Environ. Sci. Technol. 2005, 39, 7185-7193
Does the Forest Filter Effect Prevent Semivolatile Organic Compounds from Reaching the Arctic? YUSHAN SU AND FRANK WANIA* Department of Chemical Engineering and Applied Chemistry and Department of Physical and Environmental Sciences, University of Toronto at Scarborough, 1265 Military Trail, Toronto, Ontario, Canada M1C 1A4
Forests act as efficient filters for many airborne semivolatile organic compounds (SOCs). However, most simulations of an organic chemical’s long-range transport in the atmosphere do not account for this filter effect. In this study, forests are introduced into an existing zonally averaged global distribution model (Globo-POP) to investigate how such a change affects a chemical’s potential to undergo long range transport and accumulation in the Arctic, as quantified by the Arctic contamination potential (ACP). Simulation results indicate that the ACP of a “space” of perfectly persistent hypothetical organic chemicals, defined by log KOA and log KAW, is reduced by introducing forests in the global model. Depending on partition characteristics, this reduction can be as large as a factor of 2. Model calculations also indicate that it is mostly the boreal forests, specifically boreal deciduous forests, which play a key role in this respect. Sensitivity analyses establish the deposition velocity to boreal forests, especially for gaseous compounds, as one of the most influential parameters controlling this global forest filter effect. The extent of the effect is further sensitive to the forest density and precipitation rate in the boreal zone, and the degradation rates of the chemical. Specifically, degradation in the forest canopy may enhance the effect and further reduce an SOC’s long range transport to remote regions. Simulations for three PCB congeners suggest that forests may reduce concentrations in air, ocean, and freshwater at the expense of increased concentrations in forest soils and may lead to substantially increased overall global residence times.
Introduction It is becoming apparent that forests play an important role in the environmental fate of many semivolatile organic compounds (SOCs). Forest soil regularly exhibits higher concentrations of SOCs than nearby nonforest soil (1-3), which is believed to relate to elevated atmospheric deposition to the forest canopy (4, 5). Quantitatively examining the atmospheric deposition of SOCs to deciduous and coniferous forests in Bayreuth, Germany, Horstmann and McLachlan (6) observed that deposition of almost all SOCs was higher under the canopies than in a nearby clearing. Building on the result of their field study, they then used a mathematical model to identify the physical-chemical partitioning proper* Corresponding author
[email protected]. 10.1021/es0481979 CCC: $30.25 Published on Web 08/16/2005
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(416)287-7225;
2005 American Chemical Society
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ties, which result in a pronounced filtering effect (7). The “window” of partition property combinations yielding the highest forest filter effect includes SOCs with an octanol-air partition coefficient (log KOA) between 7 and 11 and an airwater partition coefficient (log KAW) above -6. Wania and McLachlan (8) included a canopy compartment into an existing fugacity-based non-steady-state multimedia fate model (CoZMo-POP), parametrizing it on the basis of the German field study (6). The modeling results indicated that within the forest filter window, the efficient uptake in forest can lead to substantially lowered air and water concentrations of SOCs with 9 < log KOA < 10 and -3 < log KAW < -2. Such SOCs are efficiently deposited to the forest during the spring and summer when deciduous forest canopies have their highest uptake capacity, and unstable atmospheric conditions increase the rate of deposition. A regional multimedia model of Northern Europe also showed an important role of forests in the distribution, transport, and fate of hexachlorocyclohexanes (9, 10). Using the CoZMo-POP model and a simplified description of global forests, MacLeod (11) predicted that forests reduce air concentration only up to a factor of 1.35. He suggested that the forest filter effect is much smaller on a global scale because of the large area covered by oceans. Relying on the CliMoChem model, Wegmann et al. (12) pointed out that global vegetation and high soil organic carbon (OC) content contribute to reduce northbound transport of DDT from source regions at lower latitudes. Responding to an increasing interest in the forest filter effect for SOCs, a forum in Stochastic Environmental Research and Risk Assessment (SERRA) recently debated this issue in detail (13). The potential of organic chemicals for long-range transport and deposition in remote regions can be investigated by calculating an Arctic contamination potential (ACP) (14). Relying on Globo-POP, a zonally averaged global multimedia fate model, the ACP relates the amount of a chemical in the northernmost zone of that model, that is, the Arctic, with the total globally emitted amount. Wania (14) calculated the ACP for a “space” of perfectly persistent organic chemicals of variable, but hypothetical, partitioning property combinations. Among the chemicals with high ACPs are “semivolatile and relatively hydrophobic” substances (14). Interestingly, the part of the chemical partitioning space showing high ACP values overlaps with the forest filter window (7, 8). This led to the question whether the “boreal forests of the northern hemisphere, in particular, could be an important filter for compounds moving north that are still gaseous at these latitudes but which condense onto particles and are deposited in the colder polar air” (8). Wania and McLachlan (8) further suggested that the “addition of a forest compartment [...] into existing models of the global fate of SOCs will present a possibility to evaluate the nature and extent of the impact of forests on the global partitioning processes of SOCs.” This current study is a first attempt in this direction. Forest compartments are included into the Globo-POP model, and the results of simulation scenarios with and without forests are compared.
