Environ. Sci. Technol. 1997, 31, 665-669
Field Measurements of PCB Partitioning between Water and Planktonic Organisms: Influence of Growth, Particle Size, and Solute-Solvent Interactions J O H A N A X E L M A N , * ,† D A G B R O M A N , † , ‡ A N D C A R I N A N A¨ F † Aquatic Chemical Ecotoxicology, Department of Zoology, Stockholm University, S-106 91 Stockholm, Sweden, and Institute of Applied Environmental Research, Stockholm University, S-106 91 Stockholm, Sweden
Due to long equilibration times, growth of planktonic organisms significantly dilutes cell concentrations of adsorbed highly hydrophobic organic compounds (HOCs). Behavior of polychlorinated biphenyls (PCBs) in field samples of 0.2-2, 2-25, and >100 µm particle size fractions confirmed this. The in-situ log Koc values showed a near linear relationship with hydrophobicity (log Kow) with a slope of 1.2 for the 0.2-2 µm size fraction, whereas the in-situ log Koc values remained within 1 log unit throughout the entire log Kow interval for the 2-25 µm size fraction. In the largest size fraction, there was a weak positive relationship between log Koc and log Kow with a linear regression slope of 0.28. The results imply that equilibrium concentrations in planktonic organisms cannot be used in food chain modeling. Observed high equilibrium log Koc values relative to log Kow values are discussed in terms of solutesolvent interactions in the octanol-water system as opposed to the organic carbon-water system in the field.
Introduction Partitioning processes of hydrophobic organic compounds (HOCs) between particles and surrounding water are important for understanding the transport and fate of these chemicals in the environment. Models of HOC behavior in the aquatic environment have generally worked with equilibrium concentrations in small particles (e.g., refs 1-3). However, a number of studies of the kinetics of the sorption processes have been carried out (e.g., refs 4-7), and the exchange of HOCs between particles and the surrounding water has been shown to be a reversible process (8), rate limited by intraparticle diffusion (9, 10). Most investigations of the kinetics of particle partitioning processes have used sediment or soil particles. However, in the offshore euphotic zone of oceans and of large, deep lakes, most of the particles in the water are planktonic organisms or particles originating from the in-situ production of biomass. Interest has only recently been shown for kinetic aspects of the partitioning of HOCs between planktonic organisms and water (11-13). It has also been suggested in a correlative study by Smith (14) that rapid phytoplankton growth is responsible for the shortterm decrease of HOC levels in herring gull eggs in the Great * Corresponding author telephone: +48 8 16 40 15; fax: +46 8 16 77 15; e-mail:
[email protected]. † Department of Zoology. ‡ Institute of Applied Environmental Research.
S0013-936X(96)00088-0 CCC: $14.00
1997 American Chemical Society
Lakes area. Theoretically, a population of growing particles cannot reach chemical equilibrium because the energyconsuming process of growth continuously dilutes the organic carbon phase. The effect has been described in other contexts such as growth dilution in fish by Sijm et al. (15). In field studies, it is not possible to quantitatively determine the mechanisms responsible for the partitioning behavior of HOCs due to the heterogeneity of the particles and the complexity of the carbon turnover in particles of different kinds. Also, the dynamics of carbon and other elements such as nitrogen and phosphorous are far from fully understood. In addition, the different types of particles may have different affinity for HOCs depending on the structure of the organic carbon and carbon-oxygen ratio. However, with some assumptions and conservative calculations, it is possible to establish whether it is feasible that growth explains the observed partitioning behavior of HOCs as an effect of turnover of organic carbon. Koelmans et al. (13) found no reason to expect that growth would have an influence on the partition coefficients of chlorobenzenes in natural