Chlorinated pesticides - 292

ABSTRACT - Despite the growing popularity ofsolid-phase microextraction (SPME) among the com-munity of analytical chemists, applications of SPMEin the measurement of very hydrophobic organiccompounds (VHOCs) have remained limited. This isdue, in part, to the difficulty of calibrating SPMEdevices for VHOCs. Here, we present an analyticalprocedure used to determine the distribution coeffi-cients (Kf values) for a large suite of polychlorinatedbiphenyl (PCB) congeners and chlorinated pesticidesbetween a polydimethylsiloxane (PDMS) phase (100µm thickness) and seawater. Losses of analytes tosample containers and stirring bars were accountedfor in the determination of Kf. The correlationbetween log Kf and log Kow, the octanol-water parti-tion coefficient, was positively linear for PCB con-geners with log Kow up to ~6.5, but became negative-ly linear for PCB congeners with log Kow >6.5. Whengrouped based on the number of chlorines(homolog), log Kf increased linearly with increasinglog Kow for homologs 3-5 and decreased forhomologs 6-10. These findings were inconsistentwith existing data acquired using thinner PDMS coat-ings (7 and 15 µm), which exhibited a positively lin-ear relationship between log Kf and log Kow for allPCB congeners. We postulate that the larger PCBcongeners cannot readily sorb into the bulk PDMSphase, as would be required to maintain a consistentsorptive capacity for the thick 100 µm fiber coating.This effectively lowers the sorption capacity ofPDMS-coated SPME devices for high molecularweight PCB congeners. This hypothesis contributesadditional insight toward understanding the mecha-nism of SPME processes with PDMS phases.

INTRODUCTIONSolid-phase microextraction is an organics

extraction method based on quantitation of analytessorbed on a polymeric phase, often coated on a glassfiber, in contact with water or the headspace abovethe aqueous phase. Since the introduction of SPMEas a quantitative analytical technique by Arthur andPawliszyn (1990) more than a decade ago, a largeamount of data has been obtained concerning thefundamental mechanisms governing the SPMEprocesses and potential applications of SPME in avariety of research areas (Pawliszyn 1997, 1999,Heringa and Hermens 2003, Mayer et al. 2003). Thesuccess of SPME can be attributed to its simplicityof use, combination of extraction and concentrationin a single step, relatively short sample processingtimes, minimal solvent use, and cost effectiveness.

Successful development and implementation of arobust SPME-based method are strongly dependentupon a thorough understanding of the factors dictat-ing the distribution of analytes between the SPMEsorbent phase and sample matrix. Many SPME-based methods have been developed for specificsample matrices only; therefore, their usefulness islimited. A more universal approach is to employ thecoefficient of distribution (Kf) of an analyte betweenthe sorbent phase and water for quantitation, withadditional considerations of matrix effects if neces-sary. Consequently, accurate determination of Kf

values becomes a critical step toward the develop-ment of a robust SPME-based method. While Kf

values for organic compounds with low hydropho-bicity are relatively easy to determine with precision,

Determination of polydimethylsiloxane(PDMS)-seawater distribution coefficientsfor polychlorinated biphenyls and chlori-nated pesticides by solid-phase microex-traction

Eddy Y. Zeng*, David Tsukada,James A. Noblet2 and Jian Peng

*Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, P.O. Box 1131, Guangzhou 510640, China1California State University-San Bernardino 5500 University Parkway, San Bernardino, CA 92407-2397

quantifying Kf values for very hydrophobic organiccompounds (VHOCs) has remained a challenge toanalytical chemists. In addition, determination of Kf

has been hindered by uncertainties regarding themechanisms of the SPME process, highlighted bythe ongoing vigorous debate over whether absorptionor adsorption is the primary SPME sorption process(Yang et al. 1998, Yang et al. 1998, Hawthorne et al.2000, Poerschmann et al. 2000, Vaes et al. 2000).

One of our goals is to utilize the SPME technol-ogy in field sampling of VHOCs in oceanic environ-ments, a critical compartment for regional and globaldispersal and transport of VHOCs. This objectiverequires calibration of the SPME process for a largenumber of analytes, and thus their associated Kf val-ues. To accomplish this goal, a slow-stirring system(Figure 1) was employed to calibrate a large set ofPDMS-coated fibers for selected polychlorinatedbiphenyls (PCBs) and chlorinated pesticides (includ-ing o,p’- and p,p’-DDT, DDD, and DDE). Thesecompounds normally are measured in southernCalifornia ocean monitoring programs, such as arecent regional survey (Noblet et al. 2002). The 100µm PDMS phase was chosen to maximize the sensi-tivity of the sampling method. Several studies cali-brated PDMS-coated fibers for selected PCB con-geners (Potter and Pawliszyn 1994, Yang et al. 1998,Yang et al. 1998, Mayer et al. 2000, Poerschmann etal. 2000, Paschke and Popp 2003), but Kf values var-ied substantially for different coating thicknesses,

even when the same extraction procedures wereemployed. Since SPME performance is a functionof both fiber thickness and extraction procedure, afurther calibration of the 100 µm PDMS-coated fiberwas warranted for our unique purposes.