Methods Globo-POP is a fugacity-based non-steady-state multimedia fate model of the global environment. Ten climate zones are each composed of four vertical atmospheric layers, different types of soil (i.e., agricultural and uncultivated soil), freshwater, freshwater sediment, and the surface ocean. Chemical fugacities, amounts and concentrations in these media, and chemical fluxes between them are computed by solving a set VOL. 39, NO. 18, 2005 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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TABLE 1. Forest Compartments and Respective Relative Coverage in Seven Climate Zones of the Zonally Averaged Globo-POP Model zone N-boreal N-temperate N-subtropic N-tropic S-tropic S-subtropic S-temperate
forest type and coverage in percent of terrestrial surface coniferous (51.4%) coniferous (15.5%) high-density deciduous (12.7%) evergreen forest (24.8%) evergreen forest (33.8%) high-density deciduous (10.5%) coniferous (8.3%)
of differential equations, if chemical partitioning and degradation properties and historical global emission estimates are provided. Chemicals can be permanently lost through degradation in all media, sediment burial in freshwater, and transfer to the deep sea. A detailed description of the model can be found elsewhere (15-17). Several previous modifications are explained by Wania and Daly (18), whereas the changes introduced for the current study are described below. The description of forests in Globo-POP follows the approach described by Wania and McLachlan (8) for CoZMo-POP, except that coniferous and deciduous canopies are no longer bulked. Instead, separate compartments and thus mass balance equations are defined for specific forest types. Briefly, chemical input to the forest compartments occurs through direct emission (EF) and atmospheric deposition (DAF), whereas chemicals are lost from the forest canopies by evaporation (DFA), leaves falling to the ground (DFB), and degradation (DRF). No chemical uptake or transport from forest soil to the canopy is considered because of the hydrophobic characteristics of the chemicals of primary interest. In fugacity terms, the mass balance equation for the forest canopy is expressed as follows:
d(VF‚ZF‚fF)/dt ) EF + DAF‚fA - (DRF + DFA + DFB)‚fF (1) where fA and fF are the fugacity in air and forest canopy, respectively, ZF is the fugacity capacity of the forest canopy, and t is time. For details on the derivation of the D-values and ZF, see ref 8. For a given type of forest canopy, ZF is only a function of the temperature-dependent KOA. Field observations suggest that ZF for coniferous needles increases with increasing needle age (19, 20) and also changes seasonally (20), possibly related to the production of new epicuticular waxes. The increase of ZF from one needle year to the next is not relevant in the current study, as a complete canopy comprised of all needle year classes is represented by one average ZF value. Introducing seasonal variability of ZF could improve the model by explicitly describing the production and erosion of wax materials; however, this modification would only affect the forest filter effect for those chemicals that approach or establish equilibrium during the life span of the needles. Moreover, further studies are required to fully understand this process quantitatively. The world’s forests differ widely in character. Large differences exist, for example, in terms of the density of the canopy, from very thin marginal forests at the Northern tree line to lush multi-story rain forests in the tropics. Some forest canopies experience dramatic seasonal changes, whereas others have a similar appearance year-round. There are also large differences in the relative abundance of deciduous and coniferous trees, or in terms of the organic carbon content of the forest soils (21). Many of these characteristics will influence SOC uptake in a forest. For example, the deposition velocity of SOCs to a deciduous canopy in Germany was much higher than that to a coniferous one (6). This suggests that it is necessary to distinguish different forest types in a global model. In the interest of simplicity, however, the number of forest compartments should be kept to a 7186
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low-density deciduous (30.1%) high-density deciduous (9.9%) low-density deciduous (6.9%) low-density deciduous (20.8%) low-density deciduous (35.8%) low-density deciduous (13.0%) high-density deciduous (22.2%)
minimum. On the basis of the work by Horstmann and McLachlan (6), forest density and tree type (deciduous vs coniferous) would be expected to have the largest impact on SOC uptake. Therefore, the model distinguishes four categories of forests that differ in terms of density and tree type: (i) coniferous forests, (ii) high-density deciduous forests, (iii) low-density deciduous forests, and (iv) evergreen forest. Because of very little forest coverage in the N-polar zone and the complete absence of forests in the S-subpolar and S-polar zones, forest compartments only need to be added to seven climate zones. Each of these seven climate zones includes two (out of these four) types of forests. The spatial extension of these forests in the various model zones was derived with the help of a global GIS data set (22), which distinguishes 15 types of surface cover (see Table S1), six of which are forests, forest and woodland, high latitude deciduous, coniferous forest and woodland, mixed coniferous/broadleaf deciduous, broadleaf deciduous, and broadleaf evergreen forest. Relative coverage of these six types of forest in various zones of the global model environment is listed in Table S1 in the