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Laboratory Simulation of VOC. Entry into Residence Basements from Soil Gas. DAVID FISCHER AND. CHRISTOPHER G. UCHRIN*. Department of ...
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Environ. Sci. Technol. 1996, 30, 2598-2603

Laboratory Simulation of VOC Entry into Residence Basements from Soil Gas DAVID FISCHER AND CHRISTOPHER G. UCHRIN* Department of Environmental Sciences, Rutgers University, New Brunswick, New Jersey 08903, and Environmental and Occupational Health Sciences Institute, 681 Frelinghuysen Road, Piscataway, New Jersey 08855

Pollutants in groundwater can be a source of exposure to residents of houses overlying contaminated aquifers. Volatile compounds may migrate through soil gas and enter below-grade basements under negative pressure. A three-dimensional apparatus was built to simulate intrusion of volatile organics from groundwater into residence basements. Three reference soil materials were used to fill the model, each with different air permeabilities and organic matter contents. A simulated basement was equipped with holes in the floor, which were sealed in three configurations to represent different size cracks. Experiments were run on each soil, with each hole configuration, at several levels of depressurization. Soil permeability was found to be the overriding factor controlling advective TCE intrusion into basements. Soil porosity as well as particle size and shape distribution will dictate the diffusive migration of TCE through the soil profile and toward the building superstructure. Basement crack size does not appear to be a significant variable, and degree of depressurization is only significant in terms of dilution at higher rates of flow. The experiments also served to verify previous hypotheses proposed by mathematical models and field experiments.

Introduction Soil gas overlying a contaminated aquifer may contain significant concentrations of the contaminant, especially in the case of highly volatile compounds. Volatile organic compounds (VOCs) are widely found in groundwater systems and in the vadose zone above the groundwater table due to spills, leaks, and improper usage and disposal practices. When present in soil gas, VOCs can enter residences that normally exist under negative pressure and may pose a source of exposure to the occupants. This route * Corresponding author present address: Department of Environmental Sciences, Cook College, P.O. Box 231, New Brunswick, NJ 08903-0231; telephone: (908) 932-9444; fax: (908) 932-8644; e-mail address: [email protected].

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of entry is similar to that of radon, whose presence in indoor air is thought to be primarily due to the entry of soil gas into residences (1). Soil gas may infiltrate a home by advective (pressure-driven) entry through cracks in the building’s substructure, by diffusive entry through those cracks, or by diffusion through the actual building material, which may be porous (1-4). Recently, more interest has been focused on this phenomenon, and several investigators have monitored actual (2, 4-9) or experimental (10, 11) structures in the field in an attempt to quantify the risk factors and significant variables involved in radon or VOC transport from soil gas into basements. Additionally, mathematical models have been developed (3, 12-15) to simulate soil gas intrusion into basements and attempt to accurately predict VOC or radon concentrations in houses overlying contaminated soils or groundwater. To better understand the mechanisms involved in this phenomenon, however, it is preferable to be able to control the variables that significantly impact soil gas intrusion, such as basement construction, degree of depressurization, and soil properties. This paper describes the construction and operation of a physicalscale model that simulates VOC entry into a basement via soil gas volatilizing from groundwater and discusses the results of experiments with this apparatus utilizing three different soils. Several factors may affect depressurization of basements: Wind loading on the superstructure of a house, temperature differences between the soil and the basement, barometric pressure changes due to the weather, and precipitation (1) as well as unbalanced ventilation due to operation of furnaces or exhaust fans (8, 16). Arnold (17) found wind loading to be a significant source of pressure differential, with temperature differences becoming important on cold calm days. Narasimhan et al. (18) found large barometric pressure fluctuations to be most significant in cases of low soil permeability. The degree of underpressurization may vary between 0 and 10 Pa (4), with a typical value being 5 Pa or less (9). Experiments conducted in the field (2, 4, 6, 8, 11) have shown a pressure “coupling” between the basement and surrounding soil, which creates disturbances in the pressure field in the soil, influencing the degree and direction of air movement toward the basement. Loureiro et al. (14) used mathematical modeling to develop contours of disturbance pressures in the soil originating from the basement depressurization. This pressure field was used to simulate radon flux across the soil-gap interface and showed that convective flux will increase dramatically with increased pressure differential while diffusive flux will become insignificant. It was also shown that radon concentrations in the soil gas along the perimeter of the gap may increase with increasing pressure disturbance, until a point at which a dilution effect begins to be noticed. This increase is least noticeable with lower permeability soils and only becomes significant at permeabilities over 10-8 cm2, where diffusion becomes less important. Revzan et al. (15) later modified this model to include convection of soil gas resulting from the heating of the basement in the winter. Garbesi and Sextro (2) found that pressure-driven air flow is a significant

