title: A variance decomposition approach to uncertainty quantification and sensitivity analysis of the Johnson and Ettinger model.
abstract: The Johnson and Ettinger (J&E) model is the most widely used vapor intrusion model in the United States. It is routinely used as part of hazardous waste site assessments to evaluate the potential for vapor intrusion exposure risks. This study incorporates mathematical approaches that allow sensitivity and uncertainty of the J&E model to be evaluated. In addition to performing Monte Carlo simulations to examine the uncertainty in the J&E model output, a powerful global sensitivity analysis technique based on Sobol indices is used to evaluate J&E model sensitivity to variations in the input parameters. The results suggest that the J&E model is most sensitive to the building air exchange rate, regardless of soil type and source depth. Building air exchange rate is not routinely measured during vapor intrusion investigations, but clearly improved estimates and/or measurements of the air exchange rate would lead to improved model predictions. It is also found that the J&E model is more sensitive to effective diffusivity than to effective permeability. Field measurements of effective diffusivity are not commonly collected during vapor intrusion investigations; however, consideration of this parameter warrants additional attention. Finally, the effects of input uncertainties on model predictions for different scenarios (e.g., sandy soil as compared to clayey soil, and "shallow" sources as compared to "deep" sources) are evaluated. Our results not only identify the range of variability to be expected depending on the scenario at hand, but also mark the important cases where special care is needed when estimating the input parameters to which the J&E model is most sensitive.
authors.affiliation: a Department of Civil & Environmental Engineering , University of Massachusetts-Dartmouth , North Dartmouth , MA , USA.
authors.forename: Ali
authors.initials: A
authors.lastname: Moradi
authors.forename: Mazdak
authors.initials: M
authors.lastname: Tootkaboni
authors.forename: Kelly G
authors.initials: KG
authors.lastname: Pennell
mesh_terms: D000393:Air Pollutants / Q000032:analysis*; D016902:Air Pollution, Indoor / Q000032:analysis*; D000704:Analysis of Variance; D004784:Environmental Monitoring / Q000379:methods*; D008962:Models, Theoretical; D009010:Monte Carlo Method; D012680:Sensitivity and Specificity; D012987:Soil / Q000737:chemistry*; D035501:Uncertainty
chemical_list: D000393:Air Pollutants; D012987:Soil