Anaerobic Wastewater Treatment Plants Research Articles

Monitoring of di-(2-ethylhexyl)phthalate, nonylphenol, nonylphenol ethoxylates, and polychlorinated biphenyls in anaerobic and aerobic sewage sludge by gas chromatography–mass spectrometry

The occurrence of di-(2-ethyhexyl)phthalate (DEHP), nonylphenol and nonyphenol mono- and diethoxylates (NPEs) and seven polychlorinated biphenyl (PCB) congeners in different types of sludge samples is reported. The analysis of these compounds was carried out by sonication-assisted extraction and analytical determination by gas chromatography coupled with a mass spectrometry detector, following a previously described method. The applicability of the method was tested by monitoring the organic pollutants in primary, secondary, mixed, and digested-dehydrated sludge samples from two wastewater treatment plants (WWTPs) based on aerobic and on anaerobic biological stabilization. The occurrence of these compounds in sewage sludge and the influence of sludge stabilization process on the further farmland application of the sludge were evaluated. DEHP and NPEs were detected in all analysed sludge samples from both WWTPs at concentration levels in the range of 22.3–601 mg kg−1 and 136–2357 mg kg−1 dm (dry matter), respectively. PCBs were detected in all types of sludge analysed from the anaerobic WWTP but was not detected in any sludge sample from the aerobic WWTP. Concentration levels of the sum of the seven PCBs congeners were up to 1.5 mg kg−1 dm. The concentration of DEHP, sum of NPEs, and sum of the seven PCB congeners were higher than the limits fixed in the third draft of the future Sludge Directive for land application of sludge in the 67%, 100%, and 11% of samples from the anaerobic WWTP and in the 83%, 92%, and 0% of samples from the aerobic WWTP, respectively.

Fuzzy-Based Control of an Anaerobic Reactor Treating Wastewaters Containing Ethanol and Carbohydrates

In this work, a fuzzy logic-based system for diagnosis and control of an anaerobic wastewater treatment plant was developed. Three variables (methane production, hydrogen concentration in the gas phase, and intermediate alkalinity/total alkalinity ratio) were selected, according to previous works, as the more adequate for organic overload identification. The diagnosis and control system was developed using expert's knowledge related with normal or overload process states for establishing a set of rules considering the selected variables. The control system computes the feed flow rate for adjusting the organic load applied to the reactor. The control law is based on a response surface obtained according to fuzzy inference Mamdani methodology. The diagnosis and control system was validated at three different levels: (a) simulation with ADM1 (wastewater containing ethanol); (b) open-loop methodology using experimental data from a hybrid upflow sludge bed-filter (USBF) anaerobic pilot plant treating a wastewater containing ethanol; and (c) closed-loop control of a USBF pilot plant treating wastewater containing carbohydrates. The proposed system diagnoses correctly the different episodes, and it demonstrated a high reliability, supplying an adequate control action to achieve the desired set point as well as to manage a sudden change in influent COD. Moreover, the performance of the developed system can depend slightly of the noise in the measured variables used for determining the process state.

Evaluation of Input Variables in Adaptive-Network-Based Fuzzy Inference System Modeling for an Anaerobic Wastewater Treatment Plant under Unsteady State

A conceptual neural-fuzzy model based on adaptive-network-based fuzzy inference system (ANFIS) was proposed to estimate effluent chemical oxygen demand (COD) of a full-scale anaerobic wastewater treatment plant for a sugar factory operating at unsteady state. The fitness of simulated results was improved by adding two new input variables into the model; phase vectors of operational period and effluent COD values of last five days (history). In modeling studies, individual contribution of each input variable to the resulting model was evaluated. The addition of phase vectors and history of five days into the input variable matrix in ANFIS modeling for anaerobic wastewater treatment was applied for the first time in literature to increase the prediction power of the model. By this way, the correlation coefficient between estimated and measured values of output variable (COD) could be increased to the value of 0.8940, which is considered a good fit.

Data mining to support anaerobic WWTP monitoring

The stable and efficient operation of anaerobic wastewater treatment plants (WWTPs) is a major challenge for monitoring and control systems. Support for distributed anaerobic WWTPs through remotely monitoring their data was investigated in the TELEMAC framework. This paper describes how the accumulating filtered sensor data was mined to contribute to the refining of expert experience for insights into digester states. Visualisation techniques were used to present cluster analyses of digester states. A procedure for determining prediction intervals is described together with its application for volatile fatty acid concentrations; this procedure enables prediction risk assessment.

