Wastewater Treatment Process: A Modified Mathematical Model for Oxidation Ponds

Wastewater treatment aims to eliminate as many suspended solids as possible from the remaining water, known as effluent, before it is released into the environment. Pond oxidation methods have been practically proven successful for the wastewater treatment process because of their low construction and maintenance costs. This study aimed to investigate the degradation of wastewater pollutants through an oxidation pond treatment system. The purpose was to observe the relationship between the concentration of bacteria which are phototrophic and coliform, chemical oxygen demand (COD), and dissolved oxygen (DO). In this paper, a modified model consist of a set of an ordinary differential equation (ODE) has been developed by incorporating the Monod Equation. The model was solved numerically using the 4th order Runge Kutta method embedded in the MATLAB software. The sum of squared estimate of errors (SSE) for the modified model was compared with the SSE of the existing model. The results revealed that the modified model demonstrated a lower SSE compared to the existing model. Thus, the modified mathematical model gives better result than the existing model. The model provides an excellent approximation for concentration needed for an oxidized pond to produce good water quality.

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A MATHEMATICAL MODEL FOR WASTEWATER TREATMENT PROCESS OF AN OXIDATION POND

Jurnal Teknologi ◽

10.11113/jt.v78.7815 ◽

2016 ◽

Vol 78 (3-2) ◽

Author(s):

Amir S. A. Hamzah ◽

Akbar Banitalebi ◽

Ali H. M. Murid ◽

Zainal A. Aziz ◽

Hasniza Ramli ◽

...

Keyword(s):

Mathematical Model ◽

Wastewater Treatment ◽

Dissolved Oxygen ◽

Treatment Process ◽

Oxygen Demand ◽

Wastewater Treatment Process ◽

Oxidation Pond ◽

Coupled Equations ◽

Proposed Model ◽

The Mathematical Model

This study presents a mathematical model for wastewater treatment process (WWTP) of an oxidation pond. The model permits investigating the effects of a biological-based product called mPHO on the degradation of contaminants as well as increase the amount of dissolved oxygen (DO) in the pond. At this aim, an ordinary differential equation with coupled equations has been developed to study the correlation between the amount of bacteria (phototrophic and Coliform), chemical oxygen demand (COD), and dissolved oxygen (DO) existing in the pond. The mathematical model is employed to simulate the behaviour of the system where the numerical results demonstrate that the proposed model gives a good approximation of the interaction processes that occur naturally between biological and chemical substances involved in the pond

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Comparison of F-specific bacteriophage, enterococci, and faecal coliform densities through a wastewater treatment process employing oxidation ponds

Water Science & Technology ◽

10.2166/wst.1995.0568 ◽

1995 ◽

Vol 31 (5-6) ◽

pp. 85-89 ◽

Cited By ~ 6

Author(s):

S. J. Turner ◽

G. D. Lewis

Keyword(s):

Wastewater Treatment ◽

Treatment Process ◽

Faecal Coliform ◽

Indicator Organisms ◽

Faecal Coliforms ◽

Wastewater Treatment Process ◽

Oxidation Pond ◽

Oxidation Ponds ◽

Specific Bacteriophage

Over a 12 month period F-specific bacteriophages, faecal coliforms and enterococci were compared as microbial indicator organisms for the quality of a wastewater treatment (oxidation pond) system. Results suggest that enterococci may be the most useful indicator for oxidation pond systems.

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Development of a cost-effective wastewater treatment process: combination of different process

E3S Web of Conferences ◽

10.1051/e3sconf/202123301106 ◽

2021 ◽

Vol 233 ◽

pp. 01106

Author(s):

Song Du ◽

Wenbiao Jin

Keyword(s):

Wastewater Treatment ◽

Catalytic Oxidation ◽

Treatment Process ◽

Batch Reactor ◽

Oxygen Demand ◽

Cost Effective ◽

Fenton Oxidation ◽

Wastewater Treatment Process ◽

Combination Process ◽

Electro Catalytic Oxidation

Caprolactam wastewater produced by the production process of caprolactam is characterized by a very high toxicity and chemical oxygen demand (COD) values, having potential harm to the environment if treated improperly. However, these characteristics make caprolactam wastewaters difficult to treat using traditional methods. So the aim of this work was to develop a cost-effective caprolactam wastewater treatment process. Fenton oxidation, sequencing batch reactor activated sludge process (SBR) and electro-catalytic oxidation were proposed to treat caprolactam wastewater in the laboratory scale, and the treatment effects were investigated. Compared with Fenton oxidation, SBR and electro-catalytic oxidation can treat caprolactam wastewater at a lower cost and more efficiently. The pilot test results indicate that the COD can be decreased to less than 1000 mg/L by the combination process, and when the COD removal rates maintain 90%, the cost of caprolactam wastewater treatment is below 6 yuan/m3. The combination process showed better economic benefit.

