Environ. Sci. Technol. 2003, 37, 1344-1351
Assessing the Potential of Persistent Organic Chemicals for Long-Range Transport and Accumulation in Polar Regions FRANK WANIA* Division of Physical Sciences, University of Toronto at Scarborough, 1265 Military Trail, Toronto, Ontario, Canada M1C 1A4
A zonally averaged global distribution model is used to identify chemical partitioning properties and emission scenarios that favor enrichment in Arctic ecosystems. An immediate and a long-term Arctic Contamination Potential (ACP) are defined as the fraction of the total amount in global surface media that is in the Arctic after 1 and 10 years of steady emissions with a generic zonal distribution. Simulations for a two-dimensional “space” of hypothetical chemical property combinations indicate that the ACP of a perfectly persistent organic chemical is determined by a complex set of processes but tends to be higher for two combinations of partitioning properties: relatively volatile (log KOA < 9) and water soluble (4 > log KAW > -0.5) substances and substances which are semivolatile (log KOA 6.5-10) and relatively hydrophobic (log KAW > -3). Very volatile chemicals with log KOA < 6.5 and log KAW > -0.5 remain in the atmosphere even under Arctic temperature conditions, whereas very involatile chemical with a log KOA > 10 are efficiently and irreversibly deposited with atmospheric particles before reaching the Arctic. The two sets of partitioning characteristics with elevated ACP overlap in the range 6.5 < log KOA < 10 and -0.5 > log KAW > -3, which also corresponds to a log KOW range of 5 to 8, i.e., comprises substances with a potential for bioaccumulation. Organic contaminants known to accumulate in the Arctic, such as hexachlorobenzene and the lighter PCBs, indeed have such partitioning properties. Marine currents contribute significantly to the long-range transport of chemicals with log KAW < -2. Emissions to surface media greatly reduce the ACP, except for chemicals with octanol/water partition coefficients log KOW < 5. The ACP of chemicals with different partitioning properties is sensitive to different sets of environmental parameters, reflecting the different pathways which determine their global transport behavior. The ACP of most chemicals is sensitive to the temperature dependence of the partition coefficients, temperature, atmospheric mixing coefficients, and sea ice cover.
Introduction In the context of the recent Stockholm Convention on Persistent Organic Pollutants (POPs) the need arises for identifying and classifying chemicals as “being subject to * Corresponding author phone: (416)287-7225; fax: (416)287-7279; e-mail:
[email protected]. 1344
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long-range transport” (LRT) (1, 2). The requirement for predicting long range transport potential (LRTP) is clearly prompted by the occurrence of many POPs in the Arctic environment far from any sources and the desire to identify chemicals that may have the potential to experience a similar transport to remote regions. Early on multimedia mass balance models have been identified as playing an important role in that context. The purpose of the models is to take into account the influence of a chemical’s environmental phase distribution on its ability to be transported over long distances. The environmental phase distribution is influenced by a large number of factors related to both environmental and chemical characteristics and is not necessarily intuitive or easily comprehended. A multimedia model provides a tool to take most of these factors into account in a transparent, objective, and reproducible manner (3). Accordingly, there has been intense scientific activity within the past few years aimed at developing model-based approaches to LRTP assessment (4). These approaches usually take the form of calculating a chemical’s characteristic distance (5-7) or spatial range (8, 9). The process of atmospheric LRT to remote regions can be seen as consisting of three distinct steps (Figure 1). First, in source regions the chemical must reach the atmosphere in significant quantities, either by being directly emitted into air or by evaporating into the atmosphere from the medium to which it has been emitted (step A1). Second, the