ARTICLE pubs.acs.org/est
Simultaneous Estimation of GlassWater Distribution and PDMSWater Partition Coefficients of Hydrophobic Organic Compounds Using Simple Batch Method Min-Kai Hsieh,†,§ Chung-Te Fu,†,‡ and Shian-chee Wu*,† † ‡
Graduate Institute of Environmental Engineering, National Taiwan University, 71 Chou Shan Road, Taipei City 106, Taiwan Department of Environmental Engineering, Vanung University, 1 Vanung Road, Chungli City 325, Taiwan
bS Supporting Information ABSTRACT: A simple batch method by use of refilling and nonrefilling experimental procedures and headspace solid phase microextraction was applied to simultaneously obtain the glasswater distribution coefficients (KGW) and polydimethylsiloxane(PDMS)water partition coefficients (KPW ) of hydrophobic organic compounds (HOCs). The simple batch method takes into consideration the glass-surface bound HOCs and the corresponding equilibrium distribution of HOCs among the glass, water, headspace, and polydimethylsiloxane (PDMS). The KPW and KGW values of 53 PCB congeners were determined. The glassbound fraction predominated over other fractions for highly chlorinated PCBs. Ignoring glass adsorption and assuming a complete mass balance could thus substantially underestimate the KPW for HOCs in traditional work. Good linear correlations of logα (the overall mass transfer rate constant) vs logKPW, logKPW vs logKOW, and logKGW vs logKOW were observed, with logα = 0.91 logKPW + 1.13, R2 = 0.93; logKPW = 1.032 logKOW 0.493, R2 = 0.947; and logKGW = 0.93 logKOW 2.30, R2 = 0.90. The KPW values from this study were compared with those in the literature. With an account of the glass adsorption, the accuracy of the KPW determination and the estimation of the dissolved concentration in water for highly hydrophobic compounds can be significantly improved.
’ INTRODUCTION Solid phase microextraction (SPME), initially introduced as a sampling technique for analyzing trace chemicals two decades ago,1 has been extended to measure the concentrations of truly dissolved hydrophobic organic compounds (HOCs) in natural water samples by using, for instance, a polydimethylsiloxane (PDMS) coated fiber as a solid phase sorbent.24 The dissolved concentration of a HOC has been used to evaluate its bioavailability to aquatic organisms. It is usually measured by placing a short piece of PDMS coated fiber into a water sample to allow the HOC to partition into the PDMS phase until equilibrium is reached.57 The concentration of a HOC in the PDMS phase is then analyzed and converted to the freely dissolved concentration through the HOC’s PDMSwater partition coefficient (KPW). Usually, only a negligible amount of the HOC is extracted from the sample to PDMS phase.8,9 Since the freely dissolved concentration of a HOC in water is determined via KPW, the accuracy of the measurement depends critically on the accuracy of KPW. It has been recognized, however, that the common method for measuring KPW of a HOC by analyzing the HOC concentration in water via a solvent extraction of the entire batch reactor fails to take into account r 2011 American Chemical Society
the HOC sorption onto system surfaces, such as those of polytetrafluoroethylene-coated (PTFE) stirrers and glass container walls.1013 The sorption of HOCs onto PTFE or glass surface may result in a significant depletion of HOCs in water, especially for HOCs of high octanolwater partition coefficients (KOW).13 Thus, traditional approaches, which ignore the surface sorption, tend to underestimate KPW, with the extent usually increasing with increasing KOW. Other potential causes of poor KPW include insufficient experimental time toward equilibrium and improper assumption of negligible HOC depletion in water, as discussed in more detail in recent literature.14 There have been attempts to modify traditional methods or develop more advanced approaches to establish more accurate KPW values for HOCs.9,1522 The methods of special interest are those that eliminate the glass adsorption effect, such as the total system mass balance,16,22 cosolvent models,17 the flow-through system,18 the flow-through kinetic system,19 the constant source method,20 Received: June 25, 2010 Accepted: August 14, 2011 Revised: August 12, 2011 Published: August 15, 2011 7785
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and the glass-ware-excluded aqueous extraction. 21 The logKPW values obtained by these methods show an improved linearity with a nearly unity slope with their logKows when compared to those obtained by traditional approaches. However, significant discrepancies of KPW values for PCBs of high KOW were still observed.14 Further, although these methods have been developed to eliminate the influence of the glass adsorption, they provide no means to quantify the glassadsorption effect. As HOCs, PCBs consist of 209 congeners, with 1 to 10 chlorines attached to biphenyl; they are carcinogenic and bioaccumulative. 23 Although the use and production of PCBs is currently banned by most countries, large amounts of PCBs have been spread to environmental media due to improper earlier disposal.24 An accurate measurement of freely dissolved PCB concentrations in natural water is critical to evaluation of the human exposure and environmental health risks. Besides adverse health impacts, PCBs cover a wide range of hydrophobicity, that is, a wide range of KOW.25 Thus, a pursuit of accurate KPW values for PCBs has an important bearing on the quantification of their truly dissolved concentrations by using PDMS fibers and on the establishment of a general relationship between logKOW and logKPW for all HOCs. The KOW values of all PCB congeners have been relatively well established,25 and the KPW values of many PCB congeners have been established by using advanced approaches taking into account the glass adsorption. 17,21,26 However, the glass adsorption effect of PCBs has not been well quantified. A better predictive relationship between logKPW and logKOW is timely needed for PCB congeners as well as for other HOCs. The purpose of this study was to develop a simple approach to simultaneously estimate KPW and KGW of PCBs using experimental data from a glasswaterheadspacePDMS system. The mass transfer kinetics and the equilibrium distribution among glass surface, water, headspace, and PDMS were considered. Overall mass transfer rate coefficients of PCBs were also studied. The obtained KPW values were evaluated by comparing the relationship of logKPW vs logKOW derived from the present and literature data.
