Environ. Sci. Technol. 2000, 34, 1095-1102
Influence of Eutrophication on Air-Water Exchange, Vertical Fluxes, and Phytoplankton Concentrations of Persistent Organic Pollutants J O R D I D A C H S , †,‡ S T E V E N J . E I S E N R E I C H , * ,† A N D RAYMOND M. HOFF§ Department of Environmental Sciences, Rutgers University, 14 College Farm Road, New Brunswick, New Jersey 08901-8551, and Joint Center for Earth Systems Technology, University of Maryland, 1000 Hillton Circle, Baltimore, Maryland 21250
The influence of eutrophication on the biogeochemical cycles of persistent organic pollutants (POPs) such as polychlorinated biphenyls (PCBs) is largely unknown. In this paper, the application of a dynamic air-waterphytoplankton exchange model to Lake Ontario is used as a framework to study the influence of eutrophication on airwater exchange, vertical fluxes, and phytoplankton concentrations of POPs. The results of these simulations demonstrate that air-water exchange controls phytoplankton concentrations in remote aquatic environments with little influence from land-based sources of pollutants and supports levels in even historically contaminated systems. Furthermore, eutrophication or high biomass leads to a disequilibrium between the gas and dissolved phase, enhanced airwater exchange, and vertical sinking fluxes of PCBs. Increasing biomass also depletes the water concentrations leading to lower than equilibrium PCB concentrations in phytoplankton. Implications to future trends in PCB pollution in Lake Ontario are also discussed.
Introduction Eutrophication is one of the main processes affecting water quality in lakes, estuarine, and coastal areas (1). Furthermore, increasing biomass and phytoplankton growth rates influence the biogeochemical cycles of persistent organic pollutants (POPs) such as polychlorinated biphenyls (PCBs) in aquatic environments (2). For example, lower PCB concentrations in zooplankton have been observed at increased biomass due to a dilution effect (particle dilution), and it has been suggested to be also true for phytoplankton (3). Higher growth rates lead to lower PCB concentrations in the phytoplankton due to dilution by the new organic matter introduced in the ecosystem (growth dilution) (4-6). Vertical sinking of particleassociated pollutants may be enhanced by eutrophication since higher primary productivity leads to larger vertical fluxes of particles and organic carbon (7-9). Furthermore, POP * Corresponding author phone: (732)932-9588; fax: (732)932-3562; e-mail:
[email protected]. † Rutgers University. ‡ Present address: Department of Environmental Chemistry, IIQAB-CSIC, Jordi Girona 18-24, Barcelona 08034, Catalunya, Spain. § University of Maryland. 10.1021/es990759e CCC: $19.00 Published on Web 02/04/2000
2000 American Chemical Society
accumulation and sequestration by sediments is also enhanced in eutrophic environments (10, 11) by preservation of natural organic matter The influence of eutrophication on air-water exchange of POPs has received little attention. Millard et al. (7, 12) observed a decrease in the volatilization losses of PCBs when increasing biomass in model ecosystems. A similar effect has also been observed in two small lakes in the Experimental Lakes Area in western Ontario (9). Recently a model for airwater-phytoplankton exchange was developed that elucidated the interactions between air-water exchange and phytoplankton uptake (13). This model showed that airwater exchange dynamics is influenced by phytoplankton biomass and growth rate, with longer times to reach equilibrium at high biomass. These longer equilibration times are associated with the depletion of the water phase by phytoplankton uptake, thus driving air-water exchange out of equilibrium. Models predicting bioaccumulation assuming equilibrium conditions may not be realistic for hydrophobic compounds (13). Air-water exchange also influences bioaccumulation since it is the limiting step of the air-water-phytoplankton exchange process (13). Knowledge of the factors governing phytoplankton uptake is important to predict bioaccumulation in the trophic food web (14-16). The link between phytoplankton bioaccumulation and air-water exchange has been suggested by a number of observations. PCB and PAH concentration profiles observed in the water column, either in the dissolved phase or in the phytoplankton, are similar to those found in the gas phase, which suggests that airwater exchange supports and may even control the PCB concentrations in phytoplankton (9, 17). The major role of the atmospheric gas phase is further supported by the occurrence of POPs such as low chlorinated PCB congeners and low molecular weight PAHs in pristine and remote aquatic environments (9, 18, 19). The mutual influences between air-water exchange and phytoplankton uptake may have an important role on the cycling of POPs. The objectives of this paper are to evaluate the influence of eutrophication or high phytoplankton biomass on diffusive air-water exchange, vertical fluxes, and phytoplankton concentrations of persistent organic pollutants using Lake Ontario as a demonstration. PCB pollution and eutrophication have been two important issues of concern in Lake Ontario (20-23). Concentrations of PCBs in water and phytoplankton are estimated by means of a dynamic model for air-water-phytoplankton exchange. The model was first run for observed values of biomass, and subsequently, the sensitivity of biomass on air-water exchange and vertical fluxes of POPs was elucidated by running the model for a lower biomass. These simulations lead to estimates of the annual air-water and water-column vertical fluxes of POPs. Finally, the results obtained from the simulations are compared with field observations, and implications for the cycling of POPs are discussed.
