Environ. Sci. Technol. 2004, 38, 1505-1512
Influence of Vegetation on the Environmental Partitioning of DDT in Two Global Multimedia Models F. WEGMANN, M. SCHERINGER,* M. MO ¨ LLER, AND K. HUNGERBU ¨ HLER Institute of Chemical and Bioengineering, Swiss Federal Institute of Technology Zu ¨ rich, ETH Ho¨nggerberg, CH-8093 Zu ¨ rich
Two multimedia models are used to investigate the effect of a vegetation compartment on the environmental partitioning of dichlorodiphenyltrichloroethane (DDT): a steady-state unit world model using global averages of vegetation cover and land-to-sea ratio and a dynamic model with latitudinal zones and zone-specific vegetation types and annual temperature courses. The vegetation compartment represents canopies of deciduous and coniferous forests and blades of grasses; the organic carbon content of the vegetation-covered soil is higher than in the bare soil. In the steady-state model, transfer from the air to the vegetation and the underlying soil as well as revolatilization from the foliage and reduced deposition to the soil is observed, depending on the chemical’s degradation rate constant in vegetation and the deposition velocities of the gaseous and particle-bound fractions. In both models, a significant effect of the organic carbon content of the vegetation-covered soil increasing the effect of the vegetation compartment is observed. In the steady-state model, the changes in the DDT concentrations in air do not exceed 7% difference between the cases with and without vegetation; the soil concentrations differ by maximally a factor of 2.7. In the spatially and temporally resolved model, however, air concentration differences up to 90% are observed, depending on the type and amount of vegetation in the latitudinal zones. Long-range transport is less pronounced in the model with vegetation.
substance properties can lead to a highly complex pattern of processes affecting the environmental fate of SOCs. Besides field and laboratory measurements, multimedia fate and transport models are increasingly being used to investigate the effect of vegetation on the fate of SOCs. Aspects so far addressed by modeling studies include the uptake of SOCs by foliage (8, 14), the general change of partitioning behavior and persistence (15-17), the effects of vegetation on the potential for LRT (17, 18), and the occurrence of an FFE (8, 9). On the other hand, there are several points requiring further clarification. These include the effect of varying soil organic matter content in comparison to the direct effect of forest canopies, the effect of the spatial variability of vegetation and soil types on a global scale, and the effect of the high uncertainty of the degradability of SOCs in vegetation. In this study, we use two multimedia fate models to address these issues. With the example of DDT as an SOC of environmental relevance, we compare modeling results from model variants without and with a vegetation compartment. This compartment only represents the canopies of deciduous and coniferous forests and the surface cover of grasslands but does not include roots, stems, bark, and branches. We first investigate the effect of different combinations of degradation rate constants in the vegetation and deposition velocities for air-vegetation transfer and then analyze the effect of the canopy itself and of increased organic carbon (OC) contents in the soil underneath. We further identify the different effects of the vegetation compartment on steady-state and dynamic model solutions and on the spatial distribution of DDT in a global transport model. It needs to be kept in mind that vegetation is represented in current multimedia fate models only in a highly simplified manner. However, although the description of vegetation in multimedia models neglects many phenomena observed in reality, even such a simplified modeling approach leads to a multitude of results requiring thorough interpretation. Accordingly, one main objective of this study is to improve the understanding of the effects caused by inclusion of a vegetation compartment into multimedia models. On this basis, it is also discussed to what extent the general trends observed in the model results can be extrapolated to reality.