populations of Anabaena ssp. and Scenedesmus ssp. due to the fast sorptive exchange. Their results did suggest however that the sorptive exchange would be slower in larger algal species and for more hydrophobic sorbates (e.g., PCBs). However, Koelmans et al. (13) provided no quantitative relationship between cell size and sorption kinetics that could be used to estimate the likely influence of growth in larger cells. A rough estimate can be done using a one-compartment exchange model with first-order sorption kinetics. In a one-compartment model, growth rate would influence the apparent partition coefficient as follows: dyn
Koc )
k1 k2 + kgrowth
(1)
where k1 is the uptake rate constant (per time unit), k2 is the depuration rate constant (per time unit), and kgrowth is the growth rate constant (per time unit). The index dyn (abbreviation for dynamic) indicates that Koc in this case is not a chemical equilibrium constant but instead a dynamic partition coefficient. From the equation, it follows that growth has an observable influence only when the growth rate constant is in the same order as, or larger than, the depuration rate constant. Several reports on growth rates for natural populations of algae exist in the literature ranging up to one doubling per day during the productive season (e.g., refs 16 and 17). To establish whether dynKoc could be affected, a quantitative relationship between sorption rate and cell size and sorbate hydrophobicity is needed. The most exact model for the sorptive exchange would be an intraparticle radial diffusion model as described by Schwartzenbach et al. (18). This model assumes an approximation of the particles to spheres that does not hold in the case of growing cells, mainly due to the cell division process. Instead, we used a simple one-compartment model with first-order kinetics. This model underestimates immediate sorption and overestimates longterm sorption but describes the intermediate sorption process well (18). The intraparticle radial diffusion model can however provide an estimate of the first-order desorption rate constant and its dependency on particle size by using the solution of the sorptive exchange equation for the time needed to achieve half of the equilibrium concentration in the particle, which is approximately 0.03DeffR-2. The first-order desorption rate constant can thus be estimated as (18)
k2 ≈
23Deff
(2)
R2
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TABLE 1. Selected Molar Volumes, Log Koc* Values, and Calculated Log Particle Sizea hypothetical PCB (cm3
molar vol log Koc log dynKoc (0.7 d-1, 1 µm) log dynKoc (0.01 d-1, 10 µm) log dynKoc (0.7 d-1, 10 µm) log dynKoc (0.7 d-1, 20 µm) mol-1)
dynK
oc
Values for Four Different Cases of Growth and
mono
di
tri
tetra
penta
hexa
hepta
octa
nona
205.5 5 5.000 4.998 4.985 4.943
226.4 5.5 5.500 5.494 5.460 5.357
247.3 6 6.000 5.985 5.905 5.704
268.2 6.5 6.497 6.466 6.304 5.984
289.1 7 6.994 6.929 6.648 6.222
310 7.5 7.487 7.363 6.944 6.443
330.9 8 7.974 7.761 7.211 6.666
351.8 8.5 8.452 8.120 7.467 6.896
372.7 9 8.916 8.448 7.723 7.138
a High growth rate constant for 1 µm diameter particles, high and low growth rate for 10 µm particles, and high growth rate constant for 20 µm particles.
This relationship can only be used on the assumption that the surrounding water is not depleted of HOCs during the sorption process, a reasonable assumption for the field situation due to the relatively rapid gas exchange with the atmosphere and the high hydroturbulence in the surface water. R is the radius of the particle, and Deff is the effective diffusive constant. Deff, in turn, is dependent on the diffusion coefficient for the sorbate in pure water, Dw, corrected for the intraparticle organic carbon-water partition coefficient, porosity, carbon content of the particle, and restriction of diffusion due to the structure of the particle (eq 4). In order not to overestimate the influence of growth, we have here assumed zero restriction of diffusion within the particle, which seems plausible since there are no crystalline solid phases inside the cells that can hinder diffusion. Phytoplankton cells are often surrounded by some type of cell wall, sometimes perforated crystalline structures that would hinder diffusion, but due to the lack of data, this could not be included in the model. Equations for estimates of Dw can be found in the literature (18):
