Environ. Sci. Technol. 2009, 43, 1115–1121
Modeling PCB Mass Transfer and Bioaccumulation in a Freshwater Oligochaete Before and After Amendment of Sediment with Activated Carbon XUELI SUN,† DAVID WERNER,‡ AND U P A L G H O S H * ,† Department of Civil and Environmental Engineering, University of Maryland, Baltimore County, Baltimore, Maryland 21250, and School of Civil Engineering and Geosciences, Newcastle University, NE1 7RU Newcastle, U.K.
Received July 9, 2008. Revised manuscript received November 22, 2008. Accepted November 24, 2008.
A mass transfer model is presented that couples sediment geochemistry with PCB bioaccumulation by the benthic invertebrate, Lumbriculus variegatus. This model accounts for PCB intraparticle mass transfer, desorption, and adsorption by different particle types, and uptake by the benthic invertebrates through two pathways, dermal absorption, and sediment ingestion. The biological parameters, dermal uptake coefficients, depuration rates, sediment ingestion rates, and uptake efficiencies, were measured independently. The model was evaluated by laboratory bioaccumulation experiments for three freshwater sediments that were characterized for PCB concentration, PCB desorption rate, and equilibrium partitioning behavior. The model was also tested for its ability to predict changes in PCB bioaccumulation in the three sediments after amendment with activated carbon to reduce PCB bioavailability. For most PCB congeners, the modeled results and measured values agree within a factor of 2 for all three sediments before and after treatment with activated carbon. This model broadly agrees with the experimental data and can be used to predict changes in bioaccumulation of hydrophobic organic compounds by the benthic organisms in sediments with known geochemical characteristics and under different sorbent amendment scenarios.
Introduction Organisms residing in sediments form the base of the aquatic food web that is primarily responsible for the transfer of sediment-bound historic contaminants to the upper trophic levels. Sound mechanistic models that link sediment geochemistry to contaminant biouptake processes are necessary for the understanding of long-term fate and bioaccumulation of sediment bound contaminants, for sediment risk assessment, and for the evaluation of long-term effects of potential remediation technologies. Equilibrium partitioning models based on thermodynamic equilibrium be* Corresponding author phone: 410-455-8665; e-mail: ughosh@ umbc.edu. † University of Maryland. ‡ Newcastle University. 10.1021/es801901q CCC: $40.75
Published on Web 01/23/2009
2009 American Chemical Society
tween sediment, porewater, and organisms are widely used to predict organic chemical accumulation in benthic invertebrates (1). Limitations of the equilibrium partitioning model are that it does not account for chemical disequilibria, species specific feeding strategies, and different uptake routes. Alternative bioaccumulation models have been developed that take into account various uptake and elimination rate processes for an organism and have been used to simulate steady-state concentrations in tissue (2, 3). However, these models do not incorporate ongoing mass transfer processes within sediments. Recent studies have demonstrated that the readily desorbed and weakly bound fractions of organic contaminants in sediment contribute greatly to the biouptake, whereas the slowly desorbing and strongly bound fractions limit the biouptake (4-7). Intraparticle diffusion models have been applied to describe the sorption/desorption mass transfer process as chemical diffusion through the porous structure of the matrix and have been verified by laboratory experimental results (8, 9). Coupled mass transfer and biouptake models can account for different biodynamic processes and the kinetics of sorption processes in sediment. Mechanistic-based models are necessary to explain contaminant fate processes especially under dynamic conditions such as when sediment geochemistry is altered by the addition of a strong sorbent. In this paper, we combine a geochemical mass transfer model with a biodynamic model to simulate the contaminant mass transfer and biouptake process from untreated and activated carbon (AC) treated sediments. AC is a strong sorbent for hydrophobic chemicals and has been proposed as an amendment to remediate sediments contaminated with hydrophobic organic compounds. The PCBs desorbed from sediments are transferred to AC resulting in a reduction of the aqueous phase concentration and bioavailability to organisms (10, 11). Past observations have indicated a relatively fast initial mass transfer of PCBs into the added carbon followed by a long period of slow mass transfer during which PCB bioavailability and aqueous phase concentrations decline over years (11, 12). Intraparticle diffusion-based models can predict such long-term trends in PCB bioavailability, especially after amendment with AC to change sediment geochemistry (9). The primary objectives of this study were to (1) develop a mathematical model incorporating intraparticle PCB mass transfer and biouptake processes of PCBs in a freshwater oligochaete, (2) independently measure the model parameters through separate laboratory microcosm experiments, (3) verify the model by comparing the predicted bioaccumulation results to previously published laboratory data (10), and (4) predict short and long-term PCB uptake profiles by L. variegatus based on the measured parameters after the sediments are amended with different particle size and dosage of AC.