chemical must be transportedsusually over a considerable distances through the atmosphere to the remote region (step A2). In order for the chemical to survive this long journey, it must be sufficiently persistent in the atmosphere, with the actual level of persistence required depending on the distance to be traveled and the atmospheric travel time. Last, the transported chemical must have the potential to be significantly deposited in the remote regions in order to have a notable impact on the local ecosystem (step A3). Alternatively, the chemical can undertake the long distance migration with ocean currents or major rivers, which requires it to be sufficiently water soluble and very persistent in the aqueous phase (step B). Most existing techniques for LRT assessment, in particular those relying on the calculation of a characteristic travel distance, have focused on step A2 of the overall process by estimating how atmospheric degradation and deposition limit the LRT of a substance in the air. Step A1 is bypassed by only considering chemicals emitted into the atmosphere or by defining an effective travel distance (7). Most current approaches to LRTP assessment are also restricted to transport in the atmosphere, although Beyer et al. (7) showed that the very same principles can be applied to assess LRTP in the oceans. Beyer and Matthies (10) presented an approach that it is capable of assessing the LRTP in coupled air-ocean systems, suggesting that the LRTP in such systems is higher than if transport in each of the two phases is considered separately. The spatial range approach by Scheringer (8, 9) accounts for oceanic transport and for emissions into media other than air. The need for deposition to the remote ecosystem (step 3C) is virtually always ignored, as is the variability of the global environment, especially temperature, and the impact that can have on LRT and accumulation in remote regions. An exception is the study by Scheringer et al. (11), who derived a cold condensation potential describing a chemical’s tendency to move to, and accumulate in, polar regions. The cold condensation potential indicates whether a chemical’s concentration profile increases toward the poles and is calculated with the CliMoChem model as the ratio of 10.1021/es026019e CCC: $25.00
2003 American Chemical Society Published on Web 02/27/2003
FIGURE 1. Schematic of the various steps involved in the accumulation of organic chemicals in remote regions. the concentration in the polar zone and the minimum concentration between equator and polar zone. Here an alternative approach to assessing the LRTP of organic chemicals is presented that explicitly takes into account the potential to deposit and accumulate in Arctic regions. An existing global multimedia distribution model is used to examine the effect of a chemical’s properties and mode of emission on its capability to establish elevated levels in Arctic surface media. Based on the results we seek to identify those chemical property combinations and emission scenarios which conspire to make a chemical most susceptible to LRT and deposition in polar regions. In principle, two processes can lead to a relative enrichment in the Arctic. The strong temperature dependence of gas phase/condensed phase partitioning together with the spatial temperature gradients on a global scale can lead to the enrichment of highly persistent and semivolatile chemicals in cold regions by a process which has been termed “cold condensation” (12, 13). The other mechanism of relative enrichment is the climate-dependent persistence of organic chemicals. A chemical that is being degraded in warm environments, yet preserved in cold regions, will eventually show higher concentrations in the cold regions (14, 11). It is possible to separate these two mechanisms by assessing the potential for Arctic contamination for perfectly persistent chemicals, for which the second mechanism is not occurring. In this contribution we will be restricting the discussion to the “cold condensation” effect and investigate the impact of a chemical’s partitioning properties on its potential for Arctic contamination. The impact of a chemical’s persistence on its relative enrichment in Arctic latitudes will be addressed at a later stage.
