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Data · dataset · 2025

Performance of coffee husk biochar in sulfadiazine retention and remediation of soil water contamination: a batch and column study_Article

Listed in Teesside University Research Data Repository

This research aimed to analyse the effect of biochar as a filtering layer in the transfer mechanisms of Sulfadiazine (SDZ), an antibiotic found in urban surface waters.

Description

Laboratory tests of kinetics and sorption isotherms of SDZ with biochar were conducted in batch conditions. Additionally dynamic adsorption analyse was performed on sand column experiments and breakthrough curves were established.

As it is fundamental for understanding the SDZ transport dynamics, simulations of the breakthrough curves were performed using Hydrus-1D, for comparison. The results suggest that the biochar significantly improves the SDZ sorption rates. With a biochar filtering layer into the column, a rapid increase in sorption was observed throughout the first hours, reaching the equilibrium condition within 24 hours, and the experimental data were best fitted through a pseudo-second-order model.

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Additionally, a markable dependency was observed for the loading capacity of the biochar with the experimental condition of the sorption test, as the loading value without batch (41%) was below the obtained in the batch trials (53%). The simulations also showed that the Convection Dispersion Equation and the two site sorption models best fit the observed data, indicating no chemical equilibrium. Furthermore, the adjustments of the kinetics and sorption isotherms suggest that chemisorption in multiple layers was the predominant mechanism in sorption.

Consequently, it is possible to infer that despite the risk SDZ represents to the environment and humans, the coffee husk biochar can be an effective alternative to mitigate its presence, or even more, to remove this contaminant from urban waters.

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Where it is published

Catalogue records · 1

Topics

From keywords
Earth & Environmental Science · Engineering · Humanities · Life Sciences · Mathematics & Statistics · Social Science
Inferred from text
Ecological applications 71%
Provenance · 1 source records, 12 field assertions
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Teesside University Research Data Repositoryoai:data.mendeley.com/8m7mptk249.111 d agoJSON v1
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