Desorption of Polychlorinated Biphenyls from Contaminated St

Ind. Eng. Chem. Res. 2004, 43, 397-404

397

Desorption of Polychlorinated Biphenyls from Contaminated St. Lawrence River Sediments with Supercritical Fluids Wu Zhou, Gheorghe Anitescu, and Lawrence L. Tavlarides* Department of Chemical Engineering and Materials Science, Syracuse University, Syracuse, New York 13244

Laboratory- and bench-scale polychlorinated biphenyl (PCB) desorption experiments using supercritical fluids are conducted on air-dried, contaminated St. Lawrence River sediments (SLRS) to demonstrate the remediation and scale-up potential of the process. Laboratory-scale desorption experiments reveal that PCB concentrations can be reduced from 2200 ppm to less than 5 ppm in 60 min (99.77% extraction efficiency) when supercritical CO2 with 5 mol % methanol is used at 118 bar and 323 K. Similar or better results are achieved at a bench-scale size of 2 L volume (400 × scale-up) under similar conditions. It is found that the PCB concentration in the sediments can be reduced from 1840 ppm to less than 5 ppm in ∼40 min (>99.73% extraction efficiency). The final PCB concentrations after 60 min of extraction are around 3 ppm, which is comparable with the final PCB concentrations of ∼4 ppm for the laboratory-scale experiments (when the supercritical fluid is CO2/MeOH). These results suggest that the scale-up factors are not significant over this range on the desorption processes of PCBs from real-world SLRS. A two-step linear driving force model is shown to predict well the benchscale desorption results when using a model obtained independently and the effective diffusion coefficients and mass-transfer coefficients determined from the laboratory-scale information. 1. Introduction Supercritical fluid extraction (SFE) is seen as an alternative method to remove persistent organic pollutants (POPs) such as polychlorinated biphenyls (PCBs) from contaminated soils/sediments. Supercritical fluids (SCFs) show enhanced solvation power to dissolve POPs, and this ability can be easily tuned by changing temperature and/or pressure, leading to simple solutesolvent separation schemes. Other attractive features of SCFs such as low viscosity and high diffusivity are essential to reduce mass-transfer resistance during the desorption processes. The SFE technology is able to clean up PCB-contaminated soils/sediments with PCB concentrations falling in very broad ranges and is particularly effective to remediate soils/sediments with high PCB concentrations.1-3 The concentrated PCB solutions collected after the extraction can be destroyed using other available methods such as liquid-phase chemical destruction or supercritical water oxidation (SCWO).3 A two-stage SCF technology has been developed at Syracuse University to remediate PCB-contaminated soils/sediments.1-3 The proposed process consists of SFE of PCBs from the contaminated materials and SCWO of the extracts. To support this concept, a database required to design and evaluate a full-scale remediation process is being developed. This study focuses only on the first step of SFE. SFE of contaminated soils/sediments has been extensively studied.4-12 Effects of pressure, temperature, cosolvent, soil moisture content, and initial concentration on PCB desorption from soil/sediment samples were investigated.4,12-16 The structure and properties of PCB congeners are also found to have some effect on the PCB * To whom correspondence should be addressed. Tel.: 315443-1883. Fax: 315-443-1243. E-mail: [email protected].

desorption behavior.11,14 Reported results on mass transfer, diffusion coefficients, and desorption rates in SFE processes have greatly improved the understanding of the desorption mechanism in SCFs, the effect of operational variables such as temperature and pressure, and cosolvent and soil properties on extraction efficiency.17-21 Still, information accumulated so far is not yet sufficient for the design and optimization of a full-scale SFE remediation process because PCB desorption phenomena depend on multiple sample characteristics and process conditions.11,22 The limitations of the reported studies include the use of spiked instead of real-world samples, insufficient thermodynamic data such as PCB partition coefficients between soils/sediments and SCFs, and the lack of systematic and comprehensive benchscale tests. As an effort to reduce this knowledge gap between laboratory results and application requirement, this work characterizes the SFE of PCBs from real-world contaminated St. Lawrence River sediments (SLRS) both on laboratory- and bench-scale equipment with CO2 and CO2/MeOH as SCFs. The laboratory-scale experiments have better flexibility and are less time- and sample-consuming. Accordingly, the objectives of the laboratory-scale SFE study are to investigate the effects of various operational variables of the desorption process, define proper operating conditions for larger scale studies, and obtain PCB desorption data for modeling. The bench-scale experiments have been performed to confirm expected desorption efficiencies based on the laboratory-scale experiments and to unveil whether any substantial differences occur in the scale-up process. The major factors affecting PCB desorption rates and efficiencies are cosolvent employed and soil moisture content. The effects of soil moisture content on PCB desorption processes are somewhat complicated. While small amounts of moisture present in SCFs or in soil

