Giuseppe Guglielmi

Activated sludge model (ASM) based modelling of membrane bioreactor (MBR) processes: a critical review with special regard to MBR specificities.

Membrane bioreactors (MBRs) have been increasingly employed for municipal and industrial wastewater treatment in the last decade. The efforts for modelling of such wastewater treatment systems have always targeted either the biological processes (treatment quality target) as well as the various aspects of engineering (cost effective design and operation). The development of Activated Sludge Models (ASM) was an important evolution in the modelling of Conventional Activated Sludge (CAS) processes and their use is now very well established. However, although they were initially developed to describe CAS processes, they have simply been transferred and applied to MBR processes. Recent studies on MBR biological processes have reported several crucial specificities: medium to very high sludge retention times, high mixed liquor concentration, accumulation of soluble microbial products (SMP) rejected by the membrane filtration step, and high aeration rates for scouring purposes. These aspects raise the question as to what extent the ASM framework is applicable to MBR processes. Several studies highlighting some of the aforementioned issues are scattered through the literature. Hence, through a concise and structured overview of the past developments and current state-of-the-art in biological modelling of MBR, this review explores ASM-based modelling applied to MBR processes. The work aims to synthesize previous studies and differentiates between unmodified and modified applications of ASM to MBR. Particular emphasis is placed on influent fractionation, biokinetics, and soluble microbial products (SMPs)/exo-polymeric substances (EPS) modelling, and suggestions are put forward as to good modelling practice with regard to MBR modelling both for end-users and academia. A last section highlights shortcomings and future needs for improved biological modelling of MBR processes.

Modelling respirometric tests for the assessment of kinetic and stoichiometric parameters on MBBR biofilm for municipal wastewater treatment

Moving Bed Biofilm Reactor (MBBR) technology is a suitable option for up-grading and retro-fitting wastewater treatment plants. Although being introduced in late 80s, design and operational guidelines of MBBR are mainly based on empirical approaches. This work was aimed to assess the biokinetics on both detached and undisturbed biofilm samples from a large pilot-scale MBBR treating pre-settled municipal wastewater. Experimental OUR profiles of heterotrophic biomass in detached and undisturbed biofilm have been obtained with respirometric tests and then modelled with an extended version of ASM3 which assumes biomass growth to take place on both readily biodegradable substrate and storage products. Results indicated the storage mechanism to be prevalent for heterotrophic biomass growth, with a 80% fraction of soluble substrate converted into storage products. The active heterotrophic biomass in the film was estimated in detached biofilm samples; on average, it corresponded to a 39% fraction of particulate COD. Tests on undisturbed biofilm were carried out to quantify autotrophic ammonia and nitrite removal, showing an effective specialisation of the nitrifying biomass. The parameters obtained could support a more rational design approach for the moving-bed biofilm process.

Impact of chemical cleaning and air-sparging on the critical and sustainable flux in a flat sheet membrane bioreactor for municipal wastewater treatment

The paper discusses the experimental optimisation of both chemical and mechanical cleaning procedures for a flat-sheet submerged membrane bioreactor fed with municipal wastewater. Fouling was evaluated by means of the critical flux concept, which was experimentally measured by short-term flux-stepping tests. By keeping constant most important parameters of the biological process (MLSS, sludge age), two different chemical cleaning protocols (2,000 mg L(-1) NaOCl and 200 mg L(-1) NaOCl) were applied with different frequency and, after approximately 9 months of operation, the criticality threshold was determined under different values of SAD(m) (specific aeration demand per unit of membrane surface area). The weaker and more frequent chemical cleaning regime (200 mg L(-1), monthly) proved much more effective than the stronger and less frequent strategy (2,000 mg L(-1), once every three months). The improvement of performances was quantified by two TMP-based parameters, the fouling rate and the DeltaTMP (difference between TMP values during the increasing and decreasing phase of hysteresis). The best performing configuration was then checked over a longer period by running four long-term trials showing an exponential trend of the sub-critical fouling rate with the imposed flux.

Multivariate statistically-based modelling of a membrane bioreactor for wastewater treatment using 2D fluorescence monitoring data

This work presents the development of multivariate statistically-based models for monitoring several key performance parameters of membrane bioreactors (MBR) for wastewater treatment. This non-mechanistic approach enabled the deconvolution of 2D fluorescence spectroscopy data, a powerful technique that has previously been shown to capture important information regarding MBR performance. Projection to latent structure (PLS) modelling was used to integrate 2D fluorescence data, after compression through parallel factor analysis (PARAFAC), with operation and analytical data to describe an MBR fouling indicator (transmembrane pressure, TMP), five descriptors of the effluent quality (total COD, soluble COD, concentration of nitrite and nitrate, total nitrogen and total phosphorus in the permeate) and the biomass concentration in the bioreactor (MLSS). A multilinear correlation was successfully established for TMP, CODtp and CODsp, whereas the optimised models for the remaining outputs included quadratic and interaction terms of the compressed 2D fluorescence matrices. Additionally, the coefficients of the optimised models revealed important contributions of some of the input parameters to the modelled outputs. This work demonstrates the applicability of 2D fluorescence and statistically-based models to simultaneously monitor multiple key MBR performance parameters with minimal analytical effort. This is a promising approach to facilitate the implementation of MBR technology for wastewater treatment.

