J. Ribes

Experimental study of the anaerobic urban wastewater treatment in a submerged hollow-fibre membrane bioreactor at pilot scale

The aim of this study was to assess the effect of several operational variables on both biological and separation process performance in a submerged anaerobic membrane bioreactor pilot plant that treats urban wastewater. The pilot plant is equipped with two industrial hollow-fibre ultrafiltration membrane modules (PURON® Koch Membrane Systems, 30 m² of filtration surface each). It was operated under mesophilic conditions (at 33 °C), 70 days of SRT, and variable HRT ranging from 20 to 6h. The effects of the influent COD/SO₄-S ratio (ranging from 2 to 12) and the MLTS concentration (ranging from 6 to 22 g L⁻¹) were also analysed. The main performance results were about 87% of COD removal, effluent VFA below 20 mg L⁻¹ and biogas methane concentrations over 55% v/v. Methane yield was strongly affected by the influent COD/SO₄-S ratio. No irreversible fouling problems were detected, even for MLTS concentrations above 22 g L⁻¹.

Factors that affect the permeability of commercial hollow-fibre membranes in a submerged anaerobic MBR (HF-SAnMBR) system

A demonstration plant with two commercial HF ultrafiltration membrane modules (PURON(®), Koch Membrane Systems, PUR-PSH31) was operated with urban wastewater. The effect of the main operating variables on membrane performance at sub-critical and supra-critical filtration conditions was tested. The physical operating variables that affected membrane performance most were gas sparging intensity and back-flush (BF) frequency. Indeed, low gas sparging intensities (around 0.23 Nm(3) h(-1) m(-2)) and low BF frequencies (30-s back-flush for every 10 basic filtration-relaxation cycles) were enough to enable membranes to be operated sub-critically even when levels of mixed liquor total solids were high (up to 25 g L(-1)). On the other hand, significant gas sparging intensities and BF frequencies were required in order to maintain long-term operating at supra-critical filtration conditions. After operating for more than two years at sub-critical conditions (transmembrane flux between 9 and 13.3 LMH at gas sparging intensities of around 0.23 Nm(3) h(-1) m(-2) and MLTS levels from around 10-30 g L(-1)) no significant irreversible/irrecoverable fouling problems were detected (membrane permeability remained above 100 LMH bar(-1) and total filtration resistance remained below 10(13) m(-1)), therefore no chemical cleaning was conducted. Membrane performance was similar to the aerobic HF membranes operated in full-scale MBR plants.

DESASS: A software tool for designing, simulating and optimising WWTPs

This paper presents a very useful software tool to design, simulate and optimise wastewater treatment plants. The program is called DESASS (DEsign and Simulation of Activated Sludge Systems) and has been developed by CALAGUA research group. The mathematical model implemented is the Biological Nutrient Removal Model No.1 (BNRM1) which allows simulating the most important physical, chemical and biological processes taking place in treatment plants. DESASS calculates the performance under steady or transient state of whole treatment schemes including primary settlers, volatile fatty acid generation systems by primary sludge fermentation, activated sludge systems for biological organic matter and nutrient removal, chemical phosphorus precipitation, secondary settlers, gravity thickeners and sludge digesters (aerobic and anaerobic). Biological conversions occurring in settlers and thickeners (primary sludge fermentation, denitrification) are also taken into account, i.e. they are considered as reactive elements. DESASS also includes pH calculation coupled to biological processes in all the elements, so pH effect on biological processes can be directly simulated. Furthermore, the effect of sidestreams on nutrient removal efficiency can be estimated because the performance of the whole plant can be simulated.

