Statistical optimization of glyphosate adsorption by biochar and activated carbon with response surface methodology
The introduction of glyphosate, found in herbicides, to waterbodies is of concern due to its toxicity and hence potential threat to public health and ecological systems. The present study has compared glyphosate removal from aqueous solution with activated carbon and biochar. Box-Behnken design, and...
Saved in:
Main Authors: | , , |
---|---|
Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2021
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/152718 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-152718 |
---|---|
record_format |
dspace |
spelling |
sg-ntu-dr.10356-1527182021-09-24T04:59:24Z Statistical optimization of glyphosate adsorption by biochar and activated carbon with response surface methodology Herath, Gayana Anjali Dissanayake Poh, Leong Soon Ng, Wun Jern Interdisciplinary Graduate School (IGS) School of Civil and Environmental Engineering Nanyang Environment and Water Research Institute Environmental Bio-innovations Group Engineering::Environmental engineering Glyphosate Box-behnken Method The introduction of glyphosate, found in herbicides, to waterbodies is of concern due to its toxicity and hence potential threat to public health and ecological systems. The present study has compared glyphosate removal from aqueous solution with activated carbon and biochar. Box-Behnken design, and percent contribution with Pareto analysis techniques were used in surface response and efficiency calculations modelled the process conditions and their effects. The adsorption data better fitted the Freundlich isotherm model than the Langmuir model. The rate of glyphosate adsorption was found to follow a pseudo-second-order model. pH of the solutions was regulated by buffering during the adsorption process. Higher efficacy of glyphosate removal was obtained by optimising parameters such as operating pH, initial glyphosate concentration, temperature, adsorbent dose, and contact time. The conditions yielding the best removals were pH 8.0, 0.2 mg/L, 50.0 °C, 11.4 g/L, 1.7 h for activated carbon and pH 5.0, 0.7 mg/L, 50.0 °C, 12.3 g/L, 1.9 h for biochar, for the aforementioned parameters respectively. The maximum removal capacity and efficiency were 0.0173 mg/g and 98.45% for activated carbon, and 0.0569 mg/g and 100.00% for biochar. The test results indicated biochar could be important from the perspective of performance and affordability. 2021-09-20T02:09:42Z 2021-09-20T02:09:42Z 2019 Journal Article Herath, G. A. D., Poh, L. S. & Ng, W. J. (2019). Statistical optimization of glyphosate adsorption by biochar and activated carbon with response surface methodology. Chemosphere, 227, 533-540. https://dx.doi.org/10.1016/j.chemosphere.2019.04.078 0045-6535 https://hdl.handle.net/10356/152718 10.1016/j.chemosphere.2019.04.078 31004820 2-s2.0-85064455357 227 533 540 en Chemosphere © 2019 Elsevier Ltd. All rights reserved. |
institution |
Nanyang Technological University |
building |
NTU Library |
continent |
Asia |
country |
Singapore Singapore |
content_provider |
NTU Library |
collection |
DR-NTU |
language |
English |
topic |
Engineering::Environmental engineering Glyphosate Box-behnken Method |
spellingShingle |
Engineering::Environmental engineering Glyphosate Box-behnken Method Herath, Gayana Anjali Dissanayake Poh, Leong Soon Ng, Wun Jern Statistical optimization of glyphosate adsorption by biochar and activated carbon with response surface methodology |
description |
The introduction of glyphosate, found in herbicides, to waterbodies is of concern due to its toxicity and hence potential threat to public health and ecological systems. The present study has compared glyphosate removal from aqueous solution with activated carbon and biochar. Box-Behnken design, and percent contribution with Pareto analysis techniques were used in surface response and efficiency calculations modelled the process conditions and their effects. The adsorption data better fitted the Freundlich isotherm model than the Langmuir model. The rate of glyphosate adsorption was found to follow a pseudo-second-order model. pH of the solutions was regulated by buffering during the adsorption process. Higher efficacy of glyphosate removal was obtained by optimising parameters such as operating pH, initial glyphosate concentration, temperature, adsorbent dose, and contact time. The conditions yielding the best removals were pH 8.0, 0.2 mg/L, 50.0 °C, 11.4 g/L, 1.7 h for activated carbon and pH 5.0, 0.7 mg/L, 50.0 °C, 12.3 g/L, 1.9 h for biochar, for the aforementioned parameters respectively. The maximum removal capacity and efficiency were 0.0173 mg/g and 98.45% for activated carbon, and 0.0569 mg/g and 100.00% for biochar. The test results indicated biochar could be important from the perspective of performance and affordability. |
author2 |
Interdisciplinary Graduate School (IGS) |
author_facet |
Interdisciplinary Graduate School (IGS) Herath, Gayana Anjali Dissanayake Poh, Leong Soon Ng, Wun Jern |
format |
Article |
author |
Herath, Gayana Anjali Dissanayake Poh, Leong Soon Ng, Wun Jern |
author_sort |
Herath, Gayana Anjali Dissanayake |
title |
Statistical optimization of glyphosate adsorption by biochar and activated carbon with response surface methodology |
title_short |
Statistical optimization of glyphosate adsorption by biochar and activated carbon with response surface methodology |
title_full |
Statistical optimization of glyphosate adsorption by biochar and activated carbon with response surface methodology |
title_fullStr |
Statistical optimization of glyphosate adsorption by biochar and activated carbon with response surface methodology |
title_full_unstemmed |
Statistical optimization of glyphosate adsorption by biochar and activated carbon with response surface methodology |
title_sort |
statistical optimization of glyphosate adsorption by biochar and activated carbon with response surface methodology |
publishDate |
2021 |
url |
https://hdl.handle.net/10356/152718 |
_version_ |
1712300648364507136 |