Modeling the Effect of Snow and Ice on the Global Environmental Fate

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Environ. Sci. Technol. 2007, 41, 6192-6198

Modeling the Effect of Snow and Ice on the Global Environmental Fate and Long-Range Transport Potential of Semivolatile Organic Compounds JUDITH STOCKER, MARTIN SCHERINGER,* FABIO WEGMANN, AND KONRAD HUNGERBU ¨ HLER Safety and Environmental Technology Group, Institute for Chemical and Bioengineering, Swiss Federal Institute of Technology, ETH Zurich, HCI G127, CH-8093, Zurich, Switzerland

Snow and ice have been implemented in a global multimedia box model to investigate the influence of these media on the environmental fate and long-range transport (LRT) of semivolatile organic compounds (SOCs). Investigated compounds include HCB, PCB28, PCB180, PBDE47, PBDE209, R-HCH, and dacthal. In low latitudes, snow acts as a transfer medium taking up chemicals from air and releasing them to water or soil during snowmelt. In high latitudes, snow and ice shield water, soil, and vegetation from chemical deposition. In the model version including snow and ice (scenario 2), the mass of chemicals in soil in high latitudes is between 27% (HCB) and 97% (RHCH) of the mass calculated with the model version without snow and ice (scenario 1). Amounts in Arctic seawater in scenario 2 are 8% (R-HCH) to 21% (dacthal) of the amounts obtained in scenario 1. For all investigated chemicals except R-HCH, presence of snow and ice in the model increases the concentration in air by a factor of 2 (HCB) to 10 (PBDE209). Because of reduced net deposition to snow-covered surfaces in high latitudes, LRT to the Arctic is reduced for most chemicals whereas transport to the south is more pronounced than in scenario 1 (“southward shift”). The presence of snow and ice thus considerably changes the environmental fate of SOCs.

Introduction Persistent organic pollutants (POPs) and other semivolatile organic compounds (SOCs) have been measured in snow and ice in high altitudes and latitudes (1-8). Additionally, it is known from field and modeling studies that snowfall events and the presence of snow covering soil and vegetation influence the environmental distribution of chemicals (911). Therefore, it is important to understand how SOCs interact with snow and ice and how they are transported to cold regions. The latter is especially important in the context of international regulation of chemical use to reduce transboundary pollution and to protect remote regions against chemical pollution (12, 13). * Corresponding author e-mail: [email protected]; fax: +41 (0) 44 632 11 89. 6192

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Multimedia fate and transport models are important instruments to address these issues because they help to understand mechanisms and pathways of long-range transport (LRT) and the resulting environmental distribution of chemicals. None of the existing global multimedia box models (14-17), however, include snow or ice compartments. Daly and Wania have included a snow compartment in a regional model (18). They found that snow has a notable influence on the environmental fate of chemicals by functioning as a temporary storage reservoir. In their study, release of accumulated contaminants during the melt period resulted in temporarily elevated concentrations in air, water, and soil. Hansen et al. (19) developed an arctic snow model to describe the exchange of POPs between the atmosphere and the snowpack during a winter season. They found chemical fluxes to be highly dynamic. Chemicals having a higher snow-air partition coefficient were efficiently retained within the snowpack, which resulted in a seasonal increase in the chemicals’ concentrations in the air at the end of the winter. In this paper, we present for the first time a description of snow and polar ice implemented in a global multimedia box model. We use CliMoChem (Climate Zone Model for Chemicals, (17)) to analyze the effects of snow and polar ice on the mass budget and LRT of seven chemicals with different affinities for snow and ice. The model is used to assess how processes linked to snow and ice affect the mass balance of chemicals in soil, water, vegetation, and air in different latitudinal zones. Results are compared to field and modeling data in order to evaluate model outputs and process descriptions.