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FIGURE 1. Air permeameter.

pathway not only through major cracks in the floor but also through permeable materials and networks of small cracks.

Experimental Section Reference Soils. Three reference soils were used: Acidwashed sand, as described in Fischer and Uchrin (19); Cohansey soil, a high organic mater (1.44% organic carbon) sand excavated from the surface horizon near Chatsworth, NJ; and Neshaminy soil, a silty clay loam excavated from near Princeton, NJ. All soils were air dried. Dry bulk density, porosity, and moisture content were determined for all soils. Air permeability of each soil was determined by the use of a permeameter, shown in Figure 1. Two glass bulbs were connected with a Teflon fitting (Ace Glass, Vineland, NJ), 8 cm long and 5 cm in diameter. The Teflon fitting was filled with soil and separated from the glass bulbs by 30µm nylon mesh. Air flowed in through one glass bulb, through the soil, and out through the other glass bulb, which led to an air flow bubble meter (Gilian Instrument Corp., West Caldwell, NJ). Each glass bulb was connected to a differential manometer (Dwyer Instruments, Michigan City, IN) to note the pressure difference between the influent and effluent sides. All connections were sealed with Teflon O-rings. Air flow, regulated by a needle valve, was adjusted to correspond to a given pressure differential and allowed to equilibrate. This was done for several levels of pressure gradients, and the air flow was noted for each pressure gradient. Using a variation of Darcy’s law

Q)-

(ηk)(∂P∂x)

(1)

where Q is the air flow through a sample of length x, k is the permeability coefficient, η is the viscosity of air, and ∂P/∂x is the pressure drop across the sample, air permeability was computed for each pressure gradient, and the average was taken as the air permeability for the soil. Although air permeability measurements have been shown to be scale-dependent (20), the readings obtained by this method are thought to be fairly accurate and are deemed to be sufficient for comparative purposes in this model. Scale Model. A Plexiglas tank, measuring 58 × 25 × 51 cm was constructed (see Figure 2), similar to that described in ref 19, with modifications as follows: Four vapor ports were added to this model to enable monitoring of TCE in the vapor phase throughout the soil column. Gas sampling valves (Kloehn Company, Brea, CA) were fitted in each vapor port and kept in the closed position except during sampling. A 10-gauge, 4 in. long needle was attached to each valve inside the tank to sample soil gas. Three aqueous sampling ports were added in the influent constant head chamber,

