Article pubs.acs.org/est
Biological Pump Control of the Fate and Distribution of Hydrophobic Organic Pollutants in Water and Plankton Luca Nizzetto,*,†,‡ Rosalinda Gioia,‡ Jun Li,§ Katrine Borgå,† Francesco Pomati,∥ Roberta Bettinetti,⊥ Jordi Dachs,# and Kevin C. Jones‡ †
Norwegian Institute for Water Research, Gaustadalléen, 21 NO-0349 Oslo, Norway Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, United Kingdom § State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China ∥ Department of Aquatic Ecology, Swiss Federal Institute of Aquatic Science and Technology (EAWAG), Seestrasse 79, 6047 Kastanienbaum, Switzerland ⊥ Department of Theoretical and Applied Sciences, University of Insubria, Via Dunant 3, 21100 Varese, Italy # Department of Environmental Chemistry, Institute of Environmental Assessment and Water Research (IDAEA), Spanish Council for Scientific Research (CSIC), Jordi Girona 18-24, Barcelona 08034, Catalunya, Spain ‡
S Supporting Information *
ABSTRACT: The goal of this study was to experimentally assess the coupling between primary producer biomass dynamics and the distribution and fate of persistent organic pollutants (POPs) in a lake pelagic ecosystem. This was done by following the short-term evolution of polychlorinated biphenyl (PCB) concentrations in water and biota (phytoplankton and zooplankton) and the variability of bioconcentration (BCF), biomagnification (BMF), and bioaccumulation (BAF) factors during the development of a typical spring ecological progression in which the phytoplankton bloom is followed by a peak in the zooplankton abundance. The bulk of compounds with log KOW > 6.5 in the lake epilimnion was mainly associated with primary producer biomass. The phytoplankton biological pump was a major driver of POP export from the epilimnion, causing the decline of dissolved-phase concentrations. The BCF of phytoplankton for the more hydrophobic PCBs showed minima during the period of biomass climax. The concentration in the zooplankton of all selected PCBs sharply declined from March to May, with BAFs having minima in the post algal bloom phase. Biomagnification occurred during the pre algal bloom and algal bloom phases but appeared to be absent during the post algal bloom. This study highlights the occurrence of a prompt and complex response in the fate and distribution of POPs to dynamic biogeochemical control. Within the frame of the ecological succession, phytoplankton and zooplankton biomass dynamics produced bioaccumulation metrics varying over 1−2 orders of magnitude in the time frame of a few weeks and resulted in reduced trophic web exposure.
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INTRODUCTION The role of biogeochemical cycles in influencing intercompartment exchange and ultimately regional and global distribution of many ubiquitous hydrophobic chemicals has been the focus of recent research.1,2 The carbon cycle has been shown to have a key role in controlling environmental sink processes such as burial in soils and sediments.3−6 Uptake by highly dynamic organic carbon (OC) pools, such as primary producer biomass, may influence chemical concentrations in the abiotic transport media (namely, air and water),2,7 thereby affecting the magnitude of advection and ultimately chemicals' long-range transport. The occurrence of a relationship among ecosystem productivity, aquatic organism exposure, and magnitude of sedimentation fluxes of chemicals has been highlighted in some studies (e.g., refs 5, 8, and 9). Dachs et al.7 provided a first © 2012 American Chemical Society
theoretical assessment of the possible control of plankton biomass dynamics on both the water-dissolved phase and air− water exchange of hydrophobic chemicals, such as persistent organic pollutants (POPs). In summary, the different magnitudes of the resistances controlling chemical exchange between air and water and between water and plankton may lead to a depletion of dissolved-phase concentration in surface water, promoting net diffusive transfer from the atmosphere to the surface water, followed by chemical transfer to deeper water in association with sinking particles. In more recent papers (e.g., refs 10 and 11), this process has been referred as a Received: Revised: Accepted: Published: 3204
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Air sampling was carried out from a metal platform fixed on the rocky cliffs on the east coast. The platform is located about 4 m directly above the lake approximately 0.5−1 km from the water sampling area. The GF/A filter and PUF plugs were substituted every 10−15 d, and 100−200 m3 of air was collected each time. Samples of water and plankton were collected from a small boat. During the period of the study, six sampling campaigns were carried out (March 23, March 31, April 8, April 22, May 9, and May 25). Total suspended particle concentrations (CTSP, pg L−1) were measured by collecting the particles on a glass fiber filter (Whatman GF/F) (filtering surface area 175 cm2, nominal pore size 0.6 μm), while the dissolved-phase concentration (CXAD, pg L−1) was determined by collecting the total dissolved fraction