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Remediation of saturated soil contaminated with petroleum products using air sparging with thermal enhancement
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Journal of Environmental Management 83 (2007) 339–350 www.elsevier.com/locate/jenvman
Remediation of saturated soil contaminated with petroleum products using air sparging with thermal enhancement A.M.I. Mohamed, Nabil El-menshawy, Amany M. Saif Mechanical Power Department, Faculty of Engineering, Suez Canal University, Egypt Received 18 April 2005; received in revised form 3 April 2006; accepted 4 April 2006 Available online 17 July 2006
Abstract Pollutants in the form of non-aqueous phase liquids (NAPLs), such as petroleum products, pose a serious threat to the soil and groundwater. A mathematical model was derived to study the unsteady pollutant concentrations through water saturated contaminated soil under air sparging conditions for different NAPLs and soil properties. The comparison between the numerical model results and the published experimental results showed acceptable agreement. Furthermore, an experimental study was conducted to remove NAPLs from the contaminated soil using the sparging air technique, considering the sparging air velocity, air temperature, soil grain size and different contaminant properties. This study showed that sparging air at ambient temperature through the contaminated soil can remove NAPLs, however, employing hot air sparging can provide higher contaminant removal efficiency, by about 9%. An empirical correlation for the volatilization mass transfer coefficient was developed from the experimental results. The dimensionless numbers used were Sherwood number (Sh), Peclet number (Pe), Schmidt number (Sc) and several physical-chemical properties of VOCs and porous media. Finally, the estimated volatilization mass transfer coefficient was used for calculation of the influence of heated sparging air on the spreading of the NAPL plume through the contaminated soil. r 2006 Elsevier Ltd. All rights reserved. Keywords: NAPLs; Air sparging; Volatilization mass transfer coefficient; Soil
1. Introduction Non-aqueous phase liquids (NAPLs) pose a significant threat to ground water resources. When NAPLs infiltrate to the subsurface they descend as an immiscible phase. In cases where of the spilled quantity exceeds the retention capacity of the ground water saturated zone; the NAPLs will reach the capillary fringe. A NAPL less dense than water (LNAPL) will form pools at the water table, while a more dense one (DNAPL) will move through the saturated zone, spreading along the less permeable layers and leaving behind a portion of its volume as immobilized pockets of liquid called residual saturation (Okeson et al., 1997). In the case of both DNAPL and LNAPL, pumping to remove free product within a highly NAPL saturated lens cannot completely recover the NAPL. With the rising of the water table or DNAPL lens migration, NAPL will Corresponding author. Tel.: +20 0 10 1597112; fax: +20 0 66 3400936.
E-mail address: [email protected] (A.M.I. Mohamed). 0301-4797/$ - see front matter r 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.jenvman.2006.04.005
become trapped during pumping as a discontinuous residual. Entrapped NAPLs act as long-term sources of groundwater contamination, (Fisher et al., 1999; Sprague and Delahaye, 1996; Held and Celia, 2001). The present research work aims at the enhancement of the air sparging remedial technology. Air sparging is a costeffective, time-efficient system for the remediation of volatile and/or biodegradable contaminants. This technique involves introducing forced air into the saturated zone of an aquifer to encourage volatilization of contaminants into the unsaturated zone where the contaminants can then be removed with another complementary technology such as soil vapor extraction (SVE), bioventing, horizontal wells, or heating (Sprague and Delahaye, 1996; Reddy et al., 1999). The airflow behavior induced by air sparging is typically characterized by a conical air plume, often known as the radius of influence (Johnson, 1998; Mohtar et al., 1996). Ji et al. (1993) visualized the steady state air distribution patterns using a thin Plexiglas tank with uniform lighting
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Nomenclature A a C Cs D dp d0 d1 H h K kL kG ms _ m Pe Q Sc Sh T t UC u Va
surface area, m2 specific interfacial area, m2/m3 concentration, mg/cm3 aqueous saturation concentration, mg/cm3 molecular diffusion coefficient, cm2/s particle diameter of the soil, mm normalized mean particle size pipe diameter, ‘mm dimensionless Henry’s constant Henry’s constant, atm.m3/mol permeability, mm2 liquid phase volatilization mass transfer coefficient, cm/min gas phase volatilization mass transfer coefficient, cm/min initial mass of VOC injected into the employed soil rate of mass transferred, mg/min Peclet number aeration rate, L/min Schmidt number Sherwood number temperature, K time, s uniformity coefficient of the porous media air velocity, cm/s air phase volume, cm3
behind the tank and glass beads as porous media. They observed two patterns of airflow in soils. The first pattern was observed for medium to coarse grained media where the airflow is characterized by a plume of discrete air bubbles. The second pattern describes the airflow regime for coarse to fine grained media that resemble the textures of sand, silts and clays of natural aquifer material. This flow regime was dominated by channel flow where air plumes are formed from discrete and continuous air channels. As the injection rate increases air channels increase in number and grow into a condensed continuous cone-shape cavity. Braida and Ong (2000) conducted experiments using a single air channel setup to study the influence of porous media properties and air velocity on the fate of NAPLs under air sparging conditions. Their study showed that the presence of advective airflow in air channels controlled the spreading of the dissolved phase but the overall removal efficiency was independent of the air flowrate. In addition, they noted that the removal efficiencies and dissolution rates of the NAPL were strongly affected by the mean particle size of the porous media during air sparging. This agrees with the investigations made by Reddy and Adams (1998). They performed a series of one dimensional column experiments to study the effects of soil type, air injection mode, and the synergistic effects of co-
x z X Z
distance in x-dir., cm depth in z-dir., cm soil reactor width, cm soil reactor depth, cm
Greek letters Zrem l t e n ym o
The contaminant removal efficiency weight factor for the finite difference technique tortuosity factor of the porous media porosity of the porous media kinematic viscosity, cm2/s normalized mean temperature uncertainty of measured or estimated values
Subscripts a diff diss i in G L NAPL out ref w
air phase diffusion dissolution interfacial inlet gas phase liquid phase non-aqueous phase liquid outlet reference water phase
contaminants on air sparging removal efficiency. They found that there is a threshold value for the effective particle size (dp10), which is equal to 0.2 mm; above this threshold value, the rate of removal is linearly proportional to the (dp10) value; while below this value, there is a drastic increase in the time required for contaminant removal. Additionally, they found that the pulsed air injection mode has no advantage over continuous injection for coarse sand; however, pulsed air injection led to substantial reductions in system operating time for fine sand. Also they observed a slight increase in removal rate when benzene and toluene coexisted in the test soil compared to when they existed alone. Chao et al. (1998) developed non-equilibrium water-toair mass transfer experiments for six volatile organic compounds during air sparging in soil columns packed with coarse, medium, or fine sand or glass beads. They performed a numerical study and assumed that the concentration in the bulk phase remained constant due to slow diffusion of VOCs in the aqueous phase to the air–water interface as compared to the rapid volatilization of VOCs at the air–water interface. Therefore, they modeled the interface mass transfer alone. At an in-situ air sparging remediation site contaminated through the spillage of a LNAPL waste, the influence of the system design parameters in terms of contaminant
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removal time was reported by Benner et al. (2000). They suggested that only the type of sparging operation (i.e. pulsed or continuous) was significant in terms of total contaminant removal time, while both the sparging operation and air injection rate were significant in terms of removal of critical xylene species. However, the contaminants within the radius of influence will not be removed with equal efficiencies due to the natural inherited heterogeneity of the porous medium that yields non-uniform and asymmetrical air plumes (Ahlfeld et al., 1994). Rahbeh and Mohtar (2001) studied the influence of porous media heterogeneity and air channelization on contaminant removal by air sparging. Their results showed that the contaminant removal is proportional to channel spacing, and controlled by the process of diffusion between air channels. On the other hand, the contaminant removal is inversely proportional to the spatial variability of the flow field. Many investigators such as Hussein (1997, 1999), Chrysikopoulos and Kim (2000), Chrysikopoulos et al. (2002), Ghoshal and Luthy (1998), and Illangasekare et al. (2000) have demonstrated the complex flow and transport behavior of non-aqueous phase liquids in porous media. Kueper and Frind (1989) developed a two-dimensional vertical section finite difference model to study the simultaneous movement of a dense, non-aqueous phase liquid and water under the water table in heterogeneous porous media. The model was validated against a parallel plate laboratory experiment involving the infiltration of tetrachloroethylene into a heterogeneous sand pack initially saturated with water. Imhoff et al. (1995) investigated experimentally the hot water flooding effects on the remediation of porous media contaminated with tetrachloroethylene at residual saturation. Interfacial tension measurements indicated that there was no change in the tetrachloroethylene -aqueous interfacial tension over the temperature range examined in this study (10–40 1C). On the other hand, flushing with hot water increased the mass transfer rate coefficient by approximately a factor of two as the aqueous phase temperature was increased from 5 to 40 1C. Hot water flushing was suggested to be used before using air sparging remediation technology. The main objective of this work is to investigate numerically as well as experimentally the influence of soil gradation, aeration rate and sparging air temperature on the removal efficiency of NAPLs, such as petroleum products, from contaminated soil. Further, the effect of sparging air temperature on the fate of NAPLs is also investigated numerically.
by channel flow where air plumes are formed from discrete and continuous air channels. The principle mechanism of mass transfer behind in-situ air sparging technology is the volatilization of dissolved VOCs and NAPLs into the air phase. The single-air channel approach has been successfully used for providing information on contaminant removal occurring at the air-channel level during airsparging (Braida and Ong, 1998, 2000). Since a constant air–water interfacial area is available through this approach, it is convenient for studying the influence of soil gradation, aeration rate and sparging air temperature on the removal efficiency of NAPLs at the level of air-channels formed during in-situ sparging of clean air into the contaminated soil. The conceptual experimental set-up used in the current study is a two-dimensional dissolutiondiffusion-volatilization model shown schematically in Fig. 1. The model is designed for a thin air channel located above the water-saturated soil. The one component NAPL (source point) is injected into the reactor at the point (x0, z0). In the case of the NAPL–water interface it reaches equilibrium. Several mathematical models describing the dissolution of residual NAPLs in porous media employ the assumption that the dissolved concentration along the NAPL–water interface is equal to the solubility or aqueous saturation concentration Cs. The results from many previous experimental studies associated with residual NAPL dissolution support the applicability of this assumption (Chrysikopoulos and Kim, 2000). Then, the dissolved NAPL disperses through the saturated soil by molecular diffusion. When the dissolved NAPL molecules reach the plane of the air–water interface (at z ¼ 0), the volatilization of the dissolved contaminant occurs. Batch tests determined that the adsorption of organic contaminants onto the soil solids was negligible (Semer and Reddy, 1998). Further, due to the low organic carbon content, sorption of benzene is not considered in the formulation of the model. Mixing effects as a result of transfer of momentum from the air phase to the aqueous phase are negligible. Assuming stagnant conditions for the aqueous phase. The dissolved concentration along the NAPL–water interface is equal to the solubility or aqueous saturation concentration (Cs).