4.774 × 10-5 Dw ) 1.14 (m2 h-1) µ × V ′0.589
(3)
where µ is the viscosity of the solution (10-2 g cm-1 s-1) (1.307 at 10 °C (19)) and V ′ is the molar volume of the chemical (cm3 mol-1). Deff in the case of zero restriction can be estimated by
Deff )
DwΦ Koc*(1 - Φ) + Φ
(m2 h-1)
(4)
where Φ is the porosity (dimensionless) and Koc* is the intraparticle organic carbon-water partition coefficient (assumed to be equal to the equilibrium Koc for the particle as a whole related to the surrounding water). The organic carbon in the particle was assumed to have a density of 1 g cm-3, and the fraction organic carbon of the non-aqueous phase was assumed to be 1. Carbon content for the particles was calculated according to the equation given for phytoplankton (20):
TABLE 2. Filters Used and Volumes Filtrated for Different Samples Collected size fraction/sample depth (m) vol (L) 0.2-2 µm A 2-25 µm A >100 µm A dissolved A 0.2-2 µm B 2-25 µm B >100 µm B dissolved B 0.2-2 µm C 2-25 µm C dissolved C
12 12 12 12 6 6 6 6 15 15 15
3696 274 4915 403 5348 234 6265 437 3628 283 252
filter type ceramic/polymer crossflow Millipore AP20 nylon PUF ceramic/polymer crossflow Millipore AP20 nylon PUF ceramic/polymer crossflow Millipore AP20 PUF
according to
kgrowth ) dgrowth ln (2)
(7)
Table 1 lists dynKoc values calculated for three different particle sizes, 1, 10, and 20 µm in diameter, at different growth rates for a series of hypothetical polychlorinated biphenyls (PCBs). Koc* values had to be selected for the hypothetical PCB congeners. In this case, we selected relatively high Koc* values in relation to molar volumes and degree of chlorination (see discussion below) compared to what could be found in the literature for PCBs (21). This does not have any significant influence on the results since the calculated dynKoc values are relatively insensitive to V ′, instead Koc* is the governing parameter. From this theoretical point of view, growth can be expected to decrease the in-situ partition coefficients significantly for larger particles (Table 1). However, the smaller size fraction, in the present study represented by the 0.2-2 µm size fraction, should not be affected. What could also be learned from the model is that although growth is a prerequisite for the effect, variations in size will probably cause most of the differences in the partitioning behavior in the field. The calculated dynKoc is more sensitive to changes in size than growth rate constant since k2 is inversely proportional to the square of R.
Materials and Methods log C ) 0.866 log V - 0.460
(5)
cell-1)
where C is the carbon content (pg and V is the cell volume (µm3). Since the density of organic carbon was assumed to be 1 g cm-3, Φ was calculated as
Φ)1-
C V
(6)
k1 can be calculated from the product of Koc* and k2. Values from the upper and lower ends of the range of typical growth rates, kgrowth, were taken from the literature (16, 17) (Table 1). The growth rates that are generally given as doublings per day, dgrowth, are transformed to first-order rate constants
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Sampling of Different Particle Size Fractions and Dissolved PCBs. Samples were collected July 25-27, 1994, from three different depths in the open sea in the northern Baltic proper (58.1 W, 18.0 N). All sampling data, such as the volumes filtered, size fractions collected, and the different sampling depths, are listed in Table 2. A set of samples was taken at each depth according the scheme in Figure 1. The truly dissolved fraction was collected on a prewashed (24 h toluene/ 24 h acetone Soxhlet) polyurethane foam (PUF) adsorbent, placed after a pre-combusted (480 °C, 5 h) Whatman GF/F filter at a flow rate of approximately 10 bed vol min-1. The PUF adsorbent, the 100 µm nylon filters, and the Millipore AP20 2 µm planar filters were stored frozen (-18 °C) until chemical analysis.
