This report focuses exclusively on îhis second class of sites, where advection and diffusion occur through a soil layer and into an enclosed space and time is available to adequately ad
Key Technical Considerations
When developing Risk-Based Screening Levels (RBSL), it is crucial to consider factors often overlooked, such as diverse soil types, layered stratigraphies, biodegradation of contaminants, and depleting sources, as these can significantly impact the vapor intrusion pathway assessment on a site-specific level Additionally, various site-specific sampling options, as illustrated in Figure 1, should be evaluated Key technical considerations for selecting data collection and analysis methods include the integration of measurements into standard site assessments, with a focus on utilizing soil cores, soil moisture, and soil gas measurements.
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Methods that do not depend on soil vapor and soil contamination partitioning calculations are preferred, emphasizing the use of soil gas measurements Current site assessment practices and tools make it challenging to accurately define source zone masses While considering depleting sources on a site-specific basis is often impractical, it may be relevant when developing generic Risk-Based Screening Levels (RBSLs).
The time for vapors to achieve near-steady concentrations increases with the square of the distance from the source and is influenced by the chemical properties of the compound Additionally, surface barriers such as pavement and buildings can impact near-surface vapor concentrations When assessing potential future impacts, it is crucial to prioritize soil gas measurements near the source over those taken near the surface or in enclosed spaces.
An estimate of the time T~~ [d] required to reach near-steady vapor concentrations and fluxes at any distance L [m] from a source is:
The vapor-phase retardation factor, denoted as R, is defined by Equation (3) and is integral to Equation (4), which is derived from transient diffusion solutions (Crank 1956) under step-change boundary conditions at zero time Figure 3 illustrates the calculated z,& values across various soil moisture contents.
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For reference, the chemicals most likely to cause exceedences of flammable levels (Cindoor
At fuel release sites, chemicals such as propanes, butanes, and pentanes exhibit retardation factors close to unity, indicating minimal delay in their movement In contrast, oxygen migrates with little retardation due to its high Henry's Law constant and low sorption Health-related chemicals, like benzene, demonstrate vapor-phase retardation factors ranging from 10 to 100 Consequently, various chemicals will reach near-steady concentrations at different times.
Soil gas hydrocarbon concentrations near the source zone stabilize quickly, typically within hours to days, while those several meters away may take years or even decades to reach similar conditions due to the square relationship with distance from the source However, analyses that account for chemical reactions indicate that near-steady conditions can be achieved more rapidly, especially when significant degradation rates are present, allowing for steady state at lower concentrations Additionally, significant advection, such as pressure-driven vapor flow through permeable conduits, can further reduce the time required to attain near-steady conditions.
Soil gas concentrations measured close to a source typically reflect near-steady conditions, while concentrations taken several meters away may not Therefore, it is essential to exercise caution when relying on indoor, near-surface, or distant soil gas concentrations for site-specific assessments These assessments should only be conducted if it is confirmed that sufficient time has passed since the release, surpassing the estimated time to reach near-steady conditions Utilizing soil gas concentrations from near the source is advisable, provided there is a clear understanding of the subsurface geology between the source and the enclosed space.
Site-Specific Assessment of the Significance of Vapor Migration to
Emergency response situations have been addressed, and site conditions have been evaluated against generic risk-based screening levels, with noted exceedances Consequently, a more tailored assessment of future and long-term impacts is necessary.
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Generic Risk-Based Screening Levels (RBSLs) typically assume a homogeneous, sandy, and dry vadose zone, neglecting biodegradation and treating the vapor source as constant over time However, site-specific assessments may reveal increased attenuation potential due to factors such as layered strata, higher moisture content, biodegradation in the vadose zone, and source depletion over time Additionally, direct measurements of enclosed-space concentrations or near-foundation soil gas can be pursued for more accurate evaluations.
This article explores various measurement techniques for vapor migration impacts, including direct enclosed-space measurement in section 4.1 and near-foundation measurements in section 4.2 It examines factors that reduce vapor migration potential compared to standard regulatory cases, with increased diffusion resistance covered in section 4.3, the use of soil gas concentrations with depth for refined analyses in section 4.4, and the role of vadose zone biodegradation in section 4.5 Additionally, source depletion is briefly addressed in section 4.6.
Table 1 summarizes the options and data collection requirements for each.