Materials and Methods Model Description. In the present model, three particle types are considered: sediment particles that desorb PCBs fast (F), sediment particles that desorb PCBs slowly (S) and AC particles mixed in the sediments (AC) as shown in Figure 1. Several assumptions are made in the model: (1) PCB concentration in the aqueous phase is in linear partitioning equilibrium with PCB concentration on the surface of the three particle types (9); (2) PCB uptake by L. variegatus has a negligible impact on PCB concentrations in the sediment; and (3) the growth of microorganisms and biodegradation of PCBs are negligible within the time frame of the experiVOL. 43, NO. 4, 2009 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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TABLE 1. Measured Biological Parameters and Literature Log Kow Values for PCB Congeners Used in Model Simulationa
FIGURE 1. Conceptual model for PCB mass transfer in sediments and bioaccumulation in L. variegatus. ments and are not included in the model. The PCB desorption and absorption in the different particles is described by sorption retarded intraparticle radial diffusion process (9, 13):
(
∂Cx(r) Da,x ∂ 2 ∂Cx(r) rx ) 2 ∂t ∂r r ∂r x
)
(1)
Where Da,x is the apparent diffusion coefficient and Cx denotes the volumetric PCB concentration in the particles (g cm-3) with x ) F for fast, S for slow, or AC for activated carbon. The bulk aqueous concentration of PCBs determined by the diffusion process, Caq, is given by (9)
[
]
VF d 3 RF 2 dCaq r CF(r)dr )dt Vaq dt R3 0 F VS d 3 RS 2 VAC d 3 r CS(r)dr Vaq dt R3 0 Vaq dt R3 S AC
[
∫
∫
]
[
∫
RAC 2
0
r CAC(r)dr
]
(2)
where Vx denotes the total volume of each phase component (cm3) and Rx is the particle geometric mean radius (cm). A first order uptake model is used to simulate the bioaccumulation process by L. variegatus from the sediments through two major routes: adsorption from aqueous phase and uptake through contaminated sediment ingestion as described in eq 3. This bioaccumulation model is similar to McLeod et al. (3) with several differences. For example, in the present model the assimilation efficiencies of sediment and AC are treated separately and the fraction of PCBs transferred to AC is determined by the geochemical component of the model. Also, the way PCB absorption from the water phase is treated is different for a clam and a worm. d C (t) ) kderm · Caq(t) + dt b
∑ R · S · IR · C j
i
s,i(t) - kelim · Cb(t)
(3) Where Cb(t) is PCB concentration in the worm tissue (gg-1), Caq(t) is the aqueous phase contaminant concentration (g cm-3), Cs,i(t) is the PCB mass associated with particle type i per total mass of sediment (gg-1), Si is the selectivity index for particle type i (mass fraction in ingested sediment relative to mass fraction in bulk sediment), kderm is the dermal absorption rate (cm3 g-1s-1), kelim is the elimination rate (s-1), Rj is the fractional uptake efficiency (-) of PCB congener j in the digestive tract, and IR is the weight-specific sediment ingestion rate (gg-1s-1). The validity of the underlying assumptions of the geochemical part of the model has been discussed by Werner et al. (9). Model Implementation. The intraparticle diffusion model was implemented following the explicit numerical scheme described by Werner et al. (9). To achieve optimal computa1116
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PCB congener
Log Kow (22)
kderm (cm3 g-1s-1)
kelim ( × 10-6s-1)
r (-)
18 19 22 25 26 28 31 40 42 44 45 47 49 51 64 74 83 85 91 97 99 100 101 105 118 128 132 136 146 153
5.24 5.02 5.58 5.67 5.66 5.67 5.67 5.66 5.76 5.75 5.53 5.85 5.85 5.63 5.95 6.20 6.26 6.30 6.13 6.29 6.39 6.23 6.38 6.65 6.33 6.74 6.58 6.22 6.89 6.92
0.181 0.250 0.190 0.230 0.191 0.172 0.174 0.203 0.193 0.177 0.192 0.206 0.213 0.275 0.180 0.184 0.178 0.187 0.199 0.215 0.260 0.247 0.210 0.173 0.198 0.290 0.134 0.168 0.177 0.133
9.25 9.77 7.98 8.45 8.10 8.43 8.54 6.76 6.79 7.24 7.38 5.99 6.65 4.45 6.65 6.41 5.35 5.37 5.57 5.70 4.98 6.32 5.25 5.46 5.17 4.60 4.41 4.60 4.14 4.48
0.26 0.37 0.22 0.11 0.11 0.22 0.11 0.20 0.17 0.20 0.23 0.20 0.19 0.16 0.14 0.16 0.15 0.16 0.15 0.11 0.15 0.11 0.15 0.16 0.14 0.16 0.12 0.13 0.12 0.17
a Note: kderm is dry tissue based (cm3 per g dry weight per second); kelim is elimination rate (s-1), Rj is the fractional uptake efficiency (-) of PCB congener j in the digestive tract.