THEORETICAL BACKGROUNDFor the convenience of discussion, the analyte

under consideration is assumed to be present initiallyin the aqueous phase. Although this assumptiondoes not affect the generality of the conclusionsderived herein, it is particularly suitable for under-standing the SPME sorption processes for VHOCs asthe vapor pressures of VHOCs are extremely low atroom temperature. If SPME experiments are con-ducted in a closed system, composed of the sorbentphase, water, and headspace only and free of matrixinterferences, the total amount (N0) of the analyteupon completion of SPME can be expressed as:

N0 = Nf + Nw + Nh (1)

where Nf, Nw, and Nh are the amounts of the analytein the sorbent phase, water, and headspace, respec-tively. An equation used to relate Nf with the initialanalyte concentration ( ) can be derived fromEquation (1) (Zeng and Noblet 2002):

Nf = (2)

where Vf, Vw, and Vh are the volumes of the sorbentphase, water, and headspace, respectively, and is the dimensionless Henry’s Law constant. Mostinitial efforts for the development and applications ofSPME-based methods were dedicated to volatileorganic compounds (VOCs), because of the apparentbenefits of using SPME with this group of chemi-cals. VOCs have low hydrophobicity, and thereforelow Kf values. Commercially available SPMEdevices usually have sorbent coating volumes lessthan 1 µL with Kf values less than 100 for VOCs.Hence, use of a moderate sample volume (e.g., ~10mL) could easily satisfy Vw >> KfVf , resulting in thesimplification of Equation (2) to Nf = KfVf

regardless of whether matrix effects are significant.With this simplified equation, the concentrations ofVOCs could be determined conveniently whether theaqueous phase or the headspace is sampled withSPME devices.

Chlorinated pesticides - 293

0w

h'Hwff

h'Hwff ) (

CVKVVK

VKVVK++

+

Figure 1. Schematic of the SPME experimental setup.

0wC

0wC

K 'H

In the case of VHOCs, the Henry’s Law constantis small so that KfVf ≈ Vw >> KH’Vh if the headspacevolume is comparable to the sample volume.Therefore, Equation (2) becomes

Nf = =

Apparently, SPME measurements of VHOCs aredependent on calibration of KfVf or Kf if the sorbentcoating volume is known. For complex samples,matrix effects must be accounted for. For example,an additional term (defined as matrix sorption term,θ) related to interfering sorbent phases was proposedto be included in the sample volume in Equation (3),in order to correctly calculate the analyte concentra-tion (Zeng and Noblet 2002).

Two general calibration methods have beenemployed to determine KfVf values. The firstmethod is a static SPME within a closed system.The following equation or equivalent was derived tocalculate KfVf (Poerschmann et al. 2000, Paschkeand Popp 2003):

KfVf = (4)

One apparent drawback with this method is thatlarge measurement errors may occur if the analyteamount (Nf) in the sorbent phase is approaching theinitial analyte amount ( Vw), i.e., the amount of theanalyte in the sample matrix is severely depletedupon completion of SPME. This could occur withVHOCs if a small sample volume is used. To over-come this drawback, Mayer et al. (2000) proposed aslightly different static SPME strategy. They pre-pared a series of samples with the same analyte con-centration, and added different amounts of PDMS-coated fibers to the samples to obtain varyingPDMS-to-water volume ratios. Subsamples werecollected into 12 mL vials and extracted with con-ventional SPME to determine the analyte concentra-tions. A reference sample without addition ofPDMS-coated fibers was also analyzed. The ratio(Crelative) of the analyte concentrations in the treatedand reference samples was related to the ratio (Vf/Vw)of the volumes of the PDMS coating and water viathe following equation (Mayer et al. 2000):

Crelative = (5)

A nonlinear regression between Crelative and Vf/Vw

yields the distribution coefficient Kf. The advantageof this approach is that the extent of depletion of theanalyte could be adjusted to an optimal range byvarying the amount of PDMS-coated fibers added tothe samples. In addition, Kf was determined withmultiple analyte concentration points, leading toenhanced applicability of Kf within a broad concen-tration range.

The second calibration method is dynamicSPME in which a constant analyte concentration ismaintained by an external supply source (via a flow-through strategy) so that losses of analytes to non-SPME sorbent phases, and consequently matrixeffects, can be disregarded (Poerschmann et al. 2000,Shurmer and Pawliszyn 2000). In this approach,mass balance no longer holds, and Kf is calculateddirectly from its definition, Kf = Cf/Cw. However,the analyte concentration, Cw, in the sample needs tobe determined by a separate analytical protocol, typi-cally a liquid-liquid extraction method. Therefore,the accuracy of the Kf values is subject also to theperformance of a non-SPME method.

