scholarly journals Ozonation Pretreatment for Reduction of Landfill Leachate Fouling on Membranes: A Response Surface Methodology Analysis

Processes ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 506
Author(s):  
Everton Gripa ◽  
Alyne M. Costa ◽  
Juacyara C. Campos ◽  
Fabiana V. da Fonseca
Keyword(s):  
Response Surface Methodology ◽  
Experimental Design ◽  
Response Surface ◽  
Reverse Osmosis ◽  
Organic Compounds ◽  
Landfill Leachate ◽  
Operational Conditions ◽  
Toxicity Factor ◽  
High Concentrations ◽  
Modified Fouling Index

Batch ozonation was performed to assess its efficacy as a pretreatment for reverse osmosis (RO) membranes for treating leachate with high concentrations of recalcitrant organic compounds. Leachate samples from two different landfills were collected and characterized. The modified fouling index (MFI) was used to estimate the fouling potential of raw and ozonized leachates. A response surface experimental design was applied to optimize operational pH and ozone dose. The results demonstrate that the best operational conditions are 1.5 g/L of O3 at pH 12.0 and 1.5 g/L of O3 at pH 9.0 for Landfills 1 and 2, which reduce MFI by 96.22% and 94.08%, respectively. Additionally, they show toxicity factor decays of 98.44% for Landfill 1 and 93.75% for Landfill 2. These results, along with the similar behavior shown by leachate samples from distinct landfills, suggest that ozonation is a promising technology to fit this kind of wastewater into the requirements of RO membranes, enabling their use in such treatment.

scholarly journals Optimization with Response Surface Methodology of Microwave-Assisted Conversion of Xylose to Furfural

Molecules ◽  
2020 ◽  
Vol 25 (16) ◽  
pp. 3574
Author(s):  
Carmen Padilla-Rascón ◽  
Juan Miguel Romero-García ◽  
Encarnación Ruiz ◽  
Eulogio Castro
Keyword(s):  
Response Surface Methodology ◽  
Experimental Design ◽  
Response Surface ◽  
Lignocellulosic Materials ◽  
Operational Conditions ◽  
Design And Optimization ◽  
Microwave Assisted ◽  
Microwave Reactor ◽  
Key Steps ◽  
Experimental Design And Optimization

The production of furfural from renewable sources, such as lignocellulosic biomass, has gained great interest within the concept of biorefineries. In lignocellulosic materials, xylose is the most abundant pentose, which forms the hemicellulosic part. One of the key steps in the production of furfural from biomass is the dehydration reaction of the pentoses. The objective of this work was to assess the conditions under which the concentration of furfural is maximized from a synthetic, monophasic, and homogeneous xylose medium. The experiments were carried out in a microwave reactor. FeCl3 in different proportions and sulfuric acid were used as catalysts. A two-level, three-factor experimental design was developed for this purpose. The results were further analyzed through a second experimental design and optimization was performed by response surface methodology. The best operational conditions for the highest furfural yield (57%) turned out to be 210 °C, 0.5 min, and 0.05 M FeCl3.

Decolorization and mineralization of Diarylide Yellow 12 (PY12) by photo-Fenton process: the Response Surface Methodology as the optimization tool

2012 ◽  
Vol 65 (10) ◽  
pp. 1795-1800 ◽  
Author(s):  
Edison GilPavas ◽  
Izabela Dobrosz-Gómez ◽  
Miguel Ángel Gómez-García
Keyword(s):  
Response Surface Methodology ◽  
Experimental Design ◽  
Response Surface ◽  
Textile Industry ◽  
Fenton Process ◽  
Photo Degradation ◽  
Operational Conditions ◽  
Response Optimization ◽  
Wavelength Radiation ◽  
Optimized Conditions

