Optimization of ozonation process for organic matter and ecotoxicity removal from landfill leachate by applying rotatable central composite design (RCCD)

2021 ◽  
pp. 1-14
Author(s):  
Heloisa B. Bastos ◽  
Larissa L. S. Silva ◽  
Érika C. A. N. Chrisman ◽  
Fabiana V. Fonseca ◽  
Juacyara C. Campos
Keyword(s):  
Organic Matter ◽  
Central Composite Design ◽  
Landfill Leachate ◽  
Central Composite ◽  
Ozonation Process

scholarly journals Application of Anaerobic and Ozonation Processes in the Landfill Leachate Treatment

2006 ◽  
Vol 1 (3) ◽  
Author(s):  
A. Vilar ◽  
S. Gil ◽  
M. A. Aparicio ◽  
C. Kennes ◽  
M. C. Veiga
Keyword(s):  
Organic Matter ◽  
Landfill Leachate ◽  
Biological System ◽  
Contact Time ◽  
Treatment Process ◽  
Tap Water ◽  
Leachate Treatment ◽  
Ozone Dose ◽  
Pre Treatment ◽  
Ozonation Process

The optimization of leachate treatment was investigated as well as the configuration of a biological-ozonation process. The leachate used for the experiments was diluted to 1/5 with tap water and treated anaerobically. The anaerobic effluent and the raw leachate were treated with ozone in order to increase their biodegradability getting the minimum organic matter removal. Both were submitted to the ozonation process, applying a constant ozone dose and varying the contact time. The ozonation of raw leachate produced a decrease of COD and BOD5 concentrations as well as BOD5/COD ratios, applying an ozone dose of 38.72 mg/L·min and contact times between 15 and 60 minutes. Ozonation as a pre-treatment process to the biological system did not improve the biodegradability of the raw leachate. The anaerobic effluent from the reactor fed with leachate diluted to 1/5, was subjected to an ozone dose of 34.99 mg/L·min and applying different contact times. BODf values increased from 74.75 up to 1220 mg/L and BODf/COD ratios reached values higher than 1. Then, the application of ozone to the anaerobic effluent led to the improvement of the biodegradability of the leachate as well as the BODf/COD ratio for all the contact times used.

Application of the central composite design for condition optimization for semi-aerobic landfill leachate treatment using electrochemical oxidation

2010 ◽  
Vol 61 (5) ◽  
pp. 1257-1266 ◽  
Author(s):  
Soraya Mohajeri ◽  
Hamidi Abdul Aziz ◽  
Mohamed Hasnain Isa ◽  
Mohammad Ali Zahed ◽  
Mohammed J. K. Bashir ◽  
...  
Keyword(s):  
Reaction Time ◽  
Central Composite Design ◽  
Electrochemical Oxidation ◽  
Current Density ◽  
Landfill Leachate ◽  
Electrolyte Concentration ◽  
Process Conditions ◽  
Leachate Treatment ◽  
Condition Optimization ◽  
Central Composite

In the present study, Electrochemical Oxidation was used to remove COD and color from semi-aerobic landfill leachate collected from Pulau Burung Landfill Site (PBLS), Penang, Malaysia. Experiments were conducted in a batch laboratory-scale system in the presence of NaCl as electrolyte and aluminum electrodes. Central composite design (CCD) under Response surface methodology (RSM) was applied to optimize the electrochemical oxidation process conditions using chemical oxygen demand (COD) and color removals as responses, and the electrolyte concentrations, current density and reaction time as control factors. Analysis of variance (ANOVA) showed good coefficient of determination (R2) values of >0.98, thus ensuring satisfactory fitting of the second-order regression model with the experimental data. In un-optimized condition, maximum removals for COD (48.77%) and color (58.21%) were achieved at current density 80 mA/cm2, electrolyte concentration 3,000 mg/L and reaction time 240 min. While after optimization at current density 75 mA/cm2, electrolyte concentration 2,000 mg/L and reaction time 218 min a maximum of 49.33 and 59.24% removals were observed for COD and color respectively.