tion times the number of nodes within each particle type (N) chosen for the model runs were NF ) 11, NS ) 61 and NAC ) 601. The system of differential equations for both intraparticle diffusion and biological models was solved with an explicit Euler scheme. A time step constraint was used to avoid instability in the most sensitive component of the system. The model was coded in Matlab (MathWorks, Natic, MA). The 30 PCB congeners simulated by the model are listed in Table 1. These congeners range from tri- through hexachlorobiphenyls and represent 30-50% of the total PCBs measured in the three sediments. Bioaccumulation Tests. One sediment sample from Grasse River (GR) and two from Milwaukee River, Eastbrook Park (EB-1 and EB-2) were collected for the PCB bioaccumulation studies and were described in Sun and Ghosh (10). The concentrations of total PCB in the GR, EB-1, and EB-2 sediments were 6.8 ( 0.3, 45.2 ( 2.9, and 87.4 ( 6.9 µg/g, respectively. The granular activated carbon (AC) used was type TOG (Calgon Corp. Pittsburgh, PA) with the particle size range of 75-300 µm. The percentage AC added by weight of GR, EB-1, and EB-2 sediment was 2.6, 1.6, and 1.9%, respectively, to achieve 0.5-fold of the sediment native TOC. The AC treated and untreated sediment were rolled in a glass bottle for one month in a bottle roller at 3 rpm before conducting bioaccumulation assays using a mixed age population of L. variegatus as described previously (10). After exposure to sediments for 28 days, the L. variegatus were counted and transferred to a shallow glass pan with 15 mL clean spring water and purged for 8 h (20). L. variegatus tissue was crushed with sodium sulfate and extracted by sonication in hexane-acetone based on EPA SW846 method 3550B. PCB cleanup was based on EPA SW846 methods 3630C
TABLE 2. Example values of Input Parameters Used in Model Calculations parameters
parameter
activated carbon (AC) AC particle radius AC solid phase density AC porosity AC dose PCBs AC-water partition coefficient water phase diffusion coefficient bulk sediment-water partition coefficient PCB fast release fraction apparent diffusion coefficient in strong sorption sites (slow release particles) apparent diffusion coefficient in weak sorption sites (fast release particles) water/sediment ratio L. Variegatus selectivity index for particle type i (mass fraction in ingested sediment relative to mass fraction in bulk sediment) dermal absorption rate PCB elimination rate fractional uptake efficiency from fast release particles fractional uptake efficiency from slow release particles fractional uptake efficiency from activated carbon weight-specific sediment ingestion rate
values
sensitivity
sources
RAC (cm) dAC (g/cm3) pAC (-) dose (g/g)
0.0075 1.96 0.55 0.026
0.526 0.260 -0.871 -0.618
Werner et al. (9) Werner et al. (9) Werner et al. (9) measured
no. 47 KAC (cm3/g) Daq (cm2/s) Kd (cm3/g) f
3.98 × 107 5.59 × 10-6 22163 0.76
-0.328 -0.249 1.430 0.380
estimated from dataa estimatedb measured estimated from datac
Da,S/RS2(s-1)
2.00 × 10-8 -0.339
estimated from datac
Da,F/RF2(s-1)
6.00 × 10-7 -0.008
estimated from datac
ratiows (cm /g)
1
0.000
Werner et al. (9)
Si
1
0.873
estimated
0.111 -1.09 0.357 0.494 0.006 0.867
measuredd measured measured measured McLeod, et al. (14) measuredd
3
3
-1 -1
kderm (cm g s ) 0.206 kelim (s-1) 5.99 × 10-6 R1 0.20 R2 0.20 R3 0.01 IR (gg-1s-1) 1.24 × 10-4
a See Supporting Information for calculation of KAC. b Estimated by the method in Schwarzenbach, et al. (15). c Estimated by fitting eq 4 to the desorption kinetics data presented in ref (10). d Dry tissue based values (dry tissue weight is 10% of wet tissue weight).
(silica gel cleanup) and 3665A (sulfuric acid cleanup). PCBs were analyzed by gas chromatography with electron capture detection (6890N, Agilent Technologies) using methods described previously (21). A summary description of quality assurance/quality control procedures for PCB analyses are provided in the Supporting Information. Model Parameterization. Table 2 shows the input parameters used in the model and their sources. The apparent diffusion rates in AC were estimated by the methods described in Werner et al. (9). The AC-water partition coefficients were estimated as the average of the values determined from 1 and 6 month contact experiments by manually fitting the model aqueous concentration to measured aqueous concentrations in AC amended sediment slurries as described in Supporting Information Figure S1. The aqueous PCB measurement methods and results are presented elsewhere (10). As shown in Supporting Information Figure S1, the KAC value apparently increases from 1-month contact to 6-month contact period. Fouling affects PCB sorption and migration in the macropores more than sorption in the less accessible microporous regions of AC that remain available for PCB sorption. The fast release fraction (f ) and the desorption rates associated with fast release particles (Da,F/RF2) and slow release particles (Da,S/RS2) were calculated by fitting an analytical solution of eq 1 to measured PCB desorption kinetics data of bulk sediments (9):
[
∞
(
Da,F 6 1 M(t) )1-f 2 exp - 2 n2π2t Mtot π n)1 n2 RF
∑
[
∞
)]
- (1 - f )
(
Da,S 6 1 exp - 2 n2π2t 2 2 π n)1 n RS
∑
)]
(4)
where Mtot and M(t) are the initial PCB mass and PCB desorbed at time t, respectively. Results of the desorption study are described in detail elsewhere (10).