10.1021/ie0301177 CCC: $27.50 © 2004 American Chemical Society Published on Web 10/10/2003

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Ind. Eng. Chem. Res., Vol. 43, No. 2, 2004

have been reported to enhance organic desorption equilibrium or even desorption rates, the presence of larger amounts of water in soil (>5-10%) will always reduce the extraction rates significantly.14 The former effect can be explained through the competition for and interaction with the soil active sites by polar water molecules and the latter by the formation of an aqueous layer around the soil particles and inside the pores, which reduces the mass-transfer rate.2 From the remediation point of view, air-dried or slightly moistened samples will serve the SFE process well. No further moisture effects have been studied in this work. Both the type and the presence of cosolvents in supercritical CO2 can affect SFE rates and efficiency significantly. Up to date reported data suggest that methanol is the best cosolvent among those investigated for SFE of PCBs from soils/sediments.2,3,14,15 The effects of methanol on PCB desorption rates and efficiencies from real-world sediments are investigated in this work. 2. Experimental Section 2.1. Main Desorption Parameters. Pressure, temperature, and flow rates of SCFs are the operation parameters that can have significant effects on the operation cost of the SFE processes. Both moderate pressure (100-150 bar) and temperature (313-333 K) values are proposed in this study in the perspective of reducing processing costs. On the basis of our previous desorption2,23 and the PCB partition equilibrium data,24 the pressure of 118 bar and temperature of 323 K (corresponding to the density of 13.0 mol/L for pure supercritical CO2) are employed in both the laboratoryand bench-scale studies. Two different SCF flow rates are tested to determine the minimum flow rate necessary for effective PCB desorption. The real-world sediments used had initial PCB concentrations of 2200 and 1840 ppm for the laboratory- and bench-scale experiments, respectively. 2.2. Laboratory-Scale Apparatus. Desorption experiments on air-dried SLRS are conducted for pure CO2 and CO2/5% (mole) MeOH SCFs in a 5-mL fixed-bed Supelco extractor immersed in a water bath (Fisher circulator model 9105; (0.1 K). High-pressure carbon dioxide and methanol are delivered by a Newport Scientific compressor (model 46-13421-2) and an ISCO syringe pump (model 100DM), respectively. The pressure in the system is controlled by a backpressure regulator and monitored by a Heise digital pressure indicator (model 901A). The flow direction of SCFs is downward through the bed and silica restrictors are employed to control the flow rates and depressurize the SCFs. The flow rates of pure CO2 at experimental conditions (118 bar and 323 K) are measured using the volumetric method as 0.031 mol/min [0.227 g of CO2/ min‚(g of soil) or 0.04 mL/s] for the 50-µm restrictor and 0.018 mol/min [0.133 g of CO2/min‚(g of soil) or 0.02 mL/ s] for the 40-µm restrictor. These flow rates are found virtually unchanged when 5% (mole) MeOH is present in supercritical CO2. The flow rates are monitored by a rotary flowmeter, and a dry test meter is used to measure the total amount of effluent gas. Sample vials filled with hexane are used to collect effluent PCBs and then are weighed to determine the amount of the PCB/ hexane solution. After each experiment, the sediment in the extractor is removed and the concentration of the remaining PCBs in the sample is analyzed as a residual PCB concentration.2,23

Figure 1. Simplified schematic of the bench-scale SFE unit (AOV, air operated valve; PCV, pressure control valve; T, thermocouple; P, pressure transducer; dashed line, control signal flow).