Methods Original CliMoChem Model. CliMoChem is a global multimedia box model consisting of a flexible number of latitudinal zones. Here we use 10 zones of 18° width with zone 1 at the North Pole (72° N-90° N) and zone 10 at the South Pole (72° S-90° S). Each zone is individually described in terms of temperature (20), land-to-water surface area ratios, and vegetation types (21). Environmental compartments included are bare soil, oceanic surface water, tropospheric air, vegetation, and vegetation-covered soil. Processes included in CliMoChem are (i) gaseous deposition and revolatilization, (ii) advective phase exchange processes (dry and wet deposition of particle-bound chemicals, vapor scavenging by rain, leaf fall from vegetation to soil, runoff from soil to water, and deposition to deep sea), (iii) temperature-dependent first-order degradation of chemicals in all compartments, and (iv) transport of chemicals in oceanic surface water and tropospheric air. All phaseexchange processes take place in parallel and make it possible for a chemical to undergo several cycles of deposition, revolatilization, and transport. The temporal resolution is 4 seasons per year with environmental parameters averaged over 3 months for each season; season 1 lasts from January to March. In ref 17 we discuss the choice of the temporal resolution of one season. More details on process descriptions and numerical values of the model parameters are given elsewhere (17, 22). Results obtained in previous studies using the CliMoChem model have been published in refs 17 and 22-25. Model Modifications. Snow and ice were implemented as two new compartments. First, the model geometry was modified. The global 1° by 1° land cover map based on remote sensing data from ref 21 was combined with geo-referenced global 1° by 1° maps of monthly snow and ice cover (26, 27). The combined map was then aggregated in longitudinal 10.1021/es062873k CCC: $37.00

 2007 American Chemical Society Published on Web 07/28/2007

direction resulting in a table containing the fractions of the different surface media for 180 latitudinal bands of 1° width. The entries of this table were further aggregated for each of the 10 latitudinal zones and four seasons so that fractions of surface area covered by the different surface media were obtained for each zone. The ice compartment represents the surface part of perennial and ephemeral ice that is in exchange with other environmental media. A depth of 0.1 m is used for this compartment. Deep ice, i.e., deeper layers of perennial ice, is not modeled explicitly but transfer to deep ice is included as a sink for chemicals in surface ice. Chemicals transferred to deep ice are assumed to remain there and their amount is recorded as part of the chemical’s overall mass balance. In regions where the ice compartment represents ephemeral ice, there is no transfer to deeper ice, as described in section 1 of the Supporting Information (SI). Spatial extent and depth of the snow cover vary according to the data from ref 26. Second, chemical fate processes were implemented for snow and surface ice. These include deposition of chemicals from the atmosphere to snow or surface ice by wet and dry deposition (particulate and gaseous); removal processes from snow and surface ice such as meltwater runoff from snow to soil and water; degradation within snow or surface ice (there is no degradation in deep ice); and transfer from surface ice to deep ice. In zones where the ice compartment completely melts in the course of the year (ephemeral ice), transfer to deep ice is zero. The volumes and properties of the snow and the ice compartment change with season and the concentrations of the chemical in the different environmental compartments are modified accordingly: if the volume decreases, the amount of chemical in the melted ice or snow volume is transferred to the underlying compartments and the chemical’s concentration in these compartments is increased (end-of-season transfer of chemicals with snowmelt). According to the changes in temperature, density, and specific surface area (SSA) of the snowpack, the snowair and snow-water partition coefficients also change with season, see below. Third, snow and surface ice properties were defined in terms of SSA, density, and content of water, air, and organic matter. Depending on the season, snow has SSA values between 22 and 32 m2/kg and densities from 280 to 380 kg/ m3. Values for ice are 10 m2/kg and 910 kg/m3, respectively. A detailed description of the properties of snow and ice and the parameterization of chemical fate processes in ice and snow is given in Section 1 in the SI for different latitudinal zones and times of the year. For every chemical, an amount of 106 t is emitted to air in zone 3 (36° N to 54° N) at the beginning of season 1. Single pulse emissions in zone 3 are used because many compounds are actually released in the northern temperate zone and there is significant snow cover in this zone. The model was run for 15 years. Calculations were performed with the original model version (scenario 1) and the modified version including snow and ice compartments (scenario 2); results from the two scenarios are systematically compared to investigate the effects of snow and ice. Physical-Chemical Properties and Degradation Rate Constants of Chemicals. Investigated are the polychlorinated biphenyl (PCB) congeners 28 and 180; the polybrominated diphenyl ether (PBDE) congeners 47 and 209; R-hexachlorocyclohexane (R-HCH), hexachlorobenzene (HCB), and the herbicide dacthal. They were chosen because of their environmental relevance (they are toxic, persistent, and have potential for LRT) and because they cover a wide range of physicochemical properties: log KOW ranges from 3.81 (RHCH) to 7.15 (PCB180), log KAW from -4.04 (dacthal) to -1.51 (HCB); and log KCA varies between -2.66 (HCB) and 4.69 (PBDE209). KOW is the octanol-water partition coefficient,