’ MATHEMATICAL APPROACH Kinetics of HOCs Mass Transferring. A first-order mass
transfer model has been developed to study the sorption kinetics of a HOC in a waterPDMS system.29,30 When the glass surface is considered with the assumption that (1) a linear relation exists between the surface density and the concentration of a HOC at low aqueous concentration (examined in the Supporting Information, SI S-6), (2) the mass transfer rate-determining step is the diffusion in the boundary layer near PDMS21,30 (i.e., the headspace diffusion layer near PDMS in this study), and (3) the headspace capacity of the HOC is negligible in the system (verified in SI S-3). The previously proposed mass-transfer model29 was modified (the derivation of equations can be found in SI S-1), which is expressed as CP ¼ CP, t f ∞ ð1 eαt Þ
ð1Þ
where CP is the HOC concentration in PDMS (mol/μm3) at time t, CP,tf∞ is CP at equilibrium (mol/μm3), and α is the overall mass transfer rate (s1). In eq 1, CP,tf∞ and α are
defined as CP, t f ∞ ¼
M KGW 1 AG þ VW þ VP KPW KPW
KGW 1 AG þ VW þ VP KPW KPW KGW 1 KPW VP AG þ VW KPW KPW
ð2Þ
kA KAW AP α¼
ð3Þ
where KGW is the glasswater distribution coefficient (μm3/μm2), KAW is the airwater partition coefficient (μm3/μm3), KPW is the PDMSwater partition coefficient (μm3/μm3), M is the total molar mass of the HOC (mol), AP is the surface area of PDMS (μm2), AG is the surface area of the glass wall (μm2), VW is the aqueous-phase volume (μm3), VP is the volume of PDMS (μm3), and kA is the mass transfer rate constant in the headspace diffusion layer near PDMS (μm/s). At equilibrium, the relationship of the HOC concentrations in the system can be expressed as CW ¼
CP CG CA ¼ ¼ KPW KGW KAW
ð4Þ
where CW is the HOC concentration in the water phase (mol/μm3), CA is the concentration in the head space (mol/μm3), and CG is the HOC surface concentration on the glass surface (mol/μm2). Determination of KPW and KGW with Refilling and Nonrefilling Experiments. KPW and KGW values of a HOC can be determined through two parallel experiments: the refilling experiment and the nonrefilling experiment. Similar to the kinetic study, a glasswaterheadspacePDMS system was employed. In the refilling experiment, when the first equilibrium is reached in the system, PDMS and water phases are replaced with clean materials for the next equilibrium cycle. The procedure can be repeated for several times. In each cycle, total HOC mass in the system is equal to the mass retained on the glass surface from the previous cycle, since only the glass surface has not been replaced. Thus, the mass balance in each cycle can be written as CG, n1 AG ¼ CW, n VW þ CG, n AG þ CP, n VP
ð5Þ
where the subscripts n and n-1 denote the nth and n-1th equilibrium cycle during the experiment. From the equilibrium relationships given in eq 4, the following relationship can be derived (see SI S-2) R
CP, n KGW AG ¼ CP, n1 KGW AG þ VW þ KPW VP
ð6Þ
where R is the ratio of the HOC equilibrium concentrations in PDMS from two consecutive cycles in the refilling experiment. In essence, the ratio is equal to the ratio of the HOC response factors per unit volume of PDMS (such as the peak area) observed with an analytical instrument, such as a gas chromatograph. The parallel nonrefilling experiment is similar to the refilling experiment except that the aqueous phase is not replaced in each cycle. Thus, in each cycle the total mass of HOC in the system is the sum of the mass on the glass surface and the mass in water phase retained from the previous cycle. Thus, the mass balance 7786
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Table 1. PCBs to PDMS Overall Mass Transfer Coefficient (α), PDMWWater Partition Coefficients (KPW), and GlassWater Distribution Coefficients (KGW) Obtained from This Study log KOWa
a
log α 1
(α: s )
log
log KGW
KPW
(KGW: μm /μm ) 3
PCB18
5.24
ND
4.91
ND
PCB16,32
5.16, 5.44
ND
5.12
ND
PCB28,31
5.67
3.56
5.17
ND
PCB33,53 PCB22
5.60, 5.62 5.58
3.55 3.70
5.18 5.30
ND ND
PCB52
5.84
3.84
5.48
2.98
PCB47,48
