Poly(dimethylsiloxane) as Passive Sampler Material for Hydrophobic

Anal. Chem. 2008, 80, 3859–3866

Poly(dimethylsiloxane) as Passive Sampler Material for Hydrophobic Chemicals: Effect of Chemical Properties and Sampler Characteristics on Partitioning and Equilibration Times Thomas L. ter Laak,* Frans J. M. Busser, and Joop L. M. Hermens IRASsInstitute for Risk Assessment Sciences, Utrecht University, Yalelaan 2, 3584 CM Utrecht, The Netherlands Information about sampling rates and equilibration times of passive samplers is essential in their calibration in field monitoring studies as well as sorption studies. The kinetics of a sampler depends on the distribution coefficient between the sampler material and aqueous phase and the exchange rates of chemicals between these phases. In this study, the elimination kinetics of four poly(dimethylsiloxane) (PDMS) passive samplers with different surface-volume ratios are compared. The samplers were loaded with polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs) that cover a broad range of hydrophobicities. The surface-volume ratios of the samplers could largely explain the observed kinetics. Furthermore, a simple diffusion-based model illustrates that the exchange of chemicals was limited by diffusion through the aqueous diffusion layer surrounding the sampler. On the basis of this simple diffusion model, equilibration times are predicted for organic chemicals that vary in hydrophobicity and samplers with different dimensions and polymeric phases. This information is of importance in the selection of a passive sampler for a specific purpose. Passive sampling devices, made of different materials, have been applied to sample (hydrophobic) organic chemicals in environmental monitoring and sorption studies.1,2 They can be applied at equilibrium and in the kinetic mode.3–5 Either way, they are time-integrated samplers, because they integrate concentrations over a certain exposure time. Some samplers absorb chemicals, whereas others adsorb chemicals, and some samplers consist of a single sampling material, whereas others consist of multiple materials (e.g., solvents, polymers). In general, samplers of a single absorbing material are preferred, because the absorp* To whom correspondence should be addressed. Phone: +31302535018. Fax: +31302535077. E-mail: [email protected] or [email protected]. (1) Namiesnik, J.; Zabiegala, B.; Kot-Wasik, A.; Partyka, M.; Wasik, A. Anal. Bioanal. Chem. 2005, 381, 279–301. (2) Vrana, B.; Mills, G. A.; Allan, I. J.; Dominiak, E.; Svensson, K.; Knutsson, K.; Morrison, G.; Greenwood, R. TrAC, Trends Anal. Chem. 2005, 24, 845– 868. (3) Mayer, P.; Tolls, J.; Hermens, J. L. M.; Mackay, D. Environ. Sci. Technol. 2003, 37, 184A–191A. (4) Heringa, M. B.; Hermens, J. L. M. TrAC, Trends Anal. Chem. 2003, 22, 575–587. (5) Ouyang, G.; Pawliszyn, J. J. Chromatogr., A 2007, 1168, 226–235. 10.1021/ac800258j CCC: $40.75  2008 American Chemical Society Published on Web 04/19/2008

tion processes are usually concentration independent and the use of a single material is more straightforward in determining distribution coefficients to the sampler material.6 Knowledge on sampling rates or kinetics is essential in environmental monitoring. For example, when environmental concentrations fluctuate, small unicellular algae will follow these fluctuations rather closely because their exchange kinetics with the aqueous phase is fast, while fish will respond much slower to fluctuating concentrations in the aqueous phase.7 Ideally, one would also like to apply a series of passive samplers with a range of faster sampling rates to simulate exposure conditions of different organisms. Additionally, knowledge on sampling kinetics is also essential when passive samplers are applied to study sorption to dissolved phases, such as humic acids8 and proteins,9,10 and particulate phases, such as sediments and soils.11,12 These studies generally make use of thin polymer films with fast sampling rates, in order to reach equilibrium without depleting the test system.3,13 The selection of a sampler and sampling mode to study a particular problem is not always straightforward. Two major factors characterize a sampler: the affinity of the sampler material for chemicals and the sampling rate. The affinity of chemicals to the sampling material depends on the strength of interactions such as van der Waals interactions and hydrogen bonding.14 The exposure time to maintain a continuous flux (as preferred in kinetic sampling) or reach equilibrium between the sampler and its environment is determined by the size and geometry of the sampler, the sampling matrix, mixing conditions, and physicochemical properties of the chemical and the sampler material(s). Samplers with larger surface-volume ratios will have faster (6) Dettmer, K.; Engewald, W. Anal. Bioanal. Chem. 2002, 373, 490–500. (7) Hendriks, A. J.; Van Der Linde, A.; Cornelissen, G.; Sijm, D. T. H. M. Environ. Toxicol. Chem. 2001, 20, 1399–1420. (8) Dewulf, J.; van Langenhove, H.; Everaert, M. J. Chromatogr., A 1997, 761, 205–217. (9) Vaes, W. H. J.; Urrestarazu Ramos, E.; Verhaar, H. J. M.; Seinen, W.; Hermens, J. L. M. Anal. Chem. 1996, 68, 4463–4467. (10) Kramer, N. I.; Eijkeren, J. C. H.; Hermens, J. L. M. Anal. Chem. 2007, 79, 6941–6948. (11) Awata, H.; Johnson, K. A.; Anderson, T. A. Toxicol. Environ. Chem. 1999, 73, 25–42. (12) Mayer, P.; Vaes, W. H. J.; Wijnker, F.; Legierse, K. C. H. M.; Kraaij, R.; Tolls, J.; Hermens, J. L. M. Environ. Sci. Technol. 2000, 34, 5177–5183. (13) Heringa, M. B.; Pastor, D.; Algra, J.; Vaes, W. H. J.; Hermens, J. L. M. Anal. Chem. 2002, 74, 5993–5997. (14) Goss, K.-U.; Schwarzenbach, R. P. Environ. Sci. Technol. 2001, 35, 1–9.

