Detoxification of photo-catalytically treated 2-chlorophenol: optimization through response surface methodology

2017 ◽  
Vol 76 (2) ◽  
pp. 323-336 ◽  
Author(s):  
Muhammad Z. Ahamd ◽  
S. Ehtisham-ul-Haque ◽  
Numrah Nisar ◽  
Khizar Qureshi ◽  
Abdul Ghaffar ◽  
...  

The present study was conducted to degrade and detoxify 2-chlorophenol (2-CP) under UV irradiation in the presence of titanium dioxide (TiO2) and hydrogen peroxide (H2O2). The treatment efficiency was evaluated on the basis of degradation and cytotoxicity reduction as well as biochemical oxygen demand (BOD), chemical oxygen demand (COD) and total organic carbon (TOC) removal. The process variables such as TiO2, pH, UV irradiation time and H2O2 were optimized. Central composite design in combination with response surface methodology was employed to optimize the process variables. A quadratic model was proposed to predict the treatment efficiency and analysis of variance was used to determine the significance of the variables. The correlation between the experimental and predicted degradation was confirmed by the F and P values (<0.05). The coefficient of determination (R2 = 0.99) were high enough to support the validity of developed model. At optimized conditions, up to 92% degradation of 2-CP was achieved with 3.5 × 10−4 s−1 rate constant. Significant reductions in BOD, COD and TOC values were also achieved. Cytotoxicity was evaluated using bioassays and it was observed that UV/TiO2/H2O2 reduced the cytotoxicity considerably. It is concluded that UV/TiO2/H2O2 could possibly be used to detoxify 2-CP in industrial wastewater.

Molecules ◽  
2021 ◽  
Vol 26 (11) ◽  
pp. 3150
Author(s):  
Mengwei Xu ◽  
Chao Huang ◽  
Jing Lu ◽  
Zihan Wu ◽  
Xianxin Zhu ◽  
...  

Magnetic MXene composite Fe3O4@Ti3C2 was successfully prepared and employed as 17α-ethinylestradiol (EE2) adsorbent from water solution. The response surface methodology was employed to investigate the interactive effects of adsorption parameters (adsorption time, pH of the solution, initial concentration, and the adsorbent dose) and optimize these parameters for obtaining maximum adsorption efficiency of EE2. The significance of independent variables and their interactions were tested by the analysis of variance (ANOVA) and t-test statistics. Optimization of the process variables for maximum adsorption of EE2 by Fe3O4@Ti3C2 was performed using the quadratic model. The model predicted maximum adsorption of 97.08% under the optimum conditions of the independent variables (adsorption time 6.7 h, pH of the solution 6.4, initial EE2 concentration 0.98 mg L−1, and the adsorbent dose 88.9 mg L−1) was very close to the experimental value (95.34%). pH showed the highest level of significance with the percent contribution (63.86%) as compared to other factors. The interactive influences of pH and initial concentration on EE2 adsorption efficiency were significant (p < 0.05). The goodness of fit of the model was checked by the coefficient of determination (R2) between the experimental and predicted values of the response variable. The response surface methodology successfully reflects the impact of various factors and optimized the process variables for EE2 adsorption. The kinetic adsorption data for EE2 fitted well with a pseudo-second-order model, while the equilibrium data followed Langmuir isotherms. Thermodynamic analysis indicated that the adsorption was a spontaneous and endothermic process. Therefore, Fe3O4@Ti3C2 composite present the outstanding capacity to be employed in the remediation of EE2 contaminated wastewaters.


