Environ. Sci. Technol. 1991, 25, 924-929
Brugmann, L. Rapp. P.-V. Reun., Cons. Int. Erplor. Mer 1986. 186. 329-342. Sanders, J. G. Rapp. P.-V. Reun., Cons. Int. Explor. Mer 1986. 186, 185-192. Sanders, J . G.; Abbe: G. R. Continent. Shelf Res. 1987, 7, 135771361, Sanders, J. G.; Abbe, G. R. In Aquatic Toxicology and Ewironmental Fate; Suter, G. W., 11, Lewis, M. A,, Eds.; ASTM: Philadelphia, PA, 1989; Vol. XI, pp 5-18. Smith, D. R.; Stephenson, M. D.; Flegal, A. R. Enuiron. Toxicol. Chem. 1985, 5 , 129-138. Van Dolah, F. M.; Siewicki,T. C.; Collins, G. W.; Logan, J. S. Arch. Environ. Contam. Toxicol. 1987, 16, 733-743. Sanders, J. G.; Riedel, G. F. In Phytochemical Effects of Environmental Compounds; Saunders, J. A,, KosakChanning, L., Conn, E. E., Eds.; Plenum Press: New York, 1987; Chapter 5 . Sanders, J. G.; Osman, R. W.; Riedel, G. F. Mar. Biol. 1989, 103, 319-325. Galtsoff, P. S. US., Fish Wildl. Sew. Bull. 1964, 64, 30. Cuningham, P.A. In Marine Pollution: Functional Responses; Vernberg, W. B., Calabrese, A., Thurberg, F. P., Vernberg, F. J., Eds.; Academic Press: New York, 1979; pp 183-221. Zamuda, C. D. Ph.D. Dissertation, University of Maryland, College Park, 1984. Spacie, A,; Hamelink, J. L. In Fundamentals o f Aquatic Toxicology; Rand, G. M., Pettrocelli, S. R., Eds.; Hemisphere Publishers: Washington, DC, 1985; Chapter 17. Amiard-Triquet, C.; Amiard, J. C.; Ballan-Dufranqais,C.; Berthet, B.; Gouzerh, P.; Jeantet, A. Y.; Martoja, R.; Tru-
chet, M. In Heavy Metals in the Environment; Lindberg, S. E., Hutchinson, T. C., Eds.; CEP Consultants Ltd.: Edinburgh, U.K., 1987;Vol. 2, pp 488-490. (19) Martoja, R.; Ballan-Dufranqais,C.; Jeantet, A. Y.; Gouzerh, P.; Amiard, J. C.; Amiard-Triquet, C.; Berthet, B.; Baud, J. P. Can. J . Fish. Aquat. Sci. 1988, 45, 1827-1841. (20) Abbe, G. R.; Sanders, J. G. Estuarine, Coastal Shelf Sci. 1990, 31, 113-123. (21) Harris, P. 0.;Ramelow, G. S. Environ. Sci. Technol. 1990, 24, 220-228. (22) Van Loon, J. C. Selected Methods of Trace Metal Analysis: Biological and Environmental Samples; John Wiley and Sons: Yew York, 1985; pp 100-101. (23) Sanders,J. G.; Abbe, G. R.; Riedel, G. F. Sci. Total Environ. 1990, 97/98, 761-769. (24) Guillard, R. R. L.; Ryther, J. H. Can. J . Microbiol. 1962, 8, 229-239. (25) Sanders, J. G.; Riedel, G. F.; Abbe, G. R. In Estuaries and Coasts: Spatial and Temporal Intercomparisons; Elliott, M., Ducrotoy, J.-P.,Eds.; Olsen & Olsen Press: Fredensborg, Denmark, in press. (26) Reinfelder, J. R.; Fisher, N. S. Science 1991,251,794-796. (27) Fisher, N. S.; Bohe, M.; Teyssie, J.-L. Mar. Ecol. Prog. Ser. 1984, 18, 201-213. (28) Crist, R. H.; Oberholser, K.; Schwartz, D.; Marzoff, J.; Ryder, D. Enuiron. Sci. Technol. 1988, 22, 755-760. Received for revieu August 6, 1990. Revised manuscript received December 20, 1990. Accepted January 3, 2991. This research was supported by the Baltimore Gas and Electric Co. and the Academy of Natural Sciences.