KAW is the air-water partition coefficient, and KCA is the partition coefficient between snow or surface ice and air. KCA is calculated with the polyparameter linear free energy relationship (pp-LFER) from ref 28. The discussion in ref 28 shows that sorption calculated from KCA is considerably stronger than adsorption to the surface of a layer of subcooled water. Physicochemical properties and degradation rate constants of the investigated chemicals are summarized in Tables SI-1 to SI-4 in the SI. They are temperature dependent and differ between zones and seasons. In CliMoChem, the snowflake-air partition coefficient, KSFA, the partition coefficients between bulk snow/ice and bulk air, KSA and KIA, and the partition coefficients between bulk snow/ice and meltwater, KSMW and KIMW, are calculated from KOW, KAW, and KCA as described in Section 2 in the SI. This is necessary because the overall sorptive capacity of bulk snow and surface ice depends on the content of particles, air, and water in snow/ice. Interpretation Procedure. The interpretation of the results includes short-term and long-term results and focuses on zones 1-4 in the northern hemisphere because transport to the southern hemisphere is slower than mixing within the northern hemisphere. We first investigate the fate of chemicals in snow by analyzing results obtained in scenario 2. In particular, we evaluate seasonal mass fluxes of chemicals, Fijl (t/season), which represent the entire amount of chemical transferred into or lost from compartments during a season:

Fijl )

1 tend

∫

tend f (t) t)0 ijl

dt )

1 tend

∫

tend

t)0

kijl‚cij(t)‚Vij dt

(1)

where a chemical mass flux, f (t/d), of process l in zone i and compartment j is integrated over time (tend is the length of a season, 90 days). V, k, and c are volume (m3), rate constant of process l (d-1), and chemical concentration (kg/m3), respectively, in compartment j and zone i. Results from scenario 1 and scenario 2 are compared to understand the effects of snow and ice on the mass balances of chemicals. The difference of the seasonal mass fluxes to and from compartment j in zone i is displayed in Figures 1 and 2. Negative values represent larger mass fluxes of output processes in scenario 2 (Fijl_S2Out > Fijl_S1Out) or larger mass fluxes of input processes in scenario 1 (Fijl_S1In > Fijl_S2In). Positive values indicate larger mass fluxes of input processes in scenario 2 (Fijl_S2In > Fijl_S1In) or larger mass fluxes of output processes in scenario 1 (Fijl_S1Out > Fijl_S2Out).

Results and Discussion The effects of snow and ice on the environmental fate of chemicals are caused by (i) filtering of chemicals from the atmosphere by vapor scavenging by snow; (ii) enhanced revolatilization due to the small storage capacity of the snow compartment; (iii) transport of chemicals from air to soil or water by snowmelt or end-of-season transfer; and (iv) inhibition of the exchange between air and snow-covered compartments. First, we analyze main deposition and removal pathways of chemical to and from snow and surface ice in winter. Fate of Chemicals in Snow. In the northern hemisphere, between 14% (PCB28, minimum value) and 55% (R-HCH, maximum value) of the total amount initially released to air is deposited to snow in season 1. Deposition pathways include vapor scavenging by snow, dry and wet particle deposition, and dry gaseous deposition. The dominant deposition pathway to snow is determined by the particle-bound fraction in air, φair, and the snowflake-air partition coefficient, KSFA, of the chemicals. The positive values in Figure 1A-C show that the relative importance of deposition pathways to snow in zones 4 VOL. 41, NO. 17, 2007 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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FIGURE 1. Seasonal mass fluxes in season 1 to and from snow in zones 4 (A) to 2 (C), and to and from ice in zone 1 (D). In panels A and D, the scale is 1 order of magnitude smaller than that in panels B and C. The sequence of panels is clockwise.