on a 95 mL XAD-2 resin column. An FMI-Q2-SAN pump (with wet parts in polytetrafluoroethylene (PTFE), stainless steel, or ceramic), operating at 0.5 L min−1, was connected upstream of the sampling train. A 10 mm i.d. PTFE tube was used to collect water from a depth of about 10 m. Water sample volumes ranged from 100 to 180 L. Plankton samples were consistently collected and concentrated using a 10 μm mesh nylon net, manually operated within the upper 20 m of the water column (the vertical tow speed was about 0.5 m s−1). Bulk samples were fractionated through a nylon screen to separate the phytoplankton fraction (10−95 μm) from the zooplankton fraction (>95 μm). Plankton samples were transferred onto GF/F filters and stored at −20 °C until chemical analysis. The concentration in the phytoplankton fraction (Cpp) and the zooplankton fraction (Czoo) were expressed in picograms per gram of organic carbon associated with the respective fraction. Organic Carbon Analysis. At each sampling event 500 mL water were collected for total organic carbon (TOC) and particulate organic carbon (POC) analyses using a Niskin bottle at 10 m depth. Aliquots of the plankton samples were also analyzed for OC content. Details on sample handling and analytical methods are reported in the Supporting Information (Text S1). Flow Cytometry. Aliquots (50 mL) of the water samples were fixed with a filter-sterilized solution of paraformaldehyde and glutaraldehyde (0.01% and 0.1% final concentrations, pH 7) and stored at 2 °C in the dark. Analyses were carried out with the scanning flow cytometer Cytobuoy (Woerden, The Netherlands, http://www.cytobuoy.com).18 Further details are reported in the Supporting Information (Text S1). Chemical Analysis and Quality Assurance (QA)/ Quality Control (QC). The list of analyzed PCBs and information on chemical analysis are given in the Supporting Information (Text S2). All analytical procedures were monitored using strict quality assurance and control measures including laboratory and field blanks. Method detection limits (MDLs) were derived from the field blanks and quantified as 3 times their standard deviation. MDLs ranged from 1 to 3 pg μL−1 for the dissolved phase, from 1 to 21 pg μL−1 for the air phase, and from 1 to 14 pg μL−1 for the particulate phase. Recoveries were routinely monitored using the 13C12-PCBs as surrogate standards for PCBs, and they ranged from 70% to 109% (see Text S3 (Supporting Information) for more details). Geophysical and Meteorological Data. Meteorological data (see Table S7, Supporting Information) were kindly provided by the Centro Geofisico Prealpino from a station on
phytoplankton biological pump for semivolatile hydrophobic chemicals. Although well-characterized from the theoretical point of view, empirical evidence of the effectiveness of the biological pump is limited. Jeremiason et al.,12,13 for example, showed that the overall lake trophic state can influence air−water exchange fluxes of POPs, although no clear relationship was found between phytoplankton biomass dynamics and changes in water-dissolvedphase concentrations. Conditions promoting primary productivity can also lead to lower exposure of biogenic particles due to growth dilution.8,14 A recent study15 highlighted the occurrence of an inverse relationship between the spatial variability of plankton biomass and phytoplankton exposure to POPs, which has been related to the interaction of air−water exchange and settling fluxes of POPs. The importance of ecosystem properties (such as ecology and trophic state) for the transfer of contaminants from water and primary producers via secondary producers to the rest of the food web is identified as a knowledge gap.16 Despite the relevance of the biological pump for the overall exposure of POPs to aquatic ecosystems, an experimental assessment providing a consistent and integrated picture of the dynamic coupling among algal biomass dynamics, dissolved-phase concentrations, and aquatic biota exposure (e.g., zooplankton) is currently not available. The goal of the present study was to experimentally assess this coupling by following the distribution of selected POPs across the abiotic and biotic (phytoplankton and zooplankton) interface to assess the scale and time of response of ecosystem exposure in relationship to changes in the biotic conditions and to evaluate if the biological pump contributes to lowering or enhancing the exposure of the pelagic trophic web by either subjecting POPs to sedimentation with settling material or by subjecting them to trophic transfer. The evolution of PCB concentrations (taken as a model for POPs) in the water and biota (phytoplankton and zooplankton) phases and relevant bioaccumulation metrics such as bioconcentration (BCF), biomagnification (BMF), and bioaccumulation (BAF) factors were obtained during the development of a typical spring ecological progression taking place in the epilimnion of a deep oligotrophic lake, in which a period of rapid phytoplankton biomass growth (hereafter referred as algal bloom, for the sake of simplicity) was followed by the rapid development of zooplankton biomass.
