Screening Houses for Vapor Intrusion Risks: A Multiple Regression Analysis Approach

Johnston, Jill; Gibson, Jacqueline Mac Donald

doi:10.1021/es4003795

Cited by 23 publications

(26 citation statements)

References 42 publications

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“…Thus it appears unlikely that the six orders of magnitude variation in source-to-subslab attenuation is attributable to temporal effects. Moreover, the effect of building construction differences is not nearly significant enough to induce such variation [14]. …”

Section: Resultsmentioning

confidence: 99%

“…This value is consistent with the maximum

α_{g w}^{s s}

(0.4) from Figure 5, and the earlier derived

α_{s s}^{i n}

of 0.02. Johnston and Gibson [14] likewise showed that this value (0.004) would be conservative for most cases in EPA database, except for a few with shallow groundwater source, slab-on-grade construction on very coarse soil. The above analysis shows that the greater weakness in prediction of

α_{g w}^{i n}

may be in the prediction of

α_{g w}^{s s}

.…”

Section: Resultsmentioning

confidence: 99%

“…Johnston and Gibson [14] reported that the soil type plays a significant role in influencing attenuation factor, with fine-grained soils giving lower values than coarse-grained. This is understood in terms of the influence of permeability on the soil gas entry rate, as illustrated in (9).…”

Section: The Physical Basis Of Attenuation Factorsmentioning

confidence: 99%

“…This is understood in terms of the influence of permeability on the soil gas entry rate, as illustrated in (9). Also, the attenuation factors are higher in winter, in which stack effect depressurization ( Δ p ) is expected to be high and air exchange rate lower, except for crawl-space houses [14]. Consequently, the attenuation factors for soil transport (and the source-to-subslab attenuation) and for building entry (and the

α_{s s}^{i n}

) are governed by different physical variables, and there is no reason to expect that the values of these attenuation factors should be related to each other.…”

Section: The Physical Basis Of Attenuation Factorsmentioning

confidence: 99%

“…The background levels of these different contaminants of concern are all actually different, but close enough on the chosen logarithmic scale as to be indistinguishable. A statistical analysis of factors influencing attenuation factors also showed that the influences of differing molecular weights and diffusivities of contaminants are small [14]. So for the moment they are treated as the same (distinctions between different contaminants will be shown below).…”

Section: Introductionmentioning

confidence: 99%

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

Yao

Suuberg

et al. 2015

Journal of Hazardous Materials

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The basis upon which recommended attenuation factors for vapor intrusion (VI) have been derived are reconsidered. By making a fitting curve to the plot showing the dependence of observed indoor air concentration (cin) on subslab concentration (css) for residences in EPA database, an analytical equation is obtained to identify the relationship among cin, css and the averaged background level. The new relationship indicates that subslab measurements may serve as a useful guide only if css is above 500 μg / m3. Otherwise, cin is independent of css, with a distribution in good agreements with other studies of background levels. Therefore, employing this screening value (500 μg / m3), new contaminant concentration attenuation factors are proposed for VI, and the values for groundwater-to-indoor and subslab-to-indoor air concentration attenuation factors are 0.004 and 0.02, respectively. The former is applied to examining the reported temporal variations of cin obtained during a long-term monitoring study. The results show that using this new groundwater-to-indoor air concentration attenuation factor also provides a reasonably conservative estimate of cin.

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Section: Resultsmentioning

confidence: 99%

“…This value is consistent with the maximum

α_{g w}^{s s}

(0.4) from Figure 5, and the earlier derived

α_{s s}^{i n}

α_{g w}^{i n}

may be in the prediction of

α_{g w}^{s s}

.…”

Section: Resultsmentioning

confidence: 99%

Section: The Physical Basis Of Attenuation Factorsmentioning

confidence: 99%

α_{s s}^{i n}

) are governed by different physical variables, and there is no reason to expect that the values of these attenuation factors should be related to each other.…”

Section: The Physical Basis Of Attenuation Factorsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Yao

Suuberg

et al. 2015

Journal of Hazardous Materials

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A two‐dimensional analytical model of vapor intrusion involving vertical heterogeneity

