The impact of low-temperature seasonal aquifer thermal energy storage (SATES) systems on chlorinated solvent contaminated groundwater: modeling of spreading and degradation.

Groundwater systems are increasingly used for seasonal aquifer thermal energy storage (SATES) for periodic heating and cooling of buildings. Its use is hampered in contaminated aquifers because of the potential environmental risks associated with the spreading of contaminated groundwater, but positive side effects, such as enhanced contaminant remediation, might also occur. A first reactive transport study is presented to assess the effect of SATES on the fate of chlorinated solvents by means of scenario modeling, with emphasis on the effects of transient SATES pumping and applicable kinetic degradation regime. Temperature effects on physical, chemical, and biological reactions were excluded as calculations and initial simulations showed that the small temperature range commonly involved (ΔT<15 °C) only caused minor effects. The results show that a significant decrease of the contaminant mass and (eventually) plume volume occurs when degradation is described as sediment-limited with a constant rate in space and time, provided that dense non-aqueous phase liquid (DNAPL) is absent. However, in the presence of DNAPL dissolution, particularly when the dissolved contaminant reaches SATES wells, a considerably larger contaminant plume is created, depending on the balance between DNAPL dissolution and mass removal by degradation. Under conditions where degradation is contaminant-limited and degradation rates depend on contaminant concentrations in the aquifer, a SATES system does not result in enhanced remediation of a contaminant plume. Although field data are lacking and existing regulatory constraints do not yet permit the application of SATES in contaminated aquifers, reactive transport modeling provides a means of assessing the risks of SATES application in contaminated aquifers. The results from this study are considered to be a first step in identifying the subsurface conditions under which SATES can be applied in a safe or even beneficial manner.

Toluene biodegradation rates in unsaturated soil systems versus liquid batches and their relevance to field conditions.

Contaminant biodegradation in unsaturated soils may reduce the risks of vapor intrusion. However, the reported rates show large variability and are often derived from slurry experiments that are not representative of unsaturated conditions. Here, different laboratory setups are used to derive the biodegradation capacity of an unsaturated soil layer through which gaseous toluene migrates from the water table upwards. Experiments in static unsaturated soil microcosms at 6-30 % water-filled porosity (WFP) and unsaturated soil columns at 9, 14, and 27 % WFP were compared with liquid batches containing the same culture of Alicycliphilus denitrificans. The biodegradation rates for the liquid batches were orders of magnitude lower than for the other setups. Hence, liquid batches do not necessarily reflect optimal conditions for bacteria; either oxygen or toluene mass transfer at the cell scale or the absence of soil-water-air interfaces seemed to be limiting bacterial activity. For the column setup, the rates were limited by mass supply. The microcosm results could be described by apparent first-order biodegradation constants that increased with WFP or through a numerical model that included biodegradation as a first-order process taking place in the liquid phase only. The model liquid phase first-order rates varied between 6.25 and 20 h(-1) and were not related to the water content. Substrate availability was the primary factor limiting bioactivity, with evidence for physiological stress at the lowest water-filled porosity. The presented approach is useful to derive liquid phase biodegradation rates from experimental data and to include biodegradation in vapor intrusion models.

Sensitivity analysis on parameters and processes affecting vapor intrusion risk.

A one-dimensional numerical model was developed and used to identify the key processes controlling vapor intrusion risks by means of a sensitivity analysis. The model simulates the fate of a dissolved volatile organic compound present below the ventilated crawl space of a house. In contrast to the vast majority of previous studies, this model accounts for vertical variation of soil water saturation and includes aerobic biodegradation. The attenuation factor (ratio between concentration in the crawl space and source concentration) and the characteristic time to approach maximum concentrations were calculated and compared for a variety of scenarios. These concepts allow an understanding of controlling mechanisms and aid in the identification of critical parameters to be collected for field situations. The relative distance of the source to the nearest gas-filled pores of the unsaturated zone is the most critical parameter because diffusive contaminant transport is significantly slower in water-filled pores than in gas-filled pores. Therefore, attenuation factors decrease and characteristic times increase with increasing relative distance of the contaminant dissolved source to the nearest gas diffusion front. Aerobic biodegradation may decrease the attenuation factor by up to three orders of magnitude. Moreover, the occurrence of water table oscillations is of importance. Dynamic processes leading to a retreating water table increase the attenuation factor by two orders of magnitude because of the enhanced gas phase diffusion.

Calibration of parameter fields consisting of multiple statistical populations.

If a parameter field to be calibrated consists of more than one statistical population, usually not only the parameter values are uncertain, but the spatial distributions of the populations are uncertain as well. In this study, we demonstrate the potential of the multimodal calibration method we proposed recently for the calibration of such fields, as applied to real-world ground water models with several additional stochastic parameter fields. Our method enables the calibration of the spatial distribution of the statistical populations, as well as their spatially correlated parameterization, while honoring the complete prior geostatistical definition of the multimodal parameter field. We illustrate the implications of the method in terms of the reliability of the posterior model by comparing its performance to that of a "conventional" calibration approach in which the positions of the statistical populations are not allowed to change. Information from synthetic calibration runs is used to show how ignoring the uncertainty involved in the positions of the statistical populations not only denies the modeler the opportunity to use the measurement information to improve these positions but also unduly influences the posterior intrapopulation distributions, causes unjustified adjustments to the cocalibrated parameter fields, and results in poorer observation reproduction. The proposed multimodal calibration allows a more complete treatment of the relevant uncertainties, which prevents the abovementioned adverse effects and renders a more trustworthy posterior model.