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EXPERIMENTAL SECTION Study Site. Lake Maggiore is located in the Italian Southern Alps (see Figure S1, Supporting Information). The lake has predictable seasonal biological progressions occurring in the epilimnion, generally starting in March. A long-term comprehensive monitoring program has been continuously carried out since 1978 by the Institute for Ecosystem Studies of the Italian National Research Council (CNR-ISE). As a result, detailed information on biological, hydrological, physical, and chemical aspects is available.17 The sampling location (Figure S1) had a depth of about 260 m and was not directly exposed to inflow of major effluents. Sample Collection. Sampling occurred between March 23 and May 25, 2009. Air samples (n = 4) were taken continuously during this period using a glass fiber filter (Whatman GF/A) (for trapping particles) and two polyurethane foam (PUF) plugs in series (to trap gas-phase chemicals), connected to a pump operating at 7 L min−1 and an electronic mass flow meter. 3205
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the Leggiuno shores. The surface water temperature and information on thermocline depth were kindly provided by the CNR-ISE.17 Detailed monthly data of sedimentation fluxes of OC (FOC, kg m−2 d−1) in the pelagic area of Lake Maggiore are available from a two year monitoring program19 performed in 1990 and 1991. In that study, data were collected monthly using sediment traps deployed at 50 m depth at the point of the lake’s maximum depth.
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RESULTS AND DISCUSSION Physical and Biological Scenario. During February 2009, the lake water column was mixed to the depth of about 100 m. The process of thermal stabilization started in March and evolved (by the end of this month) into a stratified water column with a thermocline positioned at an average depth of about 10−15 m.17 During the period of the sampling campaign (end of March to May), the epilimnion (zone above the thermocline) remained consistently confined within the first 10 m. The temperature of the epilimnion (e.g., 5 m depth) ranged between 7 °C at the end of March and 13 °C at the beginning of May (Table S8, Supporting Information). The water temperature and the stratification of the water column are the key drivers of spring algal blooms.17 In the selected sampling area the bloom started during the last week of March, reaching the climax around the second half of April as shown by POC results (Figure 1A; Table S1, Supporting Information). POC passed from about 250 to 560 μg L−1 between the second and fourth sampling campaigns, and then it decreased to about 400 μg L−1 during May. This behavior is also confirmed by the flow cytometry results. There is no evidence of correlation between the density of nonfluorescent particles (encompassing detritus, bacteria, and protozoa) and POC. Instead, the occurrence of a statistically significant linear relationship between the density of fluorescent particles and POC indicates that this pool of OC is mainly associated with phytoplankton (Figure S2, Supporting Information). The dynamics of POC concentrations is the result of the early season ecological progression taking place in the epilimnion. After the algal biomass reached the maximum, grazing by zooplankton became an important factor controlling phytoplankton biomass. The volumetric concentration (e.g., grams per liter) of OC associated with zooplankton was derived from the OC content in the >95 μm fraction by estimating the volume of water screened through the plankton net during vertical towing. The accuracy of this method for the determination of volumetric concentrations is poor. However, it successfully reflected the time trend of OC associated with zooplankton as reported from the biological monitoring of CNR-ISE.17 The observed trends of POC and the OC associated with zooplankton are the consequence of trophic transfer between primary producers and the lower trophic levels of the lake food web, producing the “delayed” primary consumer peak.20 Particle settling to the hypolimnion (the portion of the water column below the thermocline) also represents a key control of the primary producer “standing crop” and is a key aspect involved in the biological pump process. Reference 19 reports the occurrence in the Lake Maggiore pelagic system, with maximum OC settling fluxes (FOC, mg of OC m−2 d−1) during spring. To verify the consistency of these data with the scenario of the present study, FOC was also estimated as a product between the POC data measured here and the settling velocity
Figure 1. (A) Time trends of [POC] (black line, left scale) and [OC] associated with the >95 μm fraction (zooplankton) (dotted line, right scale). Bars represent estimated data of OC settling fluxes FOC19 averaged for three periods of the campaign. (B) Time trends of CTD, Cpp, and Czoo of PCB 118. (C) Temperature-corrected log BCF and log BAF for PCB 118 during the sampling period. (D) BMF. PCB 118 was chosen as an example. See Figures S7−S9 (Supporting Information) for all results. The zooplankton samples were collected with a plankton net, and the volumetric concentration of [OC] in zooplankton was derived by estimating the tow sampling volume.