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sampling rates and, therefore, shorter response times. However, large surface-volume ratios usually coincide with smaller sampling volumes that make the sampler less sensitive. An important aspect in understanding sampler kinetics is the distinction of the rate-limiting steps in the transfer of chemicals between the sampler and the sampling matrix. The transfer can be limited by the aqueous diffusion layer surrounding the sampler or the sampler material itself. If the aqueous diffusion layer is rate-limiting, processes such as facilitated transport can strongly affect the uptake kinetics.10,15,16 Detailed information on these phenomena is essential in the selection of samplers and exposure times in specific matrixes. The objective of this study is to characterize a series of samplers with poly(dimethylsiloxane) (PDMS) as the sampling material. PDMS was chosen because it is a well-defined hydrophobic phase that linearly absorbs hydrophobic organics over a very wide concentration range.17 This study would like to give insight into the following aspects: (i) is the partitioning to different PDMS samplers similar, (ii) can kinetics be predicted from the dimension of the sampler, (iii) what is the rate-limiting step in the uptake? For this purpose, four PDMS samplers with different surface-volume ratios were loaded with 14 polychlorinated biphenyls (PCBs) and 4 polybrominated diphenyl ethers (PBDEs) that cover a broad range of hydrophobicities (octanol-water partition coefficients vary from 104.7 to 108.3). PDMS-water partition coefficients were determined by equilibrating the samplers with an aqueous phase. Furthermore, the sampler kinetics were studied by monitoring the elimination of chemicals from the sampler in time. The experimental data were analyzed via a simple diffusion-based model. This model was also applied to estimate kinetics for a number of samplers with different dimensions and sampling materials. Knowledge on chemical and sampler-specific response times of different samplers under different test conditions is essential in designing experiments and selecting an appropriate sampler for a specific purpose. THEORETICAL SECTION Exchange of Chemicals between Phases. In a system with a hydrophobic absorbing sampler and an aqueous phase, the concentration of a chemical in the sampler (Cs) in time (t) can be described by a one-compartment model, if the aqueous concentration (Cw) is not depleted by the sampler: Cs(t) ) CwKsw(1 - exp-ket)

(1)

where Ksw is the dimensionless hydrophobic phase-water partition coefficient and ke (t-1) is the system- and chemical-specific elimination rate constant. If the sampler initially contains the chemical at a certain concentration Cs(0), the kinetics during an elimination study can be described by the same elimination rate constant: Cs(t) ) Cs(0) exp-ket

(2)

(15) Oomen, A. G.; Mayer, P.; Tolls, J. Anal. Chem. 2000, 72, 2802–2808. (16) Mayer, P.; Karlson, U.; Christensen, P. S.; Johnsen, A. S.; Trapp, S. Environ. Sci. Technol. 2005, 39, 6123–6129. (17) Ter Laak, T. L.; Agbo, S. O.; Barendregt, A.; Hermens, J. L. M. Environ. Sci. Technol. 2006, 40, 1307–1313.

