scholarly journals Bioreactor and wetland combinations

2019 ◽  
pp. 163-171
Author(s):  
Rune Bakke
Keyword(s):  
Wastewater Treatment Plants ◽  
Control Strategies ◽  
Surface Flow ◽  
Efficient Treatment ◽  
Natural Processes ◽  
Advanced Control ◽  
Wetland Treatment ◽  
Computer Controlled ◽  
Alternative Solutions ◽  
Anaerobic Pretreatment

Wastewater treatment plants combining bioreactors and natural processes, designed to achievecost efficient treatment, are described and evaluated. The plants have a common generallayout: an anaerobic pretreatment, an aerated bioreactor, sedimentation with sludge return anda final sub-surface flow wetland treatment. Variations in this design, adaptations to variousapplications, process control strategies and sludge handling are discussed. Removalefficiencies obtained varies in the range: 96-99 % BOO7, 72-88 % COD, 92-96 % SS, 80-99% P, 37-91% N, where more advanced control yield higher efficiency. Thermo-tolerant fecalcoliform bacteria are typically removed by 99.9 %. Most of the nitrogen is removed in thebioreactors. Computer controlled aeration and sludge handling is required to obtain the hightotal nitrogen removal (> 80 %) Phosphorus can also be removed in the bioreactors andexported as sludge, or, more cost effectively, mainly removed in the wetland part of the plants.The cost efficiency of such treatment plants is good compared to alternative solutions.

scholarly journals Calibration and simulation of two large wastewater treatment plants operated for nutrient removal

2004 ◽  
Vol 50 (6) ◽  
pp. 87-94 ◽  
Author(s):  
J. Ferrer ◽  
J.J. Morenilla ◽  
A. Bouzas ◽  
F. Garcia-Usach
Keyword(s):  
Phosphorus Removal ◽  
Biological Process ◽  
Wastewater Treatment Plants ◽  
Control Strategies ◽  
Nitrogen And Phosphorus ◽  
Nitrogen And Phosphorus Removal ◽  
Good Correspondence ◽  
Advanced Control ◽  
Performance Results ◽  
Biological Nitrogen

Control and optimisation of plant processes has become a priority for WWTP managers. The calibration and verification of a mathematical model provides an important tool for the investigation of advanced control strategies that may assist in the design or optimization of WWTPs. This paper describes the calibration of the ASM2d model for two full scale biological nitrogen and phosphorus removal plants in order to characterize the biological process and to upgrade the plants' performance. Results from simulation showed a good correspondence with experimental data demonstrating that the model and the calibrated parameters were able to predict the behaviour of both WWTPs. Once the calibration and simulation process was finished, a study for each WWTP was done with the aim of improving its performance. Modifications focused on reactor configuration and operation strategies were proposed.

scholarly journals Global Evaluation of Wastewater Treatment Plants Control Strategies Including CO 2 Emissions

2017 ◽  
Vol 50 (1) ◽  
pp. 12956-12961 ◽  
Author(s):  
Marian Barbu ◽  
Ramon Vilanova ◽  
Montse Meneses ◽  
Ignacio Santin
Keyword(s):  
Wastewater Treatment ◽  
Wastewater Treatment Plants ◽  
Control Strategies ◽  
Global Evaluation

scholarly journals Advanced control strategies for bioprocess chromatography: Challenges and opportunities for intensified processes and next generation products

2021 ◽  
Vol 1639 ◽  
pp. 461914
Author(s):  
Alexander Armstrong ◽  
Kieran Horry ◽  
Tingting Cui ◽  
Martyn Hulley ◽  
Richard Turner ◽  
...  
Keyword(s):  
Control Strategies ◽  
Next Generation ◽  
Advanced Control ◽  
Challenges And Opportunities