2.3. Bench-Scale Equipment. A fixed-bed, benchscale SFE unit has been designed, constructed, commissioned, and tested in our laboratory with the assistance of personnel from Autoclave Engineers, a Division of Snap-Tite, Inc. A simplified schematic of this unit is given in Figure 1, where only the major components, material flow paths, and the control signal flow paths are shown. a. SCF Delivery System. A double-headed piston pump is used to deliver high-pressure CO2 to the system from a storage vessel, wherein the pressure is computercontrolled in the range of 24-28 bar at 268 K. A chiller drops the temperature of liquid CO2 around the pump heads to ∼258 K to prevent vapor formation. Two ISCO syringe pumps (model 100DM) operating alternatively deliver MeOH as the cosolvent. The high-pressure CO2 and MeOH pass through an inline static mixer before entering a preheater to increase the fluid temperature to the operation value of 323 K. b. Extraction System. The major parts of this subsystem are the extractor vessel and the recycle pump. A heating blanket for temperature control covers the extractor. A removable bucket with a capacity of ∼2 L (400 × scale-up), equipped with porous sintered metal plugs (0.5-µm pores) at both ends, is used to load sediment samples into the extractor. The sediment bed is equally divided into four layers, and after each experiment, the content of each layer is removed from the sample bucket and then analyzed separately for PCB concentrations. The recycle pump is designed to circulate SCF around the extractor to improve the utilization efficiency of SCF. An automatic valve controls the pressure inside the extractor. The total void volume (dead volume of the system plus the void volume inside the bed) is estimated to be about 2-3 L and requires a pressurization time of ∼3 min. Therefore, the startup effects could significantly affect the results of any desorption experiment lasting for less than 5-10 min. c. Separation and CO2 Recycle System. The separation of CO2 from MeOH and PCBs is achieved by expansion in the separator where the temperature is kept in the range of 268-283 K. The pressure inside the separator is controlled automatically and kept around 3.1 MPa. A filter and demister are also installed inside the separator to prevent small MeOH/PCB drops to be entrained by the clean CO2 vapor. The clean CO2 vapor enters the condenser for reuse, and the MeOH/ PCBs mixture can be collected from the bottom of the

Ind. Eng. Chem. Res., Vol. 43, No. 2, 2004 399

Figure 2. Comparison of PCB congener distribution patterns before and after extraction for laboratory-scale experiments (only congeners with relative abundance >0.5% are shown).

separator for further treatment (methanol recovery and PCB destruction). 2.4. Description of the PCB-Polluted Sediments. Real-world sediment samples contaminated with PCBs are collected from a polluted site in a former bay of the St. Lawrence River near Massena, NY.25 Prior to utilization, the sediments were air-dried under laboratory conditions and then sieved through a screen (0.06cm opening) to remove rocks and debris. Subsequently, mineral properties, total organic carbon (TOC), and initial PCB concentrations as an average of three different sediment samples are determined. The SLRS employed in this study contains 58% sand, 22% clay, 19% silt, 1.76% TOC, and 1840 and 2200 ppm of PCBs (bench- and laboratory-scale experiments, respectively). All of the PCB desorption experiments are conducted on air-dried SLRS samples equilibrated with air at 298 K and 50% relative humidity for at least 2 weeks to ensure a constant moisture level for all samples. The composition and initial PCB concentrations of the realworld sediment samples were then established by multiple-sample analysis. Figure 2 shows the distribution pattern of major PCB congeners in the sediment sample used in the experiments. 2.5. Analytical Method. The concentrations of PCB congeners in hexane solutions are determined using a Hewlett-Packard 5890 series II gas chromatograph (GC) equipped with an automatic capillary injection system, an electron capture detector (ECD), and an ultraperformance capillary column (Hewlett-Packard Ultra 2; 25 m × 0.20 mm i.d., 0.33-µm film thickness). This congener-specific analytical method is based on a 71peak chromatogram of PCB standard solutions (SOL I) prepared from individual congeners and an internal standard. The PCB concentrations in sediments are determined using a sonication-enhanced liquid-extraction method to transfer all PCBs from the sediments to hexane solutions, which are subsequently analyzed by GC. The details of these methods are presented elsewhere.2,23 Essentially, a sediment extract of PCBs in hexane and a series of diluted solutions of this extract are employed as new standard solutions for each type of sediment sample. These solutions match both PCB congener distribution and the composition range of the samples taken from the experiments. The sedimentbased solutions used as GC-ECD standards are calibrated against the synthetic standard solutions SOL I. The precision of these methods is ∼5%.