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The elimination rate constant integrates mass transfer processes in water and sampler. This exchange process can be described by the diffusion coefficient in water (Dw, m2 h-1) and the sampler (Ds, m2 h-1), the diffusion layer thickness in water (δw, m) and sampler (δs, m), the dimensionless sampler-water partition coefficient, and the transport surface (A, m2) and volume (V, m3) of the sampler:18 1 VδwKsw Vδs ) + ke ADw ADs

(3)

If the mass transfer in the aqueous phase is rate-limiting, VδwKsw Vδs . ADw ADs

(4)

the elimination rate constant is determined by the mass transfer in the aqueous phase: ke ≈

ADw VδwKsw

(5)

If the mass transfer in the sampler material is rate-limiting, VδwKsw Vδs , ADw ADs

(6)

the elimination rate constant is determined by the mass transfer in the sampler material: ke ≈

ADs Vδs

(7)

EXPERIMENTAL SECTION Chemicals, Samplers, and Solvents. PCB 2, 14, 18, 28, 35, 52, 72, 77, 101, 118, 126, 153, 180, 203, and 209 were purchased at Accustandard (New Haven, CT) and PBDE 49, 99, 153, and 183 were purified and provided by Ake Bergman, Stockholm University, Sweden (for background information see Table S1 of the Supporting Information). PDMS-coated fibers were obtained from Poly Micro Industries (Phoenix, AZ). The coating thicknesses were 6.5 µm (later referred to as 7 µm fiber), 28.0 µm (later referred to as 30 µm fiber), and 99.75 µm (later referred to as 100 µm fiber) with respective glass core diameters of 110, 114.5, and 113 µm and volumes of 2.38, 12.27, and 66.67 µL m-1. PDMS sheets with a thickness of ∼500 µm were obtained from Altec (www.altecweb.com). The n-hexane, 2,2,4-trimethylpentane, acetone, and methanol (Lab-Scan, Dublin, Ireland) were of pestiscan grade. Highly pure water (R g 18 MΩ) was prepared by a Millipore water purification system, equipped with organic-free kit (Millipore Waters, Amsterdam, The Netherlands). All experiments were performed at 20 ± 1 °C. Loading Samplers. Fibers were cut into pieces of 5.0 cm and washed three times with methanol and stored in Millipore water. The PDMS sheets were cut into circular chips with a surface 0.132 cm2 and a weight of 7.85 ± 0.1 mg. The density was 1.15 ± 0.01 g (18) Gobas, F. A. P. C.; Opperhuizen, A.; Hutzinger, O. Environ. Toxicol. Chem. 1986, 5, 637–646.

Figure 1. Picture of the experimental setup for the sampler elimination.

mL-1, and the thickness was calculated to be 517 µm. The sheets were washed three times with trimethylpentane, one time with acetone, and one time with methanol before storing them in Millipore water. All cleaned samplers were loaded by exposing them to a 1:1 methanol-water mixture containing PCBs and PBDEs. Samplers were loaded for at least 1 week. PDMS-Water Partitioning. PDMS-water partitioning was determined by equilibrating the loaded passive samplers in 40 mL vials (Supelco, Bellefonte, CA) containing 38 ± 1 mL of Millipore water with 50 mg L-1 sodium azide (Merck, Amsterdam, The Netherlands) to inhibit bacterial activity. The 7 and 30 µm fibers were extracted with 200 µL of trimethylpentane, the 100 µm fiber was extracted with 1.0 mL of trimethylpentane, and the 500 µm sheet was extracted with 5.0 mL of trimethylpentane. The trimethylpentane contained 50 µg L-1 PCB 209 as internal standard. Extractions are considered exhaustive because three subsequent extractions showed that 99.6-100.3% was extracted by a single extraction when the extraction recovery was corrected for the loss (0.5%) of internal standard. The aqueous concentrations were determined by extracting 25 mL of water with 2 mL of n-hexane, by shaking by hand (1 min), and gently by rock and rolling (Stuart roller mixer SRT9D, Warrenville, IL) for at least 6 h. After extraction, the sample was frozen at -20 °C overnight, and the n-hexane was decanted. This extraction step was repeated three times. The collected n-hexane extract was evaporated in a fume hood, and 100 µL of trimethylpentane was added when approximately 100 µL of n-hexane was left. Subsequently, the residual n-hexane was evaporated and 200 µL of trimethylpentane, containing 50 µg L-1 PCB 209 as injection standard, was added. The extract (final volume ∼250 µL) was stored until analysis. The extraction recoveries were determined by spiking the n-hexane that was used to extract the aqueous samples. They ranged from 95% to 105%, so no correction for extraction efficiency was made. Only PCB 2 had a lower extraction recovery (84.3%), which was used to correct concentrations in the aqueous phase. All aqueous concentrations were below aqueous solubility. Elimination Kinetics. Figure 1 illustrates the test setup of the sampler elimination study. The loaded samplers as described above were separately exposed in 7.5 mL amber vials (Supelco, Bellefonte, CA) with 5 mL of Millipore water containing 50 mg L-1 sodium azide. The vial also contained a clean 14.3 cm2, ∼500 µm thick PDMS sheet. This 14.3 cm2 sheet functioned as an infinite sink for the chemicals desorbing from the loaded fibers and loaded PDMS sheet of 0.132 cm2. The vials were shaken on a Stuart roller mixer set at 10 rpm. Direct contact between the

