Environ. Sci. Technol. 1990, 2 4 , 750-757
Fundamentals for the Thermal Remediation of Contaminated Soils. Particle and Bed Desorption Models JoAnn S. Lighty,” Geoffrey D. Silcox, and David W. Pershing
Department of Chemical Engineering,+ University of Utah, Salt Lake City, Utah 84112 Vic A. Cundy
Department of Mechanical Engineering, Louisiana State University, Baton Rouge, Louisiana 70803 David G. Linz
Environment and Safety Research, Gas Research Institute, Chicago, Illinois 6063 1
A major research effort has been initiated to characterize the rate-controlling processes associated with the evolution of hazardous materials from soils. A 3-fold experimental approach was used in conjunction with computer modeling to analyze thermal desorption of contaminants. Phenomena occurring both inside particles (intraparticle) and within a bed of particles (interparticle) were studied. The results obtained suggest that the most important process variables are local thermal environment and gas-phase contaminant concentration because the adsorption equilibrium characteristics of the contaminant/soil pair control the desorption of contaminant from a particle a t a given temperature. A mass-transfer/desorption model, which assumes gas/solid equilibrium a t all points and time, is proposed and the model was found to predict the measured temperature dependence.
Introduction Thermal treatment is a common and proven technology for the remediation of contaminated solids, in particular soils. Demand for and growth in thermal-destruction technologies is expected ( I ) . The thermal-treatment process usually occurs in two parts: primary desorption and secondary incineration. Mass transfer and heat transfer are the common rate-limiting steps in the desorption process. Research focusing on the primary desorber environment, where the contaminants evolve from the solids, is limited. The primary desorber is often operated at high temperatures, which is costly, particularly for the cleanup of contaminated soils, due to high auxiliary fuel requirements. A more desirable option is to desorb the contaminants from the soil a t lower temperatures and then expose the off-gas to a high-temperature afterburner for decomposition of the hazardous compounds. Studies by deLeer et al. (2) and Koltuniak (3),which focused on low-temperature (less than 500 “C) desorption of contaminants from soils, found that contaminants could be effectively removed in this temperature range. To understand the desorption process, research must explore the rate-controlling processes that are occurring, as in the studies by Wendt, Linak, and co-workers (4, 5 ) on the fundamental mechanisms controlling the transient evolution of liquids from sorbent in a rotary kiln. The primary-combustor process fundamentals, volatilization of contaminants from the solid, mass transer, and heat transfer, need to be understood to model the system and to determine the primary-combustor conditions required to obtain a “clean” ash. Address where work was done.
750
Environ. Sci. Technol., Vol. 24, No. 5, 1990
The overall goal of this research is to develop an understanding of the fundamental transport phenomena associated with the evolution of hazardous materials from soils in the primary-desorber environment. In addition, the rate information obtained can be used to model the thermal desorption of contaminants under a variety of experimental conditions; from these results, large-scale operating parameters can be determined for optimum cleanup conditions. A 3-fold experimental program is being used to understand the transport phenomena that occur during the thermal desorption of contaminants from solids. Experiments have been designed to (1)characterize intraparticle transport, where the concentration and temperature at the particle surface are well-defined, (2) characterize interparticle transport, where the concentration and temperature are known at the top of a bed of particles, and finally, (3) provide time-resolved measurements of the species evolution in a realistic primary-desorption environment. A particle-characterization reactor (PCR) is used to evaluate intraparticle resistances. A bed-characterization reactor (BCR) is used in a one-dimensional mass-transfer and heat-transfer experiment to consider resistances within a soil bed that is swept by a desorbent gas at the solid surface (across the top of a bed of solid). Finally, a rotary kiln simulator has been used to evaluate the transport processes occurring in a full-scale rotary kiln system where the effects of solids mixing and heat transfer (flame radiation, wall conduction) must be taken into account. In this paper, PCR data have been evaluated to determine the controlling phenomena at a soil particle’s surface. A model was formulated and found to favorably describe the data. Once the mechanism of desorption at the particle was known, interparticle resistances were introduced through experiments in the BCR. The BCR represents a system where heat must be conducted through a bed of soil and desorbed contaminant must diffuse through the bed. The resistance of the soil bed is an important consideration in these transport processes. The modeling of these processes, based on the results of the particle study, is also discussed. Industrially, in thermal treatment systems where the material is stagnant, such as a moving-grate incinerator, or where the soil is rotated slowly such that layers of solid are stagnant, the heat and mass transfer through the bed must be understood to optimize and predict the system’s performance. Experimental Program
Experimental Equipment. The high-temperature, particle-characterization reactor, shown in Figure 1, has been designed to explore particle desorption and intra-
0013-936X/90/0924-0750$02.50/0
0 1990 American Chemical Society
Left-Side
7 Inlet
Exhaust Gas Gc/FID Andy
Exit-
Right-Side Gas Heat Exchanger Preheated Desorbent Gas
Heat Ex
-
Exit
Ass"
.