Description of Models Introduction Airborne semivolatile organic chemicals (SOCs) are deposited to and taken up by plants (1-7). On one hand, the SOC uptake by plants has to be considered as a pathway for human exposure, and on the other hand, it is of interest to what extent the environmental partitioning, persistence, and potential for long-range transport (LRT) is influenced by the interaction of SOCs with vegetation. The main factor affecting the fate of SOCs with log Kow > 3 is assumed to be filtering of airborne material by forest canopies (5, 8, 9). This “forest filter effect” (FFE) depends not only on the efficiency of the air-foliage transfer but also on the degradability of the SOCs at the foliage surface and the transfer to the soil by leaf fall. Root uptake and incorporation into the wood are less important for SOCs with log Kow > 3 (10-13). The interplay of environmental conditions, vegetation properties, and * Corresponding author phone: +41-1-632 30 62, fax: +41-1-632 11 89, e-mail:
[email protected]. 10.1021/es034262n CCC: $27.50 Published on Web 01/23/2004
2004 American Chemical Society
Multimedia Models Used. To investigate the effect of a vegetation compartment, we employ the two models VegeZoMo and CliMoChem. VegeZoMo is a purely evaluative unitworld model without transport that is solved for steady-state conditions (19). CliMoChem is a level IV model with different climate zones that is used here to investigate the influence of zone-specific vegetation parameters and study temporal trends in the vegetation effect as well as the combined effects of vegetation and LRT on the fate of SOCs. CliMoChem consists of a sequence of latitudinal zones and is used to model the temperature-dependent effects of global transport, partitioning, and degradation processes on SOC fate (20). Both models contain the five media tropospheric air (height 6 km), surface ocean (depth 200 m), bare soil (depth 0.1 m), vegetation-covered soil (depth 0.1 m), and foliage, see Figure S1 in the Supporting Information. Specific water-to-land ratios and annual temperature courses are attributed to all zones (21, 22). Each compartment is well mixed, based on the assumption that mixing within a latitudinal zone is much faster than transport in the north-south direction. AccordVOL. 38, NO. 5, 2004 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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TABLE 1. Annually Averaged Vegetation Parameters for VegeZoMoa soil cover grassland coniferous forest deciduous forest
diff νa-v (m/day)
59.1 6.74 × 102 2.13 × 103
part,dry νa-v (m/day)
31.4 43.2 4.31 × 102
flipid (-) 0.02 0.06 0.01
Vv (m3/m2 soil) 10-4
2.77 × 1.68 × 10-3 7.81 × 10-4
tleaf (d)
frf (-)
4.06 × 2.01 × 103 4.06 × 102
0.068 0.350 0.193
102
a νdiff : gaseous deposition velocity air-vegetation; νpart,dry: dry particle deposition velocity air-vegetation; f lipid: lipid content of vegetation; a-v a-v Vv: vegetation volume; tleaf: leaf lifetime; frf: fraction of intercepted rainfall. Original data and references are given in the Supporting Information.
ingly, the model is not suited to investigate a chemical’s fate on the time scale of a few days or weeks. A variety of transport, partitioning, and removal processes take place in the five compartments. While the processes’ rate constants are calculated for a constant temperature of 298 K in VegeZoMo, these parameters are a function of temperature in CliMoChem and therefore specific to every zone. Processes included are wet and dry deposition of gaseous and particle-bound chemical from the air to the surface media, revolatilization from the surface media, soil runoff, and degradation. Degradation takes place in all media with temperature-dependent first-order rate constants. Description of Vegetation. We only consider the foliage part of the vegetation (leaves, needles, and blades of grass) in the models. Compounds with log KOW > 3 are neither taken up from the soils by roots nor transferred from air to the stem interior through the bark (10-13); therefore, the wood interior is excluded. Bark, on the other hand, is accessible to airborne SOCs and reflects the pattern of air contamination (4). However, because the bark’s storage capacity is small on a global scale and degradation is probably slow in the bark, absorption by bark does not strongly affect the mass budget in a global model. In particular, because the transfer from the bark to the soil is very slow, absorption by bark does not strongly influence the partitioning between air and soil. (In a steady-state multimedia model with a bark compartment that has no sinks, inclusion or exclusion of this compartment does not affect the concentrations in the other media at all.) For these reasons, bark is also excluded from the models. In conclusion, the vegetation model only represents partitioning into the lipophilic fraction of the leaf’s cuticle and cellular lipids (23). The 1° × 1° resolution database of 11 vegetation types from ref 21 is aggregated into four types of land cover: bare soil, grassland, coniferous forests, and deciduous forests (Figure S2, Supporting Information). This yields a table containing the fractions of these four types of land cover for 180 latitudinal bands of 1° width. Depending on the number of latitudinal zones, the entries of this table are further aggregated for each of the zones so that an area-weighted distribution of vegetation types is obtained for each zone. VegeZoMo has only one zone, i.e., one global average is calculated from the data. The model variants with vegetation contain the following vegetation-specific processes: diffusive exchange between air and foliage, wet deposition of the gaseous fraction, wet and dry deposition of the particle-bound fraction, degradation within the foliage, and deposition to the vegetation soil by leaf fall. In the vegetation-covered soil, the same processes take place as in the bare soil (degradation, revolatilization, and runoff). Parameters describing these processes are shown in Table 1. Broad leaf plants do not have a lifetime in CliMoChem; instead, the volume of the deciduous foliage is modeled to have its maximum during the summer season, 10% of the maximum value in winter, and 55% in spring and fall (9). At the beginning and end of fall, the foliage volume is decreased and the corresponding fractions of leaf-sorbed substance are transferred to the vegetation soil. Within the tropic zones, there are no seasonal foliage volume changes. 1506
