Optimization of process condition for the preparation of amine-impregnated activated carbon developed for CO2 capture and applied to methylene blue adsorption by response surface methodology

Process Optimization Study of Zn2+ Adsorption on Biochar-Alginate Composite Adsorbent by Response Surface Methodology (RSM)

A novel biochar alginate composite adsorbent was synthesized and applied for removal of Zn2+ ions from aqueous solution. Kinetics, equilibrium and thermodynamic studies showed the suitability of the adsorbent. From a Langmuir isotherm study, the maximum monolayer adsorption capacity of the composite adsorbent was found to be 120 mg/g. To investigate the effect of process variables like initial Zn2+ concentration (25–100 mg/L), adsorbent dose (0.4–8 g/L) and temperature (298–318 K) on Zn2+ adsorption, response surface methodology (RSM) based on a three independent variables central composite design of experiments was employed. A quadratic model equation was developed to predict the relationship between the independent variables and response for maximum Zn2+ removal. The optimization study reveals that the initial Zn2+ concentration and adsorbent dose were the most effective parameters for removal of Zn2+ due to higher magnitude of F-statistic value which effects to a large extent of Zn2+ removal. The optimum physicochemical condition for maximum removal of Zn2+ was determined from the RSM study. The optimum conditions are 43.18 mg/L initial metal ion concentration, 0.062 g adsorbent dose and a system temperature of 313.5 K. At this particular condition, the removal efficiency of Zn2+ was obtained as 85%.

Modeling and optimization of process variables for HCl gas removal by response surface methodology

In the present article, optimization of process variables has been done to maximize the removal efficiency of toxic HCl gas in a submerged self-priming venturi scrubber. Response surface methodology with central composite design has been chosen to predict the effect of process variables on the removal efficiency. A quadratic equation was found from this study to predict the removal efficiency and from the ANOVA test, the significance of process variables was evaluated. Regression analysis confirmed the suitability of the developed model by the higher R² square value (0.9717). Optimum conditions were obtained as 55.18 m s^-1 of throat gas velocity, 405.10 ppm of inlet HCl concentration and 0.0038 N of NaOH concentration in scrubbing liquid to achieve 90.80% of the HCl removal efficiency.

Defluoridation of synthetic and industrial wastewater by using acidic activated alumina adsorbent: characterization and optimization by response surface methodology

Excessive contamination of fluoride in wastewater is the cause of several chronic health problems. For this purpose, an adsorbent was prepared from alumina by acidic activation using sulfuric acid. The current research aims to find the maximum fluoride adsorption (%) from synthetic and industrial wastewater at optimum process parameters by using response surface methodology (RSM). All batch scale experiments were carried out according to the statistical-design order. Central composite design (CCD) was applied to ascertain the effect of adsorbent dose, pH, initial fluoride concentration and temperature on fluoride adsorption (%). Maximum fluoride removal was predicted based on the quadratic model developed. Validation of the model was done with negligible error. The regression coefficient of the model was found to be 0.96. From the analysis of variance (ANOVA), the factors with the greatest effect on the adsorption of fluoride were identified. Under optimized condition, the adsorbent dose 13.89 g L^-1, pH 5.52, temperature 25 °C and initial fluoride concentration 18.67 mg L^-1 resulted in 96% of maximum fluoride adsorption. Under the same optimized parameters, the fluoride adsorption from industrial wastewater found to be 92.10%.