for POC measured in ref 19 at 50 m depth. Estimated FOC (Figure 1A) values were consistent within a factor of 2 with reported measurements.19 PCB Distribution in Surface Water. The distribution of PCBs among the subcompartments in the bulk water was analyzed. Concentrations (pg L−1) in the different phases (namely, the truly dissolved concentration, CTD, dissolved organic carbon associated concentration, CDOC, concentration associated with the total suspended particles in water, CTSP, and concentration associated with large particles (>95 μm, e.g., zooplankton)) were measured as described in the Supporting Information (Text S5). Czoo,v (pg L−1) (namely, the concentration of PCBs associated with particles >95 μm per unit volume of water) was estimated from the net samples (by estimating the towing volume). The fractional distribution of PCBs in the 3206
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that the decline corresponded to a loss from the epilimnion of 120−220 pg m−2 d−1 (depending on the compound). This is roughly 5−10% of the total epilimnic burden lost per week. This behavior cannot be explained by changes in the mixed layer depth (potentially acting on the volume of the surface water compartment); in fact, the thermocline depth remained relatively constant during the campaign (Table S8, Supporting Information). One hypothesis is that the surface water temperature could have led to net revolatilization of chemicals from water to the atmosphere. The epilimnion temperature, in fact, showed a considerable increase during the sampling campaign, going from 7 °C in March to 13 °C at the beginning of May. This hypothesis can be evaluated by looking at the ratio fa/f w between the fugacities of air and water.22 Fugacities were calculated using experimental data as described in Text S4 (Supporting Information). The results are shown in Figure S4 (Supporting Information) for selected PCBs. This analysis shows that, during most of the spring, air and water were close to the partitioning equilibrium for the compounds which showed declining CTD trends. During the period of net algal biomass growth (April samples) some congeners (e.g., PCB 118 and PCB 132/153) even showed a weak tendency for net deposition (fa/f w ranged between 3.3 and 5). A tendency for net revolatilization was only observed on the last sampling date. This analysis therefore suggests that it is unlikely that the temperature (and volatilization) controlled the observed decline in CTD for the more chlorinated compounds during the period of the algal bloom. Similarly, degradation cannot explain the steady loss of heavier PCBs. In fact, the half-lives of PCBs in surface waters are reported to be in the range of years,23 a temporal scale which is incompatible with the observed loss rate from the dissolved phase. Finally, it is unlikely that changing watershed inputs can determine changes in the dissolved concentration at the observed rate. In fact, the renewal of epilimnic water of Lake Maggiore is a process expected to occur in the time frame of several months to years as detailed in ref 17 due to the lake dimensions. The most probable explanation is that the declines in waterdissolved concentrations were due to the effectiveness of the biological pump in driving PCB shifts from the dissolved phase to growing biomass and export to the hypolimnion. The goal of the following section is to provide a quantitative assessment of this hypothesis. Biological Pump Driven Export Fluxes. The magnitude of the biological pump induced export flux (Fbp, ng m−2 d−1) of POPs from the epilimnion to the deeper water was assessed during the algal bloom phase. Fbp was calculated using the estimated FOC values (Figure 1A) multiplied by the OC-normalized PCB concentrations measured in the phytoplankton fraction (Cpp, ng g−1 of OC). In principle, Fbp must be calculated by correcting for the contribution of the settling of exogenous POC (derived from the watershed); in fact, exogenous POC does not relate to the lake biological pump. From the y axis intercept of the plot in Figure S2 (Supporting Information) it can be estimated, to a first approximation, that exogenous POC accounts for about 40% of the total POC. Sinking fluxes were therefore corrected by multiplying their value by 0.6 (thus, Fbp = 0.6FOCCpp). Calculations were performed for PCB 90/101, 118, 138, and 132/153 taken as examples by averaging the results of the
different phases of the bulk water was calculated. The results are reported in Figure 2. In summary, the fraction associated with
Figure 2. Estimated distribution of selected PCB congeners in the different phases of the bulk water (average of all samples).
