Resumen de Risk managment of complex aquifers contaminated by chemical mixtures: numerical tools and human health risk assessment
Christopher Henri
Human impact on groundwater resources has led to a rapid growth of social concerns worldwide owing to an increasing presence of toxic chemicals released in the subsurface. Risk assessment provides the scientific tool needed to quantify the actual thread that these potential hazards pose to human health. Specifically, risk analysis enables decision makers to answer: What can happen? How likely is it to happen? What can be the consequences? Risk assessment is in this context essential. However, modeling efforts involve in risk analysis are still facing several problems. Among them, in some cases, degradation products can constitute new noxious chemical compounds not necessarily less toxic than their parent product. Thus, the original pollutants and their daughter products are susceptible to co-exist in the aquifer forming a hazardous chemical mixture composed of products of different toxicity. This renders the quantification and interpretation of human health risk a non-trivial and challenging task. Also, the lack of information in the hydraulic and biochemical properties renders transport predictions to be highly uncertain. Stochastic human health risk assessment incorporates hydrogeological uncertainty in human health predictions. This way, probabilistic risk models can be used to determine the likelihood of risk exceeding a given regulatory threshold value or the expected threat to the exposed population and its uncertainty. Unfortunately, these approaches are very computationally demanding. Moreover, the diverse mineralogical composition of a real soil and the complex spatial variability of aquifer properties can produce a mixture of rates of mass transfer between regions of mobile and immobile contaminants. Finally, risk predictions are typically challenged by the complexity of the source zone condition. Existing reactive transport models based on Eulerian methods still undergo computational burden and numerical problems when modeling strong hydro-biochemical heterogeneities with complex reactions in multi-porosity systems. In this context, Particle Tracking Methods constitute a feasible alternative but these methods are limited in the range of applicability. The work presented in this thesis proposes an efficient particle tracking solution capable to simulate serial-parallel degradation reactions in multiple porosity systems with rate-limited mass transfer and strong heterogeneities. The method is then used to characterize the human health risk posed by chemical mixtures in highly heterogeneous porous media under complex source zone conditions. In particular, we investigate the interaction between aquifer heterogeneity, connectivity, contaminant injection mode and chemical toxicity in the probabilistic characterization of health risk. We illustrate how chemical-specific travel times control the regime of the expected risk and its corresponding uncertainties. Results indicate conditions where preferential flow paths can favor the reduction of the overall risk of the chemical mixture. The overall human risk response to aquifer connectivity is shown to be non-trivial for multi-species transport. This non-triviality is a result of the interaction between aquifer heterogeneity and chemical toxicity. To quantify the joint effect of connectivity and toxicity in health risk, we propose a toxicity-based Damköhler number. Results also show that the degradation capacity of immobile water regions and the mass depletion model can play a significant role on the spatiotemporal behavior of the contaminant mixture. Our work furthermore highlights the potential impact of the water flux passing through the source zone on the effective increased lifetime cancer risk due to a reactive chemical mixture. Counter-intuitively, the source zone efficiency is shown to have a beneficial effect on the risk. The total risk tends indeed to decrease for high source zone efficiency due to the consequential decrease in travel times near the source zone.