Bioconcentration of Chlorinated Aromatic Hydrocarbons in Aquatic Macrophytes Frank A. P. C. Gobas,” Edmund J. McNeil, Lesley Lovett-Doust, and G. Douglas Haffner The Great Lakes Institute, University of Windsor, Windsor, Ontario, Canada N9B 3P4
This study reports the bioconcentration and the uptake and elimination kinetics of a series of nonreactive, hydrophobic organic substances in the submerged aquatic macrophyte Myriophyllum spicatum. The tested substances represent a wide range of aqueous solubilities and 1-octanol-water partition coefficients (Kow). The plantwater bioconcentration factor is shown to follow a linear relationship with the octanol-water partition coefficient for all chemicals, including the superhydrophobic chemicals with log Kow up to 8.3. The uptake and elimination rate constants tend to follow a “biphasic” relationship with Kow. A kinetic model is developed for organic chemical bioconcentration in submerged aquatic macrophyte species. This model is applied to the Detroit River and Lake St. Clair to illustrate the role of aquatic macrophytes in chemical dynamics in aquatic systems. Introduction Because of their limited mobility, their abundance in many aquatic systems, and their potential to sorb organic substances, aquatic macrophytes have the potential to function as in situ biomonitors of waterborne contaminants. The use of in situ aquatic plants as biomonitors is especially attractive since they require less maintenance than animal biomonitors. However, before levels of organic * T o whom correspondence may be addressed: Natural Resources Management Program, Simon Fraser University, Burnaby, British Columbia, Canada V5A 1S6. 924
Environ. Sci. Technol., Vol. 25, No. 5, 1991
contaminants in aquatic macrophytes can be interpreted in terms of ambient concentrations, the mechanisms and kinetics of chemical uptake and depuration must be understood. Aquatic macrophytes are also used in some water treatment plants to remove organic and inorganic substances from the water ( I ) . The removal efficiency of this treatment method is largely dependent on the affinity of the chemicals for the macrophytes and their uptake and elimination kinetics. Another reason for such information is that aquatic macrophytes may play an important role in the cycling of organic substances in aquatic ecosystems. Their seasonal increase in biomass (growth) provides sorptive sites for organic substances in aqueous solution. Their decay may release chemicals back to the water and/or to the sediments. I t has further been found that drifting macrophytes can act as a vehicle for chemical transport in rivers (2). The objective of this study was therefore to determine the mechanism and the dynamics of chemical uptake, bioconcentration, and depuration of a series of organic substances in a submerged aquatic macrophyte species, namely, Myriophyllum spicatum. The compounds selected cover a wide range of aqueous solubilities and octanol-water partition coefficients (KOw). The experimental results are presented and used to develop a model for the exchange of organic substances between the aquatic macrophytes and the water, which can provide estimates of the bioconcentration potential and uptake and elimination
0013-936X/91/0925-0924$02.50/0
0 1991 American Chemical Society
kinetics of organic substances in aquatic macrophytes.
Materials and Methods Chemicals. 1,3,5-Tri-, 1,2,4,5-tetra-,penta-, and hexachlorobenzene were obtained from Aldrich. 2,2‘,5,5’Tetra-, 2,2’,4,4’,6,6’-hexa-, 2,2’ ,3,3’,4,4’,5,5’-octa-, and decachlorobiphenyl and octachlorostyrene were from Analabs. Analytical grade n-hexane, petroleum ether, 2,2,4trimethylpentane, and dichloromethane were obtained from Caledon Ltd., Ontario, BC, Canada. Florisil 60/ 100-pm mesh and silica gel 100/200-pm mesh were obtained from Supelco Canada Ltd. Anhydrous sodium sulfate, from J. T. Baker Chemical Co., was heated to 650 “C overnight and stored a t 130 “C before use. Plants. M.yriophyllum spicatum was collected from Goose Lake, Ontario, BC, Canada. The plants used in the experiment had an average wet weight of 9 g and a lipid content of 0.20 (f0.02)70. During the experiment, the plants were freely floating in the water. They were kept in a submerged state at all times by attaching lead weights to the stems. No soil or sediment was present. Throughout the experiment, which lasted from July 25 to December 30, 1988, the plants were exposed to natural sunlight in Windsor, Ontario. During the experiments, the plants were actively photosynthesizing. The formation of new leaves and adventitious roots indicated that the plants were growing. Plant growth was quantified by removing and successively weighing new leaves and roots. Over the entire uptake and depuration experiment, plant growth was less than 5 % of the plant’s original weight. No plant decay