loaded sampler and the clean sheet was prohibited by a stainless steel spring (DR1340, Alcomex veren, Opmeer, The Netherlands) in which the loaded sampler was placed. The loaded PDMS sheet was pierced by a stainless steel needle (Sorbo HT 257, Utrecht, The Netherlands) to keep it inside this spring. A clean 4.5 cm long 7 µm PDMS-coated fiber was exposed outside of the spring to monitor aqueous concentrations during the sampler elimination. No quantifiable concentrations were obtained from these clean fibers, showing that aqueous concentrations were very close to zero during sampler depletion. Springs, needles, and the clean 14.3 cm2 PDMS sheets were washed by the same procedure as the loaded 0.132 cm2 PDMS sheet. The loaded fibers and sheet inside the spring and the clean fibers on the outside the spring were sampled after 5 (7 and 30 µm fibers only), 15 (fibers only), and 30 min, 1, 2, 4, 8, 16, and 28 h, and 2, 4, 7, 11, 16, 21 (7 µm fiber only), 28 (excluding 7 µm fiber), 36 (100 µm fiber and sheet only), and 176 days (sheet only). The initial concentrations in the PDMS material are listed in Table S2 of the Supporting Information. The loaded fibers and sheets were extracted as described in the section “PDMS-water Partitioning”. Concentrations of the chemicals in these samplers were normalized to initial concentrations, and one-phase exponential elimination curves were fitted through the data to obtain elimination rate constants (eq 2). Chemical Analysis. The concentrations in the aqueous and sampler extracts were determined by gas chromatography with electron capture detection (GC-ECD). The system consisted of a Fisons AS 800 autosampler, a Fisons HRGC 8000 GC, and a Carlo Erba ECD 40 electron capture detector with an ECD 400 controller (all instruments, Rodano, Italy). Helium (150 kPa) was used as a carrier gas. After a stabilization time of 2 min at 90 °C, 1.0 µL of extract was injected on-column on a deactivated uncoated precolumn (1.5 m × 0.53 mm) connected to the fused-silica DB5.625 separation column of 30 m × 0.25 mm with a coating thickness of 0.25 µm (J&W Scientific, Folsom, CA). The column was kept at 90 °C for 2 min after injection, before it was increased with 10 °C min-1 to 170 °C, with 2 °C min-1 to 290 °C, and with 20 °C min-1 to 315 °C where it was kept for 5 min. The GC-ECD performance was tested every ∼10 samples by injection of an external standard solution. Chromatograms were checked by hand after automatic integration (Chromcard 2.2.3. software, Rodano, Italy). Analytical accuracy and detection limits of the individual chemicals are listed in the Supporting Information, Table S1. RESULTS AND DISCUSSION PDMS-Water Partitioning. In a pilot study, concentrations in a 2.5 cm long loaded 7 µm fiber and an aqueous phase (38 mL in a 40 mL vial) were determined after 7, 14, and 27 days. After 27 days, at least 94% of the steady state was reached for all chemicals (Supporting Information, Figure S1). The sampler was only marginally depleted during this equilibration process. Consequently, the equilibrium kinetics is mainly determined by the ratio of the exchange surface of the sampler and the aqueous volume.19 The surface of the fibers and sheets in the partitioning experiment is larger than the surface of the 2.5 cm long 7 µm fiber from the pilot experiment, while aqueous volumes and (19) Banerjee, S.; Sugatt, R. H.; O’Grady, D. P. Environ. Sci. Technol. 1984, 18, 79–81.


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Table 1. PDMS-Water Partition Coefficients of the Different Samplersa chemical

7 µm fiber log KPDMS-water



500 µm sheet log KPDMS-water

PCB 2 PCB 14 PCB 18 PCB 28 PCB 35 PCB 52 PCB 72 PCB 77 PCB 101 PCB 118 PCB 126 PCB 153 PCB 180 PCB 203 PBDE 47 PBDE 99 PBDE 153 PBDE 183

4.09 (0.04, 8) 4.86 (0.06, 8) 5.05 (0.05, 8) 5.27 (0.06, 8) 5.23 (0.05, 8) 5.58 (0.05, 8) 5.78 (0.06, 14) 5.61 (0.05, 16) 6.07 (0.06, 15) 6.10 (0.05, 17) 6.09 (0.08, 12) 6.48 (0.07, 11) 6.67 (0.10, 6) 6.85 (0.17, 6) 5.85 (0.06, 12) 6.22 (0.06, 11) 6.43 (0.08, 6) 6.52 (0.12, 6)