Loading Door
Front View
I
Window - I
Desorbent Gas Inlet
Figure 1. Particle-characterizationreactor (PCR) assembly. Reprinted with permission from ref 6. Copyright 1988 Pergamon Press.
particle transport phenomena by using a bed of soil (up to 2.5 cm thick) through which a preheated desorbent gas is passed. The exhaust gas is analyzed for contaminant by use of a gas chromatograph (GC) equipped with a flame-ionization detector (FID). Exhaust gas was pumped from the PCR through the GC, equipped with a six-port sampling valve. Samples were taken every 3-4 min during the experiment. This reactor represents a system of direct gas/ solid contacting and efficient heat transfer where the soil bed is essentially isothermal. After initiation of the desorbent gas flow, the soil bed reaches 90% of its final operating temperature in approximately 10 min (for the temperature range in this study). The reactor is constructed of stainless steel and the soil-bed assembly is 7.6 cm in diameter. A heat-exchanger assembly is used to preheat the desorbent gas via a series of stainless steel tubes. Both assemblies fit in a cylindrical high-temperature electric furnace. Details of this reactor have been previously reported by Lighty and co-workers (6). The bed-characterization reactor, schematically shown in Figure 2, is a one-dimensional experiment examining the heat-transfer and mass-transfer resistances through a bed of soil. The temperature and concentration gradients within the depth of the soil are used to obtain the effective thermal conductivity and diffusivity for the system. Heated desorbent gas passes over the top of two trays. One tray contains 12 Type-K thermocouples as shown in Figure 3, while the second tray is placed on an electronic balance to measure the transient weight loss resulting from the evolution of residual moisture, soil organics, and contaminant. A radiant heater is located above both trays. Further details have been previously reported (7). The GC /FID was used to determine the transient weight loss of contaminant from the BCR experiments. Weight loss data from the balance and temperatures within the soil bed were recorded manually. Materials and Methods. The soil studied in this work was a 10% moisture clay with quartz, illite, and montmorillonite mineralogy. Drying a t 100 "C for 24 h, to remove initial moisture, preceded all experiments. The average pore diameter was approximately 80 A and the
.
.u.
I
U
Figure 2. Bed-characterization reactor (BCR): left-side view, right-side view, and front view. Reprintedwith permission from ref 7. Copyright 1989 American Institute of Chemical Engineers.
T.C. #1,5,9 are 3.8-cm from bottom
T.C. #2,6,10 are 6:3-cm from bottom T.C. #3,7,11 are 8.9-cm from bottom T.C. #4,8,12 are 11.4-cm from bottom Soil Tray is 14-cm deep
Figure 3. Thermal tray-thermocouple
locations.
