen concentration in the aerobic tank and the pollutant, i.e., ammonium, nitrate, nitrite, concentrations at acceptable levels in the effluent water at the outlet of the activated sludge process. To this end, the Activated Sludge Model no. 1 (ASM1) is first reduced using biological arguments and a singular perturbation method, and a simplified model of the secondary settler is included. In contrast with previous studies that make use of piecewise linear models, an average operating point is evaluated using available data (here data from the COST Action 624) and the reduced-order model is linearized around it using standard techniques. Finally, a H(2) robust control strategy acting on the oxygen injection and the recirculated flow rate is designed and tested in simulation.

Development and calibration of a nitrification PDE model based on experimental data issued from biofilter treating drinking water.

To remove ammonia for production of drinking water, nitrification can be performed in a bio-filter. At least 1 month is necessary to capture from the groundwater and then grow a sufficient amount of nitrifying bacteria to reach the desired removal efficiency. Improving start-up of bio-filters at low substrate concentration is therefore a major challenge. In this connection, it is important to develop appropriate models for designing, monitoring or analysing biofilm systems during start-up or following disinfection events. This study discusses the development and calibration of a nitrification PDE model which reflects the compromise between the complexity associated with the description of the full physical and biochemical mechanisms and the search for a simplified model with identifiable parameters. This model takes only the relevant phenomena (considering the full operating range) into account. The validity of the calibrated model has been evaluated through experiments under very different operational conditions, at the laboratory and under real industrial conditions, involving the full upstream chain of water treatment (iron oxidation and sand filter).

Online estimation of wastewater nitrifiable nitrogen, nitrification and denitrification rates, using ORP and DO dynamics.

Biological nitrogen removal is susceptible to disturbances in activated sludge processes. Significant improvement of performances are obtained by controlling the process taking into account wastewater modifications and sludge activity. In this work a specific sensor is developed, based on oxidation-reduction potential (ORP) and dissolved oxygen (DO) measurements performed in a completely mixed reactor which can be the activated sludge basin itself. This reactor is continuously fed by wastewater and sludge issued from the recirculation stream of the process, and submitted to alternating aeration. DO profiles and ORP bending point are linked to nitrification and denitrification in the sensor. Signal dynamics are treated with a physical model for simultaneously estimating nitrifiable nitrogen concentration in wastewater, nitrification rate, and denitrification rate. Results show very good prediction of experimental oxygen profiles and the software sensor allows us to recalculate nitrate and ammonia profiles in the reactor with a good accuracy. The estimation of nitrifiable nitrogen and removal rates has been validated experimentally. The system allows us to follow highly variable influent nitrogen concentration, toxic events, and changes in the COD concentration or quality in wastewater.

Modelling and simulation of the steady-state of secondary settlers in wastewater treatment plants.

This paper discusses the steady-state modelling of thickening in circular secondary settlers of activated sludge processes. The limitations of the solid flux theory basic models to represent steady-state operating conditions serve as a basis to introduce more sophisticated models derived from computational fluid dynamics. Parameter identification and sensitivity studies have been performed from lab-scale continuous experiments.

Phenol degradation by Ralstonia eutropha: colorimetric determination of 2-hydroxymuconate semialdehyde accumulation to control feed strategy in fed-batch fermentations.

Phenol biodegradation by Ralstonia eutropha was modeled in different culture modes to assess phenol feeding in biotechnological depollution processes. The substrate-inhibited growth of R. eutropha was described by the Haldane equation with a Ks of 2 mg/L, a Ki of 350 mg/L and a mumax of 0.41 h(-1). Furthermore, growth in several culture modes was characterized by the appearance of a yellow color, due to production of a metabolic intermediate of the phenol catabolic pathway, 2-hydroxymuconic semialdehyde (2-hms) which was directly correlated to the growth rate and/or the phenol-degradation rate, because these two parameters are coupled (as seen by the constant growth yield of 0.68 g biomass/g phenol whatever the phenol concentration). This correlation between color appearance and metabolic activity was used to develop a control procedure for optimal phenol degradation. A mass-balance equation modeling approach combined with a filtering step using an extended Kalman filter enabled state variables of the biological system to be simulated. A PI controller, using the estimation of the phenol concentration provided by the modeling step, was then built to maintain the phenol concentration at a constant set-point of 0.1 g/L which corresponded to a constant specific growth rate of 0.3 h(-1), close to the maximal specific growth value of the strain. This monitoring strategy, validated for two fed-batch cultures, could lead, in self-cycling fermentation systems, to a productivity of more than 19 kg of phenol consumed/m(3)/d which is the highest value reported to date in the literature. This system of monitoring metabolic activity also protected the bacterial culture against toxicity problems due to the transient accumulation of phenol.

An effective automated glucose sensor for fermentation monitoring and control.

An industrial glucose analyser was partnered to an automated injection system to evaluate glucose in the culture medium of a bioreactor. This sensor has been validated on continuous cultures ofSchizosaccharomyces pombe and continuous and fed-batch cultures ofSaccharomyces cerevisiae. In addition to the advantage of a more accurate process monitoring, the main interest of this sensor deals with the control of the substrate concentration to a prespecified reference signal. Several experiments have been carried out first to validate the sensor, then to control the process evolution.