The Response Surface Methodology (RSM) was applied as a tool for the optimization of the operational conditions of the photo-degradation of highly concentrated PY12 wastewater, resulting from a textile industry located in the suburbs of Medellin (Colombia). The Box-Behnken experimental Design (BBD) was chosen for the purpose of response optimization. The photo-Fenton process was carried out in a laboratory-scale batch photo-reactor. A multifactorial experimental design was proposed, including the following variables: the initial dyestuff concentration, the H2O2 and the Fe+2 concentrations, as well as the UV wavelength radiation. The photo-Fenton process performed at the optimized conditions resulted in ca. 100% of dyestuff decolorization, 92% of COD and 82% of TOC degradation. A kinetic study was accomplished, including the identification of some intermediate compounds generated during the oxidation process. The water biodegradability reached a final DBO5/DQO = 0.86 value.

scholarly journals Modeling and Sensitivity Analysis of the Forward Osmosis Process to Predict Membrane Flux Using a Novel Combination of Neural Network and Response Surface Methodology Techniques

Membranes ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 70
Author(s):  
Jasir Jawad ◽  
Alaa H. Hawari ◽  
Syed Javaid Zaidi
Keyword(s):  
Response Surface Methodology ◽  
Experimental Design ◽  
Response Surface ◽  
Forward Osmosis ◽  
Feed Solution ◽  
Operating Conditions ◽  
Ann Model ◽  
Membrane Flux ◽  
Input Variables ◽  
Rsm Model

The forward osmosis (FO) process is an emerging technology that has been considered as an alternative to desalination due to its low energy consumption and less severe reversible fouling. Artificial neural networks (ANNs) and response surface methodology (RSM) have become popular for the modeling and optimization of membrane processes. RSM requires the data on a specific experimental design whereas ANN does not. In this work, a combined ANN-RSM approach is presented to predict and optimize the membrane flux for the FO process. The ANN model, developed based on an experimental study, is used to predict the membrane flux for the experimental design in order to create the RSM model for optimization. A Box–Behnken design (BBD) is used to develop a response surface design where the ANN model evaluates the responses. The input variables were osmotic pressure difference, feed solution (FS) velocity, draw solution (DS) velocity, FS temperature, and DS temperature. The R2 obtained for the developed ANN and RSM model are 0.98036 and 0.9408, respectively. The weights of the ANN model and the response surface plots were used to optimize and study the influence of the operating conditions on the membrane flux.

scholarly journals Removal of Pharmaceutical Micropollutants with Integrated Biochar and Marine Microalgae

2020 ◽  
Vol 9 (1) ◽  
pp. 4
Author(s):  
Amin Mojiri ◽  
Maedeh Baharlooeian ◽  
Reza Andasht Kazeroon ◽  
Hossein Farraji ◽  
Ziyang Lou
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Response Surface Methodology ◽  
Cell Viability ◽  
Response Surface ◽  
Contact Time ◽  
Marine Microalgae ◽  
Chaetoceros Muelleri ◽  
Mean Squared Errors ◽  
High Concentrations

Using microalgae to remove pharmaceuticals and personal care products (PPCPs) micropollutants (MPs) have attracted considerable interest. However, high concentrations of persistent PPCPs can reduce the performance of microalgae in remediating PPCPs. Three persistent PPCPs, namely, carbamazepine (CBZ), sulfamethazine (SMT) and tramadol (TRA), were treated with a combination of Chaetoceros muelleri and biochar in a photobioreactor during this study. Two reactors were run. The first reactor comprised Chaetoceros muelleri, as the control, and the second reactor comprised Chaetoceros muelleri and biochar. The second reactor showed a better performance in removing PPCPs. Through the response surface methodology, 68.9% (0.330 mg L−1) of CBZ, 64.8% (0.311 mg L−1) of SMT and 69.3% (0.332 mg L−1) of TRA were removed at the initial concentrations of MPs (0.48 mg L−1) and contact time of 8.1 days. An artificial neural network was used in optimising elimination efficiency for each MP. The rational mean squared errors and high R2 values showed that the removal of PPCPs was optimised. Moreover, the effects of PPCPs concentration (0–100 mg L−1) on Chaetoceros muelleri were studied. Low PPCP concentrations (<40 mg L−1) increased the amounts of chlorophyll and proteins in the microalgae. However, cell viability, chlorophyll and protein contents dramatically decreased with increasing PPCPs concentrations (>40 mg L−1).

