Multicomponent Adsorption of Paracetamol and Metronidazole by Batch and Fixed-Bed Column Processes: Application of Monte Carlo Bayesian Modeling

This study addresses the growing concern of water contamination by pharmaceutical residues, focusing on the simultaneous removal of paracetamol (PAR) and metronidazole (MTZ). Batch and fixed-bed column adsorption processes were evaluated using activated carbon. In the batch experiments, the effects...

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Main Authors: Letícia Reggiane de Carvalho Costa, Júlia Toffoli de Oliveira, Fayola Silva Silveira, Liliana Amaral Féris
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Applied Sciences
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Online Access:https://www.mdpi.com/2076-3417/15/13/7316
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author Letícia Reggiane de Carvalho Costa
Júlia Toffoli de Oliveira
Fayola Silva Silveira
Liliana Amaral Féris
author_facet Letícia Reggiane de Carvalho Costa
Júlia Toffoli de Oliveira
Fayola Silva Silveira
Liliana Amaral Féris
author_sort Letícia Reggiane de Carvalho Costa
collection DOAJ
description This study addresses the growing concern of water contamination by pharmaceutical residues, focusing on the simultaneous removal of paracetamol (PAR) and metronidazole (MTZ). Batch and fixed-bed column adsorption processes were evaluated using activated carbon. In the batch experiments, the effects of pH (3, 7, and 11), adsorbent mass (0.5, 1.25, and 2 g), and contact time (10, 30, and 60 min) were evaluated, while the fixed-bed column was optimized considering initial pollutants concentration (30, 40, and 50 mg/L), adsorbent mass (0.5, 0.75, and 1 g), and flow rate (5, 10, and 15 mL/min) to improve the maximum adsorption capacity of the bed for both pollutants (q<sub>maxPAR</sub> and q<sub>maxMTZ</sub>). Parameter estimation and model selection were performed using a Bayesian Monte Carlo approach. Optimal conditions in the batch system (pH = 7, W = 2 g, and time = 60 min) led to high removal efficiencies for both compounds (≥98%), while in the column system, the initial pollutant concentration was the most significant parameter to improve the maximum adsorption capacity of the bed, resulting in values equal to 49.5 and 43.6 mg/g for PAR and MTZ, respectively. The multicomponent Gompertz model showed the best performance for representing the breakthrough curves and is suitable for scale-up (R<sup>2</sup> ≥ 0.75). These findings highlight the complexity of multicomponent adsorption and provide insights, contributing to the development of more efficient and sustainable water treatment technologies for pharmaceutical residues.
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spelling doaj-art-fabdb4efb0994498948a737a785b03b52025-08-20T02:35:59ZengMDPI AGApplied Sciences2076-34172025-06-011513731610.3390/app15137316Multicomponent Adsorption of Paracetamol and Metronidazole by Batch and Fixed-Bed Column Processes: Application of Monte Carlo Bayesian ModelingLetícia Reggiane de Carvalho Costa0Júlia Toffoli de Oliveira1Fayola Silva Silveira2Liliana Amaral Féris3Department of Chemical Engineering, Federal University of Rio Grande do Sul, Ramiro Barcelos Street, 2777, Porto Alegre 90035-007, RS, BrazilDepartment of Chemical Engineering, Federal University of Rio Grande do Sul, Ramiro Barcelos Street, 2777, Porto Alegre 90035-007, RS, BrazilDepartment of Chemical Engineering, Federal University of Rio Grande do Sul, Ramiro Barcelos Street, 2777, Porto Alegre 90035-007, RS, BrazilDepartment of Chemical Engineering, Federal University of Rio Grande do Sul, Ramiro Barcelos Street, 2777, Porto Alegre 90035-007, RS, BrazilThis study addresses the growing concern of water contamination by pharmaceutical residues, focusing on the simultaneous removal of paracetamol (PAR) and metronidazole (MTZ). Batch and fixed-bed column adsorption processes were evaluated using activated carbon. In the batch experiments, the effects of pH (3, 7, and 11), adsorbent mass (0.5, 1.25, and 2 g), and contact time (10, 30, and 60 min) were evaluated, while the fixed-bed column was optimized considering initial pollutants concentration (30, 40, and 50 mg/L), adsorbent mass (0.5, 0.75, and 1 g), and flow rate (5, 10, and 15 mL/min) to improve the maximum adsorption capacity of the bed for both pollutants (q<sub>maxPAR</sub> and q<sub>maxMTZ</sub>). Parameter estimation and model selection were performed using a Bayesian Monte Carlo approach. Optimal conditions in the batch system (pH = 7, W = 2 g, and time = 60 min) led to high removal efficiencies for both compounds (≥98%), while in the column system, the initial pollutant concentration was the most significant parameter to improve the maximum adsorption capacity of the bed, resulting in values equal to 49.5 and 43.6 mg/g for PAR and MTZ, respectively. The multicomponent Gompertz model showed the best performance for representing the breakthrough curves and is suitable for scale-up (R<sup>2</sup> ≥ 0.75). These findings highlight the complexity of multicomponent adsorption and provide insights, contributing to the development of more efficient and sustainable water treatment technologies for pharmaceutical residues.https://www.mdpi.com/2076-3417/15/13/7316water contaminationpharmaceutical residuesadsorptionbatch processfixed-bed columnBayesian technique
spellingShingle Letícia Reggiane de Carvalho Costa
Júlia Toffoli de Oliveira
Fayola Silva Silveira
Liliana Amaral Féris
Multicomponent Adsorption of Paracetamol and Metronidazole by Batch and Fixed-Bed Column Processes: Application of Monte Carlo Bayesian Modeling
Applied Sciences
water contamination
pharmaceutical residues
adsorption
batch process
fixed-bed column
Bayesian technique
title Multicomponent Adsorption of Paracetamol and Metronidazole by Batch and Fixed-Bed Column Processes: Application of Monte Carlo Bayesian Modeling
title_full Multicomponent Adsorption of Paracetamol and Metronidazole by Batch and Fixed-Bed Column Processes: Application of Monte Carlo Bayesian Modeling
title_fullStr Multicomponent Adsorption of Paracetamol and Metronidazole by Batch and Fixed-Bed Column Processes: Application of Monte Carlo Bayesian Modeling
title_full_unstemmed Multicomponent Adsorption of Paracetamol and Metronidazole by Batch and Fixed-Bed Column Processes: Application of Monte Carlo Bayesian Modeling
title_short Multicomponent Adsorption of Paracetamol and Metronidazole by Batch and Fixed-Bed Column Processes: Application of Monte Carlo Bayesian Modeling
title_sort multicomponent adsorption of paracetamol and metronidazole by batch and fixed bed column processes application of monte carlo bayesian modeling
topic water contamination
pharmaceutical residues
adsorption
batch process
fixed-bed column
Bayesian technique
url https://www.mdpi.com/2076-3417/15/13/7316
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