Methods The Global Distribution Model. The calculations presented in this study rely on Globo-POP, a zonally averaged multimedia model of the global fate of persistent organic pollutants (15, 16). This model divides the global environment into 10 latitudinal bands or “climate zones” (Figure 2), each consisting of nine compartments representing the atmosphere (in four vertical layers), two different types of soil (cultivated and uncultivated), freshwater and freshwater sediments, and the surface ocean. The model calculates the interphase transfer of chemical in addition to meridional transfer of chemical in the atmosphere and surface ocean. Loss processes considered include the degradation of chemical in all media, freshwater sediment burial, and transport of chemical to the deep sea. A more detailed description of the model is provided elsewhere (15, 16). It has previously been employed
to simulate the long-term global fate of R-hexachlorocyclohexane (17-19) and several polychlorinated biphenyl congeners (20). The Arctic Contamination Potential. The aim is to identify combinations of chemical properties and emission scenarios that result in a chemical being enriched in Arctic ecosystems. To express this tendency of a chemical quantitatively an Arctic Contamination Potential was defined as the fraction of the total amount in the global environment that is present in Arctic surface media (all the media except the atmosphere). The Arctic is defined as Globo-POP’s northernmost zone, the boundaries of which are based on a climate map of the world (15) (Figure 2). An equivalent definition may be used to express an Antarctic Contamination Potential. This definition excludes the amounts present in the polar atmosphere. Highly volatile chemicals may be transported to polar regions without difficulty, but since they may never deposit to the surface their inclusion in the accumulation parameter would provide misleading results. Globo-POP is a dynamic model allowing for changes in emissions and environmental parameters over time. Emissions also may occur into different zones and media. The ACP as defined above is thus not a fixed quantity, but a function of time that is strongly dependent on where, when, and for how long emissions took place. To make a meaningful comparison between chemicals, one or more generic emission scenarios representative of the use of many chemical substances need to be defined. Since the majority of contaminants reach the environment through human activity, it appears reasonable to assume that emissions tend to be highest in densely populated areas and lowest in uninhabited regions. To provide a first approximation, it was assumed that the rate of chemical emission is linearly correlated with population. The zonal distribution of population in Table 1 was determined from a UNEP/GRID database (21). Almost 90% of the world’s population lives in the Northern Hemisphere, mainly in the three zones (NTemperate, N-Subtropic, and N-Tropic) nearest to the equator. Assuming that the zonal distribution of the emissions is equivalent to the zonal distribution of the population neglects the fact that people in industrialized nations have considerably different consumption patterns than people in developing nations. It was further assumed that there is continuous release of chemical into one of the three media atmosphere, freshwater or cultivated soil, resulting in three generic emission scenarios. The ACP after 1 year of continuous release, starting on a January 1st, referred to as ACP1, is a measure of the immediate potential for enrichment in the Arctic, whereas the ACP10, established after 10 years of continuous release, quantifies the long term or delayed contamination potential. The Chemical Space. Instead of calculating the ACP for a series of real chemicals, the ACP was calculated for a large number of hypothetical chemical properties combinations. To characterize a particular chemical, the Globo-POP model requires the input of the three coefficients describing equilibrium partitioning between air, water, and octanol (KOW, KAW, KOA) at 25 °C as well as their temperature dependence (expressed as internal energies of phase transfer ∆AWU, ∆OAU, ∆OWU), degradation half-lives in five different media, a degradation rate with OH radicals in air, and six activation energies. Considering only perfectly persistent chemicals (PPCs) at this stage eliminates the need to specify degradation half-lives and activation energies. It is further assumed that KOW can be calculated from KOA/KAW, which implies that the mutual solubility of octanol and water is assumed to have no impact on the partitioning properties of the chemical. Finally, the temperature dependence of the partition coefficients is assumed to be the same for all chemical property combinations, specifically the energies of phase transfer VOL. 37, NO. 7, 2003 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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FIGURE 2. Zonal subdivision of the Globo-POP model, based on a climatic map of the world (31).