Biological Nutrient Removal Model Nº 2 (BNRM2): A general model for Wastewater Treatment Plants

This paper presents the plant-wide model Biological Nutrient Removal Model No. 2 (BNRM2). Since nitrite was not considered in the BNRM1, and this previous model also failed to accurately simulate the anaerobic digestion because precipitation processes were not considered, an extension of BNRM1 has been developed. This extension comprises all the components and processes required to simulate nitrogen removal via nitrite and the formation of the solids most likely to precipitate in anaerobic digesters. The solids considered in BNRM2 are: struvite, amorphous calcium phosphate, hidroxyapatite, newberite, vivianite, strengite, variscite, and calcium carbonate. With regard to nitrogen removal via nitrite, apart from nitrite oxidizing bacteria two groups of ammonium oxidizing organisms (AOO) have been considered since different sets of kinetic parameters have been reported for the AOO present in activated sludge systems and SHARON (Single reactor system for High activity Ammonium Removal Over Nitrite) reactors. Due to the new processes considered, BNRM2 allows an accurate prediction of wastewater treatment plant performance in wider environmental and operating conditions.

A methodology for sequencing batch reactor identification with artificial neural networks: A case study

This paper presents a systematic methodology based on the application of artificial neural networks for sequencing batch reactor (SBR) identification. The SBR is a fill-and-draw biological wastewater technology, which is specially suited for nutrient removal. The proposed approach makes optimal use of the available data during the training stage and it is aimed at achieving high generalization ability. For this purpose, a wide range of experimental conditions, including different solids retention times and influent characteristics, has been used. The methodology is successfully applied to develop a soft-sensor for monitoring a laboratory-scale SBR operated for enhanced biological phosphorus removal. The main interest is the utilization of the soft-sensor to determine the optimal length of the SBR stages within each cycle according to the actual process requirements. Note that SBRs are normally operated with constant predefined duration of the stages, thus, resulting in low efficient operation. Data obtained from the on-line electronic sensors installed in the SBR and from the control quality laboratory analysis have been used to develop the optimal architecture of two different ANNs. The ANNs were trained for on-line prediction of phosphorus (P) concentration in the SBR. One ANN uses only inexpensive and reliable on-line measurements as input data and the other one also includes as input the previous P measurement (lag −1), thus considering the quality variable dynamics. The latter ANN can be used to overcome the delay introduced by the measurement procedure of phosphorus concentration. The results have shown that the developed models can be used as efficient and cost-effective predictive tools for the system analysed, since they accurately reproduced the phosphorus behaviour in the SBR.

A systematic approach for fine-tuning of fuzzy controllers applied to WWTPs

A systematic approach for fine-tuning fuzzy controllers has been developed and evaluated for an aeration control system implemented in a WWTP. The challenge with the application of fuzzy controllers to WWTPs is simply that they contain many parameters, which need to be adjusted for different WWTP applications. To this end, a methodology based on model simulations is used that employs three statistical methods: (i) Monte-Carlo procedure: to find proper initial conditions, (ii) Identifiability analysis: to find an identifiable parameter subset of the fuzzy controller and (iii) minimization algorithm: to fine-tune the identifiable parameter subset of the controller. Indeed, the initial location found by Monte-Carlo simulations provided better results than using trial and error approach when identifying parameters of the fuzzy controller. The identifiable subset was reduced to 4 parameters from a total of 33, which improved the quality of the optimization of the control system by a minimization algorithm. Overall the systematic approach considerably improved the performance of the control system as measured by the Integral Absolute Error (deviation between the set-point and the controlled variable) of the controllers. Moreover, the methodology overcomes the dependency of the initial parameter space issue typical of local identifiability analysis. All in all this systematic approach is expected to facilitate the design and application of fuzzy controllers in particular to WWTPs compared to the time-consuming and tedious trial and error approach currently used in practice.

Instrumentation, control, and automation for submerged anaerobic membrane bioreactors.