In this study, a static SPME strategy was adoptedwith a large sample volume (1.6 L) and multipleSPME devices. In addition, the glassware walls andstirring bar surface were treated as two non-SPMEsorbent phases to improve the quality of the calibrat-ed Kf values. As a result of mass balance, Equation(1) can be modified to:

N0 = Nw + Nf(i) + Nsb(i’) (6)

where Nf(i) is the amount of the analyte sorbed onthe ith SPME device; n the total number of SPMEdevices; Nsb(i’) the amount of the analyte sorbed onthe i’th non-SPME sorbent phase; and n’ the numberof non-SPME sorbent phases. Using the same pro-cedure described previously (Zeng and Noblet 2002),the amount of the analyte sorbed on the jth SPMEdevice is given by:

Nf(j) = (N0 - Nf(i)) (7)

where θ is defined as a matrix sorption term, whichaccounts for the Nsb term in Equation 6. The θ termwill be further discussed below. If S is defined asthe slope of the linear regression of Nf(j) versus (N0 -

Nf(i)), the following equation can be derived:

Chlorinated pesticides - 294

0w

wff

wff CVVK

VVK

+ 0ff

ff NVVK

VK

w+

fw0w

wf

NVC

VN

−

0wC

)/(101

1

wf)log( f VVK+

�=

n

i 1�

=

n'

i 1'

θ++ wff

ff

VVK

VK�⋅

n

ji

(3)

�⋅

n

ji

Σ Σ

Σ

Σ

Chlorinated pesticides - 295

S = or (8)

KfVf =

Apparently, the present analytical method isdeveloped directly from the linearity between theanalyte amount retained by an SPME device and theinitial analyte amount (subtracting the analyteamounts retained by all other SPME devices).Linear regression over a large concentration range (2to 50 ng/L in the present study) ensures the wide-range applicability of the measured Kf values. Inaddition, the use of multiple SPME devices in onecalibration system allows the calibration data to beanalyzed statistically. To estimate the value of θ in agiven system, we rewrite θ as (Zeng and Noblet2002):

θ = (9)

where n’ is the number of non-SPME sorbent phasespresent in the system; is the distribution coeffi-cient of the analyte between the ith non-SPME sor-bent phase and water; and is the apparent mass ofthe ith non-SPME sorbent phase. By definition, =

/Cw, where is the concentration of the analytein the ith non-SPME sorbent phase. By substitutingthis relationship into Equation (9) and noting Nsb(i) =

, the following equation can be derived:

= θ Cw (10)

Therefore, θ can be estimated from the linear regres-sion of versus Cw with being determinedwith any non-SPME method. In the present study,the glassware walls and stirring bars were the non-SPME sorbent phases. Headspace was deemed aninsignificant phase for the target analytes underinvestigation.

METHODSStudy Design

This study was conducted in three incrementalsteps. First, a series of seawater spiked with thesame amount of the target analytes were extractedfor various time durations to establish the kinetics ofthe SPME process. Second, SPME experimentswere conducted at the equilibrium state derived from

the kinetics experiments and were used to determineKfVf values for the target analytes. Finally, the valueof the matrix sorption term, θ, for each analyte wasestimated from non-SPME experiments and used tocorrect for interferences with the determination ofKfVf values from container walls and stir bar surface.

Apparatus and MaterialsSPME devices with 100 µm PDMS coating were

purchased from Supelco (Bellefonte, PA). EachSPME device was washed with hexane and heated at280oC under helium stream (on a gas chromatogra-phy (GC) injection port) for 1 h prior to initial use orafter each injection. Conditioned SPME deviceswere stored in a freezer at –20oC if not used immedi-ately. Glass Erlemeyer flasks with a volume of ~1.7L were obtained from Corning (Corning, NY). Theywere washed with detergent and tap water, rinsedwith deionized water, kilned at 420oC for at least 4 h.Immediately prior to use, each flask was silanizedwith a solution of 15% dimethyldichlorosilane intoluene (Aldrich Chemical, Milwaukee, WI) for ~1min. Silanized flasks were rinsed twice with tolueneand three times with methanol, stored at 100oC, andrinsed with deionized water. Teflon®-coated stirringbars (Corning, Corning, NY) were rinsed with deion-ized water, sonicated in methylene chloride for 20min, and dried at 100oC. Sodium azide was obtainedfrom Mallinckrodt Baker (Phillipsburg, NJ).

Custom-made mixtures of PCB congeners (20µg/mL each in hexane:isooctane (98:2)) and chlori-nated pesticides (100 µg/mL each in acetone) weresupplied by AccuStandards (New Haven, CT).OPTIMA grade acetone and hexane were purchasedfrom Fisher Scientific (Pittsburgh, PA) and used assupplied. Sand-filtered seawater was collected froman off-shore intake of Southern California Edison(Redondo Beach, CA) and used without any treat-ment.