BET (N,) surface area was 15 m2/g. The clay contained 0.24% organic carbon and 0.41% organic matter. The nitrogen-adsorption/-desorption curve was representative of a slit-shaped pore configuration. Prior to drying and contamination, the clay was sized to remove particles greater than 1.3 cm. The clay was contaminated with p-xylene (0.5 wt %) after drying and sizing. p-xylene was carefully dropped into a bottle of the clay soil; the bottle was immediately shaken to distribute the p-xylene throughout the soil evenly. After various methods of contamination were studied, this method was found to give a reproducible distribution of contaminant (6). The level of contamination was chosen for weighing and contamination reasons; a lower concentration of p-xylene made measurement and distribution difficult. Studies have also been conducted on the time of adsorption of contaminant, from 1 day to 1 year, and no change in desorption characteristics was apEnviron. Sci. Technol., Vol. 24, No. 5 , 1990
751
Table I. Particle Model Parameters
parameter
value
particle diameter, d gas mass flow rate bed porosity, e bed density, p
itt
Inlet Gas Flow, superficial velocity, u, Tg(XJ)
C,(& t)
parent (6). p-Xylene was chosen as the surrogate contaminant due to its relatively nontoxic nature, and pxylene is a volatile organic hydrocarbon contaminant found at several Superfund sites.
units m kg/(m2 s)
8.38 X 0.034 0.43 0.94
g/cm3
assuming negligible radial gradients and axial dispersion as in Sherwood, Pigford, and Wilke (9),the following is obtained:
ac, - P acZ - ac,
-u-
(1) at where x is the distance through the solid's bed, t ;_S time, C, is the gas-phase concentration of contaminant, C is the solid-phase contaminant concentration, u is the superficial velocity of gas through the reactor, and p and E are the bed density and bed porosity. The Peclet number is approximately 2.0 in this experiment, yielding an axial diffusion coefficient of approximately 6 X m2/s; hence, as an initial guess, axial diffusion was neglected. By use of the Freundlich isotherm model and the assumption that a t all points and for all times the bed is in local equilibrium ax
--E-
Particle Studies
Experimental Results. The initial screening studies in the PCR indicated that temperature was the dominant independent parameter. Even above the boiling point of p-xylene (139 "C), the amount of p-xylene remaining in the soil was high and the rate of removal leveled off with time, indicating that a threshold concentration remaining in the soil would evolve very slowly (6). Further, increasing the desorbent gas flow rate increased the evolution rate in exact proportion to the flow rate increase so that the gas-phase exhaust concentration remained constant. The constant gas-phase concentration indicated that intraparticle and film transport limitations were not affecting the desorption rate. The leveling of the evolution curves and the flow rate results suggested that the controlling influence during the desorption of contaminant from the particle might be adsorption/desorption equilibrium, not intraparticle transport. In addition, theoretical calculations of Knudsen and molecular diffusivities suggested that internal diffusion processes should be several orders of magnitude faster than the overall evolution rates indicated by experimental measurements. When the PCR was used as an adsorption reactor, by passing contaminated desorbent gas through a bed of clean clay, even above the boiling point of p-xylene, contaminant adsorbed onto the clay. A series of adsorption experiments where conducted at different temperatures and gas-phase concentrations (6, 7). A nonlinear least-squares program was used to fit the adsorption data to the Freundlich isotherm model, as detailed in Brunauer (8), where the heat of adsorption varies logarithmicallywith surface coverage. The equations for the isotherms, as functions of temperature and gasphase concentration, are given in Appendix A. A fit to the Langmuir isotherm did not yield satisfactory results at the lower gas-phase concentration levels where most of the PCR data lie. PCR Model Formulation. The PCR modeling efforts focused on understanding the experimental evidence that the equilibrium between the gas and solid appears to be the most significant influence on the rate of desorption of p-xylene from the clay. The concept of this model is shown in Figure 4. By performing a mass balance on the gasphase concentration of p-xylene within the bed of clay and 752
