Abstract
In this study, Rosa damascena leaf powder was evaluated as a biosorbent for the removal of copper from aqueous solutions. Process variables such as the biosorbent dose, pH, and initial copper concentration were optimized using response surface methodology. A quadratic model was established to relate the factors to the response based on the Box-Behnken design. Analysis of variance (ANOVA) was used to assess the experimental data, and multiple regression analysis was used to fit it to a second-order polynomial equation. A biosorbent dose of 4.0 g/L, pH of 5.5, and initial copper concentration of 55 mg/L were determined to be the best conditions for copper removal. The removal of Cu(2+) ions was 88.7% under these optimal conditions, indicating that the experimental data and model predictions were in good agreement. The biosorption data were well fitted to the pseudo-second-order and Elovich kinetic models. The combination of film and intra-particle diffusion was found to influence Cu(2+) biosorption. The Langmuir and Dubinin-Radushkevich isotherm models best fit the experimental data, showing a monolayer isotherm with a q(max) value of 25.13 mg/g obtained under optimal conditions. The thermodynamic parameters showed the spontaneity, feasibility and endothermic nature of adsorption. Scanning electron microscopy, energy-dispersive X-ray spectroscopy, and Fourier transform infrared spectroscopy were used to characterize the biosorbent before and after Cu(2+) biosorption, revealing its outstanding structural characteristics and high surface functional group availability. In addition, immobilized R. damascena leaves adsorbed 90.7% of the copper from aqueous solution, which is more than the amount adsorbed by the free biosorbent (85.3%). The main mechanism of interaction between R. damascena biomass and Cu(2+) ions is controlled by both ion exchange and hydrogen bond formation. It can be concluded that R. damascena can be employed as a low-cost biosorbent to remove heavy metals from aqueous solutions.