SPME ProceduresStandard solutions containing all target analytes

were mixed with acetone to make up spiking solu-tions (in 0.5 mL acetone) with various analyte con-centrations. Each Erlemeyer flask was filled with1.6 L of seawater and spiked with a spiking solution.One stirring bar was placed in the flask. The antibi-otic agent, sodium azide, was added to the flask ifthe experiment was to be conducted for longer than 4

θ++ wff

ff

VVK

VK

S

S(V

−

+

1

)w θ

in'

i

i mK sb1

sb�=

�=

n'

iiN

1sb )(

iKsb

imsbiKsb

iCsbiCsb

iCsbimsb

�=

n'

i

iN1

sb )( �=

n'

i

iN1

sb )(

Σ

Σ

Σ Σ

d. A silanized Teflon® sheet was bound to the open-ing of the flask with rubber bands to make the sys-tem airtight. Upon rinse with hexane, multipleSPME devices were pierced through the Teflon sheetand into the spiked seawater. The PDMS-coatedfibers were protracted and exposed to the spiked sea-water. The flask was placed on a Corning stirrer(Corning, NY). To minimize heat transfer from thestirrer motor to the flask, a 150 x 15 mm polystyrenePetri dish with lids was placed between the stirrerand the flask. All experiments were conducted atambient temperature 22±2oC. At the end of theextraction, the PDMS-coated fibers were removedwith care from the flask and dipped briefly intodeionized water to remove residual salt from the sea-water. The fibers then were shaken rigorously toremove any water residues before being retractedinto the needle sleeves. Analytes sorbed on SPMEdevices were thermally desorbed into a programmedinjector on a specified gas chromatography/massspectrometry (GC/MS) instrument. SPME devicesnot analyzed immediately were stored at –20oC.

For uptake kinetics experiments, three SPMEdevices were used simultaneously in one flask.SPME extraction times were 1, 2, 4, 8, and 16 h and1, 2, 4, 6, 8, 12, 16, and 24 d. Two agitation speeds,380 and 870 revolutions per minute (rpm), were test-ed. For equilibrium calibration experiments, anextraction time of 12 d and an agitation speed of 870rpm were chosen, based on the results of the kineticsexperiments, to determine Kf values. Nine SPMEdevices were placed in one flask. The calibrationconcentrations were 2, 5, 20, and 50 ng/L for all tar-get analytes.

Non-SPME ProceduresTo determine the θ values, four seawater samples

(1.6 L) containing the target analytes at 100, 250,500, and 1000 ng/L, respectively, were prepared infour Erlemeyer flasks. One stirring bar was placedin each flask and the samples were treated using thesame method as those with the SPME procedures,except that no SPME devices were added. At theend of the 12-d extraction period, seawater wasprocessed with a solid-phase extraction method(Zeng and Khan 1995), stirring bars were extractedwith a roller table method (Zeng and Vista 1997),and the glassware walls were rinsed with methylenechloride and the rinsates were collected. All frac-tions were condensed to 1 mL using a ZymarkTurboVap 500 (Zymark Corporation, Hopkinton,

MA). Internal standards, PCB 30 and 205, wereadded to all extracts prior to instrumental analysis.

GC/MS AnalysisTwo Varian Saturn 2000 GC/Ion Trap MS sys-

tems were used for sample analysis, labeled as GC-MS-1 and GC-MS-2. To maintain consistency, allSPME devices used in the kinetics experiments wereanalyzed using GC-MS-1. SPME devices from theequilibrium experiments were categorized into ana-lytical batches 1 to 7. Devices in batches 1-4 wereanalyzed with GC-MS-1, and those in batches 5-7were analyzed with GC-MS-2. The chromatographicconditions used for these two instruments basicallywere identical except where it was indicated.Chromatographic separation was made with 60 m ´0.25 mm-i.d. (0.25 µm film thickness) DB-5MScolumns (J&W Scientific, Folsom, CA). Columntemperature was programmed from 80oC (hold for 1min) to 176oC at a rate of 8oC/min, followed by aramp to 230oC at a rate of 1.5oC/min, and finallyincreased to 290oC (5oC/min) where it was held for21 min. Both SPME and direct solvent injectionswere conducted with a split/splitless mode (split ini-tially, splitless 0.01 min after injection, and splitagain 2.5 min after injection). The injector tempera-ture was programmed from 100oC (held for 0.05min) to 280oC with the maximum ramping rate(~100oC/min) and held for 40 min at 280oC. Underthese chromatographic conditions, slightly differentretention times were obtained on the two instrumentsfor the same target analytes. To reduce the retentiontime difference, the flow rate was set at 1.0 and 1.3mL/min for GC-MS-1 and GC-MS-2, respectively.All the extracts obtained from the non-SPME proce-dures were analyzed with GC-MS-1.

Mass spectra were acquired with the electronionization mode. Mass spectra were acquired from100 to 504 m/z with a scan time of 0.7 scans per sec-ond and an emission current of 15 mamps. Withinthis range, the ion storage level was 79 and the ion-ization time factor was 100%. The ionization timefactor was 10% outside this range. Electron multi-plier voltage was 1900-2000 eV for GC-MS-1 and1500-1600 eV for GC-MS-2, because a newer elec-tron multiplier was installed in GC-MS-2.Temperatures of the ion trap, manifold, and transferline were set at 200, 80, and 280oC, respectively. Toensure the linearity of the instrument performance,calibration standard solutions containing all the tar-get analytes at 50, 100, 250, 500, 1000, and 2000

Chlorinated pesticides - 296

ng/mL with internal standards at 500 ng/mL wereanalyzed frequently throughout the study. Linearcalibration curves were always obtained for all targetanalytes.