2. Mathematical formulation and numerical model 2.1. Mathematical formulation As mentioned by Ji et al. (1993), the steady state air distribution pattern for fine to coarse media is dominated
341
Fig. 1. Schematic diagram of the approach model.
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Considering the two-dimensional diffusion–dissolution equation (Braida and Ong, 2000) for any interior node in the reactor we obtain: 2 qC w q C w q2 C w ANAPL ¼ tD þ ðC w CsÞ, J kdiss qt qxx qzx V element (1) where J ¼ 1, in the elements where the NAPL is present, and 0 otherwise. Eq. (1) describes the two dimensional diffusion-dissolution of a contaminant through the water saturated contaminated soil. As shown in Fig. 1 the NAPL is injected at point (x0, z0), therefore, the injected NAPL will be assumed as a spherical glob of radius, r. The above equation is subject to the following boundary conditions. Considering Eq. (1), the initial conditions are: 9 C 0w ðx0 r; zÞ ¼ Cs = ; ðz0 rÞpzpðz0 þ rÞ C 0w ðx0 þ r; zÞ ¼ Cs ; 9 C 0w ðx; z0 rÞ ¼ Cs = ; ðx0 rÞpxpðx0 þ rÞ C 0w ðx; z0 þ rÞ ¼ Cs ; C 0w ðx; zÞ ¼ 0;
elsewhere;
ð2Þ
and the boundary conditions are: 9 qC tw ð0;zÞ ¼0= qx ¯ t 0; 0pzpZ qC tw ðX ;zÞ ; ¼ 0 qx o qC tw ðx;ZÞ ¼ 0 t 0; 0pxpX¯ qz
(3)
At the air–water interface, the volatilization of the dissolved NAPL (at z ¼ 0) will be as follows: qC tw ðx; 0Þ kL Ca ¼ C w ðx; 0Þ t40; 0pxpX¯ . (4) qz tD H
2.2. Numerical technique For solving the basic governing equations of the system introduced above, a finite-difference procedure has been used which is based on a method published by Zheng and Bennett (1995). An explicit-implicit Crank-Niclson form of the finite difference technique is used (Croft and Lilley, 1977). This method was found to be much more stable with a minimum round error compared with the other methods.
A regular grid and a Cartesian coordinate system were applied in the present study. The finite difference formulations were derived for each node of the finite difference mesh. This generates the matrix of the solution, which was solved iteratively to obtain the contaminant concentration distribution through the contaminated soil reactor. A computer program was developed to simulate the behavior of the time variant contaminant concentration distribution through the contaminated soil. The code was written in FORTRAN programming language. It consists of a main program and different subprograms for calculating the volatilization mass transfer coefficient and iterating the solution of the concentration distribution. 2.3. Model validation The numerical model results were validated against the results of two-dimensional sand pack experiments, which were conducted by Braida and Ong (2000) for the same boundary and physical conditions. Benzene was used as a NAPL while medium silica sand of (dp50 ¼ 0.305 mm, UC ¼ 1.41) and fine silica sand of (dp50 ¼ 0.168 mm, UC ¼ 1.64) were used as the contaminated soil. The dissolution mass transfer coefficient, kdiss, and the liquid phase volatilization mass transfer coefficient, kL, are taken from the reference experimental data (Braida and Ong, 2000). Table 1 contains the main operating conditions, which were used in the air sparging experiments for benzene NAPL with an aeration rate of 27.5 mL/min. A comparison between the predicted contaminant concentrations and experimental data obtained from Braida and Ong (2000) is demonstrated in Fig. 2(a–c) for 24, 48, and 72 h from the beginning of benzene injection in the medium silica sand composed of mean particle size of 0.305 mm under an aeration rate of 27.5 mL/min at the air–water interface. The maximum discrepancy between the present theoretical results and the available experimental data from Braida and Ong (2000) was about 20%. The comparison between the present numerical model results and the reference experimental results shows, in general, acceptable agreement. The discrepancies between the two comparative groups of data, the numerical model results and the data obtained from Braida and Ong (2000), for the two types of silica sand are expected due to uncertainties in the measured quantities obtained by Braida and Ong (2000) and the simplifying assumptions in the numerical solution in addition to the computational errors.
Table 1 Parameters used by Braida and Ong (2000) Experiment number 1 2
Soil Medium sand (dp50 ¼ 0.305 mm) Fine sand (dp50 ¼ 0.168 mm)
e 0.37 0.4
t 0.51 0.47
kL (cm/min) 3
1.16 10 1.23 103
kdiss (cm/min) 0.227 0.0041
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Fig. 2. Comparison of the present model results of theoretical concentration distribution with experimental data obtained from Braida and Ong (2000) through contaminated soil of (dp50 ¼ 0.305 mm) under aeration rate of 27.5 mL/min after 24, 48 and 72 h.
2.4. Numerical model results Two-dimensional isoconcentration lines of benzene for the numerical model runs were drawn. By assuming a benzene source with a concentration equal to the benzene solubility, the software used a Linear Variogram Kriging Procedure and the estimated concentration from the numerical model to draw the isoconcentration lines. The isoconcentration lines for benzene through the contaminated soil of mean particle size 0.305 mm at an aeration rate of 27.5 mL/min at 24, 48, and 72 h are presented in Fig. 3(a–c). A lateral symmetrical diffusion of benzene from the NAPL can be observed. It can be seen that the isoconcentration lines through the contaminated soil get wider with the increase in time. The 1 mg/L isoconcentration line of the plume extends further in both the lateral and vertical directions after 72 h than at 48 and 24 h. 3. Experimental setup A schematic description of the experimental test rig is shown in Fig. 4. The airflow discharged from the blower is controlled by a by-pass system via control valves. The air is then passed through an air filter, which is fixed inside the
main pipe. The filtered air is then passed to the electric heating system and finally to the contaminated soil which is located in the reactor test section. A slurry of the soil and water is packed into the soil reactor. The reactor consists of a box made of Plexiglas, which has dimensions of 0.20 m long, 0.11 m high, and 0.05 m wide. The design of the experimental set-up allows the air to pass over the saturated soil through an air channel. A sampling point for the measurement of the sparged VOC vapor concentration in the exhaust air is included. The employed soils were washed thoroughly and dried in an oven at 105 1C. The contaminated soils employed in the experimental study were fine sand and medium sand with an average particle size (dp50) of 0.278 and 0.39 mm, respectively. Three VOCs were used in the experimental study of the volatilization mass transfer process under air sparging conditions. The employed VOCs were benzene, toluene and m-xylene. A digital unidirectional hot-wire anemometer (Testo 435) was used to measure the air velocity with an accuracy of 0.01 m/s and the air temperature with an accuracy of 70.5 1C. The effluent air VOC concentration was measured by using a multi-gas monitor (Q-RAE PLUS— PGM-2000). The readings are displayed as a percentage of the LEL (lower explosive limit) or as a percentage by
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Fig. 3. Isoconcentration lines (mg/L) for benzene NAPL through contaminated soil of (dp50 ¼ 0.305 mm) under aeration rate of 27.5 mL/min after 24, 48 and 72 h.
The contaminant removal efficiency and the volatilization mass transfer coefficient can be calculated from the experimental data. The following equation represents a first-order kinetic process, which models the non-equilibrium mass transfer between air and water phases (Chao et al., 1998): _ aw ¼ kG Ai ðHC wi C a Þ. m Fig. 4. Schematic diagram of the test rig, 1—holder, 2—blower, 3—bypass valve, 4—control valve, 5—air filter, 6—electric heaters, 7— insulation, 8—thermostats, 9—orifice meter, 10—soil reactor, 11—stand, 12—U-tube manometer.
The air phase contaminant concentration is described by the following equation (Chao et al., 1998): Va
volume when the combustible gases go beyond the lower explosive range. A volume of 1.5 cm3 of the employed contaminant was injected into the soil reactor at approximately 20 mm below the air–water interface, 100 mm from the air inlet, and 25 mm from the front and back side walls. A set of experiments were conducted with the single-air channel setup for different soils (Medium and Fine), different types of VOCs (benzene, toluene, and m-xylene), different air velocities (from 1 to 6 cm/s) and different air inlet air temperatures (varied from 16 to 38 1C). During the experiments, air samples were taken from the effluent sampling port every 5–15 min and analyzed.
(5)
dC a _ a. ¼ kG Ai ðHC wi C a Þ QC dt
(6)
The air temperature was normalized using a reference temperature, Tref. Therefore, the obtained results are presented in the form of the normalized mean temperature, ym, which is defined as ym ¼
ðT ain þ T aout Þ=2 . T ref
(7)
The contaminant removal efficiency, Zrem is defined as follows:
Zrem ¼
Q_
Rt
C a dt 100ð%Þ. mc
0
(8)
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The contaminant mass removal is believed to be controlled by two distinct processes of advection and diffusion. Initially the mass of the removed contaminant is controlled by advection. Contaminant is removed by relatively quick volatilization from the air–water interface and subsequent advection by air, until the contaminant concentration in the air channel decreases below that in the aqueous phase. Then at that time, the diffusion process will begin to dominate the contaminant removal. These two regions of flow regimes are seen as initial peaks followed by asymptotic behavior in all of the obtained results for the contaminant removal curves. Fig. 5 shows the variation of benzene concentration in the effluent air against the elapsed time for two types of contaminated soils at 6 cm/s air velocity while the temperature of the air sparging over the contaminated soil was maintained approximately constant at 16 1C (ym ¼ 1). The removed amount of benzene from the contaminated soil that had a mean particle size of 0.39 mm was higher than that of 0.278 mm for approximately the first half hour of the experiment. This trend was then reversed for the remaining elapsed time of the experiment where the contaminated soil of mean particle size of 0.278 mm had higher benzene concentrations than that of mean particle size 0.39 mm. This indicates that contaminated soil that has a smaller mean particle size will delay the spreading of the dissolved benzene plume to the air–water interface and will in turn result in initially less volatilization at the air–water interface. The total benzene mass removal efficiency for medium grained contaminated soil of mean particle size 0.39 mm, after the elapsed time of the experiment (5 h), was about 75.65%. However for the finer contaminated soil of mean particle size 0.278 mm, the mass removed was 68.6%.