TABLE 1. Zonal Distribution of Global Population (21) zone
population (%)
N-Polar N-Boreal N-Temperate N-Subtropic N-Tropic S-Tropic S-Subtropic S-Temperate S-Subpolar S-Polar
0.18 3.43 21.68 34.15 29.62 8.81 2.06 0.07 0.01 0
∆AWU, ∆OAU, and ∆OWU are 60, -80, and -20 kJ‚mol-1, respectively. These are typical values for POPs (22), but it should be cautioned that many chemicals have quite different thermodynamic characteristics. The number of chemical properties is thus reduced to KAW and KOA, making it possible to map the ACP results in a two-dimensional “chemical space” (3). Implicit in this approach is the assumption that the environmental phase distribution of a chemical is well described by the empirical relationships based on KOW and KOA, that are implemented in the model, for example that KOC equals 0.35‚KOW (23). Whereas that is reasonable for the nonpolar organic substances for which these relationships have been developed originally, it is less likely to be fulfilled for more polar substances (24). When calculating the fate of hypothetical chemical property combinations this is only an apparent problem, as a hypothetical chemical with a particular KOW can simply be considered to stand for a chemical with a KOC of 0.35‚KOW. It is important however to be aware of this issue when comparing the physical chemical properties of real chemicals with the hypothetical property combinations used in this study. A more serious question is whether the model appropriately describes all the environmental fate processes of relevance for a chemical with particular partitioning properties. The Globo-POP model was designed for persistent organic pollutants, a fairly select group of nonpolar chemicals with intermediate volatility. POPs are multimedia chemicals, and Globo-POP thus includes fate processes relevant for chemicals present in the gas phase, dissolved in water, and sorbed to organic matter. However, it is still possible that for some chemical property combinations toward the fringe of the investigated partitioning space the fate descriptions developed for POPs are insufficient. For example, for very water soluble substances the assumption of steady precipitation used in Globo-POP is inappropriate (25). For more 1346
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polar substances, sorption to solids other than organic matter may become important. ACP1 and ACP10 were calculated for all log KAW-log KOA combinations within the ranges 3 e log KOA e 14 and -4 e log KAW e 3 using logarithmic increments and assuming either emissions to air, freshwater, or cultivated soil. Figure 3 shows the two-dimensional “chemical space” defined by these log KOA-log KAW combinations. The partitioning properties defining the axes of maps such as shown in Figure 3 are at 25 °C, although they are of course allowed to vary with temperature in the global fate calculations. Not all of the combinations within that space actually occur. Notably, chemicals with log KAW greater than -1 are unlikely to have a very high log KOA value (upper right-hand corner). Different sections of the space, delineated by different colors in Figure 3, identify chemicals with particular partitioning preferences. Chemicals in the upper left-hand corner of the plot (red) tend to partition mostly into the gas phase, those in the lower left-hand corner (blue) mostly into the aqueous phase, and those in the lower right-hand corner (yellow) tend to partition mostly onto atmospheric particles, soils, and other solid phases. Chemicals which are located “centrally” in Figure 3 (green) have the ability to partition into all three phases to a notable extent and are characterized as semivolatile or multimedia environmental chemicals. These include the PCBs, the PCDD/Fs, and smaller PAHs. The Globo-POP model failed to calculate ACPs for highly water soluble substances with a log KAW < -4, because the process of precipitation scavenging is occurring too fast for the minimum step size of the numerical solution of 1 h. Similarly, very volatile substances with a log KOA < 3 can neither be described with Globo-POP, because of the high rates of atmosphere-surface exchange of such chemicals. This is not considered a serious limitation, as the LRTP of chemicals to the extremes of the chemical space is better investigated with media specific modeling approaches, i.e., the