Determination of arsenic removal efficiency by ferric ions using response surface methodology

Arsenic contamination of drinking water is a serious problem in many parts of the world. The precipitation/coprecipitation method was used for arsenic removal from drinking water by ferric chloride, ferric sulfate and ferrous sulfate as coagulant. A Box-Behnken statistical experiment design method was used to investigate the effects of major operating variables such as initial arsenate concentration (10-1000 mu g L-1). coagulant dose (0.5-60 mg L-1) and pH (4-9) were investigated. Experimental data were used for determination of the response functions coefficients. Predicted values of arsenate removal obtained using the response functions were in good agreement with the experimental data. Fe(III) ions were more effective and economic than Fe(II) ion due to required lower coagulant dose and pH. In the low initial arsenate concentrations, the highest arsenate removal efficiency was required high ferric chloride and ferric sulfate dose of 50 and 40 mg L-1, while in the high initial arsenate concentrations, the highest arsenate removal efficiency was provided at low ferric chloride and ferric sulfate dose of 37 and 32 mg L-1, respectively. This study showed that Box-Behnken design and response surface methodology was reliable and effective in determining the optimum conditions for arsenic removal by coagulation and flocculation. (C) 2008 Elsevier B.V. All rights reserved

A statistical experiment design approach for arsenic removal by coagulation process using aluminum sulfate

Arsenic removal from drinking water by precipitation-coprecipitation method using aluminum sulfate was investigated. The Box-Behnken statistical experiment design (BBD) and response surface methodology (RSM) were used to investigate the effects of major operating variables. Initial arsenate concentration, pH, and aluminum sulfate dose were selected as independent variables in BBD while arsenate removal was considered as the response function. The predicted values of arsenate removal obtained using the response function were in good agreement with the experimental data. Aluminum sulfate was found as effective and reliable coagulant due to required dose, residual arsenate and aluminum concentration. The optimum pH range for maximum arsenate removal was 6-8. In the low initial arsenate concentrations, the highest arsenate removal efficiency was obtained at high aluminum sulfate doses, while in the high initial arsenate concentrations, the highest arsenate removal efficiency was provided at low coagulant doses. This study showed that statistical design methodology was an efficient and feasible approach in determining the optimum conditions for arsenic removal by coagulation and flocculation. The use of all types of coagulant aids increased the removal efficiency of the treatment method but application of cationic polyelectrolyte was more effective than anionic and nonionic ones. © 2009 Elsevier B.V. All rights reserved

Graphene oxide-iron modified clinoptilolite based composites for adsorption of arsenate and optimization using response surface methodology

In this study, graphene oxide and composites of graphene oxide-iron modified clinoptilolite were synthesized and used for arsenate removal from aqueous solution. All adsorbents were characterized using X-ray diffraction and specific surface area analysis. The specific surface areas of composites were found to be less than the iron modified clinoptilolite. The time required to reach equilibrium was determined as 3 hours for all adsorbents. The Box-Behnken statistical experiment design method was used to determine the effects of initial arsenate concentration, pH and the amount of adsorbent on the percent arsenate removal. Graphene oxide was not as effective as composites for arsenate adsorption from water. Arsenate adsorption on composites was showed good compatibility with the Freundlich isotherm. The maximum arsenate uptake was realized at pH 4 for graphene oxide and at pH 7 for composites. The maximum adsorption capacities obtained at the optimum points determined by using the Box-Behnken design method were calculated as 39.49, 117.98 and 124.64 mu g.g(-1) for graphene oxide and composites, respectively.Scientific Research Projects Department of the Pamukkale University, Denizli, Turkey [2018FEBE047]This study was supported by the Scientific Research Projects Department of the Pamukkale University, Denizli, Turkey under grant number of 2018FEBE047

Removal of arsenate using graphene oxide-iron modified clinoptilolite-based composites: adsorption kinetic and column study

