Full-scale anaerobic sequencing batch biofilm reactor for sulfate-rich wastewater treatment

This paper describes the performance and biofilm characteristics of a full-scale anaerobic sequencing batch biofilm reactor (ASBBR; 20 m(3)) containing biomass immobilized on an inert support (mineral coal) for the treatment of industrial wastewater containing a high sulfate concentration. The ASBBR reactor was operated during 110 cycles (48 h each) at sulfate loading rates ranging from 6.9 to 62.4 kgSO(4)(2-)/cycle corresponding to sulfate concentrations of 0.58-5.2 gSO(4)(2-)/L. Domestic sewage and ethanol were utilized as electron donors for sulfate reduction. After 71 cycles the mean sulfate removal efficiency was 99%, demonstrating a high potential for biological sulfate reduction. The biofilm formed in the reactor occurred in two different patterns, one at the beginning of the colonization and the other of a mature biofilm. These different colonization patterns are due to the low adhesion of the microorganisms on the inert support in the start-up period. The biofilm population is mainly made up of syntrophic consortia among sulfate-reducing bacteria and methanogenic archaea such as Methanosaeta spp.

Effect of Fill Time on the Performance of Pilot-scale ASBR and AnSBBR Applied to Sanitary Wastewater Treatment

Many lab-scale studies have been carried out regarding the effect of feed strategy on the performance of anaerobic sequencing batch reactors (ASBR); however, more detailed pilot-scale studies should be performed to assess the real applicability of this type of operation. Therefore, the objective of this work was to assess the effect of feed strategy or fill time in a 1-m(3) mechanically stirred pilot-scale sequencing batch reactor, treating 0.65 m(3) sanitary wastewater in 8-h cycles at ambient temperature. Two reactor configurations were used: one containing granular biomass (denominated ASBR) and the other immobilized biomass on polyurethane foam as inert support (denominated anaerobic sequencing batch biofilm reactor (AnSBBR)). The reactors were operated under five distinct feed strategies, namely: typical batch and fed-batch for 25%, 50%, 75%, and 100% of the cycle length. Stirring frequency in the ASBR was 40 rpm with two flat-blade turbine impellers and 80 rpm in the AnSBBR with two helix impellers. The results showed that both the ASBR and AnSBBR when operated under typical batch, fed-batch for 50% and 75% of the cycle length, presented improved organic matter removal efficiencies, without significant differences in performance, thus showing important operational flexibility. In addition, the reactors presented operation stability under all conditions.

Influence of carbon sources and C/N ratio on EPS production in anaerobic sequencing batch biofilm reactors for wastewater treatment

The objective of this work was to evaluate the influence of different carbon sources and the carbon/nitrogen ratio (C/N) on the production and main composition of insoluble extracellular polymers (EPS) produced in an anaerobic sequencing batch biofilm reactor (ASBBR) with immobilized biomass in polyurethane foam. The yield of EPS was 23.6 mg/g carbon, 13.3 mg/g carbon, 9.0 mg/g carbon and 1.4 mg/g carbon when the reactor was fed with glucose, soybean oil. fat acids, and meat extract, respectively. The yield of EPS decreased from 23.6 to 2.6 mg/g carbon as the C/N ratio was decreased from 13.6 to 3.4 gC/gN, using glucose as carbon source. EPS production was not observed under strict anaerobic conditions. The results suggest that the carbon source, microaerophilic conditions and high C/N ratio favor EPS production in the ASBBR used for wastewater treatment. Cellulose was the main exopolysaccharide observed in all experimental conditions. (C) 2009 Elsevier Ltd. All rights reserved.