Data AnalysisNormalization of MS Responses. Calibration is a

necessary step in instrumental analysis in order toaccount for the variability in instrument perform-ance. In a regular GC/MS analysis, instrument vari-ability can be corrected intrinsically by the additionof internal standards into the calibration standardsolutions and samples. With SPME, however, inter-nal calibration is possible only if both the target ana-lyte and its deuterated counterpart are analyzedsimultaneously. This approach faces two obstacles.First, the cost of employing deuterated standardscould become extraordinary for a large number ofanalytes. Second, even with the use of deuteratedcompounds, the SPME behavior and MS responsesmust be assumed identical for both the undeuteratedand deuterated counterparts, which remains to befully verified. In line with these considerations, anexternal calibration method was used in our study.

Prior to the analysis of each batch of up to sevenloaded SPME devices, 1 µL of a standard mixturecontaining all the target analytes at 2 µg/mL wasinjected into the GC/MS instrument with anautosampler. The MS responses from the directinjection of the standard solution and desorption ofanalytes sorbed on SPME devices were used to cal-culate either normalized responses for the kineticsexperiments or analyte amounts for the equilibriumexperiments.

Kinetic Data. A typical SPME process generallyis believed to occur via a first-order diffusion of thetarget analyte across the polymeric coating-waterinterface. The amount (Nf) of the analyte sorbed onan SPME device may be related to extraction time (t)through the following equation (Ai 1997):

Nf = (1 - e-bt) (11)

where is the amount of the analyte sorbed on thedevice fiber at truly equilibrium state (t→∝) and b isa kinetic constant related to the types of polymericcoating and analyte, as well as the sample volume(Ai 1997). In the context of sorption and desorptioninvolved in a diffusion process, b can also be regard-ed as the rate of desorption from the SPME sorbentphase to the aqueous phase. Apparently, Equation

(11) can be rearranged to estimate the percent ofequilibrium state (defined as PES) with finite extrac-tion time t:

PES = 100% (1 - e-bt) (12)

Finally, if the system is not at equilibrium state whenthe analyte is sampled, the time factor is given by 1 -e-bt, based on a nonequilibrium model (Ai 1997).Equation (8) can be modified to

KfVf =

RESULTS AND DISCUSSIONKinetics of SPME Process

The SPME process was simulated reasonablywell with a first-order diffusion model depicted byEquation (11). The correlation coefficients for themodel simulation were largely about 0.7 (Table 1),indicating a fair amount of variability in the kineticexperiments. Since different PDMS-coated fiberswere used at different time points in the experiments,the variability may partially reflect differences in thesorptive capacity among individual fibers.

The values increased initially and thendecreased with congener number for PCBs, but bessentially decreased with increasing congener num-ber. As a result, the percent of equilibrium state(PES) calculated with Equation (12) at 12 d generallydecreased with increasing congener number (Table1). However, the PES values at 12 d were greaterthan 80% for all analytes but PCB 209. In general,chlorinated pesticides reached a higher percent ofequilibrium state than PCBs under the experimentalconditions. In the equilibrium experiments, anextraction time of 12 d was used. Because of themoderate variability of the data set, there was noneed to include the extraction time factor as indicat-ed in Equation (13) in the determination of KfVf val-ues.

As stated previously, one objective of this studywas to develop a feasible field sampling methodbased on the SPME technology. Consequently, theagitation speed was set to simulate the speed of bot-tom currents in the coastal ocean of southernCalifornia. A previous study obtained the near-bot-tom current speeds at ~5-6 cm/s around the coastaloceans off southern California (Southern CaliforniaCoastal Water Research Project 1994). The agitation

Chlorinated pesticides - 297

ofN

ofN

Se

S(Vbt −−

+-w

1

)θ

ofN

velocity in water, labeled as u(r), could be estimat-ed through the following equation (Pawliszyn1997):

u(r) = 0.575pNR2 for r > 0.74R (14)

where R is the radius of the stir bar; N is the revo-lutions per second; and r is the distance betweenthe center of the container and the PDMS-coatedfiber. The agitation velocity in our experimentsestimated from Equation (14) was about 4 cm/s.Note that Equation (14) is applicable to cylindricalcontainers, whereas the flasks used in our experi-ments are pear-shaped. As the PDMS-coatedfibers were positioned at the smaller end of theflask (Figure 1), the agitation velocity based onEquation (14) was likely underestimated.Therefore, the actual agitation velocity is consid-ered slightly greater than 4 cm/s, but still muchslower than those normally used by otherresearchers. One negative consequence of using aslow-stirring procedure with a large sample vol-ume (1.6 L) is the extended experimental timeneeded to reach equilibrium. This could allowbacteria to grow, which could biodegrade the ana-lytes. We observed that both o,p’- and p,p’-DDTbegan to suffer losses after more than 4 d ofSPME experiments without the antibiotic agent(sodium azide) added. Therefore, it was necessaryto add the antibiotic agent to samples subject toSPME of equal to or longer than 4 d.