5.85, 5.78
3.70
5.49
3.02
PCB44
5.75
3.94
5.44
3.49
PCB41,71
5.69, 5.98
ND
5.49
3.33
PCB70
6.20
ND
5.79
3.32
PCB66
6.20
ND
5.70
3.28
PCB95 PCB56,60
6.13 6.11
ND 4.28
5.77 5.86
3.52 3.58
PCB101
6.38
4.30
6.01
3.57
PCB99
6.39
4.31
6.17
3.58
PCB83
6.26
4.42
6.02
3.24
PCB97
6.29
4.47
6.05
3.23
PCB87
6.29
4.48
6.19
3.34
PCB85
6.30
4.44
6.38
3.58
PCB110 PCB151
6.48 6.64
4.54 4.56
6.03 6.31
3.52 3.75
PCB135
6.64
4.60
6.48
3.48
PCB149
6.67
4.64
6.42
3.84
PCB118
6.74
4.81
6.23
3.66
PCB146
6.89
4.82
6.66
4.07
PCB153
6.92
4.85
6.62
4.07
PCB105,132
6.65, 6.58
4.91
6.40
3.93
PCB141,179 PCB138
6.82, 6.73 6.83
4.94 5.03
6.73 6.61
4.20 4.09
PCB163
6.99
5.08
6.56
4.13
PCB158
7.02
5.03
6.83
4.28
PCB182,187
7.20, 7.17
5.01
6.96
4.44
PCB183
7.20
5.02
6.26
4.41
PCB128
6.74
5.14
6.61
4.11
PCB185
7.11
5.07
6.86
4.36
PCB174 PCB177
7.11 7.08
5.13 5.10
7.04 7.02
4.52 4.53
PCB171,202
7.11, 7.24
5.21
PCB180 PCB170
7.36 7.27
5.20 5.25
6.78 6.89
4.40 4.53
6.82
4.55
PCB201
7.62
5.18
7.06
4.83
PCB203
7.65
5.17
7.09
4.83
PCB195
7.56
5.20
6.89
4.81
PCB194
7.80
5.26
6.79
4.77
where C0 denotes the HOC concentration in the nonrefilling experiment. Similar to the refilling experiment, the following relationship can be derived through eq 4 (see SI S-2) r
2
C0P, n KGW AG þ VW ¼ 0 CP, n1 KGW AG þ VW þ KPW VP
ð8Þ
where r is the ratio of the HOC equilibrium concentrations in PDMS of two consecutive cycles in the nonrefilling experiment. Equations 6 and 8 are two-variable linear equations, in which KPW and KGW can be derived (see SI S-2) KPW ¼
VW ð1 rÞ VP ðr RÞ
ð9Þ
KGW ¼
VW R AG ðr RÞ
ð10Þ
If a different PDMS volume (V’) is used in the nonrefilling experiment, eqs 9 and 10 should be modified accordingly as (see SI S-2) KPW ¼
VW ð1 rÞ 0 V P rð1 RÞ VP Rð1 rÞ
ð11Þ
KGW ¼
VW RðV 0P r VP r þ VP Þ AG ½V 0P rð1 RÞ VP Rð1 rÞ
ð12Þ
’ MATERIALS AND ANALYTICAL METHODS
Data adopted from Hawker and Connell (1988).
equation for the nonrefilling experiment is C0W, n1 VW þ C0G, n1 AG ¼ C0W, n VW þ C0G, n AG þ C0P, n VP ð7Þ
Experimental Apparatus, PDMS Fibers, and Chemicals. A system with PDMS in headspace has the advantage of preventing the sorption of other nonvolatile compounds, which might carry species other than freely dissolved target compounds onto PDMS.27,28 Although in this study the PCB solutions were prepared with pure water, the method was aimed to be applicable to environmental media such as river water, sediment pore water, etc. Thus, the system with PDMS in the headspace is employed. Glass bottles with volume of approximately 2 and 5 L (with the inner glass surface of approximately 860 and 1600 cm2, respectively) made of borosilicate were used as batch reactors (Schott Duran, Germany). Disposable bulk PDMS coated fibers were obtained from Prime Optical Fiber Co. (Taiwan); the fiber has a 200 μm central-core diameter and a 16.5 μm coated PDMS film thickness, thus giving a volume of 0.112 μL per centimeter. The PDMS fibers were cut into desired lengths by clean sharp knife and were rinsed with analytic grade ethanol and baked at 250 °C for one hour before service. PCBs stock aqueous solutions, with a total PCB concentration of 15 μg/L, were prepared by spiking 1-mL 30 mg/L mixed Aroclor 1242/1254/ 1260 (Supelco, St. Louis, MO), with the ratio of 1:1:1, to 23 mL of ethanol and further diluted to a volume of 2-L with distilled water. The PCB congener composition in Aroclors was obtained from Agency for Toxic Substances and Disease Registry31 and can be found in SI S-8. All experiments were conducted at room temperature (approximately 25 °C). Kinetics and Refilling and Nonrefilling Experiments. In the kinetics study, 8 glass bottles containing 2 L each of the aqueous solution of PCBs at 0.1875 μg/L were prepared. Each glass bottle had 0.4 L headspace in which 1 cm PDMS fiber was placed for either 1, 3, 6, 12, 24, 48, 91, or 188 h and then removed from the 7787
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Figure 1. PCBs capacity fraction on glass surface, water, headspace, and PDMS in the 2 L batch reactor.