Table 1. Model-Related Properties for Laboratory-Scale Extraction soil bed properties SCF properties at 323 K and 118 bar

particle radiusa (cm) bulk densityb (g/mL) void fractionc densityb (g/mL) partition coefficientsb (mL/g)

SCF flow rates (mL/s) (CO2)1 (CO2)2 (CO2/MeOH)1 (CO2/MeOH)2 extractor radius (cm)

0.03 1.37 0.427 0.572 CO2 CO2/MeOH 0.658 0.817 CO2 CO2/MeOH 0.429 0.023 0.040 0.021 0.036 0.398

a Determined by sieve size. b Reference 24. c Determined by the water displacement method.

3. Modeling Development 3.1. Laboratory Scale. Previous desorption studies on the laboratory-scale unit for both CO2 and CO2/5% (mole) MeOH at conditions of Table 1 demonstrate that PCBs undergo consecutive rapid and slow desorptions.2,23 Also, the initial desorption rate in the supercritical CO2/MeOH fluid is faster than that in the supercritical CO2 only, and the final PCB residual concentration is much lower. Further, it is observed that no significant PCB congener pattern shift occurs from the initial to the final distribution for either system (Figure 2). These results indicate that all of the PCB congeners are quite evenly extracted and that the overall desorption process is not equilibrium-controlled but rather diffusion-controlled.26 Accordingly, it is reasonable to treat the PCB mixture as a pseudocompound to model this process. Calculations ensure that a single pseudocompound matches the initial (fast) desorption period reasonably well but fails for the long-time (slow) desorption period. Several investigators22,27-29 suggested that PCBs in the sediment may not be associated with active sites evenly. Some PCBs are loosely bound and can be removed easily, and other PCBs are tightly bound and difficult to extract. To deal with such desorption systems, the use of a two-step model has been suggested30 in which solutes are divided into two fractions and each is governed by different mass-transfer parameters or mechanisms. At least two more parameters, the ratio of the two fractions and a new mass-transfer parameter, have to be introduced in a two-step model, making this model more

400


complicated. Alternatively, the two-step desorption processes are simulated in this study by dividing PCBs into two fractions and applying the same model to each fraction but employing different diffusion coefficients (Dpi). This simulation treats the fast- and slow-desorbing PCBs as two different pseudocompounds with no interaction with each other, whereas for the two-step model, the two fractions differ only by the intraparticle masstransfer process. Similar to the two-step model, three parameters are employed in this simulation (a diffusion coefficient for the fast-desorption PCBs, Dp1, a diffusion coefficient for the tightly bound PCBs, Dp2, and the initial concentration of the tightly bound PCBs, q02). Given the conditions of operation encountered in this study, an order of magnitude analysis shows that the axial dispersion can be neglected in the differential mass balance equation for the fixed bed. Also, as shown for similar systems,31-33 the linear driving force approximation is reasonable to describe intraparticle diffusion, for which a spherical particle approximation is employed. These approximations permit the governing equations for the fixed-bed SFE system to be written as

∂C u ∂C 1 - ∂q j + + F )0 ∂t ∂z p ∂t

(1)

∂q j 15Dpi (KC - q j) ) ∂t r2

(2)

and

q′i(t) ) q0i -

QBq0i

[

w(1 + BK)

t+

1 (e-Ai(1+BK)t Ai(1 + BK) 1)

]

when t < L/u (8)

and

qi(t) ) q′i(t) +

QAiBq0i

e-(FbAiKL/u)

w(1 + BK)

(x

BKe-Ai(1+BK)(τ-L/u)eAiBKx)I0

t ∫L/u ∫0τ-L/u(e-Ax +

)

4FbAi2KL x dx dτ u when t g L/u (9)

Other symbols used in the above equations are

Ai ) 15Dpi/r02

(10)

B ) (1 - )Fp/

(11)

Fb ) (1 - )Fp

(12)

Q is the volumetric flow rate of SCFs (mL/s), K is the PCB partition coefficient (mL/g) at experimental conditions,24 L is the height of sediment bed, Fb is the bulk density of the bed (g/mL), and u is the superficial velocity of SCFs (cm/s). There are three adjustable parameters in the model: the lumped diffusion coefficients of pseudocomponents, Dp1 and Dp2 embedded in Ai, and the initial concentration of the pseudocomponent, q02.