or death was observed. Since the plants were not provided with nutrient solutions, the plants may have been subjected to nutrient stress. Uptake Experiment. The uptake kinetics of the chemicals in the plants were determined in a continuous-flow apparatus ( 3 ) . T h e continuous-flow apparatus consisted of (i) a 150-L glass tank, filled with dechlorinated, aerated, and carbon-filtered Windsor tap water, (ii) an Asti Teflon pump (Cole-Parmer Instrument Co.), and (iii) a generator column. The water was circulated from the tank, through the generator column, and back to the tank at a flow rate of 60 L / h . The generator column was prepared by coating 200 mg each of tri-, tetra-, and pentachlorobenzene, 100 mg of hexachlorobenzene, 50 mg each of octachlorostyrene and tetrachlorobiphenyl, 20 mg of hexachlorobiphenyl, and 10 mg each of octa- and decachlorobiphenyl onto 10 g of 60/80 pm mesh hexane-washed Chromosorb. Before the plants were added, the water was circulated for 5 days. Then, 120 plants, with an average wet weight of 9 g, were placed in the tank. The temperature was 21 ( f l ) “C. A water sample and three plants were collected after 0, 0.5, 1, 2, 3, 5, 7, 14, 21, and 25 days and analyzed individually. Elimination Experiment. The kinetics of chemical elimination from the plants were determined by transferring the plants a t the end of the 25-day uptake period to a 150-L glass tank, containing clean, uncontaminated, carbon-filtered water. Throughout the elimination period this water was continuously filtered by an activated carbon filter at a flow rate of 100 L/h. Plant samples were taken after 0.25, 1, 2 , 3, 5 , 7, 14, 21, 28, 37, 61, and 133 days. Water Analysis. Water samples of 250 mL were taken from three different locations in the tank. They were immediately extracted, first with 150 mL and then twice with 75 mL of petroleum ether. T o remove dissolved water, the petroleum ether extract was passed through a 0.025 X 0.60 m column containing 20 mL of sodium sulfate. The extract was then concentrated to 3-4 mL by evaporation (Buchner Rotavap). Cleanup was performed by
passing the concentrated extract through a 0.025 X 0.60 m column containing, from top to bottom, 10 mL of sodium sulfate and 40 mL of Florisil. The column was then washed with 200 mL of petroleum ether. This extract was concentrated to 1-10 mL by evaporation and then analyzed by gas chromatography. The recoveries of the entire analysis procedure, with the exception of the petroleum ether-water extraction, were determined with spiked petroleum ether samples. Rates of recovery ranged from 89 ( f 3 ) % for trichlorobenzene to 97 (f3)% ( n = 3) for octachloro- and decachlorobiphenyl. Plant Analysis, I. Extraction. After each plant was collected and weighed, it was cut into small pieces with scissors. The pieces from each individual plant were transferred to a mortar together with 30 mL of anhydrous sodium sulfate and then ground to a paste. This paste was added to a 0.025 X 0.60 m column, containing, from bottom to top, glass wool, 10 mL of anhydrous sodium sulfate, and 70 mL (1:l)of dichloromethane-petroleum ether. Then another 10 mL of anhydrous sodium sulfate was added on top of the column. After 1 h, the column was eluted with 250 mL (1:l)of dichloromethane-petroleum ether. Then, 2 mL of 2,2,4-trimethylpentane was added to the extract, after which the extract was concentrated to approximately 1-2 mL. Plant Analysis. 11. Cleanup. The concentrate was passed through a 0.01 X 0.55 m column, containing, from bottom to top, 8 mL of silica, 8 mL of acidified silica (40% (w/w) sulfuric acid), and 3 mL of anhydrous sodium sulfate. This column was eluted with 50 mL of petroleum ether. The extract was concentrated to 1mL, then diluted to 10 mL in hexane, and analyzed by gas chromatography. The recovery of the entire plant analysis procedure ranged from 85 (*5)% for trichlorobenzene to 98 (f5)% ( n = 3) for octachlorobiphenyl. Lipid Content. After extraction, but before cleanup, the plant extract was evaporated to dryness and then further dried in an oven a t 60 “C for 1 h. The lipids were then determined by weight. Gas Chromatography. Gas chromatographic analysis was performed on a Varian 3500, equipped with a 30-m DB-5 capillary column (J&W Scientific), a 63Ni electron capture detector, and an integrator. Injector temperature was 250 OC, detector temperature was 300 “C, and column temperature was programmed from 50 to 300 “C. The carrier gas was ultrahigh-purity grade helium a t 1.5 mL/min. The make-up gas was ultrahigh-purity grade 5% methane-95% argon a t 60 mL/min. The injection mode was splitless, with an injection volume of 1pL. Standards were prepared from the pure chemicals. Statistics. Standard deviations are reported in parentheses. Confidence intervals are reported in square brackets and have a 95% probability.