In several previous studies, the equilibriumtime for SPME of PCBs varied from several hours(Yang et al. 1998, Yang et al. 1998) to severalweeks (Mayer et al. 2000), depending mainly onthe effective agitation velocity around the SPMEfiber. As indicated by Equation (14), the agitationvelocity is disproportional to the distance betweenthe SPME fiber and the center of the container.Hence, the agitation velocity likely decreases withincreasing sample size. It is also beneficial to usestirring bars with a large radius if a large samplecontainer is employed.

Determination of KfVf ValuesTable 2 summarizes the data acquired from the

calibration of the 100 µm PDMS-coated fibers.The log Kf values were calculated from the KfVf

data and the Vf value of 0.612 µL provided bySupelco. The five-point calibration (including theorigin) procedure employed to obtain KfVf using

Chlorinated pesticides - 298

Table 1. Kinetic parameters associated with SPMEprocesses based on Equations (11) and (12). R2 is the cor-relation coefficient for the nonlinear regressions.

r1

Equation (7) appeared valid, as signaled by generallyhigh r2 values for a total of 60 analytes. The linearregressions to estimate θ values for all the analytesusing Equation (10) were also reasonably sound asan average r2 value was 0.88±0.14.

An unexpected occurrence is the significant dif-ference between the KfVf values obtained with twoseemingly identical GC/MS systems. The target ana-lytes that do not have significant different KfVf val-ues obtained with GC-MS-1 and GC-MS-2 are PCB194, PCB 206, PCB 209, endrin, and o,p’-DDT.Except for o,p’-DDT, KfVf values for these com-pounds are all unexpectedly low (Table 2). As theSPME devices were randomly selected from a largepool purchased on different days, variability in thesorption property of the commercial PDMS-coatedfibers was ruled out as the significant source of thedifference. The Corning stirrers were maintained atthe same operational mode during the entire experi-mental period and were chosen randomly for specifictesting batches. Hence, agitation speed was alsoruled out as the main reason for the difference. Inanalyses of the analytes desorbed from the PDMS-coated fibers, mass spectral abundances (area counts)from analysis of solvent-prepared standards wereused to normalize those from the PDMS-coatedfibers. It appears that the two GC/MS instrumentshad different responses to the mass spectral abun-dances from the injection of solvent-prepared stan-dards, compared to those from desorption of analytessorbed in the PDMS phase. This caused a substan-tial discrepancy between the normalized area countsobtained with the two GC/MS instruments for thesame level of SPME exposure. However, the mecha-nism behind the discrepancy remains to be identi-fied.

Regardless of the difference between the twogroups of calibration data, the correlation betweenlog Kf and log Kow was similar for both groups(Figure 2). Log Kf increases with log Kow initially,but reaches a plateau at log Kow ≈ 6.5, and thendecreases as log Kow continues to rise. To betterdemonstrate the dependence of log Kf on log Kow, thePCB congeners in Group 1 (analytical batches 1-4)were grouped based on the number of chlorines(homolog) on the benzene rings. Log Kf increaseswith increasing log Kow for homologs 3-4 and 5, butdecreases with increasing log Kow for homologs 6and 7-10 (Figure 3). Doong and Chang (2000) alsoreported a linear correlation between Kf and Kow for

polycyclic aromatic hydrocarbon (PAH) compoundswith log Kow less than six, but obtained a negativecorrelation for five- and six-ring PAHs.

In general, the quality of linear regressions withGroup 1 is better than that with Group 2 (Table 2).Therefore, the calibration data for Group 1 will beused in the following section to compare with previ-ously acquired data in the literature.

Comparison with Previous StudiesA number of studies obtained Kf values for

selected PCB congeners and DDT compounds withPDMS-coated fibers (Table 3). Apparently, a largevariability in Kf values has been obtained with differ-ent experimental procedures, PDMS coating thick-ness, and researchers. For example, Mayer et al.(2000) obtained higher Kf values with increasing Kow

values with a 6-wk extraction time compared to a 3-d extraction using a 15 µm coating. Sufficient equi-librium time was cited as an important factor toachieve appropriate Kf values. Poreschmann et al.(2000) acquired higher Kf values with a larger sam-ple volume (250 mL) than with a smaller one (4 mL)using a static SPME method. They were able toachieve even higher Kf values using a dynamicSPME method in which the analyte concentrationswere maintained constant by an external supplysource. More recently, Paschke and Popp (2003)used a static SPME method to determine Kf on 7 andand 10 µm PDMS-coated fibers in an Erlenmeyerflask (with a sample size of 480 mL). The Kf valuesfor PCB congeners on the 7 µm PDMS-coated fibersessentially increase with increasing Kow values. TheKf values for PCB congeners on the 10 µm PDMS-coated fibers also increase initially with increasingKow values, but top out at log Kow≈ 6.9 and thendecrease slightly afterwards (Table 3). The log Kf

values obtained in the present study using a 100 µmPDMS coating increase with increasing log Kow upto log Kow≈ 6.5, and decreases drastically afterwards(Figure 2). The log Kf value for p,p’-DDE(5.74±0.07) determined in the present study is simi-lar to those acquired by Meyer et al. (2000) using a15 µm PDMS coating (5.73±0.09 and 5.88±0.05 forextractions times of 3 d and 6 wks, respectively), butquite distinct from those obtained by Paschke andPopp (2003) for 7 µm (5.39) and 100 µm (5.26)PDMS coatings. Our log Kf values of p,p’-DDD andp, p’-DDT were also inconsistent with those meas-