FIGURE 2. Zone 3 and season 1: Differences of input and output fluxes (t/season) between scenario 1 and scenario 2 for air (A), vegetation (B), and vegetation-covered soil (C). (subtropical) to 2 (boreal) does not change for chemicals with very low affinity for particles and snowflakes (HCB and PCB28, mainly deposited by dry gaseous deposition) and highly particle-bound chemicals (PBDE209, mainly removed from air by particle scavenging by snow). For the other compounds, particle deposition and vapor scavenging by snow becomes increasingly important from zone 4 to zone 6194

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1. R-HCH and dacthal are not sorbed to aerosol particles in the air but have considerably higher KCA than HCB and PCB28. Therefore, vapor scavenging by snow is particularly important for these two compounds. After deposition, between 73% (PBDE209) and 99% (HCB) of the total amount of chemical transferred to snow in the northern hemisphere is removed from the snow compart-

ment by re-volatilization, meltwater runoff, or end-of-season transfer (negative contributions in Figure 1A-C). Temperature is the main parameter influencing the removal pathways from snow by determining the meltwater runoff velocity. Therefore, most chemicals show a zonally dependent pattern in the relative importance of the different removal pathways, except for chemicals having a very low or a very high affinity for bulk snow; these compounds re-volatilize (HCB and PCB28) or remain in the snow compartment till the end of season 1 (PBDE209). For PCB180, R-HCH, dacthal, and PBDE47, Figure 1A shows that in zone 4 (subtropical), where meltwater runoff velocity is high (0.01 m/d), runoff with meltwater is the main removal process. In zone 2 (boreal), in contrast, meltwater runoff velocity is zero in season 1 and the chemicals are removed only by end-of-season transfer when the mass of the snowpack is reduced at the transition from season 1 (winter) to season 2 (spring) (Figure 1C). When meltwater velocity is low (0.002 m/d in zone 3 and season 1), the magnitude of the bulk snow-meltwater partition coefficient, KSMW, determines whether chemicals with medium to high affinity for bulk snow are removed from snow by meltwater (R-HCH and dacthal, log KSMW < 0) or remain in the snow compartment till the end of season 1 (PCB180 and PBDE47, log KSMW > 0); see Figure 1B. Figure 1A-C further indicates that re-volatilization is an important removal pathway in zones 4 to 2. In CliMoChem, mass transfer coefficients for transfer across the snow-side resistance in the snow-air interface are 0.8 m/d and 0.02 m/d for HCB and R-HCH, respectively. Herbert et al. (11) investigated diffusion of chemicals in fresh and aged snow in a snowfield in northern Norway. For fresh snow, division of their measured diffusivities by the depth of the fresh snow yields mass transfer coefficients in snow of 10 m/d for HCB and 1 m/d for R-HCH. These values are 12 and 52 times higher than the corresponding coefficients calculated in CliMoChem. This indicates that the pp-LFER approach tends to overestimate sorption of chemicals to bulk snow as discussed in ref 11. Also the storage capacity of bulk snow varies considerably among the different latitudinal zones. In zones 3 (temperate) and 4 (sub-tropical), for all investigated chemicals, less than 10% of the total zonal mass is stored in snow in the winter. Accordingly, snow is an important transfer medium for chemicals after deposition in these zones. In zone 2 (boreal), in contrast, snow is a main storage compartment for all investigated chemicals except for HCB and PCB28; between 22% (PBDE209) and 30% (R-HCH) of the total mass in zone 2 is stored in the snow compartment in winter. For chemicals with high KOA values, the storage capacity of snow is determined by the organic matter content. In the model, fractions of PCB28 and PCB180 associated with particles in snow are 82% and 98%, respectively. Gustafsson et al. measured dissolved and particulate concentrations of individual PCB congeners in snow samples from the Barents Sea marginal ice zone (29). In these measurements, up to 84.5% and 98.7% of PCB28 and PCB180, respectively, were particle associated. The values calculated in CliMoChem agree well with these results. Fate of Chemicals in Surface Ice. In zone 1, between 1% (HCB) and 5% (R-HCH) of the total mass initially released in zone 3 is deposited to surface ice in the first simulation season. For chemicals having a very low affinity for snowflakes (HCB) or a very high affinity for particles in air (PBDEs), deposition with particles is the main pathway into surface ice (Figure 1D). Chemicals with a medium to high affinity for snowflakes and a medium to low affinity for particles in air (PCBs, R-HCH, and dacthal) are mainly deposited to ice by vapor scavenging by snow (Figure 1D). For all chemicals investigated, transfer from surface ice to deep ice is the dominant removal pathway in zone 1 (Figure