4.18 (0.06, 7) 4.94 (0.07, 7) 5.13 (0.07, 7) 5.34 (0.07, 7) 5.30 (0.08, 7) 5.65 (0.07, 7) 5.86 (0.08, 12) 5.67 (0.07, 14) 6.14 (0.08, 13) 6.14 (0.08, 15) 6.14 (0.12, 12) 6.53 (0.11, 11) 6.78 (0.07, 3) 7.05 (0.07, 3) 5.91 (0.07, 8) 6.35 (0.07, 8) 6.47 (0.08, 3) 6.62 (0.08, 3)

4.14 (0.02, 4) 4.87 (0.03, 4) 5.11 (0.05, 4) 5.24 (0.04, 4) 5.29 (0.06, 4) 5.60 (0.05, 4) 5.83 (0.09, 4) 5.57 (0.05, 4) 6.06 (0.03, 4) 5.87 (0.11, 4) 5.89 (0.20, 2) 6.68 (0.15, 4) 6.76 (0.12, 2)b 6.95 (0.08, 2)b 5.92 (0.06, 4) 6.33 (0.08, 3) 6.67 (0.13, 4)b 6.70 (0.15, 4)b

4.31 (0.06, 7) 5.04 (0.04, 7) 5.24 (0.05, 7) 5.44 (0.05, 7) 5.49 (0.05, 7) 5.74 (0.05, 7) 6.00 (0.07, 7) 5.85 (0.09, 7) 6.24 (0.04, 7) 6.15 (0.14, 7) 6.20 (0.14, 5) 6.82 (0.10, 7) 6.94 (0.07, 4)b 7.09 (0.06, 3)b 6.17 (0.04, 7) 6.64 (0.08, 6) 6.94 (0.11, 5)b 6.90 (0.12, 5)b

a Standard deviations and number of observations are given between brackets. b Concentrations of the aqueous extracts that were used to determine these partition coefficients were extremely low (nanograms per liter range). Peak heights were down to 2 times noise level, whereas 5 times noise level was set as the limit of quantification. Therefore, the determined partition coefficients are less accurate.

shaking conditions are identical. Therefore, the steady state will be reached faster than in the pilot study. The 7 and 30 µm fibers were exposed for 37 days, and the 100 µm fiber and sheet were exposed for 152 days. After these exposure times, concentrations in the PDMS and aqueous phase should be at steady state. The partition coefficients of the three fibers and the sheet are very similar to each other (Table 1) and comparable to literature.20,21 Differences between partition coefficients of the samplers do not exceed 0.5 log units and are even smaller if only the fibers are compared ( ∼106 that is observed for all samplers might be explained by an extra transfer of the hydrophobic chemicals generated by a third phase.10,15,16 Possibly, microscopic pieces or molecules (e.g., PDMS oligomers) coming from the clean sheet or loaded sampler might facilitate the transport of the chemicals in the aqueous diffusion layers. The most hydrophobic chemicals have the highest affinity for such a phase. Subsequently, small quantities of this material in the aqueous phase can facilitate transport over the aqueous diffusion layer for these chemicals. Aqueous Diffusion Layer Thickness. The kinetic limitation by the aqueous diffusion layer, and the fact that the aqueous concentration remains (nearly) zero, allow us to calculate its thickness according to eq 5. The determination of the aqueous diffusion layer needs the PDMS-water partition coefficient, the volume and surface area of the PDMS sampler, and the aqueous diffusivity of the chemical of interest. The PDMS-water partition coefficient was obtained from the previous experiment (Table 1). Additionally, the surface area and volume of the fibers were (27) Ter Laak, T. L.; Durjava, M.; Struijs, J.; Hermens, J. L. M. Environ. Sci. Technol. 2005, 39, 3736–3742.