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Effect of the rotifer Lecane inermis, a potential sludge bulking control agent, on process parameters in a laboratory-scale SBR system

Water Science & Technology ◽

10.2166/wst.2013.453 ◽

2013 ◽

Vol 68 (9) ◽

pp. 2012-2018 ◽

Cited By ~ 6

Author(s):

Wioleta Kocerba-Soroka ◽

Edyta Fiałkowska ◽

Agnieszka Pajdak-Stós ◽

Mateusz Sobczyk ◽

Małgorzata Pławecka ◽

...

Keyword(s):

Wastewater Treatment ◽

Treatment Process ◽

Sewage Treatment ◽

Treatment Plant ◽

Oxygen Demand ◽

Control Agent ◽

Batch Reactors ◽

Activated Sludge Process ◽

Filamentous Bacteria ◽

Wastewater Treatment Process

The influence of a high density of rotifers, which is known to be able to control filamentous bacteria, on the parameters of an activated sludge process was examined in four professional laboratory batch reactors. These reactors allow the imitation of the work of a wastewater treatment plant with enhanced nutrient removal. The parameters, including oxygen concentration, pH and temperature, were constantly controlled. The experiment showed that Lecane rotifers are able to proliferate in cyclically anaerobic/anoxic and aerobic conditions and at dissolved oxygen concentrations as low as 1 mg/L. In 1 week, rotifer density increased fivefold, exceeding the value of 2,200 ind./mL. The grazing activity led to an improvement in settling properties. Extremely high numbers of rotifers did not affect the main parameters, chemical oxygen demand (COD), N-NH4, N-NO3, P-PO4 and pH, during sewage treatment. Therefore, the use of rotifers as a tool to limit the growth of filamentous bacteria appears to be safe for the entire wastewater treatment process.

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Research on a soft measurement model of sewage treatment based on a case-based reasoning approach

Water Science & Technology ◽

10.2166/wst.2017.417 ◽

2017 ◽

Vol 76 (12) ◽

pp. 3181-3189 ◽

Cited By ~ 3

Author(s):

Jiayan Zhang ◽

Cuicui Du ◽

Xugang Feng

Keyword(s):

Neural Network ◽

Wastewater Treatment ◽

Treatment Process ◽

Sewage Treatment ◽

Oxygen Demand ◽

Prediction Method ◽

Measurement Model ◽

Case Based Reasoning ◽

Wastewater Treatment Process ◽

Case Based

Abstract In this paper, the measurement of biochemical oxygen demand (BOD) in a wastewater treatment process is analyzed and an intelligent integrated prediction method based on case-based reasoning (CBR) is proposed in order to overcome difficulties. Due to the fact that there are many factors that influence the accuracy of the prediction model, the radial basis function, which is a neural network with a 3 layer feedforward network, is employed to reduce the dimension of input values. Under these circumstances, a back propagation neural network combining with a nearest neighbor retrieval strategy is adopted to match case. Then, the measurement of BOD in wastewater treatment process is analyzed. Finally, the validity of the improved CBR in sewage treatment is demonstrated by using numerical results.

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Prediction of BOD Concentration in Wastewater Treatment Process Using a Modular Neural Network in Combination with the Weather Condition

Applied Sciences ◽

10.3390/app10217477 ◽

2020 ◽

Vol 10 (21) ◽

pp. 7477

Author(s):

Wenjing Li ◽

Junkai Zhang

Keyword(s):

Neural Network ◽

Wastewater Treatment ◽

Prediction Accuracy ◽

Clustering Algorithm ◽

Treatment Process ◽

Weather Condition ◽

Oxygen Demand ◽

Wastewater Treatment Process ◽

Training Time ◽

Modular Neural Network

Since weather has a huge impact on the wastewater treatment process (WWTP), the prediction accuracy for the Biochemical Oxygen Demand (BOD) concentration in WWTP would degenerate if using only one single artificial neural network as the model for soft measurement method. Aiming to solve this problem, the present study proposes a novel hybrid scheme using a modular neural network (MNN) combining with the factor of weather condition. First, discriminative features among different weather groups are selected to ensure a high accuracy for sample clustering based on weather conditions. Second, the samples are clustered based on a density-based clustering algorithm using the discriminative features. Third, the clustered samples are input to each module in MNN, with the auxiliary variables correlated with BOD prediction input to the corresponding model. Finally, a constructive radial basis function neural network with the error-correction algorithm is used as the model for each subnetwork to predict BOD concentration. The proposed scheme is evaluated on a standard wastewater treatment platform—Benchmark Simulation Model 1 (BSM1). Experimental results demonstrate the performance improvement of the proposed scheme on the prediction accuracy for BOD concentration in WWTP. Besides, the training time is shortened and the network structure is compact.

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