FIGURE 2. Relationship between PCB concentrations in dry tissue and water for PCB 28, 49, 85, and 153. The symbols, square (0), star (*), circle (O), and triangle (∆) are for PCB 28, 49, 85, and 153, respectively. The dermal uptake coefficients are 0.172, 0.213, 0.187, and 0.133 cm-3g-1s-1, respectively, based on the 3 h exposure. The dermal absorption rates (kderm) were measured by exposing the worms to aqueous PCB solutions. The PCB solutions were generated by filtering streamwater through a 0.45 µm filter paper and passing through a glass generator column packed with PCB coated glass wool as described in Ghosh et al. (16). The PCB solution generated was passed through the exposure chamber with a constant flow rate of 8.5 mL per minute. About 0.3 g L. variegatus were placed in the exposure chamber and allowed to remain in contact with aqueous PCBs for three hours (Supporting Information Figure S2). At sampling times, the worms were harvested, rinsed with DI water, weighed, and extracted in a mixture of hexane and acetone for PCB analysis. The results shown in Figure 2 indicate that within a short exposure period of 3 h, PCB concentration in tissue was linearly related to the water phase concentration. Therefore, dermal absorption rates (kderm) were calculated by dividing the linear regression slopes by VOL. 43, NO. 4, 2009 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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the exposure time. This dermal absorption rate measurement is based on the assumption that the elimination rate is not important during the initial portion of the uptake curve (17). The elimination rate (kelim) was measured by exposing L. variegatus to PCB contaminated sediments for 14 days followed by depuration in clean sediment. The organisms were sampled from clean sediments at 0 h, 6 h, 1 day, 3 days, 7 days, and 14 days. The elimination rates were calculated by fitting the first order model described in eq 5 to the elimination kinetics data (18). dCb(t) ) -kelimCb(t) dt
(5)
Where Cb(t) is contaminant concentration in the worm tissue (gg-1dry tissue), and kelim is elimination rate of contaminants from the tissues (s-1). The uptake efficiency (R) defined as the fraction of PCBs in sediment taken up by the organism during gut passage, was calculated based on the PCB concentrations in sediment and feces. Sediment (80 g) was transferred into a 100 mL beaker and a thin layer of sand was placed on the top of sediment with 2-3 cm water on the surface layer (Supporting Information Figure S3). About 0.15 g worms were added to the beaker with a plastic pipet. After three days, the feces on the top of the sand layer were collected gently to avoid any disturbance of the sediments and extracted for PCB measurement. The uptake efficiency was calculated using the equation below:
(
R) 1-
Cfeces Csed
)
(6)
Where R is the fractional uptake efficiency of L. variegatus from the ingested sediment, Cfeces, and Csed are concentrations of PCBs in the feces and sediment, respectively (g/g). The weight specific sediment ingestion rates (IR) were estimated by measuring the mass of feces and worms described above based on the assumption that the fecal pellets represent the sediment ingested by worms. A previous study demonstrated that the sediment mass assimilation of deposit feeders is very low (19). Our experimental procedure measures the overall uptake efficiency from sediment R, which was set equal to the uptake efficiency from both, the fast and slow release sediment particles.
