Environ. Sci. Technol. 1993, 27, 2489-2496
Lipid-Containing Semipermeable Membrane Devices for Monitoring Organic Contaminants in Water James N. Hucklns,’J Gamlni K. Manuweera,* Jlmmie D. Petty,t Donald Mackay,§ and Jon A. Lebot
National Fisheries Contaminant Research Center, U S . Fish and Wildlife Service, 4200 New Haven Road, Columbia, Missouri 65201, Pesticide Registration Office,Gatambe, Peradeniya, Sri Lanka, and Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, Ontario, Canada M5S 1A4
A semipermeable membrane device (SPMD) is described for passive in-situ monitoring of organic contaminants in water. The device consists of a thin film of neutral lipid (molecular mass generally 1600 Da), such as triolein, enclosed in thin-walled layflat tubing made of low-density polyethylene or another nonporous polymer. Mathematical models are developed for the device and fitted to concentration data from 2,2’,5,5’-tetrachlorobiphenyland phenanthrene flow-through exposures and dissipation experiments. Model estimates of the average concentrations of test chemicals in laboratory exposure water differed from the measured concentrations by 98% purity, 19.4 mCi/mmol), a model polyaromatic hydrocarbon (PAH), were purchased from Sigma Chemical Co., St. Louis, MO. Autoradiography, Envlron. Sci. Technol., Vol. 27, No. 12, 1993 2491
Table I. Selected Propertiee of Test Compounds
compound phenanthrene 2,2/,5,5/-tetrachlorobiphenyl
molecular weight 178 292
box dimensionsa (A) length breath* depth
H2O solubility (rgII-4)
log KOW’
log K m e
log Ksw f
7.9 8.6
1000
4.4 5.8
4.2 4.6
5.0 5.6
11.6 11.6
3.2 6.5
30
a Smallest box (ref 27) dimensions that the molecule (minimized energy configuration) will fit into, calculated using Alchemy 11. * Crossfrom refs 28 and 3, respectively. sectional diameter; the second largest dimension. H20 solubility of phenanthrene and 2,2’,5,5’-tetrachlorobiphenyl d 1-Octanol-water partition coefficient from refs 28 and 3. e PE membrane-water partition coefficient. f Triolein-water partition coefficient.
Table 11. Estimation of Average Analyte Water Conoentration Using Eq 6 for SPMD Flow-Through Exposure Data
analyte phenanthrene 2,2’,5,5’-tetrachlorobiphenyl a
exposure time (h)
water concn measured (ng/L)
water concn model estimate (ng/L)
diffusion coefficient* (m2/h)
X-intercept (h)
0-504 0-672 0-336
0.76 5.48 0.90
0.53 4.95 0.85
2.64 X 10-11 2.29 X 10-11 6.15 X 10-12
0 0 10.5
0-336
9.60
6.39
7.82 X 1@12
9.3
At steadv state. diffusivitv is eauivalent to k,Y or P I K m .
just prior to study initiation, was used to confirm that the purity of these test chemicals was >95%. Details of the static exposure system have been reported elsewhere (31, and key aspects of the flow-through systems are as follows. Radiolabeled test chemicals were dissolved in nanograde acetone, and the appropriate amounts of stock solution were delivered into aquaria water by Micromedic pumps. Forty-eight SPMDs per aquarium were suspended vertically from 30.5-cm-diameter stainless steel rings whose centrums were the input points of exposure water. Each aquarium contained 30 L of water, and the volume was exchanged every 30 min. Test chemical stock bottles were amber glass and light was maintained at a minimal level to reduce the potential for photolysis. Concentrations of test chemicals in exposure system water were determined weekly or more often by liquid scintillation counting of hexane extracts of water samples. These results were confirmed by capillary gas chromatography (GC) analysis of selected samples. Electron capture and photoionization GC detectors were used for 2,2’,5,5’-TCB and phenanthrene, respectively. Dissipation studies were conducted in 1-L beakers (one SPMD per beaker) with a complete volume exchange of untreated water in 0.69871, a good fit of eqs 4 and 6 to the data was anticipated. As shown in Table 11, model (eq 6) estimates of phenanthrene concentrations (CW)in exposure water are close to the measured values.
500
I
~
Rate Constant
400
I
= 1 84X10-3
-
1
400
nc
\M e
300
v
-c 0 *
2 200 .-c 0
e
0
0
100
0 ‘ 0
I
I
I
200
400
600
0 800
0
Flgure 3. Plot of eq 6fitted to SPMD data from a flow-through exposure (672 h) to 5.48 ng/L of phenanthrene. Four replicate SPMDs were analyzed at each sample time, and error bars (not shown when smaller than symbols) represent standard devlations. I
!
