Results of ‘PASt21’ – the Portuguese initiative for performance assessment of water and wastewater treatment plants

2012 ◽  
Vol 12 (3) ◽  
pp. 372-386 ◽  
Author(s):  
C. Silva ◽  
P. Ramalho ◽  
S. Quadros ◽  
H. Alegre ◽  
M. J. Rosa
Keyword(s):  
Wastewater Treatment ◽  
Performance Assessment ◽  
Performance Indicator ◽  
Wastewater Treatment Plants ◽  
Treatment Plant ◽  
Drinking Water Treatment ◽  
Plant Performance ◽  
Water And Wastewater Treatment ◽  
Pi Systems ◽  
Overall Performance

Performance assessment of water supply and wastewater services is today a major issue. Over the past six years, the National Civil Engineering Laboratory (Portugal) has been developing performance assessment systems for drinking water treatment plants (WTPs) and wastewater treatment plants (WWTPs). In 2009, a national field-test was launched in Portugal, ‘PASt21’, involving 27 plants (10 WTPs and 17 WWTPs). This paper presents an overview of the second generation of the performance indicator (PI) systems for the overall performance assessment of WTPs and WWTPs, the extent to which the systems were applied in the 5-year study period (2006–2010), and the aggregated results (average, median, percentiles 25 and 75, maximum and minimum) of representative PIs in each assessment group. It was concluded that all indicators are relevant, and the results show the ability of the proposed PI systems to assess the overall performance of a given treatment plant. The aggregated results are very important for the continuous improvement of the plant performance through benchmarking and periodic reassessment of targets.

scholarly journals Biological Nutrient Removal Model No. 2 (BNRM2): a general model for wastewater treatment plants

2013 ◽  
Vol 67 (7) ◽  
pp. 1481-1489 ◽  
Author(s):  
R. Barat ◽  
J. Serralta ◽  
M. V. Ruano ◽  
E. Jiménez ◽  
J. Ribes ◽  
...  
Keyword(s):  
Wastewater Treatment ◽  
Nitrogen Removal ◽  
Nutrient Removal ◽  
Wastewater Treatment Plants ◽  
Treatment Plant ◽  
Operating Conditions ◽  
Plant Performance ◽  
Biological Nutrient Removal ◽  
Nitrite Oxidizing Bacteria ◽  
Removal Model

This paper presents the plant-wide model Biological Nutrient Removal Model No. 2 (BNRM2). Since nitrite was not considered in the BNRM1, and this previous model also failed to accurately simulate the anaerobic digestion because precipitation processes were not considered, an extension of BNRM1 has been developed. This extension comprises all the components and processes required to simulate nitrogen removal via nitrite and the formation of the solids most likely to precipitate in anaerobic digesters. The solids considered in BNRM2 are: struvite, amorphous calcium phosphate, hidroxyapatite, newberite, vivianite, strengite, variscite, and calcium carbonate. With regard to nitrogen removal via nitrite, apart from nitrite oxidizing bacteria two groups of ammonium oxidizing organisms (AOO) have been considered since different sets of kinetic parameters have been reported for the AOO present in activated sludge systems and SHARON (Single reactor system for High activity Ammonium Removal Over Nitrite) reactors. Due to the new processes considered, BNRM2 allows an accurate prediction of wastewater treatment plant performance in wider environmental and operating conditions.

Integrated Wastewater Treatment Plant Performance Evaluation Using Artificial Neural Networks

1999 ◽  
Vol 40 (7) ◽  
pp. 55-65 ◽  
Author(s):  
Mohamed F. Hamoda ◽  
Ibrahim A. Al-Ghusain ◽  
Ahmed H. Hassan
Keyword(s):  
Neural Networks ◽  
Wastewater Treatment ◽  
Artificial Neural Networks ◽  
Wastewater Treatment Plant ◽  
Municipal Wastewater ◽  
Wastewater Treatment Plants ◽  
Treatment Plant ◽  
Plant Performance ◽  
Municipal Wastewater Treatment ◽  
Artificial Neural