Model Description and Data Sources Air-Water-Phytoplankton Exchange Model. Air-water exchange may be treated in the traditional manner (24-27), where the air-water flux (FA-W, ng m-2 d-1) is given by
(
FA-W ) kol CW -
)
CA H′
(1)
where CW and CA are the POP concentrations in water (freely dissolved phase) and air (gas phase), respectively (ng m-3), VOL. 34, NO. 6, 2000 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
9
1095
FIGURE 1. Schematic of the Lake Ontario simulations on air-water-phytoplankton exchange. H′ is the dimensionless Henry’s law constant corrected for temperature, and kol is the overall mass transfer rate between air and water (m d-1). Details on methods and correlations used for estimation of H′ and kol can be found in the above references. Phytoplankton uptake of POPs may be described as (13, 28)
dCP,M ) kuCW - kdCP,M - kGCP,M dt
(2)
where CP,M (ng kg-1) is the POP concentration in the phytoplankton matrix, ku and kd are the uptake and depuration constants, and kG is the phytoplankton growth rate. Multiplying eq 2 by phytoplankton biomass (BP, kg m-3) and dividing by the phytoplankton surface area (SP, m2 m-3), the chemical flux per square meter of plankton surface is obtained. To obtain the water-phytoplankton flux in the same units as the air-water flux over the mixing depth (eq 1), eq 2 should also be multiplied by the mixing depth (hmix, m) and SP:
FP-W ) -hmixSP
BP dCP,M SP dt
(3)
FP-W is positive when the flux is from phytoplankton to water (depuration) and negative during uptake. Equation 3 can be rewritten as
(
FP-W ) hmixkuBP CP,M
kd + kG - CW ku
)
(4)
Equation 4 gives the water-phytoplankton flux considering phytoplankton as a simple homogeneous compartment. However, experimental data suggest that phytoplankton uptake is better described by a two-compartment model (29, 30), incorporating a second set of uptake (kad) and depuration (kdes) constants for the fast first sorption step. Thus, waterphytoplankton flux of POPs is given by
(
FP-W ) hmixkadBP CP,S
1096
9
)
kdes + kG - CW + kad kd + kG hmixkuBP CP,M - CW (5) ku
(
)
ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 34, NO. 6, 2000
where CP,S (ng kg-1) is the POP concentration in the first compartment, usually identified either as phytoplankton surface or cell walls. Equations 1 and 5 describe the air-water-phytoplankton exchange. A detailed sensitivity analysis of this model is reported elsewhere (13). Briefly, the air-water exchange response times depend not only on physical variables such as wind speed and temperature but also on mixing depth, phytoplankton biomass, and growth rate. Indeed, phytoplankton uptake-induced depletion of the POP dissolvedphase concentration due to either new or high biomass drives air and water out of equilibrium, thus increasing the times to reach equilibrium between the air and water phases. Lake Ontario Modeling and Data Sources. Lake Ontario was chosen as a case study because it is a mesotrophic lake and has been heavily impacted by PCB inputs (10, 31). Thus, it provides a good example to study the potential effect of eutrophication on the biogeochemical cycles of POPs. Potential inputs and outputs of POPs in aquatic environments are wet and dry deposition, riverine inputs/outputs, airwater exchange, vertical sinking of particle-associated pollutants, transformation/degradation, and sediment accumulation and resuspension processes. Only air-water exchange and vertical sinking of particles will be considered in the present study. These two processes are known to play an important role in the biogeochemical cycles of POPs such as PCBs (9, 24, 26, 32, 33) and are influenced by trophic status (13). Settling of particles has a major role as a removal mechanism of PCBs from surface waters. PCBs are hydrophobic and, thus, are incorporated into large limnic and marine aggregates rich in organic matter such as fecal pellets and marine snow (32-34). In Lake Ontario, the vertical fluxes of organic carbon and PCBs are particularly important near tributaries such as the Niagara River but less so in open waters (20, 35). However air-water exchange is a major source of PCBs to Lake Ontario, being more important than wet and dry deposition (36). This simplified scenario in which water and phytoplankton concentrations are controlled by airwater exchange and vertical sinking of particles may be representative of open Lake Ontario waters as well as coastal and open seas. Figure 1 shows the processes considered in this study. Simulations of Lake Ontario were performed for a hypothethical site in open waters, without direct influence of tributary inputs and resuspension processes. We assume that
TABLE 1. Physical-Chemical Properties of the PCB Congeners Used in the Simulations of the Present Studya
PCB congener 31 (2,4′,5) 52 (2,2′,5,5′) 101 (2,2′,4,5,5′) 153 (2,2′,4,4′,5,5′) 187 (2,2′,3,4′,5,5′,6)
H298 × 104 (atm m3 ku (m3 kd ksa (m3 ksd mol-1) kg-1 d-1) (d-1) kg-1 d-1) (d-1) 2 2 0.9 0.24 0.1
98.2 402.5 1559 2474 1298
0.74 55770 287.6 0.89 82608 287.6 1.15 121044 287.6 1.08 110039 287.6 0.53 81668 287.6
a Henry’s law constants were obtained from Brunner et al. (58). Phytoplankton uptake parameters were obtained from Ko (59).
