scholarly journals Modeling of nitrate removal from aqueous solution by Fe-doped TiO2 under UV and solar irradiation using response surface methodology

2015 ◽  
Vol 17 (2) ◽  
pp. 379-388 ◽  
Keyword(s):  
Aqueous Solution ◽  
Response Surface Methodology ◽  
Solar Radiation ◽  
Response Surface ◽  
Removal Efficiency ◽  
Nitrate Removal ◽  
Operating Conditions ◽  
Solar Irradiation ◽  
Design Matrix ◽  
Statistical Tool

<div> <p>Nitrate is a common groundwater pollutant all over the world. In some regions of Iran, its levels are high enough to cause serious problems to human health and the environment<span dir="RTL">.</span> The objectives of this work were to evaluate the efficiency of Fe-doped TiO<sub>2</sub> nanoparticles at removing nitrate from aqueous solutions under UV and solar radiation and to model nitrate removal using response surface methodology techniques. In this study, a response surface methodology based on the Box&ndash;Behnken design matrix was used to describe the process of nitrate removal from an aqueous solution with four independent parameters, namely Fe-doped TiO<sub>2</sub> (dose 1-2 g l<sup>-1</sup>), nitrate concentration (25-100 mg l<sup>-1</sup>), contact time (10-120 min), and pH (4-9). The results indicated that the removal efficiency of nitrate in the presence of ultraviolet and solar radiation was 56.5 % and 21.8%, respectively. The removal efficiency of nitrate increased with time and initial concentration of nitrate. Analysis of variance (ANOVA) indicated that the proposed model was essentially in accordance with the experimental results with the correlation coefficient R<sup>2 </sup>= 0.9237 and Adj-R<sup>2</sup> = 0.8347. Response surface methodology (RSM) proved to be a powerful statistical tool for investigating the operating conditions for nitrate removal under UV irradiation.</p> </div> <p>&nbsp;</p>

scholarly journals Assessment of ampicillin removal efficiency from aqueous solution by polydopamine/zirconium(iv) iodate: optimization by response surface methodology

RSC Advances ◽  
2020 ◽  
Vol 10 (34) ◽  
pp. 20322-20337 ◽  
Author(s):  
Nafisur Rahman ◽  
Poornima Varshney
Keyword(s):  
Aqueous Solution ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Removal Efficiency

Polydopamine/zirconium(iv) iodate was prepared by incorporating polydopamine into zirconium iodate gel and studied as an effective adsorbent for ampicillin.

scholarly journals Arsenic removal by the micellar-enhanced ultrafiltration using response surface methodology

2019 ◽  
Vol 20 (2) ◽  
pp. 574-585 ◽  
Author(s):  
Oznur Begum Gokcek ◽  
Nigmet Uzal
Keyword(s):  
Response Surface Methodology ◽  
Aqueous Solutions ◽  
Response Surface ◽  
Removal Efficiency ◽  
Surfactant Concentration ◽  
Arsenic Removal ◽  
Operating Conditions ◽  
Optimum Operating ◽  
Micellar Enhanced Ultrafiltration ◽  
The Impact

Abstract The present research investigates the removal of arsenic (As) from aqueous solutions using micellar-enhanced ultrafiltration (MEUF) by utilizing two different surfactants: benzethonium chloride and dodecyl pyridinium chloride (BCl and DPCl). The impact of the operating variables and maximum removal efficiency were found under different conditions for BCl and DPCl surfactants. The maximum As rejection efficiency for MEUF with BCl and DPCl surfactants is 92.8% and 84.1%, respectively. In addition to this, a statistics-based experimental design with response surface methodology was used for the purpose of examining the impact of operating conditions, including initial pH, initial As concentration (ppb), and surfactant concentration (BCl, mM) in As-removal from aqueous solutions. In the analysis of the experimental data, a second-order polynomial model that was validated by statistical analysis for the BCl surfactant was used. On the basis of the response model created, the removal of As ions was acquired at optimum operating parameters, including the initial As concentration of 150 ppb, surfactant concentration of 5 mM and pH 10 for the BCl surfactant with 92.8% As-removal efficiency.

scholarly journals Adsorption of Remazol Brillant Green 6B (RBG 6B) on chitin: process optimization using response surface methodology

