RT3D Reaction Modules for Natural and Enhanced Attenuation of Chloroethanes, Chloroethenes, Chloromethanes, and Daughter Products

Abstract

This document describes a suite of Monitored Natural Attenuation/Enhanced Attenuation (MNA/EA) reaction modules that were developed for addressing complex chlorinated solvent reactions using the RT3D numerical solute transport code. As an introduction, an overview of these MNA/EA reaction modules is presented, including discussions of similarities between reaction modules, the purpose of key reaction parameters, and important considerations for using the reaction modules. Subsequent sections provide the details of the reaction kinetics (conceptual model and equations), data input requirements, and example (batch reactor) results for each reaction module. This document does not discuss reaction module implementation or validation; such information will accompany the software in the form of release notes or a supplement to the RT3D manual.

A Critical Review of the Modelling Tools for the Reactive Transport of Organic Contaminants

“…RT3D is equipped with several pre-programmed reaction modules and one user-defined reaction module. The list of ready-to-use modules includes: aerobic instantaneous degradation of BTEX, kinetically limited degradation of BTEX, a double-monod model, sequential degradation reactions, an aerobic/anaerobic model for the degradation of PCE/TCE, natural and enhanced attenuation of chloroethanes, chloroethenes, chloromethanes, and daughter products [713,714]. Similar to MT3D, RT3D uses a separate model, usually Modflow [715], to determine the velocity and groundwater pressure distribution.…”

Natural and Enhanced Attenuation of Chlorinated Solvents Using RT3D

“…For numerical groundwater modelling, empirical relationships providing an estimate of the overall rate of transformation and dependence of this rate on the concentrations of chemical species related to the transformation reaction are typically used. Contaminant transformation processes under natural attenuation conditions are typically described using a lumped first-order kinetic form (e.g., Equation 15) that has been effective in simulating transformation rates under a variety of conditions [U.S. EPA, 1998;Clement et al, 2000] (but see Johnson and Truex [2006] for discussion on the suitability of first-order expressions). It is also feasible to add dependencies of this rate related to the concentration of reactants or inhibitors.…”

“…For MNA/EA sites, chloroethene reductive dechlorination using substrate/biomass-dependent reaction rates or cometabolic dechlorination can be selected to model the impact of substrates and electron donors on dechlorination. The RT3D reaction modules in Figure 14 are briefly described in Table 5 and are described in detail in Johnson and Truex [2006]. Dechlorination of a mixture of chloroethene, chloroethane, and chloromethane compounds using first-order rate expressions.…”

“…The geochemical indicators can also be allowed to react and change over time if there is sufficient data available to define these rates of reactions. See Johnson and Truex [2006] for details on the reaction module implementing this type of geochemical indicator approach to dechlorination.…”

Influential sources of uncertainty in glyphosate biochemical degradation in soil

“…More importantly, under the perspectives of health protection and pollution control, toxic metabolites contribute to dietary risk assessment [25] as well as surface water quality risk assessment [61]. Recent developments in coupling reaction networks with ecohydrological processes have improved the capability to predict herbicide dynamics in spite of the increased complexity in model structure (e.g., PRZM [17], MACRO [39], SWAT [4], HYDRUS [47], MODFLOW-RT3D [40], TOUGHREACT [87], and BRTSim [54]). These types of simulations need to be endowed with uncertainty and sensitivity analyses to account for errors in data collection, parameter value estimation, and model structure, which usually result in nonlinear model responses and unforeseen outcomes [20,70,76,88].…”