Anaerobic sequencing batch biofilm reactor applied to automobile industry wastewater treatment: Volumetric loading rate and feed strategy effects

This paper presents a technological viability study of wastewater treatment in an automobile industry by an anaerobic sequencing batch biofilm reactor containing immobilized biomass (AnSBBR) with a draft tube. The reactor was operated in 8-h cycles, with agitation of 400 rpm, at 30 degrees C and treating 2.0 L wastewater per cycle. Initially the efficiency and stability of the reactor were studied when supplied with nutrients and alkalinity. Removal efficiency of 88% was obtained at volumetric loading rate (VLR) of 3.09 mg COD/L day. When VLR was increased to 6.19 mg COD/L day the system presented stable operation with reduction in efficiency of 71%. In a second stage the AnSBBR was operated treating wastewater in natura, i.e., without nutrients supplementation, only with alkalinity, thereby changing feed strategy. The first strategy consisted in feeding 2.0 L batch wise (10 min), the second in feeding 1.0 L of influent batch wise (10 min) and an additional 1.0 L fed-batch wise (4 h), both dewatering 2.0 L of the effluent in 10 min. The third one maintained 1.0 L of treated effluent in the reactor, without discharging, and 1.0 L of influent was fed fed-batch wise (4 h) with dewatering 1.0 L of the effluent in 10 min. For all implemented strategies (VLR of 1.40, 2.57 and 2.61 mg COD/L day) the system presented stability and removal efficiency of approximately 80%. These results show that the AnSBBR presents operational flexibility, as the influent can be fed according to industry availability. In industrial processes this is a considerable advantage, as the influent may be prone to variations. Moreover, for all the investigated conditions the kinetic parameters were obtained from fitting a first-order model to the profiles of organic matter, total volatile acids and methane concentrations. Analysis of the kinetic parameters showed that the best strategy is feeding 1.0 L of influent batchwise (10 min) and 1.0 L fed-batch wise (4 h) in 8-h cycle. (c) 2007 Elsevier B.V. All rights reserved.

Water Treatment Plant Sludge Discharge to Wastewater Treatment Works: Effects on the Operation of Upflow Anaerobic Sludge Blanket Reactor and Activated Sludge Systems

This experiment examined the effects of the discharge of water treatment plant (WTP) sludge into the following three types of wastewater treatment systems: a pilot-scale upflow anaerobic sludge blanket (UASB) reactor, a pilot-scale activated sludge system, and a full-scale activated sludge sequencing batch reactor (SBR). The UASB reactor received 50 mg of suspended solids ( SS) of WTP sludge per liter of wastewater in the first phase, and, in the second phase, it received 75 mg SS/L. The pilot-scale activated sludge system received 25 and 50 mg SS/L in the first and second phases, respectively. The full-scale WWTP ( SBR) received approximately 74 mg SS/L. The results of the experiments showed that, despite some negative effects on nitrification, there were positive effects on phosphorus removal, and, furthermore, there was the addition of solids in all systems. Water Environ. Res., 82, 392 ( 2010).

Engineered ecosystem for sustainable on-site wastewater treatment

A Pilot-Scale Engineered Ecosystem (PSEE) operated for over two years in sub-tropical conditions, produced an effluent with COD (median 38 mg/L) and TSS (median 3 mg/L) levels comparable to that required by the AS/NZS 1547:2000 Onsite Domestic Wastewater Management standard. Only partial nitrification was achieved as dissimilatory nitrate reduction to ammonia occurred; however the level of NH4-N was reduced by 75% and total inorganic nitrogen by 53%. Phosphorus was not removed by the system due to the lack of regular sludge removal. Mass balances around the system showed that bacteria removed 36% of the influent nitrogen and 76% of the influent COD. Algae and plants were shown to remove 5% of the influent nitrogen, and 6% of the influent phosphorus. Challenges in developing a sustainable on-site wastewater treatment system were largely met by minimising chemical, energy and labour inputs, eliminating the need for frequent sludge handling, and creating an effluent quality suitable for re-use in non-potable applications. However, the sludge removal from the system needs to be adequately managed to avoid excessive accumulation as this can cause a range of negative impacts.

