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An approximative method for the transformation of kinetic sorption data from batch-experiments to transport processes in model soil columns

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Book cover Surfactants and Colloids in the Environment

Part of the book series: Progress in Colloid & Polymer Science ((PROGCOLLOID,volume 95))

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Abstract

In connection with the mathematical modeling of the transport of pollutants in soil the selection of data from literature plays an important role. In the case of sorption of pollutants mainly partition coefficients and rate constants from batch-experiments are available. For the transformation of these sorption parameters to the transport of pollutants in soil, however, the dependence of these parameters from the concentration of the adsorbent in the batch-experiment and in soil must be considered.

In the present paper, for the relatively frequent case of a pollutant sorbing only partially reversibly, the transformation of these parameters is described by a model regarding the numerical effect of this transformation on the transport of pollutants in precharged and non-precharged soil. Model assumptions were made in order to extend the equilibrium case to the non-equilibrium case. As an example, sorption of 3-chlorophenol in a model soil column from Na bentonite was chosen. Results show that a considerable influence of adsorbent concentration on the proportion of reversibly and irreversibly adsorbed species and, therefore, also via this effect on the transport velocity in the model soil column is to be expected.

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M. J. Schwuger F. H. Haegel

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© 1994 Dr. Dietrich Steinkopff Verlag GmbH & Co. KG

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Struck, B.D., Sistemich, I., Pelzer, R. (1994). An approximative method for the transformation of kinetic sorption data from batch-experiments to transport processes in model soil columns. In: Schwuger, M.J., Haegel, F.H. (eds) Surfactants and Colloids in the Environment. Progress in Colloid & Polymer Science, vol 95. Steinkopff. https://doi.org/10.1007/BFb0115711

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  • DOI: https://doi.org/10.1007/BFb0115711

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  • Publisher Name: Steinkopff

  • Print ISBN: 978-3-7985-0994-8

  • Online ISBN: 978-3-7985-1668-7

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