Proper operation of municipal wastewater treatment plants is important in producing an effluent which meets quality requirements of regulatory agencies and in minimizing detrimental effects on the environment. This paper examined plant dynamics and modeling techniques with emphasis placed on the digital computing technology of Artificial Neural Networks (ANN). A backpropagation model was developed to model the municipal wastewater treatment plant at Ardiya, Kuwait City, Kuwait. Results obtained prove that Neural Networks present a versatile tool in modeling full-scale operational wastewater treatment plants and provide an alternative methodology for predicting the performance of treatment plants. The overall suspended solids (TSS) and organic pollutants (BOD) removal efficiencies achieved at Ardiya plant over a period of 16 months were 94.6 and 97.3 percent, respectively. Plant performance was adequately predicted using the backpropagation ANN model. The correlation coefficients between the predicted and actual effluent data using the best model was 0.72 for TSS compared to 0.74 for BOD. The best ANN structure does not necessarily mean the most number of hidden layers.

The Use of Computational Fluid Dynamics for Improving the Design and Operation of Water and Wastewater Treatment Plants

1999 ◽  
Vol 40 (4-5) ◽  
pp. 81-89 ◽  
Author(s):  
C. J. Brouckaert ◽  
C. A. Buckley
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Wastewater Treatment ◽  
Potable Water ◽  
Wastewater Treatment Plants ◽  
Treatment Plant ◽  
Water Treatment Plant ◽  
Outer Wall ◽  
Water And Wastewater Treatment ◽  
Secondary Clarifier

Computational Fluid Dynamics (CFD) studies of a secondary clarifier at Durban's Northern Wastewater Treatment Works, and of a clarifier at the potable water treatment plant at Umzinto, a small town near Durban, have been undertaken with a view to improving their load capacities. In both cases the units are located in relatively old treatment plants, which face continually increasing loads due to population growth. Increasing the capacity of existing equipment, rather than installing new equipment, constitutes an efficient use of development capital. Although the two clarifiers have considerable design differences, the CFD studies indicated remarkably similar circulating flows, which concentrate up-flow near the outer wall of the clarifier in the region of the clarified water overflow weirs. Baffles were designed to disrupt the circulation so as to distribute up-flow over a wider area, thereby reducing the maximum vertical velocities. In the case of the wastewater secondary clarifier, the modification has been implemented, and evaluated in comparative tests involving an otherwise identical unmodified clarifier. In the case of the potable water clarifier, the modification has still to be implemented.

Model-based evaluation of nitrogen removal in a tannery wastewater treatment plant

2004 ◽  
Vol 50 (6) ◽  
pp. 251-260 ◽  
Author(s):  
M.S. Moussa ◽  
A.R. Rojas ◽  
C.M. Hooijmans ◽  
H.J. Gijzen ◽  
M.C.M. van Loosdrecht
Keyword(s):  
Wastewater Treatment ◽  
Activated Sludge ◽  
Wastewater Treatment Plants ◽  
Computer Modelling ◽  
Treatment Plant ◽  
Domestic Wastewater ◽  
Plant Performance ◽  
Accurate Estimation ◽  
Model Parameters ◽  
Biological Tests

Computer modelling has been used in the last 15 years as a powerful tool for understanding the behaviour of activated sludge wastewater treatment systems. However, computer models are mainly applied for domestic wastewater treatment plants (WWTPs). Application of these types of models to industrial wastewater treatment plants requires a different model structure and an accurate estimation of the kinetics and stoichiometry of the model parameters, which may be different from the ones used for domestic wastewater. Most of these parameters are strongly dependent on the wastewater composition. In this study a modified version of the activated sludge model No. 1 (ASM 1) was used to describe a tannery WWTP. Several biological tests and complementary physical-chemical analyses were performed to characterise the wastewater and sludge composition in the context of activated sludge modelling. The proposed model was calibrated under steady-state conditions and validated under dynamic flow conditions. The model was successfully used to obtain insight into the existing plant performance, possible extension and options for process optimisation. The model illustrated the potential capacity of the plant to achieve full denitrification and to handle a higher hydraulic load. Moreover, the use of a mathematical model as an effective tool in decision making was demonstrated.