0

4. Results and Discussion The initial and boundary conditions are

C(z,t)0) ) 0

(3)

q j (z,t)0) ) q0

(4)

C(0,t) ) 0

(5)

Dpi are the lumped diffusion coefficients of the pseudoPCB components for the fast (i ) 1) and slow (i ) 2) desorption periods given by

Dpi )

Dei 5DeiKFp +1 r0kf

(6)

Here, K (mL/g) is the previously developed PCB partition coefficient24 for a linear isotherm, Dei is the pseudoeffective diffusion coefficient, kf is the mass-transfer film coefficient, and r0 is the particle radius. Analytical solution23 yields mi(t), the total amount (µg) of PCB pseudocomponent i in the effluent at a given extraction time t. A mass balance yields the average PCB concentrations of pseudocomponent i in the bed:

qi(t) )

wq0i - mi(t) mi(t) ) q0i w w

(7)

where w is the soil weight (g) and q0i is the initial PCB concentration in the sediment of the fast (i ) 1) and slow (i ) 2) pseudocomponents. Substituting for mi(t) yields

4.1. Laboratory Scale. The PCB desorption data for the two SCFs show similar trends, a near-linear fast desorption period followed by a slow desorption (Figure 3). The difference between the two SCF systems is that the initial desorption rate is faster and the final PCB residual concentration is much lower for the CO2/MeOH system than those for the pure CO2 system. The presence of methanol as a cosolvent not only increases the PCB desorption rates but also reduces the final PCB residual concentrations in the sediment probably because of the strong interactions between methanol and the active sites of soil matrixes. After 60 min of extraction, PCB residual concentrations (∼4 ppm for the CO2/MeOH system and ∼50 ppm for the CO2 system, as shown in Table 2) suggest that 5% MeOH as a cosolvent is necessary to achieve our goal of reducing the PCB concentration to less than a 5 ppm level. The low flow-rate effects for the long-time extraction periods suggest that PCB desorption is controlled only by an intraparticle mass-transfer process during these periods. Considering that the remediation goal is determined only by the final PCB concentrations, the observed flow-rate effects also indicate that, for a singlebed extraction system, the lower SCF flow rate investigated here (0.018 mol/min of CO2) can reach the same remediation goal as the higher flow rate does while keeping the operation cost low. In addition, because these results do not show significant differences at long extraction time, further reduction of the SCF flow rate and, consequently, the operational cost is possible. The initial flow-rate effects observed here could be important for the overall extraction efficiency in a multibed system. A multibed extraction system would permit the use of lower SCF flow rate or shorter extraction time to achieve


Figure 3. Laboratory-scale PCB desorption data (initial period only) vs bed volume of SCF at 323 K and 118 bar. Comparison between pure supercritical CO2 and supercritical CO2/MeOH systems.

the same remediation goal and, therefore, is practically attractive. Theoretically, the significant flow-rate effects on desorption rates indicate that the process is controlled by either an equilibrium, a film mass transfer, or the combination of both phenomena. An approach to illustrate the controlling mechanism of the PCB desorption process is to plot the desorption data versus the amount of effluent SCF (bed volume), as shown in Figure 3. For the pure CO2 system, an equal amount of supercritical CO2 removes roughly the same amount of PCBs at both flow rates, indicating that the PCB desorption process is similar to an equilibrium-controlled process and therefore the use of a lower flow rate will not improve the CO2 usage efficiency. In contrast, noticeable mass-transfer effects are demonstrated in Figure 3 for the CO2/MeOH system where the same amount of SCF at the higher flow rate (short residence time) removes a smaller amount of PCBs than at the lower flow rate (longer residence time). Therefore, for the CO2/MeOH system, the use of the lower flow rate will improve the SCF usage efficiency. In the discussion of PCB partition equilibrium data,24 it was concluded that, at equilibrium, low-chlorinated PCBs are likely to be removed more easily from the sediments than the higher chlorinated congeners. Among the 209 PCB congeners, 16 PCB congeners are listed as the most environmentally threatening POPs.34 Because the extraction efficiency of the total PCBs has been employed for the evaluation of the SFE of PCBs, there remains a concern over the potential relative accumulation of the most environmentally threatening PCB congeners during the SFE processes. Because it is observed that all of the PCB congeners are extracted quite evenly during the process, it is possible to treat the PCB mixture as a single PCB pseudocompound during modeling analysis of PCB desorption data (Fig-