Direct Measurement of Enclosed-Space Vapor Concentrations
In situations where explosions, fires, or acute health risks are suspected, vapor samples are promptly collected from enclosed spaces However, the use of direct measurement for long-term site-specific assessments is expected to be more limited due to the complexities involved in obtaining and interpreting these samples Indoor vapor sources may already exist, and sampling in occupied buildings can lead to unnecessary emotional distress for residents Therefore, unless other indicators suggest an immediate threat, direct indoor vapor sampling is generally discouraged Guidance on indoor air sampling considerations can be found in USEPA (1992), while complications related to indoor air sampling are discussed in the Total Exposure Assessment Methodology (TEAM) studies by USEPA (1987).
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The current vapor concentrations may not accurately reflect long-term conditions, as insufficient time may have elapsed to achieve near-steady states Additionally, these concentrations could be influenced by dynamic factors, such as seasonal variations in soil conditions.
In addition, many site-specific assessments will involve sites where a building or enclosed space does not currently exist, and the concern is for impacts under reasonable potential future scenarios
Therefore, as stated above, this option is envisioned to be of limited use when making more refined site-specific assessments of potential impacts from vapor migration to enclosed spaces
4.2 Use of Soil Gas Samples Collected Near Surface, or Near the Foundation of the
Near surface and sub-foundation sampling is appealing for two main reasons: it allows for easy sample collection, often achievable by hand or with simple tools, and it simplifies data analysis by eliminating the need for further subsurface characterization or predictions of vapor transport For instance, as illustrated in Figure 2, one can estimate short-term indoor concentrations based on sub-foundation measurements.
The chemical concentration of radon in soil gas, denoted as Csoilga [mg/m³], is measured near the basement wall or foundation This estimate aligns with previous inputs and is supported by field studies that examine the correlation between soil gas radon levels and indoor radon concentrations (Nazaroff 1987) In enclosed areas with limited air circulation, indoor radon levels may be significantly higher.
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As in the case of direct indoor measurement, it should be noted that there are also serious limitations to this approach, mainly:
Near-surface soil gas measurements are more prone to sampling errors (short- circuiting along the sampling probes)
Surface barriers, such as pavements and buildings, can influence near-surface vapor concentrations, making measurements at open sites potentially unrepresentative of soil gas levels beneath structures However, vapor concentrations close to the source remain largely unaffected by surface conditions.
It is possible that not enough time has passed since the release for near-steady soil gas concentrations to be achieved near the surface as discussed above
4.3 Use of Site-Specific Diffusion Coefficients in the Generic RBSL Algorithms
In this refinement approach, algorithms used for creating generic Risk-Based Screening Levels (RBSLs) are adapted by substituting generic effective diffusion coefficients, soil types, moisture contents, and source-receptor distances with site-specific values To generate a conservative estimate of indoor air concentration for a particular site, essential data includes the vapor concentration in the source zone, as well as the location, thickness, and moisture content of all subsurface layers between the source and the enclosed area.
Once the required inputs are measured or estimated from available data, the following analyses are performed:
1) a subsurface conceptual model is created in which the subsurface is divided into distinct strata, each having a thickness Li [m]
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Effective vapor-phase porous media diffusion coefficients (\$D_i'\$) are determined for each layer using Equation (2), or alternatively, site-specific values can be obtained through the method outlined by Johnson et al (1998).
3) the overall effective difision coefficient for the region between the source and enclosed space D T ~ ~ [m2/d] is calculated using:
D P 1 where LT (= CLi) is the distance between the source and building Resistances (Li/&") to diffusion are in series and additive
4) use the (DT"%T) value calculated with Equation (6) and Equation (1) to calculate a, or read the attenuation factor value fiom Figure 2, if the Figure 2 inputs are reasonable for that site
5) use a and the measured source zone vapor concentration Cs,-,urce to determine if expected indoor concentrations exceed target levels
The data in Table 2 illustrates a site with five depth intervals, where moisture content decreases with depth, leading to an increase in the effective diffusion coefficient Specifically, the value of \((D_{T~~}/L_T) = 0.0042 \, d \, d\) results in \(a = 1.5 \times 10^4\) In contrast, standard assumptions for sandy soil at 1 m depth yield \((D_{T~~}/L_T) = 0.061 \, d \, d\) and \(a = 8.4 \times 10^4\) By accounting for the site-specific soil moisture distribution, the generic concentration estimate for enclosed spaces was significantly reduced to approximately one-sixth.