Benchmark for evaluating control strategies in wastewater treatment plants

1999 ◽  
Author(s):  
J. Alex ◽  
J. F. Beteau ◽  
J. B. Copp ◽  
C. Hellinga ◽  
U. Jeppsson ◽  
...  
Keyword(s):  
Wastewater Treatment ◽  
Wastewater Treatment Plants ◽  
Control Strategies

Small wastewater treatment plants in Flanders (Belgium): standard approach and experiences with constructed reed beds

2000 ◽  
Vol 41 (1) ◽  
pp. 57-63 ◽  
Author(s):  
S. Vandaele ◽  
C. Thoeye ◽  
B. Van Eygen ◽  
G. De Gueldre
Keyword(s):  
Wastewater Treatment ◽  
Removal Efficiency ◽  
Wastewater Treatment Plants ◽  
Treatment Plant ◽  
Pilot Scale ◽  
Surface Flow ◽  
Limiting Factor ◽  
Vertical Flow ◽  
Reed Beds ◽  
Reed Bed

In Flanders (Belgium) an estimated 15% of the population will never be connected to a central wastewater treatment plant (WWTP). Small WWTPs can be a valuable option. Aquafin bases the decision to build SWWTPs on a drainage area study. To realise an accelerated construction the process choice is made accordingly to a standard matrix, which represents the different technologies in function of the size and the effluent consents. A pilot scale constructed two-stage reed bed is used to optimise the concept of the reed beds. The concept consists of a primary clarifier, two parallel vertical flow reed beds followed by a sub-surface flow reed bed. The removal efficiency of organic pollutants is high (COD: 89%, BOD: 98%). Phosphorus removal is high at the start-up but diminishes throughout the testing period (from 100% to 71% retention after 7 months). Nitrogen removal amounts to 53% on average. Nitrification is complete in summer. Denitrification appears to be the limiting factor. In autumn leakage of nitrogen is assumed. Removal efficiency of pathogens amounts to almost 99%. Clogging forms a substantial constraint of the vertical flow reed bed. Problems appear to be related with presettlement, feed interval and geotextile.

scholarly journals ANN-Based Soft Sensor to Predict Effluent Violations in Wastewater Treatment Plants

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1280 ◽  
Author(s):  
Ivan Pisa ◽  
Ignacio Santín ◽  
Jose Vicario ◽  
Antoni Morell ◽  
Ramon Vilanova
Keyword(s):  
Wastewater Treatment ◽  
Short Term Memory ◽  
Wastewater Treatment Plants ◽  
Control Strategies ◽  
False Positive Rate ◽  
Soft Sensor ◽  
Aquatic Life ◽  
Pollutant Concentrations ◽  
High Concentrations ◽  
Artificial Neural Network Ann

Wastewater treatment plants (WWTPs) form an industry whose main goal is to reduce water’s pollutant products, which are harmful to the environment at high concentrations. In addition, regulations are applied by administrations to limit pollutant concentrations in effluent. In this context, control strategies have been adopted by WWTPs to avoid violating these limits; however, some violations still occur. For that reason, this work proposes the deployment of an artificial neural network (ANN)-based soft sensor in which a Long-Short Term Memory (LSTM) network is used to generate predictions of nitrogen-derived components, specifically ammonium ( S N H ) and total nitrogen ( S N t o t ). S N t o t is a limiting nutrient and can therefore cause eutrophication, while nitrogen in the S N H form is toxic to aquatic life. These parameters are used by control strategies to allow actions to be taken in advance and only when violations are predicted. Since predictions complement control strategies, the evaluation of the ANN-based soft sensor was carried out using the Benchmark Simulation Model N.2. (BSM2) and three different control strategies (from low to high control complexity). Results show that our proposed method is able to predict nitrogen-derived products with good accuracy: the probability of detecting violations of BSM2’s limits is 86%–94%. Moreover, the prediction accuracy can be improved by calibrating the soft sensor; for example, perfect prediction of all future violations can be achieved at the expense of increasing the false positive rate.

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