Energy and process data processing and visualisation for optimising wastewater treatment plants

2015 ◽  
Vol 10 (1) ◽  
pp. 10-18 ◽  
Author(s):  
Christian M. Thürlimann ◽  
David J. Dürrenmatt ◽  
Kris Villez
Keyword(s):  
Wastewater Treatment ◽  
Performance Indicator ◽  
Wastewater Treatment Plants ◽  
Data Communication ◽  
Decision Support Tool ◽  
Plant Performance ◽  
Process Data ◽  
Support Tool ◽  
Effluent Quality ◽  
Visualisation Tool

For complex systems such as wastewater treatment plants (WWTPs), effective data communication is an important step to enable operators to assess their plant. However, examples in practice show that this step is insufficiently considered. In this article, we describe a fast, relevant, and intuitive decision-support tool for operators. We have developed a key performance indicator (KPI) visualisation tool for energy and process data embedded in a larger process optimisation software. The KPI set consists of indicator values relating to energy and effluent quality. In order to ensure that the visualisation tool will be used and cover the needs of the plant staff, we developed this part of the software in collaboration with two WWTPs. At the time of writing, the tool is used in the daily operation of both plants. The operators see the tool's most important advantages as its ability to quickly assess current plant performance and to simplify the tracking and analysis of inter- and intra-process relationships and dynamics.

Integrated soft sensor model for flow control

2006 ◽  
Vol 53 (4-5) ◽  
pp. 473-482 ◽  
Author(s):  
G. Äijälä ◽  
D. Lumley
Keyword(s):  
Wastewater Treatment ◽  
Control System ◽  
Flow Control ◽  
Wastewater Treatment Plants ◽  
Treatment Plant ◽  
Soft Sensor ◽  
Plant Performance ◽  
Unit Process ◽  
Flow Models ◽  
Flow Control System

Tighter discharge permits often require wastewater treatment plants to maximize utilization of available facilities in order to cost-effectively reach these goals. Important aspects are minimizing internal disturbances and using available information in a smart way to improve plant performance. In this study, flow control throughout a large highly automated wastewater treatment plant (WWTP) was implemented in order to reduce internal disturbances and to provide a firm foundation for more advanced process control. A modular flow control system was constructed based on existing instrumentation and soft sensor flow models. Modules were constructed for every unit process in water treatment and integrated into a plant-wide model. The flow control system is used to automatically control recirculation flows and bypass flows at the plant. The system was also successful in making accurate flow estimations at points in the plant where it is not possible to have conventional flow meter instrumentation. The system provides fault detection for physical flow measuring devices. The module construction allows easy adaptation for new unit processes added to the treatment plant.

Predicting wastewater treatment plant performance during aeration demand shifting with a dual-layer reaction settling model

2019 ◽  
Vol 81 (7) ◽  
pp. 1365-1374 ◽  
Author(s):  
Matteo Giberti ◽  
Recep Kaan Dereli ◽  
Damian Flynn ◽  
Eoin Casey
Keyword(s):  
Wastewater Treatment ◽  
Municipal Wastewater ◽  
Wastewater Treatment Plants ◽  
Kinetic Equations ◽  
Treatment Plant ◽  
Plant Performance ◽  
Extended Model ◽  
Municipal Wastewater Treatment ◽  
Potential Benefits ◽  
Municipal Wastewater Treatment Plants

Abstract Demand response (DR) programmes encourage energy end users to adjust their consumption according to energy availability and price. Municipal wastewater treatment plants are suitable candidates for the application of such programmes. Demand shedding through aeration control, subject to maintaining the plant operational limits, could have a large impact on the plant DR potential. Decreasing the aeration intensity may promote the settling of the particulate components present in the reactor mixed liquor. The scope of this study is thus to develop a mathematical model to describe this phenomenon. For this purpose, Benchmark Simulation Model No.1 was extended by implementing a dual-layer settling model in one of the aerated tanks and combining it with biochemical reaction kinetic equations. The performance of this extended model was assessed in both steady-state and dynamic conditions, switching the aeration system off for 1 hour during each day of simulation. This model will have applications in the identification of potential benefits and issues related to DR events, as well as in the simulation of the plant operation where aerated tank settling is implemented.

