کاربرد روش سطح پاسخ جهت بهينه‌سازي حذف رنگ مالاشيت سبز با نانو جاذب Cl-nZVI Application of Response Surface Methodology to Optimize Malachite Green Removal by Cl-nZVI Nanocomposites
Journal Title: آب و فاضلاب - Year 2017, Vol 28, Issue 4
Abstract
Application of Response Surface Methodology to Optimize Malachite Green Removal by Cl-nZVI Nanocomposites F. Ghorbani1, H. Molavi2, S. Fathi3, F. Piri3 1. Faculty Member of Environmental Engineering, Faculty of Natural Resources, Kurdistan University, Sanandaj (Corresponding Author) f.ghorbani@uok.ac.ir 2. MSc Student of Environmental Engineering, Faculty of Natural Resources, Kurdistan University, Sanandaj 3. BSc Student of Environmental Engineering, Faculty of Natural Resources, Kurdistan University, Sanandaj (Received Dec. 8, 2015 Accepted May, 1, 2016) Abstract Disposal of effluents containing dyes into natural ecosystems pose serious threats to both the environment and its aquatic life. Malachite green (MG) is a basic dye that has extensive industrial applications, especially in aquaculture, throughout the world. This study reports on the application of the central composite design (CCD) under the response surface methodology (RSM) for the optimization of MG adsorption from aqueous solutions using the clinoptilolite nano-zerovalence iron (Cl-nZVI) nanocomposites. The sorbent structures produced are characterized by means of scanning electron micrograph (SEM), energy-dispersive X-ray spectroscopy (EDS), and vibrating sample magnetometer (VSM). The effects of different parameters including pH, initial MG concentration, and sorbent dosage on the removal efficiency (R) of MG were studied to find the optimum operating conditions. For this purpose, a total of 20 sets of experiments were designed by the Design Expert.7.0 software and the values of removal efficiency were used as input response to the software. The optimum pH, initial MG concentration, and sorbent dosage were found to be 5.6, 49.21 mg.L-1, and 1.43 g.L-1, respectively. A high MG removal efficiency (57.90%) was obtained with optimal process parameters. Moreover, a desirability value of 0.963 was obtained for the optimization process.
Authors and Affiliations
Farshid Ghorbani, Hadieh Molavi, Somayyeh Fathi, Fatemeh Piry
Keywords
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- EP ID EP243279
- DOI 10.22093/wwj.2017.44300
- Views 84
- Downloads 0
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