Results and Discussion Dermal Absorption Rates. The kderm values are in the range of 0.133 to 0.290 cm3g-1s-1 for the selected congeners (dry tissue based) (Table 1). The values are relatively constant at about 0.2 cm3g-1s-1 up to a log Kow value of 6.5 and then decreases with increasing Kow values (see Supporting Information Figure S4). Our observations may be the first reported direct measurement of the dermal uptake coefficients of PCB congeners for this organism. Past investigators have calculated these values by fitting one compartment models to the kinetic uptake data of worms exposed to sediment. For example, modeled wet tissue based uptake constants for PCB 15, 47, and 153 by L. variegatus were reported to be 0.029, 0.038, and 0.037 cm3g-1s-1, respectively (23). Our observations when converted to wet tissue based kderm (dividing by 10) are close to these previously reported values. PCB Elimination Rates. Figure 3 presents the PCB tissue residues normalized by initial concentrations vs the elimination time for PCB 28, 49, 85, and 153. Elimination process for the four congeners is fast during the first three days and then slows down. The elimination rate was calculated from the first 3 days depuration that followed first order kinetics and represented a loss of 70-90% of each congener. The natural logarithms of body burden were plotted against the depuration time, and the elimination rate constants of 1118
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FIGURE 3. Fitted elimination rate model and measured tissue PCB residues normalized to initial concentrations during elimination in clean sediment for PCB 28, 49, 85, and 153. different congeners were estimated by linear regression giving values in the range of 4.14 × 10-6 - 9.77 × 10-6 s-1 (Table 1) and half-life from 0.82 to 1.94 days for the different congeners. As shown in Table 1, the kelim value decreases by a factor of 2 with an increase in PCB chlorination level from trichloro- to hexachlorobiphenyls. Schuler et al. (17) found the depuration half-life of PCB 152 in L. variegatus is 4.1 days which is twice the value measured in the present study. Possible explanations for a slower estimate of elimination rate by Schueler at al (17) are different sediment characteristics and the use of the entire 10 day duration of the elimination period for fitting elimination rate as compared to the initial fast elimination period of 3-days fitted in the present study. Sediment Ingestion Rates and Uptake Efficiencies. Sediment ingestion can be the principal route for the accumulation of sediment associated hydrophobic contaminants (24). Therefore, to understand and model the uptake and accumulation of PCBs by the worms, the two critical parameters, sediment ingestion rate, and uptake efficiency which determines the uptake across the gut lining, need to be measured. In order to avoid the effect of different sediment characteristics, ingestion rates were measured for the Grasse River and Milwaukee river sediments separately and found to be 12.5 ((0.6) × 10-5 gg-1s-1 and 7.25 ((0.39) × 10-5 gg-1s-1 (dry weight basis), respectively. Leppanen and Kukkonen (24) reported that ingestion rates were linearly related to the worm size. Based on their ingestion rate equation and the worm size in the present experiment, the calculated ingestion rates are from 5.58 × 10-5 gg-1s-1 to 42.3 × 10-5 gg-1s-1 (dry weight basis). Moreover, Val Klump et al. (25), observed that the ingestion rates of tubificid worms similar to L. variegatus ranged between 1.4 × 10-5 gg-1s-1 and 6.9 × 10-5 gg-1s-1 (dry weight basis). Therefore, our measurements of sediment ingestion rates are in the range of previous observations for benthic worms. Supporting Information Figure S5 shows the uptake efficiencies of selected PCB congeners during the experiment. It appears that the uptake efficiencies decline first and then increase indicating those parameters vary with exposure time. The uptake efficiency is the fraction of sediment associated PCBs that are incorporated into the worm tissue and is the sum of assimilation and postdigestive soluble excretion indicating it might be related to the ingestion rates. As the ingestion rates increase during the exposure, the uptake efficiencies tend to decrease due to the decline of the gut retention time (26). For example, uptake efficiency of PCB 153 by tubificid worms decreased from 36 to 15% over the initial 10 day period, whereas the ingestion rates increased from 0.05 to 0.25 mg mg-1h-1 over the same period (25). Leppa¨nen and Kukkonen (24) showed that the uptake rates
FIGURE 4. Comparison of measured and predicted PCB aqueous concentration after the sediments were treated with different doses of AC: 0.2 (]), 1.0 (O), and 2.0 (∆) times TOC. KAC values used were calculated based on an AC dose of 0.5 times of TOC. of L. variegatus (5-9 mg wet weight) peaked after about 6-8 days. These previous findings may explain why the observed uptake rates and efficiencies change with time. Table 1 shows the average assimilation efficiencies by L. variegatus from sediments which varies from 10.9 to 36.5% for the different congeners consistent with the previously published data (25). The assimilation efficiencies from AC should be very low due to strong absorption. McLeod et al. (14) observed differences in absorption efficiency between compounds and PCB-52 bound to activated carbon exhibited less than 2% absorption efficiency by clams. Due to the different species of organisms and wide range of PCB congeners investigated, an average assimilation efficiency of 0, 1, and 2% for AC are used for simulation in the present study. Kukkonen and Landrum (26) reported that L. variegatus is a general feeder and ingests all fine particles equally without selective feeding on the organic rich ones. As shown in Supporting Information Figure S6, there is little difference in TOC between ingested particles and whole sediment. Hence, we assume the selectivity index is one for all particle types in the model simulation. Evaluation of the