Comparison of two types of inocula during acclimation and stable operation for nitrophenol biodegradation in an anaerobic-aerobic SBR

This work presents a comparison of two inocula used for the acclimation of two anaerobic-aerobic sequencing batch bioreactors used for toxic wastewater treatment. The bioreactors were acclimated with different types of sludge: one coming from an anaerobic wastewater treatment plant and the other one from a conventional aerobic activated sludge plant. The model toxic compound was p-nitrophenol, which is reduced to p-aminophenol during the initial anaerobic phase of the reaction, and later mineralized during a posterior aerated reaction phase. Biodegradation of the compounds was monitored using UV/Vis spectrophotometry. After acclimation stabilization of the sludge and of the process was also monitored. Results show that there is no significant difference in acclimation times and stability of the process between the two employed inocula, and thus an originally anaerobic inoculum presents no apparent advantage over a more easily accessible aerobic one.

Application and biomolecular monitoring of psychrophilic anaerobic digestion

Thirteen anaerobic hybrid expanded granular sludge bed-anaerobic filter bioreactors were used for psychrophilic (15-18 degrees C) anaerobic digestion of a variety of synthetic and non-synthetic wastewaters, including: food-processing, dairy, aromatic- and aliphatic-containing and brewery discharges. Specific methanogenic activity assays were employed to assess temporal physiological activity dynamics. Terminal restriction fragment length polymorphism genetic fingerprinting and fluorescent in situ hybridization were used to monitor shifts in the structure of the microbial communities in the bioreactors in response to operating conditions. Treatment efficiencies obtained were comparable to previous mesophilic (37 degrees C) trials. Methanogenic activity developed under psychrophilic conditions and putative psychrophilic populations were detected within otherwise psychrotolerant mesophilic communities. Shifts in the population structure of archaeal (methanogenic) communities were more indicative of process disruption than bacterial communities. Biomolecular techniques were demonstrated as valuable tools for anaerobic wastewater treatment plant monitoring.

An integrated system to remote monitor and control anaerobic wastewater treatment plants through the internet

The TELEMAC project brings new methodologies from the Information and Science Technologies field to the world of water treatment. TELEMAC offers an advanced remote management system which adapts to most of the anaerobic wastewater treatment plants that do not benefit from a local expert in wastewater treatment. The TELEMAC system takes advantage of new sensors to better monitor the process dynamics and to run automatic controllers that stabilise the treatment plant, meet the depollution requirements and provide a biogas quality suitable for cogeneration. If the automatic system detects a failure which cannot be solved automatically or locally by a technician, then an expert from the TELEMAC Control Centre is contacted via the internet and manages the problem.

Evaluation of the Wastewater Treatment Plant of the Starch Plant of the Egyptian Starch, Yeast, and Detergents Company, Alexandria

Starches are insoluble in water. Starch is used in cooking for thickening sauces. In industry, it is used in the manufacture of adhesives, paper, and textiles. The most promising new market for corn starches is as raw material for the production of industrial chemicals and plastics which are today made from petroleum feedstock. Wastewater effluent of starch production is characterized by high total suspended solids of high organic load. The Egyptian Starch, Yeast, and Detergents Company is one of most famous factories producing food starch. It is located in Alexandria. As its final wastewater effluent highly exceeds the permissible limits of total suspended solids [TSS] and chemical oxygen demand [COD] of Decree No. 44/2000 of Low No. 93/1962, the starch company established an anaerobic wastewater treatment plant [WWTP] since 2002. The present study aimed at evaluating the existing WWTP and the compliance of its final discharge with the regulatory limits for the disposal of final wastewater into public sewer. WWTP shows stable and controlled treatment unit with high treatment efficiency. It is fruitful to apply the same technology in treatment of end pipe industrial wastes having similar characteristics.

Fuzzy Observer for the Anaerobic Digestion Process

In this paper a Takagi-Sugeno fuzzy observer for an anaerobic wastewater treatment plant is introduced. First, anaerobic digestion process is briefly explained. After that, Takagi-Sugeno systems are described. Next, observer design is presented and its performance is illustrated via simulations. Finally relevant conclusions are stated.