Environ. Sci. Technol., Vol. 24, No. 5, 1990
Substituting the result of eq 2 in eq 1, the following is obtained for a mass balance over the bed, subject to the initial condition and boundary condition shown:
-E
ax
at
(3)
a t t < 0, C, = Co for all x a t t 2 0, C, = 0 for x = 0 where f'(C,) is the derivative of the Freundlich isotherm with respect to concentration (4)
The heat-up of the soil bed was found by applying an energy balance on the bed and by assuming negligible conduction through the solid (the solid is primarily heated via convection from the gas since the gas is passing through the bed) and that the effect of heat loss due to evaporation is small. The convective heat-transfer coefficient was estimated by using the correlation from Yoshida, Ramaswami, and Hougen (IO). Table I lists the values of the parameters used. The particle diameter was chosen as the average diameter of the screened particles and the gas flow rate was held constant. E and p were found experimentally. Equations for the desorption (eq 3) and heat transfer were solved simultaneously by approximating the partial derivatives in x with finite differencing, obtaining a system of first-order ordinary differential equations (ODEs). The ODEs where solved by using a first-order ODE solver for stiff and nonstiff systems, LSODA (11, 12). Analysis of PCR Model Results. The heat-transfer results are shown in Figure 5 for three sweep gas temperatures. The model predicts the increase in the temperature of the center of the soil bed quite accurately. Within approximately 10 min the temperature is within 90% of the final operating temperature. The assumptions
1
S k w p gas t!empexad = 270
I
'd
'
1L
- A
200
u
-
Sweep gas temperature = 215 OC
A I
I
-'
m
I
I
Heat transfer results
01 0
I
1
I
10
I
I
1
20
I
I
30 Time, min
I
1
I
I
50
40
Temperature, OC
60
Flgure 5. Model predictions of bed temperature compared with experimental measurements of the bed center temperatures (symbols). 250
l
l
l
l
r
l
,
l
l
l
Flgure 7. Model predictions of concentration of p-xylene remaining on the soil after desorption for 1 h compared with experimental results (symbols). 1.0
,
1
"
I
"
I
"
T e m p t u r e is 240 O C Solid Temperature at x=O
11
c
1501
8
//
0.6
/Solid Temperature at x=1.27 cm 3
5
0.4
u
100
+
0
v
1 I I
0
r
i .x-
I w - Represents uncontaminated soil weight-loss data
0.0 0 300
600
900 1200 Time, sec
1500
1800
400 Time, min
600
Flgure 8. Typical bed-characterization reactor results.
Flgure 6. Model predictions of inlet and exhaust solid temperatures for an inlet gas temperature of 215 "C.
of negligible solid-phase conduction through the bed and evaporation heat losses appear to be satisfactory, as evidenced by accurate prediction of the experimental data. Figure 6 illustrates model predictions for the solid bed temperature at the inlet and the exit as a function of time for an inlet gas temperature of 215 "C. Initially, the inlet temperature is greater than the exit; however, within approximately 10 min, the bed reaches a uniform temperature. Thus, the model predicts negligible axial temperature gradients within 10 min. The model was also used to predict gas-phase concentrations within the depth of the 1.3-cm bed as a function of time. By use of the Freundlich isotherm equation,
c = ACgb
200
(5)
where C, was predicted in the model, the corresponding solid-phase concentration, 6, was found at each location after 1h of desorption. Taking the integral over the bed, an average solid-phase concentration was calculated; these results are illustrated in Figure 7, where the predicted average concentration of p-xylene remaining in the soil after desorption for 60 min is compared with the experimental results (7)as a function of temperature. The model predicts the significant temperature dependence of solidphase concentration remaining in the soil. This depen-
dence on temperature has also been seen by BorkentVerhage and co-workers (13) in the desorption of lindane from a humic sand. The agreement between the model and the data further validates the experimental observation that the adsorption characteristics of the contaminant and solid control the evolution of the contaminant from solid particles.
