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.

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.

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.

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).

High occurrence of hepatitis E virus in samples from wastewater treatment plants in Switzerland and comparison with other enteric viruses.

Hepatitis E virus (HEV) is responsible for many enterically transmitted viral hepatitides around the world. It is currently one of the waterborne diseases of global concern. In industrialized countries, HEV appears to be more common than previously thought, even if it is rarely virulent. In Switzerland, seroprevalence studies revealed that HEV is endemic, but no information was available on its environmental spread. The aim of this study was to investigate -using qPCR- the occurrence and concentration of HEV and three other viruses (norovirus genogroup II, human adenovirus-40 and porcine adenovirus) in influents and effluents of 31 wastewater treatment plants (WWTPs) in Switzerland. Low concentrations of HEV were detected in 40 out of 124 WWTP influent samples, showing that HEV is commonly present in this region. The frequency of HEV occurrence was higher in summer than in winter. No HEV was detected in WWTP effluent samples, which indicates a low risk of environmental contamination. HEV occurrence and concentrations were lower than those of norovirus and adenovirus. The autochthonous HEV genotype 3 was found in all positive samples, but a strain of the non-endemic and highly pathogenic HEV genotype I was isolated in one sample, highlighting the possibility of environmental circulation of this genotype. A porcine fecal marker (porcine adenovirus) was not detected in HEV positive samples, indicating that swine are not the direct source of HEV present in wastewater. Further investigations will be necessary to determine the reservoirs and the routes of dissemination of HEV.

Prediction of the bulking phenomenon in wastewater treatment plants

The control and prediction of wastewater treatment plants poses an important goal: to avoid breaking the environmental balance by always keeping the system in stable operating conditions. It is known that qualitative information — coming from microscopic examinations and subjective remarks — has a deep influence on the activated sludge process. In particular, on the total amount of effluent suspended solids, one of the measures of overall plant performance. The search for an input–output model of this variable and the prediction of sudden increases (bulking episodes) is thus a central concern to ensure the fulfillment of current discharge limitations. Unfortunately, the strong interrelationbetween variables, their heterogeneity and the very high amount of missing information makes the use of traditional techniques difficult, or even impossible. Through the combined use of several methods — rough set theory and artificial neural networks, mainly — reasonable prediction models are found, which also serve to show the different importance of variables and provide insight into the process dynamics

Application of a support system to the design of wastewater treatment plants

This paper presents a case study that explores the advantages that can be derived from the use of a design support system during the design of wastewater treatment plants (WWTP). With this objective in mind a simplified but plausible WWTP design case study has been generated with KBDS, a computer-based support system that maintains a historical record of the design process. The study shows how, by employing such a historical record, it is possible to: (1) rank different design proposals responding to a design problem; (2) study the influence of changing the weight of the arguments used in the selection of the most adequate proposal; (3) take advantage of keywords to assist the designer in the search of specific items within the historical records; (4) evaluate automatically thecompliance of alternative design proposals with respect to the design objectives; (5) verify the validity of previous decisions after the modification of the current constraints or specifications; (6) re-use the design records when upgrading an existing WWTP or when designing similar facilities; (7) generate documentation of the decision making process; and (8) associate a variety of documents as annotations to any component in the design history. The paper also shows one possible future role of design support systems as they outgrow their current reactive role as repositories of historical information and start to proactively support the generation of new knowledge during the design process

Assessment of airborne virus contamination in wastewater treatment plants

INTRODUCTION: Occupational exposure to bioaerosols in wastewater treatment plants (WWTP) and its consequence on workers׳ health are well documented. Most studies were devoted to enumerating and identifying cultivable bacteria and fungi, as well as measuring concentrations of airborne endotoxins, as these are the main health-related factors found in WWTP. Surprisingly, very few studies have investigated the presence and concentrations of airborne virus in WWTP. However, many enteric viruses are present in wastewater and, due to their small size, they should become aerosolized. Two in particular, the norovirus and the adenovirus, are extremely widespread and are the major causes of infectious gastrointestinal diseases reported around the world. The third one, hepatitis E virus, has an emerging status. GOAL AND METHODS: This study׳s objectives were to detect and quantify the presence and concentrations of 3 different viruses (adenovirus, norovirus and the hepatitis E virus) in air samples from 31 WWTPs by using quantitative polymerase chain reaction (qPCR) during two different seasons and two consecutive years. RESULTS: Adenovirus was present in 100% of summer WWTP samples and 97% of winter samples. The highest airborne concentration measured was 2.27×10(6) genome equivalent/m(3) and, on average, these were higher in summer than in winter. Norovirus was detected in only 3 of the 123 air samples, and the hepatitis E virus was not detected. CONCLUSIONS: Concentrations of potentially pathogenic viral particles in WWTP air are non-negligible and could partly explain the work-related gastrointestinal symptoms often reported in employees in this sector.