1D). Between 46% (HCB) and 62% (dacthal) of the total amount of chemical deposited to surface ice is transferred to deep ice. At the end of season 1, between 15% (HCB) and 62% (R-HCH) of the total amount of chemical in zone 1 is stored in ice (surface ice and deep ice). Finally, Figure 1 shows that dry gaseous exchange between air and surface ice is not important in zone 1, whereas gaseous exchange contributes significantly to deposition to and removal from snow in zones 4 to 2. In CliMoChem, a twofilm model describes the gaseous exchange between air and snow or surface ice. The total transfer resistance is given by the air-side resistance and the snow or ice-side resistance connected in series; the latter consists of the resistance in water and air-filled pores in snow or ice connected in parallel. Diffusion through air-filled pores was identified as the ratelimiting step for the gaseous exchange between air and snow in an earlier study (30). In CliMoChem, the volume fraction of air in snow is 2 orders of magnitude higher than in ice and a wind pumping factor (see Section 2.1 in the SI) increases diffusion in snow. Therefore, diffusion through the snow boundary layer is 4 orders of magnitude faster than through the ice boundary layer resulting in larger mass fluxes of dry gaseous deposition and re-volatilization in snow. Effects of Snow in Mid Latitudes (Zone 3). Snow and ice also change the mass balance of chemicals in other environmental media. The following analysis focuses on the effects of snow on air, vegetation, and soil in winter in zones 3 and 2 and on the impact of ice on air and seawater in winter in zone 1. Effects in low latitudes (zone 4) are not very strong and are mainly caused by increased inflow of chemicals from zone 3. Seasonal mass fluxes are given in Figure 2 for zone 3 and in Figures SI-5 to SI-7 for the other zones. Figure 3 shows the effect of snow or ice on the chemicals’ masses at the end of season 1 in all compartments in zones 4 to 1. In zone 3 and season 1, snow covers mainly vegetation and vegetation-covered soil and accounts for 35% of the total surface area. In the model version with snow and ice, net deposition from air to surface media decreases for all chemicals except R-HCH. For PCB180, dacthal, and PBDE47 it is visible in Figure 2A that vapor scavenging by snow is more efficient than the sum of the deposition processes in the model version without snow and ice. However, because of more pronounced re-volatilization, net deposition is lower than that in scenario 1 and the chemicals’ concentrations in air increase (Figure 3A). Re-volatilization is enhanced because the snow-air partition coefficients of the chemicals are several orders of magnitude smaller than their soil-air and vegetation-air partition coefficients. R-HCH, which is relatively volatile, persistent, and has high affinity for snow, is the only compound for which vapor scavenging by snow is so efficient that net deposition increases and concentration in air decreases. An important implication of these changes in net deposition is that for all chemicals except R-HCH net transport from zone 3 (temperate) to zone 2 (boreal) decreases (in zone 2, because of the extensive snow cover, net deposition is also lower in scenario 2) whereas net outflow from zone 3 to zone 4 (subtropical) is stronger than that in scenario 1. Again, only R-HCH is different in that it shows reduced transport to the south and slightly increased transport to the north (Figure 2A). In zone 3, snow covers 65% of vegetation and vegetationcovered soil in season 1, inhibiting transfer of chemicals between these compartments and air. Dry gaseous deposition to vegetation is reduced for all chemicals (negative contributions in Figure 2B). Consequently, degradation in and revolatilization from vegetation also decrease (positive contributions in Figure 2B). In scenario 2, the amount of chemical in vegetation is between 31% (PBDE47) and 98% (HCB) of the amount in scenario 1 (Figure 3B). VOL. 41, NO. 17, 2007 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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FIGURE 3. Masses in different environmental media at the end of season 1 in scenario 2 divided by corresponding masses in scenario 1 for zones 4 (panel A) to 1 (panel D). In vegetation-covered soil, transport of chemicals from air to snow to soil via snowmelt or end-of-season transfer increases the mass of PCB180, R-HCH, dacthal, and PBDE47 in zone 3 in winter (positive contributions in Figure 2C). In scenario 2, their amount in vegetation-covered soil is between 1.08 (PCB180) and 1.83 (R-HCH) times higher than in scenario 1 (Figure 3B). Inhibition of the exchange between air and snow-covered compartments is the main effect on the mass balance of HCB, PCB28, and PBDE209 in soil; amounts in scenario 2 are 48% (PCB28) to 78% (PBDE209) of amounts in scenario 1 (Figure 3B). Effects of Snow in High Latitudes (Zone 2). In zone 2, 55% of the surface area is snow-covered in winter. Inhibited deposition to snow-covered compartments, filtering of chemicals by vapor scavenging by snow, and enhanced revolatilization determine the mass balance of chemicals in air in zone 2 (Figure SI-5A). As in zone 3, amounts in air of all chemicals except R-HCH are higher than in scenario 1 (Figure 3C). In zone 2, inhibition of the exchange with air is the dominant effect of snow on the mass balance of all chemicals in soil and vegetation (negative contributions in Figure SI5B/C). Amounts in soil are between 27% (HCB) and 97% (R-HCH) of those observed in scenario 1 (Figure 3C). Mass in vegetation is only 8% (R-HCH) to 15% (PCB28) of the mass in vegetation in calculations without snow and ice (Figure 3C). Effects of Ice in the Arctic (Zone 1). The main effect of ice in zone 1 is inhibition of the exchange between air and ice-covered compartments, mainly seawater (Figure SI-7B). Ice covers 90% of ocean water in zone 1 in winter and the amount of chemicals in ocean water reaches only 7.7% (RHCH) to 21.3% (dacthal) of the mass in scenario 1 (Figure 3D). As in the other zones, net deposition from air to the ground is reduced and amounts of chemicals in air at the end of season 1 are larger than those in scenario 1 for all investigated chemicals except R-HCH (Figure 3D). To investigate the long-term effect of ice in the Arctic, we evaluate results from a model simulation over 15 years. In scenario 1 and during the first year, the total amount of chemical in zone 1 is dominated by the amount in water. In 6196