Bed Studies Experimental Results. Typical BCR data for the clay soil contaminated with p-xylene are shown in Figure 8 for a temperature of 240 "C and bed depth of 7.6 cm. These data were obtained to ensure that the p-xylene evolution measured by the GC system agreed with the measured weight loss. The upper curve, the percent loss of soil weight (1821.8 g in weight tray and 1548.9 g in temperature tray) as a function of time, was obtained from the balance. The data below (the triangles) were calculated from time-integrated GC measurements. The weight-loss data for uncontaminated clay, exposed to the same temperature environment, are represented by the squares. Finally, the solid line in Figure 8 is the difference between the upper two curves. As shown in the figure, the contaminated-soil balance data (circles) minus the GC data (represented by the solid line) agree well with the percent weight loss of an uncontaminated soil (the squares). The desorption of soil organics could be the "extra" weight loss. Total weight Environ. Sci. Technol., Vol. 24, No. 5, 1990 753
200
150
i
'
l
'
I
i
'
l
'
l
l
'
i
'
i
'
-
0
50
100
150
x=o
5.1-cm from the top 7.6-cm from the top
300
350
400
450
loss was 0.8% of the soil weight while contaminant loss was only 0.4%; the additional loss can be accounted for by considering organics in the soil (0.41%). With these data, a material balance was obtained to within 20%. The vertical bed temperature distributions within the bed are shown in Figure 9, for a gas temperature of 240 "C and radiant-heater temperature of 240 "C. As expected, a significant vertical temperature gradient exists within the bed as a result of the thermal resistances within the soil bed. The slightly higher initial temperatures a t the bottom of the bed are a result of conduction from the furnace floor through the bottom of the tray. The temperatures obtained a t any cross section of the bed are within 5 "C (readings of thermocouple 1versus 9, shown in Figure 3), with the maximum a t the center; therefore, conduction losses through the sides of the trays are minor. BCR Model Formulation. As previously discussed, the BCR experiment has been designed to simulate a onedimensional heat-transfer and mass-transfer system. Gradients exist within the depth of the bed; boundary conditions are known at the top and the bottom of the bed. The model concept is shown in Figure 10. For the heat-transfer model, radiation and convection occur a t the top of the bed due to the sweep gas, with a temperature T , and the radiant heater, with a surface temperature of !bS,located above the bed. The bottom-bed temperatures are measured with the thermocouples; these temperatures are then fitted to an equation, obtaining temperatures as functions of time. The heat loss due to evaporation of contaminant is assumed to be negligible. By use of these assumptions, the following equations are obtained from an energy balance on an element of bed (parameters are given in Table 11): CY
=
k -
(6)
PCP
at x = 0, ae(T,4 - P ) + h(T, - T ) + at t
dT kz
=0
< 0, T = Tinitial for all x
a t x = M (bottom of the bed), T =
Tbottom(t)for
all t
The partial differential equations (PDEs) are converted to first-order, ordinary differential equations (ODES) by approximating the derivatives in x with finite differencing. For the mass-transfer equations, the concentration at 754
SweepGasOver Bed
-
Figure 10. Concept of bed desorption model.
2.5-cm from the top
200 250 Time, min
a2T - dT where ax2 at
T
Radiant Heater
*
x=M
Figure 9. Temperature distribution for 7.6-cm bed of soil with gas temperature of 240 'C.
CY-
-
Ts
1
-.I
50
0
'
Environ. Sci. Technol., Vol. 24, No. 5 , 1990
the top of the bed is assumed to be zero (due to the sweep gas), and a t the bottom of the bed, the concentration gradient is zero. The concentration within the particle is represented by an average concentration, C. Given the stagnant conditions within the bed, the Sherwood number is assumed to be 2. Performance of a mass balance using the gas-phase concentration, C,, and the average soil concentration, C, after Wendt, Linak, and McSorley ( 5 ) , results in (7)
at t
< 0, C,
= Co and
C
=
a t x = 0, C, = C =
Co for all x > 0
o for all t
a t x = M , d C , / d x = 0 for all t
Co represents the initial contaminant loading in the soil and Co is the gas-phase concentration in equilibrium with the solid concentration, as determined by the Freundlich isotherm model, found to be valid in the PCR modeling. The molecular diffusivity and effective diffusivity, Dab and Deff,are functions of temperature, given by Dab = 7.0
X
10-6[T/298]1*5
(9)
The gas concentration a t the surface of the particle, Csat, is found by using the Clausius-Clapeyron equation and the heat of adsorption from the Freundlich isotherm equation, where
for
C < Ccrit,m
a d
= H~ In
(C/CCrit)- AH,,,
During the initial, constant "drying" period, when C is greater than the critical concentration, Ccrit,the heat of adsorption is simply the heat of evaporation of the contaminant. Once the concentration in the solid drops below this concentration, the heat of adsorption is a function of the contaminant surface coverage. The Freundlich isotherm was used to estimate the heat of adsorption as a result of the PCR model, which showed that the particle surface was in equilibrium with the gas phase, hence, the logarithmic variation in the heat of adsorption with surface coverage.