FIGURE 1. Sampling scheme for the four different sample types taken; the three different particle sizes >100, 2-25, and 0.2-2 µm and the truly dissolved fraction. The filters/adsorbent not listed in Table 2 were Millipore CP25 (25 µm capsule), Millipore CP20 (2 µm capsule), and Whatman GF/F 297 mm planar glass fiber filter. The smallest size fraction, i.e., the bacterial fraction (0.2-2 µm), was collected with a Millipore Ceraflo crossflow filtration system using ceramic filters (22) with a 0.2-µm-specific cutoff. A total of 4-5 m3 of seawater was concentrated to a retentate volume of approximately 12 L, which was then further concentrated to 500 mL in a Millipore Pellicon system, with a 0.2 µm cutoff. The retentate was then preserved in formaldehyde (KeboLab, purum) to a final concentration of 2% and stored in a capped glass flask in darkness at +8 °C until workup. After transport to the laboratory, the particles were centrifuged at 18000g, and the pellets were stored frozen (-18 °C) until chemical analysis. A massive blue green algal (cyanobacterial) bloom of Nodularia sp. forming filaments from millimeter to centimeter in size occurred at the time of sample forming. However, as the algae filaments occurred mostly near the surface during the daytime while the sampling was performed deeper, the sampling efficiency was not affected. The precipitate in the 100 µm nylon filters, which normally consists of zooplankton, was dominated by the blue green algae. Carbon Analysis. Particulate organic carbon (POC) was sampled by filtering 1 L of unfiltrated seawater on pretreated (480 °C, 5 h) Whatman GF/F filters using acid-washed equipment. The filters were then analyzed in an elemental analyzer Leco CHN-900. Blanks were run in parallel and subtracted from samples. Organic carbon in the 0.2-2 µm fraction was analyzed from an aliquot of the particle pellet, dried in +60 °C (8 h), which removed excess formaldehyde, and analyzed on a Carlo Erba EA 1108 HCN-O element analyzer. No organic carbon analysis was done for the >100 µm fraction. Chemical Analysis. All samples and blanks were Soxhlet extracted for 24 h using different solvents for the different samples. Nylon filters were extracted with acetone:hexane (60:40), Millipore AP20 filters were extracted with hexane, and bacterial pellets and PUF plugs were extracted with toluene. All solvents used were of glass distilled quality (Burdick & Jackson). A Dean-Stark trap was attached on the Soxhlet apparatus for water removal (23) for all extractions, except the nylon filters. All samples and blanks were spiked with five 13C-labeled PCBs (52, 101, 118, 138, and 180) prior to extraction. The volume-reduced extracts were eluted on 100 × 10 mm columns containing deactivated SiO2 (10% water w/w) with hexane as mobile phase (24, 25). The extracts were then further cleaned up with HPLC (26) using an amino column in straight phase mode for separation of PCBs from alkanes/monoaromatic hydrocarbons and polycyclic aro-
FIGURE 2. Log in-situKoc vs log Kow for the PCB congeners in the two particle size fractions 0.2-2 µm (filled circles) and 2-25 µm (open circles) for the three samples A, B, and C. Black and gray lines are the linear regression lines for the 0.2-2 and 2-25 µm size fractions, respectively. Dashed lines are 95% confidence limits for the regression lines. matic hydrocarbons. The samples were then analyzed on a Fisons GC8000/MD800 (EI, single ion recording mode), and the PCB congeners were quantified against the 13C-labeled standard with the same or nearest number of chlorine atoms (di- and trichlorobiphenyls against the tetra-chlorinated 13Clabeled 52 and octachlorobiphenyls against the heptachlorinated 13C-labeled 180). The samples and blanks were analyzed for content of the following congeners denoted by their IUPAC numbers: (8, 5), 18, 15, 17, 31, 28, (33, 20), 22, 52, 49, 44, (41, 64), (70, 76), 66, 95, (101, 90), 99, 97, (87, 115), 110, 149, 118, (153, 132), 105, 138, (187, 182), 183, 128, 167, 185, (174, 181), 177, 171, 156, 157, 180, 199, (170, 190), (203, 196), and 194 (congeners given in pairs within parentheses co-elute with the dominant congener first). Content in samples was corrected for content in blanks. Response factors for the analyzed congeners were determined from a standard mixture of different Aroclor mixtures in known amounts (1242, 1254, and 1260), and the five 13C-labeled PCBs were cleaned up in the same way as the samples with concentrations of the different congeners taken from ref 27. The peaks were manually identified by means of retention times from ref 28 relative to the 13C-labeled PCB used for quantification. A qualifier ion was recorded in parallel for each congener for confirmation of correct peak identification.