Their average diffusion layers with standard deviations were 3.2 ± 0.6, 5.4 ± 0.9, 7.1 ± 1.5, and 15.8 ± 2.7 µm for the 7, 30, 100 µm fiber, and 500 µm sheet, respectively. The diffusion layer thicknesses increased by a factor of 5 with the size of the passive sampler. This effect might be explained by the convergent shape of the diffusion layer surrounding the cylindrical fibers, which results in a thinner apparent diffusion layer than the actual diffusion layer.30 However, for these particular samplers and calculated diffusion layer thicknesses, the effect will be negligible. Subsequently, the observed trend must be related to the differences in size, geometry, and density of the samplers. The fibers with thinner coatings have a higher average density because a smaller part of their total volume consists of PDMS (1.15 g mL-1) and a larger part of fused silica (2.2 g mL-1). These physical properties likely affect the movement of the sampler in the metal spring and therefore the thickness of the aqueous diffusion layer of the sampler.3 Predicting Equilibration Times in PDMS Based on Surface-Volume Ratio and Diffusion Coefficient. Experiments under controlled shaking conditions in pure water illustrate that the kinetics of various passive samplers can largely be explained by their surface-volume ratio (Figure 4). In addition, the differences in uptake and elimination rate constants between chemicals can be largely deduced from their PDMS-water partition coefficient (Figure 3). Both observations enable us to estimate the kinetics and equilibration times from one chemical to another chemical and from one sampler to another sampler (eq 3). Figure 5 shows the time to reach 95% of the equilibrium (t95%) in relation to the PDMS-water partition coefficient for the different samplers, under the assumption that aqueous concentrations are constant during exposure. The t95% can be obtained from the elimination rate constant:

t95% )

2.99 ke

(8)

The aqueous diffusion layer thickness is taken from the experimental results (average of PCBs with four or less chlorine atoms). The diffusion layer thickness in the sampler material δS can be estimated by the area (A) and volume (V) of the sampler according to Salaun and Buffle:31 Figure 2. Elimination profiles of PCB 2 (A), 101 (B), and 203 (C) from the 7 µm fiber (triangle), the 30 µm fiber (square), the 100 µm fiber (circle), and the 517 µm thick PDMS sheet (star). Eq 2 was fitted to the data, and an elimination rate constant was obtained from this fit. T ) 0 was set at 10-3 h for visual purposes and fitting on a log scale. Elimination profiles of the other chemicals can be found in Figure S3 of the Supporting Information.

calculated from dimensions provided by the manufacturer, and the surface and volume of the sheet were measured. Furthermore, the aqueous diffusivity of the chemicals was calculated according to Hayduc and Laudie,28 using molecular volumes of LeBas.29 Results are presented in Table 2. Diffusion layer thicknesses of PCBs with four or less chlorine atoms were very similar. (28) Hayduc, W.; Laudie, H. AIChE J. 1974, 20, 611–615. (29) LeBas, G. The Molecular Volumes Of Liquid Chemical Compounds; Longmans, Green: London, 1915.

δS ≈ 0.5

V A

(9)

The diffusion layer in a polymer passive sampler is related to its volume and surface area because the polymer phase is not agitated. During equilibration, the effective diffusion layer is about half of the V/A ratio because the concentration gradient is present close to the polymer-water interface, and levels off near the center of the polymer phase.31 The diffusivity of a chemical in the aqueous phase can be estimated from various molecular weightor size-related models. Aqueous diffusivities of most environmentally relevant organic molecules fall within a range of a factor 2.32 (30) Heyrovsky, J.; Kuta, J. Principles of Polarography; Academic Press: New York, 1966. (31) Salaun, P.; Buffle, J. Anal. Chem. 2004, 76, 31–39. (32) Schwarzenbach, R. P.; Gschwend, P. M.; Imboden, D. M. Environmental Organic Chemistry, 2nd ed.; John Wiley & Sons: Hoboken, NJ, 2003.


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Figure 3. Elimination rate constants (A) and uptake rate constants (B) of the 7 µm fiber (triangle), the 30 µm fiber (square), the 100 µm fiber (circle), and the 517 µm thick PDMS sheet (star) plotted against the PDMS-water partition coefficient. Table 2. Calculated Diffusion Layer Thicknesses for the Different Chemicals and Samplersa chemical

aqueous diffusion layer of the 7 µm fiber µm



aqueous diffusion layer of the 500 µm sheet µm

PCB 2 PCB 14 PCB 18 PCB 28 PCB 35 PCB 52 PCB 72 PCB 77 PCB 101 PCB 118 PCB 126 PCB 153 PCB 180 PCB 203 PBDE 47 PBDE 99 PBDE 153 PBDE 183

4.29 (0.47) 3.49 (0.37) 3.74 (0.29) 3.18 (0.29) 3.06 (0. 34) 3.22 (0.31) 2.44 (0.22) 2.49 (0.36) 2.06 (0.18) 1.91 (0.25) 1.44 (0.26) 1.29 (0.15) 0.96 (0.14) 1.18 (0.22) 1.45 (0.26) 1.13 (0,22) 0.90 (0.19) 0.72 (0.16)

5.71 (0.76) 5.17 (0.54) 6.16 (0.61) 5.84 (0.58) 6.77 (0.59) 4.82 (0.49) 3.79 (0.34) 5.18 (0.41) 2.79 (0.26) 3.02 (0.30) 2.57 (0.32) 1.66 (0.17) 1.08 (0.13) 0.76 (0.09) 3.67 (0.36) 2.02 (0.19) 1.74 (0.24) 1.25 (0.22)