These results show that the long-term contaminant mass removal is dependent on the aqueous diffusion of the dissolved phase towards the air–water interface. Fig. 6 presents the variation of the contaminant concentration in the effluent air against elapsed time for benzene, toluene, and m-xylene in contaminated soil of mean particle size 0.39 mm at 6 cm/s air velocity while the temperature of the air sparging over the contaminated soil was maintained approximately constant at 16 1C (ym ¼ 1). Benzene has the lowest Henry’s constant but the highest solubility and diffusion coefficients in air and water in this group of VOCs. This explains the reason for the increased benzene concentration in the effluent air compared to toluene and m-xylene over the elapsed time of the experiment and consequently the total contaminant removal efficiency. The total benzene removal efficiency reached 75.65% while the total removal efficiencies for toluene and m-xylene were only 67% and 52.9%, respectively. These results clearly indicate that the volatilization mass transfer increases with the increase in the air and water diffusion coefficients of the VOCs. Furthermore, regarding the Henry’s law constant of the VOCs, an inversely proportional trend is observed. Fig. 7 demonstrates the variation of benzene concentration in the effluent air against elapsed time and the total benzene mass removal efficiency for 6, 2.5 and 1.5 cm/s air velocities in contaminated soil of mean particle size 0.39 mm while the temperature of the air sparging was maintained approximately constant at 16 1C (ym ¼ 1). It can be seen that as the air velocity increased, the benzene concentrations in the effluent air decreased. However, the air flowrates for these three velocities were not the same. Therefore, in order to investigate the effect of increasing air velocity and hence the air flowrates on the benzene removal, the removed mass of benzene was integrated to estimate the total benzene mass removal efficiencies. The total benzene removal efficiency for an air velocity of
Fig. 5. Effluent air benzene concentration against elapsed time for various types of contaminated soils (6 cm/s and ym ¼ 1).
Fig. 6. Effluent air VOC concentration against elapsed time in contaminated soil of dp50 ¼ 0.39 mm at 6 cm/s and ym ¼ 1.
4. Results and discusion 4.1. Experimental results
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Fig. 7. Effluent air benzene concentration against elapsed time for various air velocities (contaminated soil of (dp50 ¼ 0.39 mm) at ym ¼ 1).
1.5 cm/s (air flowrate ¼ 0.27 L/min) was only 34.5% and for an air velocity of 2.5 cm/s (air flowrate ¼ 0.46 L/min) it was 49.6% but for an air velocity of 6 cm/s (air flowrate ¼ 1 L/min) it was 75.65%. These results indicate that an increase in air flowrate produces an increase in the overall long term mass removal and this might be related to an increase in the mass transfer zone affected by the air sparging channel. Fig. 8 illustrates respectively the effluent air benzene concentration against elapsed time and the total benzene removal efficiency for various inlet air temperatures (16 1C (ym ¼ 1) and 24 1C (ym ¼ 1.019)). A sparging air velocity of 2.5 cm/s was attained over the contaminated soil of mean particle size 10.39 mm. It can be seen that initially, as the air temperature increased the benzene air phase concentration increased. This behavior is attributed to the change of the properties of the benzene at the air–water interface where increased air temperature increases the benzene air diffusion coefficient. However, after about 40 min from the beginning of benzene injection, the effluent air benzene concentration for (ym ¼ 1.019) was lower than that at (ym ¼ 1). However, the later change in the benzene concentration may have occurred because the rate of volatilization at the air–water interface is greater than the rate of diffusion in the aqueous phase, and this would in turn decrease the average water concentration at the air–water interface. The total benzene removal efficiency for a normalized mean temperature of (ym ¼ 1) was about 49.6% while for a normalized mean air temperature of (ym ¼ 1.019) it was 53.8%. It is clear that raising the inlet air temperature results in an improvement in the contaminant removal efficiency. This observation is repeated in Fig. 9 which shows the results of three air sparging runs at 6 cm/s air velocity in contaminated soil of mean particle size 0.39 mm. Concentrations of the sparged contaminant, benzene, in the effluent air, as a function of time for inlet air temperatures
Fig. 8. Effluent air benzene concentration against elapsed time for different normalized mean temperatures in contaminated soil of dp50 ¼ 0.39 mm and 2.5 cm/s.
Fig. 9. Effluent air benzene concentration against elapsed time for different normalized mean temperatures in contaminated soil of dp50 ¼ 0.39 mm and 6 cm/s.
of approximately 16 1C (ym ¼ 1), 33 1C (ym ¼ 1.037), and 38 1C (ym ¼ 1.051) are compared. It is clear that as the air temperature increased the benzene concentration in the effluent air increased for about 50 min from the beginning of benzene injection and then decreased laterally. This may occur for the reason given for the previous group of curves in Fig. 8. Furthermore, the aeration rate for this group of curves was higher than that of the previous one. The total benzene removal efficiency for the inlet air temperature of 16 1C and normalized mean temperature of (ym ¼ 1) was about 75.65% while for the inlet temperature of 33 1C and normalized mean temperature of (ym ¼ 1.037) it was 80.65% and for the inlet air temperature of 38 1C and normalized mean temperature of (ym ¼ 1.051) it was 82.4%. Therefore, to improve the contaminant removal efficiency, it is desirable to promote a
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relatively high-normalized mean temperature for the air sparging over the contaminated soil. 4.2. Air–water mass transfer correlation The gas phase mass transfer coefficient is calculated from Eq. (6). When the contaminant glob is injected close to the air–water interface, the dissolved phase concentration at the air–water interface, Cwm, is assumed to be slightly less than the value of the contaminant solubility concentration, Cs. The value of the contaminant concentration at the air water interface is assumed equal to the solubility concentration at a certain time, when the air phase concentration reaches its peak value. The estimated mass transfer coefficients, KG, are correlated with several dimensionless numbers. The dimensionless numbers used were the Sherwood number (Sh), Peclet number (Pe), Schmidt number (Sc) and several physical-chemical properties of VOCs and porous media. The definitions of the Sherwood number, Peclet number and Schmidt number are as follows: Sh ¼
K G dp50 , DG
(9)
Pe ¼
ua dp50 , DG
(10)
n . DG
(11)
Sc ¼
Fig. 10. Comparison of experimentally determined Sherwood numbers with predicted Sherwood numbers.
4.3. Uncertainty analysis of experimental results
Both the Henry’s law constant and the normalized mean particle size are considered for the correlation. The normalized mean particle size is defined as d 0 ¼ dp50 =d m ,
(12)
where (dm ¼ 0.05 cm) is the mean grain size of medium sand. The effect of sparging air temperature is introduced in the correlation by the normalized mean temperature, ym. The empirical dimensionless correlation may be presented as b
Sh ¼ b0 Peb1 Scb2 d 0 3 H b4 ybm5 ,
(13)
where b0, b1, b2, b3, b4 and b5 ¼ constants. The parameters bi are estimated by stepwise multiple regression analysis to obtain the best fit parameters for the log-linearized form of Eq. (13). The best fit correlation (R2 ¼ 0.98) is 1:133 2:32 Sh ¼ 6:2E 4Pe0:96 Sc0:04 d 1:03 ym . 0 H
(14)
Eq. (14) shows that mass transfer is affected by the physical properties of the contaminated soil such as the particle size, air flowrate, the diffusivity of the VOCs, sparging air temperature and the volatility of the VOCs as represented by the dimensionless Henry’s law constant. Fig. 10 presents a comparison of experimentally determined Sherwood numbers with Sherwood numbers predicted by the empirical formula. As illustrated in Fig. 10, the predictions of the correlation show good agreement with the experimentally determined Sherwood numbers.
Eq. (8) was used to determine the contaminant removal efficiency, Zrem . The contaminant removal efficiency is a function of the initial mass of injected contaminant, the aeration rate—which depends on the measured air velocity and the diameter of the pipe at the measuring point—and the contaminant concentration in the effluent air which is based on the LEL reading of the Q-RAE PLUS multi-gas monitor: Zrem ¼ f ðmc; u; d 21 ; CaÞ.
(15)
The uncertainty of the contaminant removal efficiency is equal to the square root of the sum of the squares of the uncertainties of the separated terms (Holman, 1986): oZrem
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi s 2 2 2 2ffi qZrem qZrem qZrem qZrem omc þ ou þ ¼ od 1 þ oC a . qmc qu qd 1 qC a
(16) Table 2 summarizes the expected individual uncertainties of the measured quantities: From Eq. (16), the uncertainty of the contaminant removal efficiency could be written as sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi homci2 houi2 od 2 oC 2 oZrem 1 a . (17) ¼ þ þ 2 þ mc u Zrem d1 Ca Substituting the individual expected uncertainties of the measured quantities in Eq. (17) yields that the systematic uncertainty in the contaminant removal efficiency will be not greater than about 71.953%.
