Engineering of highly Brachychiton populneus shells@polyaniline bio-sorbent for efficient removal of pesticides from wastewater: Optimization using BBD-RSM approach

[Display omitted] •The BP@PANI composite was facilely prepared by chemical polymerization method for Thiabendazole and Methyl parathion removal.•The experimental results show that the adsorption of TBZ and MP were described by the PSO.•The maximum adsorption amount of TBZ and MP is 255.39 and 78.59 mg. g−1.•RSM-BBD was used to optimize TBZ and MP adsorption conditions. New biocomposite based on polyaniline and Brachychiton populneus shells (BP@PANI) was successfully synthesized through in situ chemical polymerization. The prepared composite was characterized using different analytical techniques such as scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), Fourier transform infrared spectroscopy (FTIR) and Brunauer-Emmett-Teller (BET) analysis. The BP@PANI material was effectively used as an adsorbent to remove thiabendazole (TBZ) and methyl parathion (MP) pesticides from wastewater. The kinetic and equilibrium results indicated that the adsorption process followed the pseudo-second-order model and the Langmuir isotherm. The optimum adsorption amounts were 255.39 and 78.59 mg.g−1 for TBZ and MP, respectively. The biosorption mechanism of both pesticides was evaluated and assigned to electrostatic interactions, pi-pi interactions and hydrogen bonding. The desorption study proved the excellent recycling of BP@PANI biosorbent. Moreover, the biosorption process was optimized by the response surface methodology combined with the Box Behnken design (RSM-BBD). The optimal parameters were found to be : Dose = 0.88 g.L−1, Ci = 5 mg.L−1 and Time = 100 min for TBZ and Dose = 1 g.L−1, Ci = 5 mg.L−1 and Time = 120 min for MP. The predicted elimination efficiency was determined to be 85% for TBZ and 84% for MP. The experimental data obtained were in good agreement with that predicted by the model, which indicates the importance of the RSM approach in terms of modeling and optimization.