I
I
I
I
1
I
I
350
400
-4
Rate C o n s t a n t
= 3 24x10
-
0
0
50
I
!
I
100
150
200
50
100
150 200
250
300
350
400
Time (h)
Time (h)
I
1
250 300
Time (h) Flgure 4. Plot of eq 6 fitted to SPMDdata froma flow-through exposure (336 h) to 0.9 ng/L of 2,2‘,5,5’-TCB. Four repllcate SPMDs wereanalyzed at each sample time, and error bars represent standard deviations.
The PCB uptake data plotted in Figures 4 and 5 show linear kinetic control throughout the 336-h exposures. There is evidence of a delay in analyte uptake by SPMD lipid, Le., the curve does not pass through the origin because of the time required for membrane penetration. Specifically, the 2,2’,5,5’-TCB to values or lag times from eq 6 were 10.5 h (0.9 ng/L) and 9.3 h (9.6 ng/L). No significant tovalue was observed for phenanthrene uptake. Although 2,2’,5,5’-TCB concentrations in SPMDs did not reach the curved region of uptake, estimates of 2,2’,5,5’-TCB concentrations in water using eq 6 (Table 11) were still close to measured values. Analysis of variance associated with fitting eq 6 to phenanthrene and 2,2’,5,5’-TCB exposure data revealed that deviation from regression was not significant (P > 0.05) and R2values ranged from 0.95 to 0.97. An incorrect solution based on a local minimum is possible, but this type of error is unlikely because of the similarity of the estimates of two concentrations and the close approxi-
Flgure 5. Plot of eq 6 fitted to SPMD data from a flow-through exposure
(336h)to9.6 ng/Lof 2,2’,5,5’-TCB. FourrepllcateSPMDswereanalyzed at each sample tlme, and error bars (not shown when smaller than symbols) represent standard deviations.
mation of the measured CW’S. In the case of the 2,2‘,5,5‘TCB exposures Rws lo6), assuming biofouling of the exterior membrane surface can be controlled (22), uptake by SPMDs should still be in the linear kinetic region at 14 d. For chemicals having a Ksw of about 20 000 or less, equilibrium should be approached during longer exposures (128 d) because kdKMstl Vs or k,t will be relatively large and exp(-k,t) will be small. In this study, SPMD performance appeared to be adequately described by eq 4. For both test compounds, the group kdKMW/VS or k,Ksw lies in the range of 100200 h-l during the exposure times shown in Table 11.The implication is that, for each hour of exposure, the lipid in the device effectively removed a chemical from a volume of water some 100-200 times its own volume. Actually, the device’s contaminant removal rate is significantly higher, because the PE membrane is about 3 times the mass of the lipid and measured KMSvalues ranged from about 0.1 to 0.3 (3). Thus, if organic solvent dialysis (16) is used to recover contaminants from intact SPMDs, the mass of analytes detected in SPMDs reflects concentrations in both the lipid and membrane phases. Lebo et al. ( 4 ) reported that CS values can be determined from the total analyte mass in a SPMD dialyzate (MD)by
Envlron. Scl. Technol., Vol. 27, No. 12, 1993
(9)
where M S and MMare the weights of the sequestering media and the membrane, respectively. Earlier work (10) with a high free-volume membrane showed that, w h e n K m is very large, membrane resistance becomes negligible, switching rate control to the water diffusional layer. In general, membrane control of SPMD sampling rate is desirable because the variance associated with intrinsic properties of the device and similar controlled-release membrane systems should be smaller than that associated with systems controlled by extrinsic boundary layers (3, 11). Other SPMD research (3), the common use of thin P E films for increasing resistance to mass transfer in controlled-releasemembrane systems (II), and a review by Lloyd and Meluch (19) on polymeric membrane permeability suggest that PE SPMDs should maintain membrane control of the uptake rates of most high Kow analytes. In this study, the lack of a significant increase in CS during turbulent thinning of the SPMD aqueous diffusional layer indicates that, for the PCB congener tested, resistance to mass transfer through the membrane (l/kp) was the rate-limiting step in uptake. However, it is possible that a KMWregion exists for some chemicals in which mass-transfer resistance in the aqueous layer exceeds that of the PE membrane phase. More SPMD uptake data are needed for a variety of chemicals with a range of KSWand KMWvalues before a definite conclusion can be reached on the relative magnitude of the various MTCs and resistances. Both temperature and biofouling of membrane surfaces can affect SPMD samplingrates. Huckins et ai. (19)found that weekly dipping (submersing for 15min) of SPMDs in Sanaqua (didecyldimethylammonium chloride) reduced biofouling and enhanced phenanthrene uptake relative to untreated SPMDs. The use of a permeability reference