Results At the start of the uptake period, the concentrations of the chemicals in the water, Cw,o(Fg/L), were a t or below their solubility levels (Table I). The only exception was decachlorobiphenyl for which the initial concentration exceeded the aqueous solubility, suggesting t h a t the measured concentration did not truly represent the concentration of actually dissolved decachlorobiphenyl in the water. After the plants were introduced to the water (i.e., the start of the experiment), Cw dropped and then, after 3 days, it reached a constant level or it slowly declined during the remaining 22 days ofthe uptake period. T h e initial drop of the chemical concentration in the water was virtually absent for 1,3,5-trichlorobenzene,but it was larger Environ. Sci. Technol., Vol. 25, No. 5, 1991
925
trichlorobenzene tetrachlorobenzene pentachlorobenzene hexachlorobenzene tetrachlorobiphenyl octachlorostyrene hexachlorobiphenyl octachlorobiphenyl decachlorobiphenyl
4.02 [4] 4.51 [4] 5.03 [4] 5.47 [4] 6.1 [5] 6.29 [6] 7.0 [5] 7.8 [5] 8.26 [5]
0.346 1.00 5.92 5.90 0.072 4.96 1.00 0.21 0.1
4120 [4] 2351 [4] 831 [4] 4.69 [4] 30.1 [5] 2.5 [7] 0.69 [ 5 ] 0.2 [5] 0.0012 [5]
20 93 275 150 450 403 500 496 162
0.60 0.54 0.20 0.14 0.09 0.065 0.02 0.0008 0.0003
1.52 2.24 3.14 3.03 3.70 3.79 4.40 5.79 5.73
0.16 0.13 0.082 0.055 0.043 0.010 0.0014 0.0009
4.22 4.94 5.84 5.73 6.40 6.49 7.10 8.49 8.43
22 13 12 15 15 16 19 19 43
'The data include the logarithm of the octanol-water partition coefficient log Kow, the water concentration a t the beginning of the experiment Cw,o, the chemical's aqueous solubility S W , the uptake rate constant k l in the plant, the elimination rate constant determined from the uptake data k,, the elimination rate constant determined from the elimination data kz*, the logarithm of the plant-water bioconcentration factor log KPW,the logarithm of the plant-water bioconcentration factor expressed on a lipid weight basis log KLW, and the normalized deviation between the observed and predicted chemical concentrations in the plants E.
;*-;I
+ Model
.
0.60
1, -0.20
0
,.---AH*
: 5
.:
: 10
15
Log
fit
cw
20
-2
rn 25
0
for the higher Kow chemicals. The greatest drop was observed for decachlorobiphenyl, which fell from 0.1 to 0.006 pg/L, Le., close to its reported water solubility of 0.0012 pg/L. During the uptake period, chemical concentrations in the plants, Cp (pg/kg), increased with time and approached a constant concentration toward the end of the uptake period. Typical results of the uptake experiment are illustrated in Figure 1, which shows the uptake of hexachlorobenzene. After the uptake period, when plants were transferred to clean, uncontaminated water, a loss of the chemical from the plants with time was observed (Figure 2). The elimination was characterized by an initial phase of relatively rapid elimination, followed by a phase of slower elimination. The first 28 days of the elimination period accounted for the elimination of more than 95% of the accumulated chlorobenzenes and, respectively, 84 and 77% of tetrachlorobiphenyl and octachlorostyrene. For hexa-, octa-, and decachlorobiphenyl, differences between initial and later elimination rates were very small and not significant ( P < 0.05).
Developing a Kinetic Model The observed chemical uptake from the water (Figure I ) , followed by the drop of the chemical concentration in the plant after the plants are transferred to clean water (Figure a), suggests that the chemical exchange between the plant and the water is a reversible process. The simplest description of this process is k,
(1)
k,
where Cp and Cw are the chemical concentrations (pg/L) in, respectively, the plant and the water. This model describes the exchange of the chemical between two compartments, i.e., the plants and the water, which are both considered to be homogeneous. Chemical 926
Environ. Sci. Technol., Vol. 25, No. 5, 1991
20
40
so
80
100
120
1 Kl
TIME (days)
Figure 1. Logarithms of the concentrations of hexachlorobenzene in the water, C, (pg/L), and in the plant, Cp (pg/L), during the uptake experiment. The solid line illustrates the model fit.
- cp
rn
c
-3
TIME (d)
cw
% . -,
Figure 2. Logarithm of the concentrations of trichlorobenzene (0), tetrachlorobenzene (O),pentachlorobenzene (W), hexachlorobenzene (A),and hexachlorobiphenyl ( * ) in the plant C p (pg/L) during the course of the elimination experiment. The inset in the top right-hand corner represents the largest observed standard deviation (n = 3).