bottle for PCB analysis with gas chromatography (a schematic of the experimental apparatus used can be found in SI S-9). To reduce the sorption loss to laboratory wares, the bottle caps with PTFE coating were lined with aluminum foil, and naked metal magnetic stirrers were used for agitation. While the formation of glass particles from scratches by the metal stirrer might be of concern, no glass particles were visually observed in the 4-day test period. The experimental setup for refilling experiment was similar to that of the kinetic study. However, a larger glass bottle containing 5 L of water with the PCB concentration at 0.1875 μg/L and 1 L headspace was utilized. A 2-cm PDMS fiber (the PDMS volume = 0.224 μL) was placed in the headspace. After a 4-day exposure, the fiber was removed for PCB analysis, and the aqueous solution was then discarded. Distilled water of 5 L (with no PCBs) was then injected to the same glass bottle, and a new 2-cm long PDMS was placed in the headspace for another 4-day equilibration. This process was repeated 3 times. Similar procedures were performed for nonrefilling experiments except that the water solution was not replaced and twelve 4.5-cm long PDMS fibers (PDMS volume = 6.05 μL) were used in each 4-day test. The reason of using different PDMS fiber length for nonrefilling experiment was to enhance the analytical sensitivity. PCBs Analysis. PDMS fibers, after being exposed in the kinetic and refilling/nonrefilling experiments, were rinsed with distilled water and wiped with clean tissues and inserted into the GC inlet for analysis. The GC (Hewlett-Packard 5890 series II) was equipped with a 63Ni electron capture detector (ECD) and a 30 m 0.25 mm 0.25 μm, 5% phenyl phase fused silica capillary column (Rtx-5mx, J&W). For PCB analysis, nitrogen was used as the carrier gas, the column flow rate was set at 1 mL/ min. The oven temperature was programmed as the following: 80 °C for 4 min, to 180 at 15 °C/min, to 265 at 2 °C/min, to 295 at 25 °C/min and holding for 2 min. The injector was set at 250 °C with a splitless mode, and the detector was set at 295 °C. Fifty-three PCB congeners and forty-four peaks (see Table 1) were identified and confirmed by an Agilent 6890/5973 GC/MS (Agilent, Santa Clara, CA). The concentrations of PCBs in PDMS fibers were estimated with the calibration curve obtained by a series of reference Aroclor solutions in ethanol by using liquid injection in the same GC condition. After a series of careful pretests, using a Flip Top Inlet Sealing System (Agilent, Santa
ARTICLE
Figure 2. Double-log plot of overall mass transfer rate coefficients (α) and PDMSwater partition coefficients (KPW) of PCBs (logα = 0.91 logKPW + 1.13, R2 = 0.93).
Clara, CA), directly inserting the fiber into GC under the splitless mode without cooling was adopted as the standard injection procedure. Mass Transferring Constant, KPW, and KGW. From the kinetic study, values of mass transfer coefficient (α) were obtained through a regression analysis of experimental data with eq 1. The coefficients of correlation of the regression analysis were also determined. From refilling and nonrefilling experiments, three R and three r values were determined for most PCBs analyzed since 3 cycles were performed for each of both experiments, that is, n ranged from 1 to 4 in eqs 6 and 8. The average values and standard deviations of R and r for each PCB congener were determined, and the averaged R and r were then used to determine KPW and KGW by eqs 11 and 12.