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the long term, PCB180, PBDE47, and PBDE209 accumulate in the vegetation-covered soil containing more than 95% of their total regional mass after 15 years. HCB and PCB28, in contrast, are evenly distributed between water and vegetation-covered soil several years after the pulse release, and the water-soluble compounds R-HCH and dacthal remain mainly in the water; see Figure 4A for R-HCH. In scenario 2, in contrast, the amount of chemicals in zone 1 is dominated by the mass in surface ice or, in the case of HCB, in air during the first few seasons when transport in air is dominant. Then, inflow into zone 1 in water becomes more important and the total amount of chemicals in zone 1 is increasingly influenced by their mass in water (beneath the ice cover). Finally, it is the amount of chemical deposited to deep ice that determines the total mass of chemicals in polar regions. This long-term effect of ice in northern polar regions is similar for all investigated chemicals and is illustrated in Figure 4 for the example of R-HCH. For all investigated chemicals, deposition to deep ice results in an accumulation of chemicals in polar zones. Figure 4C shows the mass fraction of the amount of compound stored in surface and deep ice in zone 1 after 15 years. Longterm accumulation is highest for R-HCH, which is relatively volatile and has a long half-life in air and a high affinity for snow/ice. Other chemicals are either relatively rapidly degraded in air (PCB28, dacthal, PBDE47) or removed from the atmosphere by deposition before they reach zone 1 (PCB180 and PBDE209), or have a low affinity for snow (HCB). Environmental Significance. The process descriptions used in our modeling study are generally consistent with findings from other modeling studies and with field data (11, 18, 19, 30). In particular, the dominant pathways of PCB28, PCB180, R-HCH, PBDE47, and PBDE209 in snow are in good agreement with the results presented by Daly and Wania (18). There was some disagreement between mass transfer coefficients of HCB and R-HCH measured in snow in the field and the values used in the model, which indicates that the snow-air partition coefficients calculated with the ppLFER from ref 28 may overestimate sorption of SOCs to snow. More measurements of the sorption of organic chemicals to