Yao¹,

Verginelli

Suuberg

2017

Water Resources Research

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In this work, we present an analytical chlorinated vapor intrusion (CVI) model that can estimate source‐to‐indoor air concentration attenuation by simulating two‐dimensional (2‐D) vapor concentration profile in vertically heterogeneous soils overlying a homogenous vapor source. The analytical solution describing the 2‐D soil gas transport was obtained by applying a modified Schwarz‐Christoffel mapping method. A partial field validation showed that the developed model provides results (especially in terms of indoor emission rates) in line with the measured data from a case involving a building overlying a layered soil. In further testing, it was found that the new analytical model can very closely replicate the results of three‐dimensional (3‐D) numerical models at steady state in scenarios involving layered soils overlying homogenous groundwater sources. By contrast, by adopting a two‐layer approach (capillary fringe and vadose zone) as employed in the EPA implementation of the Johnson and Ettinger model, the spatially and temporally averaged indoor concentrations in the case of groundwater sources can be higher than the ones estimated by the numerical model up to two orders of magnitude. In short, the model proposed in this work can represent an easy‐to‐use tool that can simulate the subsurface soil gas concentration in layered soils overlying a homogenous vapor source while keeping the simplicity of an analytical approach that requires much less computational effort.

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Chlorinated vapor intrusion indicators, tracers, and surrogates (ITS): Supplemental measurements for minimizing the number of chemical indoor air samples—Part 1: Vapor intrusion driving forces and related environmental factors

Schuver

Lutes

Kurtz

et al. 2018

Remediation Journal

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Vapor intrusion (VI) assessment is complicated by spatial and temporal variability, largely due to compounded interactions among the many individual factors that influence the vapor migration pathway from subsurface sources to indoor air. Past research on highly variable indoor air datasets demonstrates that conventional sampling schemes can result in false negative determinations of potential risk corresponding to reasonable maximum exposures (RME). While high‐frequency chemical analysis of individual chlorinated volatile organic compounds (CVOCs) in indoor air is conceptually appealing, it remains largely impractical when numerous buildings are involved and particularly for long‐term monitoring. As more is learned about the challenges with indoor air sampling for VI assessment, it has become clear that alternative approaches are needed to help guide discrete sampling efforts and reduce sampling requirements while maintaining acceptable confidence in exposure characterization. Indicators, tracers, and surrogates (ITS), which include a collection of quantifiable metrics and tools, have been suggested as a potential solution for making VI pathway assessment and long‐term monitoring more informative, efficient, and cost‐effective. This review, compilation, and evaluation of ITS demonstrates how even low numbers of indoor air CVOC samples can provide high levels of confidence for representing the RME levels (e.g., 95th percentile) often sought by regulatory agencies for less than chronic effects. A two‐part compilation of available evidence for select low‐cost ITS is presented, with Part 1 focused on introducing the concepts of ITS, meteorologically based ITS, and the evidence from data‐rich studies to support lower cost CVOC VI assessments. Part 1 includes the results of quantitative analyses on two robust residential building VI datasets, where numerous supplemental metrics were collected concurrently with indoor air concentration data. These are supplemented with additional less‐intensive studies in different circumstances. These analyses show that certain ITS metrics and tools, including differential temperature, differential pressure, and radon (in Part 2), can provide benefits to VI assessment and long‐term monitoring. This includes indicators that narrow the assessment period needed to capture RME conditions, tracers that enhance understanding of the conceptual site model, and aid in the identification of preferential pathways and surrogates that support or substitute for CVOC sampling results. The results of this review provide insight into the scientifically supportable uses of ITS.

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Screening Houses for Vapor Intrusion Risks: A Multiple Regression Analysis Approach

Cited by 23 publications

References 42 publications

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

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

A two‐dimensional analytical model of vapor intrusion involving vertical heterogeneity

Chlorinated vapor intrusion indicators, tracers, and surrogates (ITS): Supplemental measurements for minimizing the number of chemical indoor air samples—Part 1: Vapor intrusion driving forces and related environmental factors

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