Diagnosis of acidification states in an anaerobic wastewater treatment plant using a fuzzy-based expert system

A fuzzy-logic-based diagnosis system for the determination of acidification states on an anaerobic wastewater treatment plant was developed. The diagnosis system uses experts’ knowledge to determine the acidification state of the process. The information of several on-line measured variables, which are classified under linguistic labels, and the expert knowledge are implemented by means of a fuzzy-based rules structure. The acidification state of the system within the anaerobic reactor is determined by means of evaluating the fuzzy inference system for the given inputs. A representative experiment of application of the developed diagnosis system to a progressive acidification caused by a hydraulic overload in the digester is presented and discussed.

On-line estimation of unmeasured inputs for anaerobic wastewater treatment processes

This paper deals with the design of an unknown input observer for anaerobic wastewater treatment plants. A key problem in bioprocessing systems is the absence, in some cases, of reliable on-line measurements for real-time monitoring applications. The objective is to develop on-line estimation of unmeasured input (i.e. unknown input) for anaerobic processes defined as unknown input affine nonlinear systems. Based on a nonlinear state space model, the design approach is to find an observable subsystem insensitive to unmeasured inputs according to the linear theory. This subsystem is used to estimate, from available on-line measurements, the state and the unmeasured inputs. This study focuses on the on-line estimation of unmeasured inputs over a wide range of simulation and a practical experimentation on a pilot plant: an anaerobic fixed bed reactor.

Expert system for the on-line diagnosis of anaerobic wastewater treatment plants

A diagnosis system for anaerobic wastewater treatment processes is presented. The system is able to recognise the state and trend of the operation and suggest the appropriate control action. The on-line variables measured were gas flow rate and composition (methane and carbon monoxide), feed and recycling flow rates, temperature and pH, while the manipulable inputs are feed, recycling and buffer-addition flow rates. The diagnosis system comprises a structured rule base, incorporating expert knowledge using fuzzy logic features. The structure of the system is based on the classification of information related to the process in three categories: i) the state of the process, ii) its trend and iii) the recommended set-point values for the inputs manipulated: feeding, buffer and recycling pumps. The system was applied to diagnose the operation of a 1.1 m3 hybrid UASB-UAF treating wastewater from a fibreboard production factory under different conditions (overload and underload), corresponding to some of the typical causes of destabilisation in anaerobic wastewater treatment plants. These situations require control action in order to maintain the stability and the treatment capacity of the reactor. The application of the system developed for the purpose of managing the situation proved to be reliable for supplying the actual state and trend of the process, as well as the adequate set point values to recover stable operation and/or to avoid further destabilisation.

An expert system for monitoring and diagnosis of anaerobic wastewater treatment plants

In this paper, an expert system (ES) developed for the monitoring and diagnosis of anaerobic wastewater treatment plants (AWT), is presented. The system was evaluated in a hybrid pilot plant of 1.1 m 3 located in an industrial environment for the treatment of wastewaters from a fibreboard production factory. The reactor is a hybrid USBF, combining an upflow anaerobic sludge blanket (UASB) in the lower part and an upflow anaerobic filter (UAF) at the top.

Advanced monitoring and control of anaerobic wastewater treatment plants: fault detection and isolation

In this paper, a fault detection and isolation approach using fuzzy logic is described for on-line analysis of problems occurring in anaerobic digestion processes. The measurements available on the process are preprocessed to build a vector of fault residuals indicating the magnitude of the problems. This vector is classified into a prespecified category (i.e., a class) which is a state of the system, according to discrimination fuzzy rules. Three different types of classes were defined in a hierarchical structure: sensors faults, sub-process faults and process faults. This approach was developed to handle in real time both technical and biological problems. Demonstration of the practical interest of this study was made using real life experiments and large improvement of the reliability and safety of the process was obtained, thus optimizing the overall wastewater treatment.

