Estimation of contaminant subslab concentration in vapor intrusion

Abstract

This study is concerned with developing a method to estimate subslab perimeter crack contaminant concentration for structures built atop a vapor source. A simple alternative to the widely-used but restrictive one-dimensional (1-D) screening models is presented and justified by comparing to predictions from a three-dimensional (3-D) CFD model. A series of simulations were prepared for steady-state transport of a non-biodegradable contaminant in homogenous soil for different structure construction features and site characteristics. The results showed that subslab concentration does not strongly depend on the soil diffusivity, indoor air pressure, or foundation footprint size. It is determined by the geometry of the domain, represented by a characteristic length which is the ratio of foundation depth to source depth. An extension of this analytical approximation was developed for multi-layer soil cases.

Vapor intrusion attenuation factors relative to subslab and source, reconsidered in light of background data

“…Their study indicated that the simulated ${\alpha }_{gw}^{ss}$ in most cases ranged from 0.1~1. This is consistent with Yao et al 's approximation that used the square root of the ratio of foundation to source depth to predict c ss [19]. Both studies, which used a similar physical modeling framework, were thus predicting attenuation factors that were at the far upper end of the actually measured values.…”

“…The general soil gas contaminant concentration profile is then determined mainly by diffusive transport through the soil. Thus, throughout most of the soil domain surrounding the structure of interest, the convection term is negligible [19], and $$0=\nabla \cdot true(D_i\nabla c_{ig}true)-R_i$$ There are two major classes of contaminants of concern for VI in U.S. - the chlorinated solvents, including tetrachloroethylene (PCE) and trichloroethylene (TCE), and the other includes petroleum hydrocarbons. In China, the major contaminants includes pesticide [20-23].…”

Estimation of contaminant subslab concentration in petroleum vapor intrusion

“…Though the subslab concentration is indirectly related to human exposure, it still plays an important role in determining indoor air contaminant concentration. In previous studies, a series of analytical approximation methods (AAMs) were developed, which can provide estimates of contaminant subslab concentration in VI scenarios involving no biodegradation [12,13]. This approach assumed that the influence of a building foundation on contaminant subslab concentration could be approximated as involving mainly the “blocking” or “capping” effect of the building foundation on diffusional transport of contaminant to the atmosphere.…”

Evaluation of site-specific lateral inclusion zone for vapor intrusion based on an analytical approach

“…In 2012, Yao et al proposed a simple equation to estimate non-degradable contaminant subslab concentration for cases with homogenous source distribution and soil geology [31]: $$\frac{C_{ss}}{C_s}\approx \sqrt{\frac{d_f}{d_s}}$$ where C s is the source vapor concentration [M/L 3 ]; d f and d s are the foundation depth and source depth below ground surface [L], respectively. For scenarios involving multilayer soil geology, equation (1) was modified as $$\frac{C_{ss}}{C_s}\approx \sqrt{\frac{\frac{d_f}{D_n}}{\sum \frac{L_t}{D_t}}}$$ where n is the total number of layers, L i and D i are the thickness [L] and the effective diffusivity in i layer counted from the bottom [L 2 /T].…”

“…In this study, with the help of three-dimensional (3-D) numerical simulations and mathematical approximations, we introduce a VI screening tool (AAMLPH) as an alternative to evaluate lateral VI inclusion zones based on site-specific characterizations including surface cover and soil geology, by employing a critical subslab concentration C ss and source-to-subslab attenuation factor ${\alpha }_s^{ss}$ as the screening criteria. Similar to the Analytical Approximations Methods (AAMs) developed in previous studies [17, 31–32], AAMLPH can be used independent of building operational conditions without computational efforts.…”