Tetracycline adsorption by tilapia fish bone-based biochar: Mass transfer assessment and fixed-bed data prediction by hybrid statistical-phenomenological modeling

Abstract

Abstract The intense use of antibiotics and their presence in water bodies has risen serious health and environmental concerns. Adsorption stands out as a promising method for the treatment of such persistent contaminants; however, a suitable adsorbent material and operational conditions must consider the specificities of one target pollutant. For an adequate process development, a comprehensive understanding of the involved mechanisms and phenomena are crucial. In this context, the objective of this work was to evaluate the potential of a biochar produced from tilapia fish bone-residue for tetracycline (TC) adsorption, in batch and fixed-bed systems. For this, the biochar was characterized in terms of its textural and surface chemistry properties. Also, a mathematical model was used to support the understanding of mass transfer and equilibrium mechanisms as well as to obtain relevant parameters to support the prediction and scale-up of the adsorption system in fixed bed columns. First, the biochar production was investigated, with the TC removal capacity as a response variable, then biochar (in the best carbonization condition – 550 °C) was submitted to the characterization. In the mathematical modeling, three different rate-limiting steps were applied to kinetic data, namely, external mass transfer resistance (EMTR), internal mass transfer resistance (IMTR) and monolayer-multilayer adsorption (MMA). Based on equilibrium and kinetic parameters obtained in the batch mode, a hybrid (statistical-phenomenological) model was developed to predict the behavior of the breakthrough curves in fixed bed column. IMTR (homogeneous intraparticle diffusion) and BET isotherm models were found to be significantly more consistent with the kinetic and equilibrium data in batch system, indicating that the adsorption kinetics is governed by the internal diffusion of the TC within the biochar porous structure and that the adsorption may undergo multilayer formation for high TC concentration levels. The biochar characterization showed presence of apatites and predominance of a mesoporous structure with a 124 m2 g-1 superficial area. Near-neutral pH conditions, namely, between the isoelectric point of the TC (5.30) and the zero point of surface charge of the biochar (7.81) favored the adsorption process due to electrostatic attraction. Based on the batch parameters the hybrid phenomenological model was able to adequately predict the fixed-bed column performance, which was validated by independent experimental data. Therefore, the predictive model can be useful for adsorption systems scale-up, while presenting potential to predict and optimize fixed bed operational conditions.