Results and Discussion Influence of Growth and Particle Size. In-situ partition coefficients for all PCB congeners between organic carbon and water (expressed as L kg-1) were calculated for the two size fractions 0.2-2 and 2-25 µm from concentrations in the particles and in the dissolved phase (Table 2). In Figure 2, log in-situKoc values for the two size fractions are plotted against log Kow values taken from Hawker and Connell (29), and the linear regression lines are drawn with 95% confidence limits. For the 0.2-2 µm size fraction, there is a linear relationship throughout the entire log Kow interval. The slope is 1.19 and r 2 ) 0.762 with p < 0.0001 for the regression. All congeners in this size fraction appear to be in equilibrium, as was expected from the model, although there are significant deviations for individual in-situKoc values. The picture is completely different for the 2-25 µm size fraction, there being no correlation between log in-situKoc and log Kow. The slope does not differ significantly from zero (p ) 0.582). Unfortunately, none of the lighter congeners was above the detection limit, making it impossible to see whether this holds true for the entire log Kow interval or if the relationship levels off at log Kow ) 6, as could be expected from the combined picture of the two size fractions. Though the variation is significant, the larger size fraction clearly shows lower in-situ
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FIGURE 3. Log in-situKoc vs log Kow for the PCB congeners in the >100-µm particle size fraction for the two samples A and B with 0.5 log unit between horizontal gridlines. Solid line is the linear regression line, and dashed lines are its 95% confidence limits. partition coefficients compared to the smaller size fraction than would be predicted by the model using the typical growth rates observed in the field. In fact, the influence is even stronger than predicted for the 20 µm case with extremely high growth rate in Table 1. The calculated sorption rate constants according to eqs 2 and 4 appear to be overestimated. Intracellular as well as extracellular structures could restrict diffusion, thus causing sorption rates to be lower. The noncorrelation between log in-situKoc and log Kow observed in the 2-25 µm size fraction has also been observed for PCBs (log Kow interval 5-8) in growing algae (growth rate 0.13 doubling per day) in laboratory experiments by Swackhamer and Skoglund (11). The model used in the present study predicts increasing uptake rate constants, k1, with increasing hydrophobicity of the PCBs due to the fact that the decrease in the calculated k2 values does not account for all of the increase in Koc values. However, a one-compartment model with firstorder rate constants applied to the in-situKoc values of the 2-25 µm size fraction would suggest constant uptake rates, k1, throughout the entire log Kow interval observed for this size fraction (5.75-7.7). This, in turn, implies a rate-limiting step, such as membrane passage or passage through pores in some kind of crystalline cell wall, that is more or less independent of hydrophobicity. Quantitative estimates of the particulate carbon pool have shown that it generally consists mainly of non-living particles (16) such as detritus. The relative composition varies between seasons, with a maximum fraction (up to 50% of POC) of living cells occurring during the productive summer period (30). During this period also, the non-living particles should have a turnover of carbon since they originate from the primary production and there is only a small accumulation of detritus in the watermass as compared to primary production. The turnover of carbon in detritus is, however, probably slower than in phytoplankton, which would decrease the influence on the partition coefficients. Still, the influence found in the field samples is significant. This could be due to several reasons that are impossible to differentiate in the present study and that are possibly also acting in combination. The turnover of organic carbon in the detritus could be high enough to account for some of the growth dilution effect. Another explanation could be that the organic carbon in the non-living particles is of poorer HOC-adsorbing quality, thus having only a negligible influence on the observed relationship between log Kow and log in-situKoc for the 2-25 µm size fraction. Due to the lack of organic carbon data, it was not possible to compare the >100 µm size fraction directly with the two others, but since the partition coefficients are expressed as log values, it is possible to calculate “fictional” nominal log in-situK values and compare slopes. In Figure 3, the nominal oc log in-situKoc is plotted against log Kow for the PCB congeners
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in the >100 µm size fraction. The regression line is drawn with 95% confidence limits. In the >100 µm size fraction, there is a weak correlation between log in-situKoc and log Kow, with a slope of 0.283 and r 2 ) 0.302 (p < 0.001 for the regression). The difference between the two larger size fractions is converse to that expected from the growth dilution model. One explanation could be the possible influence of consumers in the largest size fraction, which due to biomagnification could account for concentrations of heavier congeners closer to equilibrium. Solute-Solvent Interactions. The results from the field data of this study show a relatively large discrepancy between Kow and observed Koc in the 0.2-2 µm size fraction. At first this seems somewhat surprising since relatively good linear relationships between log Koc and log Kow have been found earlier (31):