FIGURE 4. Temporal trends of r-HCH in zone 1 in scenarios 1 (panel A) and 2 (panel B); C: fraction of amount initially released that is accumulated in ice in zone 1 after 15 years. snow are needed to determine more exactly the type of this interaction. A comparison of the model results to measured concentrations has not been possible because sufficiently accurate emission inventories for most chemicals measured in snow or ice in the field are not available. However, the singlepulse release used in our investigation does provide insight into the mechanisms determining the mass balances of the chemicals in a multimedia box model (24). Therefore, our analysis still reveals several important trends. A key finding is that for all chemicals except R-HCH net deposition from air to the ground decreases because significant amounts of the chemcials re-volatilize after deposition via snow scavenging. This changes the LRT of these chemicals: transport to the north is less effective because of the repulsive effect of snow in zones 3 to 1, whereas transport to the south is more effective (“southward shift”). This southward shift is reflected by reduced amounts of these chemicals in zone 1; it is most pronounced for the relatively volatile compounds HCB and PCB28. An interesting follow-up question is to what extent the southward shift influences the global fractionation pattern of SOCs. PCB180 and PBDE47 have a strong affinity for particles in air and in snow. Snow in zone 2 (boreal) stores about 25% of the zonal mass of these chemicals in winter. In scenario 2, heavy PCBs and PBDEs show higher amounts in soil in zone 3 (end-of-season-transfer after snowmelt) but lower amounts in soil in zone 2 and water in zone 1 than in scenario 1 (soil and water covered by permanent snow and ice). R-HCH is the only chemical for which net deposition in scenario 2 is higher than that in scenario 1. Because R-HCH has a relatively low KOW and KOA but still a high KCA, its fraction in the gas phase is high and vapor scavenging by snow is very effective; also storage in snow is effective. R-HCH does not show the southward shift but exhibits slightly increased transport to the north and reduced transport to the south. The high affinity for snow of R-HCH also implies that amounts of R-HCH in soil are higher in zones 3 and 2 (meltwater runoff and end-of-season transfer) and that relevant amounts are stored in snow and ice in zones 2 and 1. Similar to R-HCH, dacthal has low KOW and high KCA, but is less persistent. Accordingly, very effective vapor scavenging by snow and

transfer to soil with meltwater is observed in zone 3. Both southward and northward transport of dacthal are reduced because of this strong net deposition. The seven different chemicals illustrate the variety of effects by which snow and ice influence the environmental fate of SOCs. A global distribution model reflecting different effects in various latitudinal zones and their interplay is an essential tool for the analysis of the complex effects of snow and ice on the environmental fate of SOCs.

Acknowledgments We gratefully acknowledge financial support by the Swiss National Science Foundation. We thank Matthew MacLeod for helpful comments.

Supporting Information Available Information on snow and ice properties, environmental processes regarding snow and ice, physical-chemical properties, and degradation rate constants of investigated chemicals. This material is available free of charge via the Internet at http://pubs.acs.org.

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Received for review December 4, 2006. Revised manuscript received June 15, 2007. Accepted June 20, 2007. ES062873K