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The fraction of intercepted rainfall (frf) describes the reduction of rainfall by the foliage; wet deposition rate constants reduced by a factor frf apply to the vegetationcovered soil. While a seasonally and globally averaged value of frf ) 0.14 is used in VegeZoMo, a season- and zone-specific range of 0.01-0.30 is employed in CliMoChem. The determination of the parameters flipid (lipid content of leaves), Vv (vegetation volume), and tleaf (lifetime of leaves) is described in the Supporting Information. The storage capacity of the vegetation is given by a vegetation-air partition coefficient proportional to the octanol-air partition coefficient (23): Kva ) flipid‚Koa. Annual averages of the velocities of gaseous diff part,dry and dry particle deposition, νa-v and νa-v (in m/day), are based on measurements from ref 5, see Supporting Information. The gaseous deposition velocity is much higher for forest canopies than for bare soil and is an influential parameter in the description of vegetation. The zonal vegetation types combined with the typespecific vegetation parameters (Table 1) yield the overall zonal vegetation parameters used in the model equations. In reality, the soil OC content is correlated with the vegetation type, but in the models, these two factors are independent: the soil OC content can be selected independent of the description of the vegetation compartment. The soil OC content is calculated as 0.095 (grassland), 0.27 (deciduous woodland), and 0.35 (coniferous woodland) based on data on organic matter in different soil types (24) and a carbon content of 50% in soil organic matter (25, 26, see the Supporting Information for details). The influence of vegetation on the DDT concentrations in air is expressed in terms of quotients of the concentration in a model with vegetation divided by the concentration in the corresponding model without vegetation (models without vegetation are called NoVegeZoMo and NoVegCliMoChem). If the concentration quotient is below 1, we call this an air concentration reduction effect (ACRE). The effect of vegetation on the soil concentrations is expressed as the quotient of the concentrations in the vegetation-covered and bare soils in a model with vegetation. Soil concentration quotients above 1 indicate a soil concentration increase effect (SCIE); a shielding effect occurs for quotients below 1 (vegetation shields soil from deposition). Substance Parameters. The model calculations are performed with p,p′-DDT (CAS no. 50-29-3) as an organochlorine insecticide that is still of environmental relevance. The following degradation rate constants and partition coefficients are used: ks ) 4.10 × 10-4 day-1, kw ) 2.62 × 10-3 day-1, ka ) 2.97 × 10-1 day-1, kv ) 3.32 × 10-2 day-1, log KAW ) -3.33, log KOW ) 6.16, log KOA ) 10.1. Degradation rate constants are from refs 27 and 28, see Supporting Information, and partition coefficients from ref 29. The degradation rate constants for soil and water represent biodegradation, while the degradation in air is caused by reaction with hydroxyl radicals. The degradation in and on plants is phytodegradation, possibly performed by an enzymatic reaction, and photodegradation. Temperature dependencies of the degradation rate constants are expressed by estimated activation energies of 30 kJ mol-1 for water and soil and 10 kJ mol-1 for air. For calculating the Henry’s law constant for different
FIGURE 1. Ratios of DDT concentrations in VegeZoMo and NoVegeZoMo as a function of the particle-bound fraction, Φ, and the degradation rate constant in vegetation, kv. (A) Air concentrations of VegeZoMo divided by those of NoVegeZoMo. ACRE: air concentration reduction effect. (B) Concentration in vegetation soil divided by concentration in bare soil of VegeZoMo. SCIE: soil concentration increase effect. The lines at kv ) 1 × 10-3 day-1 are explained in the text.
TABLE 2. Ranges of Ratios of DDT Concentrations in Air and Soil, Persistence, and Fraction in Vegetation, Calculated with VegeZoMo and NoVegeZoMoa
scenario
diff νa-v
fOC (-)
air concentration ratio, cVMo /cNVMo a a (min, max)b
1 2 3
100% 10% 100%
0.02 0.02 0.17
0.931, 1.064 0.994, 1.033 0.931, 1.061
soil concentration ratio, VMo cVMo vs /cbs (min, max)c
persistence ratio τVMo/τNVMo (min, max)d
% of DDT mass in vegetation (min, max)
0.600, 2.673 0.572, 1.632 0.606, 2.702
0.786, 1.840 0.832, 1.346 0.790, 1.851
0.0080, 11.7 0.0078, 8.09 0.0076, 11.6
a Three scenarios with high and reduced velocities for gaseous deposition to vegetation and low and high fractions of organic carbon are compared. b Ratios below 1 correspond to an air concentration reduction effect (ACRE). Concentrations in two model variants with and without vegetation are compared. c Ratios above 1 correspond to a soil concentration increase effect (SCIE). Concentrations in the vegetation-covered soil (vs) and the bare soil (bs) of the VegeZoMo model are compared. d Persistence calculated as residence time (steady-state mass (kg) divided by the release flux (kg/day)).
temperatures, the energy of the air-water phase transfer is assumed to be 45 kJ mol-1. All of these parameters are fraught with uncertaintyssee ref 30 for Kowsbut their influence on the concentration ratios considered here is weaker than on absolute concentrations.
