Simulation of Pb(II) and Ni(II) Adsorption in a Packed Column: Effects of Bed Height, Flow Rate, and Initial Concentration on Performance Metrics

Numerous studies have been conducted employing various techniques to remove pollutants from water bodies. Among these techniques, adsorption a surface phenomenon that utilises adsorbents derived from agricultural residues has shown considerable potential for the removal of contaminants such as heavy metals. However, most of these investigations have been carried out at the laboratory scale, with limited efforts directed towards predicting the performance of these systems at an industrial level. Accordingly, the present study aims to model a packed bed column at industrial scale for the removal of Pb(II) and Ni(II) ions from aqueous solutions, employing biomass derived from oil palm residues as the adsorbent material. To achieve this, Aspen Adsorption was used as a modelling and simulation tool to evaluate the impact of bed height, inlet flow rate, and initial concentration through a parametric assessment. This evaluation incorporated the Freundlich, Langmuir, and Langmuir–Freundlich isotherm models in conjunction with the Linear Driving Force (LDF) kinetic model. The results indicated that the optimal operating parameters included a column height of 5 m, a flow rate of 250 m3/day, and an initial metal concentration of 5000 mg/L. Moreover, all models demonstrated removal efficiencies of up to 94.6% for both Pb(II) and Ni(II). An increase in bed height resulted in longer breakthrough and saturation times but led to a reduction in adsorption efficiency. Conversely, higher flow rates shortened these times yet enhanced efficiency. These findings underscore the potential of computational modelling tools as predictive instruments for evaluating the performance of adsorption systems at an industrial scale.

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Journal
Processes
Published
2025-07-05
DOI
https://doi.org/10.3390/pr13072141
Citations
2
Primary Topic
Adsorption and biosorption for pollutant removal
Type
article
Field-Weighted Citation Impact
1.63
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article

Simulation of Pb(II) and Ni(II) Adsorption in a Packed Column: Effects of Bed Height, Flow Rate, and Initial Concentration on Performance Metrics

Ángel Darío González-Delgado, Candelaria Tejada-Tovar, Rodrigo Ortega‐Toro, Ángel Villabona-Ortíz et al.
2 citations
Processes
Adsorption and biosorption for pollutant removal
1.63
article

Simulation of Pb(II) and Ni(II) Adsorption in a Packed Column: Effects of Bed Height, Flow Rate, and Initial Concentration on Performance Metrics

Ángel Darío González-Delgado, Candelaria Tejada-Tovar, Rodrigo Ortega‐Toro, Ángel Villabona-Ortíz, Sebastián Ortega-Puente
article en
2 citations

Abstract

Numerous studies have been conducted employing various techniques to remove pollutants from water bodies. Among these techniques, adsorption a surface phenomenon that utilises adsorbents derived from agricultural residues has shown considerable potential for the removal of contaminants such as heavy metals. However, most of these investigations have been carried out at the laboratory scale, with limited efforts directed towards predicting the performance of these systems at an industrial level. Accordingly, the present study aims to model a packed bed column at industrial scale for the removal of Pb(II) and Ni(II) ions from aqueous solutions, employing biomass derived from oil palm residues as the adsorbent material. To achieve this, Aspen Adsorption was used as a modelling and simulation tool to evaluate the impact of bed height, inlet flow rate, and initial concentration through a parametric assessment. This evaluation incorporated the Freundlich, Langmuir, and Langmuir–Freundlich isotherm models in conjunction with the Linear Driving Force (LDF) kinetic model. The results indicated that the optimal operating parameters included a column height of 5 m, a flow rate of 250 m3/day, and an initial metal concentration of 5000 mg/L. Moreover, all models demonstrated removal efficiencies of up to 94.6% for both Pb(II) and Ni(II). An increase in bed height resulted in longer breakthrough and saturation times but led to a reduction in adsorption efficiency. Conversely, higher flow rates shortened these times yet enhanced efficiency. These findings underscore the potential of computational modelling tools as predictive instruments for evaluating the performance of adsorption systems at an industrial scale.

ProcessesVol. 13(7)
University of Cartagena (CO)
Openalex Percentile: Top 16%
Adsorption and biosorption for pollutant removal
1.63
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