Technical Papers
Nov 28, 2017

Parameterization Study for Modeling Biosurfactant-Enhanced Aquifer Remediation Processes Based on Flow Cell Experiments

Publication: Journal of Environmental Engineering
Volume 144, Issue 2

Abstract

Applications of biosurfactant in enhanced aquifer remediation processes have been widely studied. In order to clarify the significant parameters and analyze their interactions, and thus be able to describe the processes in an efficient and robust approach, as well as evaluate the performance of biosurfactant, this research performed a parameterization study for modeling biosurfactant-enhanced aquifer remediation (BSEAR) processes based on flow cell experiments. Lab synthetized surfactant solution was deployed together with soil flushing using water to remove the diesel contaminants from the soil sample. By using the developed hybrid stochastic and design of experiment (DOE)–aided parameterization method, it was revealed that the interactions between the distribution coefficient and Henry’s constant were significant in general for modeling the removal of benzene, toluene, ethylbenzene, and xylene (BTEX). In particular, the interaction between the distribution coefficient and the first 12-h loading ratio is significant in modeling the removal of ethylbenzene. It was also found that enhanced mobility and solubility increase of contaminants were achieved after applying the surfactant solution. After parameterization, R2 values showed good consistency, which indicated the effectiveness in modeling BSEAR processes.

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Acknowledgments

This research is supported by Natural Sciences and Engineering Research Council of Canada (NSERC), Canada Foundation for Innovation (CFI), and Research & Development Corporation of Newfoundland and Labrador (RDC NL).

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Go to Journal of Environmental Engineering
Journal of Environmental Engineering
Volume 144Issue 2February 2018

History

Received: Aug 3, 2016
Accepted: Jul 20, 2017
Published online: Nov 28, 2017
Published in print: Feb 1, 2018
Discussion open until: Apr 28, 2018

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Master Student, Northern Region Persistent Organic Pollution Control Laboratory, Faculty of Engineering and Applied Science, Memorial Univ. of Newfoundland, St. John’s, NF, Canada A1B 3X5. E-mail: [email protected]
Bing Chen, Ph.D., M.ASCE [email protected]
Professor and Director of Northern Region Persistent Organic Pollution Control Laboratory, Faculty of Engineering and Applied Science, Memorial Univ. of Newfoundland, St. John’s, NF, Canada A1B 3X5; Adjunct Professor, College of Environmental Science and Engineering, Peking Univ., Beijing 100871, China (corresponding author). E-mail: [email protected]
Hongjing Wu, Ph.D. [email protected]
Postdoctoral Fellow, Northern Region Persistent Organic Pollution Control Laboratory, Faculty of Engineering and Applied Science, Memorial Univ. of Newfoundland, St. John’s, NF, Canada A1B 3X5. E-mail: [email protected]
Master Student, Northern Region Persistent Organic Pollution Control Laboratory, Faculty of Engineering and Applied Science, Memorial Univ. of Newfoundland, St. John’s, NF, Canada A1B 3X5. E-mail: [email protected]
Research Fellow, Northern Region Persistent Organic Pollution Control Laboratory, Faculty of Engineering and Applied Science, Memorial Univ. of Newfoundland, St. John’s, NF, Canada A1B 3X5. E-mail: [email protected]
Kedong Zhang [email protected]
Master Student, Northern Region Persistent Organic Pollution Control Laboratory, Faculty of Engineering and Applied Science, Memorial Univ. of Newfoundland, St. John’s, NF, Canada A1B 3X5. E-mail: [email protected]
Baiyu Zhang, Ph.D., M.ASCE [email protected]
Associate Professor, Northern Region Persistent Organic Pollution Control Laboratory, Faculty of Engineering and Applied Science, Memorial Univ. of Newfoundland, St. John’s, NF, Canada A1B 3X5. E-mail: [email protected]

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