Sensitivity Analysis with the Monte Carlo Method and Prediction of Atenolol Removal Using Modified Multiwalled Carbon Nanotubes Based on the Response Surface Method: Isotherm and Kinetics Studies

Abstract

Atenolol (ATN) is a β-blocker drug extensively used to treat arrhythmias and high blood pressure. Because the human body cannot metabolize it completely, this drug has been commonly found in many environmental matrices. In the present study, the response surface method (RSM) was used for adsorption prediction of ATN on modified multiwalled carbon nanotubes (M-MWCNTs) by NaOCl and ultrasonic. The sensitivity analysis was done by the Monte Carlo method. Sensitivity analysis was performed to determine the effective parameter by the Monte Carlo simulator. Statistical analysis of variance (ANOVA) was performed by using the nonlinear second-order model of RSM. The influential parameters including contact time (min), adsorbent dosage (g/L), pH, and the initial concentration (mg/L) of ATN were investigated, and optimal conditions were determined. Kinetic of ATN adsorption on M-MWCNTs was evaluated using pseudo-first, pseudo-second-order, and intraparticle diffusion models. Equilibrium isotherms for this system were analyzed by the ISOFIT software. As per our result, optimum conditions in the adsorption experiments were pH 7, 60 min of contact time, 0.5 mg/L ATN initial concentration, and 150 mg/L adsorbent dose. In terms of ATN removal efficiency, coefficients of R2 and adjusted R2 were 0.999 and 0.998, respectively. Sensitivity analysis also showed that contact time has the greatest effect on increasing the removal of ATN. Pseudo-first-order (R2 value of 0.99) was the best kinetic model for the adsorption of ATN, and for isotherm, BET (AICC value of 3.27) was the best model that fit the experimental data. According to the obtained results from sensitive analysis, time was the most important parameter, and after that, the adsorbent dose and pH affect positively on ATN removal efficiency. It can be concluded that the modified multiwalled carbon nanotubes can be applied as one of the best adsorbents to remove ATN from the aqueous solution.

Artificial Neural Networks and Genetic Algorithms: An Efficient Modeling and Optimization Methodology for Degradation of Atenolol Using Activated Persulfate with Ultrasound

“…In recent decades, a group of emerging pollutants, pharmaceutical and personal care products (PPCPs), and medical compounds, due to worldwide use and complex sustainable structures, are one of the major environmental problems, which have attracted increasing attention [1,2]. Atenolol (ATN) is a representative PPCP compound and one kind of the most prescribed antagonist β-blocker drugs that has been used for nearly 40 years, commonly used to treat hypertension, arrhythmia, glaucoma, and angina, and against coronary heart diseases [1,3,4].…”

“…Advanced oxidation processes (AOPs) are generally defned as oxidation methods and in the last decade have received special attention due to being economical and having high efciency. AOPs are primarily based on producing high oxidizing radicals such as OH•, O•, and SO 4 • that can remove a large range of organic pollutants [16,17].…”