A reactive transport benchmark on modeling biogenic uraninite re-oxidation by Fe(III)-(hydr)oxides


Sengoer S. S., Mayer K. U., Greskowiak J., Wanner C., Su D., Prommer H.

COMPUTATIONAL GEOSCIENCES, cilt.19, sa.3, ss.569-583, 2015 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 19 Sayı: 3
  • Basım Tarihi: 2015
  • Doi Numarası: 10.1007/s10596-015-9480-0
  • Dergi Adı: COMPUTATIONAL GEOSCIENCES
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.569-583
  • Anahtar Kelimeler: Reactive transport benchmark, Uranium, Bioremediation, Reoxidation, Numerical dispersion, URANIUM, GROUNDWATER, REDUCTION
  • Orta Doğu Teknik Üniversitesi Adresli: Hayır

Özet

A reactive transport benchmark on uranium (U) bioreduction and concomitant reoxidation has been developed based on the multicomponent biogeochemical reaction network presented by Spycher et al. (Geochim Cosmochim Acta 75:4426-4440, 2011). The benchmark problem consists of a model inter-comparison starting with the numerical simulations of the original batch experiments of Sani et al. (Geochim Cosmochim Acta 68:2639-2648, 2004). The batch model is then extended to 1D and 2D reactive transport models, designed to evaluate the model results for the key biogeochemical reaction processes and their coupling with physical transport. Simulations are performed with four different reactive transport simulators: PHREEQC, PHT3D, MIN3P, and TOUGHREACT. All of the simulators are able to capture the complex biogeochemical reaction kinetics and the coupling between transport and kinetic reaction network successfully in the same manner. For the dispersion-free variant of the problem, a 1D-reference solution was obtained by PHREEQC, which is not affected by numerical dispersion. PHT3D using the sequential non-iterative approach (SNIA) with an explicit TVD scheme and MIN3P using the global implicit method (GIM) with an implicit van Leer flux limiter provided the closest approximation to the PHREEQC results. Since the spatial weighting schemes for the advection term and numerical dispersion played an important role for the accuracy of the results, the simulators were further compared using different solution schemes. When all codes used the same spatial weighting scheme with finite-difference approximation, the simulation results agreed very well among all four codes. The model intercomparison for the 2D-case demonstrated a high level of sensitivity to the mixing of different waters at the dispersive front. Therefore this benchmark problem is well-suited to assess code performance for mixing-controlled reactive transport models in conjunction with complex reaction kinetics.