global transport behavior of very volatile substances and of substances sorbed to atmospheric particles should be investigated with atmospheric dispersion models, whereas that of highly water soluble, nonvolatile substances is better described with oceanic transport models. Sensitivity Analysis. For five selected physical-chemical property combinations, additional calculations were performed to explore the effect of the zone of emission and the choice of environmental input parameters. The selected property combinations include a particle-sorbed chemical (A, log KAW ) -4, log KOA ) 12), a water-soluble chemical (B, log KAW ) -4, log KOA ) 5), a relatively volatile and water soluble chemical (C, log KAW ) -2, log KOA ) 3), a multimedia chemical (D, log KAW ) -2, log KOA ) 7), and a very hydrophobic, semivolatile chemical (E, log KAW ) 1, log KOA
FIGURE 3. Primary environmental compartments for hypothetical chemicals defined by their partitioning properties log KAW, log KOA, and log KOW. The distribution between media was calculated with the Globo-POP model assuming 10 years of steady emissions of perfectly persistent chemicals into air, water, and soil (1/3 each) using a zonal emission distribution matching that of the human population. Chemicals with a log KOW > 10 are unlikely to exist. The white circles locate the five chemicals used in the sensitivity analysis within that chemical space. Closed curves indicate the partitioning properties of the chlorobenzenes (CBzs), polychlorinated biphenyls (PCBs), polychlorinated dibenzo-p-dioxins (PCDDs), and dibenzofurans (PCDFs). ) 7). The location of these chemicals in the chemical space is indicated in Figure 3. To explore the effect of emission location, emissions were in turn assumed to take place into one of the 10 zones only, instead of following the zonal distribution of the human population. To investigate the sensitivity of ACP results to the environmental input parameters and default values for the energies of phase transfer, these parameters were increased by 10%, and the resulting effects of these changes on ACP1 and ACP10 evaluated. This was done for all three modes of emission. To limit the number of necessary calculations the parameters were increased in all 10 model zones at the same time. Sensitivity to a parameter X was calculated using
SX ) [(ACP - ACPref)/ACPref]/[(X - Xref)/Xref] ) [(ACP - ACPref)/ACPref]/0.1 where ACPref refers to the ACP using the default parameters Xref.
Results Figure 4 displays the calculated ACP for perfectly persistent chemicals as a function of log KOA and log KAW, with emissions occurring either entirely into air (graphs in the left column), water (middle column), or soil (right column). The graphs display ACP1 (graphs in top row) and ACP10 (second row) in percent. A red color in these graphs indicates a high potential for accumulation in the Arctic surface media; a green color indicates a low potential. The ratio between ACP10/ACP1, indicating which chemicals have the largest increase in ACP over time, are shown in Figure S1 in the Supporting Information. Ratios of ACPs obtained with different modes of emission are shown in Figures S2 and S3. The results of the sensitivity analysis are summarized in Table S1 in the Supporting Information. Selected results for the sensitivity of ACP10 assuming emission to the atmosphere are shown in Table 2. The influence of the zone of emission for ACP10 is shown in Figure 5. The diagrams in Figure 4 constitute contour maps, identifying where the ACP is very sensitive to changes in
partitioning properties. Steep “slopes” on these maps, i.e., closely spaced contour lines, indicate threshold values where large changes in ACP occur for small changes in partitioning coefficients. A horizontal threshold indicates a change with air-water partitioning properties (with water soluble substances at the bottom), a vertical threshold indicates a change with octanol-air partition coefficients (with volatile substances on the left), and a diagonal threshold indicates a dependence on the octanol-water partition coefficient (with hydrophobic substances on the upper right). All three types of thresholds occur, indicating that the potential for Arctic contamination is the result of a complex interaction of processes, which depend on the partitioning into air, water, and organic phases.