’ RESULTS AND DISCUSSION Values of α, KPW, and KGW. Values of α, KPW, and KGW in a log scale obtained from kinetic studies and refilling/nonrefilling experiments are presented in Table 1 (the associated statistic analyses of α, KPW, and KGW can be found in SI S-4 and S-5). Table 1 shows that the mass transfer rate coefficient decreases with increasing hydrophobicity of the PCB. Within 4 days most congeners (48 of 53) reached more than 90% equilibrium status, and all PCBs reached more than 85% equilibrium status. Values of logKPW and logKGW of some PCBs show large standard deviation (SI Table S-2). The deviation can be traced back to the variation of R and r values (SI S-5). At higher cycles the retained PCBs in refilling and nonrefilling experiments had lower concentrations and at low concentrations the measurements are less accurate. Therefore, the results showed a large error at higher cycles. This is a limitation of the proposed simple batch method. A potential means to rectify this problem is to obtain replicate R and r values from different batches rather than the same batches with multiple cycles. he logKPW values of the 53 studied PCBs increases from 4.91 (PCB18) to 7.09 (PCB203) with increasing degree of chlorination. The logKGW of the 45 detected PCBs also increase from 2.98 (PCB52) to 4.83 (PCB201, PCB203) with increasing degree of chlorination. 7788
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Figure 3. Double-log plot of glasswater distribution coefficients (KGW) and octanolwater partition coefficients (KOW) of PCBs (logKGW = 0.93 logKOW 2.30, R2 = 0.90).
The PCBs capacity ratio in the glass surface, aqueous phase, and PDMS can be expressed as Glass :Water: PDMS ¼ KGW AG : VW :K PW VP
ð13Þ
The capacity fractions on the glass surface, water, and PDMS in the 2-L reactors used in the kinetic study are shown in Figure 1. The value of AG used for preparing Figure 1 was the total inner glass surface, most of which is in contact with water. Figure 1 reveals that the water phase dominated PCB distribution for light to medium PCB congeners, whereas the glass surface dominated the distribution for heavy PCB congeners. This explains why traditional approaches might overestimate CW and thus lead to underestimation of KPW especially for heavy congeners. The large glass adsorption found in this study indicates that the amount of chemicals on glass surfaces should not be ignored for very hydrophobic compounds, i.e., with logKow > 6.5, as reported in the literature.15,32,33 Correlation between α and KPW. The double-log plot of α vs KPW is presented in Figure 2. A nearly inverse linear correlation between logα and logKPW is observed (where logα = 0.91 logKPW + 1.13, R2 = 0.93, with a standard error (SE) of regression being 0.15, the SE of the slope 0.04, and a SE of the intercept 0.25). In kinetics experiments, the PCB mass in PDMS was no higher than 20% (Figure 1), so that eq 3 can be simplified as α=
kA AP KAW VP KPW
ð14Þ
where kA is DA/δA (DA is diffusion coefficient in headspace (μm2/s), and δA is the diffusion layer thickness of the headspace in contact with PDMS (μm)). Since AP, VP, and δA are constants, eq 14 can be expressed as log α = log KPW þ log DA þ log KAW þ B
ð15Þ
where B is a constant. It is observed that the logDA of PCBs varies within an order of magnitude,24 and the logKAW of PCBs varies within 0.5 log units without a clear trend.34 Since the logKPW vary over nearly 3 log units (Table 1), the logKPW dominates the variation of logα in eq 15. Thus, log α ≈ log KPW þ B0
ð16Þ
where B0 is a constant. The nearly inverse linear relation between logα and logKPW shown in Figure 2 is in agreement with eq 16. Indeed, if the rate-limiting (the slowest) step had been the
Figure 4. Double-log plot of PDMSwater partition coefficients (KPW) and octanolwater partition coefficients (KOW) of PCBs.
diffusion in PDMS, α should not have varied over an order of magnitude, since in this case α would be proportional to the molecular diffusivity in PDMS, the value of which does not vary more than an order of magnitude.21,35 Correlation between KGW and KOW. The double-log plot of KGW and KOW is shown in Figure 3, which shows that logKGW and logKOW are linearly related with nearly a unity slope (logKGW = 0.93 logKOW 2.30, R2 = 0.90, with the SE of regression being 0.18, the SE of slope 0.05 and the SE of intercept 0.32). The linear relationship between logKGW and logKOW indicates that the adsorption of PCBs on glass surfaces is a physical process strongly influenced by the hydrophobicity of the compound.36 Correlation between KPW and KOW. Figure 4 shows the logKPW values of PCBs obtained experimentally from this study (solid circle in the figure) and those reported in the literature.9,15,17,21,22,26,37 For a meaningful comparison, the KOW values used in Figure 4 are from a single source.25 The values from Smedes et al.17 (solid diamonds, average values of AlteSil polymers) were obtained from the analyses of data using cosolvent models, which have eliminated the effect of glass adsorption. The values of ter Laak et al.21 (solid triangles) were obtained via a direct measurement of PCB concentrations in PMDS and aqueous concentration without extracting PCBs on glass surfaces. The values of Yang et al.26 (solid squares) were from methods that consider the total system mass balance, which also have eliminated the glass adsorption effect. However, some PCBs might be lost during transferring samples to the extracting bottle. Also, the leveling-off of the relationship between logKPW and logKOW for highly chlorinated PCBs was also found. Nevertheless, the logKPW values obtained with advanced approaches are more consistent with the values from the present study. Other logKPW values (open squares, open diamonds, open triangles, asterisks, crosses, and Xs), which show varying trends with logKOW, e.g., a tailing-off, or even a curving-down after logKOW > 6.5, might be due to a neglect of glass adsorption or to inadequate equilibration time of the experimental methods employed. To illustrate the influence of neglecting glass adsorption on the logKPW estimation, let us image that a traditional approach (say, using 50 mL vials and assuming that the total PCB mass is in PDMS and water only) is used without considering the glass adsorption to estimate logKPW, the values obtained will be the those shown as open circles in Figure 4. This again implies that a significant underestimation of KPW values can occur when 7789
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’ ASSOCIATED CONTENT
bS
Supporting Information. This file contains derivation of first-order mass transferring kinetic model, derivation of equations for refilling and nonrefilling experiments, verification of negligible headspace capacity, experimental data of kinetic study, experimental data of refilling and nonrefilling experiments, verification of CG-CW linear relationship, values of KPW obtained in the present study and in the literature, PCB composition in Aroclors, and a schematic diagram of the experimental apparatus used in this study. This material is available free of charge via the Internet at http://pubs.acs.org.
