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

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.