Models and statistical analysis of organic micropollutants in groundwater-based drinking water resources
Abstract
The access to safe drinking water is essential for the well being of the population. The spread of micropollutant contamination jeopardise many freshwater reservoirs, and is a serious threat for human health, especially because of its long-term effects. To asses the threat of contamination, models are required to study the main contamination pathways, and to make predictions of pollution fluxes. Groundwater is used as drinking water in many countries because subsurface processes can mitigate pollution and purify the water by removing xenobiotic compounds. However, groundwater often interacts with surface water, which is more vulnerable to contamination, and can transfer pollution to groundwater. The fate of micropollutants in aquifers is influenced by many factors: sorption, degradation and dilution are processes that can interact together and create very complex systems, which are difficult to model. The identification of dominant processes is an essential step in the understanding of system behaviour, because it enables the development of simplified models that can approximate the fate of contaminants with the best trade-off between model complexity and reliability of results. In this thesis, global sensitivity analysis techniques are used to assess detailed models in order to identify the main processes involved in the degradation of chlorinated solvents in the subsurface, and in the transport of pesticides from surface water into nearby wells in confined aquifers. Statistical techniques are also employed to identify large-scale contamination processes by examining observations of contamination in drinking water wells in Zealand, Denmark. Results show that persistent compounds in surface water can leach into nearby pumping wells even if an impermeable clay layer overlies the well screen. Thus aquitards may not provide adequate protection against contamination by micropollutants in surface water, as generally thought. Results also show that the fermentation of organic compounds and the sulphate concentration in groundwater govern the success of sequential reductive dechlorination in aquifers, and that the simulation of chlorinated aliphatic hydrocarbon degradation cannot be approximated by simple models without losing the ability to simulate important system behaviour. The statistical analysis of contaminant concentrations in Danish drinking water wells demonstrates that drinking water well contamination by BAM, a pesticide metabolite, is mainly a problem in urban areas, and that in Zealand, wells close to surface water are generally more vulnerable to pesticide contamination.
Info
Thesis PhD, 2011
UN SDG Classification
DK Main Research Area
Science/Technology