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Table 2 Expected accuracy of the measured quantities Measured quantity
Expected accuracy
Initial mass of injected contaminant, mc Sparging air velocity, u Pipe diameter at the measuring point, d1 Air phase contaminant concentration, Ca
71.67% 70.025% 70.08% 71%
4.4. Theoretical results The effect of the normalized mean air temperature on the transient behavior of the dissolved NAPL concentration through the water-saturated soil was studied theoretically. This was achieved by using the estimated volatilization mass transfer coefficient, which was predicted from the experimental work, with the theoretical model. Theoretical study was conducted to investigate the benzene NAPL concentration through the saturated silica sand of mean particle size diameter 0.39 mm. An aeration rate of 27.51 mL/min was employed for different normalized mean air temperatures. The dissolution mass transfer coefficient was used from the literature and was equal to 0.227 cm/min for the current studied conditions. Fig. 11 presents the effect of normalized mean air temperature on the benzene concentrations at the air–water interface (z ¼ 0 cm) through silica sand of dp50 ¼ 0.39 mm under an aeration rate of 27.5 mL/min after 24 h for normalized mean air temperatures of 1, 1.05, 1.1, 1.15 and 1.2. It could be noticed that the changes in the benzene concentrations for different normalized mean air temperatures are concentrated at x ¼ 4.5 cm to x ¼ 12.5 cm. In addition, the benzene concentrations are considered to be symmetrical about the vertical plane of (x ¼ 8.5 cm) which is the vertical plane of the injection of the NAPL. For an inlet temperature of the sparging air equal to the reference temperature of 16 oC (ym ¼ 1), the maximum recorded concentration was 54.7 mg/L while for an inlet temperature of 80 1C (ym ¼ 1.2), the maximum concentration of benzene was 37.8 mg/L. For a horizontal plane of (z ¼ 0.25 cm), Fig. 12 presents the effect of normalized mean air temperatures of 1, 1.05, 1.1, 1.15 and 1.2 on the benzene concentration through silica sand of (dp50 ¼ 0.39 mm) with an aeration rate of 27.5 mL/min after 24 h from the beginning of the injection of the NAPL. Again, it could be noticed that the changes in benzene concentrations for different normalized mean air temperatures are concentrated at x ¼ 4.5 cm to x ¼ 12.5 cm. Also, the distribution of benzene concentrations is considered to be symmetrical about the vertical plane of NAPL injection (x ¼ t8.5 cm). For an inlet temperature of the sparging air equal to the reference temperature of 16 1C (ym ¼ 1), the maximum benzene concentration was 181 mg/ L while for an inlet temperature of 80 1C (ym ¼ 1.2) the maximum achieved concentration of dissolved benzene was 168 mg/L.
Fig. 11. The effect of normalized mean air temperature on the benzene concentration for (z ¼ 0 cm) at 24 h (Silica sand of (dp50 ¼ 0.39 mm) and aeration rate of 27.5 mL/min).
Fig. 12. The effect of normalized mean air temperature on the benzene concentration for (z ¼ 0.25 cm) at 24 h (Silica sand of (dp50 ¼ 0.39 mm), and aeration rate of 27.5 mL/min).
The benzene concentrations for the planes (x ¼ 8.5 and 6 cm) through silica sand of (dp50 ¼ 0.39 mm) with an aeration rate of 27.5 mL/min after 24 h for normalized mean air temperatures of 1, 1.05, 1.1, 1.15 and 1.2 are presented in Figs. 13 and 14 respectively. Clearly, the effect of normalized mean air temperature on the distribution of the dissolved benzene concentrations for these planes gets lower with the increase in depth into the saturated soil. In Fig. 13, for (x ¼ 8.5 cm), the benzene concentrations are approximately similar below the horizontal plane of (z ¼ 1 cm). But for (x ¼ 6 cm) as presented in Fig. 14, the benzene concentrations are approximately similar below the horizontal plane of (z ¼ 1.75 cm). This means that for the horizontal planes in the zone affected by the heated air, the increase of sparging air temperature has more effect for points far from the point of injection of the NAPL glob than the other points near it. This may happen
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taminated soil under different hot air sparging conditions for different NAPLs and soil properties. The conclusions are as follows:
Fig. 13. The effect of normalized mean air temperature on the benzene concentration for (x ¼ 8.5 cm) at 24 h (Silica sand of (dp50 ¼ 0.39 mm) and aeration rate of 27.5 mL/min).
The long-term mass removal for a glop of NAPL located close to an air channel was dependant on the aqueous diffusion of the dissolved phase towards the air–water interface which in turns increases with the increase in the mean particle size of the contaminated soil. An increase in air flowrate produces an increase in the overall mass removal and this might be related to an increase of the mass transfer zone affected by the air sparging channel. The volatilization mass transfer increased with the increase of the air and water diffusion coefficients of the VOCs. With regard to the Henry’s law constant of the VOCs, an inversely proportional trend was obtained. Using hot sparging air through the single air channel setup provided higher contaminant removal efficiencies, as deduced from the experimental study, by about 9%. Promoting a relatively high-normalized mean temperature for the air sparging over the contaminated soil improved the contaminant removal efficiency as a result of enhancing the volatilization mass transfer process. This would, in turn, affect the spreading of the dissolved NAPL plume through the mass transfer zone affected by the sparging air.
References
Fig. 14. The effect of normalized mean air temperature on the benzene concentration for (x ¼ 6 cm) at 24 h (Silica sand of (dp50 ¼ 0.39 mm) and aeration rate of 27.5 mL/min).
because the benzene diffusion from the NAPL plume dominates over the volatilization mass transfer process resulting from the sparging air for the neighborhood close to the NAPL glob. The above results show that heating the sparging air affects the spreading of the dissolved NAPL plume through the saturated contaminated soil. This behavior seems to be in agreement with the experimental study where promoting a relatively high normalized mean temperature for the sparging air over the contaminated soil improves the contaminant removal efficiency. 5. Conculsions Experimental and theoretical investigations were conducted for predicting the dynamic behavior of the contaminant concentration through water saturated con-
Ahlfeld, D.P., Dahmani, A., Ji, J.W., 1994. A conceptual model of field behavior of air sparging and its implications. GWMR, pp. 132–139. Benner, M.L., Stanford, S.M., Lee, L.S., Mohtar, R.H., 2000. Field and numerical analysis of in-situ air sparging: a case study. Journal of Hazardous Materials 72, 217–236. Braida, W., Ong, S.K., 2000. Influence of porous media and airflow rate on the fate of NAPLs under Air Sparging. Transport in porous media 38, 29–42. Chao, K., Ong, S.K., Protopapas, A., 1998. Water-to-air mass transfer of VOCs: laboratory scale air sparging system. ASCE. Journal of environmental engineering, 124 (11), 1054–1060. Chrysikopoulos, C.V., Kim, T., 2000. Local mass transfer correlations for nonaqueous phase liquid pool dissolution in saturated porous media. Transport in Porous Media 38, 167–187. Chrysikopoulos, C.V., Hsuan, P., Fyrillas, M., 2002. Bootstrap estimation of the mass transfer coefficient of a dissolving nonaqueous phase liquid pool in porous media. Water Resources Research 38 (3). Croft, D., Lilley, D., 1977. Heat Transfer Calculations Using Finite Difference Equations. Applied Science Publishers LTD, London. Fisher, C.L., Schmitter, R.D., Lane, E.O., 1999. Manufactured Gas Disposal Report Manufactured Gas Plants: The Environmental Legacy. George institute of technology, Nov., Atlanta, GA. Ghoshal, S., Luthy, R.G., 1998. Biodegradation kinetics of naphthalene in non aqueous phase liquid water mixed batch systems: comparison of model predictions and experimental results. Biotechnology and Bioengineering 57 (3), 356–366. Held, R.J., Celia, M.A., 2001. Pore-scale modeling and upscaling of nonaqueous phase liquid mass transfer. Water Resources Research 37 (3), 539–549. Holman, J.P., 1986. Experimental Methods for Engineers. McGraw-Hill, New York.
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Hussein, M., 1997. Impact of ground-water contamination on the Great Miami River basin. Ph.D. Thesis, Ohio State University. Hussien, M., 1999. Development of a combined analytical/semi-analytical approach for simulating surface flow of petroleum. technical report. Illangasekare, T.H., Saenton, S., Saba, T.A., Willson, C.S., 2000. Upscaling of NAPL dissolution from entrapped sources: Implications on End-points for risk assessment. In: Johnson, C.D. (Ed.), Proceedings the 2000 Contaminated Site Remediation Conference: From Source Zones to Ecosystems, Centre of groundwater studies, Melbourne, Vectoria, Australia, Dec., vol. 2, pp. 605–612. Imhoff, P.T., Frizzell, A., Miller, C.T., 1995. An evaluation of thermal effects on the dissolution of a nonaqueous phase liquid in porous media. Center for Multiphase Research News 2 (1), 2–5. Ji, W., Dahmani, A., Ahlfeld, D.P., Lin, J.D., Hill, E., 1993. Laboratory study of air sparging: air flow visualization. Ground Water Monitoring and Remediation 13 (4), 115–126. Johnson, P.C., 1998. Assessment of the contribution of volatilization and biodegradation to in situ air sparging performance. Environmental Science and Technology 13 (4), 115–126. Kueper, B.H., Frind, E., 1989. The Behavior of Dense non Aqueous Phase Liquids in Heterogeneous Porous Media, 1: Model Development, Verification and Validation. Waterloo Center for Groundwater Research, University of Waterloo, Canada. Mohtar, R.H., Segerlind, L.J., Wallace, R.B., 1996. Finite element analysis for air sparging in porous media. Fluid/Particle separation Journal 9(3). Okeson, S., Illangasekare, T.H., Szlag, D.C., Ewing, J., 1997. Modeling of dissolution transport of nonaqueous phase liquid wastes in hetero-
geneous aquifers. Proceedings of the 10th Annual Conference on Hazardous Waste Research, 1997, pp. 146–152. Rahbeh, M., Mohtar, R., 2001. The influence of heterogeneity and air channelization on contaminant removal by air sparging. ASAE Meeting Paper No. 013151. Sacremento, ASAE,CA. Reddy, K.R., Adams, J.A., 1998. System effects on benzene removal from saturated soils and ground water using air sparging. ASCE Journal of Environmental Engineering 124 (3), 288–299. Reddy, K.R., Adams, J.A., Richardson, C., 1999. Potential technologies for remediation of brownfields. ASCE Practice Periodical of Hazardous, Toxic, and Radioactive Waste Management 3 (2), 61–68. Semer, R., Reddy, K.R., 1998. Mechanisms controlling toluene removal from saturated soils during in situ air sparging. Journal of Hazardous Materials 57 (1–3), 209–230. Sprague, N., Delahaye, A., 1996. Air sparging (http://www.ce.vt.edu/ programarea-areas/environmental/teach/gwprimer/airsparg2/airsparg. html). Zheng, C., Bennett, G.D., 1995. Applied Contaminant Transport Modeling. Van Nostrand Reinhold, New York.
Further reading Julio, S., Drucker, A.S., 2000. Air sparging remediation: A study on heterogeneity and air mobility reduction. Proceedings of the 2000 Conference on Hazardous Waste Research.
