Evaluating the impact of back diffusion on groundwater cleanup time

Back diffusion of groundwater contaminants from low permeability (K) zones can be a major factor controlling the time to reach cleanup goals in downgradient monitor wells. We identify the aquifer and contaminant characteristics that have the greatest influence on the time (TOoM) after complete source removal for contaminant concentrations to decline by 1, 2 and 3 Orders-of-Magnitude (T1, T2 and T3). Two aquifer configurations are evaluated: (a) layered geometry (LG) with finite thickness low K layers; and (b) boundary geometry (BG) with thick semi-infinite low K boundaries. A semi-analytical modeling approach (Muskus and Falta, 2018) is used to simulate the concentration decline following source removal for a range of conditions and generate ≈21,000 independent values of T1, T2 and T3. Linear regression is applied to interpret this large dataset and develop simple relationships to estimate TOoM from three characteristic parameters – the mass residence time (TM), diffusion time (TD), and ratio of low K to high K mass storage (γ). TM is most important predictor of T1, T2 and T3 for both geometries and is equal to the combined high and low K contaminant mass divided by the mass flux, at the end of the loading period (TL). For LG, T3 is strongly influenced by TD = RLLD2/(4D*), where RL is the low K retardation factor, LD is the half-thickness of the embedded low K layers, and D* is the effective diffusion coefficient. For BG, T3 is strongly influenced by γ. Contaminant decay in low K zones can significantly reduce cleanup times when λLTD > 0.01, where λL is the effective first order decay rate in the low K zone. The 1st Damköhler (Da), equal to TM/TD, provides a useful indicator of the relative importance of back diffusion on TOoM. Back diffusion impacts are greatest on T3 when 0.01 > Da > 0.1, then decrease with increasing Da. Back diffusion has less impacts on T2, with limited influence on T1. The results are summarized in a simple conceptual model to aid in evaluating the impact of back diffusion on the time for concentrations to decline by 1–3 OoM. [Display omitted] •Groundwater cleanup time controlled by characteristic time scales and mass ratio.•Regressions to estimate time to 90, 99, and 99.9% concentration reductions.•90% reduction controlled by advection, 99.9% reduction controlled by diffusion.•Back diffusion impacts are greater for boundary geometry, than for layered geometry.•Simple conceptual model to understand back diffusion impacts.