Supporting Information. The six forest types from the surface cover database were allocated to one of the two designated forest compartments in each of seven zones using the approach outlined in Table S2. Table 1 shows the aggregated relative coverage for the forest compartments in different zones of the Globo-POP model. Parametrizing the forest compartments requires the definition of various input parameters to describe the SOC uptake characteristics of the 14 forests in Globo-POP. This is a considerable challenge, as empirical data on the uptake capacity and kinetics only exist for temperate forests. It is thus necessary to extrapolate the measured values for temperate forests to those of other climates. In the following, we describe how this was done. Extrapolation of the Partitioning Properties of the Forest Canopy. Chemical distribution between air and forest canopy is described through an equilibrium distribution coefficient KFA (8). Two different regression equations between KFA and KOA are available for deciduous and coniferous forests (6). These regression equations are applied to describe the partitioning characteristics of all deciduous and coniferous global forests. Assuming that evergreen forests share greater similarity with deciduous than with coniferous forests, the regression equation for deciduous forests is also used to approximate the distribution properties of evergreen forests. The KFA value of various deciduous and evergreen forest compartments thus differs only because of the different temperature in various zones. The effect of temperature is taken into account through its effect on KOA. Extrapolation of Forest Canopy Size. The uptake capacity of a forest canopy is strongly dependent on its size, which is expressed in the model using a specific canopy volume in m3 forest canopy per m2 ground area. However, so far only very few measurements of specific canopy volume exist. Measurements in Bayreuth, Germany, recorded values of 0.0012 m3/m2 for a deciduous canopy and 0.00034 m3/m2 for a coniferous canopy during fall (6). Data of the leaf area
TABLE 2. Estimated Leaf Thickness of Deciduous and Coniferous Forest specific canopy volume in 10-3 m3/m2 maximum LAI in m2/m2 leaf thickness in millimeters a
deciduous
coniferous
1.2a
1.7 [5 yr‚0.34‚10-3 m3/(m2‚yr)]a 4.59 0.37
4.27 0.28
Measured in Bayreuth, Germany (6).
index (LAI) in unit of m2 leaf surface per m2 ground area are much more common and are available on a spatially and monthly resolved basis (22). It should thus be possible to extrapolate the specific canopy volumes measured in Bayreuth to all forest compartments by converting twodimensional LAIs into three-dimensional specific canopy volumes. This requires knowledge of the thickness of leaves, which is quite variable and not easily obtained for different types of vegetation. As a first approximation, we derived a typical leaf thickness for deciduous and coniferous forests from the canopy volumes reported for Bayreuth and the LAI data for N-temperate forests. We took into account that the LAI only refers to one side of a leaf (23). Horstmann and McLachlan (6) measured the specific volumes for the deciduous canopy by collecting the leaves on ground level during fall. It was assumed that nearly all of the deciduous leaves that had developed during a whole year were falling to the ground at that time. Therefore, the maximum LAI reported for a year is needed to estimate a leaf thickness for deciduous trees. Coniferous needles were assumed to have a lifetime of 5 years. The derived “typical” leaf thickness for different types of forest is listed in Table 2. These values, in the range of a few millimeters, appear not unreasonable. In particular, the thickness of coniferous foliage is expected to be slightly higher than that of deciduous foliage. These two thickness values were applied throughout the global forests to derive seasonally variable, specific canopy volumes from monthly resolved LAI data (spatially averaged for the 14 forest compartments using GIS). The estimated seasonally resolved specific canopy volumes for 12 different forests, together with the measured ones for the other two forests, are listed in Table S3. Extrapolation of Deposition Velocities. The deposition velocities for gases and particles are controlling the rate of chemical uptake in the forest canopy. Measurements quantifying chemical exchange processes between the atmosphere and forests are very limited. In fact, again only one set of deposition velocities for organic contaminants to deciduous and coniferous forests has been reported (6). The measured high deposition velocities of selected SOCs to a deciduous forest suggest that chemical resistance on the air side is much more important than that on the canopy side (i.e., cuticle resistance). The same is the case for the deposition of some inorganic chemicals (e.g., HNO3). A multiple resistance analogy approach has been developed to model inorganic chemical deposition to vegetation (24, 25). Good agreement between field measurements and model predictions was found for several inorganic chemicals (26, 27), suggesting that this model may serve to extrapolate the measured deposition velocities of SOCs by Horstmann and McLachlan (6) to other global forests. The model expressions developed for quantifying dry deposition of inorganic chemicals to forests, in combination with meteorological and forest surface roughness data (22), were therefore used to deduce deposition velocities to the 12 remaining forests. For details of the extrapolation method, refer to Tables S4 and S5 in the Supporting Information. The deposition velocities for all forest compartments are summarized in Table 3.