the soil compartment, and the effluent constant head chamber. Quick disconnect fittings were placed in these ports to enable easy sampling. To minimize the effects of capillary rise in the model, the bottom 10 cm of the tank was filled with gravel. Soil was filled in the next 28 cm in a manner similar to that described in ref 19. The fume hood was disabled during the filling phase to prevent the loss of fine soil particles. The basement structure was placed 10 cm deep in the soil, so that 2.5 cm extended above the soil surface. The contaminated water flowed only through the gravel layer, at a depth of 2.5 cm below the bottom of the soil layer. This was necessary due to the large amount of capillary rise found with fine soils in the prototype study, which would transport aqueous-phase contaminants to the basement floor, making it impossible to study the vapor-phase transport phenomena. It is assumed that the gravel/soil interface is not a significant barrier to vapor transport compared to the scenario of soil alone. The dividers between the soil compartment and constant head chambers were designed as removable pieces, with four 5 cm long rods holding the dividers in place against the soil. The bottom 10 cm of each divider had 0.5-in. holes drilled across to allow for even flow of water. Two layers of Teflon mesh, pore sizes 1000 and 105 µm, respectively, were placed between the dividers and the gravel to restrict gravel and soil migration into the constant head chambers. Each constant head chamber was equipped with a Teflon-coated wooden block that was installed above the water level to minimize evaporation and volatilization from the water. The basement structure is simulated by a Teflon-coated Plexiglas cube, 12.7 cm on each side (2048 cm3 volume) with four holes drilled in the “floor”, two of 0.64 cm diameter and two of 0.32 cm diameter, to allow for simulation of different crack sizes by sealing different holes. Round holes were used rather than straight cracks because scaling down straight cracks to laboratory sizes imply such slight widths that edge effects would be considerable. It was decided that, although the geometry of holes causes different patterns of soil gas flow than straight cracks, this effect in a small model is slight while the edge effects of a thin crack would be substantial. The top of the cube is removable and is sealed during experimental runs. It features two ports with Teflon elbows, one for drawing air out of the basement and one for pressure readings. Both lead to ports in the tank wall, which feature quick disconnect fittings on the outside of the tank. An additional pressure reading was taken in the soil with a perforated Teflon tube connected to a quick disconnect fitting in the tank wall. The two pressure ports remain connected to a differential manometer (Dwyer Co.) to maintain accurate readings of basement depressurization. A blower located outside of the fume hood delivered a constant clean air flow over the soil surface. Flow velocity was maintained at approximately 2400 ft/min. A small sheet of Teflon mesh was placed near the air input port to diffuse the air flow over the entire soil surface. For each of the three soils, three experiments were run to test three different basement hole configurations: (1) All four holes open, i.e., 0.794 cm2 total crack area. (2) Two 0.32 cm holes open, i.e., 0.159 cm2 total crack area. (3) One 0.32 cm hole open, i.e., 0.0794 cm2 total crack area.

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FIGURE 2. Laboratory model schematic. TABLE 1

Reference Soil Properties soil type acid-washed sand Cohansey sand Neshaminy clay loam

bulk air density porosity permeability moisture (g/ml) (%) (cm2) (%) 1.68 1.60 1.22

34.1 33.4 50.5

6.02 × 10-7 3.59 × 10-7 6.53 × 10-9

0.12 0.24 1.9

For each experiment, a number of different pressure gradients were tested, beginning at 0 and continuing to larger negative gradients until a definite dilution effect could be noted from the air over the soil. At each level of depressurization, readings were taken one to three times daily until a steady state of basement TCE concentration was reached. It is hoped that the size of this model is adequate to minimize boundary effects and to allow extrapolation of the data to actual houses. As with any scale model, however, some boundary effects are inevitable and should be taken into account when using the data for real-world scenarios.

Results and Discussion For purposes of this section, V4, V3, V2, and V1 refer to TCE concentrations at the four vapor sampling ports, beginning with the highest, and in, mid, and out refer to aqueous TCE concentrations in the influent, middle, and effluent aqueous sampling ports. In addition, bsmt refers to TCE vapor concentration in the simulated basement as measured at the gas sampling bulb. Detailed results can be found in Fischer (21). Soil properties are outlined in Table 1. While the Neshaminy soil exhibits much lower permeability, its clayey nature dictates a much higher porosity than the sandy soils. By comparing the vapor concentration (across all configurations and depressurizations, excluding initial nonsteady-state readings) at V1-V4 to the aqueous concentrations under the vapor sampling ports, we can form a profile of TCE concentrations in the soil gas. An average of in and mid was used to estimate the aqueous concentration directly under the sampling ports, and the vapor concentrations

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FIGURE 3. TCE profile in soil gas.

