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Adsorption–Desorption Processes in Subsurface Reactive Transport Modeling
- Sabine Goldberg, Louise J. Criscenti, David R. Turner, James A. Davis, Kirk J. Cantrell
- Vadose zone journal 2007 v.6 no.3 pp. 407-435
- soil pollution, vadose zone, aquifers, groundwater contamination, pollutants, adsorption, desorption, metal ions, radionuclides, geochemistry, mathematical models, chemical reactions, soil water movement, groundwater flow, saturated flow, unsaturated flow
- Adsorption–desorption reactions are important processes that affect the transport of contaminants in the environment. Various empirical approaches, such as the distribution coefficient and Freundlich and Langmuir isotherm equations, have been used to represent adsorption. The empirical approaches are not capable of accounting for the effects of variable chemical conditions, such as pH, on adsorption reactions. This can be done using chemical models such as surface complexation models. These models define specific surface species, chemical reactions, equilibrium constants, mass balances, and charge balances, and their molecular features can be given thermodynamic significance. Ion adsorption mechanisms and surface configurations for the surface complexation models can be established from independent experimental observations. These include both indirect measurements, such as point of zero charge shifts, ionic strength effects, and calorimetry, and direct spectroscopic techniques, including vibrational spectroscopy, nuclear magnetic resonance (NMR) spectroscopy, and X-ray absorption spectroscopy. Surface complexation models were developed for single mineral phases but have now been applied to natural mineral assemblages using both component additivity (CA) and generalized composite (GC) approaches. Surface complexation models have been incorporated into subsurface transport models at several field sites, although simplifying assumptions are needed to deal with heterogeneous materials. Surface complexation models for contaminant adsorption have the potential to increase the confidence and scientific credibility of transport modeling by reducing the uncertainty in quantifying retardation and providing a means of quantifying that uncertainty.