Investigation and optimization of the SND–SBR system for organic matter and ammonium nitrogen removal using the central composite design

2018 ◽  
Vol 37 (5) ◽  
pp. 1638-1646 ◽  
Author(s):  
Seyed Mohammad Ali Masoudi ◽  
Amin Hedayati Moghaddam ◽  
Javad Sargolzaei ◽  
Abolfazl Darroudi ◽  
Vahid Zeynali
Keyword(s):  
Organic Matter ◽  
Central Composite Design ◽  
Nitrogen Removal ◽  
Ammonium Nitrogen ◽  
Central Composite

Degradation of refractory organic matter in the effluent from a semi-aerobic aged refuse biofilter-treated landfill leachate by a nano-Fe3O4 enhanced ozonation process

2021 ◽  
pp. 0734242X2110662
Author(s):  
Yuyu Huang
Keyword(s):  
Organic Matter ◽  
Influencing Factors ◽  
Landfill Leachate ◽  
Electrical Energy ◽  
Effluent Treatment ◽  
Leachate Treatment ◽  
Refractory Organic Matter ◽  
Aged Refuse ◽  
Initial Ph ◽  
Ozonation Process

In this study, the transformation and degradation mechanisms of refractory organic matter in biologically treated leachate from a semi-aerobic aged refuse biofilter (SAARB) in a nano-Fe3O4 enhanced ozonation process (nFe3O4-O3) were investigated in batch experiments. A continuous experiment then confirmed the effectiveness of the process for SAARB effluent treatment. In a batch experiment, the effects of influencing factors, including nFe3O4 dosage, O3 dosage and initial pH on the treatment performance of nFe3O4-O3 process, were comprehensively investigated. The results showed that when the nFe3O4 dosage = 6 g L−1, O3 dosage = 0.15 L minute−1 and initial pH = 7, the total organic carbon, absorbance at 254 nm and colour number removal efficiencies were 40.58%, 62.55% and 89.80%, respectively. In addition, most of the humic- and fulvic-like substances in the SAARB effluent were removed, and the condensation degree, aromaticity and humification degree of the organics were substantially reduced. The morphology and elemental valence state analysis showed that the nFe3O4 in the process was relatively stable and could form an nFe3O4-organic complex. Therefore, the probability of organics reacting with hydroxyl radical increased and the oxidation efficiency was enhanced. In the continuous experiment, both the O3 dosage and hydraulic retention time (HRT) were the key influencing factors. The treatment efficiency of the nFe3O4-O3 process was enhanced at a higher O3 dosage and longer HRT. The electrical energy consumption of the continuous nFe3O3-O3 process was calculated to be 17.72 kW h m−3 in SAARB effluent treatment. This study proved the feasibility of biologically treated landfill leachate treatment by the nFe3O3-O3 process.

Application of central composite design and artificial neural network in modeling of reactive blue 21 dye removal by photo-ozonation process

2016 ◽  
Vol 74 (1) ◽  
pp. 184-193 ◽  
Author(s):  
Ali Mehrizad ◽  
Parvin Gharbani
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Reaction Time ◽  
Light Intensity ◽  
Central Composite Design ◽  
Uv Light ◽  
Relative Significance ◽  
Artificial Neural ◽  
Central Composite ◽  
Ozonation Process

The present study deals with use of central composite design (CCD) and artificial neural network (ANN) in modeling and optimization of reactive blue 21 (RB21) removal from aqueous media under photo-ozonation process. Four effective operational parameters (including: initial concentration of RB21, O3 concentration, UV light intensity and reaction time) were chosen and the experiments were designed by CCD based on response surface methodology (RSM). The obtained results from the CCD model were used in modeling the process by ANN. Under optimum condition (O3 concentration of 3.95 mg L−1, UV intensity of 20.5 W m−2, reaction time of 7.77 min and initial dye concentration of 40.21 mg L−1), RB21 removal efficiency reached to up 98.88%. A topology of ANN with a three-layer consisting of four input neurons, 14 hidden neurons and one output neuron was designed. The relative significance of each major factor was calculated based on the connection weights of the ANN model. Dye and ozone concentrations were the most important variables in the photo-ozonation of RB21, followed by reaction time and UV light intensity. The comparison of predicted values by CCD and ANN with experimental results showed that both methods were highly efficient in the modeling of the process.

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