Skip to main content
U.S. Department of Energy
Office of Scientific and Technical Information

Simulation modeling of vegetation effects on [sup 222]Rn transport into basements

Thesis/Dissertation ·
OSTI ID:6121641
The author developed a model of [sup 222]Rn transport through soils and into experimental basements. The model was based on current theories and data from the Radon Project experimental basements at Colorado State University were used to calibrate it to that site. Uncertainty analysis of the model showed that model predictions of indoor [sup 222]Rn concentrations come from a distribution having a CV of no greater than 0.25. Sensitivity analysis of the model indicated that the dry bulk density, the [sup 226]Ra concentration of the soil and the effective permeability of the basement wall are, perhaps, the most important parameters in the model for determining a set of output. The effective diffusion coefficient of the basement wall is also important. The model was perturbed in manners consistent with three expected mechanisms, and their combination, by which vegetation might influence indoor [sup 222]Rn concentration. The presence of vegetation, acting by any mechanism, reduces indoor [sup 222]Rn concentration. Vegetation also influences the pattern in time of indoor [sup 222]Rn. In general, indoor [sup 222]Rn concentrations tend to follow surface soil moisture, with variability added to the trend by the wind speed. This pattern was modified, however, by vegetation action. Based on these results, I developed a set of predictions which can be tested by experiment at the Radon Project experimental basements to determine which of the hypothesized mechanisms of vegetation action is supported.
Research Organization:
Colorado State Univ., Fort Collins, CO (United States)
OSTI ID:
6121641
Country of Publication:
United States
Language:
English