Journal of Environmental Management 83 (2007) 339–350 www.elsevier.com/locate/jenvman
Remediation of saturated soil contaminated with petroleum products using air sparging with thermal enhancement A.M.I. Mohamed, Nabil El-menshawy, Amany M. Saif Mechanical Power Department, Faculty of Engineering, Suez Canal University, Egypt Received 18 April 2005; received in revised form 3 April 2006; accepted 4 April 2006 Available online 17 July 2006
Abstract Pollutants in the form of non-aqueous phase liquids (NAPLs), such as petroleum products, pose a serious threat to the soil and groundwater. A mathematical model was derived to study the unsteady pollutant concentrations through water saturated contaminated soil under air sparging conditions for different NAPLs and soil properties. The comparison between the numerical model results and the published experimental results showed acceptable agreement. Furthermore, an experimental study was conducted to remove NAPLs from the contaminated soil using the sparging air technique, considering the sparging air velocity, air temperature, soil grain size and different contaminant properties. This study showed that sparging air at ambient temperature through the contaminated soil can remove NAPLs, however, employing hot air sparging can provide higher contaminant removal efficiency, by about 9%. An empirical correlation for the volatilization mass transfer coefficient was developed from the experimental results. The dimensionless numbers used were Sherwood number (Sh), Peclet number (Pe), Schmidt number (Sc) and several physical-chemical properties of VOCs and porous media. Finally, the estimated volatilization mass transfer coefficient was used for calculation of the influence of heated sparging air on the spreading of the NAPL plume through the contaminated soil. r 2006 Elsevier Ltd. All rights reserved. Keywords: NAPLs; Air sparging; Volatilization mass transfer coefficient; Soil
1. Introduction Non-aqueous phase liquids (NAPLs) pose a significant threat to ground water resources. When NAPLs infiltrate to the subsurface they descend as an immiscible phase. In cases where of the spilled quantity exceeds the retention capacity of the ground water saturated zone; the NAPLs will reach the capillary fringe. A NAPL less dense than water (LNAPL) will form pools at the water table, while a more dense one (DNAPL) will move through the saturated zone, spreading along the less permeable layers and leaving behind a portion of its volume as immobilized pockets of liquid called residual saturation (Okeson et al., 1997). In the case of both DNAPL and LNAPL, pumping to remove free product within a highly NAPL saturated lens cannot completely recover the NAPL. With the rising of the water table or DNAPL lens migration, NAPL will Corresponding author. Tel.: +20 0 10 1597112; fax: +20 0 66 3400936.
E-mail address: [email protected] (A.M.I. Mohamed). 0301-4797/$ - see front matter r 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.jenvman.2006.04.005
become trapped during pumping as a discontinuous residual. Entrapped NAPLs act as long-term sources of groundwater contamination, (Fisher et al., 1999; Sprague and Delahaye, 1996; Held and Celia, 2001). The present research work aims at the enhancement of the air sparging remedial technology. Air sparging is a costeffective, time-efficient system for the remediation of volatile and/or biodegradable contaminants. This technique involves introducing forced air into the saturated zone of an aquifer to encourage volatilization of contaminants into the unsaturated zone where the contaminants can then be removed with another complementary technology such as soil vapor extraction (SVE), bioventing, horizontal wells, or heating (Sprague and Delahaye, 1996; Reddy et al., 1999). The airflow behavior induced by air sparging is typically characterized by a conical air plume, often known as the radius of influence (Johnson, 1998; Mohtar et al., 1996). Ji et al. (1993) visualized the steady state air distribution patterns using a thin Plexiglas tank with uniform lighting
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Nomenclature A a C Cs D dp d0 d1 H h K kL kG ms _ m Pe Q Sc Sh T t UC u Va
surface area, m2 specific interfacial area, m2/m3 concentration, mg/cm3 aqueous saturation concentration, mg/cm3 molecular diffusion coefficient, cm2/s particle diameter of the soil, mm normalized mean particle size pipe diameter, ‘mm dimensionless Henry’s constant Henry’s constant, atm.m3/mol permeability, mm2 liquid phase volatilization mass transfer coefficient, cm/min gas phase volatilization mass transfer coefficient, cm/min initial mass of VOC injected into the employed soil rate of mass transferred, mg/min Peclet number aeration rate, L/min Schmidt number Sherwood number temperature, K time, s uniformity coefficient of the porous media air velocity, cm/s air phase volume, cm3
behind the tank and glass beads as porous media. They observed two patterns of airflow in soils. The first pattern was observed for medium to coarse grained media where the airflow is characterized by a plume of discrete air bubbles. The second pattern describes the airflow regime for coarse to fine grained media that resemble the textures of sand, silts and clays of natural aquifer material. This flow regime was dominated by channel flow where air plumes are formed from discrete and continuous air channels. As the injection rate increases air channels increase in number and grow into a condensed continuous cone-shape cavity. Braida and Ong (2000) conducted experiments using a single air channel setup to study the influence of porous media properties and air velocity on the fate of NAPLs under air sparging conditions. Their study showed that the presence of advective airflow in air channels controlled the spreading of the dissolved phase but the overall removal efficiency was independent of the air flowrate. In addition, they noted that the removal efficiencies and dissolution rates of the NAPL were strongly affected by the mean particle size of the porous media during air sparging. This agrees with the investigations made by Reddy and Adams (1998). They performed a series of one dimensional column experiments to study the effects of soil type, air injection mode, and the synergistic effects of co-
x z X Z
distance in x-dir., cm depth in z-dir., cm soil reactor width, cm soil reactor depth, cm
Greek letters Zrem l t e n ym o
The contaminant removal efficiency weight factor for the finite difference technique tortuosity factor of the porous media porosity of the porous media kinematic viscosity, cm2/s normalized mean temperature uncertainty of measured or estimated values
Subscripts a diff diss i in G L NAPL out ref w
air phase diffusion dissolution interfacial inlet gas phase liquid phase non-aqueous phase liquid outlet reference water phase
contaminants on air sparging removal efficiency. They found that there is a threshold value for the effective particle size (dp10), which is equal to 0.2 mm; above this threshold value, the rate of removal is linearly proportional to the (dp10) value; while below this value, there is a drastic increase in the time required for contaminant removal. Additionally, they found that the pulsed air injection mode has no advantage over continuous injection for coarse sand; however, pulsed air injection led to substantial reductions in system operating time for fine sand. Also they observed a slight increase in removal rate when benzene and toluene coexisted in the test soil compared to when they existed alone. Chao et al. (1998) developed non-equilibrium water-toair mass transfer experiments for six volatile organic compounds during air sparging in soil columns packed with coarse, medium, or fine sand or glass beads. They performed a numerical study and assumed that the concentration in the bulk phase remained constant due to slow diffusion of VOCs in the aqueous phase to the air–water interface as compared to the rapid volatilization of VOCs at the air–water interface. Therefore, they modeled the interface mass transfer alone. At an in-situ air sparging remediation site contaminated through the spillage of a LNAPL waste, the influence of the system design parameters in terms of contaminant
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removal time was reported by Benner et al. (2000). They suggested that only the type of sparging operation (i.e. pulsed or continuous) was significant in terms of total contaminant removal time, while both the sparging operation and air injection rate were significant in terms of removal of critical xylene species. However, the contaminants within the radius of influence will not be removed with equal efficiencies due to the natural inherited heterogeneity of the porous medium that yields non-uniform and asymmetrical air plumes (Ahlfeld et al., 1994). Rahbeh and Mohtar (2001) studied the influence of porous media heterogeneity and air channelization on contaminant removal by air sparging. Their results showed that the contaminant removal is proportional to channel spacing, and controlled by the process of diffusion between air channels. On the other hand, the contaminant removal is inversely proportional to the spatial variability of the flow field. Many investigators such as Hussein (1997, 1999), Chrysikopoulos and Kim (2000), Chrysikopoulos et al. (2002), Ghoshal and Luthy (1998), and Illangasekare et al. (2000) have demonstrated the complex flow and transport behavior of non-aqueous phase liquids in porous media. Kueper and Frind (1989) developed a two-dimensional vertical section finite difference model to study the simultaneous movement of a dense, non-aqueous phase liquid and water under the water table in heterogeneous porous media. The model was validated against a parallel plate laboratory experiment involving the infiltration of tetrachloroethylene into a heterogeneous sand pack initially saturated with water. Imhoff et al. (1995) investigated experimentally the hot water flooding effects on the remediation of porous media contaminated with tetrachloroethylene at residual saturation. Interfacial tension measurements indicated that there was no change in the tetrachloroethylene -aqueous interfacial tension over the temperature range examined in this study (10–40 1C). On the other hand, flushing with hot water increased the mass transfer rate coefficient by approximately a factor of two as the aqueous phase temperature was increased from 5 to 40 1C. Hot water flushing was suggested to be used before using air sparging remediation technology. The main objective of this work is to investigate numerically as well as experimentally the influence of soil gradation, aeration rate and sparging air temperature on the removal efficiency of NAPLs, such as petroleum products, from contaminated soil. Further, the effect of sparging air temperature on the fate of NAPLs is also investigated numerically.
by channel flow where air plumes are formed from discrete and continuous air channels. The principle mechanism of mass transfer behind in-situ air sparging technology is the volatilization of dissolved VOCs and NAPLs into the air phase. The single-air channel approach has been successfully used for providing information on contaminant removal occurring at the air-channel level during airsparging (Braida and Ong, 1998, 2000). Since a constant air–water interfacial area is available through this approach, it is convenient for studying the influence of soil gradation, aeration rate and sparging air temperature on the removal efficiency of NAPLs at the level of air-channels formed during in-situ sparging of clean air into the contaminated soil. The conceptual experimental set-up used in the current study is a two-dimensional dissolutiondiffusion-volatilization model shown schematically in Fig. 1. The model is designed for a thin air channel located above the water-saturated soil. The one component NAPL (source point) is injected into the reactor at the point (x0, z0). In the case of the NAPL–water interface it reaches equilibrium. Several mathematical models describing the dissolution of residual NAPLs in porous media employ the assumption that the dissolved concentration along the NAPL–water interface is equal to the solubility or aqueous saturation concentration Cs. The results from many previous experimental studies associated with residual NAPL dissolution support the applicability of this assumption (Chrysikopoulos and Kim, 2000). Then, the dissolved NAPL disperses through the saturated soil by molecular diffusion. When the dissolved NAPL molecules reach the plane of the air–water interface (at z ¼ 0), the volatilization of the dissolved contaminant occurs. Batch tests determined that the adsorption of organic contaminants onto the soil solids was negligible (Semer and Reddy, 1998). Further, due to the low organic carbon content, sorption of benzene is not considered in the formulation of the model. Mixing effects as a result of transfer of momentum from the air phase to the aqueous phase are negligible. Assuming stagnant conditions for the aqueous phase. The dissolved concentration along the NAPL–water interface is equal to the solubility or aqueous saturation concentration (Cs).