were then divided by the result, as a measure of normalization. The resulting profiles are shown in Figure 3. The shapes of the profile curves are indicative of the Fickian diffusion equation. Fick’s law states that the diffusion coefficient of a component in soil will dictate the flux of that component through the soil profile. By this equation, we can see that diffusion is heavily dependent on porosity of the media. Thus, the Neshaminy soil, having a much higher porosity than the Cohansey, shows greater concentrations in its profile. In fact, neglecting soil moisture, which is negligible for our soils, we can utilize the equation Ds ) Dgφ4/3, which indicates that diffusive flux is 67% higher for a soil of 50% porosity (such as Neshaminy) than one of 34% porosity (such as Cohansey). Also notable is the higher V4 value for the Neshaminy soil, which is a result of the low permeability of the soil restricting TCE losses to the “atmosphere”, as shown by Jury et al. (22). The acid-washed sand has a porosity similar to that of the Cohansey soil. One would expect, therefore, to see the profile for sand fall closer to the Cohansey profile than the Neshaminy profile. The high soil gas concentrations found during the sand experiments are thought to be a result of the very high air permeability of that soil, leading to increased mass transfer rates between the groundwater and the gravel zone to the soil. This leads to a higher V1 and,

FIGURE 4. Basement depressurization vs soil gas flow into basement.

FIGURE 5. Average basement normalized TCE concentration vs depressurization.

consequently, higher readings throughout the soil column. V4 values were consistently low for the sand, as the high permeability of the soil offered little resistance to atmospheric loss. In order to examine the basement concentration of TCE relative to the soil gas concentration outside of the basement floor, we normalize bsmt by the estimated TCE concentration in the soil gas, and thus instead of graphing using bsmt as a comparison, we use normbsmt, where

normbsmt )

bsmt V3 × (mid + out/in + mid)

(2)

Since multiple readings were taken for each depressurization level, average values were used to arrive at final data points. Certain data points were discarded due to malfunctioning equipment, flow interruptions, or other circumstances. In addition, the first readings on each soil, i.e., those that were taken prior to a noticeable leveling out in the normalized vapor concentrations, were discarded as transient and inappropriate for steady-state analyses. This equilibration period was necessary as each soil series was initiated using clean water and required some time for the TCE to migrate upwards and reach steady state. For the Cohansey experiments, this was even more significant as a period of increased sorptive activity was noticeable in the initial period, causing a longer equilibration time than acidwashed sand or Neshaminy soils, which seemingly reached equilibrium in a matter of a few days. Equivalent depressurizations imply different air flows for each soil, as can be seen in Figure 4. Lower permeability soils such as Neshaminy provide more resistance to air flow, yielding lower flow than the sandy soils. Figure 5 shows average normbsmt for each soil versus level of depressurization. Analysis of variance (ANOVA)

