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Smart Kd-values, their uncertainties and sensitivities - Applying a new approach for realistic distribution coefficients in geochemical modeling of complex systems

M. Stockmann, J. Schikora

2017engeochemical modelingrisk assessmentdistribution coefficientssorptionsensitivity analysis

Abstract

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One natural retardation process to be considered in risk assessment for contaminants in the environment is sorption on mineral surfaces. A realistic geochemical modeling is of high relevance in many application areas such as groundwater protection, environmental remediation, or disposal of hazardous waste. Most often concepts with constant distribution coefficients (Kd-values) are applied in geochemical modeling with the advantage to be simple and computationally fast, but not reflecting changes in geochemical conditions. In this paper, we describe an innovative and efficient method, where the smart Kd-concept, a mechanistic approach mainly based on surface complexation modeling, is used (and modified for complex geochemical models) to calculate and apply realistic distribution coefficients. Using the geochemical speciation code PHREEQC, multidimensional smart Kd-matrices are computed as a function of varying (or uncertain) environmental conditions. On the one hand, sensitivity and uncertainty statements for the distribution coefficients can be derived. On the other hand, smart Kd-matrices can be used in reactive transport (or migration) codes (not shown here). This strategy has various benefits: (1) rapid computation of Kd-values for large numbers of environmental parameter combinations.

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Cite This Work

@article{b4732a29-c83e-40b0-842f-38e72fde1baa,
  title={Smart Kd-values, their uncertainties and sensitivities - Applying a new approach for realistic distribution coefficients in geochemical modeling of complex systems},
  author={M. Stockmann and J. Schikora},
  year={2017},
  language={en}
}
TY  - JOUR
TI  - Smart Kd-values, their uncertainties and sensitivities - Applying a new approach for realistic distribution coefficients in geochemical modeling of complex systems
AU  - M. Stockmann
AU  - J. Schikora
PY  - 2017
LA  - en
ER  -

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