transfer from the water to the plant is represented by a rate constant k,, which has units of day-'. Chemical transfer from the plant to the water is characterized by a rate constant k2 with units of day-l. The net flux of chemical FP (pg/day) between the water and the plant, with a volume of Vp (L), can be described by F p = d(VpCp)/dt = k1VpCw - hZVpCp (2) where k,VpCw is the flux F , (pg/day) from the water into the plant, and k2VPCPis the flux F2 (pg/day) from the plant to the water. The applicability of the reversible plant-water exchange model can be determined by fitting the model to the experimental data. Since the plants were growing and chemical concentrations in the water were not constant throughout the uptake period (Figure l),the model (Le., eq 2) was fitted to the experimental data by a numerical integration procedure. This procedure derives the chemical mass in the plant, i.e., Xp (in pg) or VpCp,as the sum of increments in chemical mass d X p over time intervals dt, i.e., X p = C d X p . Each d X p is calculated from eq 2 as dXp = (k1VpCw - k2VpCp) dt (3) where d t was chosen to be sufficiently small, and Cw and Vp a t every exposure time t , or x d t , followed from the measurements of, respectively, the water concentration and plant volume by fitting the observed values to a series of linear functions, each of which connect the observed data at two consecutive exposure times. Then, values for h, and k 2 were selected to produce the best agreement between calculated and observed Xp. The best fit of the observed data was the one with k, and k, values, for which the sum of the squared differences between calculated and observed Xp was the smallest. In this fashion, k l and kz of all
7
7
I
KOW Oi-4
5
8
7
8
II
Figure 3. Relationship between the logarithm of the plant-water bioconcentration factor, log K,,, and the logarithm of octanol-water partition coefficient, log Kow. The solid line represents eq 6 .
chemicals were determined and listed in Table I. The quality of the fit can be expressed by the mean deviation, E , of the predicted (i.e., model-fitted) from the observed chemical concentrations in the plant, i.e. n
,
I
Q
I
where Cp,pis the observed and Cp,iMis the model-predicted concentration in the plant a t each exposure time and n is the number of samples throughout the exposure period. In this fashion, it was estimated that observed and fitted concentrations of hexachlorobenzene vary, on average, by 1570,which is well within the range of experimental error associated with the plant and water analysis. In general, the deviation between observed and fitted plant concentrations ranged from 12 to 43% (Table I). This demonstrates that, considering the experimental detail achieved in this experiment, eq 2 satisfactorily describes the chemical exchange between the plants and the water. In a similar fashion, eq 2 can be fitted to the elimination data. Since during the elimination period Cw is 0, eq 2 can be integrated to give log Xp = log Xp,t=O- (k,/2.303)t (5) where XP,t=O is the chemical mass in the plant a t the beginning of the elimination period. The elimination data for hexa-, octii-, and decachlorobiphenyl are in good agreement with eq 5, thus providing an estimate of k2 derived from elimination data, which we will refer to as k2* (Table I). Figure 2 illustrates that the initial drop of Cp, and also Xp of the chlorobenzenes, tetrachlorobiphenyl, and octachlorostyrene, is in good agreement with eq 5. After the initial elimination phase, the decrease of Cp and Xp tends to be slower, which does not agree with the plant-water two-compartment model and indicates that a two-compartment or multicompartment plant model may be more appropriate. However, since the initial elimination phase accounted for the elimination of the majority of the test chemicals from the plant, and since it is advantageous to keep the model simple, eq 5 was fitted to the data of the first 28 days of the elimination period for the chlorobenzenes, tetrachlorobiphenyl, and octachlorostyrene. The resulting k2* values are listed in Table I. Table I demonstrates that there is a reasonable agreement between the independent measurements of the elimination rate constant from uptake and elimination data. But, in general, the elimination rate constants derived from the elimination experiment (Le., h2*) are somewhat lower than those derived from the uptake experiment (i.e,, k 2 ) . Now that k , and k2 have been determined, it is possible to derive the bioconcentration factor (KPw)of each chemical in the plant as k 1 / k 2 . The bioconcentration factors are listed in Table I and plotted versus the octanol-water
Figure 4. Logarithm of the uptake rate constant k , (day-'), in the plant plotted versus log Kow. The solid line represents the model fit, i.e., eq 11.