A submerged anaerobic membrane bioreactor (AnMBR) demonstration plant with two commercial hollow-fibre ultrafiltration systems (PURON®, Koch Membrane Systems, PUR-PSH31) was designed and operated for urban wastewater treatment. An instrumentation, control, and automation (ICA) system was designed and implemented for proper process performance. Several single-input-single-output (SISO) feedback control loops based on conventional on–off and PID algorithms were implemented to control the following operating variables: flow-rates (influent, permeate, sludge recycling and wasting, and recycled biogas through both reactor and membrane tanks), sludge wasting volume, temperature, transmembrane pressure, and gas sparging. The proposed ICA for AnMBRs for urban wastewater treatment enables the optimization of this new technology to be achieved with a high level of process robustness towards disturbances.

Low cost-sensors as a real alternative to on-line nitrogen analysers in continuous systems

This paper is focused on the evaluation of the applicability of low-cost sensors (pH and ORP) versus nutrient analysers for controlling biological nitrogen removal in WWTPs. A nutrient removal pilot plant located in Carraixet WWTP (Valencia, Spain) that is equipped with a significant number of nutrient analysers and low-cost sensors was used. The relations between reliable, cheap on-line sensors such as pH and ORP (located in anaerobic, anoxic and aerobic zones) and the nitrification/denitrification processes are provided. The nitrification process can be evaluated by measuring the pH difference between the first and last aerobic zones. The denitrification process can be evaluated by measuring the pH difference between the first and last anoxic zones and the ORP in the last anoxic zone. Furthermore, when WWTPs include an anaerobic reactor, the ORP in the anaerobic zone can also be used. With all these factors in mind, these sensors give valuable information for applying advanced control systems such as fuzzy logic-based controllers. Also, low-cost sensors involve lower investment, maintenance and operational costs and lower energy consumption derived from aeration and pumping than nutrient analysers. Thus, low-cost sensors can be successfully used as an attractive alternative to nutrient analysers to control biological nitrogen removal in WWTPs.

Modelling of an activated primary settling tank including the fermentation process and VFA elutriation

A complete model of a primary settler including both sedimentation and biological processes is presented. It is a one-dimensional model based on the solids flux concept and the conservation of mass that uses the Takács model for the settling velocity, which is corrected by a compression function in the lower layers. The biological model is based on the ASM2 and enlarged with the fermentation model proposed by this research group. The settler was split in ten layers and the flux terms in the mass balance for each layer is obtained by means of the settling model. A pilot plant has been operated to study the primary sludge fermentation and volatile fatty acids (VFA) elutriation in a primary settler tank. The model has been tested with pilot plant experimental data with very good results. It has been able to simulate the VFA production in the settler and their elutriation with the influent wastewater for all the studied experiments. The developed model is easily applicable to secondary settlers and thickeners, also taking into account biological activity inside them.

Calibration of denitrifying activity of polyphosphate accumulating organisms in an extended ASM2d model

This paper presents the results of an experimental study for the modelling and calibration of denitrifying activity of polyphosphate accumulating organisms (PAOs) in full-scale WWTPs that incorporate simultaneous nitrogen and phosphorus removal. The convenience of using different yields under aerobic and anoxic conditions for modelling biological phosphorus removal processes with the ASM2d has been demonstrated. Thus, parameter η(PAO) in the model is given a physical meaning and represents the fraction of PAOs that are able to follow the DPAO metabolism. Using stoichiometric relationships, which are based on assumed biochemical pathways, the anoxic yields considered in the extended ASM2d can be obtained as a function of their respective aerobic yields. Thus, this modification does not mean an extra calibration effort to obtain the new parameters. In this work, an off-line calibration methodology has been applied to validate the model, where general relationships among stoichiometric parameters are proposed to avoid increasing the number of parameters to calibrate. The results have been validated through a UCT scheme pilot plant that is fed with municipal wastewater. The good concordance obtained between experimental and simulated values validates the use of anoxic yields as well as the calibration methodology. Deterministic modelling approaches, together with off-line calibration methodologies, are proposed to assist in decision-making about further process optimization in biological phosphate removal, since parameter values obtained by off-line calibration give valuable information about the activated sludge process such as the amount of DPAOs in the system.