Results VegeZoMo Occurrence of the Forest Filter Effect. Wania and McLachlan investigated the effect of varying partition coefficients on the transfer of SOCs from air to vegetation (9). VegeZoMo results for varying partition coefficients are consistent with the findings of Wania and McLachlan and indicate that air concentrations are reduced for chemicals with log Koa between 9 and 11 and log Kaw greater than -4, see Supporting Information. Besides partition coefficients, also kinetic parameters affect the occurrence of an FFE. To analyze the influence of deposition from air to foliage and degradation in the foliage, we systematically vary the degradation rate constant in vegetation, kv, and the particle-bound fraction of DDT, Φ. kv is varied because only few measurements, spanning some orders of magnitude, have been reported for degradation in vegetation (31-33). The particle-bound fraction exhibits considerable variability, e.g., with temperature and particle concentration (34). In the models it is assumed that the particle-bound fraction is not degraded by OH radicals. Thus, Φ affects both the chemical’s deposition processes and lifetime in air and is therefore a crucial model parameter. Several methods to derive Φ have been proposed; see overview in ref 35. To cover the full variability of the particle-
bound fraction, Φ is varied here from 0 to 1 (36). Later, we discuss the influence of the diffusive air-vegetation deposidiff , and of the OC content in the vegetationtion velocity, νa-v covered soil. Figure 1A shows the steady-state concentration of VegeZoMo divided by the steady-state concentration of NoVegeZoMo for air as a function of Φ and kv. Φ is varied independent of all other substance properties, which reflects the possible effects of variable aerosol concentration and composition (with constant temperature). Emission is into air, vegetation parameters from Table 1 are used, and the fraction of organic carbon of the vegetation-covered soil is 0.02. This parameter set is called scenario 1, see Table 2. The air quotients range from 0.93 to 1.06 in this scenario. In Figure 1B, the corresponding soil concentration quotients are depicted; their values range from 0.60 to 2.67. Two main areas are found in both plots. In the upper left half of Figure 1A, the air concentration ratios are below 1, which is caused by efficient deposition to the foliage and subsequent degradation or deposition to the soil. In the lower right corner, the quotients are above 1; in this domain, a major fraction of the DDT mass in air is assumed to be bound to particles and the degradation in foliage is slow. Due to the fast revolatilization, the foliage “bounces” substance back into the air (shielding effect). The major part of the graph in Figure 1B has concentration ratios below 1; an SCIE is observed only for Φ below 0.22 (fast gaseous deposition to the vegetation and then by leaf fall to the soil). A second way of varying Φ is to link Φ to the vapor pressure or Koa. In this case, higher Φ corresponds to lower vapor VOL. 38, NO. 5, 2004 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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FIGURE 2. Differences between NoVegeZoMo and VegeZoMo mass fluxes as function of Φ for kv ) 1 × 10-3 day-1 (bold lines in Figure 1). (A) Differences of air-related mass fluxes with different rate constants in VegeZoMo and NoVegeZoMo. The sum of all contributions (∆Fa, denoted by “+”) determines the occurrence of the ACRE. (B) Differences of soil-related mass fluxes with different rate constants for vegetation soil and bare soil. “+”: sum of all contributions (∆Fs). pressure, higher Koa, and also higher Kva. This also implies lower temperature and, accordingly, lower Kaw and degradation rate constants. In such a scenario, revolatilization from the vegetation is slower for higher Φ, and there is an ACRE for all values of kv and Φ (results not shown). The SCIE is found left of the line from Φ ) 0, kv ) 1 × 10-1 day-1 to Φ ) 0.8, kv ) 1 × 10-4 day-1; to the right of this line, the soil is shielded from deposition because of degradation in the vegetation. Temperature-dependent Φ values are used in the CliMoChem calculations below. Analysis of Mass Fluxes. To understand the observed concentration ratios, we analyze the underlying mass fluxes in the model variants with and without vegetation. Because several fluxes going in different directions are involved, we employ the following method in this analysis (see ref 37 for a more detailed description). Inclusion of the vegetation compartment changes the mass fluxes between air and soil. This can be due to changed concentrations, c, in the expressions for the mass fluxes, F ) k‚c‚V (in kg s-1), or due to changed concentrations and different rate constants, k. Accordingly, there are two groups of mass fluxes: those with different rate constants and those with identical rate constants in the two model variants. For the air compartment, the first group contains diffusion of gas-phase DDT in to and out of the vegetation and dry particle deposition to the vegetation. The second group includes degradation in air, wet deposition to the vegetation, all deposition processes from air to water, and revolatilization from the water. In eq 1, all of these fluxes are grouped in four sets: (a) fluxes with different rate constants in the two model variants, leaving the air (index i); (b) fluxes with different rate constants, entering the air (index j); (c) fluxes with identical rate constants, leaving the air (index h); (d) fluxes with identical rate constants, entering the air (index l; this last group also contains the continuous release)