The source zone vapor concentrations at this site are measured at 94,000 mg/m³ (approximately 0.02% VIV) for total hydrocarbons and 120 ppm for benzene Based on site-specific estimates, the projected indoor concentrations are 14 mg/m³ (around 3 ppm) for total hydrocarbons and 20 ppb (80 pg/m³) for benzene.
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The analysis shows that concentrations in the enclosed space should stay significantly below flammable levels The low benzene levels are unlikely to be detected by portable field instruments and are only slightly higher than typical urban background levels (Shaw and Singh 1988).
Consistent with this analysis, petroleum hydrocarbons and benzene were not detected above background levels in the building at this site
Fischer et al (1996) analyzed soil gas and indoor air concentrations at a petroleum spill site, revealing a degradation factor (\$a = 10^{-4}\$) for nondegrading compounds near the studied building This finding aligns with the generic \$a\$ plot in Figure 2, which, when combined with site-specific soil moisture and porosity data, results in a calculated \$@T'~/LT) = 0.035 m/d\$ and \$a = 7 \times 10^{-4}\$ However, the measured isopentane concentrations indicate a degradation factor of \$N = 7 \times 10^{-7}\$, suggesting that indoor concentrations are approximately one-thousandth of the predictions from Figure 2 The comparison between field observations and the screening-level model estimates shows a close agreement within a factor of about 100 when utilizing site-specific building characteristics and exchange rates.
4.4 Use and Interpretation of Soil Gas Data with Depth
Soil gas samples collected at various depths, although not essential for the initial analysis, can support the assumptions made in the site conceptual model, such as those related to soil moisture and geology Additionally, these samples are valuable for determining whether further refinements to the model are necessary.
Soil gas data can effectively characterize a site when sufficient time has elapsed for near steady conditions at the sampling depth Factors such as the distance from the source, an understanding of the spill history, and reference to Figure 3 are essential in making this determination.
Soil gas concentrations must be graphed against depth and analyzed in relation to the anticipated soil gas concentration profile based on soil moisture content and type, or compared with the site-specific effective diffusion coefficients as measured (Johnson et al 1998).
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Figures 4a and 4b illustrate sample data presentations from BP (1997) and Fischer et al (1996), with BP data reflecting soil gas samples taken at varying depths near a building, while Fischer et al focused on samples collected from beneath a building For effective data visualization, it is recommended to overlay soil gas concentrations on a conceptual subsurface model or plot them alongside it, including available moisture content data After plotting, it is crucial to identify regions where concentrations exhibit sharp increases or decreases.
Use and Interpretation of Soil Gas Data with Depth
Soil gas samples collected at various depths, although not essential for the initial analysis, can support the assumptions made in the site conceptual model, such as those related to soil moisture and geology Additionally, these samples are valuable for determining whether further refinements to the model are necessary.
Soil gas data can effectively characterize a site when sufficient time has elapsed for near steady conditions at the sampling depth Factors such as the distance from the source, awareness of the spill history, and reference to Figure 3 are essential in making this determination.
Soil gas concentrations must be analyzed in relation to depth and compared against the anticipated soil gas concentration profile based on soil moisture content and type, or with the site-specific effective diffusion coefficients as measured (Johnson et al 1998).
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Figures 4a and 4b illustrate sample data presentations from BP (1997) and Fischer et al (1996), with BP data reflecting soil gas samples taken at varying depths near a building, while Fischer et al focused on samples collected from beneath a building For effective data visualization, it is recommended to overlay soil gas concentrations on a conceptual subsurface model or plot them alongside it, including available moisture content data After plotting, it is crucial to identify regions where concentrations exhibit sharp increases or decreases.
To ensure data consistency as outlined in section 4.1, measured vapor concentrations must be compared to the expected concentration profile for a conservative scenario where soil properties change with depth but degradation is absent In a system with n layers, the concentration \( C_j(Z) \) in layer j is determined by the concentration at the upper boundary \( C(LT) \) and the thickness of each layer \( L_i \), along with the effective diffusion coefficient \( D_{ieff} \) In layered environments, greater concentration gradients are anticipated in areas with finer-grained soils and higher moisture levels Figures 5a and 5b illustrate the predicted concentration profiles corresponding to the data in Figures 4a and 4b For open surfaces, \( C(LT) \) is typically much lower than \( C(z=0) \) and can often be disregarded; however, this assumption may not apply to covered sites or areas beneath buildings (Fischer et al 1996, BP 1997).