In this study, graphene oxide (GO), iron modified clinoptilolite (FeZ), and composites of GO-FeZ (GOFeZA and GOFeZB) were synthesized and characterized using SEM, EDS, XRF, FTIR, and pH(pzc). The arsenate uptake on composites of GOFeZA and GOFeZB was examined by both kinetic and column studies. The adsorption capacity increases with the increase of the initial arsenate concentration at equilibrium for both composites. At the initial arsenate concentration of 450 mu g/L, the arsenate adsorption on GOFeZA and GOFeZB was 557.86 and 554.64 mu g/g, respectively. Arsenate adsorption on both composites showed good compatibility with the pseudo second order kinetic model. The adsorption process was explained by the surface complexation or ion exchange and electrostatic attraction between GOFeZA or GOFeZB and arsenate ions in the aqueous solution due to the relatively low equilibrium time and fairly rapid adsorption of arsenate at the beginning of the process. The adsorption mechanism was confirmed by characterization studies performed after arsenate was loaded onto the composites. The fixed-bed column experiments showed that the increasing the flow rate of the arsenate solution through the column resulted in a decrease in empty bed contact time, breakthrough time, and volume of treated water. As a result of the continuous operation column study with regenerated GOFeZA, it was demonstrated that the regenerated GOFeZA has lower breakthrough time and volume of treated water compared to fresh GOFeZA.Scientific Research Projects of the Pamukkale University, Denizli, Turkey [2018FEBE047]This work was supported by the Scientific Research Projects of the Pamukkale University, Denizli, Turkey, under grant number 2018FEBE047

Synthesis and characterization of novel activated carbon from Medlar seed for chromium removal: Experimental analysis and modeling with artificial neural network and support vector regression

In this study, for the first time the activated carbon has been produced from medlar seed (Mespilus germanica) via chemical activation with KOH. The carbonization process was carried out at different temperatures of 450, 550, 650 and 750 °C. The Nitrogen adsorption-desorption, Fourier transform infrared spectroscopy (FTIR) and Field Emission Scanning Electron Microscope (FESEM) analyses were carried out on the adsorbents. The effect of operating parameters, such as pH, initial concentration of Cr(VI), adsorbent dosage and contact time were investigated. The experimental data showed better agreement with the Langmuir model and the maximum adsorption capacity was evaluated to be 200 mg/g. Kinetic studies indicated that the adsorption process follows the pseudo second-order model and the chemical reaction is the rate-limiting step. Thermodynamic parameters showed that the adsorption process could be considered a spontaneous (ΔG < 0), endothermic (ΔH > 0) process which leads to an increase in entropy (ΔS > 0). The application of support vector machine combined with genetic algorithm (SVM-GA) and artificial neural network (ANN) was investigated to predict the percentage of chromium removal from aqueous solution using synthesized activated carbon. The comparison of correlation coefficient (R2) related to ANN and the SVR-GA models with experimental data proved that both models were able to predict the percentage of chromium removal, by synthetic activated carbon while the SVR-GA model prediction was more accurate

Application of colloidal gas aphron suspensions produced from Sapindus mukorossi for arsenic removal from contaminated soil

Colloidal gas aphron dispersions (CGAs) can be described as a system of microbubbles suspended homogenously in a liquid matrix. This work examines the performance of CGAs in comparison to surfactant solutions for washing low levels of arsenic from an iron rich soil. Sodium Dodecyl Sulfate (SDS) and saponin, a biodegradable surfactant, obtained from Sapindus mukorossi or soapnut fruit were used for generating CGAs and solutions for soil washing. Column washing experiments were performed in down-flow and up flow modes at a soil pH of 5 and 6 using varying concentration of SDS and soapnut solutions as well as CGAs. Soapnut CGAs removed more than 70% arsenic while SDS CGAs removed up to 55% arsenic from the soil columns in the soil pH range of 5–6. CGAs and solutions showed comparable performances in all the cases. CGAs were more economical since it contains 35% of air by volume, thereby requiring less surfactant. Micellar solubilization and low pH of soapnut facilitated arsenic desorption from soil column. FT-IR analysis of effluent suggested that soapnut solution did not interact chemically with arsenic thereby facilitating the recovery of soapnut solution by precipitating the arsenic. Damage to soil was minimal arsenic confirmed by metal dissolution from soil surface and SEM micrograph