Chlorinated pesticides - 299

Chlorinated pesticides - 300

Table 2. Equilibrium sorption properties of polychlorinated biphenyls (PCBs) and chlorinated pesticides onpoly(dimethylsiloxane) coated fibers. r2 is the correlation coefficient for linear regressions on Equation (7).The number of fibers (samples) for Groups 1 and 2 were 26 and 25, respectively. Water volume was 1.6 L forall the experiments.

ured by Paschke and Popp (2003) and Poreschmannet al. (2000) (Table 3).

The above comparison points to the significanceof PDMS coating thickness to the sorption capacityfor PCB congeners of different sizes. Langenfeld etal. (1996) also observed a substantial differencebetween the Kf values with 7 µm and 100 µmPDMS-coated fibers for a number of PAH com-pounds. They attributed the difference mainly topossible different physical or chemical properties ofthe PDMS-coated fibers that could greatly affect theabsorption of high molecular weight compounds. Itis interesting to note that the correlation betweenlog-based bioconcentration factors (BCFs) of PCBsobtained from field measurements of 10 perch indi-viduals and log Kow was also a bell-shaped curve(Bremle et al. 1995) similar to those displayed inFigure 2. The authors ascribed it to a number of fac-tors. Notably, solubility, fat quality, uptake rate, andhydrophobicity were considered possible factorsresponsible for the bell-shaped curve. Parallel tothese observations, the size of PCB congeners mayalso play a significant role in elucidating the sorptionmechanism for PDMS coatings. As the number ofchlorines on the phenyl rings increases, the PCBcongeners become bulky, with high electron densityfrom the chlorines. The bulky molecules have thetendency to induce dispersive forces, which are

instantaneous and repulsivein nature, from interactingwith, or permeating into thePDMS phase. If the sorbentphase is also thick, theinduced dispersive forcesmay be sufficient to substan-tially lower the sorptioncapacity for large-size PCBcongeners. Obviously, moreresearch is needed to verifythis hypothesis.

Absorption versusAdsorptionThe issue of whether the

SPME process with PDMScoating is absorption oradsorption has drawn heateddebate (Yang et al. 1998,Yang et al. 1998, Hawthorneet al. 2000, Poerschmann etal. 2000, Vaes et al. 2000).

Chlorinated pesticides - 301

Figure 2. Correlation of measured log Kf and logKow for polychlorinated biphenyls (PCBs) with (A)Group 1 and (B) Group 2. Log Kow values wereobtained from (Hawker and Connell 1988).

Figure 3. Correlation of measured log Kf and log Kow for polychlorinatedbiphenyls (PCBs) organized according to the number of chlorines(homolog): (A) homologs 3-4; (B) homolog 5; (C) homolog 6; and (D)homologs 7-10.

Chlorinated pesticides - 302

Absorption is defined as a sorption process dominat-ed by linear partitioning of the analyte into the sor-bent phase; therefore, the amount of the analytesorbed on the sorbent phase is proportional to thesorbent volume. Consequently, a linear relationshipsuch as those shown in Figures 3a and 3b existsbetween log Kf and log Kow. On the other hand,adsorption is defined as a sorption process dictatedby the interaction between the sorbent surface andthe analyte. The amount of the analyte sorbed on thesorbent phase is proportional to the sorbent surfacearea instead of volume. A negative linear correlationexists between log Kf and log Kow such as thoseshown in Figures 3c and 3d.

If the above arguments hold, sorption of PCBson 7 µm and 15 µm PDMS coatings is an absorp-tion process, whereas that of PCBs on 100 µmPDMS coating seems to be consistent with a com-bined process of absorption and adsorption (Table 3).Furthermore, sorption of PCB congeners on the 100µm PDMS coating appears to proceed via absorptionfor PCBs in homologs 3-5 and via adsorption forPCBs in homologs 6-10 (Figure 3). However, such adescription seems over-simplified. It is particularlychallenged by the hypothesis of induced dispersive

forces discussed in the previous section.Investigations into the structure of PDMS coatingand the interacting forces between PCBs and thePDMS phase are necessary to better understand themechanism of SPME processes.

LITERATURE CITEDAi, J. 1997. Solid phase microextraction for quantitativeanalysis in nonequilibrium situations. AnalyticalChemistry 69: 1230-1236.

Arthur, C.L. and J. Pawliszyn. 1990. Solid phase microex-traction with thermal desorption using fused silica opticalfibers. Analytical Chemistry 62: 2145-2148.

Bremle, G., L. Okla and P. Larsson. 1995. Uptake ofPCBs in fish in a contaminated river system:Bioconcentration factors measured in the field.Environmental Science and Technology 29: 2010-2015.

Doong, R.-A. and S.-M. Chang. 2000. Determination ofdistribution coefficients of priority polycyclic aromatichydrocarbons using solid-phase microextraction.Analytical Chemistry 72: 3647-3652.

