Objective

Millions of acres of land containing elevated levels of explosives and related materials in soil have been identified in the United States with costs for assessment and remediation of these sites estimated to be in the billions of dollars. Effective technologies are needed for predicting the fate and transport of munitions constituents (MC) at explosive-contaminated sites. To successfully model the fate of MCs on ranges, three key factors—dissolution rate, degradation rate, and partitioning to soil—must be understood. Because the major sources of MCs are from low-order (partial) detonation and propellant discharge, the constituents are deposited as mixtures of heterogeneous particles that affect their dissolution properties. Appropriate values of dissolution rates are essential as this is the source term for MCs in the environment. The concentration that reaches a biological receptor or a downgradient site will depend on the degradation rate of the compound and its sorption to the soil matrix. Given that MCs are highly polar compounds, high orders-of-magnitude errors result by trying to quantify sorption properties via the traditional methods applied to organic contaminants. New models supported by new data on dissolution and partitioning are required for more accurate prediction of MC fate and transport for scientifically sound risk assessments.

The overall objective of this project is to develop models supported by appropriate data that can predict (1) the dissolution and release rate of NG and 2,4-DNT from NC matrix propellant residue and (2) the partitioning of military grade RDX, HMX, TNT, NG, DNT, NQ, and mixtures of these MCs to soils of varying physical/chemical characteristics. This will require developing and using a chemical probe for determining the magnitude clay mineral binding sites and ascertaining whether irreversible binding occurs; modeling the results using polyparameter partitioning models and models for irreversible bonding; and initiating validation of the results using soils typical of those found at operational ranges. Researchers will initially validate the models developed in this project by comparing model results to those determined in soil column studies.