Forest Soils. Additional forest soil compartments, one for each forest canopy, were introduced to the model. The surface coverage of the uncultivated soils (15) was reduced accordingly. Whereas a uniform soil depth of 10 cm was assumed to apply to all forest soils, they were allowed to vary in organic carbon (OC) content. An average OC content for each of the 14 forest soils was derived from global soil data (21). Because of the shielding effect of the forest canopy, chemical deposition of both gaseous and particle-bound SOC from the atmosphere to forest soils is assumed to be slower than deposition to a nonforested soil by a factor of 5 (8). Meanwhile, wet deposition of chemical to forests by rainwater is split into two parts: one part is intercepted by the canopy, and another part is deposited to forest soil directly (8). The maximum interception factor by forest canopy used in this current study is 0.35. It was assumed that the interception varies with seasons depending on forest density, that is, is linearly related to the specific canopy volume. Temperatures. In addition to the changes related to forests, the model was also changed in one other respect. A separate temperature was defined for the terrestrial compartments instead of applying the zonally averaged air temperature of the lowest air compartment. Therefore, global temperature data (22) were allocated to the terrestrial and marine section of each zone using ArcView and were then averaged to generate individual monthly temperature data. A separate terrestrial temperature better reflects the seasonal variation on the continents and has much larger seasonal amplitudes. A zonally averaged air temperature, on the other hand, is more reflective of marine conditions because of the relatively large fraction of the globe that is ocean-covered. The temperature of the terrestrial environment is one of the most important factors influencing air-surface exchange of SOCs on the continents and should thus be of particular concern in a study of the effect of forest on atmospheric long-range transport. The Arctic contamination potential (eACP) is defined as the percentage of the total amount of chemical emitted globally that is present in the Arctic surface media (28). The definition of the ACP adopted here is slightly different from the one used previously (mACP), which was the percentage of the total amount of chemical accumulated in the global environment that is present in the Arctic surface media (14). eACP and mACP are nearly identical for perfectly persistent chemicals except that the eACP has slightly smaller values than mACP for the same substance because chemical can be permanently removed from the environment by sediment burial and deep sea transfer. eACP values for degradable chemicals are smaller than their mACPs because of chemical loss by degradations in various media (28). The ACP is an indicator of long-range transport, which takes into account the effect of spatially and seasonally variable temperature on chemical partitioning and degradation. Chemicals can reach the Arctic environment by both atmospheric and oceanic currents. If a generic emission scenario (e.g., a constant emission rate distributed spatially according to the world’s human population) is used, different chemicals can be compared in terms of their potential to reach and accumulate in the Arctic. Depending on the length of this hypothetical continuous emission (1 vs 10 years), an immediate and a long-term long-range transport potential can be distinguished (14). The mode of emission is an important factor influencing the long-range transport of substances. If directly emitted into the atmosphere, chemicals generally have higher eACP values than if emitted to water and soil (14). The effect of forests on a chemical’s long-range transport is expected to be most pronounced if emissions occur into air, and this mode of emission is thus applied in this study. The Chemical Partitioning Space. For perfectly persistent chemicals, the only chemical-specific input parameters VOL. 39, NO. 18, 2005 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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TABLE 3. Extrapolated Deposition Velocities in Different Global Forest Compartments deposition velocity (cm/s) zone N-boreal N-temperate N-subtropic N-tropic S-tropic S-subtropic S-temperate a
forest type
dry gaseous
dry particle-bound
coniferous low-density deciduous coniferous high-density deciduous high-density deciduous low-density deciduous evergreen forest low-density deciduous evergreen forest low-density deciduous high-density deciduous low-density deciduous coniferous high-density deciduous
0.83 4.52 0.78a 3.60a 4.32 2.46 3.48 1.01 3.38 1.67 4.75 2.47 0.75 1.66
0.06 0.89 0.05a 0.73a 0.89 0.60 0.65 0.25 0.63 0.41 0.99 0.60 0.04 0.33
Measured in Bayreuth, Germany (6).
FIGURE 1. Immediate and long-term Arctic contamination potential, eACP1 and eACP10, calculated using the Globo-POP model without (A,B) and with global forests (C,D) for hypothetical chemicals of variable partitioning properties KAW and KOA. The panels on the right display the quotient Q of the ACP values calculated without and with forests (E,F). required by Globo-POP are the partitioning coefficients between octanol, water, and air (KOW, KAW, KOA). If it is assumed that KOW can be approximated by KOA‚KAW, and that default values can be used to describe the temperature dependence of partitioning, the eACP can be calculated for hypothetical combinations of KAW and KOA. This allows the illustration of eACP results in two-dimensional maps defined by these two partition coefficients (14). Here, we calculate maps of the eACP1 and eACP10 for perfectly persistent chemicals for the part of the chemical space, in which forest was previously shown to significantly impact air concentrations, that is, 7 < log KOA< 12 and -4 < log KAW < 0 (8). Specifically, we contrast maps obtained with the Globo-POP with and without accounting for the effect of global forests. In a second step, we investigate how a chemical’s degradation in all media, specifically in the forest canopy, modulates the effect of forests on the eACP. Finally, we explore how forests impact on the historical global fate of three real SOCs.
