Predicting Colloid Deposition Parameters at the Column Scale

Abstract:

The transport behavior of pathogenic microorganisms and nanoparticles in the subsurface is usually studied by performing laboratory soil column experiments. The parameters describing colloid deposition to the soil surface are in turn estimated by fitting the observed breakthrough curves with an appropriate 1D model. However, predictive tools to estimate colloid deposition parameters knowing the system properties such as soil type, colloid type, solution chemistry and flow velocity would be useful in estimating the travel distances of pathogenic microorganisms in the subsurface. Such predictive models are rare except the colloid attachment rate coefficient under favorable conditions predicted by colloid filtration theory. A couple of theoretical and empirical predictive models are available for estimating the deposition parameters under unfavorable conditions, but are developed for a small set of data and their applicability for a wide range of conditions is unexplored. In this study we analyze several sets of column experimental data from the literature covering a wide range of experimental conditions to understand the key factors controlling colloid deposition. An empirical relationship for the attachment and detachment rate coefficients and the parameters controlling the deposition has been developed and is validated.