Neural networks complemented with genetic algorithms and fuzzy systems for predicting nitrogenous effluent variables in wastewater treatment plants

This work focuses on the prediction of the two main nitrogenous variables that describe the water quality at the effluent of a Wastewater Treatment Plant. We have developed two kind of Neural Networks architectures based on considering only one output or, in the other hand, the usual five effluent variables that define the water quality: suspended solids, biochemical organic matter, chemical organic matter, total nitrogen and total Kjedhal nitrogen. Two learning techniques based on a classical adaptative gradient and a Kalman filter have been implemented. In order to try to improve generalization and performance we have selected variables by means genetic algorithms and fuzzy systems. The training, testing and validation sets show that the final networks are able to learn enough well the simulated available data specially for the total nitrogen

DAI-DEPUR: an integrated and distributed architecture for wastewater treatment plants supervision

The activated sludge process - the main biological technology usually applied towastewater treatment plants (WWTP) - directly depends on live beings (microorganisms), and therefore on unforeseen changes produced by them. It could be possible to get a good plant operation if the supervisory control system is able to react to the changes and deviations in the system and can take thenecessary actions to restore the system’s performance. These decisions are oftenbased both on physical, chemical, microbiological principles (suitable to bemodelled by conventional control algorithms) and on some knowledge (suitable to be modelled by knowledge-based systems). But one of the key problems in knowledge-based control systems design is the development of an architecture able to manage efficiently the different elements of the process (integrated architecture), to learn from previous cases (spec@c experimental knowledge) and to acquire the domain knowledge (general expert knowledge). These problems increase when the process belongs to an ill-structured domain and is composed of several complex operational units. Therefore, an integrated and distributed AIarchitecture seems to be a good choice. This paper proposes an integrated and distributed supervisory multi-level architecture for the supervision of WWTP, that overcomes some of the main troubles of classical control techniques and those of knowledge-based systems applied to real world systems

International Advanced Water Technologies Centre, IAWTC/LADEC and LUT 2013 : Questionnaire Responses from Russian Drinking Water and Wastewater Treatment Plants

In this report, information is published concerning Russian water and wastewater treatment plants. The information is based on a questionnaire sent to 70 water and wastewater treatment plants in 2012-2013. The questionnaire was prepared by the International Advanced Water Technologies Centre (IAWTC) and Lahti Development Company (LADEC). The questions dealt with an assessment of the present state, the need for changes, renovation, investments, and how to improve the efficiency of the operation by training and investments. A significant need to renew the old pipelines, constructions, and processes was clearly evident. The aggregated answers can be utilized in Russia as internal benchmarking in order to arrange training and plant visits, which were requested in many of the answers. Sharing this open report with the respondents can aid networking and awareness of HELCOM requirements which relate to waste water treatment plants discharging their waste water directly or indirectly into the Baltic Sea. The aim of this report is to provide information for Finnish small and medium size companies (SMEs) as regards possible water related exportation to different parts of Russia.

Prediction of the bulking phenomenon in wastewater treatment plants

The control and prediction of wastewater treatment plants poses an important goal: to avoid breaking the environmental balance by always keeping the system in stable operating conditions. It is known that qualitative information — coming from microscopic examinations and subjective remarks — has a deep influence on the activated sludge process. In particular, on the total amount of effluent suspended solids, one of the measures of overall plant performance. The search for an input–output model of this variable and the prediction of sudden increases (bulking episodes) is thus a central concern to ensure the fulfillment of current discharge limitations. Unfortunately, the strong interrelation between variables, their heterogeneity and the very high amount of missing information makes the use of traditional techniques difficult, or even impossible. Through the combined use of several methods — rough set theory and artificial neural networks, mainly — reasonable prediction models are found, which also serve to show the different importance of variables and provide insight into the process dynamics

Application of a support system to the design of wastewater treatment plants

This paper presents a case study that explores the advantages that can be derived from the use of a design support system during the design of wastewater treatment plants (WWTP). With this objective in mind a simplified but plausible WWTP design case study has been generated with KBDS, a computer-based support system that maintains a historical record of the design process. The study shows how, by employing such a historical record, it is possible to: (1) rank different design proposals responding to a design problem; (2) study the influence of changing the weight of the arguments used in the selection of the most adequate proposal; (3) take advantage of keywords to assist the designer in the search of specific items within the historical records; (4) evaluate automatically the compliance of alternative design proposals with respect to the design objectives; (5) verify the validity of previous decisions after the modification of the current constraints or specifications; (6) re-use the design records when upgrading an existing WWTP or when designing similar facilities; (7) generate documentation of the decision making process; and (8) associate a variety of documents as annotations to any component in the design history. The paper also shows one possible future role of design support systems as they outgrow their current reactive role as repositories of historical information and start to proactively support the generation of new knowledge during the design process