log Koc ) log Kow - 0.39
(8)
for a number of hydrophobic compounds. However, there are few reports of actual measurements of highly hydrophobic compounds with log Kow > 6 and yet even fewer field measurements of Koc values in suspended particles for such compounds. A recent study of particles in the size fraction 10-102 µm in the euphotic zone actually reports Koc values for PCBs of up to 1 order of magnitude higher than Kow (11). We propose here an explanation for the observed high Koc values relative to Kow for the compounds included in this study having log Kow values higher than 5. An analysis of solute-solvent interactions of the octanol-water partition process indicate that the near ideal relationship between water solubility, satCw, and Kow levels off at Kow ≈ 105 in such a way that decreasing satCw does not give the expected increase in Kow (18, 32). This is partly explained by the small amount of octanol in the water phase, which increases the solubility of very hydrophobic solutes in the water phase. Chiou et al. (32) found an increase of 1.9 times for hexachlorobenzene (log Kow ) 5.73 (33)) and 2.8 times for DDT (log Kow ) 6.91 (33)). As pointed out by Chiou et al. (32), another important factor is the decreasing compatibility between the solute and the water-saturated octanol, partly due to the relatively high solubility of water in the octanol phase (2.3 M (34)). We believe that the structure of the carbon matrixes in the living planktonic organisms in this study could differ from watersaturated octanol in this aspect. Living cells have the ability to control the fluxes of polar compounds through their bilayer membranes, and it seems reasonable to assume that organic carbon matrixes of importance for the sorptive quality of these compounds are more ordered and contain less water than does water-saturated octanol. The organic phase of a living cell consisting of phospholipid bilayer membranes, liposomes, and hydrophobic domains of proteins could therefore be purer in terms of dissolved and associated water than watersaturated octanol and possibly also other non-living organic phases such as aggregates of organic macromolecules and organic coating on mineral particles, where the binding of water has shown to decrease adsorptive capacity (35). We therefore hold it possible that the planktonic organism-water system is more similar to the ideal partition coefficient calculated from subcooled liquid water solubility with no cosolvent effects. The deviation of individual Kow values for highly chlorinated PCB congeners from the ideal relationship between log satCw and log Kow is more than 1 order of a magnitude according to the observations by Schwartzenbach et al. (18). This means that our Koc values would lie close to the ideal linear relationship between log satCw and log Kow. Another and possibly complementary explanation for the high Koc values relative to Kow values could simply be that planktonic organisms have a number of sites with very high affinities for small hydrophobic molecules that would yield high Koc values. If these sites become saturated at relatively
low concentrations, they will not be detected in laboratory experiments but could still be of significance at environmental concentrations. These findings have significant implications on food chain modeling. The results show clearly that kinetic aspects in the base of the food chain must be taken into accout. A large part of the annual food intake for pelagic top consumers in temperate regions takes place during the productive season, and the concentrations of highly hydrophobic compounds in the different levels of the food web are dependent on the concentrations at the base of the food chain. The results of the present study show that the widely cited eq 8 used to predict partitioning between water and suspended particles is not applicable in the pelagial for highly hydrophobic compounds such as the PCBs. Equation 8 underpredicts the partition coefficients for all PCB congners in the 0.2-2 µm size fraction and the less hydrophobic PCB congeners in the 2-20 µm size fraction. Due to the effect of growth dilution, it also overpredicts the partition coefficients of the most hydrophobic congeners in the 2-20 µm size fraction. Because of the limited nature of the experiments above, further studies regarding the partitioning mechanisms in the field are needed before complete understanding is reached. Further studies also seem necessary in light of the bearings of these findings on environmental modeling.
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Received for review January 29, 1996. Revised manuscript received August 16, 1996. Accepted October 15, 1996.X ES960088+ X
Abstract published in Advance ACS Abstracts, January 1, 1997.
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