partition coefficient (Kow)in Figure 3. Figure 3 demonstrates that the logarithms of the plant-water bioconcentration factor and the octanol-water partition coefficients follow a linear relationship, i.e. log Kpw = 0.98 [h0.15] log Kow - 2.24 [*0.61] n =9
r2 = 0.97
(6)
This suggests that chemical bioconcentration in the plant is essentially a partitioning process that can be successfully mimicked by octanol-water partitioning. In Table I, the bioconcentration factors are also expressed on a lipid weight basis as log KLW. KLW is the ratio of the chemical concentration in extractable plant lipids, CL (Fg/L), over that in the water, i.e., CL/Cw or Kpw/Lp,where Lp (g/g) is the lipid content of the plant, Le., 0.0020 (hO.00023). It can be observed that, considering the experimental error, the lipid weights based plant-water bioconcentration factors and octanol-water partition coefficients are approximately similar and do not differ significantly. This suggests that chemical bioconcentration occurs predominantly in the extractable lipids of the plants since the solubility of the test chemicals in octanol and in lipids are often similar (8,9). From this study, in which plants were kept under nutrient-limiting conditions, it appears that bioconcentration of the investigated chemicals is largely a thermodynamically controlled process, determined by the higher solubility of the chemical in the plant lipids than in the water. The nature of the bioconcentration process in the submerged macrophytes and in fish tends to be similar since they are largely the result of lipid-water partitioning (10, 11). However, the relationship between the logarithms of the plant-water bioconcentration factor and the octanolwater partition coefficient tie., eq 6) is linear over the entire range of log Kow values (from 4 to 8.3) whereas this relationship for the fish-water bioconcentration factors tends to break down for chemicals with a log Kow exceeding 6 ( 3 , 12). This suggests that lipid-water partitioning is an adequate representation of the mechanism of bioconcentration in plants for all of the tested chemicals whereas it satisfactorily describes bioconcentration in fish only for chemicals with a log Kow up to approximately 6 (3). Developing a Mechanistic Model Figure 4, in which hl is plotted versus Kow,illustrates that for chemicals with a log Kow below 5.5, kl increases with increasing Kow,while for the chemicals with log Kow exceeding 5.5, kl tends to approach a constant value of 500 days-'. In Figure 5 , k 2 is plotted versus Kow. It shows that with increasing KO,, k 2 drops, first slowly, but then more steeply. Environ. Sci. Technol., Vol. 25, No. 5, 1991
927
-1
v
‘3
4
I
5
6
i
e
i
Log KOW Figure 5 . Logarithm of the elimination rate constants (day-’) versus log Kow. k , (m) is derived from uptake data, k,” (A)is derived from elimination data. The solid line illustrates the model fit, Le., eq 12.
- CWI\ CLI- l / D - CL w L Figure 6. Schematic illustration of the lipid-water kinetic model and the aqueous- and lipid-phase transport conductivities and resistances. C
-l/D
To explain the “biphasic” nature of the change in rate constant with increasing Kow, we propose a simple mechanism, which is based on the assumption that chemical bioconcentration in the plant involves chemical permeation through aqueous and lipid parts of the plant. Examples of lipid phases in the plants are the lipid bilayers of biological membranes such as the cell membrane, and intracellular membranes and the plant’s waxy cuticle. Aqueous phases are present in the cytoplasm and they are also associated with membranes (13). In the absence of active transfer mechanisms, the chemical flux (F)through the lipid and aqueous parts of the plant involves a combination of either (i) simple molecular diffusion, in which case F is the product of the mass-transfer coefficient, the area of diffusion, and the concentration, (ii) movement through (natural) fluid flows, such that F is the product of the fluid flow and concentration, or (iii) a combination of diffusion and fluid flows, in which case F is best represented by the product of a transport parameter D (L/ day) and concentration. D can be viewed as the chemical’s conductivity, and its reciprocal, i.e., 1/D, as a resistance R. Since our experiment is not able to identify the mode of transport involved in the bioconcentration process (i.e., whether chemical movement is by diffusion, fluid flow, or both), the chemical flux in the aqueous (F,) and lipid phases (FL)of the plant is best expressed in terms of an aqueous phase, Le., Dw, and a lipid phase, i.e., DL, transport parameter. It then follows that if chemical transport in the aqueous phases and lipid apply in series, the net flux of chemical into the plant FP can be written as F p = Dw(Cw - Cwd = DL(CLI- CL) (7) where Cwr and CLI are the chemical concentrations in, respectively, the water and the lipids at the lipid-water interface and CL is the concentration in the plant lipids, Le., Cp/Lp. A schematic diagram of this lipid-water kinetic model is presented in Figure 6. If at the plant lipid-water interface the ratio of chemical concentrations, Le., CLI(CWI, is satisfactorily represented by Kow, eq 7 can be rewritten as (8) F p = [(I/&) + (1/D~Kow)l[Cw- (Cp/LpKow)l which is equivalent to eq 2. Comparison of eqs 2 and 8, shows that (9) l / k i = (Vp/Dw) + (VP/DL,)/KOW
l / k z = (LpVp/Dw)Kow + (LpVp/DL)
(10)
which demonstrate that if chemical exchange between the 928
Environ. Sci. Technol., Vol. 25, No. 5, 1991