Supervisory control of wastewater treatment plants by combining principal component analysis and fuzzy c-means clustering

In this paper a methodology for integrated multivariate monitoring and control of biological wastewater treatment plants during extreme events is presented. To monitor the process, on-line dynamic principal component analysis (PCA) is performed on the process data to extract the principal components that represent the underlying mechanisms of the process. Fuzzy c-means (FCM) clustering is used to classify the operational state. Performing clustering on scores from PCA solves computational problems as well as increases robustness due to noise attenuation. The class-membership information from FCM is used to derive adequate control set points for the local control loops. The methodology is illustrated by a simulation study of a biological wastewater treatment plant, on which disturbances of various types are imposed. The results show that the methodology can be used to determine and co-ordinate control actions in order to shift the control objective and improve the effluent quality.

Operating space diagrams: a tool for designers of wastewater treatment plants

Recent years have seen the introduction of new and varied designs of activated sludge plants. With increasing needs for higher efficiencies and lower costs, the possibility of a plant that operates more effectively has created the need for tools that can be used to evaluate and compare designs at the design stage. One such tool is the operating space diagram. It is the aim of this paper to present this tool and demonstrate its application and relevance to design using a simple case study. In the case study, use of the operating space diagram suggested changes in design that would improve the flexibility of the process. It also was useful for designing suitable control strategies.

Sludge population optimisation: a new dimension for the control of biological wastewater treatment systems

The activated sludge comprises a complex microbiological community. The structure (what types of microorganisms are present) and function (what can the organisms do and at what rates) of this community are determined by external physico -chemical features and by the influent to the sewage treatment plant. The external features we can manipulate but rarely the influent. Conventional control and operational strategies optimise activated sludge processes more as a chemical system than as a biological one. While optimising the process in a short time period, these strategies may deteriorate the long-term performance of the process due to their potentially adverse impact on the microbial properties. Through briefly reviewing the evidence available in the literature that plant design and operation affect both the structure and function of the microbial community in activated sludge, we propose to add sludge population optimisation as a new dimension to the control of biological wastewater treatment systems. We stress that optimising the microbial community structure and property should be an explicit aim for the design and operation of a treatment plant. The major limitations to sludge population optimisation revolve around inadequate microbiological data, specifically community structure, function and kinetic data. However, molecular microbiological methods that strive to provide that data are being developed rapidly. The combination of these methods with the conventional approaches for kinetic study is briefly discussed. The most pressing research questions pertaining to sludge population optimisation are outlined. (C) 2002 Elsevier Science Ltd. All rights reserved.

Glycogen-accumulating organisms in laboratory-scale and full scale wastewater treatment processes

Laboratory-scale sequencing batch reactors (SBRs) as models for wastewater treatment processes were used to identify glycogen-accumulating organisms (GAOs), which are thought to be responsible for the deterioration of enhanced biological phosphorus removal (EBPR). The SBRs (called Q and T), operated under alternating anaerobic-aerobic conditions typical for EBPR, generated mixed microbial communities (sludges) demonstrating the GAO phenotype. Intracellular glycogen and poly-beta-hydroxyalkanoate (PHA) transformations typical of efficient EBPR occurred but polyphosphate was not bioaccumulated and the sludges contained 1.8% P (sludge Q) and 1.5% P (sludge T). 16S rDNA clone libraries were prepared from DNA extracted from the Q and T sludges. Clone inserts were grouped into operational taxonomic units (OTUs) by restriction fragment length polymorphism banding profiles. OTU representatives were sequenced and phylogenetically analysed. The Q sludge library comprised four OTUs and all six determined sequences were 99.7% identical, forming a cluster in the gamma-Proteobacteria radiation. The T sludge library comprised eight OTUs and the majority of clones were Acidobacteria subphylum 4 (49% of the library) and candidate phylum OPU (39% of the library). One OTU (two clones, of which one was sequenced) was in the gamma-Proteobacteria radiation with 95% sequence identity to the Q sludge clones. Oligonucleotide probes (called GAOQ431 and GAOQ989) were designed from the gamma-Proteobacteria clone sequences for use in fluorescence in situ hybridization (FISH); 92 % of the Q sludge bacteria and 28 % of the T sludge bacteria bound these probes in FISH. FISH and post-FISH chemical staining for PHA were used to determine that bacteria from a novel gamma-Proteobacteria cluster were phenotypically GAOs in one laboratory-scale SBR and two fullscale wastewater treatment plants. It is suggested that the GAOs from the novel cluster in the gamma-Proteobacteria radiation be named 'Candidatus Competibacter phosphatis'.