2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Praveen Kumar Siddalingappa Virupakshappa ◽  
Manjunatha Bukkambudhi Krishnaswamy ◽  
Gaurav Mishra ◽  
Mohammed Ameenuddin Mehkri

The present paper describes the process optimization study for crude oil degradation which is a continuation of our earlier work on hydrocarbon degradation study of the isolate Stenotrophomonas rhizophila (PM-1) with GenBank accession number KX082814. Response Surface Methodology with Box-Behnken Design was used to optimize the process wherein temperature, pH, salinity, and inoculum size (at three levels) were used as independent variables and Total Petroleum Hydrocarbon, Biological Oxygen Demand, and Chemical Oxygen Demand of crude oil and PAHs as dependent variables (response). The statistical analysis, via ANOVA, showed coefficient of determination R2 as 0.7678 with statistically significant P value 0.0163 fitting in second-order quadratic regression model for crude oil removal. The predicted optimum parameters, namely, temperature, pH, salinity, and inoculum size, were found to be 32.5°C, 9, 12.5, and 12.5 mL, respectively. At this optimum condition, the observed and predicted PAHs and crude oil removal were found to be 71.82% and 79.53% in validation experiments, respectively. The % TPH results correlate with GC/MS studies, BOD, COD, and TPC. The validation of numerical optimization was done through GC/MS studies and   % removal of crude oil.


Molecules ◽  
2019 ◽  
Vol 24 (4) ◽  
pp. 711 ◽  
Author(s):  
Arief Md Yusof ◽  
Siti Abd Gani ◽  
Uswatun Zaidan ◽  
Mohd Halmi ◽  
Badrul Zainudin

This study investigates the ultrasound-assisted extraction of flavonoids from Malaysian cocoa shell extracts, and optimization using response surface methodology. There are three variables involved in this study, namely: ethanol concentration (70–90 v/v %), temperature (45–65 °C), and ultrasound irradiation time (30–60 min). All of the data were collected and analyzed for variance (ANOVA). The coefficient of determination (R2) and the model was significant in interaction between all variables (98% and p < 0.0001, respectively). In addition, the lack of fit test for the model was not of significance, with p > 0.0684. The ethanol concentration, temperature, and ultrasound irradiation time that yielded the maximum value of the total flavonoid content (TFC; 7.47 mg RE/g dried weight (DW)) was 80%, 55 °C, and 45 min, respectively. The optimum value from the validation of the experimental TFC was 7.23 ± 0.15 mg of rutin, equivalent per gram of extract with ethanol concentration, temperature, and ultrasound irradiation time values of 74.20%, 49.99 °C, and 42.82 min, respectively. While the modelled equation fits the data, the T-test is not significant, suggesting that the experimental values agree with those predicted by the response surface methodology models.


2021 ◽  
Author(s):  
M.A. Olivares-Ramírez ◽  
Leticia López-Zamora ◽  
M.J. Peña-Juárez ◽  
E.J. Gutiérrez-Castañeda ◽  
J.A. Gonzalez-Calderon

Abstract The present work shows the implementation of the Response Surface Methodology (RSM), fed by an experimental Central Composite Design (CCD) to find the conditions that allow maximizing the inhibition of the microorganism Staphylococcus aureus with nanoparticles of TiO2 silanized with 3-Aminopropyltriethoxysilane (APTES) and doped with Ag. In addition, Poly(lactic) acid composites were prepared with these Ag/TiO2 nanoparticles with the aim to confer their antimicrobial effect. The independent variables considered were pH, AgNO3/TiO2 ratio (% w/w), and TiO2 nanoparticles concentration (g/250 mL), and as the variable of response, the length of the diameter of the halo or zone of inhibition presented by the microorganism (mm). Statistical analysis found that maximization of S. aureus inhibition occurs at intermediate levels with a value of 10 for pH and 5 g of TiO2 solids, while for the concentration of AgNO3 high levels are required, greater than 10% w/w. Likewise, the statistical significance was determined using the Student's t-test and the p-value; it was found that the significant effect corresponds to the concentration of AgNO3, so a second experimental CCD design equirradial with two factors was considered, estimating AgNO3 concentration and TiO2 amount, the pH at constant 10 value. The second experimental design indicated that maximization in S. aureus inhibition occurs at an AgNO3 concentration between 20-25% w/w with high amounts of TiO2 solids (7-8 g), with a resulting zone of inhibition between 26-28 mm. The quadratic model obtained, which represents the relationship between the length of the zone of inhibition with the variables considered, shows an adjustment of experimental data with a coefficient of determination (R2) of 0.82.


