Predicting longevity of iron permeable reactive barriers using multiple iron deactivation models

Abstract In this study we investigate the model uncertainties involved in predicting long-term permeable reactive barrier (PRB) remediation efficiency based on a lab-scale column experiment under accelerated flow conditions. A PRB consisting of 20% iron and 80% sand was simulated in a laboratory-scale column and contaminated groundwater was pumped into the column for approximately 1 year at an average groundwater velocity of 3.7E − 1 m d − 1 . Dissolved contaminants (PCE, TCE, cis-DCE, trans-DCE and VC) and inorganic (Ca 2 + , Fe 2 + , TIC and pH) concentrations were measured in groundwater sampled at different times and at eight different distances along the column. These measurements were used to calibrate a multi-component reactive transport model, which subsequently provided predictions of long-term PRB efficiency under reduced flow conditions (i.e., groundwater velocity of 1.4E − 3 m d − 1 ), representative of a field site of interest in this study. Iron reactive surface reduction due to mineral precipitation and iron dissolution was simulated using four different models. All models were able to reasonably well reproduce the column experiment measurements, whereas the extrapolated long-term efficiency under different flow rates was significantly different between the different models. These results highlight significant model uncertainties associated with extrapolating long-term PRB performance based on lab-scale column experiments. These uncertainties should be accounted for at the PRB design phase, and may be reduced by independent experiments and field observations aimed at a better understanding of reactive surface deactivation mechanisms in iron PRBs.