water and the macrophytes involves transfer in aqueous and lipid phases, the kinetics of uptake and elimination tend to be controlled by transport in the lipid phases of the plant when the chemical’s KO, is low. With increasing KOW,chemical transport in the aqueous phases of the plant becomes more important and ultimately dominates the kinetics. Equation 9 thus predicts that, with increasing Kow, k , increases, while transfer in the lipid phases (e.g., membranes) controls the uptake kinetics. For high-Kow chemicals, the transport in the water phase becomes the rate-determining step, and k , approaches a constant level (Le., Dw/ Vp). Likewise, eq 10 illustrates that k 2 tends to be approximately constant (Le., DL/VpLp) for low-Kow chemicals, when transfer in lipid phases of the plant is the rate-determining process, and then drops with increasing Kow, when transport through water phases becomes the rate-limiting step. The applicability of this mechanistic model is demonstrated by fitting eqs 9 and 10 to the experimental data, giving I / k , = 0.0020 + 500/Kow E = 32% (11) 1/h2 = 1.58 + 0.000015Kow
E = 55%
(12)
and demonstrating that the uptake and elimination of chemicals with a log Kow exceeding 5.5 are largely determined by the aqueous phase transfer conductivity Dw/Vp,which is between 133 and 500 days-’. For log KOw below 5.5, uptake and elimination are primarily controlled by transfer in lipid phases such as membranes. Figures 4 and 5 illustrate the excellent fit of the model to the experimental data. The only exception is decachlorobiphenyl, for which a k , of 162 days-’ was measured, which is approximately 3 times lower than the expected value of 500 days-’. The poor fit may be explained by a reduced bioavailability, possibly as a result of sorption to small amounts of organic matter present in or introduced by the plants to the water, which causes the measured concentration to overestimate the concentration in the water that was actually involved in the plant-water bioconcentration process, resulting in an underestimate of k l . It seems conceivable that, in the lipids of the plant, diffusion is the predominant mode of transport, in which case DL is kLA, where kL is the mass-transfer coefficient (m/day) in the lipids of the plant and A (m2)is the diffusion area. Consequently, it is possible to estimate kL since DL/Vp or kLA/ Vp is between 0.0013 and 0.0020 dag’ as long as the diffusion area per unit volume of the plant, Le., A/Vp, is known. Measurements of the actual diffusion area are difficult, but it can be approximated by the peripheral area, thus assuming that the diffusion area corresponds to the peripheral area. By measuring leaf surface areas and volumes, we determined area/volume ratios of 8-11 mm-l, with an average of 9.5 mm-l, for M . spicatum, which gives an estimate for hL of 1.4 X 10-7-2.1 X m/day, with an average of 1.8 x m/day. In the absence of information on mass-transfer coefficients of organic substances in submerged aquatic macrophytes, it is tempting to assume that the mass-transfer coefficients in the lipids of plants are somewhat similar, thus providing an opportunity to derive the transport kinetics in the lipids of plants from the area/volume ratio of the plant, i.e.
D L / V p = (1.8 X 10-7)A/Vp
(13)
I t should be emphasized, however, that eq 13 is an hypothesis, rather than a finding of this study. When more experimental data become available, particularly on aquatic macrophytes of contrasting morphology, it may be possible to test the validity of this relationship.
Mod e 1 A pp 1ica t io ns Now that we have developed a model for the uptake, elimination, and bioconcentration of nonreactive, hydrophobic organic substances, it is interesting to apply this model to test the role of aquatic macrophytes on organic chemical cycling in rivers and lakes. For example, the annual production of submerged aquatic macrophytes in the Detroit River has been estimated to be 1 2 380 metric tons on an ash-free dry weight (AFDW) basis, or 2.48 X lo8 kg, on a wet weight (WW) basis (14). The average flow rate of the river is 1.67 X L/year (15). If the river water contains a chemical of a log KO, of 6.3 (e.g., octachlorostyrene or PCBs) at a concentration of, for example, 1 ng/L, then the water has the potential to convey 1.67 X l O I 4 ng/year or 167 kg of chemical/year (assuming no net chemical loss to or gain from sediment or air). However, every year, the 1.67 X 1014 L interacts with 2.48 X lo8 kg of submerged macrophytes, which can, according to eq 6, bioconcentrate the chemical approximately 8600 times, assuming t h a t bioconcentration in submerged aquatic macrophytes is adequately represented by that in M . spicatum. Kt is possible that the chemical in the water will be concentrated by the macrophytes to this extent since eq 12 preldicts a k2 of 0.032 day-l. The time to reach 95% of the plant-water steady-state level is therefore approximately 3 / k 2 or 94 days, which is within the standing period of the crop. The concentration in the submerged aquatic macrophytes can therefore reach a concentration of 8600 X 1 ng/L or approximately 8600 ng/kg. At an annual production of 2.48 X lo8 kg, the submerged macrophytes can thus extract (2.48 X lo8 kg)(8600 ng/kg) or 2.1 kg of chemical from the water. This represents approximately 1.3% of the chemical transported by the river water. Similar calculations for Lake St. Clair, with an annuall production of 13780 metric tons (AFDW) or 2.8 X lo8 kg (WW) and a water flow rate of 1.61 X 1014 L/year, show that bioconcentration by submerged aquatic macrophytes could remove approximately 1.4% of the chemical from the water (16). But if, in addition, the production of phytoplankton (Le., 60 160 metric tons AFDW) and periphyton (Le., 16 720 metric tons AFDW) are considered (16),the bioconcentration of the chemical by the primary producers may be able to remove up to 9.2% of the chemical from the water. Higher Kow chemicals may thus; be removed from the water by an even greater extent. The chemical absorbed by the macrophytes may eventually become embedded in the river or lake sediments after the plants (and phytoplankton) have died, thus contributing to the water-to-sediment transport of the chemical. These calculations do not intend to adequately model the chemical dynamics in the Detroit River or Lake St.