Benefits and drawbacks of thermal pre-hydrolysis for operational performance of wastewater treatment plants

2008 ◽  
Vol 58 (8) ◽  
pp. 1547-1553 ◽  
Author(s):  
P. Phothilangka ◽  
M. A. Schoen ◽  
B. Wett
Keyword(s):  
Wastewater Treatment ◽  
Activated Sludge ◽  
Wastewater Treatment Plants ◽  
Biogas Production ◽  
Treatment Plant ◽  
Full Scale ◽  
Plant Performance ◽  
Ammonia Release ◽  
Hydrolysis Process ◽  
Solids Content

This paper presents benefits and potential drawbacks of thermal pre-hydrolysis of sewage sludge from an operator's prospective. The innovative continuous Thermo-Pressure-Hydrolysis Process (TDH) has been tested in full-scale at Zirl wastewater treatment plant (WWTP), Austria, and its influence on sludge digestion and dewatering has been evaluated. A mathematical plant-wide model with application of the IWA Activated Sludge Model No.1 (ASM1) and the Anaerobic Digestion Model No.1 (ADM1) has been used for a systematic comparison of both scenarios—operational plant performance with and without thermal pre-hydrolysis. The impacts of TDH pre-hydrolysis on biogas potential, dewatering performance and return load in terms of ammonia and inert organic compounds (Si) have been simulated by the calibrated model and are displayed by Sankey mass flow figures. Implementation of full scale TDH process provided higher anaerobic degradation efficiency with subsequent increased biogas production (+75–80%) from waste activated sludge (WAS). Both effects—enhanced degradation of organic matter and improved cake's solids content from 25.2 to 32.7% TSS—promise a reduction in sludge disposal costs of about 25%. However, increased ammonia release and generation of soluble inerts Si was observed when TDH process was introduced.

scholarly journals Determination of Polycyclic Aromatic Hydrocarbons in Sludge from Water and Wastewater Treatment Plants by GC-MS

2019 ◽  
Vol 16 (14) ◽  
pp. 2604 ◽  
Author(s):  
Chih-Feng Chen ◽  
Yun-Ru Ju ◽  
Yee Cheng Lim ◽  
Shu-Ling Hsieh ◽  
Mei-Ling Tsai ◽  
...  
Keyword(s):  
Wastewater Treatment ◽  
Polycyclic Aromatic Hydrocarbons ◽  
Aromatic Hydrocarbons ◽  
Wastewater Treatment Plants ◽  
Drinking Water Treatment ◽  
Gas Chromatography Mass Spectrometry ◽  
Water And Wastewater Treatment ◽  
Polycyclic Aromatic ◽  
Individual Pahs ◽  
Pahs Concentration

The qualitative and quantitative analysis of 16 polycyclic aromatic hydrocarbons (PAHs) in sludge samples from drinking water treatment plants (DWTP) and wastewater treatment plants (WWTP) were established using gas chromatography–mass spectrometry (GC-MS). The method was suitable to quantify PAHs in the sludge of DWTP and WWTP and it was confirmed by the relevant quality assurance/quality control (QA/QC) procedures. The recovery of individual PAHs in the spiked samples ranged from 74.3% to 108.7%. Detection limits of the analytical procedure were 0.0010–0.0046 mg/kg dw for individual PAHs. This method was used to determine the concentration of PAHs in the selected two DWTP and four WWTP sludge samples. The results showed that the total PAHs (∑PAHs) were in low levels which ranged from 0.0668 to 0.1357 mg/kg dw, and 0.5342–1.0666 mg/kg dw for DWTP and WWTP respectively. The 3- & 4-ring PAHs were predominant in DWTP sludge, ranging from 77.4% to 82.7%; the 4-ring PAHs were predominant in WWTP sludge, ranging from 40.7% to 47.6%. The PAHs of DWTP sludge are mainly composed of 3-ring phenanthrene and anthracene and 4-ring pyrene, and chrysene. The PAHs of WWTP sludge are dominated by 4-ring fluoranthene, pyrene, and chrysene. The detected PAHs concentration should be undoubtedly considered for agriculture in sludge applications based on the limits of the EU regulations. The results of this study can be used for regular monitoring to establish a reference for sludge management and application to agriculture.

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