In situ long-term modeling of phenanthrene dynamics in an aged contaminated soil using the VSOIL platform.

Management and remediation actions of polycyclic aromatic hydrocarbons (PAH) contaminated sites require an accurate knowledge of the dynamics of these chemicals in situ under real conditions. Here we developed, under the Virtual Soil Platform, a global model for PAH that describes the principal physical and biological processes controlling the dynamics of PAH in soil under real climatic conditions. The model was applied first to simulate the observed dynamics of phenanthrene in situ field experimental plots of industrial contaminated soil. In a second step, different long-term scenarios of climate change or bioavailability increase were applied. Our results show that the model can adequately predict the fate of phenanthrene and can contribute to clarify some of unexplored aspects regarding the behavior of phenanthrene in soil like its degradation mechanism and stabilization. Tested prospective scenarios showed that bioavailability increase (through the addition of solvent or surfactants) resulted in significant increase in substrate transfer rate, hence reducing remediation time. Regarding climate change effect, the model indicated that phenanthrene concentration decreased by 54% during 40years with a natural attenuation and both scenarios chosen for climatic boundaries provided very similar results.

Using a Bayesian approach to improve and calibrate a dynamic model of polycyclic aromatic hydrocarbons degradation in an industrial contaminated soil.

A novel kinetics model that describes the dynamics of polycyclic aromatic hydrocarbons (PAHs) in contaminated soils is presented. The model includes two typical biodegradation pathways: the co-metabolic pathway using pseudo first order kinetics and the specific biodegradation pathway modeled using Monod kinetics. The sorption of PAHs to the solid soil occurs through bi-phasic fist order kinetics, and two types of non-extractible bounded residues are considered: the biogenic and the physically sequestrated into soil matrix. The PAH model was developed in Matlab, parameterized and tested successfully on batch experimental data using a Bayesian approach (DREAM). Preliminary results led to significant model simplifications. They also highlighted that the specific biodegradation pathway was the most efficient at explaining experimental data, as would be expected for an old industrial contaminated soil. Global analysis of sensitivity showed that the amount of PAHs ultimately degraded was mostly governed by physicochemical interactions rather than by biological activity.