Table 11. Bed Model Parameters
bed density, p bed heat capacity, Cp bed porosity, c Stefan-Boltzmann constant, u critical concentration, Grit
effective diffusivity, Deff(at 25 "C) emissivity of system, e gas constant, R1 gas constant, R HI heat of vaporization,
1094 2300 0.35 5.67
2o 18
units
value
parameter
w
kg/m3 J/(kg K) 14 X
2.365 X 8.58 X 10"
W /(m2K4) kg-mol/ kg of soil m2/s
0.7
h
M
K v
12
a ! i 10e,
36
8 -
b
315 O C 24OT I 175 O C
-
0
6 -
0.08205 1.987 2000 8500
m3.atm/ kg-mol K cal/g-mol K cal/g-mol cal/g-mol
2m 4 -
0
Hvap
initial soil concentration, C, molecular diffusivity, Dab(at 25 "C) particle diameter, d, preexponential factor, A thermal conductivity, k
140
6.6'
1
175 'C
4.717 X 7.0 X 10" 8.38 X IO4 33259.7 2.0
kg-mol/kg of soil mz/s
W/(m K)
B 7 . 6 - c m f " top (bottomofbed) a 5.1-cmfromtop 2.5-cmfromtop
7.6-cmfromtop (bottomofbed) a 5.1-cmfromtou 2.5-cm from t.P
A
c
100-
300
350
400
450
found experimentally. The emissivity of the system, e , was found from values given in the literature for soil (0.9) and the radiant-heater material (0.75) where -1= - 1 l 1 (12) e cheater esoil
:a 4
100 150 200 250 Time, min
indicate experimental data).
120
E
SO
Figure 12. Comparison of mass-transfer model with bed data (symbols
m atm
B
c
0
-:
.
-
1 I
01. ' ' ' ' ' . ' . ' 0 SO 100 150 200 250 300 350 400 450 Time,min
Figure 11. Comparison of heat-transfer model with bed data for 7.62-cm bed (symbols indicate experimental results).
Since the assumption of negligible heat loss due to evaporation decouples the heat transfer and the mass transfer, the heat-transfer equation (eq 6) is solved independently of the mass-transfer equations (eqs 7-11). The resulting temperatures are input to the mass-transfer equations. The mass-transfer equations are solved by converting the PDEs into ODES, using finite differencing, and solving the system of equations with a stiff ODE solver (11,121. The values of the parameters are found in Table 11. The bed density, bed porosity, and heat capacity were
+--
The critical concentration, Cerit,2.365 X kg-mol/kg of soil, was estimated from the BCR data and was assumed constant over the temperature range studied. Given the initial concentration in the bed and the amount of contaminant evolved during the constant rate period, C&t was found by difference. The parameter H1 and thermal conductivity, k, were varied to fit the data. Analysis of BCR Model Results. The results of the heat-transfer model are compared with measured data for the three gas temperatures, 175, 240, and 315 "C (the radiant-heater surface temperature was the same as the gas temperatures), as shown in Figure 11for a 7.6-cm bed of clay. The model predicts the temperature gradients within the bed quite accurately for all three temperatures. As stated previously, the effective thermal conductivity, k, was adjusted to fit the data. The mass-transfer solution requires estimation of HI for use in eq 11. Initially, the value of HIwas estimated by using the Freundlich isotherm parameters in Appendix A. With this value the predictions of the 240 "C data (7.6-cm bed) were low (by approximately 20%), probably as a result of extrapolation of the isotherm data in this region. Consequently, H1was adjusted such that the resulting model predictions fit the 240 O C data. Figure 12 shows these results and the contaminant evolution versus time for 175 and 315 "C compared with data from ref 7, all for a 7.6-cm bed. The mass-transfer model accurately predicts the constant evolution rate, which tapers off at long times. The model also predicts the increase in the rate of evolution with increasing temperature. The jump in the 240 OC data, at 125 min, is a result of the concentration a t the bottom of the bed reaching the critical concentration and subsequently dropping below the critical concentration within the specified time step (10 min). As stated previously, the critical concentration was estimated from the data. With the model, a decrease in C,, resulted in an increase in the rate of desorption; hence, the time for complete removal was decreased. Given these results, the estimated critical concentration appears to be Environ. Sci. Technol., Vol. 24, No. 5, 1990
755
0
100
200 300 Time, min
400
500
Figure 13. Model predictions for 5.1-cm bed desorbed at 240 (symbols indicate experimental data).