Results and Discussion Figure 1 displays the immediate eACP1 and the long-term eACP10 calculated by Globo-POP with and without forest compartments for perfectly persistent chemicals as a function 7188
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of log KOA and log KAW at 25 °C (Figure 1A-D). A red/orange color in these maps represents partitioning properties that lead to a high potential for long-range transport and accumulation in the Arctic environment, whereas a green color indicates a low potential. Chemicals that are semivolatile (7 < log KOA < 10) and relatively hydrophobic (log KAW > -4) have larger eACP. To better illustrate the effect of forests on the eACP, we calculate the ratio Q of the eACP values without and with forest. A Q of 1 implies that the introduction of forests in the model has no effect on the calculated eACP, whereas a Q larger than 1 indicates that the forests reduce the chemical amount transferred to the Arctic. Q can thus serve as a quantitative measure of the forest filter effect. Q values are calculated separately for eACP1 and eACP10 and are plotted in Figure 1E and F, again as a function of log KOA and log KAW at 25 °C. A dark brown/red color indicates a large Q value or strong filter effect, and a green color indicates a minor effect. The eACP1 without forests ranges from 0.6 to 1.3 (Figure 1A), and the eACP10 without forests adopts higher values up to 4 after 10 years of steady emission, which indicates that transport and deposition of most chemicals to the Arctic take longer than 1 year (Figure 1B). Figure 1A and B is quite
similar to Figure 4A and D in Wania (14). Slight differences stem from two factors: (i) As discussed above, the eACP calculated in this study is slightly smaller than the mACP, and (ii) the separate definition of marine and terrestrial temperatures results in a stronger seasonal temperature variation on the continents than was present in the temperature dataset used previously. Whereas this results in somewhat reduced long-range transport in the short term, that is, lower eACP1 values, no significant difference is found for the eACP10. After forests are introduced to Globo-POP, the calculated eACP1 (Figure 1C) and eACP10 (Figure 1D) values are consistently lower, although the extent of reduction is different for different partitioning property combinations. The maximum Q for eACP1 is 2.2 and occurs for semivolatile (9 < log KOA < 11), but not very water-soluble chemicals (log KAW > -2) (Figure 1E). The effect on eACP10 is relatively smaller, with a maximum reduction by a factor of around 1.6 (Figure 1F). These results indicate that forests play an important role in reducing a chemical’s long-range transport to the Arctic. Common Arctic contaminants, such as some PCBs, typically lie in this forest filter window. The results of the model calculations suggest that the concentrations of these SOCs in Arctic ecosystems would be higher than they actually are by as much as a factor of 2, if it were not for the filtering effect of the world’s forests. This suggests that the Arctic ecosystem benefits from the forest filter effect. The pattern in Figure 1E and F is similar to the “forest filter window” presented previously (7, 8). The highest reduction of eACP occurs in the range of log KOA from 9 to 11 and log KAW from -4 to 0. However, a closer look reveals that the crest with the highest filter effect in Figure 1E and F occurs at a log KOA around 10.0, which is slightly higher than the log KOA of maximum air concentration reduction noted by Wania and McLachlan (8), which was around 9.5. This is related to the large role boreal forests play in the global forest filter effect (see below). Temperatures in the boreal region are relatively low, and KOA is strongly temperature dependent. The annual and 6-month summer average temperatures are -5 and 4 °C in the boreal zone as compared to 5 and 12 °C in the temperate zone. A 10 °C difference in temperature can easily result in a KOA change by half an order of magnitude. The original calculation on the forest filter effect with the CoZMo-POP model was done using temperate conditions (8). We note that the effect of forests on the eACP is smaller than the effect on summer time air concentrations reported in the previous study (8), which was up to a factor of 5. This can be explained by the smaller forest coverage on a global scale. Although global forests cover approximately 40% of the entire terrestrial surface, overall forest coverage globally is only about 12%, because 70% of the earth surface is covered with oceans. This overall forest coverage is much smaller than in the hypothetical region used by Wania and McLachlan (8), which only had 20% water and 50% of the terrestrial area was forest-covered (i.e., overall 40% forest coverage). A sensitivity analysis in the previous study had also shown a significant influence of forest coverage (8). Therefore, it is not surprising to obtain a lower forest filter effect on a global scale. MacLeod (11) also estimated a relatively lower reduction of air concentrations (i.e., by a factor of 1.35) by global forests and explained it by the relatively small global forest coverage. We should stress here the limitation of a zonally averaged approach to quantifying the global forest filter effect. In particular, we suspect that the real global forest filter effect may be higher than estimated here, because our approach neglects to account for the relative spatial arrangement of SOC source regions and forested areas. Both SOC source regions and forests are located on the continents and are thus in closer spatial proximity than a zonally averaged approach would imply. It may for example be of relevance
