Dynamic Removal of Nickel (II) on Elaeis guineensis Waste Bed: Study of the Breakage Curve and Simulation

Candelaria Tejada-Tovar (), Angel Villabona-Ortíz and Ángel Darío González-Delgado
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Candelaria Tejada-Tovar: Process Design, and Biomass Utilization Research Group (IDAB), Chemical Engineering Department, Universidad de Cartagena, Avenida del Consulado St. 30, Cartagena de Indias 130015, Colombia
Angel Villabona-Ortíz: Process Design, and Biomass Utilization Research Group (IDAB), Chemical Engineering Department, Universidad de Cartagena, Avenida del Consulado St. 30, Cartagena de Indias 130015, Colombia
Ángel Darío González-Delgado: Nanomaterials and Computer-Aided Process Engineering Research Group (NIPAC), Chemical Engineering Department, Universidad de Cartagena, Avenida del Consulado St. 30, Cartagena de Indias 130015, Colombia

IJERPH, 2022, vol. 19, issue 24, 1-10

Abstract: This research focused on the use of residual fiber from oil palm ( Elaeis guineensis ) for Ni (II) adsorption in a packed bed column. An analysis was conducted on the effect and statistical incidence of changes in temperature, adsorbent particle size, and bed height on the adsorption process. The results showed that particle size and bed height significantly affect the adsorption of Ni (II) ions, reaching adsorption efficiencies between 87.24 and 99.86%. A maximum adsorption capacity of 13.48 mg/g was obtained in the bed with a break time of 180 min. The Ni (II) adsorption in the dynamic system was evaluated by the analysis of the breakage curve with different theoretical models: Yoon–Nelson, dose–response, and Adams–Bohart; the dose–response model was the most appropriate to describe the behavior of the packed bed with an R 2 of 84.56%. The breakthrough curve obtained from Aspen Adsorption ® appropriately describes the experimental data with an R 2 of 0.999. These results indicate that the evaluated bioadsorbent can be recommended for the elimination of Ni (II) in aqueous solutions in a dynamic system, and the simulation of the process can be a tool for the scalability of the process.

Keywords: adsorption; heavy metals; dose–response model; oil palm; agro-industrial waste; Aspen Adsorption (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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