∑k
VMo ‚mVMo i a
i
+
∑k
VMo ‚mVMo j j
j
+
∑
∑k
VMo)NVMo hkh ‚mVMo a
VMo)NVMo ‚mVMo l l
+
) 0 (1)
l
The index a indicates air; because of the steady-state condition, the sum of all fluxes is zero (fluxes entering the air have positive sign, fluxes leaving the air a negative sign). A corresponding equation holds for the model without vegetation 1508
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∑k
NVMo ‚mNVMo i a
i
+
∑k
NVMo ‚mNVMo j j
j
∑k
VMo)NVMo ‚mNVMo h a
h
+
+
∑k
VMo)NVMo ‚mNVMo l l
) 0 (2)
l
Subtraction of eq 2 from eq 1 yields
∑(k
VMo ‚mVMo i a
- kNVMo ‚mNVMo )+ i a
i
∑k ∑k
kNVMo ‚mNVMo )+ j j
∑(k
VMo ‚mVMo j j
-
j
VMo)NVMo ‚(mVMo h a
h VMo)NVMo ‚(mVMo l l
- mNVMo )+ a
- mNVMo ) ) 0 (3) l
l
The third sum in eq 3 (index h) contains the difference between the chemical’s mass in air in the two model versions. The sign of this difference determines if the air concentration in the model with vegetation is higher or lower than in the model without vegetation. Using eq 3, we can determine this sign from the first two sums; the fourth sum (index l) is close to zero because the fluxes from the water back into the air are very similar in the two models. The first two sums can be written as (with F for a flux in kg/s)
∑F ) (F i
VMo part,dry
NVMo VMo NVMo - Fpart,dry ) + (Fgas,dry - Fgas.dry )
(4)
VMo bs-a,gas
VMo NVMo VMo + Fvs-a,gas + Fv-a,gas - Fbs-a,gas
(5)
i
and
∑F ) F j
j
The Fi fluxes are dry particle deposition and gaseous deposition to bare soil, vegetation-covered soil, and vegetation in the model with vegetation and to bare soil in the model without vegetation. The Fj fluxes are the revolatilization fluxes from the bare soil (bs), vegetation-covered soil (vs), and vegetation (v). From eq 3 it follows that if ∆Fa ) ∑iFi + ∑jFj is calculated, the sign of the difference mVMo - mNVMo is given by the sign a a of the total of all fluxes with different rate constants in the two models, ∆Fa. In Figure 2A, the values of ∆Fa (indicated by “+”) are shown for increasing Φ and kv ) 1 × 10-3 day-1 (bold horizontal line in Figure 1A). The bars represent the positive and negative contributions stemming from the individual mass fluxes (bars). A negative value of ∆Fa indicates a greater
outflow from the air compartment in VegeZoMo and, therefore, an ACRE; a positive ∆Fa corresponds to higher DDT air concentrations in VegeZoMo. The large positive contribution counteracting the ACRE (given in dark gray in Figure 2A) stems from the revolatilization of DDT deposited onto the foliage; the negative contribution decreasing with increasing Φ (light gray) is the gaseous deposition flux difference between the two models. For Φ e 0.3, ∆Fa is negative or, in other words, there is a stronger deposition to the ground in VegeZoMo than in NoVegeZoMo. This corresponds to the ACRE observed for the points 0 e Φ e 0.3 on the line at kv ) 1 × 10-3 day-1 in Figure 1A. For these low Φ values, the deposition flux difference between the two model variants is mainly caused by the strong gaseous deposition to the foliage in VegeZoMo. For Φ above 0.3, higher air concentrations are observed in VegeZoMo (shielding effect). In this domain, the gaseous deposition loses importance and is partly substituted by slower dry and wet particle-bound deposition; see deposition velocities in Table 1. To investigate the occurrence of the SCIE, we again analyze the contributions to the total flux difference, ∆Fs in this case, of the processes with different rate constants (here, fluxes of the bare soil and vegetation-covered soil in VegeZoMo are compared). These processes include revolatilization from soil to air, leaf fall, gaseous deposition from the air to the soils, wet and dry particle deposition, and washout of the gaseous substance fraction in air. The only fluxes with unchanged rate constants are runoff and degradation in the soils. In Figure 2B, the contributions of the different processes to the flux difference, ∆Fs (denoted by “+”), are shown. A negative contribution indicates a higher inflow into the bare soil, whereas a positive contribution corresponds to a higher inflow into the vegetation-covered soil (SCIE). ∆Fs is positive for Φ e 0.2; because of the leaf fall, the net inflow into the vegetation soil is higher than into the bare soil. For higher Φ values, the vegetation-covered soil has a smaller net inflow. This is mainly due to the shift from gaseous deposition to wet and dry particle