Simulation of a packed column for the removal of Pb (II) from solution using Theobroma cacao L. as a bioadsorbent
Water bodies contaminated with heavy metals have generated significant concern worldwide due to their toxicity, persistence, bioaccumulation, and non-biodegradability. Among these pollutants is Pb (II), which enters water sources primarily as a result of anthropogenic activities. Prolonged exposure...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Polish Academy of Sciences
2025-05-01
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| Series: | Archives of Environmental Protection |
| Subjects: | |
| Online Access: | https://journals.pan.pl/Content/135152/PDF/Archives%20vol%2051%20no%202%20pp33_38_1.pdf |
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| Summary: | Water bodies contaminated with heavy metals have generated significant concern worldwide due to their toxicity, persistence, bioaccumulation, and non-biodegradability. Among these pollutants is Pb (II), which enters water sources primarily as a result of anthropogenic activities. Prolonged exposure to this contaminant can cause neurological disorders, as well as respiratory and urinary issues. This research aims to model an industrial-scale packed column using Computer-Aided Process Engineering (CAPE) to remove Pb (II) from an aqueous solution, using Theobroma cacao L. as bioadsorbent. Using Aspen Adsorption, several simulations were bperformed on adsorption columns with varying configurations at an industrial scale, evaluating the parametric sensitivity to bed height, inlet flow rate, and initial concentration. The results showed that the simulated adsorption columns achieved removal efficiencies of up to 99%. The optimal simulation conditions for the column simulation included a bed height of 5 m, an initial concentration of 3000 mg/L, and an inlet flow rate of 50 m3/day. It was observed that increasing the inlet flow rate reduced the breakthrough and saturation times of the process, while increasing the bed height extended these times. These findings demonstrate the potential of computational tools as valuable alternatives for predicting the performance of adsorption columns packed with biomass. |
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| ISSN: | 2083-4772 2083-4810 |