indicates that soil type is a significant effect on normbsmt, with a p-value less than 0.0001. Further post-hoc tests (pairwise t-tests) indicate that, at a 5% level of significance, sand/Cohansey basement concentrations are not significantly different, but sand/Neshaminy and Cohansey/ Neshaminy are significantly different, and in fact are even different at a 0.1% level. Once TCE reaches the soil surrounding the basement, the main factor limiting its entry to the indoor air is thought to be the air permeability of the soil. More highly permeable soils allow greater amounts of TCE to be drawn toward the basement along with the advective flow of soil gas. Thus, the greater the permeability difference between soils, the more significant the effects on concentration will be. Hence the clayey soil exhibits great reduction compared with the sandy soils, but the two sandy soils, although exhibiting different permeabilities, are not sufficiently divergent to cause significant changes in basement concentration. By examining the trends in Figure 5, one can see that the normbsmt concentrations in the acid-washed sand experiments are quite high but decrease rapidly, even at low levels of depressurization. The Cohansey concentrations begin lower, then increase, and drop off as depressurization intensifies. Neshaminy concentrations are low and remain relatively stable over different levels of depressurization. These behaviors can be explained by the differing air flow patterns found in the three soils. The very high rate of soil gas entry in the sand experiments brings large amounts of TCE into the basement but also serves to dilute the basement air at relatively low levels of depressurization by bringing in air from cleaner areas of the soil profile depleted of their reservoirs of TCE by the rapid air flows. The same phenomenon can be detected in Cohansey but at greater depressurizations because of the lower rates of air flow. Neshaminy soil, with its very low air flow rates, exhibits very little change in normbsmt values even at high levels of depressurization. Analysis of variance (ANOVA) showed depressurization (nested in configuration) to be a significant variable in the sandy soils (p ) 0.003 for acid-washed sand, p ) 0.0001 for Cohansey) but not for Neshaminy (p ) 0.10). Pressure-driven flow through basement cracks is an advective process, and thus higher permeability soils should yield higher basement TCE concentrations. Although sand exhibits the highest normbsmt values, due to its high permeability, the values start decreasing at fairly low depressurizations. The high flow rates exhibited in Figure 4 for sand cause dilution to be a factor at even low levels of depressurization. Cohansey soil exhibits a rise in basement concentrations until approximately 10 Pa, at which point it levels off and decreases at 30 Pa. The maximum normalized concentration of the Cohansey experiments is slightly less than that of the sand experiments due to the lower air permeability of the soil. Neshaminy shows the lowest normbsmt concentrations, as expected, with its air permeability 2 orders of magnitude lower than the other soils. Neshaminy soil also exhibits the most stable normalized basement concentrations. Figure 6 shows average normbsmt for each soil broken down by hole configration. Theory dictates that at lower permeabilities crack size becomes more of a factor as diffusion becomes a significant process. ANOVA shows configuration to have a significant effect on normbsmt for all three soils at the 5% level (p ) 0.049 for sand and 0.0001 for Cohansey and Neshaminy). For the acid-washed sand,

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FIGURE 6. normbsmt vs basement depressurization by crack configuration. TABLE 2

Significance of Crack Size on normbsmt configuration combination 1/2 1/3 2/3

sand 5%

Acknowledgments

COH 1%

NESH

5%

1%

5%

1%

*

*

* *

*

*

* * *

*

Both mechanisms described here, therefore, become more significant in lower permeability soils. Basement crack size leads to greater levels of diffusion from soil gas and as such will be a more noticeable variable in lower permeability soils. The wall/soil gap, however, also becomes important in lower permeability soils, where flow rates can be extremely low, and any disturbance in the subsurface configuration can significantly change these flow rates. It is not clear from the experimental data which mechanism is responsible for the significance of crack size in the lower permeability soils. The results of these experiments validate previously hypothesized mechanisms of vapor intrusion into residences. Air permeability of the soil surrounding the basement seems to be the most significant variable, with depressurization playing more of a role in the more permeable soils and crack size playing more of a role in the less permeable soils. The data support the findings of Loureiro et al. (14) that depressurization plays an increasingly important role as permeability rises above 10-8 cm2. These experiments did not consider diffusive transport through basement walls and thus could not address the importance of that mechanism. A mathematical model calibrated on the basis of these data found that a small gap between the external wall of the basement and the soil must be considered to accurately predict TCE entry into basements (23). The model also found that the overriding factor influencing indoor air concentration of the contaminant will be the air exchange rate of the building, which was not considered in the experiments. Further investigations will investigate the role of diffusion through basement walls and the effects of ventilation.

This research was funded in part by the NIEHS Superfund Basic Research Program (Project ES-05955), the Rutgers University/RWJMS-UMDNJ Environmental and Occupational Health Sciences Institute, and the NJ Agricultural Experiment Station, Publication D-06525-3-96.