2. Mathematical formulation and numerical model 2.1. Mathematical formulation As mentioned by Ji et al. (1993), the steady state air distribution pattern for fine to coarse media is dominated
341
Fig. 1. Schematic diagram of the approach model.
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Considering the two-dimensional diffusion–dissolution equation (Braida and Ong, 2000) for any interior node in the reactor we obtain: 2 qC w q C w q2 C w ANAPL ¼ tD þ ðC w CsÞ, J kdiss qt qxx qzx V element (1) where J ¼ 1, in the elements where the NAPL is present, and 0 otherwise. Eq. (1) describes the two dimensional diffusion-dissolution of a contaminant through the water saturated contaminated soil. As shown in Fig. 1 the NAPL is injected at point (x0, z0), therefore, the injected NAPL will be assumed as a spherical glob of radius, r. The above equation is subject to the following boundary conditions. Considering Eq. (1), the initial conditions are: 9 C 0w ðx0 r; zÞ ¼ Cs = ; ðz0 rÞpzpðz0 þ rÞ C 0w ðx0 þ r; zÞ ¼ Cs ; 9 C 0w ðx; z0 rÞ ¼ Cs = ; ðx0 rÞpxpðx0 þ rÞ C 0w ðx; z0 þ rÞ ¼ Cs ; C 0w ðx; zÞ ¼ 0;
elsewhere;
ð2Þ
and the boundary conditions are: 9 qC tw ð0;zÞ ¼0= qx ¯ t 0; 0pzpZ qC tw ðX ;zÞ ; ¼ 0 qx o qC tw ðx;ZÞ ¼ 0 t 0; 0pxpX¯ qz
(3)
At the air–water interface, the volatilization of the dissolved NAPL (at z ¼ 0) will be as follows: qC tw ðx; 0Þ kL Ca ¼ C w ðx; 0Þ t40; 0pxpX¯ . (4) qz tD H
2.2. Numerical technique For solving the basic governing equations of the system introduced above, a finite-difference procedure has been used which is based on a method published by Zheng and Bennett (1995). An explicit-implicit Crank-Niclson form of the finite difference technique is used (Croft and Lilley, 1977). This method was found to be much more stable with a minimum round error compared with the other methods.
A regular grid and a Cartesian coordinate system were applied in the present study. The finite difference formulations were derived for each node of the finite difference mesh. This generates the matrix of the solution, which was solved iteratively to obtain the contaminant concentration distribution through the contaminated soil reactor. A computer program was developed to simulate the behavior of the time variant contaminant concentration distribution through the contaminated soil. The code was written in FORTRAN programming language. It consists of a main program and different subprograms for calculating the volatilization mass transfer coefficient and iterating the solution of the concentration distribution. 2.3. Model validation The numerical model results were validated against the results of two-dimensional sand pack experiments, which were conducted by Braida and Ong (2000) for the same boundary and physical conditions. Benzene was used as a NAPL while medium silica sand of (dp50 ¼ 0.305 mm, UC ¼ 1.41) and fine silica sand of (dp50 ¼ 0.168 mm, UC ¼ 1.64) were used as the contaminated soil. The dissolution mass transfer coefficient, kdiss, and the liquid phase volatilization mass transfer coefficient, kL, are taken from the reference experimental data (Braida and Ong, 2000). Table 1 contains the main operating conditions, which were used in the air sparging experiments for benzene NAPL with an aeration rate of 27.5 mL/min. A comparison between the predicted contaminant concentrations and experimental data obtained from Braida and Ong (2000) is demonstrated in Fig. 2(a–c) for 24, 48, and 72 h from the beginning of benzene injection in the medium silica sand composed of mean particle size of 0.305 mm under an aeration rate of 27.5 mL/min at the air–water interface. The maximum discrepancy between the present theoretical results and the available experimental data from Braida and Ong (2000) was about 20%. The comparison between the present numerical model results and the reference experimental results shows, in general, acceptable agreement. The discrepancies between the two comparative groups of data, the numerical model results and the data obtained from Braida and Ong (2000), for the two types of silica sand are expected due to uncertainties in the measured quantities obtained by Braida and Ong (2000) and the simplifying assumptions in the numerical solution in addition to the computational errors.
Table 1 Parameters used by Braida and Ong (2000) Experiment number 1 2
Soil Medium sand (dp50 ¼ 0.305 mm) Fine sand (dp50 ¼ 0.168 mm)
e 0.37 0.4
t 0.51 0.47
kL (cm/min) 3
1.16 10 1.23 103
kdiss (cm/min) 0.227 0.0041
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Fig. 2. Comparison of the present model results of theoretical concentration distribution with experimental data obtained from Braida and Ong (2000) through contaminated soil of (dp50 ¼ 0.305 mm) under aeration rate of 27.5 mL/min after 24, 48 and 72 h.
2.4. Numerical model results Two-dimensional isoconcentration lines of benzene for the numerical model runs were drawn. By assuming a benzene source with a concentration equal to the benzene solubility, the software used a Linear Variogram Kriging Procedure and the estimated concentration from the numerical model to draw the isoconcentration lines. The isoconcentration lines for benzene through the contaminated soil of mean particle size 0.305 mm at an aeration rate of 27.5 mL/min at 24, 48, and 72 h are presented in Fig. 3(a–c). A lateral symmetrical diffusion of benzene from the NAPL can be observed. It can be seen that the isoconcentration lines through the contaminated soil get wider with the increase in time. The 1 mg/L isoconcentration line of the plume extends further in both the lateral and vertical directions after 72 h than at 48 and 24 h. 3. Experimental setup A schematic description of the experimental test rig is shown in Fig. 4. The airflow discharged from the blower is controlled by a by-pass system via control valves. The air is then passed through an air filter, which is fixed inside the
main pipe. The filtered air is then passed to the electric heating system and finally to the contaminated soil which is located in the reactor test section. A slurry of the soil and water is packed into the soil reactor. The reactor consists of a box made of Plexiglas, which has dimensions of 0.20 m long, 0.11 m high, and 0.05 m wide. The design of the experimental set-up allows the air to pass over the saturated soil through an air channel. A sampling point for the measurement of the sparged VOC vapor concentration in the exhaust air is included. The employed soils were washed thoroughly and dried in an oven at 105 1C. The contaminated soils employed in the experimental study were fine sand and medium sand with an average particle size (dp50) of 0.278 and 0.39 mm, respectively. Three VOCs were used in the experimental study of the volatilization mass transfer process under air sparging conditions. The employed VOCs were benzene, toluene and m-xylene. A digital unidirectional hot-wire anemometer (Testo 435) was used to measure the air velocity with an accuracy of 0.01 m/s and the air temperature with an accuracy of 70.5 1C. The effluent air VOC concentration was measured by using a multi-gas monitor (Q-RAE PLUS— PGM-2000). The readings are displayed as a percentage of the LEL (lower explosive limit) or as a percentage by
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Fig. 3. Isoconcentration lines (mg/L) for benzene NAPL through contaminated soil of (dp50 ¼ 0.305 mm) under aeration rate of 27.5 mL/min after 24, 48 and 72 h.
The contaminant removal efficiency and the volatilization mass transfer coefficient can be calculated from the experimental data. The following equation represents a first-order kinetic process, which models the non-equilibrium mass transfer between air and water phases (Chao et al., 1998): _ aw ¼ kG Ai ðHC wi C a Þ. m Fig. 4. Schematic diagram of the test rig, 1—holder, 2—blower, 3—bypass valve, 4—control valve, 5—air filter, 6—electric heaters, 7— insulation, 8—thermostats, 9—orifice meter, 10—soil reactor, 11—stand, 12—U-tube manometer.
The air phase contaminant concentration is described by the following equation (Chao et al., 1998): Va
volume when the combustible gases go beyond the lower explosive range. A volume of 1.5 cm3 of the employed contaminant was injected into the soil reactor at approximately 20 mm below the air–water interface, 100 mm from the air inlet, and 25 mm from the front and back side walls. A set of experiments were conducted with the single-air channel setup for different soils (Medium and Fine), different types of VOCs (benzene, toluene, and m-xylene), different air velocities (from 1 to 6 cm/s) and different air inlet air temperatures (varied from 16 to 38 1C). During the experiments, air samples were taken from the effluent sampling port every 5–15 min and analyzed.
(5)
dC a _ a. ¼ kG Ai ðHC wi C a Þ QC dt
(6)
The air temperature was normalized using a reference temperature, Tref. Therefore, the obtained results are presented in the form of the normalized mean temperature, ym, which is defined as ym ¼
ðT ain þ T aout Þ=2 . T ref
(7)
The contaminant removal efficiency, Zrem is defined as follows:
Zrem ¼
Q_
Rt
C a dt 100ð%Þ. mc
0
(8)
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The contaminant mass removal is believed to be controlled by two distinct processes of advection and diffusion. Initially the mass of the removed contaminant is controlled by advection. Contaminant is removed by relatively quick volatilization from the air–water interface and subsequent advection by air, until the contaminant concentration in the air channel decreases below that in the aqueous phase. Then at that time, the diffusion process will begin to dominate the contaminant removal. These two regions of flow regimes are seen as initial peaks followed by asymptotic behavior in all of the obtained results for the contaminant removal curves. Fig. 5 shows the variation of benzene concentration in the effluent air against the elapsed time for two types of contaminated soils at 6 cm/s air velocity while the temperature of the air sparging over the contaminated soil was maintained approximately constant at 16 1C (ym ¼ 1). The removed amount of benzene from the contaminated soil that had a mean particle size of 0.39 mm was higher than that of 0.278 mm for approximately the first half hour of the experiment. This trend was then reversed for the remaining elapsed time of the experiment where the contaminated soil of mean particle size of 0.278 mm had higher benzene concentrations than that of mean particle size 0.39 mm. This indicates that contaminated soil that has a smaller mean particle size will delay the spreading of the dissolved benzene plume to the air–water interface and will in turn result in initially less volatilization at the air–water interface. The total benzene mass removal efficiency for medium grained contaminated soil of mean particle size 0.39 mm, after the elapsed time of the experiment (5 h), was about 75.65%. However for the finer contaminated soil of mean particle size 0.278 mm, the mass removed was 68.6%.