ure 2). This result also implies that the overall extraction process is not an equilibrium-controlled process. 4.2. Bench Scale. Two different CO2 flow rates of 2.11 and 4.22 mol/min, corresponding to the unit-soilbased flow rates of 0.046 and 0.092 g of CO2/min‚(g of soil) and superficial velocities of 0.065 and 0.13 cm/s, respectively, are investigated in the bench scale. The unit-sediment-based flow rates of bench-scale experiments are ∼2.5 times smaller than those of the laboratory-scale experiments [0.133 and 0.227 g of CO2/min‚ (g of soil)]. The corresponding SCF superficial velocities, however, are larger than those of the laboratory-scale studies for the CO2/MeOH system (0.043-0.073 cm/s). For each flow rate, three experiments are conducted at different desorption times (25, 40, and 60 min). The average PCB residual concentrations for all experiments are shown in Table 2. It is found that the PCB concentration in the sediments can be reduced from 1840 ppm to less than 5 ppm in ∼40 min for both flow rates. The final PCB concentrations after 60 min of extraction are around 3 ppm, which is comparable with the final PCB concentrations of ∼4 ppm for the laboratory-scale experiments when CO2/MeOH is used as the SCF. This result suggests that the scale-up factors are not significant over this range on the desorption processes of PCBs from real-world SLRS. The distribution patterns of PCB congeners in each layer are also analyzed and compared with the initial PCB patterns for all of the bench-scale experiments. Similar to the laboratory-scale results (Figure 2), no significant shift of PCB congener distribution patterns has been found. 4.3. Model Results. The evaluation of eqs 8 and 9 for both pseudocomponents is accomplished by using Mathematica 4.0, a commercial technical computing software (Wolfram Research, Inc.). A simplex searching method is used for the optimization of the three parameter values.23 The object function of the optimization is defined as n

∑ i)1

( ) cal qex i - qi

qex i

2

f Minimum

(13)

where n is the total number of experimental points. a. Laboratory Scale. The fitting parameters are listed in Table 3. The two-step simulation covers all of the desorption curves reasonably well at all conditions. The average absolute relative deviation (AARD ) |Ccal _ C exp|/Cexp) between experimental residual PCB concentration data and modeling results is less than 7% for all experiments except the CO2/MeOH high-flow-rate experiment, for which the AARD is 11.3% (Table 3). As shown in Table 3, the initial amounts of the slowdesorbing PCBs (q02) are in the range of 164-193 ppm (8.9-10.5% of the initial total PCBs) for the pure CO2 system and 17.6-19.3 ppm (0.96-1.05% of the initial total PCBs) for the CO2/MeOH system. The difference of 1 order of magnitude for q02 values between the two SCFs indicates that the presence of 5% MeOH as a cosolvent makes ∼90% of the slow-desorption PCBs easily accessible, possibly by competing with the adsorbed PCBs for the active sites. This result explains why the use of 5% MeOH can reduce the final PCB concentrations significantly. For each SCF system, the difference between the q02 values at two different flow rates is relatively small, which is understandable

402


Table 2. Laboratory- and Bench-Scale Experimental and Model Results (Residual ppm)a CO2 System (Laboratory Scale) extraction time (min) FR1 ) 18 mmol/min, SW1 ) 6.17 g

exp model exp model

FR2 ) 31 mmol/min, SW2 ) 6.30 g

0

1

3

6

10

15

22

30

40

60

1972 1972 1995 1995

1908 1789 1757 1610

1502 1211 883 849

836 661 338 360

281 318 197 187

165 169 152 143

119 114 120 121

95 94 95 101

76 77 78 82

52 52 56 53

CO2/MeOH System (Laboratory Scale) extraction time (min) FR1 ) 18 mmol/min, SW1 ) 6.17 g

exp model exp model

FR2 ) 31 mmol/min, SW2 ) 6.30 g

0

0.5

1.5

3.5

7.5

15

25

40

60

2210 2210 2169 2169

2137 2040 1978 1973

1467 1468 1221 1212

524 517 316 397

36 36 57 46

13 12 15 13

9.4 9.5 8.1 9.3

5.8 6.5 5.3 5.9

4.2 3.9 3.8 3.3

CO2/MeOH System (Bench Scale) extraction time (min) FR1 ) 2.11 mol/min, SW1 ) 2000 g FR2 ) 4.22 mol/min, SW2 ) 2000 g a

exp model exp model

0

25

40

60

1840 1840 1840 1840

7.1 7.0 5.6 5.4

4.9 5.0 3.8 4.0

3.3 3.3 2.8 2.7

FRi: molar flow rate of SCF. SWi: sediment weight.

