Integrating Thermal Analysis and Reaction Modeling for Rational Design of Pyrolytic Processes to Remediate Soils Contaminated with Heavy Crude Oil.

We developed a novel methodology that combines thermo-analytical measurements and mathematical methods to inform the reliable pyrolytic treatment of specific soil/contaminant systems. Our approach improves upon current "black-box" design methods that may overestimate the required treatment intensity and hinder cost efficacy. We used thermogravimetry and evolved gas analysis to characterize the complex network of soil mineral transformations, contaminant desorption, and pyrolytic reactions occurring when contaminated soils are heated in an anoxic atmosphere. The kinetics of these reactions were quantified using a distributed activation energy (DAE) approach with six pseudocomponents and used in a mathematical model for continuous-flow reactors to predict the removal of hydrocarbon contaminants without other fitting parameters. This model was tested with pilot-scale data from pyrolytic treatment of soils contaminated with crude oil and found to be a good predictor of the total petroleum hydrocarbon (TPH) removal for temperatures between 370 and 470 °C and residence times from 15 to 60 min. The light hydrocarbon fraction desorbed quickly, and over 99.7% removal was achieved at 420 °C and 15 min residence time. However, 95% removal of the heavy hydrocarbon fraction, which is a good proxy for polyaromatic hydrocarbons (PAHs), required 470 °C with 15 min residence time. This model can be employed to select operating conditions (e.g., reactor size, treatment time, and temperature) to reliably achieve remediation objectives for specific hydrocarbon/soil mixtures without inflating energy requirements, which would lower operating costs and decrease the process carbon footprint on a system-specific basis.