10.30 (1.19) 7.08 (0.58) 6.27 (0.51) 7.35 (0.62) 6.95 (0.63) 6.73 (0.50) 4.78 (0.41) 7.29 (0.68) 4.69 (0.33) 8.21 (0.59) 6.48 (0.71) 2.25 (0.22) 2.81 (0.38) 2.16 (0.27) 4.50 (0.46) 3.52 (0.38) 2.21 (0.28) 2.16 (0.33)

19.34 (2.09) 14.78 (1.07) 14.26 (1.12) 17.21 (1.39) 18.90 (1.62) 14.47 (1.23) 11.36 (1.06) 15.77 (1.38) 8.28 (0.75) 11.59 (1.17) 12.12 (1.99) 2.91 (0.35) 2.48 (0.32) 1.67 (0.23) 11.14 (1.17) 5.98 (0.64) 3.77 (0.66) 3.66 (0.52)

a

Standard errors are given between brackets.

Figure 4. Log-normalized average uptake rate constants of all test chemicals plotted against the surface-volume ratio of the four samplers. Error bars represent standard deviations.

For simplification, the aqueous diffusivity is set at an average value of 5 × 10-10 m2 s-1 in this modeling effort. Diffusivities in poly3864


mers such as PDMS are more difficult to estimate. In general, the diffusivities of organic chemicals have a stronger molecular size dependence in organized phases (e.g., polymers) than in liquids (e.g., water, solvents).33,34 In addition polymer cross-linking and average chain lengths will affect diffusivities.34 For simplification, the diffusivity in PDMS is set at 5 × 10-11 m2 s-1, which falls within observed diffusivities from literature.35,36 Under these assumed diffusivities, the shift from polymer to aqueous diffusionlimited transport is observed at PDMS-water partition coefficients ranging from 1 to 100 for all samplers (Figure 5). Since these samplers are generally not applied for chemicals with PDMSwater partition coefficients smaller than 100, transfer of chemicals will generally be limited by the aqueous diffusion layer. Predicting Equilibration Times in Various Polymer Phases Based on Surface-Volume Ratio and Diffusion Coefficient. Various other polymer phases such as polyacrylate (PA), poly(oxymethylene) (POM), low-density polyethylene, and ethylene (33) Kokes, R. J.; Long, F. A. J. Am. Chem. Soc. 1954, 75, 6142–6146. (34) Painter, P. C.; Coleman, M. M. Fundamentals of Polymer Science: An Introductory Text; Lancaster Technomic: Lancaster, PA, 1994. (35) Flynn, G. L.; Yalkowsky, S. H. J. Pharm. Sci. 1972, 61, 838–852.

Figure 5. Time after which 95% of the equilibration concentration is reached for the four passive samplers tested in this study in relation to the sampler-water partition coefficient. Equilibration times are estimated for a constant exposure concentration. It should be emphasized that the t95% values shown in this figure are calculated under the assumption that exposure concentrations in the aqueous phase are stable and that the initial concentration in the samplers is zero. If the free aqueous concentration decreases during exposure, the t95%(depletion) value will be reduced according to the following equation19: t95%(depletion) ) t95%/(1 + KSW/DF), where the dilution factor (DF) is the volume ratio of the aqueous phase and the sampler phase and the t95% and t95%(depletion) are the 95% equilibrium times with constant and depleting exposure concentrations, respectively.

Figure 6. Time after which 95% of the equilibration concentration is reached for three samplers with the dimensions of the 100 µm fiber, with varying diffusion coefficients through the sampler material, based on diffusivities in PDMS (5 × 10-11 m2 s-1), PA (3.6 × 10-12 m2 s-1), and POM (10-15 m2 s-1). Equilibration times are estimated for constant exposure concentrations.

vinyl acetate are used as an absorbing sampling phase. The diffusivity of organic chemicals in these phases varies. In this section, PDMS, PA and POM are selected to illustrate how the diffusivity can affect the t95%. The diffusivity of neutral organic chemicals in PA and POM is lower than in PDMS. Figure 6 illustrates how the t95% is affected when the diffusivity in the polymer phase decreases for a sampler with identical dimensions and aqueous diffusion layer thicknesses as the 100 µm fiber used in this study. The selected diffusivities are 5 × 10-11 m2 s-1 for (36) Rusina, T. P.; Smedes, F.; Klanova, J.; Booij, K.; Holoubek, I. Chemosphere 2007, 68, 1344–1351.