2011 ◽  
Vol 2011 ◽  
pp. 1-9 ◽  
Author(s):  
C. K. Venil ◽  
V. Mohan ◽  
P. Lakshmanaperumalsamy ◽  
M. B. Yerima

An indigenous bacterium, Bacillus REP02, was isolated from locally sourced chromium electroplating industrial effluents. Response surface methodology was employed to optimize the five critical medium parameters responsible for higher % Cr2+ removal by the bacterium Bacillus REP02. A three-level Box-Behnken factorial design was used to optimize K2HPO4, yeast extract, MgSO4, NH4NO3, and dextrose for Cr2+ removal. A coefficient of determination (R2) value (0.93), model F-value (3.92) and its low P-value (F<0.0008) along with lower value of coefficient of variation (5.39) indicated the fitness of response surface quadratic model during the present study. At optimum parameters of K2HPO4 (0.6 g L−1), yeast extract (5.5 g L−1), MgSO4 (0.04 g L−1), NH4NO3 (0.20 g L−1), and dextrose (12.50 g L−1), the model predicted 98.86% Cr2+ removal, and experimentally, 99.08% Cr2+ removal was found.


Processes ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 588
Author(s):  
Poh Gaik Law ◽  
Noor Haida Sebran ◽  
Ashraf Zin Zawawi ◽  
Azlan Shah Hussain

Statistical-based study using response surface methodology (RSM) was conducted to study the effects of process parameters towards biomass hydrogenation. Using Malaysian oil palm empty fruit bunches (EFB) fibres as feedstock, the central composite design (CCD) technique was employed and 18 runs were generated by CCD when four parameters (mass ratio of binary catalyst, hydrogen pressure, temperature and mass ratio of catalyst to feedstock) were varied with two center points to determine the effects of process parameters and eventually to get optimum ethylene glycol (EG) yield. RSM with quadratic function was generated for biomass hydrogenation, indicating all factors except temperature, were important in determining EG yield. Analysis of variance (ANOVA) showed a high coefficient of determination (R2) value of >0.98, ensuring a satisfactory prediction of the quadratic model with experimental data. The quadratic model suggested the optimum EG yield should be >25 wt.% and the EG yield results were successfully reproduced in the laboratory.


2012 ◽  
Vol 66 (4) ◽  
pp. 816-823 ◽  
Author(s):  
Zhang Huiqing ◽  
Ye Chunsong ◽  
Zhang Xian ◽  
Yang Fan ◽  
Yang Jun ◽  
...  

The objective of this study was aimed at investigating the removal of chemical oxygen demand (COD) from reverse osmosis (RO) concentrated coking wastewater by the photo-Fenton process. The optimum extraction conditions for the photo-Fenton process by Box–Behnken design (BBD) and response surface methodology (RSM) to establish a predictive polynomial quadratic model were discussed based on a single factor test. Optimized parameters validated by the analysis of variances (ANOVA) were found to be H2O2 concentration of 345.2 mg/L, pH value of 4.1 and reaction time of 103.5 minutes under ultraviolet irradiation. The experimental results of the COD removal under the optimized conditions presented better agreement with the predicted values with deviation error of 3.2%. The results confirmed that RSM based on BBD was a suitable method to optimize the operating conditions of RO concentrated coking wastewater.


2017 ◽  
Vol 69 (3) ◽  
pp. 387-392 ◽  
Author(s):  
Nor Syahirah Mohamad ◽  
Salmiah Kasolang