TSP (mainly phytoplankton) constituted by far the largest reservoir of PCBs for compounds with log KOW > 6.7,21 accounting for between 50% and 75% of the total burden in the unit volume of bulk water. For compounds with log KOW < 6.7 the truly dissolved phase was the main capacitor. The fraction associated with DOC was between 5% and 35% of the total burden, depending on KOW. The large particles were estimated to contribute only 1−3%. The estimate of Czoo, however, may be affected by large uncertainty due to the lack of precision of the tow sampling method for determining volumetric concentrations. However, this assessment demonstrates that zooplankton accounts for only a minor fraction ( 6.3) had highest BCFs postbloom and lowest BCFs in peak bloom (Figures 4 and S9). Concerning zooplankton, the temporal variability in BAFs for most PCBs followed more or less the BMF pattern and decreased from peak bloom to postbloom (Figure 4). For lower chlorinated PCBs (with log KOW < 6.45), highest BAFs were found during algal bloom, whereas PCBs with higher log KOW (>6.45) had highest BAFs prebloom. The BAFs were greater than the BCFs, except during postbloom, indicating that the zooplankton biomagnified PCBs both prebloom and during bloom while in postbloom other processes likely controlled zooplankton concentrations. In fact, the BMF generally showed postbloom factors below 1 (Figure 1D). This effect is seen for all PCBs, from low to high log KOW. Low BMF values during post algal bloom coincide with the peak in zooplankton organic carbon and the lowest values of Czoo, suggesting a very effective role of growth, diet, and physiologically related parameters in promptly controlling bioaccumulation and 3208
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controlled by the depuration rate parameter but by the growth rate parameter. BCF can in fact be expressed as BCF =
ku kd + k g
(4) −1
where ku, kd, and kg (d ) are the uptake constant, the depuration constant, and the growth rate of phytoplankton (e.g., doublings per day), respectively. During the period of net phytoplankton biomass growth kg can be high enough to affect the relationship between BCF and KOW28 and in particular the slope value. (iii) The possible role of changing phytoplankton community composition during the algal bloom may also have implications for the observed results, although flow cytometry analysis did not suggest any major shift in morphological parameters. Concerning zooplankton, a significant decline (P < 0.05) in the log BAF vs log KOW slope was also observed for the algal bloom phase. However, in this case this did not coincide with the minima in log BAF. The BAF minima, in fact, were observed during postbloom and did not display a regression curve with a low slope value. During the bloom phase (April), unlike that of phytoplankton, zooplankton biomass growth cannot explain the low slope values. In fact, on the basis of the trend of zooplankton OC concentration (used here as a proxy for zooplankton biomass), there is no evidence of a significant increase of zooplankton biomass during April (Figure 1 A). Conversely, there was an increase by a factor of 2 of the zooplankton biomass in May. The mechanistic interpretation of the observed shifts in the relationship between BAF and KOW is complicated for zooplankton by the need for taking into consideration dietary and physiological parameters, factors which are likely nonstationary in these highly unsteady conditions. These include in particular dietary changes (possibly driven by changed food availability), community scale biomass growth, and egestion of eggs which contain a high lipid content and are an efficient depuration vector in zooplankton.29 In addition, the possibility of shifts in zooplankton species composition and the rise of secondary consumer species must also be considered among the factors controlling the observed BAF values. Food is likely an important factor for zooplankton exposure during the algal bloom. In fact, the analysis of principal components performed using PCB pattern data in zooplankton and phytoplankton showed that the pattern of PCBs in zooplankton immediately before and during the algal bloom closely reflected that of phytoplankton (Figure 5) and was distinct from that of the early prebloom and postbloom samples. In particular, clustered samples were characterized by relatively higher abundance of less chlorinated congeners. This conclusion is also supported by the BMF plots (Figures 1D and 4C; Figure S10, Supporting Information), which show a tendency for maxima in the bloom phase. As a result low April slope values of the BAF vs KOW plot for the zooplankton may simply reflect the contamination profile observed in phytoplankton. The decline in BAF recorded in the postbloom phase, instead, may be due to a combination of a number of behavioral, physiological, and ecological parameters30 (as described above), among which growth dilution and egg production may be important (for example, that associated with rapid spring parthenogenic reproduction typical of Cladocera and Rotifera in
Figure 4. Relationship between octanol−water partitioning coefficient (KOW) and (A, top) BCF, (B, middle) BAF, and (C, bottom) BMF for PCBs in Lake Maggiore, Italy, during pre algal bloom (March 23−31), bloom (April 8−22), and post algal bloom (May 9−25).