that the Siberian forests may lie “downwind” of major source regions in Europe and Russia. In any case, a reduction of the ACP by as large as a factor of 2 is substantial when seen in the context of the sensitivity the ACP displayed to a variety of environmental input parameters (14). Which Forests Reduce the Arctic Accumulation of SOCs? A total of 14 forest compartments are included in the GloboPOP model, and results show that these forests have the potential to reduce a SOC’s long-range transport. However, which forests are responsible for this reduction? The boreal forests are located between the sources of contaminants, which are predominantly in mid and low latitudes, and the Arctic environment. A series of simulations were performed to elucidate whether it is primarily the boreal forest or the entire global forest that is important in this regard. The first simulation was performed with Globo-POP including only the two forests in the Boreal, whereas the second simulation included all forests except the two boreal forests. The results are expressed quantitatively by displaying Q values in a chemical space plot (Figure 2B and C). For easy comparison, Figure 2 also includes the results obtained with all 14 global forests (Figure 2A). The Q values in Figure 2B are higher for more partitioning property combinations than those in Figure 2C, which suggests that boreal forests are most important in reducing a SOC’s long-range transport to the Arctic. Apart from the location between source and receptor, other factors contribute to the strong effect of the boreal forests. Specifically, high forest coverage (e.g., 30.1 % deciduous and 51.4 % coniferous forest), relatively low temperatures, and a higher surface roughness facilitate SOC uptake by forests in this area. This is also reflected in relatively high extrapolated deposition velocities in both kinds of boreal forests (see Table 1). Two additional simulations were performed with either boreal deciduous forests only (Figure 2D) or boreal coniferous forests only (Figure 2E). Figure 2D is much more similar to Figure 2B than is Figure 2E, which suggests that boreal deciduous forests play a more important role in reducing the eACP10 than the boreal coniferous forests. Deciduous forest canopies in the Boreal undergo strong seasonal changes. Leaves develop during the spring and completely fall to the ground in the fall. SOCs are being efficiently deposited to a dense deciduous forest canopy during summer when the atmosphere is relatively unstable, which makes for efficient deposition of SOCs. Averaged of an entire year, SOCs are transferred from the atmosphere to the forest soil more quickly and more efficiently by deciduous than by coniferous forest. Although the relative surface coverage of boreal deciduous forests (30.1%) is smaller than that of coniferous forest (51.4%), the higher deposition velocity to deciduous forest leads to a higher filter effect overall. Which Parameters Are Most Important for Describing SOC Uptake in Boreal Forests? The simulations above have shown that the boreal forests, especially deciduous ones, reduce the extent to which SOCs are reaching the Arctic region. The parameters used for describing the forests in the Boreal are extrapolated on the basis of measurements in Germany (6). There is considerable uncertainty associated with such an extrapolation. It is therefore worthwhile to identify which parameters are most influential for the model output, and therefore would need to be known accurately, if progress on quantifying the effect of forests on Arctic contaminant accumulation is to be achieved. PCB-180, with a log KOA of 10.2 and a log KAW of -2.5 (29), falls within the part of the “forest filter window” with the largest predicted effect of forests on the eACP10 (refer to Figure 1E and F). It should thus be well suited for testing the sensitivity of the model results to the various parameters describing boreal forests, including gaseous deposition velocity, particle-bound deposition velocity, forest canopy volume, precipitation rate, VOL. 39, NO. 18, 2005 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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FIGURE 2. The quotient Q of the long-term Arctic contamination potential (eACP10) calculated without and with five different scenarios involving forests for hypothetical chemicals of variable partitioning properties KAW and KOA.
TABLE 4. Percentage Change of the Q-Values for the eACP1 and eACP10 of PCB Congener 180 upon a 10% Change in Different Model Input Parameters Describing Boreal Forests forest parameters
Q for eACP1
Q for eACP10
gaseous deposition velocity particle-bound deposition velocity specific canopy volume precipitation rate depth of forest soil organic carbon in forest soil
1.8% 0.1% 0.2% 0.7% 0% 0%
1.5% 0.1% 0.2% 0.8% 0% 0%
(Q - Qref)/Qref (X - Xref)/Xref
)
(Q - Qref)/Qref 10%
(2)
The results reveal that Q for PCB-180, initially assumed to be perfectly persistent, is very sensitive to the deposition velocities, specifically for gas-phase chemicals. Q for eACP10 increases by 1.5% if the gaseous deposition velocity to boreal forests is increased by 10%. This indicates that measured SOC deposition velocities to various forest canopies, especially in boreal forests, are required for a better quantitative understanding of the forest filter effect on a global scale. The specific canopy volume and precipitation rate in the boreal deciduous forest are also influential parameters. On the other hand, Q values for PCB-180 were not sensitive to either forest soil depth or the organic carbon content of forest soil, presumably because of the big uptake capacity of boreal forest soil for such chemicals. Effect of Degradation in Forest Canopy and Other Compartments. All results presented so far apply to perfectly persistent chemicals; that is, degradation is not being considered. Yet some SOCs can degrade by photolytic or biological reactions in the forest canopy, which may enhance the forest filter effect to a certain extent. For example, there 7190
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Degradation Properties of PCB-180 at 25 °C half-life (103 h) activation energy (kJ/mol) air
soil
water
sediment
Eair
Esoil
Ewater
Esed
3.84
1000
55
170
10
30
30
30
Enhancement of the Global Forest Filter Effect by Degradation simulation half-life in forest Q for eACP1 Q for eACP10
forest soil depth, and organic carbon content in forest soil. Sensitivity (SX) is defined here as the relative change in model output (i.e., Q values) in response to a relative change in one of these input parameters. The input parameters in this study were individually increased by 10%, and the respective sensitivities SX are listed in Table 4.
