Optimization of Manganese Removal from Water Using Response Surface Methodology

Manganese is important for proper functioning of biological systems, but its deficiency or excess could lead to a number of disorders. Excess amount of Mn(II) can cause neurotoxicity to human beings in terms of a syndrome resembling Parkinson’s disease. This study was performed to examine the effect of various operating parameters on percentage of manganese removal from water using zero-valent iron nanoparticles as an adsorbent. A multi-step response surface methodology was applied for the maximum removal of Mn(II) from aqueous solution to optimize the parameters that had an effect on the adsorption studies. A two-level, five factor (25) full factorial central composite design (CCD) using Design Expert Version 9.0.3 (USA) was used for the optimization. From the CCD design it was observed that the maximum removal of Manganese was 92.5 % obtained at pH 9, temperature 25 °C, dose concentration 5 g/L, Mn initial concentration 2.07 g/L for the time period of 6 h. The deviation between the experimental and theoretical result was 0.82 %. Synthesized particles were characterized by scanning electron microscope, X-ray diffraction, and Fourier transform infrared spectra