therefore exposure dynamics, causing significant variations of key metrics over relatively short time scales. BCF and BAF Status in Relation to Equilibrium. Both log BCF and log BAF increased linearly with increasing log KOW (P < 0.05) (Figure 4A,B). This behavior is generally regarded as evidence of equilibrium or near-equilibrium partitioning conditions between water and plankton. 26 During the phytoplankton bloom, however, the slopes of BCF for phytoplankton and the quality of regression with KOW were significantly lower (P < 0.05) than those of both pre- and postbloom. This may be related to the following points separately or in combination: (i) The conditions promoting rapid growth and biomass turnover had prevented chemicals (especially the more hydrophobic ones) from reaching the steady state, provided the uptake into phytoplankton is kinetically limited.27 This process would result in a lower BCF value selectively for the more chlorinated congeners, resulting in a lower slope value. (ii) If uptake is not kinetically limited, the steady-state conditions shift to a situation which is no longer 3209
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AUTHOR INFORMATION
Corresponding Author
*E-mail:
[email protected]; phone: +47 98215393; fax: +47 22185200. Notes
The authors declare no competing financial interest.
ACKNOWLEDGMENTS
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REFERENCES
We acknowledge Dr. Walter Ambrosetti (CNR-ISE), the municipality of Leggiuno, Mr. Paolo Ferretti, Centro Geophisico Prealpino, Mr. Giancarlo Bodio, and the Mainini and Anedda families (for logistic support). The Marie Curie Research Training Networks Programme under the European Commission is acknowledged for the financial support of L.N. at Lancaster University until December 2009. The Norwegian Research Council under the Yggdrasil Fellowship Program (Project No. 202813) is acknowledged for supporting R.G.'s stay in Oslo.
Figure 5. Principal component analysis of normalized values of Cpp (green) and Czoo (brown). Normalization was performed by dividing the concentration of individual congeners by the concentration of the sum of PCB congeners. Only congeners detected and quantified in all samples were included in the analysis.
alpine lakes). However, it is clear that relatively soon after the algal bloom, food intake is no longer among the key factors controlling the bulk zooplankton community concentrations. Previous studies have documented the occurrence of considerable seasonal variability of phytoplankton and zooplankton exposure and/or bioaccumulation9,30−33 and, in particular for zooplankton, related them to organism physiology and life cycle. However, so far observations were referred to yearly time scales and had lower time resolutions. In this study high variability was depicted at a higher resolution and shorter time scale as a response to short-term system trophism unsteadiness. Observed variability in concentrations and bioaccumulation metrics ranged within 1−2 orders of magnitude in the time frame of 2 months. The biological pump plays a key role in inhibiting exposure of the pelagic trophic web of Lake Maggiore. This is due to the following factors: (a) reduced dissolved-phase concentrations due to uptake onto phytoplankton, (b) enhanced export of POPs toward hypolimnion and sediments during the bloom and postbloom phases, (c) reduced concentration in biota due to rapid growth dilution, in both phytoplankton and zooplankton. These dynamics should be taken into consideration when handling or interpreting the significance of bioaccumulation metrics, especially in relationship to environmental policy implementation and monitoring, as well as for possible application in remediation actions.