Advanced monitoring and control of anaerobic wastewater treatment plants: diagnosis and supervision by a fuzzy-based expert system

A fuzzy-based expert system (ES) for the diagnosis and supervision for anaerobic digesters is presented. The system was developed in a Microsoft Windows support using fuzzy logic inference together with a rule base for the implementation of expert knowledge. The ES runs on-line through three main modules, which determine the state and trend of the process, and the best set points for the actuation on the final control elements of the plant. Two further modules run in parallel, when they are required by the operator, using off-line and on-line information for the detection of inhibition due to toxic compounds in the process and for the validation of the on-line diagnosis. The diagnosis and supervision ES was tuned up in order to adjust the membership functions describing the process, and lately tested, running on-line, to study the response of the rule base.

Advanced monitoring and control of anaerobic wastewater treatment plants: software sensors and controllers for an anaerobic digester

A mass balanced based model representing the dynamical behaviour of anaerobic digester has served as a basis for the design of software sensors for the concentration of inorganic carbon, alkalinity and volatile fatty acids. The predictions of the sensors are close to the actual off-line measurements. The model has also been used to design a model-based adaptive linearizing controller and a fuzzy controller whose objective is to regulate the ratio of the intermediate alkalinity over the total alkalinity below some desired value (0.3) under which the process is assumed to remain in stable conditions and avoid VFA accumulation. Both controllers were calibrated via extensive numerical simulations and implemented. The controllers proved successful in maintaining the ratio of TA over PA below 0.3, even in presence of large variations of the organic load.

Development of a Fuzzy-Based Diagnosis System for the Supervision of the Operation in Anaerobic Wastewater Treatment Plants

A fuzzy logic based diagnosis system for the supervision of the operation of a wastewater treatment plant was developed. The diagnosis system uses the experts’ knowledge to determine the state of the process, using several measured variables, by means of a base of rules. The system allows to know the acidification state in the reactor by using fuzzy inference system evaluations for given inputs and with variables quantified using linguistic labels. A representative experiment of an acidification of the anaerobic reactor due to a hydraulic overload, together with the fuzzy diagnosis system responses, are presented.

Knowledge-based system for telecontrol of anaerobic wastewater treatment plants

This paper describes the design and implementation of an intelligent real-time supervision system for the monitoring and control of wastewater treatment plants. The system presents a hybrid structure which integrates knowledge engineering techniques and methodologies (an expert system based on production rules embodying non-mathematical or semiquantitative knowledge of unit operation) and algorithmic process-related methods (data acquisition, signal preprocessing, calculation of plant operation parameters etc.). The fundamental design aspects consist of temporal information treatment, artifact detection and a client- server structure which allows the telesupervision of various plants by a central system.

Anaerobic digestion for wastewater treatment in Mexico: state of the technology

Due to the nascent wastewater treatment practice in Mexico there is great opportunity to introduce anaerobic digestion as the core of the wastewater treatment processes. Nevertheless, this requires an understanding of all the technical, economical and financial aspects that limit its development. According to the National Water Commission, in 1995 municipal and industrial wastewater were produced at rates of 232 and 168 m 3 s −1 respectively, but only 20 and 12% of these volumes were treated, often with very low efficiencies. In order to increase the treatment capacity of the country, approximately US$ 4515 million managed by the banks for development are supposed to be available to invest in environmental projects. Other financing mechanisms exist through treasury incentives and penalties. Within this situation, anaerobic digestion has grown although not at the required rate and bigger investments are being made on conventional aerobic and physicochemical technologies. Presently there are in the country 85 anaerobic wastewater treatment plants treating 216,295 m 3 d −1 with an installed volume of 228,551 m 3. UASB reactors account for 74% of the installed volume and national companies have supplied 76% to the anaerobic market. Proper integration of the anaerobic digestion processes for water recycling and energy recovery has not been achieved and there is a big need to demonstrate economic and ecological sustainability.

Microbiology and chemical engineering-new possibilities for interdisciplinary cooperation in the development of small anaerobic wastewater treatment plants

Anaerobic degradation of waste water in fixed bed reactors is investigated using molasses as an example of complex composed waste water. The results of differently sized rectors are shown to be transferable and can be used for the design of small waste water treatment plants. The assessment of the reactor performance is done not only by material balances but also by applying microbiological parameters. Modern microbiological methods enable the incorporation of biological parameters into reactor design and process control. The results of these measurements lead to a better understanding of the correlation between changing process parameters and the state of the microbial population. Thus new tools are available to maintain stable and save anaerobic processes.