’ AUTHOR INFORMATION Figure 5. Double-log plot of PDMSwater partition coefficients (KPW) and octanolwater partition coefficients (KOW) of PCBs, after deleting the 4 KPWs of PCBs with logKOWs larger than 7.5 and data of PCB183.
Corresponding Author
*Phone: +886-2-2362-9435. Fax: +886-2-2362-9435. E-mail: scwu@ ntu.edu.tw. Present Address §
the glass adsorption is not taken into account. Original data in Figure 4 can be found in SI S-7. Despite the nearly unity slope of the linear logKPW-logKOW relationship obtained in this study, the leveling-off of this correlation for heavy PCBs is observed. The leveling-off might potentially result from incomplete equilibrium for heavy PCBs. Although kinetic studies showed that heavy PCBs can reach 85% equilibrium within 4 days, a longer testing period might give better accuracy of the KPW measurement. By deleting the 4 KPWs of PCBs with logKOWs larger than 7.5 and data of PCB183, which has abnormally lowKPW, a new double-log plot of KPW and KOW is drawn (Figure 5). The logKPW values obtained in this study (solid circles) have a linear relationship with logKOW (logKPW = 1.032 logKOW 0.49, R2 = 0.95, the SE of regression being 0.15, the SE of slope 0.04, the SE of intercept 0.23). It has been found that noncompetitive and concentration-independent sorption prevailed in the absorption of hydrophobic organics in polymers, PDMS is one of which.30,38 Since the sorption of hydrophobic chemicals into PDMS is generally recognized as a partition process, the partition coefficients of PCBs in the PDMSwater system would be dominated by the hydrophobicity of the chemical. The free energy change for partitioning between water and octanol and that (the free energy change) for the partitioning between water and PDMS are all contributed mainly by the same excess free energy of the PCB in aqueous phase. Therefore, the free energy changes of these two processes for the same PCB congener should be varying parallel, that is, with a slope of 1 for the correlation between logKPW and logKOW. The small intercept of the correlation equation accounts for the minor difference of free energy change of partitioning into the polymer/solvent. For even heavily chlorinated and hydrophobic PCBs (higher KOWs), this linear relationship should still stand due to the still dominant high excess free energies in aqueous phase. On the other words, deviation from the linear logKPW and logKOW relationship could very probably be the results of difficulty on measuring very low aqueous concentrations of these compounds or the artifacts due to adsorption by the containers. Consequently, the observed logKPW-logKOW relation with nearly unity slope would better predict the KPWs for PCBs, including congeners with very high KOWs.