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(1) Dachs, J.; Lohmann, R.; Ockenden, W. A.; Mejanelle, L.; Eisenreich, S. J.; Jones, K. C. Oceanic biogeochemical controls on global dynamics of persistent organic pollutants. Environ. Sci. Technol. 2002, 36 (20), 4229−4237. (2) Horstmann, M.; McLachlan, M. S. Atmospheric deposition of semivolatile organic compounds to two forest canopies. Atmos. Environ. 1998, 32 (10), 1799−1809. (3) Moeckel, C.; Nizzetto, L.; Di Guardo, A.; Steinnes, E.; Freppaz, M.; Filippa, G.; Camporini, P.; Benner, J.; Jones, K. C. Persistent organic pollutants in boreal and montane soil profiles: Distribution, evidence of processes and implications for global cycling. Environ. Sci. Technol. 2008, 42 (22), 8374−8380. (4) Axelman, J.; Broman, D.; Naf, C. Vertical flux and particulate/ water dynamics of polychlorinated biphenyls (PCBs) in the open Baltic Sea. Ambio 2000, 29 (4−5), 210−216. (5) Larsson, P.; Okla, L.; Cronberg, G. Turnover of polychlorinated biphenyls in an oligotrophic and an eutrophic lake in relation to internal lake processes and atmospheric fallout. Can. J. Fish. Aquat. Sci. 1998, 55 (8), 1926−1937. (6) Nizzetto, L.; Macleod, M.; Borga, K.; Cabrerizo, A.; Dachs, J.; Di Guardo, A.; Ghirardello, D.; Hansen, K. M.; Jarvis, A.; Lindroth, A.; Ludwig, B.; Monteith, D.; Perlinger, J. A.; Scheringer, M.; Schwendenmann, L.; Semple, K. T.; Wick, L. Y.; Zhang, G.; Jones, K. C. Past, present, and future controls on levels of persistent organic pollutants in the global environment. Environ. Sci. Technol. 2010, 44 (17), 6526−6531. (7) Dachs, J.; Eisenreich, S. J.; Baker, J. E.; Ko, F. C.; Jeremiason, J. D. Coupling of phytoplankton uptake and air−water exchange of persistent organic pollutants. Environ. Sci. Technol. 1999, 33 (20), 3653−3660. (8) Larsson, P.; Andersson, A.; Broman, D.; Nordback, J.; Lundberg, E. Persistent organic pollutants (POPs) in pelagic systems. Ambio 2000, 29 (4−5), 202−209. (9) Berglund, O.; Larsson, P.; Ewald, G.; Okla, L. Influence of trophic status on PCB distribution in lake sediments and biota. Environ. Pollut. 2001, 113 (2), 199−210. (10) Jurado, E.; Dachs, J., Seasonality in the “grasshopping” and atmospheric residence times of persistent organic pollutants over the oceans. Geophys. Res. Lett. 2008, 35, (17). (11) Lohmann, R.; Breivik, K.; Dachs, J.; Muir, D. Global fate of POPs: Current and future research directions. Environ. Pollut. 2007, 150 (1), 150−165. (12) Jeremiason, J. D.; Eisenreich, S. J.; Paterson, M. J. Accumulation and recycling of PCBs and PAHs in artificially eutrophied Lake 227. Can. J. Fish. Aquat. Sci. 1999, 56 (4), 650−660. (13) Jeremiason, J. D.; Eisenreich, S. J.; Paterson, M. J.; Beaty, K. G.; Hecky, R.; Elser, J. J. Biogeochemical cycling of PCBs in lakes of
ASSOCIATED CONTENT
S Supporting Information *
Figures showing Lake Maggiore and sampling locations, correlation between POC and the density of fluorescent particles, fugacity quotients between air and water for selected PCB congeners, decline of CTD of selected PCBs with time, time trends of Czoo, and log BCF, log BAF, and BMF variation with time, text describing organic carbon analysis, flow cytometry, chemical analysis, PCB concentration in the atmosphere, PCB distribution in surface water, and calculation of fugacity quotients, and tables giving OC concentrations, gasphase concentrations, concentration in the truly dissolved phase, total suspended particle concentrations, particulate concentrations of OC, meteorological conditions, and water column temperatures. This material is available free of charge via the Internet at http://pubs.acs.org. 3210
