Risk-Based Characterization for Vapour Intrusion at a Conceptual Brownfields Site: Part 1. Data Worth and Prediction Uncertainty

Xiaomin Wang; Andre J.A. Unger; Beth L. Parker
The focus of this paper is to present a methodology to assimilate soil core permeability and trichloroethylene (TCE) soil gas concentration data, and then to assess their worth in reducing prediction uncertainty with a numerical model. The specific problem involves a residential development impacted by indoor air exposure of TCE contamination originating from a groundwater plume. Three metrics are used to quantify the prediction uncertainty, namely: the ability to accurately predict the indoor air concentration within the houses at any point in time; the ability to reduce the standard deviation of predicted indoor air concentration within these houses; and, the ability to accurately forecast the probability of indoor air concentrations exceeding a regulatory limit. The data assimilation methodology involves generating multiple realizations of heterogeneous permeability fields conditioned upon a geostatistical analysis of the borehole data, combined with a discrete static Kalman filter to assimilate actual soil gas concentration data, to estimate soil gas and indoor air concentrations at those locations where the developer does not have any data but liability. The worth of using progressively more permeability and soil gas concentration data is quantified on the basis that it provides a statistically significant improvement in the three metrics used to measure prediction uncertainty.
Brownfields; Vapour Intrusion; Prediction Uncertainty; Data Worth; Kalman Filter; Probability of Exceedance
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