Elimination of the Reaction Rate "Scale Effect": Application of the Lagrangian Reactive Particle‐Tracking Method to Simulate Mixing‐Limited, Field‐Scale Biodegradation at the Schoolcraft (MI, USA) Site. Issue 12 (13th December 2017)

• Record Type: Journal Article
• Authors: Ding, Dong; Benson, David A.; Fernàndez‐Garcia, Daniel; Henri, Christopher V.; Hyndman, David W.; Phanikumar, Mantha S.; Bolster, Diogo
• Is Part Of: Water resources research. Volume 53:Issue 12(2017)
• Page Start: 10411
• Page End: 10432
• Publication Date: 2017-12-13
• Subjects: reactive transport -- bioremediation -- particle tracking -- scale effect; Hydrology -- Periodicals; 333.91
• DOI: 10.1002/2017WR021103
• Languages: English
• ISSNs: 0043-1397

Abstract

Abstract: Measured (or empirically fitted) reaction rates at groundwater remediation sites are typically much lower than those found in the same material at the batch or laboratory scale. The reduced rates are commonly attributed to poorer mixing at the larger scales. A variety of methods have been proposed to account for this scaling effect in reactive transport. In this study, we use the Lagrangian particle‐tracking and reaction (PTR) method to simulate a field bioremediation experiment at the Schoolcraft, MI site. A denitrifying bacterium, Pseudomonas Stutzeri strain KC (KC), was injected to the aquifer, along with sufficient substrate, to degrade the contaminant, carbon tetrachloride (CT), under anaerobic conditions. The PTR method simulates chemical reactions through probabilistic rules of particle collisions, interactions, and transformations to address the scale effect (lower apparent reaction rates for each level of upscaling, from batch to column to field scale). In contrast to a prior Eulerian reaction model, the PTR method is able to match the field‐scale experiment using the rate coefficients obtained from batch experiments. Key Points: Elimination of the reaction scale effect Purely Lagrangian method separates mixing and reactions Lab‐scale reaction rates can be used in a predictive model