OC
correct, and the estimated value was used successfully at the three different temperatures, indicating that this parameter is a function of the soil and the type of contaminant, as expected, and not temperature. In addition to the various temperatures, predictions for desorption at 240 " C for a thinner bed were also obtained. Figure 13 shows the model predictions (without any parameter changes) for the 5.1-cm bed. Again, the model accurately predicts the evolution of contaminant versus time and predicts the reduction in resistances within the bed as bed depth decreases. BCR Model Application. The predictions from the BCR model are directly applicable to industrial thermal desorbers where a bed of solids is heated from the top while moving through the unit. The model suggests that obtaining low contaminant soil concentrations is a function of (1) the solids' temperature, which might need to be significantly above the boiling point of the contaminant, and (2) the bed resistances, which must be minimized by reducing bed depth or increasing solid-phase mixing. Given a certain temperature and bed depth, an increase in residence time will result in lower soil concentrations; however, once the constant rate evolution period is completed, the evolution slows down and levels off such that only a substantial increase in residence time would significantly reduce the concentration left in the soil.
Conclusions While several parameters have been found to be important in the desorption of contaminants from soil, temperature is the most important. The dependence of the adsorption characteristics of the soil on temperature appears to be a primary reason for this effect. As the temperature is increased, the equilibrium concentration of contaminant in the soil is less for the same gas-phase concentration. A mass-transfer/desorption model, based on gas/solid equilibrium at the particle surface, has been proposed to model desorption of contaminant from a particle. For the soil and contaminant studied, the experimental measurements indicated that intraparticle transport was not controlling; rather, the particle surface concentration was determined by the corresponding gas-phase concentration. The solid-phase and gas-phase concentrations can be related by the Freundlich isotherm model. Model predic756
Environ. Sci. Technol., Vol. 24, No. 5, 1990
tions and experimental results show the sharp dependence of the concentration remaining in the solid on temperature. The BCR data suggested that resistances of the soil bed to mass and heat transfer were important. The contaminant evolves at a constant rate until reaching some critical concentration; at this concentration, the "falling-off" regime begins. This regime has been described by the adsorption isotherm characteristics of the soil. The Freundlich isotherm was used as a result of PCR work where the heat of adsorption varies logarithmically with surface coverage. The heat-transfer model accurately predicts the temperature gradients within the bed of soil. The assumption of negligible heat loss as a result of evaporation is valid for this experiment; a t higher initial contaminant concentration levels, this assumption may not be valid. The rate of mass loss within the bed, increasing with increasing temperature, has been accurately calculated by use of the mass-transfer model. It appears that, while the concentrations at the particle surface in the BCR model are higher relative to the PCR than expected, the assumption of a Freundlich isotherm accurately represents the data, suggesting that the heat of adsorption varies logarithmically with surface coverage. The mass-transfer and thermal resistances within the bed, as defined by effective thermal conductivity, effective diffusivity, and bed thickness are also important in the desorption of contaminants from the bed. Reduction in these resistances, via a reduction in bed depth, results in faster desorption of contaminant. Appendix A The data from the adsorption experiments were fit to the Freundlich isotherm model by nonlinear least-squares regression. The coefficients of the Freundlich isotherm, A(T) and B ( T ) were determined at four different temperatures, where
