Modeling the impact of petroleum mixtures released from railroad tank car accidents on groundwater contamination and cleanup times

摘要

This thesis is made up of two separate papers. The first paper evaluates a number of thermodynamic and empirical models estimating mixture properties required to predict the migration and entrapment in the subsurface of nonaqueous phase liquids released due to railroad tank car accidents. The properties include density, viscosity, surface and interfacial tension. Several models are used to predict pure compounds properties, similar mixture properties, and dissimilar mixture properties. Models for estimating density and surface tension are the most accurate with errors for similar compound mixtures close to or fewer than 10% compared to measured values. Viscosity models did the next best, with errors between 15 and 33%. However, simple linear models do not work well for viscosity because of sensitivity to temperature. Interfacial tension proves to be the most difficult property to estimate, in particular for dissimilar mixtures. Interfacial tension is very sensitivity to mutual solubility parameters. This sensitivity causes large error if the parameters are not accurately measured or estimated. In the second paper, the results from the most accurate property estimation equations are used for a database in model simulation program referred to as Hazardous Materials Transportation Environmental Consequence Model, or HMTECM. This model was previously developed to simulate the spill of a pure compound on the ground surface, migration through soil, lens formation at the groundwater surface, transportation through groundwater, and pump and treat. The model has since been redeveloped to handle mixtures. All model coding was done by Hongkyu Yoon, a previous visiting research assistant professor. He developed a new semi-analytical source zone reduction model (SZRM) for multi-component light nonaqueous phase liquids (LNAPLs), and incorporated this into an existing screening model for estimating cleanup times for chemicals spills from railroad tank cars that previously considered only single component LNAPLs. Dr. Yoon compared results with SZRM, a numerical model, and a semi-analytical model. Results from the SZRM compare favorably to those from a three-dimensional numerical model, and from another semi-analytical model that does not consider source zone reduction. A sensitivity analysis is performed with the updated screening model by adjusting several key input parameters (i.e., cleanup criteria such as total petroleum hydrocarbons in soil (TPH-soil), TPH-water, and maximum contaminant levels, dispersivity, and solubility), and to evaluate groundwater contamination and cleanup times for four complex mixtures of concern in the railroad industry. In most cases, raising cleanup criteria concentrations and increasing dispersivity and solubility decrease cleanup time. Also, cleanup time is controlled by multiple cleanup criteria and can be determined by different criteria under different conditions. It is recommended that multiple cleanup criteria be applied depending upon actual conditions. Among the petroleum hydrocarbon mixtures considered, the cleanup time of diesel fuel was much longer than E95, gasoline, and crude oil. This is mainly due to the high fraction of low solubility components in diesel fuel. The results demonstrate that the updated screening model with the newly developed SZRM is computationally efficient, and provides valuable comparisons of cleanup times that can be used in assessing the health and financial risk associated with chemical mixture spills from railroad tank car accidents.