A hedging point strategy - balancing effluent quality, economy and robustness in the control of wastewater treatment plants

An operational space map is an efficient tool to compare a large number of operational strategies to find an optimal choice of setpoints based on a multicriterion. Typically, such a multicriterion includes a weighted sum of cost of operation and effluent quality. Due to the relative high cost of aeration such a definition of optimality result in a relatively high fraction of the effluent total nitrogen in the form of ammonium. Such a strategy may however introduce a risk into operation because a low degree of ammonium removal leads to a low amount of nitrifiers. This in turn leads to a reduced ability to reject event disturbances, such as large variations in the ammonium load, drop in temperature, the presence of toxic/inhibitory compounds in the influent etc. Hedging is a risk minimisation tool, with the aim to "reduce one's risk of loss on a bet or speculation by compensating transactions on the other side" (The Concise Oxford Dictionary (1995)). In wastewater treatment plant operation hedging can be applied by choosing a higher level of ammonium removal to increase the amount of nitrifiers. This is a sensible way to introduce disturbance rejection ability into the multi criterion. In practice, this is done by deciding upon an internal effluent ammonium criterion. In some countries such as Germany, a separate criterion already applies to the level of ammonium in the effluent. However, in most countries the effluent criterion applies to total nitrogen only. In these cases, an internal effluent ammonium criterion should be selected in order to secure proper disturbance rejection ability.

Adaptive multiscale principal components analysis for online monitoring of wastewater treatment

Fault detection and isolation (FDI) are important steps in the monitoring and supervision of industrial processes. Biological wastewater treatment (WWT) plants are difficult to model, and hence to monitor, because of the complexity of the biological reactions and because plant influent and disturbances are highly variable and/or unmeasured. Multivariate statistical models have been developed for a wide variety of situations over the past few decades, proving successful in many applications. In this paper we develop a new monitoring algorithm based on Principal Components Analysis (PCA). It can be seen equivalently as making Multiscale PCA (MSPCA) adaptive, or as a multiscale decomposition of adaptive PCA. Adaptive Multiscale PCA (AdMSPCA) exploits the changing multivariate relationships between variables at different time-scales. Adaptation of scale PCA models over time permits them to follow the evolution of the process, inputs or disturbances. Performance of AdMSPCA and adaptive PCA on a real WWT data set is compared and contrasted. The most significant difference observed was the ability of AdMSPCA to adapt to a much wider range of changes. This was mainly due to the flexibility afforded by allowing each scale model to adapt whenever it did not signal an abnormal event at that scale. Relative detection speeds were examined only summarily, but seemed to depend on the characteristics of the faults/disturbances. The results of the algorithms were similar for sudden changes, but AdMSPCA appeared more sensitive to slower changes.

A framework for extreme-event control in wastewater treatment

In this paper an approach to extreme event control in wastewater treatment plant operation by use of automatic supervisory control is discussed. The framework presented is based on the fact that different operational conditions manifest themselves as clusters in a multivariate measurement space. These clusters are identified and linked to specific and corresponding events by use of principal component analysis and fuzzy c-means clustering. A reduced system model is assigned to each type of extreme event and used to calculate appropriate local controller set points. In earlier work we have shown that this approach is applicable to wastewater treatment control using look-up tables to determine current set points. In this work we focus on the automatic determination of appropriate set points by use of steady state and dynamic predictions. The performance of a relatively simple steady-state supervisory controller is compared with that of a model predictive supervisory controller. Also, a look-up table approach is included in the comparison, as it provides a simple and robust alternative to the steady-state and model predictive controllers, The methodology is illustrated in a simulation study.