Clair. However, they illustrate that chemical bioconcentration may have a significant effect on the distribution and dynamics of hydrophobic organic substances in aquatic systems. It is thus important to consider the role of aquatic macrophytes when assessing the fate of hydrophobic organic chemicals in aquatic systems. The models, derived for chemical bioconcentration in M . spicatum can be useful for this purpose as well as the interpretation of plant concentrations in terms of ambient water concentrations, or for the estimation of contaminant removal efficiencies in water treatment plants. Registry No. Trichlorobenzene, 12002-48-1; tetrachlorobenzene, 12408-10-5;pentachlorobenzene, 608-93-5; hexachlorobenzene, 118-74-1; tetrachlorobiphenyl, 26914-33-0; octachlorostyrene, 29082-74-4; hexachlorobiphenyl, 26601-64-9; octachlorobiphenyl, 55722-26-4; decachlorobiphenyl, 2051-24-3. Literature Cited (1) DeBusk, T. A.; Reddy, K. R. Water Sei. Technol. 1987,19, 273-279. (2) Manny, B. A.; Nichols, S. J.; Schloesser, D. W. Hydrobiologia, in press. (3) Gobas, F. A. P. C.; Clark, K. E.; Shiu, W. Y.; Mackay, D. Environ. Toxicol. Chem. 1989, 8 , 231-247. (4) Miller, M. M.; Wasik, S. P.; Huang, G. L.; Shiu, W. Y.; Mackay, D. Enuiron. Sci. Technol. 1985, 19, 522-529. (5) Shiu, W. Y.; Mackay, D. Phys. Chem. Ref. Data 1986, 15, 911-929. (6) Veith, G. D.; DeFoe, D. F. L.; Bergstedt, B. V. J. Fish. Res. Board Can. 1979,36, 1040-1045. (7) Bjerk, J. E.; Brevik, E. M. Arch. Environ. Contam. Toxicol. 1980,9, 743-748. (8) Gobas, F. A. P. C.; Lahittete, J. M.; Garofalo, G.; Shiu, W. Y.; Mackay, D. J. Pharm. Sci. 1988, 77, 265-272. (9) Dobbs, A. J.; Williams, N. Chemosphere 1983, 12, 97-104. (10) Spacie, A.; Hamelink, J. L. Environ. Toxico1.-Chem.1982, 1, 309-320. (11) Gobas, F. A. P. C.; Opperhuizen, A.; Hutzinger, 0. Environ. Toxicol. Chem. 1986, 5, 637-646. (12) Bruggeman, W. A.; Opperhuizen, A,; Wijbenga, A.; Hutzinger, 0. Toxicol. Enuiron. Chem. 1984, 7, 173-189. (13) Flynn, G. L.; Yalkowsky, S. H. J. Pharm. Sci. 1972, 61, 838-852. (14) Edwards, C. J.; Hudson, P. L.; Duffy, W. G.; Nepszy, S. J.; McNabb, C. D.; Haas, R. C.; Liston, C. R.; Manny, B. A,; Busch, W. D. N. Proc. Int. Large Rivers Symp. Can. J. Fish. Aquat. Sci., in press. (15) Upper Great Lakes Connecting Channel Study, Ontario Ministry of the Environment, 1988. (16) Edsall, T. A.; Manny, B. A. Biological Report 85(7.03),Fish and Wildlife Service, U S . Department of the Interior, 1988. Received for review February 7, 1990. Revised manuscript received July 16,1990. Accepted January 3, 1991. We thank the Ontario Ministry of the Environment f o r providing the financial support for this study.
Environ. Sci. Technol., Vol. 25, No. 5, 1991
929
