Optimization techniques for lead (II) ions adsorption from wastewater by graphene oxide from rice straw biomass

Abstract

ABSTRACT Owing to the recent fast industrialization, industrial effluent carrying hazardous heavy metals has resulted in serious environmental problems. Lead (ii) is among the extreme hazardous elements, owing to its solubility, bioaccumulation, and lasting residence periods at low concentrations. Adsorption shows more applicability than other treatment approaches. Numerous investigations have been done to adsorb lead (ii) ions using graphene oxide (GO) from graphite powder. However, graphite is not sustainable. In addition, a number of adsorption optimization techniques have been employed, nonetheless, literature on comparison of these techniques is inadequate with reference to graphene oxide as an adsorbent. Rice straw biomass biochar (RSBB) was generated by pyrolyzing RSB at 400 C. By modifying Hummer's technique, GO was created from RSBB and then characterized by FTIR. Through batch studies, the use of GO from rice straws as an adsorbent for lead (ii) adsorption was optimized. Taguchi L27 (3 5) orthogonal array design with 27 runs as well as RSM with the CCD option with 50 runs on simulated wastewater were employed. The effects of five variables were investigated and these included; adsorbent dose (0.5-1.5g/l), pH (2-10), initial lead ion concentration (20-200 mg/L), contact duration (25-65 minutes) and temperature (20-50 0C). The optimization was performed using the signal-to-noise ratio (SNR) for Taguchi and a desirability function for RSM. Sensitivity analyses were used to ascertain the relative contributions of every individual factor on removal efficiency. One experiment in triplicate was performed to apply the models on real wastewater. Adsorption reaction isotherms and rates were also studied using five experiments each. Lead (ii) adsorption was caused by the carboxyl, hydroxyl, epoxy, and carbonyl functional groups that were present on the surface of the GO. The RSM model and Taguchi model with respective R2 of 0.876 and adjusted R2 of 0.923 were significant. With a removal efficiency of 85.82%, the RSM-CCD ideal conditions were 1.14 g/l adsorbent dose, 130.78 mg/L initial Pb concentration, 49.01 minutes contact time, 34.97 0C, and 6.36 pH. From sensitivity analysis, adsorbent dose had the highest contribution of 35 % towards removal efficiency. The Taguchi optimum control values for the adsorbent dose, initial ion concentration, contact time, temperature and pH are 1.0g, 20 mg/l, 45 minutes, 35oC and 6 respectively which yielded the mean maximum of 82 % removal efficiency. The models demonstrated satisfactory predictability when applied to real wastewater with an absolute percentage error of 0.85 % for Taguchi and 3.39 % for RSM-CCD. Although Taguchi and RSM analyses both revealed similar relationships and near identical values for the optimum experimental parameters, the Taguchi technique was actually more accurate, has less errors due to the least number of experiments. However, RSM is more reliable at foreseeing nonlinear correlations between the experimental parameters and removal efficiency. The adsorption fitted a Langmuir isotherm (R2 of 0.9948) depicting the homogenous monolayer chemisorption and agreed with the pseudo second order (R 2 of 0.99203) model. However, further studies need to be conducted on the adsorption thermodynamics as well as desorption. Key words: Graphene Oxide, Rice straws, Taguchi, Response Surface Methodology, lead adsorption