Optimization of garden radish [raphanus sativus l.] peroxidase enzyme for removal of 2,4-dichlorophenol from 2,4- dichlorophenoxyacetic acid wastewater

ABSTRACT

Environmental pollution by 2,4-dicholorphenol [2,4-DCP], commonly found in industrial wastewater has been a concern for humans over the past 50 years. Garden Radish Peroxidase [GRP] can eliminate this poisonous pollutant. The aim of this study was to apply an experimental Response Surface Methodology [RSM] and Central Composite Design [CCD] to optimize GRP-based treatment in order to maximize the removal of 2,4-DCP from wastewater. The effects of four factors; pH, enzyme activity [U/mL], hydrogen peroxide [H[2]O[2]] concentration [mM], and substrate concentration [mg/L] and their interactions were investigated for 2,4-DCP removal using a second-order polynomial model. The suitability of the polynomial model was described using coefficient of determination [R[2] =90.7%] and the results were created by analysis of variance [ANOVA]. A 3D response surface was made from the mathematical models and then applied to determine the optimal condition. These analyses exhibited that using a quadratic model was fitting for this treatment. Furthermore, desirability function was employed for the specific values of controlled factors for optimization and maximum desirability. Based on the desirability function results, the response predicted a 99.83% removal rate of 2,4-DCP from wastewater with 0.959 desirability. Under these conditions, the experimental removal percentage value would be 99.2%