Water Resources Management and Policy Research Center, Tamkang University, 151 Yingzhuan Road, Danshui Dist., New Taipei City 251, Taiwan
’ ACKNOWLEDGMENT The authors are grateful to National Science Council, ROC, for its partial financial support on this study through grant number NSC 94-2211-E-002-003. The authors thank Dr. Cary T. Chiou and Dr. Ya-Mei Yang for their valuable insight suggestions. ’ REFERENCES (1) Arthur, C. L.; Pawliszyn, J. Solid phase microextraction with thermal desorption using fused silica optical fibers. Anal. Chem. 1990, 62, 2145–2148. (2) Maruya, K. A.; Zeng, E. Y.; Tsukada, D.; Bay, S. M. A passive sampler based on solid-phase microextraction for quantifying hydrophobic organic contaminants in sediment pore water. Environ. Toxicol. Chem. 2009, 28 (4), 733–740. (3) Ter Laak, T. L.; Agbo, S. O.; Barendregt, A.; Hermens, J. L. M. Freely dissolved concentrations of PAHs in soil pore water: measurements via solid-phase extraction and consequences for soil tests. Environ. Sci. Technol. 2006, 40, 1307–1313. (4) Yang., Z. Y.; Maruya, K. A.; Greenstein, D.; Tsukada, D.; Zeng, E. Y. Experimental verification of a model describing solid phase microextraction (SPME) of freely dissolved organic pollutants in sediment porewater. Chemosphere 2008, 72, 1435–1440. (5) Yang, Y. U.; Hunter, W.; Tao, S.; Gan, J. Microbial availability of different forms of phenanthrene in soils. Environ. Sci. Technol. 2009, 43, 1852–1857. (6) Ramos, E. U.; Meijer, S. N.; Vaes, W. H. J.; Verhaar, H. J. M.; Hermens, J. L. M. Using solid-phase microextraction to determine partition coefficients to humic acids and bioavailabe concentrations of hydrophobic chemicals. Environ. Sci. Technol. 1998, 32, 3430–3435. (7) Van der Wal, L.; Jager, T.; Fleuren, R. H. L.; Barendregt, A.; Sinnige, T. L.; van Gestel, C. A. M.; Hermens, J. L. M. Solid-phase microextraction to predict bioavailability and accumulation of organic micropollutants in terrestrial organisms after exposure to a field-contaminated soil. Environ. Sci. Technol. 2004, 38, 4842–4848. (8) Baltussen, E.; Cramers, C. A.; Sandra, P. J. F. Sorptive sample preparation - a review. Anal. Bioanal. Chem. 2002, 373, 3–22. (9) Mayer, P.; Vaes, W. H. J.; Hermens, J. L. M. Absorption of hydrophobic compounds into the poly(dimethylsiloxane) coating of solidphase microextraction fibers: high partition coefficients and fluorescence microscopy images. Anal. Chem. 2000, 72, 459–464. 7790
dx.doi.org/10.1021/es201040j |Environ. Sci. Technol. 2011, 45, 7785–7791
Environmental Science & Technology (10) Potter, D. W.; Pawliszyn, J. Rapid determination of polyaromatic hydrocarbons and polychlorinated biphenyls in water using solidphase microextraction and GC/MS. Environ. Sci. Technol. 1994, 28 (2), 298–305. (11) Baltussen, E.; Sandra, P; David, F.; Janssen, H. G.; Cramers, C. Study into the equilibrium mechanism between water and poly(dimeythylsiloxane) for very apolar solutes: adsorption or Sorption? Anal. Chem. 1999, 71, 5213–5216. (12) Lung, S. C.; Altshul, L. M.; Ford, T. E.; Spengler, J. D. Coating effects on the glass adsorption of polychlorinated biphenyl (PCB) congeners. Chemosphere 2000, 41, 1865–1871. (13) Lung, S. C.; Yanagisawa, Y.; Ford, T. E.; Spengler, J. D. Characteristics of sorption losses of polychlorinated biphenyl congeners onto glass surfaces. Chemosphere 2000, 41, 1857–1864. (14) Difilippo, E. L.; Eganhouse, R. P. Assessment of PDMS-water partition coefficients: implications for passive environmental sampling of hydrophobic organic compounds. Environ. Sci. Technol. 2010, 44, 6917–6924. (15) Poerschmann, J.; Goecki, T.; Kopinke, F. D. Sorption of very hydrophobic organic compounds onto poly(dimethylsiloxane) and dissolved humic organic matter. 1. Adsorption or partitioning of VHOC on PDMS-coated solid-phase microextraction fibers— A never-ending story? Environ. Sci. Technol. 2000, 34, 3824–3830. (16) Yang, Z. Y.; Greenstein, D.; Zeng, E. Y.; Maruya, K. A. Determination of poly(dimethyl)siloxane-water partition coefficients for selected hydrophobic organic chemicals using 14C-labled analogs. J. Chromatogr., A 2007, 1048, 23–30. (17) Smedes, F.; Geertsma, R. W.; van der Zande, T.; Booij, K. Polymer-water partition coefficients of hydrophobic compounds for passive sampling: application of cosolvent models for validation. Environ. Sci. Technol. 