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'.

Development of a novel titration and off-gas analysis (TOGA) sensor for study of biological processes in wastewater treatment systems

The development of the new TOGA (titration and off-gas analysis) sensor for the detailed study of biological processes in wastewater treatment systems is outlined. The main innovation of the sensor is the amalgamation of titrimetric and off-gas measurement techniques. The resulting measured signals are: hydrogen ion production rate (HPR), oxygen transfer rate (OTR), nitrogen transfer rate (NTR), and carbon dioxide transfer rate (CTR). While OTR and NTR are applicable to aerobic and anoxic conditions, respectively, HPR and CTR are useful signals under all of the conditions found in biological wastewater treatment systems, namely, aerobic, anoxic and anaerobic. The sensor is therefore a powerful tool for studying the key biological processes under all these conditions. A major benefit from the integration of the titrimetric and off-gas analysis methods is that the acid/base buffering systems, in particular the bicarbonate system, are properly accounted for. Experimental data resulting from the TOGA sensor in aerobic, anoxic, and anaerobic conditions demonstrates the strength of the new sensor. In the aerobic environment, carbon oxidation (using acetate as an example carbon source) and nitrification are studied. Both the carbon and ammonia removal rates measured by the sensor compare very well with those obtained from off-line chemical analysis. Further, the aerobic acetate removal process is examined at a fundamental level using the metabolic pathway and stoichiometry established in the literature, whereby the rate of formation of storage products is identified. Under anoxic conditions, the denitrification process is monitored and, again, the measured rate of nitrogen gas transfer (NTR) matches well with the removal of the oxidised nitrogen compounds (measured chemically). In the anaerobic environment, the enhanced biological phosphorus process was investigated. In this case, the measured sensor signals (HPR and CTR) resulting from acetate uptake were used to determine the ratio of the rates of carbon dioxide production by competing groups of microorganisms, which consequently is a measure of the activity of these organisms. The sensor involves the use of expensive equipment such as a mass spectrometer and requires special gases to operate, thus incurring significant capital and operational costs. This makes the sensor more an advanced laboratory tool than an on-line sensor. (C) 2003 Wiley Periodicals, Inc.

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.

Online titrimetric and off-gas analysis for examining nitrification processes in wastewater treatment

The two steps of nitrification, namely the oxidation of ammonia to nitrite and nitrite to nitrate, often need to be considered separately in process studies. For a detailed examination, it is desirable to monitor the two-step sequence using online measurements. In this paper, the use of online titrimetric and off-gas analysis (TOGA) methods for the examination of the process is presented. Using the known reaction stoichiometry, combination of the measured signals (rates of hydrogen ion production, oxygen uptake and carbon dioxide transfer) allows the determination of the three key process rates, namely the ammonia consumption rate, the nitrite accumulation rate and the nitrate production rate. Individual reaction rates determined with the TOGA sensor under a number of operation conditions are presented. The rates calculated directly from the measured signals are compared with those obtained from offline liquid sample analysis. Statistical analysis confirms that the results from the two approaches match well. This result could not have been guaranteed using alternative online methods. As a case study, the influences of pH and dissolved oxygen (DO) on nitrite accumulation are tested using the proposed method. It is shown that nitrite accumulation decreased with increasing DO and pH. Possible reasons for these observations are discussed. (C) 2003 Elsevier Science Ltd. All rights reserved.