Geochemical Model Component. The geochemical model (eq 2) was used to predict PCB aqueous concentrations for the sediments contacted with different doses of AC for one month. The comparison of measured and predicted aqueous PCB values are shown in Figure 4 and indicate a generally reasonable agreement over 4 orders of magnitude in PCB concentration. There is more scatter in the data at the low concentrations possibly contributed by greater uncertainty of the experimental measurement below the ng/L concentration range. Evaluation of the Biokinetic Model Component. Figure 5a shows the comparison of modeled PCB concentrations in L. variegatus exposed to untreated sediments with those measured and reported by Sun and Ghosh (10). The ratio of predicted to observed values for most congeners simulated for theses three sediments agree within a factor of 2 across 3 orders of magnitude in PCB concentration. The deviation within a factor of 2 could arise from several factors. The biokinetic model assumes a constant value for lipid content, ingestion rate, elimination rate, and uptake efficiency, whereas experimental data indicates some changes in these parameter values with time. Also, the growth cycle of these organisms is complicated. In short, the real biological system is much more complicated than the biokinetic model presented here. Nonetheless, the biokinetic model component captures the major process affecting PCB uptake and the concentrations determined by the model are within a reasonable range of measured values. It is important to note that in this model, all the biological parameters were
measured independently and the biouptake was predicted based on the physical, chemical, and biological mechanisms rather than fitting the model to the uptake data. Therefore, this model can be used with reasonable accuracy to predict PCB uptake by L variegatus when the sediment geochemical characteristics are known. Prediction of PCB Bioavailability after AC Addition. As shown in Figure 5b, there is generally good agreement between measured and predicted PCB concentrations in worms exposed to the three sediments after treatment with AC. There is a general shift of measured and predicted concentrations to lower values in Figure 5b compared to the values in Figure 5a, but the data points are still close to the 1:1 line indicating good predictability of the effect of AC addition on PCB bioaccumulation reduction. The lower PCB concentrations are associated with higher measurement errors. Relative Importance of Uptake Pathways. The percent contribution of PCB biouptake through ingestion increases with increasing PCB hydrophobicity as shown in Supporting Information Figure S7. This is consistent with low aqueous concentrations and mass transfer fluxes of the higher chlorinated congeners. Leppa¨nen and Kukkonen (27) reported that ingested materials contributed to 61% of pyrene accumulation in L variegatus after 8 days exposure. Recently modeled PCB uptake by M. balthica and C. fluminea demonstrated that approximately 90 and 45% of their body burden came from sediment ingestion, respectively, due to differences in feeding strategies (3). M. balthica, like L. variegatus, deposit-feeds, whereas C. fluminea filter-feeds. As demonstrated earlier (21) amendment of sediment with AC reduces PCB uptake in worms through both uptake pathways and is evident from reduction of PCB aqueous concentration and PCB desorption from sediment. Sensitivity Analysis. Sensitivity analysis was performed to identify the important model parameters affecting the uptake by benthic invertebrates from sediments and is presented in Table 2. The sensitivity is evaluated by calculating model output change in response to lowering each of the input parameters by 10% while keeping other parameters constant, and are presented in Table 2. Consistent with the above, and recently reported observations (2) the results show that the most sensitive parameters for bioaccumulation are sediment water partition coefficients and diet related parameters, such as selectivity index, ingestion rate, and elimination rate confirming both the sediments physicochemical characteristics and animal biology affect bioaccumulation. Comparison of sensitivity values across parameters should also take into account possible ranges of values the parameter may assume. As shown in Supporting Information Figure S8, alteration of the uptake efficiency parameter for slow and fast desorbing sites in sediment to account for reduced uptake from stronger and increased uptake from weaker sorption sites has a small effect on the overall prediction of PCB bioaccumulation. Similarly, changing the PCB uptake efficiency for AC (0, 0.01, and 0.02) also has a small effect on predicted PCB biouptake percent reductions (Supporting Information Figure S9). The experimentally observed reductions in bioconcentration after AC amendment can only be reproduced by the model, if the uptake efficiency from AC is significantly less than the sediment values for R, which ranged from 0.11 to 0.37. A much simpler empirical model relating free aqueous PCB concentrations to PCB bioaccumulation may also provide a reasonable estimate of bioaccumulation reduction (10). However such empirical models are not able to incorporate changing sediment geochemistry and do not enhance our mechanistic understanding of the factors affecting biouptake after sorbent amendment of contaminated sediment. The current model combining intraparticle PCB mass transfer VOL. 43, NO. 4, 2009 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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FIGURE 5. The comparison of measured and predicted PCB concentrations in dry tissue of L. variegatus exposed to untreated (a: left) and activated carbon treated (b: right) sediments from Grasse River (GR: O), Milwaukee River-1 (EB-1: ]), and Milwaukee River-2 (EB-2: 4). The dose of AC is 2.6, 1.61, and 1.85% for GR, EB-1, and EB-2, respectively. Measured PCB data are from experiments presented in Sun and Ghosh (10).