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variable trophic status: A paired-lake experiment. Limnol. Oceanogr. 1999, 44 (3), 889−902. (14) Axelman, J.; Broman, D.; Naf, C. Field measurements of PCB partitioning between water and planktonic organisms: Influence of growth, particle size, and solute−solvent interactions. Environ. Sci. Technol. 1997, 31 (3), 665−669. (15) Berrojalbiz, N.; Dachs, J.; Del Vento, S.; Ojeda, M. J.; Valle, M. C.; Castro-Jimenez, J.; Mariani, G.; Wollgast, J.; Hanke, G. Persistent organic pollutants in Mediterranean seawater and processes affecting their accumulation in plankton. Environ. Sci. Technol. 2011, 45 (10), 4315−4322. (16) Borga, K.; Kidd, K.; Muir, D. C. G.; Berglund, O.; Conder, J. M.; Gobas, F. A. P. C; Kucklick, J.; Malm, O.; Powell, D. E. Trophic magnification factors: Considerations of ecology, ecosystem and study design. Integr. Environ. Assess. Manage. 2011, in press. (17) CNR-ISE, Ricerche sull’evoluzione del Lago Maggiore. Aspetti limnologici. Programma quinquennale 2008−2012. Commissione Internazionale per la protezione delle acque italo-svizzere. 2010; 135 pp. (18) Pomati, F.; Jokela, J.; Simona, M.; Veronesi, M.; Ibelings, B. W. An automated platform for phytoplankton ecology and aquatic ecosystem monitoring. Environ. Sci. Technol. 2011, 45 (22), 9658− 9665. (19) Callieri, C. Sedimentation and aggregate dynamics in lake Maggiore, a large, deep lake in Northern Italy. Mem. Ist. Ital. Idrobiol. 1997, 56, 37−50. (20) Wetzel, R. G. Limnology; Academic Press, Elsevier Science: San Diego, CA, 2001. (21) Hawker, D. W.; Connell, D. W. Octanol−water partition coefficients of polychlorinated biphenyl congeners. Environ. Sci. Technol. 1988, 22 (4), 382−387. (22) Iwata, H.; Tanabe, S.; Sakal, N.; Tatsukawa, R. Distribution of persistent organochlorines in the air and surface seawater and the role of ocean on their global transport and fate. Environ. Sci. Technol. 1993, 27 (6), 1080−1098. (23) Mackay, D.; Shiu, W. Y.; Ma, K. C. Illustrated Handbook of Physical-Chemical Properties and Environmental Fate for Organic Chemicals; Lewis Publishers: Boca Raton, FL, 1991. (24) Dachs, J.; Eisenreich, S. J.; Hoff, R. M. Influence of eutrophication on air−water exchange, vertical fluxes, and phytoplankton concentrations of persistent organic pollutants. Environ. Sci. Technol. 2000, 34 (6), 1095−1102. (25) Sobek, A.; McLachlan, M. S.; Borga, K.; Asplund, L.; Lundstedt-Enkel, K.; Polder, A.; Gustafsson, O. A comparison of PCB bioaccumulation factors between an arctic and a temperate marine food web. Sci. Total Environ. 2010, 408 (13), 2753−2760. (26) Goss, K. U.; Schwarzenbach, R. P. Linear free energy relationships used to evaluate equilibrium partitioning of organic compounds. Environ. Sci. Technol. 2001, 35 (1), 1−9. (27) Swackhamer, D. L.; Skoglund, R. S. Bioaccumulation of PCBs by algaeKinetics versus equilibrium. Environ. Toxicol. Chem. 1993, 12 (5), 831−838. (28) Skoglund, R. S.; Swackhamer, D. L. Fate of hydrophobic organic contaminantsProcesses affecting uptake by phytoplankton. In Environmental Chemistry of Lakes and Reservoirs, Baker, L. A., Ed.; 1994; Vol. 237, pp 559−573. (29) McManus, G. B.; Wyman, K. D.; Peterson, W. T.; Wurster, C. F Factors affecting the elimination of PCBs in the marine copepod Acartia tonsa. Estuarine, Coastal Shelf Sci. 1983, 17, 421−430. (30) Hargrave, B. T.; Phillips, G. A.; Vass, W. P.; Bruecker, P.; Welch, H. E.; Siferd, T. D. Seasonality in bioaccumulation of organochlorines in lower trophic level arctic marine biota. Environ. Sci. Technol. 2000, 34 (6), 980−987. (31) Smith, K. E. C.; McLachlan, M. S. Concentrations and partitioning of polychlorinated biphenyls in the surface waters of the southern Baltic SeaSeasonal effects. Environ. Toxicol. Chem. 2006, 25 (10), 2569−2575. (32) Hallanger, I. G.; Warner, N. A.; Ruus, A.; Evenset, A.; Christensen, G.; Herzke, D.; Gabrielsen, G. W.; Borga, K. Seasonality
in contaminant accumulation in arctic marine pelagic food webs using trophic magnification factor as a measure of bioaccumulation. Environ. Toxicol. Chem. 2011, 30 (5), 1026−1035. (33) Stapleton, H. M.; Skubinna, J.; Baker, J. E. Seasonal dynamics of PCB and toxaphene bioaccumulation within a Lake Michigan food web. J. Great Lakes Res. 2002, 28 (1), 52−64.
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dx.doi.org/10.1021/es204176q | Environ. Sci. Technol. 2012, 46, 3204−3211