Literature Cited however, this significance is questionable, and hole configuration is not significant at the 1% level. Post-hoc tests were done to determine which combinations of crack size were significantly different at the 5% and 1% levels. Results are summarized in Table 2, where an asterisk denotes a significant effect at the specified level. Crack size becomes more significant as permeability decreases. However, it cannot be shown from these data that diffusion is responsible for the significance of crack size in the lower permeability soils. In fact, the direction of change in concentration, which should be directly related to the change in crack size, is sometimes inversely related, leading to the conclusion that some other mechanism besides crack size may be responsible for the concentration differences. Thus, the changes in basement/soil gap size due to disturbances during configuration changes may be partially responsible for the apparent significance of crack size. This mechanism would be amplified in lower permeability soils, where the resistance to flow is greater, and any low resistance flow path, such as a gap, drastically changes the depressurization/air flow relationship and thus basement concentrations.

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(1) Nazaroff, W. W.; Moed, B. A.; Sextro, R. G. In Radon and Its Decay Products in Indoor Air; Nazaroff, W. W., Nero, A. V., Eds.; John Wiley and Sons: New York, 1988; Chapter 2. (2) Garbesi, K.; Sextro, R. G. Environ. Sci. Technol. 1989, 23, 14811487. (3) Johnson, P. C.; Ettinger, R. A. Environ. Sci. Technol. 1991, 25, 1445-1452. (4) Hodgson, A. T.; Garbesi, K.; Sextro, R. G.; Daisy, J. M. J. Air Waste Manage. Assoc. 1992, 42, 277-283. (5) Moseley, C. L.; Meyer, M. R. Environ. Sci. Technol. 1992, 26, 185-192. (6) Nazaroff, W. W.; Lewis, S. R.; Doyle, S. M.; Moed, B. A.; Nero, A. V. Environ. Sci. Technol. 1987, 21, 459-465. (7) Kliest, J.; Fast, T.; Boley, J. S. M.; van de Wiel, H.; Bloemen, H. Environ. Int. 1989, 15, 419-425. (8) Turk, B. H.; Harrison, J.; Prill, R. J.; Sextro, R. G. Health Phys. 1990, 59, 405-419. (9) Nazaroff, W. W.; Feustel, H.; Nero, A. V.; Revzan, K. L.; Grimsrud, D. T.; Essling, M. A.; Toohey, R. E. Atmos. Environ. 1985, 19, 31-46. (10) Ward, D. C.; Borak, T. B.; Gadd, M. S. Health Phys. 1993, 65, 1-11. (11) Garbesi, K.; Sextro, R. G.; Fisk, W. J.; Modera, M. P.; Revzan, K. L. Environ. Sci. Technol. 1993, 27, 466-473. (12) Sanders, P. F.; Stern, A. H. Environ. Toxicol. Chem. 1994, 13, 1367-1373. (13) Revzan, K. L.; Fisk, W. J. Indoor Air 1992, 2, 40-48. (14) Loureiro, C. O.; Abriola, L. M.; Martin, J. E.; Sextro, R. G. Environ. Sci. Technol. 1990, 24, 1338-1348.

(15) Revzan, K. L.; Fisk, W. J.; Gadgil, A. J. Indoor Air 1991, 2, 173189. (16) Little, J. C.; Daisey, J. M.; Nazaroff, W. W. Environ. Sci. Technol. 1992, 26, 2058-2066. (17) Arnold, L. J. Ph.D. Dissertation, Rutgers University, 1988. (18) Narasimhan, T. N.; Tsang, Y. W.; Holman, H. Y. Geophys. Res. Lett. 1990, 17, 821-824. (19) Fischer, D.; Uchrin, C. G. J. Environ. Sci. Health 1994, A29, 15651576. (20) Garbesi, K.; Sextro, R. G.; Robinson, A. L.; Wooley, J. D.; Owens, J. A.; Nazaroff, W. W. Water Resour. Res. 1996, 32, 547-560.

(21) Fischer, D. Ph.D. Dissertation, Rutgers University, 1995. (22) Jury, W. A.; Russo, D.; Streile, G.; Abd, H. E. Water Resour. Res. 1990, 26, 13-20. (23) Liao, H. Ph.D. Dissertation, Rutgers University, 1996.

Received for review December 29, 1995. Accepted April 12, 1996.X ES950967G X

Abstract published in Advance ACS Abstracts, June 1, 1996.

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