the atmospheric gas phase supports the PCB water and phytoplankton concentrations, while vertical sinking of particle-associated pollutants is the major removal process of PCBs from surface waters. These assumptions are consistent with a number of studies that examine the role of atmospheric inputs and air-water exchange as controls on the long-term dynamics of PCBs in the Great Lakes (36). Equations 2 and 5 give the air-water and water-phytoplankton fluxes per square meter of air-water interface, respectively. Furthermore, only surficial waters are considered since this is the part of the water column under direct influence of the atmosphere. The simulations were performed over an annual cycle so that seasonal variations of PCBs (36-38) may be incorporated. PCB concentrations measured at Point Petre, on the northeast shore of Lake Ontario, as part of the Integrated Atmospheric Network (IADN) were used. The simulations were performed for 1994 (January 1-December 31). Congener-specific simulations for PCB 31 (2,4′,5 trichlorobiphenyl), 52 (2,2′,5,5′ tetrachlorobiphenyl), 101 (2,2′,4,5,5′ pentachlorobiphenyl), 153 (2,2′,4,4′,5,5′ hexachlorobiphenyl), and 187 (2,2′,3,4′,5,5′,6 heptachlorobiphenyl) were performed in order to asses the role of the physical-chemical properties such as Henry’s law constants, phytoplankton uptake, and depuration constants on the system. These selected congeners account for an important fraction (13-17%) of the total PCB profiles in the regional Great Lakes atmosphere and water column (23, 37) and are representative of POPs with a wide range of physical-chemical properties. Uptake and depurations constants, Henry’s law constants and other physicalchemical properties used in the simulations are summarized in Table 1. Temporal trends of gas-phase PCB concentrations, in addition to the seasonal variability, show important variability at daily to weekly time scales due to fluctuation in temperature and wind direction (37, 38). To account for these shortterm fluctuations, simulation of phytoplankton growth and sinking and changing mixing depth at the same time scale are desirable. This approach would complicate the study of the effect of eutrophication on air-water exchange and phytoplankton uptake, and data are insufficient for such an approach. Furthermore, we are interested in the effects of eutrophication on air-water exchange at mid- and longterm, since this will demonstrate the effect of these processes on the fate and global biogeochemical cycles of PCBs and other POPs in aquatic environments (31, 39). Figure 2 shows the annual atmospheric cycle for the five PCB congeners used in the simulations of Lake Ontario. PCB concentrations increase slowly from winter to late spring, exhibit a maxima in summer, and then decrease to the winter values throughout the fall. Seasonal average and range of PCB congeneric gasphase concentrations were used (36). Considering the congener-specific concentrations in this way maintains the seasonal and annual averages while avoiding short-term variability (36-38).
FIGURE 2. Annual cycle of atmospheric concentrations for the PCB congeners PCB 31 (2,4′,5-trichlorobiphenyl), 52 (2,2′,5,5′-tetrachlorobiphenyl), 101 (2,2′,4,5,5′-pentachlorobiphenyl), 153 (2,2′,4,4′,5,5′hexachlorobiphenyl), and 187 (2,2′,3,4′,5,5′,6-heptachlorobiphenyl) observed at Point Petre, ON (based on ref 36).
FIGURE 3. Biomass, vertical flux of particulate matter, and temperature used for the Lake Ontario simulations. Phytoplankton productivity and biomass in Lake Ontario undergoes both seasonal and interannual variability (40, 41). Observed chlorophyll a concentrations in Lake Ontario (40) were corrected using the ratio of carbon/chlorophyll a reported by Parssons et al. (42). The obtained values were used as phytoplankton biomass in the simulations (Figure 3). Sinking fluxes have decreased during the past decade due to a decrease in productivity; therefore, sinking fluxes (FSetling, kg m-2 d-1) were estimated from the lower values of measured sediment trap fluxes reported by Charlton (35) and Oliver et al. (20) as representative of the sinking particulate fluxes during the high productivity seasons. Sinking fluxes for the rest of the year were assumed to be proportionally lower. Growth rate constants were estimated from the biomass and the sinking rates assuming that phytoplankton accounts for all the sinking material reported in Figure 3. Thus kG at time t is given by
kG )
[
(
FSetling 1 B - BP,t 1 BP,t P,t+dt BP,thmix
)]
(6)
where BP,t and BP,t+dt are the simulated biomass at time t and t + dt, respectively. Epilimnium mixed depths ranged from 10 m during stratification to 50 m during the fall turnover and are close to the prevalent hydrodynamics of the lake (43). Linear interpolation was applied between experimental measurements. Since the above estimates for biomass, sinking fluxes, and mixing depth are taken from the literature, they are representative of the real values, and the error may not be higher than a factor of 2. Furthermore, the biomass numbers estimated from chlorophyll a are very close (error
