Sensitivity analyses for modeling evolving reactivity of granular iron for the treatment of trichloroethylene

To better predict long-term performance of a remediation system, parameters of a numerical model should be constrained with care by calibrating with reliable experimental data. This study conducted sensitivity analyses for model parameters, which were shown to represent reasonably well the observed geochemical behaviors for the column experiments that evaluated evolving reactivity of granular iron for the treatment of trichloroethylene (TCE) resulting from precipitation of secondary minerals. The particular model parameters tested include iron corrosion rate, aragonite and Fe2(OH)2CO3 precipitation rates, and proportionality constants for each mineral. For sensitivity analyses, a specific parameter was systematically changed, while other parameters were fixed at the values for the base case. The ranges of parameters tested were determined based on the previous modeling study. The results showed that the most important and sensitive model parameters were secondary mineral precipitation rates. Also, not only absolute precipitation rate for each mineral but also relative precipitation rates among different minerals were important for system performance. With help of sensitivity analysis, the numerical model can be used as a predictive tool for designing an iron permeable reactive barrier (PRB) and can provide implications for the long-term changes in reactivity and permeability of the system.