These results show that the long-term contaminant mass removal is dependent on the aqueous diffusion of the dissolved phase towards the air–water interface. Fig. 6 presents the variation of the contaminant concentration in the effluent air against elapsed time for benzene, toluene, and m-xylene in contaminated soil of mean particle size 0.39 mm at 6 cm/s air velocity while the temperature of the air sparging over the contaminated soil was maintained approximately constant at 16 1C (ym ¼ 1). Benzene has the lowest Henry’s constant but the highest solubility and diffusion coefficients in air and water in this group of VOCs. This explains the reason for the increased benzene concentration in the effluent air compared to toluene and m-xylene over the elapsed time of the experiment and consequently the total contaminant removal efficiency. The total benzene removal efficiency reached 75.65% while the total removal efficiencies for toluene and m-xylene were only 67% and 52.9%, respectively. These results clearly indicate that the volatilization mass transfer increases with the increase in the air and water diffusion coefficients of the VOCs. Furthermore, regarding the Henry’s law constant of the VOCs, an inversely proportional trend is observed. Fig. 7 demonstrates the variation of benzene concentration in the effluent air against elapsed time and the total benzene mass removal efficiency for 6, 2.5 and 1.5 cm/s air velocities in contaminated soil of mean particle size 0.39 mm while the temperature of the air sparging was maintained approximately constant at 16 1C (ym ¼ 1). It can be seen that as the air velocity increased, the benzene concentrations in the effluent air decreased. However, the air flowrates for these three velocities were not the same. Therefore, in order to investigate the effect of increasing air velocity and hence the air flowrates on the benzene removal, the removed mass of benzene was integrated to estimate the total benzene mass removal efficiencies. The total benzene removal efficiency for an air velocity of
Fig. 5. Effluent air benzene concentration against elapsed time for various types of contaminated soils (6 cm/s and ym ¼ 1).
Fig. 6. Effluent air VOC concentration against elapsed time in contaminated soil of dp50 ¼ 0.39 mm at 6 cm/s and ym ¼ 1.
4. Results and discusion 4.1. Experimental results
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Fig. 7. Effluent air benzene concentration against elapsed time for various air velocities (contaminated soil of (dp50 ¼ 0.39 mm) at ym ¼ 1).
1.5 cm/s (air flowrate ¼ 0.27 L/min) was only 34.5% and for an air velocity of 2.5 cm/s (air flowrate ¼ 0.46 L/min) it was 49.6% but for an air velocity of 6 cm/s (air flowrate ¼ 1 L/min) it was 75.65%. These results indicate that an increase in air flowrate produces an increase in the overall long term mass removal and this might be related to an increase in the mass transfer zone affected by the air sparging channel. Fig. 8 illustrates respectively the effluent air benzene concentration against elapsed time and the total benzene removal efficiency for various inlet air temperatures (16 1C (ym ¼ 1) and 24 1C (ym ¼ 1.019)). A sparging air velocity of 2.5 cm/s was attained over the contaminated soil of mean particle size 10.39 mm. It can be seen that initially, as the air temperature increased the benzene air phase concentration increased. This behavior is attributed to the change of the properties of the benzene at the air–water interface where increased air temperature increases the benzene air diffusion coefficient. However, after about 40 min from the beginning of benzene injection, the effluent air benzene concentration for (ym ¼ 1.019) was lower than that at (ym ¼ 1). However, the later change in the benzene concentration may have occurred because the rate of volatilization at the air–water interface is greater than the rate of diffusion in the aqueous phase, and this would in turn decrease the average water concentration at the air–water interface. The total benzene removal efficiency for a normalized mean temperature of (ym ¼ 1) was about 49.6% while for a normalized mean air temperature of (ym ¼ 1.019) it was 53.8%. It is clear that raising the inlet air temperature results in an improvement in the contaminant removal efficiency. This observation is repeated in Fig. 9 which shows the results of three air sparging runs at 6 cm/s air velocity in contaminated soil of mean particle size 0.39 mm. Concentrations of the sparged contaminant, benzene, in the effluent air, as a function of time for inlet air temperatures
Fig. 8. Effluent air benzene concentration against elapsed time for different normalized mean temperatures in contaminated soil of dp50 ¼ 0.39 mm and 2.5 cm/s.
Fig. 9. Effluent air benzene concentration against elapsed time for different normalized mean temperatures in contaminated soil of dp50 ¼ 0.39 mm and 6 cm/s.
of approximately 16 1C (ym ¼ 1), 33 1C (ym ¼ 1.037), and 38 1C (ym ¼ 1.051) are compared. It is clear that as the air temperature increased the benzene concentration in the effluent air increased for about 50 min from the beginning of benzene injection and then decreased laterally. This may occur for the reason given for the previous group of curves in Fig. 8. Furthermore, the aeration rate for this group of curves was higher than that of the previous one. The total benzene removal efficiency for the inlet air temperature of 16 1C and normalized mean temperature of (ym ¼ 1) was about 75.65% while for the inlet temperature of 33 1C and normalized mean temperature of (ym ¼ 1.037) it was 80.65% and for the inlet air temperature of 38 1C and normalized mean temperature of (ym ¼ 1.051) it was 82.4%. Therefore, to improve the contaminant removal efficiency, it is desirable to promote a
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relatively high-normalized mean temperature for the air sparging over the contaminated soil. 4.2. Air–water mass transfer correlation The gas phase mass transfer coefficient is calculated from Eq. (6). When the contaminant glob is injected close to the air–water interface, the dissolved phase concentration at the air–water interface, Cwm, is assumed to be slightly less than the value of the contaminant solubility concentration, Cs. The value of the contaminant concentration at the air water interface is assumed equal to the solubility concentration at a certain time, when the air phase concentration reaches its peak value. The estimated mass transfer coefficients, KG, are correlated with several dimensionless numbers. The dimensionless numbers used were the Sherwood number (Sh), Peclet number (Pe), Schmidt number (Sc) and several physical-chemical properties of VOCs and porous media. The definitions of the Sherwood number, Peclet number and Schmidt number are as follows: Sh ¼
K G dp50 , DG
(9)
Pe ¼
ua dp50 , DG
(10)
n . DG
(11)
Sc ¼
Fig. 10. Comparison of experimentally determined Sherwood numbers with predicted Sherwood numbers.
4.3. Uncertainty analysis of experimental results
Both the Henry’s law constant and the normalized mean particle size are considered for the correlation. The normalized mean particle size is defined as d 0 ¼ dp50 =d m ,
(12)
where (dm ¼ 0.05 cm) is the mean grain size of medium sand. The effect of sparging air temperature is introduced in the correlation by the normalized mean temperature, ym. The empirical dimensionless correlation may be presented as b
Sh ¼ b0 Peb1 Scb2 d 0 3 H b4 ybm5 ,
(13)
where b0, b1, b2, b3, b4 and b5 ¼ constants. The parameters bi are estimated by stepwise multiple regression analysis to obtain the best fit parameters for the log-linearized form of Eq. (13). The best fit correlation (R2 ¼ 0.98) is 1:133 2:32 Sh ¼ 6:2E 4Pe0:96 Sc0:04 d 1:03 ym . 0 H
(14)
Eq. (14) shows that mass transfer is affected by the physical properties of the contaminated soil such as the particle size, air flowrate, the diffusivity of the VOCs, sparging air temperature and the volatility of the VOCs as represented by the dimensionless Henry’s law constant. Fig. 10 presents a comparison of experimentally determined Sherwood numbers with Sherwood numbers predicted by the empirical formula. As illustrated in Fig. 10, the predictions of the correlation show good agreement with the experimentally determined Sherwood numbers.
Eq. (8) was used to determine the contaminant removal efficiency, Zrem . The contaminant removal efficiency is a function of the initial mass of injected contaminant, the aeration rate—which depends on the measured air velocity and the diameter of the pipe at the measuring point—and the contaminant concentration in the effluent air which is based on the LEL reading of the Q-RAE PLUS multi-gas monitor: Zrem ¼ f ðmc; u; d 21 ; CaÞ.
(15)
The uncertainty of the contaminant removal efficiency is equal to the square root of the sum of the squares of the uncertainties of the separated terms (Holman, 1986): oZrem
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi s 2 2 2 2ffi qZrem qZrem qZrem qZrem omc þ ou þ ¼ od 1 þ oC a . qmc qu qd 1 qC a
(16) Table 2 summarizes the expected individual uncertainties of the measured quantities: From Eq. (16), the uncertainty of the contaminant removal efficiency could be written as sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi homci2 houi2 od 2 oC 2 oZrem 1 a . (17) ¼ þ þ 2 þ mc u Zrem d1 Ca Substituting the individual expected uncertainties of the measured quantities in Eq. (17) yields that the systematic uncertainty in the contaminant removal efficiency will be not greater than about 71.953%.