.(
wg of p-xylene gm of soil
)
= A (T)
(
pmol of p-xylene mol of gas
~ ( n
)
The regression analysis was then used to find A ( T ) and B(T) as functions of temperature in degrees K, resulting in A(T) = exp[1.8697 + (3.9 x 10-T) (6.6861 X 10-51*2)]for all T B(T) = 0.1938 - (2.2952
X
10-4T) for 298 K IT
< 444 K
B ( T ) = -5.0291 + (1.8956 X 10-2T) (1.6717 X 10-51"L)for 444 K IT I590 K Glossary A
c c, CP
Dab
Deff d,
e Hvap h k t
preexponential factor, atm solid-phase concentration of contaminant, kgmol/kg of soil gas-phase concentration kg-mol/m3contaminant, kg-mol/m3 heat capacity, J/(kg K) molecular diffusivity, m2/s effective diffusivity, mz/s particle diameter, m emissivity heat of vaporization, cal/g-mol heat-transfer coefficient, W/(m2 "C) thermal conductivity, W / ( m K) time, s
T U X
a €
P
temperature, K superficial velocity, m / s distance, m thermal diffusivity, m2/s bed porosity bed density, kg/m3 Registry No. p-Xylene, 106-42-3.
Literature Cited (1) Oppelt, E. T. J . Air Pollut. Control Assoc. 1987, 37, 558. (2) deLeer, Ed. W. B.; et al. Thermal Cleaning of Soil Contaminated with Cyanide Wastes from Former Coal Gasification Plants. Conference on New Frontiers for Hazardous Waste Management, 1985. (3) Koltuniak, D. L. Chem. Eng. 1986, 93, 3. (4) Linak, W. P.; McSorley, J. A.; Wendt, J. 0. L. J. Air Pollut. Control Assoc. 1987, 37, 934. (5) Wendt, J. 0.L.; Linak, W. P.; McSorley, J. A. International Symposium of Hazardous, Municipal, and Other Wastes, Fall Meeting, Palm Springs, CA, November 2-4, 1987; American Flame Research Committee of the International Flame Research Foundation, 1987. (6) Lighty, J. S.; Pershing, D. W.; Cundy, V. A.; Linz, D. G. Characterization of thermal desorption phenomena for the cleanup of contaminated soil. Nucl. Chem. Waste Manage. 1988, 8, 225.
(7) Lighty, J. S.; Silcox, G. D.; Pershing, D. W.; Cundy, V. A.; Linz, D. G. Fundamental experiments on thermal desorption of contaminants from soils. Environ. Prog. 1989, 8, 57. (8) Brunauer, S. The Adsorption of Gases and Vapors; Princeton University Press: Princeton, NJ, 1945; Vol. 1. (9) Shenvood, T. K.; Pigford, R. L.; Wilke, C. R. Mass Transfer; McGraw-Hill Book Co.: New York, 1975. (10) Yoshida, F., Ramaswami, D.; Hougen, 0. A. AIChE J . 1962, 8, 5. (11) Petzold, L. R. Automatic Selection of Methods for Solving Stiff and Nonstiff Systems of Ordinary Differential Equations. Sandia National Laboratories Report SAND80-8230, September 1980. (12) Hindmarsh, A. C. ACM-Sigmum Newsl. 1980, 14, 10. (13) Borkent-Verhage, C.; Cheng, C.; deGalan, L.; deLeer, Ed. W. B. Thermal Cleaning of Soil Contaminated with yHexachlorocyclohexane. In Contaminated Soil; Assink, J. W., van den Brink, W. J., Eds.; Martinus Nijhoff Publishers: Dordrecht, Netherlands, 1986.
Received for review February 1, 1989. Revised manuscript received October 24,1989. Accepted January 12,1990. This work was funded by the Gas Research Institute, Dave Linz, Project Manager, the National Science Foundation-Presidental Young Investigator Program, and the Advanced Combustion Engineering Research Center (NSFIACERC). Funds for the ACERC center are received from the National Science Foundation, the State of Utah, 26 industrial participants, and the U.S. Department o f Energy.
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