deposition, which are both slower for the vegetation-covered soil than for the bare soil (negative contributions in Figure 2B). Reduced Air-Vegetation Transfer Velocity. The analysis of air-related mass fluxes in Figure 2A indicated that gaseous deposition from air to vegetation is the most important diff deposition process. By reducing the velocity νa-v to 10% of its initial value, we test the sensitivities of the observed ACRE and SCIE to this parameter. The concentration quotients for air are all closer to 1 diff compared to the scenario with high νa-v , see scenario 2 in Table 2. The domains with reduced and increased DDT concentrations in air are the same as in Figure 1A. With respect to the soils, the domain for which an SCIE is observed is restricted to the lower left corner of the plot (smaller than in Figure 2B). Because of the reduced gaseous deposition to the foliage, also the deposition to the ground by leaf fall is reduced in this scenario. In combination with the interception of wet and dry particle deposition by the foliage, this leads to a smaller domain with an SCIE and also to a less pronounced SCIE (see soil concentration ratios in Table 2). Increased OC Content in Vegetation-Covered Soil. In scenarios 1 and 2 in Table 2, a low OC content of 2% was assumed for bare soil and vegetation-covered soil. However, the value fOC ) 0.02 represents an average agricultural soil and measurements show higher OC contents in many vegetation-covered soils (24). In a third scenario, a mean value of fOC ) 0.17 was therefore taken for the vegetation soil compartment of VegeZoMo (scenario 3 in Table 2).
FIGURE 3. Steady-state DDT concentrations in air in three model variants with/without vegetation and low/high fOC values (concentrations normalized to concentrations in the model without vegetation and low fOC). For emission to air, the vegetation compartment exerts the dominant effect; for emission to soil, the fOC is the dominant factor. To compare the influences of the vegetation compartment and the increased OC content of the vegetation-covered soil, we use three model versions: (1) with vegetation/low fOC; (2) no vegetation/high fOC; and (3) with vegetation/high fOC. (The degradation rate constant in vegetation is kv ) 3.32 × 10-2 day-1 and Φ is equal to 0.078 in these calculations.) In Figure 3, the DDT air concentrations in the three model versions are shown for emission into air and emission into the soils (identical sources in kg‚m-3‚day-1 for both soil types); the concentrations are normalized to the NoVegeZoMo results with a low fOC. For emission to air, the reduced DDT concentration in air is caused by including the vegetation compartment; the sole increase in the soil OC content reduces the air concentrations only marginally. However, the opposite behavior is found with the soil emission scenario: the most pronounced effect is observed if the fOC is increased from 0.02 to 0.17.
Results CliMoChem CliMoChem is different from VegeZoMo with respect to three features: (1) CliMoChem uses zone-specific values for the vegetation types and compartment volumes; (2) CliMoChem provides time-resolved concentration functions; (3) CliMoChem includes long-range transport in air and water. We address these issues below, using CliMoChem with 20 zones. Influence of Spatial and Temporal Resolution. To investigate the influence of zone-specific vegetation parameters such as vegetation types and volumes, transport between adjacent zones is switched off in a first step so that the influence of long-range transport is excluded. Calculations with low (2%) and high values (9.5-28%) of the soil OC content are conducted with release to the air in every zone (all soils have fOC values according to their zone-specific vegetation cover, see Table SI-T1 in the Supporting Information). The concentration ratios (“with vegetation” divided by “no vegetation”) obtained after 10 years (about two halflives of DDT in the soil) in the different zones are as follows: air concentration ratios range from 0.26 to 0.99 (low fOC) and from 0.064 to 0.99 (high fOC); for the soil concentrations, the quotients range from 0.81 to 1.60 (low fOC) and from 0.81 to 1.62 (high fOC). For comparison, see the values for VegeZoMo in Table 2. In addition to this spatial variability, there are also significant changes in the concentrations as functions of time. As an example, we analyze this temporal variability for the air concentrations in zone 9 of 20. Figure 4 shows the concentration quotients for the cases of low (2%) and high fOC (13%). In the first year, the quotients for low and high fOC are almost identical. After this initial period, the two curves VOL. 38, NO. 5, 2004 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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FIGURE 4. Temporal trend of the quotient of air concentrations in CliMoChem and NoVegCliMoChem for zone 9 of 20 (transport into adjacent zones switched off). Two cases with fOC values of 0.02 and 0.13 in the vegetation-covered soil are compared.