scholarly journals Optimization of Coagulation-Flocculation Process of Landfill Leachate by Tin (IV) Chloride Using Response Surface Methodology

2019 ◽  
Vol 6 (1) ◽  
pp. 41-48 ◽  
Author(s):  
Abdul Aziz Hamidi ◽  
Syed Zainal Sharifah Farah Fariza ◽  
Alazaiza Motasem Y.D
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Removal Efficiency ◽  
Landfill Leachate ◽  
Chemical Properties ◽  
Oxygen Demand ◽  
Statistical Design ◽  
Water Infiltration ◽  
Flocculation Process ◽  
Maximum Removal

Landfill leachate is highly polluted and generated as a result of water infiltration through solid waste produced domestically and industrially. This study investigated the applicability of the response surface methodology (RSM) to optimize the removal performances of chemical oxygen demand (COD), color, and suspended solids (SS) from landfill leachate by coagulation process using Tin tetrachloride pentahydrate. The leachate samples were collected from Alor Pongsu Landfill (APLS) in Perak, Malaysia. Before starting the experiments, general characterization was carried out for raw leachate samples to investigate their physical and chemical properties. The effects of the dosage and pH of SnCl4 on the removal performances were evaluated as well. An ideal experimental design was performed based on the central composite design (CCD) by RSM. In addition, this RSM was used to evaluate the effects of process variables and their interaction toward the attainment of their optimum conditions. The statistical design of the experiments and data analysis was resolved using the Design-Expert software. Further, the range of coagulant dosage and pH was selected based on a batch study which was conducted at 13000 mg/L to 17000 mg/L of SnCl4 and pH ranged from 6 to 10. The results showed that the optimum pH and dosage of SnCl4 were 7.17 and 15 g/L, respectively, where the maximum removal efficiency was 67.7% for COD and 100% for color and SS. The results were in agreement with the experimental data with a maximum removal efficiency of 67.84 %, 98.6 %, and 99.3%, for COD, color, and SS, respectively. Overall, this study verified that the RSM method was viable for optimizing the operational condition of the coagulation-flocculation process.

scholarly journals Optimization of osmotic dehydration of chestnut (Castanea sativa Mill.) slices using Response Surface Methodology

2018 ◽  
Vol 7 (1) ◽  
Author(s):  
Teresa Delgado ◽  
Bruna Paim ◽  
José Alberto Pereira ◽  
Susana Casal ◽  
Elsa Ramalhosa
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Water Loss ◽  
Osmotic Dehydration ◽  
Sucrose Concentration ◽  
Volume Ratio ◽  
Castanea Sativa ◽  
Color Variation ◽  
Process Conditions ◽  
Operational Conditions

Osmotic dehydration of chestnut slices in sucrose was optimized for the first time by Response Surface Methodology (RSM). Experiments were planned according to a three-factor central composite design (α=1.68), studying the influence of sucrose concentration, temperature and time, on the following parameters: volume ratio, water activity, color variation, weight reduction, solids gain, water loss and normalized moisture content, as well as total moisture, ash and fat contents. The experimental data was adequately fitted into second-order polynomial models with coefficients of determination (R2) from 0.716 to 0.976, adjusted-R2 values from 0.460 to 0.954, and non-significant lacks of fit. The optimal osmotic dehydration process conditions for maximum water loss and minimum solids gain and color variation were determined by the “Response Optimizer” option: 83% sucrose concentration, 20 °C and 9.2 hours. Thus, the best operational conditions corresponded to high sugar concentration and low temperature, improving energy saving and decreasing the process costs.

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