Table 3. Parameters for Model Data Presented in Table 2a system CO2 (laboratory scale) CO2/MeOH (laboratory lcale) CO2/MeOH (bench scale)

FR1 FR2 FR1 FR2 FR1 FR2

AARD (%)

q02 (ppm)

Dp1 × 107 (cm2/s)

Dp2 × 108 (cm2/s)

Deb × 106 (cm2/s)

Dec × 106 (cm2/s)

6.9 4.7 3.8 11.3 1.6 4.5

163.7 192.7 17.6 19.3 11.6 8.7

4.44 7.15 17.3 9.26 16.5 13.0

2.00 2.22 2.63 3.04 2.34 2.06

1.34 1.83 3.48 1.65 3.01 2.05

2.40 2.74 5.24 2.13 4.00 2.34

a D : lumped diffusion coefficient for the fast-desorbed PCBs. D : lumped diffusion coefficient for the slow-desorbed PCBs. q : initial p1 p2 02 concentration of slow-desorbed PCBs. De: effective diffusion coefficient for the fast-desorbed PCBs. Calculated based on De ) Dp(10KFp/ b 1/3 0.6 c Sh + 1). The Sherwood number (Sh) is calculated by Sh ) 2 + 1.1Sc Re with Sc ) µ/FfDm. The Sherwood number (Sh) is calculated by Sh ) 0.38Re0.83Sc1/3 (ref 35).

because the flow rate of SCF is not expected to affect q0i significantly. It is observed that the fast-desorbing PCBs can be removed in ∼10 min in the CO2/MeOH system. The lumped diffusion coefficients obtained for the slow-desorbing PCBs (Dp2 in Table 3) are in the range of (2-3) × 10-8 cm2/s for all experiments. The values of De of slow-desorbing PCBs for the two different SCF systems are also very close, even though there is a 1 order of magnitude difference between the q02 values in the two SCF systems. This result, in conjunction with the fact that the two values of q0 obtained are almost constant, indicates that the linear driving force model developed and the two-step simulation employed interpret the physical mechanisms of PCB desorption processes quite well, even though the simulation is only an approximation of a two-step model. The values of Dp for the fast-desorbing PCBs (Dp1 in Table 3) are about 1-2 orders of magnitude larger than those obtained for the slow-desorbing PCBs, falling in the range of 4 × 10-7-2 × 10-6 cm2/s. Considering the influence of the SCF flow rate on the value of Dp, the corresponding effective diffusion coefficients are also calculated. Overall, the values of De for the fastdesorbing PCBs are in the range of (1.34-5.24) × 10-6 cm2/s, similar to those reported in the literature.35-37 b. Bench Scale. The bench-scale PCB desorption data are analyzed based on eqs 8 and 9 using the same two-step simulation. All model-related properties are the

same as those listed in Table 1 except that the extractor radius is 3.47 cm and the SCF flow rates are 2.47 and 4.94 mL/s (2.11 and 4.22 mol/min, respectively) for the bench-scale experiments. Similar to the laboratory-scale studies, congener distribution patterns in the soil, initially and after extraction, show no significant shift due to preferential desorption based on the congener molecules. This result is for each of four layers of sediments, individually analyzed, into which the bed is equally divided. The comparisons between experimental data and the simulation are shown in Figure 4. Because all of the experimental data obtained are at long time periods, the simulation gives a better fit than the laboratory-scale experiments. The resulting AARD is 1.6% for the low-flow-rate experiment and 4.6% for the high-flow-rate experiment. It should be pointed out that, however, because of this lack of constraint from the data of the short time period, these simulating results may not reflect the real desorption processes well, especially during the fast desorption period. As a result, the parameters obtained here may not be comparable with those obtained from laboratory-scale experiments. Still, it is found that the model parameters for the benchscale experiments are in reasonable agreement with those obtained from the laboratory-scale experiments for the CO2/MeOH system (Table 3). This result demonstrates that the linear driving force model employed and the two-step simulation interpret the PCB desorption process well.


