A stochastic model of NAPL composition dynamics and relative risk reduction due to solvent extraction
Many non-aqueous phase liquids (NAPLs) of environmental concern are complex hydrocarbon mixtures of similar compounds with no single predominant species. Coal tar, a complex mixture of polycyclic aromatic hydrocarbons (PAHs), is a common subsurface contaminant at sites of former manufactured gas plants. The use of solvent extraction to enhance coal tar solubility is a remediation option that could be applied either in an in situ injection/recovery system or in an above-ground treatment operation. To describe and predict the efficacy of such a process requires an understanding of the effect of solvents on both the total NAPL dissolution behavior as well as the change in the NAPL composition. This paper presents a stochastic model in which the coal tar is represented as a continuous mixture, and statistical frequency functions are used to represent the distribution of equilibrium partition coefficients. Using mass balance and stochastic equilibrium relations, the model predicts not only the overall coal tar removal efficiency, but also a frequency distribution characterizing the composition of the residual coal tar, thus serving as a statistical representation of the solubility of the residual. This provides a convenient means of describing chemical heterogeneity of multicomponent NAPLs such as coal tar, as well as the effect of solvent extraction on this chemical heterogeneity. Data requirements for model parameterization are shown to be minimal. It is demonstrated that information about the coal tar composition and its dynamics is particularly important for risk assessment since NAPL phase composition drives aqueous phase concentrations, which ultimately determine exposure.
- OSTI ID:
- 416898
- Report Number(s):
- CONF-951023--
- Country of Publication:
- United States
- Language:
- English
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