Sx )
TABLE 5. Degradation Properties of PCB-180 (ref 18) and Enhancement Effect of Degradation in Forest Canopy on the Global Forest Filter Effect
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case 1 case 2 case 3
infinite half-lifeair half-lifesoil
1.05 1.06 1.05
1.09 1.19 1.09
is experimental evidence of the degradation of dioxins and DDT-related compounds in vegetation (30-32). This is difficult to investigate quantitatively because there are virtually no measurements or quantitative estimates of the degradation half-life of SOCs in the forest canopy. To nevertheless evaluate the effect of degradation in the forest canopy on the global forest filter effect, scenarios with different assumptions concerning the degradation half-lifes of PCB-180 in forests were performed. (i) The half-life in the forest canopy is infinite, (ii) the half-life in the forest canopy is equal to that in air, and (iii) the half-life in the forest canopy is the same as that in soil. Degradation half-lives of PCB-180 assumed to apply in air, water, soil, and sediment are listed in Table 5. The quotient of “Q of degradable PCB-180” divided by “Q of perfectly persistent PCB-180” indicates to what extent degradation in the forest canopy enhances the global forest filter effect and further reduces SOCs reaching the Arctic. A value of 1 for this quotient implies no such enhancement effect. The results of the three different simulations are listed in the lower half of Table 5. Considering degradation in all media except for the forest canopy (case 1), the forest filter effect for PCB-180 is enhanced by 5% and 9% after 1 and 10 years of steady emission, respectively. Degradation in air alone is responsible for increasing the forest filter effect by 4% and 7%, respectively (not listed in Table 5). This implies that the forest filter effect for PCB-180 is enhanced by degradation
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FIGURE 3. Cumulative mass balances of PCB-52, -101, and -180 between 1930 and 2000 in the northern hemisphere, expressed in percent of the global cumulative emission (A). Bold font is for simulation results with forests, and italic font is for simulation results without forests. Overall global lifetime of PCB-52, -101, and -180 with forests and without forests as a function of time (B).
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in media other than the canopy, especially in the atmosphere. If PCB-180 degrades in the forest canopy as fast as in air (i.e., case 2), the enhancement factor for forest filter effect is 6% for eACP1 and 19% for eACP10. Comparing case 2 with case 1, degradation in the forest canopy alone can increase the forest filter effect of PCB-180 by 10% (1.19-1.09 ) 0.10) after 10 years of steady emission if PCB-180 has the same half-life as in air. However, if a very long half-life is applied to the forest canopy (i.e., the same as in soil, see case 3), degradation in forest canopy does not affect the forest filtering of PCB-180, as is evident from the identical results for cases 1 and 3. Effect of Forests on the Global Dispersion and Distribution of Different PCB Congeners. Global forests filter SOCs to a different extent depending on their physical-chemical properties (Figure 1E,F). To quantitatively elucidate how this filtering alters the global environmental pathways of several real SOCs, the fate of three PCB congeners (PCB-52, -101, and -180) was simulated for the time period 1930-2000 using Globo-POP. The physical-chemical properties and global emissions of these PCB congeners are relatively well established. Instead of the generic emission profile employed in the above chemical space calculations, realistic emission estimates by Breivik et al. (33) were used. The physicalchemical properties and degradation properties were taken from refs 29 and 34. For lack of better information, the degradation half-life in the forest canopy was assumed to be the same as that in soil. Figure 3A shows the mass balance for these PCBs in the five different climate zones of the northern hemisphere. All values are expressed in percent of cumulative emissions (1930-2000) to circumvent the uncertainty of the absolute emission estimate. A simplified mass balance format is adopted in these figures to focus on the most important processes and patterns. Specifically, all terrestrial media are lumped together in a “continent” compartment, two-directional chemical exchange between compartments is aggregated to a net flux, losses on the continents include degradation in various surface media and freshwater sediment burial, and degradation and deep sea transfer contribute to the overall permanent loss in the oceans. The model simulations show that the three PCBs, mostly emitted into the temperate and subtropical zone of the Northern hemisphere, were dispersed from these zones in both northerly and southerly directions by atmospheric and oceanic transport (Figure 3A). Net deposition of PCBs from air to continents is generally higher in the simulation scenario with forests than in the one without. The accumulated amounts of PCBs on the continents are thus increased. The exceptions are the zones without forests, such as the Arctic, where PCB deposition to, and accumulation in, continents is smaller when forests are included. In contrast, chemical deposition to the oceans, permanent losses in different environmental media, atmospheric and oceanic interzonal transport, and