FIGURE 6. PCB (no. 49) uptake profiles in L variegatus after GR sediment is amended with different dosage (upper) and size (bottom) of AC. For the dose study, the average AC particle size is 75 µm and the profile lines from top to bottom in the plot are sediments untreated and treated with the dose of 0.2, 0.5, 1, 2, and 5 times of TOC, respectively. For the AC size study, AC dose is 0.5 times TOC, and the profile lines from bottom to top in the plot are sediments treated with AC with the sizes of 50, 75, 150, 300, 500 µm, and untreated, respectively. and organism biouptake processes allows simulation of biouptake as a function of contact time, AC dosage, or AC particle size. At contact times much greater than the biokinetic timescales, the reduction in PCB bioconcentration in AC amended sediment is related to the reduction in aqueous concentrations in the case of the lowest molecular weight congeners for which dermal uptake dominates. For the higher chlorinated PCB congeners the differences in 1120
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uptake efficiencies from ingested AC vs ingested sediment particles as well as the degree of mass transfer of PCBs from sediment to the added AC will determine the overall treatment efficiency. Slow intraparticle mass transfer processes in sediment and AC particles may prevent true equilibrium from being achieved for years or even decades. Instead, a quasisteady-state is likely to represent the delicate balance between different kinetic processes.
Biouptake Simulations under Different Amendment Scenarios and Implications. Simulated temporal profiles of PCB biouptake for L. variegatus as a function of AC size, and AC dose are shown for PCB 49 (a tetrachlorobiphenyl) in Figure 6. Based on the results, the uptake reductions are proportional to both AC size and dose and the approach to equilibrium is faster for smaller AC particle size. Therefore, small size AC particles are more efficient for bioavailability reduction, which agrees with previous experimental observations (12, 21). The model predicts a 98% reduction of PCB no. 49 biouptake as a result of 10 year sediment AC contact as compared to 87% after one month (Supporting Information Figure S10). Because the model is generic and adjustable to reflect site-specific geochemistry, it can be useful to predict PCB bioaccumulation in a broad range of sediments and to simulate long-term risk reduction after carbon amendment to sediment. The model can be easily modified to apply to a different benthic organism for which independently measured biokinetic parameters are available.
Acknowledgments This research was partly funded by the U.S. Environmental Protection Agency (EPA) Great Lakes National Program Office through EPA grant no. GL-96555401. Additional support for this work was provided by the University of Maryland Baltimore County through new faculty startup funds, and by the U.K. Engineering and Physical Sciences Research Council through grant EP/F012934/1.
Supporting Information Available Details of individual congeners selected for the model, experimental design, and model calibration are presented together with additional experimental and modeling results. Quality assurance quality control results of the analytical measurements are also available. This material is available free of charge via the Internet at http://pubs.acs.org.
Literature Cited (1) Technical Basis for Deriving Sediment Quality Criteria for Nonionic Organic Contaminants for the Protection of Benthic Organisms by Using Equilibrium Partitioning, EPA no. 822R93-011; U.S. Environmental Protection Agency: Washington, DC, 1993. (2) Morrison, H. A.; Gobas, F.A.P.C.; Lazar, R.; Haffner, G. D. Development and verification of a bioaccumulation model for organic contaminants in benthic invertebrates. Environ. Sci. Technol. 1996, 30, 3377–3384. (3) McLeod, P. B.; Luoma, S. N.; Luthy, R. G. Biodynamic modeling of PCB uptake by Macoma balthica and Corbicula fluminea from sediment amended with activated carbon. Environ. Sci. Technol. 2008, 42, 484–490. (4) Kukkonen, J. V. K.; Landrum, P. F.; Mitra, S.; Gossiaux, D. C.; Gunnarsson, J.; Weston, D. The role of desorption for describing the bioavailability of select polycyclic aromatic hydrocarbon and polychlorinated biphenyl congeners for seven laboratoryspiked sediments. Environ. Toxicol. Chem. 2004, 23, 1842–1851. (5) Kraaij, R.; Seinen, W.; Tolls, J.; Cornelissen, G.; Belfroid, A. C. Direct evidence of sequestration in sediments affecting the bioavailability of hydrophobic organic chemicals to benthic deposit-feeders. Environ. Sci. Technol. 2002, 36, 3525–3529. (6) You, J.; Landrum, P. F.; Trimble, T. A.; Lydy, M. J. Availability of polychlorinated biphenyls in field-contaminated sediment. Environ. Toxicol. Chem. 2007, 26, 1940–1948. (7) Talley, J. W.; Ghosh, U.; Tucker, S. G.; Furey, J. S.; Luthy, R. G. Particle-Scale Understanding of the Bioavailability of PAHs in Sediment. Environ. Sci. Technol. 2002, 36, 477–483.
