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Colloid-Associated Groundwater Contaminant Transport in Homogeneous Saturated Porous Media: Mathematical and Numerical Modeling

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Abstract

During the past two decades, significant efforts have been made to study contaminant transport in the presence of colloids. Several researchers reported that colloidal particles could enhance the migration of contaminants in groundwater by reducing retardation factor. When the colloidal particles are present in the aquifer, the subsurface system can be considered as a three-phase system with two solid phases and an aqueous phase. The interaction between contaminants, colloids, and solid matrix should be considered in assessing the fate and transport of the contaminant in the groundwater flow system. In this study, a one-dimensional numerical model is developed by employing a fully implicit finite difference method. This model is based on mass balance equations and mass partition mechanisms between the carriers and solid matrix, as well as between the carriers and contaminants in a saturated homogeneous porous medium. This phenomenon is presented by two approaches: equilibrium approach and fully kinetic first-order approach. The formulation of the model can be simplified by employing equilibrium partitioning of particles. However, contaminant transport can be predicted more accurately in realistic situations by kinetic modeling. To test the sensitivity of the model, the effect of the various chemical and physical coefficients on the migration of contaminant was investigated. The results of numerical modeling matched favorably with experimental data reported in the literature.

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  1. Graduate Faculty of Environment, University of Tehran, Tehran, Iran

    Mohsen Kheirabadi, Mohammad Hossein Niksokhan & Babak Omidvar

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  1. Mohsen Kheirabadi
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  2. Mohammad Hossein Niksokhan
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  3. Babak Omidvar
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Correspondence to Mohsen Kheirabadi.

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Kheirabadi, M., Niksokhan, M.H. & Omidvar, B. Colloid-Associated Groundwater Contaminant Transport in Homogeneous Saturated Porous Media: Mathematical and Numerical Modeling. Environ Model Assess 22, 79–90 (2017). https://doi.org/10.1007/s10666-016-9518-2

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  • DOI: https://doi.org/10.1007/s10666-016-9518-2

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