FIGURE 5. Zonal DDT concentration quotients in CliMoChem and NoVegCliMoChem for seawater and air after 10 years (with transport in air and ocean water). Pulse release into the air of zone 10 in the first year. All vegetation soils have high OC content. The air concentration quotient is below 1 because of the high OC content in the vegetation soil (see Figure 4). separate and the line for high fOC drops to a value of about 0.28 while the air quotient for low fOC approaches a value of 0.64. From the eighth year on, both quotients remain constant (oscillations are due to seasonal parameter changes). Again, the difference between the two cases with low and high fOC can be explained in terms of mass fluxes. A few seasons after the emission into the air, the main inflow into the air is revolatilization from the vegetation soil, but this mass flux from soil to air is strongly reduced in soils with a higher fOC. Therefore, less substance is transferred into the air compared to NoVegCliMoChem and the air quotient decreases. Note that the observed strong ACRE is not only caused by the vegetation compartment but also by the lower revolatilization flux from the vegetation soil due to the higher fOC. Since almost all of the remaining DDT is stored in the soils after a few years, soil descriptors play a major role for the air concentration quotients even when the emission was into air. This is not discernible in the steady-state model, because the continuous air emission scenario used in the steady-state model prevents the system from changing from air-controlled to soil-controlled. We call a model air-controlled when the highest fluxes occur in the air compartment. This is the case in the air emission scenario in the steady-state models because the outflow out of the air is constantly high due to the continuous source. The first few seasons of CliMoChem are also air-controlled. However, after some 1510
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years, most of the substance is transferred into the vegetation soil and the model is soil-controlled. Influence of Interzonal Transport. The influences of the vegetation compartment and the increased soil OC content in the CliMoChem model with transport is shown in Figure 5, which depicts the zonal air and ocean water concentration quotients 10 years after a pulse release into the air of zone 10. Transport in air and seawater have transferred substance to all other zones. The air quotients below 1 found in all zones are due to the aforementioned lower revolatilization flux from the vegetation soil with increased OC content. In the northern hemisphere, the air quotient shows a maximum in zones 7 and 8, a minimum in zones 4 and 5, and again a maximum in zone 1. Zones 7 and 8 contain large fractions of water, bare soils (deserts), and grassland which have, compared to zones with higher fractions of woodland, a lower ability to filter DDT from the air. In zone 7, the total deposition flux from the air to the ground assumes only 14% of the corresponding flux for zone 10 (relative to the zonal mass in air). On the other hand, the revolatilization flux from the ground to the air is about 3.6 times larger in zone 7 than in zone 10 (normalized to zonal mass in soil). Both fluxes indicate a weaker influence of vegetation and soil OC. The opposite behavior is observed for zones 4 and 5, where the sea covers less than 40% of the surface and more than 50% of the ground is covered by forests. Accordingly, the soil OC reaches its maximum of about 25% in zones 4 and 5 and the
FIGURE 6. Cumulative DDT mass distribution 25 years after a pulse release into the air of zone 10 of CliMoChem and NoVegCliMoChem. In CliMoChem, a higher fraction of mass remains in the vegetation soils in and closer to the zone of release. filtering of DDT from the air is efficient, resulting in minimal concentration quotients in these zones. To the north of zone 4, the fraction of woodland decreases steadily, resulting in a weaker vegetation influence (increasing concentration quotients in zones 4 to 1). The ratio of the DDT concentrations in seawater exhibits a minimum at zones 4 to 5 like the air quotient but has a maximum in the equatorial region where the emission took place. This maximum is a residue of the strong deposition of DDT directly after the pulse release in zone 10 and is therefore an artifact of the emission scenario used. Finally, we analyze the influence of vegetation and increased soil OC on the long-range transport of DDT in the CliMoChem model. With the parameters used for DDT in the CliMoChem calculations, the dominant vegetation-related process in the first year is diffusive transfer from the air to the vegetation. This process competes with the atmospheric transport of the chemical so that the potential for LRT is reduced. In the long term, however, it is the mass transfer to the soil that affects the global distribution of DDT. Figure 6 shows the cumulative zonal distribution of the total global DDT mass after 25 years for the two model variants with and without vegetation. Since the line of CliMoChem is below the line of NoVegCliMoChem for every zone, vegetation and increased soil OC lower the substance fraction that is transported to zones north of the emission zone. For example, 32.4% of the total mass is found north of 36°N in NoVegCliMoChem but only 19.9% in CliMoChem (20.1% for a model variant with vegetation and low fOC in the vegetation soil, not shown in Figure 6). In addition to the spatial distribution of the DDT mass, the absolute amount present in the two model variants is different. Since more DDT is stored in the vegetation-covered soil and the degradation rate constant in soil is much lower than in air, the absolute mass is higher in CliMoChem than in NoVegCliMoChem. With a high soil OC content, there is 14.4% more DDT in CliMoChem after 25 years (11.6% with fOC ) 0.02) than in NoVegCliMoChem; the overall persistence increases from 40.1 days without vegetation to 47.1 days with vegetation and high OC content. Both values are relatively low because the chemical is released to air, so that the high degradation rate constant in air strongly influences the persistence.