2018 ◽  
Vol 20 (2) ◽  
pp. 257-268 ◽  
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Removal Efficiency ◽  
Dye Removal ◽  
Freundlich Isotherm ◽  
Sem Analysis ◽  
Second Order ◽  
Operating Conditions ◽  
Coefficient Of Determination ◽  
Solution Ph

In the present study, the adsorption of Remazol Brillant Green 6B (RBG 6B) on chitin which characterized by BET, FTIR, XRD and SEM analysis was studied. Response surface methodology (RSM) was applied to determine interaction between solution pH, initial RBG 6B concentration and chitin dosage being individual variables and to optimize operating conditions. According to results of variance analysis (ANOVA), the second order polynomial model was statistically significant (P<0.0001) and coefficient of determination value (R2=0.98) was high. It was determined that dye removal efficiency increased when low solution pH and initial RBG 6B dye concentration and high chitin dosage were used. The maximum dye removal efficiency was obtained as 88% at solution pH of 3.0, initial RBG 6B concentration of 75 mg L-1 and chitin dosage of 5.0 g L-1. The isotherms and kinetics studies showed that Freundlich isotherm and pseudo-second-order kinetics model fitted well to the RBG 6B adsorption data.

Statistical Optimization for Dye Removal from Aqueous Solution by Cross-linked Chitosan Composite

2020 ◽  
Vol 14 (2) ◽  
pp. 1 ◽  
Author(s):  
Ali Jawad ◽  
Mohd shafiq Bin Aazmi ◽  
Ali Jawad
Keyword(s):  
Aqueous Solution ◽  
Response Surface Methodology ◽  
Methyl Orange ◽  
Response Surface ◽  
Removal Efficiency ◽  
Dye Removal ◽  
Statistical Optimization ◽  
P Value ◽  
Box Behnken Design ◽  
Chitosan Composite

Response surface methodology-Box–Behnken design (RSM-BBD) was employed to optimize the methyl orange (MO) dye removal efficiency from aqueous solution by cross-linked chitosan-tripolyphosphate/nano-titania composite (Chi-TPP/NTC). The influence of pertinent parameters, i.e. A: TiO2 loading (0- 50 %), B: dose (0.04-0.14 g), C: pH (4-10), and D: temperature (30-50 oC) on the MO removal efficiency were tested and optimized using RSM-BBD. The F-values of BBD model for MO removal efficiency was 93.4 (corresponding p-value < 0.0001). The results illustrated that the highest MO removal efficiency (87.27 %) was observed at the following conditions: TiO2 loading (50% TiO2), dose (0.09 g), pH 4.0, and temperature of 40 oC.  

scholarly journals Optimization of photocatalytic degradation of naproxen from aqueous solutions with UV/ZnO process: Response Surface Methodology (RSM)

2020 ◽  
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Removal Efficiency ◽  
Contact Time ◽  
Operating Conditions ◽  
Quadratic Model ◽  
Order Model ◽  
First Order ◽  
Concentration Time ◽  
Central Composite

<p>The aim of this study was to optimize the removal of Naproxen (NPX) by the UV/ZnO photocatalytic process using response surface methodology based on Central Composite Design (CCD). The effect of parameters such as ZnO concentration, contact time, pH, temperature, and initial NPX concentration were studied. The ANOVA results indicated high coefficient values of adjusted R2 (0.9843) and predicted R2 (0.9695). The quadratic model with the highest R-squared designation was chosen to predict the NPX removal efficiency of the UV/ZnO process. Under optimal conditions that include an optimum initial NPX concentration of 21.59 mg/L, ZnO concentration of 371.15 mg/L, contact time of 73.92 min, pH of 6.87, and temperature of 24.35°C, a NPX removal efficiency value of 71.19% was obtained. The results show that the removal of NPX is most affected by the variables- initial NPX concentration, time, pH, and ZnO concentration, respectively, but temperature as a variable does not have a significant effect on the efficiency of the process. Moreover, the NPX photodegradation kinetics can be explained through the pseudo-first-order model. The UV/ZnO photocatalytic method has high potential for the removal of NPX, and that CCD is an appropriate method to optimize the operating conditions for NPX photodegradation.</p>