-
standard (i.e., a noninterfering [analytically] compound with moderate SPMD fugacity added to the sequestering media just prior to deployment) was also suggested for an in-situ estimation of k, to correct for the potential effects of biofouling and changes in temperature. Manuweera (24) examined the role of temperature (18-30 “C) in P E SPMD permeability (PI or DKMW(the key variable in SPMD sampling rate) and found that phenanthrene’s P increased as expected from 18 to 24 “C but appeared to deviate from an Arrhenius relationship of temperature and permeability beyond 24 “C. Huckins et al. (3) and Johnson (7) have pointed out a number of similarities between the uptake of contaminants by passive samplers and the bioconcentration of the same compounds in aquatic organisms. Earlier work (25) also indicated that the permeation of nonelectrolytes through biological membranes and nonporous polymeric sheets represented similar phenomena. Mackay and Hughes (20) developed several equations, using the fugacity approach, to describe the uptake and depuration of organic contaminants by fish. Their model was also a version of the two-film model with resistances in a water phase and an organic phase in series. These contaminant uptake resistances are expressed as fish-specific transport times T , and T, which combine with Kow to model the clearance rate constant kz such that (10) l / k 2 = r, + KOWrw As shown earlier, the analogous term to k, is the overall uptake rate constant k, which can be shown to be = VS/k&MSA + V S K S W / k d (11) The group Vs/kd(MsA is thus an organic-phase transport , V&w/k,A is analogous to Kowr,, Le., Kow time T ~and is analogous to Ksw and Vs/k,A is analogous to r,, the water-transport time. An attractive long-term goal is to establish l/k, values or T, and rwKowvalues for various contaminants and fish species and compare these values to SPMD l/k, values for the same contaminant. This would enable the estimation of the uptake of a contaminant by fish from SPMD data.
Applications When viewed in light of SPMD theory and practice, the device has several advantages over conventional sampling. (i) If CWvaries (as is likely in aquatic systems), then the device will respond to an average value, specifically the average value which has prevailed over approximately the most recent response time T . In most environmental exposures, T should be of sufficient magnitude to ensure retention of concentrated lipophilic residues from episodic contamination events. (ii)The device samples the “available” or truly dissolved chemical, not the total concentration of chemical, because the extremely small breadthof the nonporous membrane’s transport corridors limits the molecular size of permeants. The former is of primary importance when assessing contaminant toxicity or bioconcentration potential in waters with high and variable concentrations of sorbing materials. The device appears to offer the same advantages as “fugacity sensing” (26) or sparging systems in which the chemical concentration in water is inferred from that in air bubbled through an aqueous phase.
(iii) If a contaminant’s Ksw is large, a high concentration
(CS)in SPMDs can be achieved, which generally enables more accurate analytical determinations and may be of sufficient mass for bioindicator tests. This concentration enhancement feature is increasingly important as efforts such as the “US.EPA Great Lakes Water Quality Initiative” are taken to reduce levels of some hydrophobic contaminants to CO.1 ng/L. Analysis of compounds at this ultra-trace-level requires sophisticated sampling, extraction, and quality control procedures which are beyond the capability of most laboratories. The possibility thus emerges that contaminants may be regulated at levels in water that cannot be measured by conventionalmethods. The use of an in-situ concentrating device of the type described here appears to offer a feasible solution to this problem. (iv) Because uptake and dissipation are mediated by passive-partitioning processes, the concentrations of environmentally labile contaminants (especially biodegradable compounds) in SPMDs should be more representative of actual aqueous exposure levels than residue concentrations in biomonitoring organisms. Conclusions Although lipid-containing SPMDs