Table 3. Comparison of experimentally measured log Kf (PDMS phase-water distribution coefficient) values.All data were acquired with static SPME methods except for those by Poreschmann et al. (2000) as indicated.

Hawker, D.W. and D.W. Connell. 1988. Octanol-waterpartition coefficients of polychlorinated biphenyl con-geners. Environmental Science and Technology 22: 382-387.

Hawthorne, S.B., Y. Yang, C.B. Grabanski, D.J. Miller andM.L. Lee. 2000. Response to comments on adsorptionversus absorption of polychlorinated biphenyls onto solid-phase microextraction coatings. Analytical Chemistry 72:642-643.

Heringa, M.B. and J.L.M. Hermens. 2003. Measurementof free concentrations using negligible depletion-solidphase microextraction (nd-SPME). Trac-Trends inAnalytical Chemistry 22: 575-587.

Langenfeld, J.J., S.B. Hawthorne and D.J. Miller. 1996.Quantitative analysis of fuel-related hydrocarbons in sur-face water and wastewater samples by solid-phasemicroextraction. Analytical Chemistry 68: 144-155.

Mayer, P., J. Tolls, L. Hermens and D. Mackay. 2003.Equilibrium sampling devices. Environmental Science andTechnology 37: 184A-191A.

Mayer, P., W.H.J. Vaes and J.L.M. Hermens. 2000.Absorption of hydrophobic compounds into thepoly(dimethylsiloxane) coating of solid-phase microex-traction fibers: High partition coefficients and fluores-cence microscopy images. Analytical Chemistry 72: 459-464.

Noblet, J.A., E.Y. Zeng, R.W. Gossett, C.R. Phillips, R.J.Ozretich and R. Baird. 2002. Southern California Bight1998 Regional Monitoring Program: V. SedimentChemistry. Southern California Coastal Water ResearchProject. Westminster, CA.

Paschke, A. and P. Popp. 2003. Solid-phase microextrac-tion fibre-water distribution constants of more hydropho-bic organic compounds and their correlations withoctanol-water partition coefficients. Journal ofChromatography A 999: 35-42.

Pawliszyn, J. 1997. Solid Phase Microextraction: Theoryand Practice. Wiley-VHC. New York, NY.

Pawliszyn, J. 1999. Applications of Solid PhaseMicroextraction. Royal Society of Chemistry. Cambridge,UK.

Poerschmann, J., T. Górecki and F.-D. Kopinke. 2000.Sorption of very hydrophobic compounds onpoly(dimethylsiloxane) and dissolved humic matter. 1:Adsorption or partitioning of VHOC on PDMS-coatedsolid-phase microextraction fibers - A never-ending story?Environmental Science and Technology 34: 3824-3830.

Potter, D.W. and J. Pawliszyn. 1994. Rapid determinationof polyaromatic hydrocarbons and polychlorinatedbiphenyls in water using solid-phase microextraction andGC/MS. Environmental Science and Technology 28: 298-305.

Shurmer, B. and J. Pawliszyn. 2000. Determination of dis-tribution constants between a liquid polymeric coastingand water by a solid-phase microextraction technique witha flow-through standard water system. AnalyticalChemistry 72: 3660-3664.

Southern California Coastal Water Research Project. 1994.Near-bottom currents off southern California. pp. 75-85in: J.N. Cross (ed.), Southern California Coastal WaterResearch Project Annual Report 1992-1993. SouthernCalifornia Coastal Water Research Project. Westminster,CA.

Vaes, W.H.J., P. Mayer, A.G. Oomen, J.L.M. Hermens andJ. Tolls. 2000. Comments on “Adsorption versusAbsorption of Polychlorinated Biphenyls onto Solid-PhaseMicroextraction Coatings”. Analytical Chemistry 72: 639-641.

Yang, Y., S.B. Hawthorne, D.J. Miller, Y. Liu and M.L.Lee. 1998. Adsorption versus absorption of polychlorinat-ed biphenyls onto solid-phase microextraction coatings.Analytical Chemistry 70: 1866-1869.

Yang, Y., D.J. Miller and S.B. Hawthorne. 1998. Solid-phase microextraction of polychlorinated biphenyls.Journal of Chromatography A 800: 257-266.

Zeng, E.Y. and A.R. Khan. 1995. Extraction of municipalwastewater effluent using a 90-mm C-18 bonded disks.Journal of Microcolumn Separations 7: 529-539.

Zeng, E.Y. and J.A. Noblet. 2002. Theoretical considera-tions on the use of solid-phase microextraction with com-plex environmental samples. Environmental Science andTechnology 36: 3385-3392.

Zeng, E.Y. and C. Vista. 1997. Organic pollutants in thecoastal environment off San Diego, Calfornia. 1. Sourceidentification and assessment by compositional indices ofpolycyclic aromatic hydrocarbons. EnvironmentalToxicology and Chemistry 16: 179-188.

ACKNOWLEDGEMENTSWe are indebted to V. Raco-Rands for drawing Figure

1 and D. Young for assistance in setting up some of theSPME experiments.

Chlorinated pesticides - 303