(8) Karapanagioti, H. K.; Gossard, C. M.; Strevett, K. A.; Kolar, R. L.; Sabatini, D. A. Model coupling intraparticle diffusion/sorption, nonlinear sorption, and biodegradation processes. J. Contam. Hydrol. 2001, 48, 1–21. (9) Werner, D.; Ghosh, U.; Luthy, R. G. Modeling polychlorinated biphenyl mass transfer after amendment of contaminated sediment with activated carbon. Environ. Sci. Technol. 2006, 40, 4211–4218. (10) Sun, X.; Ghosh, U. The effect of activated carbon on partitioning, desorption and biouptake of native PCB in four freshwater sediments. Environ. Toxicol. Chem. 2008, 27, 2287–2295. (11) Millward, R. N.; Bridges, T. S.; Ghosh, U.; Zimmerman, J. R.; Luthy, R. G. Addition of activated carbon to sediments to reduce PCB bioaccumulation by a polychaete (Neanthes arenaceodentata) and an amphipod (Leptocheirus plumulosus). Environ. Sci. Technol. 2005, 39, 2880–2887. (12) Tomaszewski, J. E.; Werner, D.; Luthy, R. G. Activated carbon amendment as a treatment for residual DDT in sediment from a superfund site in San Francisco Bay, Richmond, California, USA. Environ. Toxicol. Chem. 2007, 26, 2143–2150. (13) Wu, S. C.; Gschwend, P. M. Numerical modeling of sorption kinetics of organic compounds to soil and sediment particles. Water Resour. Res. 1988, 24, 1373–1383. (14) McLeod, P. B.; Heuvel-Greve, M. J. van den; Allen-King, R. M.; Luoma, S. N.; Luthy, R. G. Effects of particulate carbonaceous matter on the bioavailability of benzo[a]pyrene and 2,2′,5,5′tetrachlorobiphenyl to the clam, Macoma balthica. Environ. Sci. Technol. 2004, 38, 4549–4556. (15) Schwarzenbach, R. P.; Gschwend, P. M.; Imboden, D. M. Environmental Organic Chemistry, 2nd ed.; John Wiley and Sons, Inc. Publication.: Hoboken, NJ,2003. (16) Ghosh, U.; Weber, A. S.; Jensen, J. N.; Smith, J. R. Dissolved PCB congener distribution in generator column solutions. Water Res. 1998, 32, 1373–1382. (17) Schuler, L. J.; Wheeler, M.; Bailer, A. J.; Lydy, M. J. Toxicokinetics of sediment-sorbed benzo[a]pyrene and hexachlorobiphenyl using the freshwater invertebrates Hyalella azteca, Chironomus tentans, and Lumbriculus variegatus. Environ. Toxicol. Chem. 2003, 22, 439–449. (18) Bjo¨rk, M.; Gilek, M. Efficiencies of polychlorinated biphenyl assimilation from water and algal food by the blue mussel (Mytilus edulis). Environ. Toxicol. Chem. 1999, 18, 765–71. (19) Rasmussen, J. B. Comparison of gut contents and assimilation efficiency of fourth instar larvae of two coexisting chironomids, Chironomus riparius Meigen and Glyptotendipes paripes (Edwards). Can. J. Zool. 1984, 62, 1022–1026. (20) Methods for Measuring the Toxicity and Bioaccumulation of Sediment-Associated Contaminants with Freshwater Invertebrates, 2nd ed, EPA no. 600/R-99/064; U.S. Environmental Protection Agency: Washington, DC, 2000. (21) Sun, X.; Ghosh, U. PCB bioavailability control in Lumbriculus variegatus through different modes of activated carbon addition to sediments. Environ. Sci. Technol. 2007, 41, 4774–4780. (22) Hawker, D. W.; Connell, D. W. Octanol-water partition coefficients of polychlorinated biphenyl congeners. Environ. Sci. Technol. 1988, 22, 382–387. (23) Fisher, S. W.; Chordas, S. W.; Landrum, P. F. Lethal and sublethal body residues for PCB intoxication in the Oligochaete Lumbriculus variegatus. Aquat. Toxicol. 1999, 45, 115–126. (24) Leppa¨nen, M. T.; Kukkonen, J. V. K. Relative importance of ingested sediment and pore water as bioaccumulation routes for pyrene to oligochaete (Lumbriculus variegatus, Mu ¨ ller). Environ. Sci. Technol. 1998, 32, 1503–1508. (25) Val Klump, J.; Krezoski, J. R.; Smith, M. E.; Kaster, J. L. Dual tracer studies of the assimilation of an organic contaminant from sediments by deposit feeding oligochaetes. Can. J. Fish. Aquat. Sci. 1987, 44, 1574–1583. (26) Kukkonen, J. V. K.; Landrum, P. F. Measuring assimilation efficiencies for sediment -bound PAH and PCB congeners by benthic organisms. Aquat. Toxicol. 1995, 32, 75–92. (27) Leppa¨nen, M. T.; Kukkonen, J. V. K. Relationship between reproduction, sediment type, and feeding activity of lumbriculus variegatus (Mu ¨ ller): Implications for sediment toxicity testing. Environ. Toxicol. Chem. 1998, 17, 2196–2202.
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