Comparative Bio-sorption of Cadmium and Nickel Ions from Aqueous Solution onto Fibers of Date Palm using Fluidized Bed Column

2019 ◽  
Vol 70 (5) ◽  
pp. 1507-1512
Author(s):  
Baker M. Abod ◽  
Ramy Mohamed Jebir Al-Alawy ◽  
Firas Hashim Kamar ◽  
Gheorghe Nechifor
Keyword(s):  
Aqueous Solution ◽  
Heavy Metal ◽  
Metal Ions ◽  
Fluidized Bed ◽  
Removal Efficiency ◽  
Heavy Metal Ions ◽  
Date Palm ◽  
Operating Conditions ◽  
Initial Concentration ◽  
Bed Height

The aim of this study is to use the dry fibers of date palm as low-cost biosorbent for the removal of Cd(II), and Ni(II) ions from aqueous solution by fluidized bed column. The effects of many operating conditions such as superficial velocity, static bed height, and initial concentration on the removal efficiency of metal ions were investigated. FTIR analyses clarified that hydroxyl, amine and carboxyl groups could be very effective for bio-sorption of these heavy metal ions. SEM images showed that dry fibers of date palm have a high porosity and that metal ions can be trapped and sorbed into pores. The results show that a bed height of 6 cm, velocity of 1.1Umf and initial concentration for each heavy metal ions of 50 mg/L are most feasible and give high removal efficiency. The fluidized bed reactor was modeled using ideal plug flow and this model was solved numerically by utilizing the MATLAB software for fitting the measured breakthrough results. The breakthrough curves for metal ions gave the order of bio-sorption capacity as follow: Cd(II)]Ni(II).

scholarly journals Effective Chromium Adsorption From Aqueous Solutions and Tannery Wastewater Using Bimetallic Fe/Cu Nanoparticles: Response Surface Methodology and Artificial Neural Network

2021 ◽  
Vol 14 ◽  
pp. 117862212110281
Author(s):  
Ahmed S. Mahmoud ◽  
Nouran Y. Mohamed ◽  
Mohamed K. Mostafa ◽  
Mohamed S. Mahmoud
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Industrial Effluent ◽  
Oxygen Demand ◽  
Operating Conditions ◽  
Tannery Wastewater ◽  
P Value ◽  
Cu Nanoparticles ◽  
Artificial Neural ◽  
Cr Removal

Tannery industrial effluent is one of the most difficult wastewater types since it contains a huge concentration of organic, oil, and chrome (Cr). This study successfully prepared and applied bimetallic Fe/Cu nanoparticles (Fe/Cu NPs) for chrome removal. In the beginning, the Fe/Cu NPs was equilibrated by pure aqueous chrome solution at different operating conditions (lab scale), then the nanomaterial was applied in semi full scale. The operating conditions indicated that Fe/Cu NPs was able to adsorb 68% and 33% of Cr for initial concentrations of 1 and 9 mg/L, respectively. The removal occurred at pH 3 using 0.6 g/L Fe/Cu dose, stirring rate 200 r/min, contact time 20 min, and constant temperature 20 ± 2ºC. Adsorption isotherm proved that the Khan model is the most appropriate model for Cr removal using Fe/Cu NPs with the minimum error sum of 0.199. According to khan, the maximum uptakes was 20.5 mg/g Cr. Kinetic results proved that Pseudo Second Order mechanism with the least possible error of 0.098 indicated that the adsorption mechanism is chemisorption. Response surface methodology (RSM) equation was developed with a significant p-value = 0 to label the relations between Cr removal and different experimental parameters. Artificial neural networks (ANNs) were performed with a structure of 5-4-1 and the achieved results indicated that the effect of the dose is the most dominated variable for Cr removal. Application of Fe/Cu NPs in real tannery wastewater showed its ability to degrade and disinfect organic and biological contaminants in addition to chrome adsorption. The reduction in chemical oxygen demand (COD), biological oxygen demand (BOD), total suspended solids (TSS), total phosphorus (TP), total nitrogen (TN), Cr, hydrogen sulfide (H2S), and oil reached 61.5%, 49.5%, 44.8%, 100%, 38.9%, 96.3%, 88.7%, and 29.4%, respectively.

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.

Sign in / Sign up

Export Citation Format

Share Document