the accumulated amounts in air and oceans are consistently lower after forests are included. This indicates that forests are effective in reducing the transfer of PCBs to the oceans, by instead transferring them to the forest soils, mirroring the shift in environmental pathways already predicted by the generic calculations by Wania and McLachlan (8). It is remarkable that the calculated net transfer of PCB-52 and -101 from the temperate to the boreal zone is higher with global forests (see Figure 3A). While this may seem at first counterintuitive to a forest filter effect, it becomes understandable when we consider that forests reduce PCB transfer in two directions and the extent of reduction for the transfer from N-boreal to N-temperate is larger than that for the reverse flux (see Table S6 for gross fluxes). Even though the gross northward flux is lower with forests than without 7192
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forests, the net northward flux is higher in the scenario with forests. In other words, the increased northward net flux for these PCBs is a reflection of the particularly effective filtering of these two congeners by the boreal forests, which reduces their return to lower latitudes. The situation is somewhat different for PCB-180, for which even the net flux from temperate to boreal zone is reduced when accounting for global forests. Both PCB-52 and PCB-101 exhibit higher global mobility than PCB-180 (34), and a larger amount of such lighter PCBs is transferred to the north as compared to PCB-180. Although the temperate forests filter the lighter PCBs (i.e., PCB-52, -101) and reduce their gross transport to the north, the effect of temperate forests on these lighter PCBs is less effective than that for PCB-180. Boreal forests then take a further step filtering such chemicals and reduce their transfer to the Arctic. A similar situation applies to PCB-180, but most of it is already retarded in the source region, that is, in the N-temperate and N-subtropic zone. Therefore, all three PCBs are subject to continuous filtering while traveling north and experience reduced loadings in the Arctic regions. It may also seem peculiar that the amount of PCB-180 lost from the continental part of the N-boreal is lower with forests than without forests (see Figure 3A). The continental loss shown in Figure 3A includes both degradation and sediment burial. Even though degradation loss of PCB-180 in terrestrial media is higher with forests than without forests (0.27% vs 0.24%), its burial in freshwater sediments is lower (0.09% vs 0.18%). The smaller continental loss in the Boreal in the scenario with forests is thus due to reduced transfer of PCB-180 to the freshwater system. Effect of Forests on Overall Lifetime for Different PCB Congeners. Overall global lifetimes were calculated for the three PCB congeners as the ratio of the total global amount and the overall permanent global loss rate by degradation, sediment burial, and deep sea transfer. These lifetimes increased over the past 30 years (Figure 3B) as the fraction of the PCBs in the global environment that is found in soil compartments with low loss rates is increasing at the expense of the fraction in the compartments air and water with relatively fast loss processes (18). Regular short-term fluctuations of such lifetimes reflect the seasonal variation of forest canopy size and temperature, which influences degradation rates (35). The presence of global forests in the model consistently increased the calculated overall lifetimes for all three PCB congeners. A similar effect was noted by Wegmann et al. (12) when studying the effect of vegetation on the global fate of DDT using the CliMoChem model. The overall persistence of DDT increased from 40 to 47 days upon introducing vegetation and a high OC content in vegetationcovered soils to the model. This suggests that forests enhance the movement of SOCs from media with fast degradation rate (e.g., air) or other efficient loss (e.g., ocean and freshwater) to those with longer degradation half-lifes (soils). The extent of the increase in overall lifetime is larger for PCB-180 than for the other two congeners. This is because the heavier congener is filtered more effectively by forests (refer to Figure 1E and F) and because the relative increase in degradation half-life upon transfer to soils is larger for PCB-180.
Acknowledgments This work was inspired by M. S. McLachlan from Stockholm University, and we benefited greatly from numerous discussions with him. We would also like to thank J. Zhao for helping with GIS-related work, and L. Zhang from the Meteorological Service of Canada for discussions related to the extrapolation of the parameters describing global forests. This study was supported by the Canadian Foundation for Climate and Atmospheric Sciences.
Supporting Information Available Table with the relative distribution of global forest in the 10 climate zones of the Globo-POP model, and description of the approaches employed to extrapolate dry deposition velocities and specific forest canopy volumes, and to allocate forest compartments. This material is available free of charge via the Internet at http://pubs.acs.org.
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Received for review November 17, 2004. Revised manuscript received June 3, 2005. Accepted July 19, 2005. ES0481979
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