Real-time monitoring of membrane bioreactors with 2D-fluorescence data and statistically based models

The application of membrane bioreactors (MBR) for wastewater treatment is growing worldwide due to their compactness and high effluent quality. However, membrane fouling, mostly associated to biological products, can reduce MBR performance. Therefore, it is important to monitor MBRs as close to real-time as possible to accelerate control actions for maximal biological and membrane performance. 2D-fluorescence spectroscopy is a promising on-line tool to simultaneously monitor wastewater treatment efficiency and the formation of potential biological fouling agents. In this study, 2D-fluorescence data obtained from the wastewater and the permeate of a MBR was successfully modelled using projection to latent structures (PLS) to monitor variations in the influent and effluent total chemical oxygen demand (COD). Analysis of the results also indicated that humic acids and proteins highly contributed to the measured COD in both streams. Nevertheless, this approach was not valid for other performance parameters of the MBR system (such as influent and effluent ammonia and phosphorus), which is usually characterised through a high number of analytical and operating parameters. Principal component analysis (PCA) was thus used to find possible correlations between these parameters, in an attempt to reduce the analytical effort required for full MBR characterisation and to reduce the time frame necessary to obtain monitoring results. The 3 first principal components, capturing 57% of the variance, indicated and confirmed expected relationships between the assessed parameters. However, this approach alone could not provide robust enough correlations to enable the elimination of parameters for process description (PCA loadings ≤ 0.5). Nevertheless, it is possible that the information captured by 2D-fluorescence spectroscopy could replace some of the analytical and operating parameters, since this technique was able to successfully describe influent and effluent total COD. It is thus proposed that combined modelling of 2D-fluorescence data and selected performance/operating parameters should be further explored for efficient MBR monitoring aiming at rapid process control.

Membrane bioreactors for winery wastewater treatment: case-studies at full scale.

The membrane bioreactor technology (MBR) is nowadays a suitable alternative for winery wastewater treatment, thanks to low footprint, complete suspended solids removal, high efficiency in COD abatement and quick start-up. In this paper, data from two full-scale MBRs equipped with flat-sheet membranes (plant A and plant B) are presented and discussed. COD characterisation by respirometry pointed out the high biodegradability degree of both wastewater, with a strong prevalence of the readily biodegradable fraction. An extended version of Activated Sludge Model No. 3 was used to fit the experimental OUR profiles and to assess the maximum growth rate of heterotrophic biomass on sludge samples collected at both sites; the stoichiometric yield coefficients were also calculated. Sludge filterability and dewaterability were investigated with batch tests; laboratory results confirmed the field observations. Finally, some considerations are listed, aimed at defining possible key-issues for optimal process design and operation.

Development of a hybrid model strategy for monitoring membrane bioreactors.

In the present study, the performance of a membrane bioreactor (MBR) was modelled using a hybrid approach based on the activated sludge model number 3 (ASM3) combined with projection to latent structures (PLS) to predict the residuals of the ASM. The application of ASM to MBRs requires frequent re-calibration to adjust the model to variations in influent characteristics, determined through time-consuming analysis and batch tests. Considering this problem, the objective of this study was to improve ASM prediction ability with minimal additional monitoring effort. Hybrid models were developed to predict three MBR performance parameters: mixed liquor suspended solids (MLSS), COD in the permeate (CODp) and nitrite and nitrate concentration in the permeate (NOxp). For PLS modelling of ASM residuals three input strategies were used: (1) analytic and operating data; (2) operating data plus 2D fluorescence spectroscopy; (3) all the data. The first input strategy improved ASM prediction of the three selected outputs, and highlighted the lack of detailed and real-time information from wastewater and operating parameters in the ASM used in this study. In the second input strategy, the incorporation of updated data from 2D fluorescence spectroscopy resulted on better model fitting than in the first input strategy, for all the output parameters studied. Through the hybrid modelling approach it was possible to significantly improve the ASM predictions in real-time using 2D fluorescence measurements and other relevant parameters acquired on-line, without requiring further laboratory analysis. Furthermore, the third input strategy, incorporating all the collected data, did not significantly improve the prediction of the outputs beyond the second strategy. This shows that 2D fluorescence spectroscopy is a comprehensive monitoring tool, able to capture on-line the required information to complement, through hybrid modelling, the mechanistic information described by an ASM.