Purpose An optimized model is often deployed to reduce trial and error in experimental approach and obtain the multi-variant correlation. In this study, response surface methodology (RSM), namely, Box–Behnken design (BBD) approach, has been used to optimize the characterization of lubricant with additives. BBD is based on multivariate analysis whereby the effects of different parameters are considered simultaneously. It is a non-linear system which is more representative of the actual phenomenon. This study aims to investigate the effect of three independent variables, namely, speed, load and concentration of TiO2, on the coefficient of friction (CoF). Design/methodology/approach RSM was applied to get the multiplicity of the self-determining input variables and construct mathematical models. Mathematical models were established to predict the CoF and to conduct a statistical analysis of the independent variables’ interactions on response surface using Minitab 16.0 statistical software. Three parameters were regulated: speed (X1), load (X2) and concentration of TiO2 (X3). The output measured was the CoF. Findings The result obtained from BBD has shown that the most influential parameter was speed, followed by concentration of TiO2 nanoparticles and then normal load. Analysis of variance indicated that the proposed experiment from the quadratic model has successfully interpreted the experimental data with a coefficient of determination R2 = 0.9931. From the contour plot of BBD, the optimization zone for interacting variables has been obtained. The zone indicates two regions of lower friction values (<0.04): concentration between 0.5 to 1.0 Wt.% for a speed range of 1,000 to 2,000 rpm, and load between 17 to 20 kg for a speed in the range of 1,200 to 1,900 rpm. The optimized condition shows that the minimum value of CoF (0.0191) is at speed of 1,782 rpm, load of 20 kg and TiO2 concentration of 1.0 Wt.%. Originality/value In general, it has been shown that RSM is an effective and powerful tool in experimental optimization of multi-variants.


2020 ◽  
Author(s):  
Deepa Prabhu ◽  
P. R. Prabhu ◽  
Padmalatha Rao

Abstract This study focuses on investigating the effect of Terminalia chebula Ritz. extract (TCE) for corrosion inhibition of Al in phosphoric acid (H3PO4) using potentiodynamic polarization (PDP) technique. In this study, the effect of concentration of TCE extract, the concentration of H3PO4 acid medium, and temperature (T) was investigated on the corrosion current density (icorr) and inhibition efficiency (IE). The TCE was characterized by FTIR analysis, and the adsorption of TCE was justified with the help of kinetic, thermodynamic, adsorption isotherm parameters. The surface morphology study was done using scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDXS), and atomic force microscopy (AFM). The study also focuses on identifying the optimum process parameters for obtaining the maximum IE by applying the response surface methodology (RSM) and desirability function approach. The maximum IE of 83.24% was achieved at a temperature of 30 ℃, the concentration of TCE extract of 500 ppm, and H3PO4 acid concentration of 0.5 M. Regression analysis, Pareto chart, normal chart, main effect, and interaction effect plots are employed to acquire an in-depth understanding of process variables on IE. The IE obtained from the experiments and the predicted model is in a close match and a high value of the coefficient of determination (R2 = 99.98%) displays that the generated model was able to estimate the IE accurately from the selected process variables.


2015 ◽  
Vol 16 (3) ◽  
pp. 783-793 ◽  
Author(s):  
Sajida Rasheed ◽  
Luiza. C. Campos ◽  
Jong. K. Kim ◽  
Qizhi Zhou ◽  
Imran Hashmi

A response surface methodology (RSM) applying central composite design with rotatable full factorial (14 non-center and six center points) was used to discern the effect of granular activated carbon (GAC), sand and pH on total trihalomethanes (TTHMs) and humic acid (HA) removal from drinking water. Results showed efficient TTHMs and HA removal by GAC while a sand column showed little effect for TTHMs but was significant for total organic carbon (TOC) removal. With GAC and a sand column of 4 cm, a pH increase from 6 to 8 caused an increase in TTHM removal from 79.8 to 83.6% while a decrease in HA removal from 26.6 to 6.6% was observed. An increase in GAC column depth from 10 to 20 cm caused a slight increase in TTHM removal from 99.4 to 99.7%, while TOC removal was increased from an average of 38.85% to 57.4% removal. The developed quadratic model for TTHM removal (p = 0.048) and linear model for TOC removal (p = 0.039) were significant. GAC column depth (p &lt; 0.0117) and column depth2 (p &lt; 0.039) were the most significant factors. A 98% TTHMs, 30%TOC and 51% residual chlorine removal were optimized at 9 cm GAC and 4 cm sand column depth at pH 8 with desirability factor (D) 0.64.


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