Sensitivity analysis on parameters and processes affecting vapor intrusion risk

Abstract

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. Environ. Toxicol. Chem. 2012; 31: 1042–1052. © 2012 SETAC

A numerical investigation of vapor intrusion — The dynamic response of contaminant vapors to rainfall events

“…Local equilibrium of PCE in all phases—soil gas, soil water and soil—was assumed. While some studies (Cho et al , 1993) showed the effect of considering mass transfer rate at interfaces, assumption of local equilibrium are found to be common (Grifoll and Cohen, 1996) and sufficient (Picone et al , 2012), and this is shown in the constitutive Equations (11) and (12). Contaminant diffusion in soil gas and soil water was expressed by Millington-Quirk (Millington and Quirk, 1961) Equation (14), while other methods, such as (Kristensen et al , 2010) give similar modeling results (Shen et al , 2012; Shen et al , 2011).…”

“…Tillman and Weaver (2007) studied the influence of temporal soil moisture changes and suggested that soil moisture content measurements taken somewhere other than beneath a building of interest could not be reliably used to calculate the indoor vapor concentration effects. While infiltration was not addressed in most other field and modeling studies, other transient factors, such as groundwater level fluctuations (Picone et al , 2012), and groundwater concentration fluctuation (Folkes et al , 2010) were discussed. Short term fluctuation might have little or no effect, but the definition of “short term” or “long term” might be site specific and will need more research to define (Folkes et al , 2010).…”

Role of the source to building lateral separation distance in petroleum vapor intrusion

“…It is worth noting that the higher attenuation, i.e. the lower lateral screening distance, obtained in the case of groundwater contamination is due to the presence of the capillary fringe that, as known, strongly limits the vapor migration due to the low effective air-phase porosity (Shen et al, 2012;Picone et al, 2012). The lateral exclusion criteria described above can be drastically reduced depending on the source concentration.…”

A variance decomposition approach to uncertainty quantification and sensitivity analysis of the Johnson and Ettinger model

“…Eklund and Simon, 2007; and USEPA, 2010). To explain observed variations, several existing studies have attempted to investigate uncertainties in input parameters to vapor intrusion models, as well as, the sensitivity of these models to changes in the inputs (Johnson, 2005; Hers et al, 2001; Hers et al, 2003; Tillman and Weaver, 2006; Tillman and Weaver, 2007; Yu et al, 2009; Johnston and Gibson, 2011; Picone et al, 2012). The large variations in input parameters for vapor intrusion models, as well as discrepancies between the vapor intrusion model predictions and field measurements, highlights the need for additional research to investigate the uncertainty and sensitivity of vapor intrusion models.…”

“…Picone et al (2012) developed a one-dimensional numerical model in order to identify the critical parameters that generate large variation in model output. Three important parameters including relative distance of the sources to the nearest gas-filled pores in unsaturated zones, biodegradation and water table oscillations in aquifer were identified as major contributing factors in attenuation factor.…”