Magnetic Fe3O4 nanoparticles have been used as adsorbents for the removal of heavy-metal ions. In this study, optimization of the Pb2+ adsorption process using Fe3O4 has been investigated. The adsorbent was characterized by various techniques such as transmission electron microscopy (TEM), energy-dispersive X-ray spectroscopy (EDX), and Brunauer-Emmett-Teller (BET) analysis. The influence of process variables on adsorption of Pb2+ ions in accordance with p < 0.05 was investigated and analyzed by the Box-Behnken design (BBD) matrix with five variables (pH, adsorbent dose, initial Pb2+ ion concentration, contact time, and temperature). The pH and temperature were observed to be the most significant parameters that affected the Pb2+ ion adsorption capacity from the analysis of variance (ANOVA). Conduction of 46 experiments according to BBD and a subsequent analysis of variance (ANOVA) provide information in an empirical equation for the expected response. However, a quadratic correlation was established to calculate the optimum conditions, and it was found that the R 2 value (0.99) is in good agreement with adjusted R 2 (0.98). The optimum process value of variables obtained by numerical optimization corresponds to pH 6, an adsorbent dose of 10 mg, and an initial Pb2+ ion concentration of 110 mg L-1 in 40 min at 40 °C adsorption temperature. A maximum of 98.4% adsorption efficiency was achieved under optimum conditions. Furthermore, the presented model with an F value of 176.7 could adequately predict the response and give appropriate information to scale up the process.
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