Discussion The model results obtained in this study show a variety of possible effects of a vegetation compartment on the partitioning, persistence, and LRT potential of SOCs. One main
finding is that the effects of the vegetation compartment and of the increased OC content of vegetation-covered soils need to be considered in combination. For example, the vegetation’s effect on the air concentrations in the first season in /cNVMo > 4) disappears in the soil-controlled Figure 4 (cVMo a a regime in the dynamic model (cVMo /cNVMo < 0.3) because in a a this regime the soil OC controls the partitioning of an SOC such as DDT. This implies that for SOCs with their very different time scales in the different media, the results from a steady-state model should be complemented by a dynamic calculation. If the same release term is used in the dynamic model as in the steady-state model (with units of mass instead of mass per time), the time-integrated concentrations are identical to the steady-state concentrations. However, if also the explicit course of the concentration functions is considered, important additional model features can be elucidated. The canopy itself causes, if the particle-bound fraction is low and gaseous deposition is efficient, a transfer from the air to the soil, which increases the persistence even if the degradation rate constant in vegetation is high. With high particle-bound fractions, on the other hand, the reduction in air concentrations is less pronounced or even a revolatilization back into the air is observed (shielding effect). The higher soil OC content significantly increases the soil’s storage capacity and reduces the velocity of revolatilization from the soil, which also reduces the air concentrations. This is the reason for the low air concentration ratios, cVMo /cNVMo a a in Figure 4. With highest air concentration reductions of 7% (Table 2), the overall extent of the forest filter effect is not very pronounced on the global scale. Concerning the overall persistence, scenarios with increased but also with decreased persistence values are observed in the steady-state model, depending on the degradation rate constant in vegetation and the efficiency of the vegetation-soil transfer. In the dynamic model with transport and high OC content in the soil, the persistence is increased and the potential for LRT is slightly reduced (Figure 6) because of the more efficient transfer to the soil. The results obtained for the effects of the vegetation compartment are in agreement with results from other modeling studies. Cousins and Mackay (16) and Beyer and Matthies (18) reported the most pronounced vegetation effect for chemicals with high fractions in the gas phase and a less significant effect for compounds with higher particle-bound fractions because of the lower deposition velocity for particles than for chemicals in the gas phase. In these studies it was VOL. 38, NO. 5, 2004 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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also found that the persistence can be increased or decreased and that the fraction stored in the vegetation compartment is around 5% or lower. This is consistent with our results, see Table 2. MacLeod (38) reported air concentration reductions of less than 20% for a regional model similar to that of Wania and McLachlan (9), which is similar to our ACRE values for the steady-state model (in CliMoChem, higher ACRE values are caused by the strong effect of the increased soil OC). The importance of the soil OC content to the distribution pattern of SOCs has been demonstrated with field observations (24, 39, 40). Our model results indicating that the effect of the soil OC might increase and even exceed the pure effect of the vegetation compartment are in agreement with these findings. While the general trends observed seem to provide a reliable picture, it has to be kept in mind that the modeling approach used is based on a highly simplified description of vegetation. This description mainly includes a vegetationair partition coefficient derived from the KOA, the high airvegetation deposition velocity for gaseous material (based on field measurements), and averaged soil OC values. Experimental findings on the interaction of SOCs with pine needles (41) indicate, however, that this interaction is significantly more complex than assumed in current multimedia models. This includes, for example, that different trends are observed on different time scales and that the storage capacity of the needles is influenced by volatile compounds that are not accounted for by common lipid quantification methods. Therefore, our understanding of the way in which vegetation takes up, stores, metabolizes, and transfers SOCs back to other media needs further improvement. On this basis, it will be possible to develop a better description of the physicochemical properties of vegetation and the related exchange processes and to include these into the modeling approaches.
Acknowledgments We thank Laurent Cavin, Kathrin Fenner, Michael Salzmann, Judith Stocker, Maximilian Stroebe, Frank Wania, and Karin Wu ¨ thrich for helpful comments. Financial support by the Swiss Federal Agency for Environment, Forests and Landscape is gratefully acknowledged.
Supporting Information Available Descriptions of the two models, parameter values used in the description of the vegetation compartment, and additional model results. This material is available free of charge via the Internet at http://pubs.acs.org.
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Received for review March 23, 2003. Revised manuscript received November 26, 2003. Accepted December 3, 2003. ES034262N