Figure 4. Bench-scale PCB desorption curves from real-world SLRS at 323 K and 118 bar for CO2/MeOH (q0 ) 1840 ppm, q02 ) 11.6 ppm, Dp1 ) 1.65 × 10-6 cm2/s, and Dp2 ) 2.34 × 10-8 cm2/s) and model prediction using the average parameters obtained from the laboratory-scale data (Dp1 ) 1.33 × 10-6 cm2/s, Dp2 ) 2.83 × 10-8 cm2/s, and q02 ) 18.44 ppm).

As an effort to further evaluate the model and the two-step simulation method, the average values of the three parameters (q02 ) 18.44 ppm, Dp1 ) 1.33 × 10-6 cm2/s, and Dp2 ) 2.83 × 10-8 cm2/s) obtained from the laboratory-scale desorption data for the CO2/MeOH system are directly used to predict the bench-scale desorption data. The predicted results and the experimental data are compared in Figure 4. Observable deviations (30-60%) at low concentrations between predicted data and experimental data are found. Still, considering that the involved PCB residual concentrations (2-10 ppm) are much smaller than the initial PCB concentration (1840 ppm) and that the precise model prediction of these small residual concentrations at long extraction time is very difficult, the predicted results are acceptable. Figure 5 compares the predicted effluent PCB concentration profile of the lower flow rate bench-scale experiment based on the above-mentioned average laboratory-scale parameters with that obtained from the optimized bench-scale parameters (Table 3, lower flow rate). Because the optimized parameters fit the experimental data very well (Figure 4), the corresponding effluent PCB concentration profile is treated as the real experimental effluent PCB concentration profile. Similar results are obtained with the higher flow rate data. It is shown in Figure 5 that the two profiles agree with each other over the entire time span, suggesting that the prediction of the bench-scale desorption data based on laboratory-scale parameters is quite good. 5. Conclusions PCB desorption experiments from real-world SLRS are conducted in laboratory- and bench-scale SFE units under conditions of 118 bar and 323 K. The presence of 5% (mole) methanol in supercritical CO2 increases PCB desorption rates and reduces final PCB residual concentrations in sediments. The PCB concentration in the

Figure 5. Comparison of the model PCB concentrations in the effluent SCFs for 2.11 mol of SCF/min (bench-scale experiments).

sediment can be reduced from 2200 ppm to less than 10 ppm (99.5% extraction efficiency) in 25 min of extraction time and to less than 5 ppm (99.77% extraction efficiency) in 60 min, compared with the final PCB concentrations of ∼50 ppm after 60 min of extraction for the pure CO2 system. Bench-scale desorption experiments show that the PCB concentration in SLRS can be reduced from 1840 ppm to less than 5 ppm (more than 99.73% extraction efficiency) in 40 min. The final PCB concentrations suggest that the scale-up effect is not significant on the desorption process of PCBs from real-world SLRS. The small flow-rate effect during the long-time extraction period suggests that this step of PCB desorption is mainly controlled by intraparticle diffusion and further reduction of the flow rate is possible. A noticeable effect of the SCF flow rate is found in the fast desorption periods for both SCFs studied, though they behave differently in the two SCFs. For the pure CO2 system, the fast desorption period is similar to the partition equilibrium-controlled process and, therefore, demonstrates more a significant flow-rate effect. For the CO2/MeOH system, strong external mass-transfer effects are found for the fast desorption period. The PCB desorption data are analyzed using a linear driving force model with a two-step simulation, an approximation of a two-step desorption model. As expected, no significant flow-rate effects have been found on the values of the effective diffusion coefficients of the slow-desorbing PCBs, indicating that the linear driving force model and the two-step simulation interpret the PCB desorption processes quite well. The modeling analysis of the bench-scale data produces parameters comparable to those obtained from the laboratory-scale studies. The parameters obtained from laboratory-scale desorption data also are employed to predict the bench-scale data and give reasonably good results.

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Received for review February 6, 2003 Revised manuscript received June 30, 2003 Accepted August 20, 2003 IE0301177

Desorption of Polychlorinated Biphenyls from Contaminated St

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