have been shown to be useful tools for the detection of organic contaminants in water, their ability to function as quantitative monitoring devices has yet to be fully demonstrated. This work was conducted to contribute toward the use of SPMDs for the estimation of average concentrations of dissolved organic contaminants in water and ultimately for the prediction of Contaminant uptake by aquatic organisms. Acknowledgments We are grateful for the technical assistance and advice of V. Gibson and R. Clark during all phases of this work. Also, we appreciate the contribution of J. Zajicek in the deployment, cleanup, data reduction, and figure generation of SPMDs exposed to an urban stream. The assistance of J. Meadows in the analysis of water samples, G. Tegerdine in the GC confirmation of phenanthrene and 2,2’,5,5’-TCB residues, and M. Ellersieck in statistical analysis of SPMD data sets is gratefully acknowledged. Finally, we thank Harry Prest for encouragement, Prof. H. Yasuda for insights on polymer permeability, and M. Barron for many helpful suggestions. Author Supplied Registry Numbers: 2,2’,5,5’-TCB, 35693; phenanthrene, 85-01-8. Literature Cited (1) Underhill, D. W.; Fiegley, C.E. Anal. Chem. 1991,63,1011. (2) Fowler, W. K. Am. Lab 1982,14,80. (3) Huckins, J. N.; Tubergen, M. W.; Manuweera, 6 . K. Chemosphere 1990,20,533. (4) Lebo, J. A.; Zajicek, J. L.; Huckins, J. N.; Petty, J. D.; Peterman, P.H. Chemosphere 1992,25,697. ( 5 ) Prest, H. F.; Jarman, W. M.; Burns, S. A.; Weismuller, T.; Martin, M.; Huckins, J. N. Chemosphere 1992,25,1811. (6) Sodergren, A. Enuiron. Sci. Technol. 1987,21,855. (7) Johnson, G. D. Enuiron. Sci. Technol. 1991,25,1897. (8) Hassett, J. P.; Force, M.; Song, H. Abstracts of Papers; 198th Meeting of the American Chemical Society, Miami Beach, FL; American Chemical Society: Washington, DC,
1989;ENVR 180. (9) McEachren, I. S.;Fish, C. L.; Hassett, J. P. Abstracts of Papers; 201st Meeting of the American Chemical Society, Environ. Sci. Technol., Vol. 27, No. 12, 1993 2495
Atlanta, GA, American Chemical Society: Washington, DC, 1991; ENVR 86. (10) Flynn, G. L.; Yalkowsky, S. H. J.Pharm. Sci. 1972,61,838. (11) Comyn, J., Ed. Polymer Permeability; Elsevier Applied Science Publishers L t d New York, 1985; p 383. (12) Hwang, S. T.; Kammermeyer, K., Ed. Membranes i n Separations; Robert E. Krieger Publishing Com., Inc.: Malabar, FL, 1975; p 559. (13) Opperhuizen, A; Velde, E. W.; Gobas, F. A. P. C; Liem, D. A. K.; Steen, J. M. D. Chemosphere 1985,14,1871. (14) Chiou, C. T. Environ. Sci. Technol. 1985,19,57. (15) Gray, M. A.; Spacie, A. 12th Meeting of the Society of Environmental Toxicology and Chemistry, EMAP Session, 1991; Poster No. 272. (16) Huckins, J. N.; Tubergen, M. W.; Lebo, J. A,; Gale, R. W.; Schwartz, T. R. J. Assoc. Off. Anal. Chem. 1990,73,290. (17) Sherwood, T. K.; Pigford, R. L.; Wilke, C. R. Eds. Mass Transfer; McGraw-Hill Book Co.: New York, 1975. (18) Yasuda, H. J. Polymer Sci. 1967,5 (Part A-1) , 2952. (19) Lloyd, D. R.; Meluch, T. B. Abstracts of Papers; 187th Meeting of the American Chemical Society, Division of Polymeric Materials Science and Engineering, American Chemical Society: Washington, DC, 1984; pp 47-79. (20) Mackay, D.; Hughes, A. I. Environ. Sci. Technol. 1984,18, 439.
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(21) Connell,D. W. BioaccumulationofXenobioticCompounds; CRC Press, Inc: Boca Raton FL, 1990; p 219. (22) Huckins, J. N.; Meadows, J. C.; Manuweera, G. K.; Lebo, J. A. 12th Meeting of the Society of Environmental Toxicology and Chemistry, EMAP Session, 1991, Poster No. 315. (23) Huckins, J. N.; Gibson, V. L.; Lebo, J. A,; Manuweera, G. K.; Gale, R. W. Abstracts of Papers, 200th Meeting of the American Chemical Society, Washington, DC; American Chemical Society: Washington, DC, 1990; ENVR 29. (24) Manuweera, G . K. Ph.D. Dissertation, University of Missouri, Columbia, MO, 1992. (25) Lieb, W. R.; Stein, W. D. Nature 1969,224,240. (26) Sproule, J. W.; Shiu, W. Y.; Mackay, D.; Schroeder, W. H.; Russell, R. W.; Gobas, F. A. P. C. Environ. Toxicol. Chem. 1991,10,9. (27) Radecki, A.; Lamparaczyk, H.; Kaliszan, R. Chromatographia 1979,12,595. (28) Aquatic Fate Process Data for Organic Priority Pollutant; U.S. Environmental Protection Agency. Office of Research and Development. U.S. Government Printing Office: Washington, DC, 1982; EPA 44014-81-014. Received for review February 23, 1993.Revised manuscript received July 23, 1993.Accepted August 3, 1993.' @
Abstract published in Advance ACS Abstracts, October 1,1993.