PDMS, 3.6 × 10-12 m2 s-1 for PA37 (calculation in the Supporting Information), and 10-14 m2 s-1 for POM, which is an average of literature values.38 It can be observed that chemicals with sampler-water partition coefficient up to 105 are limited by the diffusion in POM, whereas for PDMS and PA, aqueous diffusion is the main rate-limiting process for chemicals with samplerwater partition coefficient larger than 101 and 102, respectively. These simulations show that the time to reach equilibrium in the different polymers varies by orders of magnitude for chemicals with low sampler-water partition coefficients, while equilibration times converge at high sampler-water partition coefficients, because the aqueous diffusion layer becomes rate-limiting for all sampler materials. Effect of Facilitated Transport on Equilibration Times. This study focuses on the mass transport in sampler phases present in pure water. However, aqueous phases in the environment can contain dissolved and particulate materials such as dissolved organic matter (DOM). Also in sorption studies the sorbent phase is often dissolved (DOM, proteins) or suspended (soil particles, membrane vesicles). These materials can sorb hydrophobic organic chemicals, thereby reducing free aqueous concentrations.15 Besides that, they can also facilitate transport of chemicals through aqueous diffusion layers if a substantial fraction of the chemicals is bound to these matrixes.10 As a consequence, uptake rates can increase, and the t95% can decrease, if the exchange is limited by the aqueous diffusion layer. This phenomenon will be more pronounced for more hydrophobic chemicals, because these chemicals generally have a higher affinity for these matrixes. Insight into these phenomena is relevant for the selection of an appropriate sampler, sampling time, and the calibration of a sampler. Therefore, detailed studies on effects of different types of matrixes on diffusion in aqueous phases10,16 will supply relevant information for estimating these kinds of matrix effects. Selection of Sampler Based on Properties of Chemical and Sampler. Information about sampling kinetics is essential in environmental sampling and sorption studies performed in the laboratory. A more mechanistic understanding and description of sampling kinetics in relation to their properties and exposure conditions (eq 3) might help selecting a sampler for a specific application. The diffusion layer in the sampler material can be estimated with eq 9. The diffusion layer thickness in aqueous phase is more difficult to estimate but is generally between 10 and 100 µm.39 The aqueous diffusivity can be calculated based on molecular size or weight.32 The partition coefficient between water and the sampler material can be found in literature, estimated on the basis of molecular properties14,21 or determined experimentally. However, diffusivity of a chemical in a polymer phase, and information on phenomena such as facilitated transport, are more difficult to find in literature or to predict. The mechanistic model can give a first estimation of sampler kinetics. (37) Vaes, W. H. J.; Hamwijk, C.; Urrestarazu Ramos, E.; Verhaar, H. J. M.; Hermens, J. L. M. Anal. Chem. 1996, 68, 4458–4462. (38) Ahn, S.; Werner, D.; Karapanagioti, H. K.; McGlothlin, D. R.; Zare, R. N.; Luthy, R. G. Environ. Sci. Technol. 2005, 39, 6516–6526. (39) Van Leeuwen, H. P.; Town, R. M.; Buffle, J.; Vleven, R. F. M. J.; Davison, W.; Puy, J.; Riemsdijk, W. H.; Sigg, L. Environ. Sci. Technol. 2005, 39, 8545–8556.


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However, experimental measurements of the kinetics or the use of performance reference compounds40 will often remain necessary. The uptake of chemicals by samplers with a low surface-volume ratio (>10-4 m-1) made of material with low diffusivity ( 7) kinetics can still remain very slow, and equilibration remains a true challenge. Equilibrium of these

chemicals can still be reached within a feasible time if an extremely thin coating or sampling material with a lower affinity is used,41 or when a matrix that facilitates transport is added. However, decreasing coating thickness or affinity will reduce the sensitivity of the technique, and the use of a matrix is not always appropriate within test systems.

(40) Booij, K.; Sleiderink, H. M.; Smedes, F. Environ. Toxicol. Chem. 1998, 17, 1236–1245. (41) Wilcockson, J. B.; Gobas, F. A. P. C. Environ. Sci. Technol. 2001, 35, 1425– 1431.

Received for review February 6, 2008. Accepted March 9, 2008.

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ACKNOWLEDGMENT This project was funded by the European Union (ECODIS, contract no: 518043-1). Furthermore we thank Herman van Leeuwen for many fruitful discussions on dynamic processes and Philipp Mayer for providing the 30 µm fiber. SUPPORTING INFORMATION AVAILABLE Calculation of the diffusivity in polyacrylate, elimination profiles of all chemicals from the different loaded samplers, background information on chemicals, chemical analysis, and experimental conditions, and sampler partition coefficients. This material is available free of charge via the Internet at http://pubs.acs.org.

AC800258J

Poly(dimethylsiloxane) as Passive Sampler Material for Hydrophobic

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