2009, 43, 7047–7054. (18) Shurmer, B.; Pawliszyn, J. Determination of distribution constants between a liquid polymeric coating and water by a solid-phase microextraction technique with a flow-through standard water system. Anal. Chem. 2000, 72, 3660–3664. (19) Ouyang, G.; Cai, J.; Zhang, X.; Li, H.; Pawliszyn, J. Standardfree kinetic calibration for rapid on-site analysis by solid-phase microextraction. J. Sep. Sci. 2008, 31, 1167–1172. (20) Witt, G.; Liehr, G. A.; Borck, D.; Mayer, P. Matrix solid-phase microextraction for measuring freely dissolved concentrations and chemical activities of PAHs in sediment cores from the western Baltic Sea. Chemosphere 2009, 74, 522–529. (21) Ter Laak, T. L.; Busser, F. J. M.; Hermens, J. L. M. Poly(dimethylsiloxane) as passive sampler material for hydrophobic chemicals: effect of chemical properties and sampler characteristics on partitioning and equilibration times. Anal. Chem. 2008, 80, 3859–3866. (22) Zeng, E. Y.; Tsukada, D.; Noblet, J. A.; Peng, J. Determination of polydimethylsiloxane-seawater distribution coefficients for polychlorinated biphenyls and chlorinated pestcides by solid-phase microextraction and gas chromatography-mass spectrometry. J. Chromatogr., A 2005, 1066, 165–175. (23) Safe, S. Polychlorinated biphenyls (PCBs), dibenzo-para-dioxins (PCDDs), dibenzofurans (PCDFs), and related compounds: environmental and mechanistic considerations which support the development of toxic equivalency factors (TEFS). Crit. Rev. Toxicol. 1990, 21, 51–88. (24) Schwarzenbach, R. P.; Gschwend, P. M.; Imboden, D. M. Environmental Organic Chemistry, 3rd ed.; John Wiley & Sons: New York, NY, 2002. (25) Hawker, D. W.; Connell, D. W. Octanol-water partition coefficients of polychlorinated biphenyl congeners. Environ. Sci. Technol. 1988, 22 (4), 382–387. (26) Yang, Z. Y.; Zeng, E. Y.; Xia, H.; Wang, J. Z.; Mai, B. X.; Maruya, K. A. Application of a static solid-phase microextraction procedure combined with liquid-liquid extraction to determine poly(dimethyl)siloxane-water partition coefficients for selected polychlorinated biphenyls. J. Chromatogr., A 2006, 1116, 240–247. (27) Mayer, P.; Vaes, W. H. J.; Wijnker, F.; Legierse, K. C. H. M.; Kraaij, R. H.; Tolls, J.; Hermens, J. L. M. Sensing dissolved sediment
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porewater concentrations of persistent and bioaccumulative pollutants using disposable solid-phase microextraction fibers. Environ. Sci. Technol. 2000, 34 (24), 5177–5183. (28) Resendes, J.; Shiu, W. Y.; Mackay, D. Sensing the fugacity of hydrophobic organic chemicals in aqueous systems. Environ. Sci. Technol. 1992, 26, 2381–2387. (29) Ai, J. Solid phase microextraction for quantitative analysis in nonequilibrium situations. Anal. Chem. 1997, 69, 1230–1236. (30) Mayer, P.; Tolls, J.; Hermens, J. L. M.; Mackay, D. Equilibrium sampling devices. Environ. Sci. Technol. 2003, 37 (9), 184A–191A. (31) ATSDR. Toxicological profile for polychlorinated biphenyls (PCBs); U.S. Department of Health and Human Services, Agency for Toxic Substances and Disease Registry: Atlanta, GA, 2000. (32) Yang, Y.; Hawthorne, S. B.; Miller, D. J.; Liu, Y.; Lee, M. L. Adsorption versus absorption of polychlorinated biphenyls onto soildphase microextraction coatings. Anal. Chem. 1998, 70, 1866–1869. (33) Verbruggen, E. M. J.; Vaes, W. H. J.; Parkerton, T. F.; Hermens, J. L. M. Polyacrylate-coated SPME fibers as a tool to simulate body residues and target concentrations of complex organic mixtures for estimation of baseline toxicity. Environ. Sci. Technol. 2000, 34, 324–331. (34) Fang, F.; Chu, S.; Hong, C. S. Air-water Henry’s law constants for PCB congeners: experimental determination and modeling of structure-property relationship. Anal. Chem. 2006, 78, 5412–5418. (35) Rusina, T. P.; Smedes, F.; Klanova, J. Diffusion coefficients of polychlorinated biphenyls and polycyclic aromatic hydrocarbons in polydimethylsiloxane and low-density polyethylene polymers. J. Appl. Polym. Sci. 2010, 116, 1803–1810. (36) Tremolada, P.; Sugni, M.; Gilioli, G.; Barbaglio, A.; Bonasoro, F.; Carnevali, M. D. C. A dynamic model for predicting chemical concentrations in water and biota during the planning phase of aquatic ecotoxicological tests. Chemosphere 2009, 75, 915–923. (37) Paschke, A.; Popp, P. Solid-phase microextraction fiber-water distribution constants of more hydrophobic organic compounds and their correlations with octanol-water partition coefficients. J. Chromatogr., A 2003, 999, 35–42. (38) Chiou, C. T.; Schmedding, D. W. Partitioning of organic compound in octanol-water system. Environ. Sci. Technol. 1982, 16 (1), 4–10.
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dx.doi.org/10.1021/es201040j |Environ. Sci. Technol. 2011, 45, 7785–7791