Cork processing wastewater treatment/valorisation by nanofiltration

Nanofiltration process for the treatment/valorisation of cork processing wastewaters was studied. A DS-5 DK 20/40 (GE Water Technologies) nanofiltration membrane/module was used, having 2.09 m(2) of surface area. Hydraulic permeability was determined with pure water and the result was 5.2 L.h(-1).m(-2).bar(-1). The membrane presents a rejection of 51% and 99% for NaCl and MgSO4 salts, respectively. Two different types of regimes were used in the wastewaters filtration process, total recycling mode and concentration mode. The first filtration regime showed that the most favourable working transmembrane pressure was 7 bar working at 25 degrees C. For the concentration mode experiments it was observed a 30% decline of the permeate fluxes when a volumetric concentration factor of 5 was reached. The permeate COD, BOD5, colour and TOC rejection values remained well above the 90% value, which allows, therefore, the concentration of organic matter (namely the tannin fraction) in the concentrate stream that can be further used by other industries. The permeate characterization showed that it cannot be directly discharged to the environment as it does not fulfil the values of the Portuguese discharge legislation. However, the permeate stream can be recycled to the process (boiling tanks) as it presents no colour and low TOC (< 60 ppm) or if wastewater discharge is envisaged we have observed that the permeate biodegradability is higher than 0.5, which renders conventional wastewater treatments feasible.

Fungal contamination in two Portuguese wastewater treatment plants

The presence of filamentous fungi was detected in wastewater and air collected at wastewater treatment plants (WWTP) from several European countries. The aim of the present study was to assess fungal contamination in two WWTP operating in Lisbon. In addition, particulate matter (PM) contamination data was analyzed. To apply conventional methods, air samples from the two plants were collected through impaction using an air sampler with a velocity air rate of 140 L/min. Surfaces samples were collected by swabbing the surfaces of the same indoor sites. All collected samples were incubated at 27°C for 5 to 7 d. After lab processing and incubation of collected samples, quantitative and qualitative results were obtained with identification of the isolated fungal species. For molecular methods, air samples of 250 L were also collected using the impinger method at 300 L/min airflow rate. Samples were collected into 10 ml sterile phosphate-buffered saline with 0.05% Triton X-100, and the collection liquid was subsequently used for DNA extraction. Molecular identification of Aspergillus fumigatus and Stachybotrys chartarum was achieved by real-time polymerase chain reaction (RT-PCR) using the Rotor-Gene 6000 qPCR Detection System (Corbett). Assessment of PM was also conducted with portable direct-reading equipment (Lighthouse, model 3016 IAQ). Particles concentration measurement was performed at five different sizes: PM0.5, PM1, PM2.5, PM5, and PM10. Sixteen different fungal species were detected in indoor air in a total of 5400 isolates in both plants. Penicillium sp. was the most frequently isolated fungal genus (58.9%), followed by Aspergillus sp. (21.2%) and Acremonium sp. (8.2%), in the total underground area. In a partially underground plant, Penicillium sp. (39.5%) was also the most frequently isolated, also followed by Aspergillus sp. (38.7%) and Acremonium sp. (9.7%). Using RT-PCR, only A. fumigatus was detected in air samples collected, and only from partial underground plant. Stachybotrys chartarum was not detected in any of the samples analyzed. The distribution of particle sizes showed the same tendency in both plants; however, the partially underground plant presented higher levels of contamination, except for PM2.5. Fungal contamination assessment is crucial to evaluating the potential health risks to exposed workers in these settings. In order to achieve an evaluation of potential health risks to exposed workers, it is essential to combine conventional and molecular methods for fungal detection. Protective measures to minimize worker exposure to fungi need to be adopted since wastewater is the predominant internal fungal source in this setting.