The predicted concentration distributions should be compared with field data to assess the dominant transport attenuation mechanism If there is a strong correlation, it suggests that diffusion is the primary factor, while biodegradation plays a minimal role, validating the initial site-specific attenuation estimate of 54.3 For instance, Figures 4a and 4b illustrate varying levels of prediction accuracy, with Figure 4b showing improved qualitative features compared to Figure 4a However, the agreement in Figure 4b could be enhanced by considering the moisture content.
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The study indicates that in the 0.48 to 0.58 m region below ground surface (BGS), the moisture content was approximately 0.15 g-H2O/g-soil, which is significantly higher than the 0.10 g-H2O/g-soil level This variation in moisture content impacts the predictions, as illustrated in Figure 5b.
Sharp transitions in actual concentration profiles, as shown in Figure 5a, may not be reflected in predicted profiles, and these discrepancies may not stem from typical errors in soil property measurements One potential explanation is that these transitions could arise from thin, finer-grained soil layers that were overlooked during the initial geologic assessment To investigate this hypothesis, users can either gather additional continuous soil cores or perform in situ diffusion coefficient measurements in the areas where sharp transitions occur For instance, based on the data in Figure 4, in situ diffusion coefficient measurements should be conducted at depths of 4 - 8 ft BGS and 8 - 12 ft BGS.
The study identified 12 to 16 ft BGS intervals, highlighting that multiple plausible hypotheses can exist for a single data set For instance, Fischer et al suggested that the sharp transition they observed was due to more transmissive near-surface soils and subsurface advective flow caused by wind-induced pressure gradients.
Soil gas samples should ideally be collected from each distinct soil stratum identified during the geologic assessment The preferred method for data collection involves vadose zone sampling implants connected to the ground surface using small diameter (1/8” OD) non-adsorbing tubing It is advisable to leave these implants in place for future sampling, as multiple sampling events are often required Additionally, the implants can facilitate in situ diffusion coefficient measurements Key concerns in soil gas sampling include the collection of discrete depth samples and the prevention of atmospheric dilution To address these issues, it is important to minimize sample line and vapor sampler volumes to reduce purge volume, limit the potential for atmospheric short-circuiting between the soil and sampler, and maintain sampling flow rates around 1 L/min or less.
Accounting for Attenuation Due to Biodegradation
This article discusses the integration of aerobic biodegradation into the site-specific evaluation of potential vapor migration effects The subsequent analysis, similar to sections 4.1, 4.2, and 4.4, is primarily relevant for sites that have achieved near-steady conditions.
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If near-steady conditions are unlikely, the user should refer to section $5.0$ to examine site conditions that may promote degradation and determine if these conditions are present at the site.
To determine if biodegradation is significantly reducing vapor migration, it is essential to analyze the vertical distribution of soil gas and the vapor transport characteristics in the unsaturated zone Key data required for this assessment includes total hydrocarbon soil gas concentration at various depths, specific chemical concentrations (such as benzene) with depth, oxygen levels in soil gas across depths, and a subsurface conceptual model detailing layers, soil types, and the depth to the source.
When choosing specific analytes, it is beneficial to include at least one compound that is resistant to degradation and not significantly hindered, even if it does not pose a health risk.
Discrepancies between measured concentrations and those predicted by Equation (7) can indicate significant biodegradation, as shown in Figures 4a and 6 (Ostendorf and Kampbell 1991) However, these differences may also arise from inadequate site characterization data or non-steady conditions Therefore, if biodegradation is suspected to be influential, it is crucial to seek multiple lines of supporting evidence.
As depth increases, oxygen concentrations decrease, aligning with the contaminant vapor concentration profile, which shows sharp transitions in the same region Additionally, the carbon dioxide concentration profile mirrors that of oxygen, while soil gas concentrations remain relatively stable over time.
Traditional indicators of aerobic biodegradation are often sufficient to demonstrate natural attenuation in the vadose zone at most sites However, for a more quantitative approach that incorporates bio-attenuation into site-specific vapor intrusion pathway screening levels, further analysis is required.
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Currently, the optimal approach to achieve this remains uncertain due to limited data and ongoing development of models This article presents two potential refinements for screening-level models, as discussed by Johnson and Kemblowski (1998).
The models are based on existing field and laboratory soil column data, although they have not been thoroughly validated against extensive field datasets They effectively replicate the characteristics of the available data, making them suitable for fitting and extrapolation Additionally, both models separate the transport of oxygen and hydrocarbon vapors, eliminating the need for complete speciation of the hydrocarbon vapors.
The first algorithm mimics data from shallow (