Statistical optimization of Methylene Blue dye removal from a synthetic textile wastewater using indigenous adsorbents

Abstract

This study was carried out to determine the most suitable indigenous adsorbents to remove Methylene Blue (MB) dye from aqueous solution and to statistically optimize the removal process parameters. Experiments were performed to investigate the adsorption capacities of indigenous bio-adsorbents such as charcoal, banana leaves ash (BLA), coconut coal, neem seed and rice husk ash to remove dye from industrial effluent. The dye removal process parameters were optimized using the One-Factor-at-a-Time (OFAT) method and statistically using central composite design (CCD). Banana leaves ash with particle sizes of 0.053–0.075 mm was found to be a potential adsorbent for dye removal. Among six parameters pH, incubation temperature and particle size were fixed at 8.7 (without control), 30 ± 0.5 °C (ambient) and 0.053–0.075 mm, respectively from the experimental results using the OFAT method. The other three parameters, adsorbent dose, shaking time and shaking speed were finally optimized statistically. The highest removal of MB (93.75%) was obtained through the statistical experimental design at optimum conditions of 23.9 mg/100 ml adsorbent (BLA) dose, 3 h shaking time and 356 rpm shaking speed. The ANOVA showed that the developed model is highly significant with an R 2 value of 0.99. All model terms are also highly significant (p-value<0.01, except for the interactive terms ‘adsorbent dose’ and ‘shaking time’ (p-value<0.05) (also significance at 5% confidence level). The validation experiment demonstrated great similarity between predicted and experimental results. The study indicates that BLA could be employed as a low-cost alternative adsorbent in wastewater treatment to remove dyes.