Aspergillus flavus contamination in two Portuguese wastewater treatment plants

Filamentous fungi from genus Aspergillus were previously detected in wastewater treatment plants (WWTP) as being Aspergillus flavus (A. flavus), an important toxigenic fungus producing aflatoxins. This study aimed to determine occupational exposure adverse effects due to fungal contamination produced by A. flavus complex in two Portuguese WWTP using conventional and molecular methodologies. Air samples from two WWTP were collected at 1 m height through impaction method. Surface samples were collected by swabbing surfaces of the same indoor sites. After counting A. flavus and identification, detection of aflatoxin production was ensured through inoculation of seven inoculates in coconut-milk agar. Plates were examined under long-wave ultraviolet (UV; 365 nm) illumination to search for the presence of fluorescence in the growing colonies. To apply molecular methods, air samples were also collected using the impinger method. Samples were collected and collection liquid was subsequently used for DNA extraction. Molecular identification of A. flavus was achieved by real-time polymerase chain reaction (RT-PCR) using the Rotor-Gene 6000 qPCR detection system (Corbett). Among the Aspergillus genus, the species that were more abundant in air samples from both WWTP were Aspergillus versicolor (38%), Aspergillus candidus (29.1%), and Aspergillus sydowii (12.7%). However, the most commonly species found on surfaces were A. flavus (47.3%), Aspergillus fumigatus (34.4%), and Aspergillus sydowii (10.8%). Aspergillus flavus isolates that were inoculated in coconut agar medium were not identified as toxigenic strains and were not detected by RT-PCR in any of the analyzed samples from both plants. Data in this study indicate the need for monitoring fungal contamination in this setting. Although toxigenic strains were not detected from A. flavus complex, one cannot disregard the eventual presence and potential toxicity of aflatoxins.

An uncertainty and sensitivity analysis applied to the prioritisation of pharmaceuticals as surface water contaminants from wastewater treatment plant direct emissions

In this study, the concentration probability distributions of 82 pharmaceutical compounds detected in the effluents of 179 European wastewater treatment plants were computed and inserted into a multimedia fate model. The comparative ecotoxicological impact of the direct emission of these compounds from wastewater treatment plants on freshwater ecosystems, based on a potentially affected fraction (PAF) of species approach, was assessed to rank compounds based on priority. As many pharmaceuticals are acids or bases, the multimedia fate model accounts for regressions to estimate pH-dependent fate parameters. An uncertainty analysis was performed by means of Monte Carlo analysis, which included the uncertainty of fate and ecotoxicity model input variables, as well as the spatial variability of landscape characteristics on the European continental scale. Several pharmaceutical compounds were identified as being of greatest concern, including 7 analgesics/anti-inflammatories, 3 β-blockers, 3 psychiatric drugs, and 1 each of 6 other therapeutic classes. The fate and impact modelling relied extensively on estimated data, given that most of these compounds have little or no experimental fate or ecotoxicity data available, as well as a limited reported occurrence in effluents. The contribution of estimated model input variables to the variance of freshwater ecotoxicity impact, as well as the lack of experimental abiotic degradation data for most compounds, helped in establishing priorities for further testing. Generally, the effluent concentration and the ecotoxicity effect factor were the model input variables with the most significant effect on the uncertainty of output results.

Behaviour and fate of metals in urban wastewater treatment plants: a review

The concerns on metals in urban wastewater treatment plants (WWTPs) are mainly related to its contents in discharges to environment, namely in the final effluent and in the sludge produced. In the near future, more restrictive limits will be imposed to final effluents, due to the recent guidelines of the European Water Framework Directive (EUWFD). Concerning the sludge, at least seven metals (Cd, Cr, Cu, Hg, Ni, Pb and Zn) have been regulated in different countries, four of which were classified by EUWFD as priority substances and two of which were also classified as hazardous substances. Although WWTPs are not designed to remove metals, the study of metals behaviour in these systems is a crucial issue to develop predictive models that can help more effectively the regulation of pre-treatment requirements and contribute to optimize the systems to get more acceptable metal concentrations in its discharges. Relevant data have been published in the literature in recent decades concerning the occurrence/fate/behaviour of metals in WWTPs. However, the information is dispersed and not standardized in terms of parameters for comparing results. This work provides a critical review on this issue through a careful systematization, in tables and graphs, of the results reported in the literature, which allows its comparison and so its analysis, in order to conclude about the state of the art in this field. A summary of the main consensus, divergences and constraints found, as well as some recommendations, is presented as conclusions, aiming to contribute to a more concerted action of future research. © 2015, Islamic Azad University (IAU).

Invited review: Models for the optimization of regional wastewater treatment systems

European Journal of Operational Research, nº 73 (1994)

The effect of water inorganic matrix in ibuprofen adsorption onto activated carbon for water and wastewater treatment

Dissertação para obtenção do Grau de Mestre em Engenharia Química e Bioquímica