Radionuclide Sorption Modeling Using the MLNTEQA2 Speciation Code
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RADIONUCLIDE SORPTION MODELING USING THE MINTEQA2 SPECIATION CODE DAVID R. TURNER, T. GRIFFIN, AND T.B. DIETRICH. Center for Nuclear Waste Regulatory Analyses, Southwest Research Institute 6220 Culebra Road, San Antonio, TX 78228-0510 ABSTRACT The MINTEQA2 database has been updated and expanded to include radionuclide data from the most recent release of the EQ3/6 database. Comparison of U(VI)-speciation predicted using the old and new MINTEQA2 databases indicates several significant differences, including the introduction of neutral and anionic species at neutral to alkaline pH. In contrast, comparison of results calculated by EQ3 and MINTEQA2, both using Nuclear Energy Agency (NEA) uranium data, reveals only small differences that are likely due to differences in calculated activity coefficients. With the new database, MINTEQA2 was used to model U(VI)-goethite sorption data from the literature with the Triple-Layer Model (TLM). Values were independently fixed for all but one of the model parameters. The parameter optimization code FITEQL was then used to determine binding constants for mononuclear uranium complexes (UO 2(OH). 2-). The surface complex MOH 2-UO2(OH) 4 produced a very good fit of the sorption data, which was not significantly improved by the use of two or more surface complexes. INTRODUCTION A key measure of performance for a geologic high-level waste (HLW) repository is the degree of attenuation of radionuclide transport provided by sorption on the geologic media along flow paths to the accessible environment. Performance assessment calculations commonly model sorption processes using empirical isotherms such as the Kd approach. However, because these methods do not explicitly consider the chemistry of the system of interest, the adequacy of empirical isotherms has been questioned [1-5]. In contrast, mechanistic approaches to sorption modeling such as surface complexation have been developed to provide flexible, robust models that are able to accommodate changes in system chemistry. These models require a detailed understanding of the chemical system, which in turn requires a thermodynamic database appropriate to the system of interest. The complexity of mechanistic models tends to make them more computationally intensive, limiting their practical application in performance assessment. For this reason, mechanistic models must be evaluated and streamlined where possible. The equilibrium speciation code MINTEQA2 (Version 3.0) [6] includes empirical, electrostatic, and ion exchange sorption models. By comparing different models, appropriate simplifications for incorporating mechanistic approaches into performance assessment codes may be identified. Important radionuclides in HLW include U, Pu, Np, Am, Tc, Cs, Sr, Zr, Th, Ra, and Sn [7]. With thermodynamic data imported from WATEQ3 [8], MINTEQA2 has a broad database for elements common in natural systems. However, of the radionuclides listed above, only strontium and uranium [9] are currently available in the MINTEQA2 database, and recent studies [10]
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