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Table 2 Expected accuracy of the measured quantities Measured quantity
Expected accuracy
Initial mass of injected contaminant, mc Sparging air velocity, u Pipe diameter at the measuring point, d1 Air phase contaminant concentration, Ca
71.67% 70.025% 70.08% 71%
4.4. Theoretical results The effect of the normalized mean air temperature on the transient behavior of the dissolved NAPL concentration through the water-saturated soil was studied theoretically. This was achieved by using the estimated volatilization mass transfer coefficient, which was predicted from the experimental work, with the theoretical model. Theoretical study was conducted to investigate the benzene NAPL concentration through the saturated silica sand of mean particle size diameter 0.39 mm. An aeration rate of 27.51 mL/min was employed for different normalized mean air temperatures. The dissolution mass transfer coefficient was used from the literature and was equal to 0.227 cm/min for the current studied conditions. Fig. 11 presents the effect of normalized mean air temperature on the benzene concentrations at the air–water interface (z ¼ 0 cm) through silica sand of dp50 ¼ 0.39 mm under an aeration rate of 27.5 mL/min after 24 h for normalized mean air temperatures of 1, 1.05, 1.1, 1.15 and 1.2. It could be noticed that the changes in the benzene concentrations for different normalized mean air temperatures are concentrated at x ¼ 4.5 cm to x ¼ 12.5 cm. In addition, the benzene concentrations are considered to be symmetrical about the vertical plane of (x ¼ 8.5 cm) which is the vertical plane of the injection of the NAPL. For an inlet temperature of the sparging air equal to the reference temperature of 16 oC (ym ¼ 1), the maximum recorded concentration was 54.7 mg/L while for an inlet temperature of 80 1C (ym ¼ 1.2), the maximum concentration of benzene was 37.8 mg/L. For a horizontal plane of (z ¼ 0.25 cm), Fig. 12 presents the effect of normalized mean air temperatures of 1, 1.05, 1.1, 1.15 and 1.2 on the benzene concentration through silica sand of (dp50 ¼ 0.39 mm) with an aeration rate of 27.5 mL/min after 24 h from the beginning of the injection of the NAPL. Again, it could be noticed that the changes in benzene concentrations for different normalized mean air temperatures are concentrated at x ¼ 4.5 cm to x ¼ 12.5 cm. Also, the distribution of benzene concentrations is considered to be symmetrical about the vertical plane of NAPL injection (x ¼ t8.5 cm). For an inlet temperature of the sparging air equal to the reference temperature of 16 1C (ym ¼ 1), the maximum benzene concentration was 181 mg/ L while for an inlet temperature of 80 1C (ym ¼ 1.2) the maximum achieved concentration of dissolved benzene was 168 mg/L.
Fig. 11. The effect of normalized mean air temperature on the benzene concentration for (z ¼ 0 cm) at 24 h (Silica sand of (dp50 ¼ 0.39 mm) and aeration rate of 27.5 mL/min).
Fig. 12. The effect of normalized mean air temperature on the benzene concentration for (z ¼ 0.25 cm) at 24 h (Silica sand of (dp50 ¼ 0.39 mm), and aeration rate of 27.5 mL/min).
The benzene concentrations for the planes (x ¼ 8.5 and 6 cm) through silica sand of (dp50 ¼ 0.39 mm) with an aeration rate of 27.5 mL/min after 24 h for normalized mean air temperatures of 1, 1.05, 1.1, 1.15 and 1.2 are presented in Figs. 13 and 14 respectively. Clearly, the effect of normalized mean air temperature on the distribution of the dissolved benzene concentrations for these planes gets lower with the increase in depth into the saturated soil. In Fig. 13, for (x ¼ 8.5 cm), the benzene concentrations are approximately similar below the horizontal plane of (z ¼ 1 cm). But for (x ¼ 6 cm) as presented in Fig. 14, the benzene concentrations are approximately similar below the horizontal plane of (z ¼ 1.75 cm). This means that for the horizontal planes in the zone affected by the heated air, the increase of sparging air temperature has more effect for points far from the point of injection of the NAPL glob than the other points near it. This may happen
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taminated soil under different hot air sparging conditions for different NAPLs and soil properties. The conclusions are as follows:
Fig. 13. The effect of normalized mean air temperature on the benzene concentration for (x ¼ 8.5 cm) at 24 h (Silica sand of (dp50 ¼ 0.39 mm) and aeration rate of 27.5 mL/min).
The long-term mass removal for a glop of NAPL located close to an air channel was dependant on the aqueous diffusion of the dissolved phase towards the air–water interface which in turns increases with the increase in the mean particle size of the contaminated soil. An increase in air flowrate produces an increase in the overall mass removal and this might be related to an increase of the mass transfer zone affected by the air sparging channel. The volatilization mass transfer increased with the increase of the air and water diffusion coefficients of the VOCs. With regard to the Henry’s law constant of the VOCs, an inversely proportional trend was obtained. Using hot sparging air through the single air channel setup provided higher contaminant removal efficiencies, as deduced from the experimental study, by about 9%. Promoting a relatively high-normalized mean temperature for the air sparging over the contaminated soil improved the contaminant removal efficiency as a result of enhancing the volatilization mass transfer process. This would, in turn, affect the spreading of the dissolved NAPL plume through the mass transfer zone affected by the sparging air.
References
Fig. 14. The effect of normalized mean air temperature on the benzene concentration for (x ¼ 6 cm) at 24 h (Silica sand of (dp50 ¼ 0.39 mm) and aeration rate of 27.5 mL/min).
because the benzene diffusion from the NAPL plume dominates over the volatilization mass transfer process resulting from the sparging air for the neighborhood close to the NAPL glob. The above results show that heating the sparging air affects the spreading of the dissolved NAPL plume through the saturated contaminated soil. This behavior seems to be in agreement with the experimental study where promoting a relatively high normalized mean temperature for the sparging air over the contaminated soil improves the contaminant removal efficiency. 5. Conculsions Experimental and theoretical investigations were conducted for predicting the dynamic behavior of the contaminant concentration through water saturated con-
Ahlfeld, D.P., Dahmani, A., Ji, J.W., 1994. A conceptual model of field behavior of air sparging and its implications. GWMR, pp. 132–139. Benner, M.L., Stanford, S.M., Lee, L.S., Mohtar, R.H., 2000. Field and numerical analysis of in-situ air sparging: a case study. Journal of Hazardous Materials 72, 217–236. Braida, W., Ong, S.K., 2000. Influence of porous media and airflow rate on the fate of NAPLs under Air Sparging. Transport in porous media 38, 29–42. Chao, K., Ong, S.K., Protopapas, A., 1998. Water-to-air mass transfer of VOCs: laboratory scale air sparging system. ASCE. Journal of environmental engineering, 124 (11), 1054–1060. Chrysikopoulos, C.V., Kim, T., 2000. Local mass transfer correlations for nonaqueous phase liquid pool dissolution in saturated porous media. Transport in Porous Media 38, 167–187. Chrysikopoulos, C.V., Hsuan, P., Fyrillas, M., 2002. Bootstrap estimation of the mass transfer coefficient of a dissolving nonaqueous phase liquid pool in porous media. Water Resources Research 38 (3). Croft, D., Lilley, D., 1977. Heat Transfer Calculations Using Finite Difference Equations. Applied Science Publishers LTD, London. Fisher, C.L., Schmitter, R.D., Lane, E.O., 1999. Manufactured Gas Disposal Report Manufactured Gas Plants: The Environmental Legacy. George institute of technology, Nov., Atlanta, GA. Ghoshal, S., Luthy, R.G., 1998. Biodegradation kinetics of naphthalene in non aqueous phase liquid water mixed batch systems: comparison of model predictions and experimental results. Biotechnology and Bioengineering 57 (3), 356–366. Held, R.J., Celia, M.A., 2001. Pore-scale modeling and upscaling of nonaqueous phase liquid mass transfer. Water Resources Research 37 (3), 539–549. Holman, J.P., 1986. Experimental Methods for Engineers. McGraw-Hill, New York.
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Hussein, M., 1997. Impact of ground-water contamination on the Great Miami River basin. Ph.D. Thesis, Ohio State University. Hussien, M., 1999. Development of a combined analytical/semi-analytical approach for simulating surface flow of petroleum. technical report. Illangasekare, T.H., Saenton, S., Saba, T.A., Willson, C.S., 2000. Upscaling of NAPL dissolution from entrapped sources: Implications on End-points for risk assessment. In: Johnson, C.D. (Ed.), Proceedings the 2000 Contaminated Site Remediation Conference: From Source Zones to Ecosystems, Centre of groundwater studies, Melbourne, Vectoria, Australia, Dec., vol. 2, pp. 605–612. Imhoff, P.T., Frizzell, A., Miller, C.T., 1995. An evaluation of thermal effects on the dissolution of a nonaqueous phase liquid in porous media. Center for Multiphase Research News 2 (1), 2–5. Ji, W., Dahmani, A., Ahlfeld, D.P., Lin, J.D., Hill, E., 1993. Laboratory study of air sparging: air flow visualization. Ground Water Monitoring and Remediation 13 (4), 115–126. Johnson, P.C., 1998. Assessment of the contribution of volatilization and biodegradation to in situ air sparging performance. Environmental Science and Technology 13 (4), 115–126. Kueper, B.H., Frind, E., 1989. The Behavior of Dense non Aqueous Phase Liquids in Heterogeneous Porous Media, 1: Model Development, Verification and Validation. Waterloo Center for Groundwater Research, University of Waterloo, Canada. Mohtar, R.H., Segerlind, L.J., Wallace, R.B., 1996. Finite element analysis for air sparging in porous media. Fluid/Particle separation Journal 9(3). Okeson, S., Illangasekare, T.H., Szlag, D.C., Ewing, J., 1997. Modeling of dissolution transport of nonaqueous phase liquid wastes in hetero-
geneous aquifers. Proceedings of the 10th Annual Conference on Hazardous Waste Research, 1997, pp. 146–152. Rahbeh, M., Mohtar, R., 2001. The influence of heterogeneity and air channelization on contaminant removal by air sparging. ASAE Meeting Paper No. 013151. Sacremento, ASAE,CA. Reddy, K.R., Adams, J.A., 1998. System effects on benzene removal from saturated soils and ground water using air sparging. ASCE Journal of Environmental Engineering 124 (3), 288–299. Reddy, K.R., Adams, J.A., Richardson, C., 1999. Potential technologies for remediation of brownfields. ASCE Practice Periodical of Hazardous, Toxic, and Radioactive Waste Management 3 (2), 61–68. Semer, R., Reddy, K.R., 1998. Mechanisms controlling toluene removal from saturated soils during in situ air sparging. Journal of Hazardous Materials 57 (1–3), 209–230. Sprague, N., Delahaye, A., 1996. Air sparging (http://www.ce.vt.edu/ programarea-areas/environmental/teach/gwprimer/airsparg2/airsparg. html). Zheng, C., Bennett, G.D., 1995. Applied Contaminant Transport Modeling. Van Nostrand Reinhold, New York.
Further reading Julio, S., Drucker, A.S., 2000. Air sparging remediation: A study on heterogeneity and air mobility reduction. Proceedings of the 2000 Conference on Hazardous Waste Research.