Discussion Immediate Potential for Arctic Contamination. The ACP1 for PPCs ranges from 0 to 1.2% (Figure 4A-C). For reference, the Arctic zone in Globo-POP comprises 5.2% of the total global surface area and only 0.18% of the hypothetical global emissions are occurring in that zone. The enrichment that can be achieved by nonpersistent chemicals is much higher but will not be discussed here. Most air-emitted PPCs have an ACP1 between 0.8 and 1.2%. Only partitioning properties typical of very volatile and very involatile chemicals have lower ACP1. Volatile PPCs with a log KOA < 6.5 and a log KAW > -0.5, in the upper left corner of the partitioning space and beyond, are found predominantly in the atmosphere (see Figure 3). Their potential for accumulation in the Arctic is limited by failure to undergo step A3 (Figure 1), i.e., to deposit to the Earth’s surface even at the low-temperature prevalent in the Arctic. The chlorofluorocarbons are examples of such chemicals. PPCs with a log KOA g 12, on the right edge of the partitioning space and beyond, occur in the atmosphere mostly associated with particles and their ACP1 is limited by efficient particle-associated deposition processes, i.e., by their inefficiency in undergoing step A2 (Figure 1). The immediate Arctic contamination potential is reduced considerably if emission occurs into water or soil (Figure 4B,C), emphasizing the importance of the volatilization step A1 (Figure 1) in limiting atmospheric LRT. Only water-emitted PPCs with a VOL. 37, NO. 7, 2003 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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FIGURE 4. Arctic contamination potential of hypothetical, perfectly persistent chemicals defined by their partitioning properties log KAW and log KOA after 1 (top row) and 10 years (bottom row) of steady emissions calculated with the Globo-POP model using a zonal emission distribution matching that of the human population. Emission is assumed to occur into the atmosphere (left), freshwater (middle), or cultivated soils (right). The diagonal lines indicate a log KOW of 5 and 8, delineating the region of highest bioaccumulation potential.
TABLE 2. Sensitivity of the ACP10 Results to Changes in Input Parameters for Five Hypothetical Perfectly Persistent Chemicals Emitted to the Atmosphere
chemical log KAW/log KOA atmospheric diffusivity terms atmospheric advection terms extent of sea ice cover temperature internal energies of phase transfer diffusive air/water MTC air side Meridional eddy diffusion coefficients in ocean depth of surface ocean precipitation rate dry particle deposition velocity particle scavenging ratio depth of uncultivated soil organic carbon contant in uncultivated soils diffusive soil/air MTC air side water content in uncultivated soil solid phase diffusion coefficient in soils depth of cultivated soil
A particlesorbed -4/12 -2.53 0.06 0.32 0.11 -0.01 0.03 -0.01 -0.26 -0.27 -0.25 -0.04
log KOA < 7 and soil-emitted PPCs with log KOA < 5 are sufficiently volatile to achieve ACP1 over 0.4%. Long-Term Potential For Arctic Contamination. For most property combinations ACP10, the measure of the longterm Arctic Contamination Potential, was larger than ACP1 (Figure S1). This means that most chemicals will take longer than 1 year to be transferred northward. The ACP10 can reach levels as high as 4.5%. The inverted L-shaped region of elevated ACP that already became apparent for ACP1 (Figure 4A) is much more pronounced and well-defined after 10 years of emissions (Figure 4D). The vertical and horizontal bar of that inverted L correspond to PPCs with intermediate KOA 1348
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B watersoluble
C volatile
-4/5
-2/3
-3.20 -0.23 -0.11 0.25 -0.15 -0.08 0.34 0.00 -0.05 -0.01
-0.31 -0.09 -0.92 0.18 -0.09 0.40 0.10 -0.15 -0.02
D multimedia -2/7 -0.32 -0.04 -0.69 0.45
0.31 0.08 -0.12 -0.03
0.05 0.01 0.04 0.03 -0.04 0.04
E hydrophobic semivolatile 1/7 0.04 0.01 -0.01 0.82 1.55 0.01
0.59 0.43 0.24 0.20 -0.13 0.11
and KAW values, respectively. The vertical bar corresponds to hydrophobic (log KAW > -3, log KOW > 6) chemicals with an intermediate log KOA between 7 and 9, whereas the horizontal bar corresponds to relatively volatile (log KOA < 9) and watersoluble (-0.5 > log KAW > -4, log KOW < 6) substances. These semivolatile substances readily undergo air-surface exchange within the environmental temperature range. The former (hydrophobic) group mostly exhibits atmospheric exchange with the terrestrial surface, whereas the latter (water-soluble) group mostly undergoes exchange with the oceans. The two sets of partitioning characteristics with elevated ACP overlap in the range 6.5 < log KOA < 10 and
FIGURE 5. Dependence of the Arctic contamination potential of five perfectly persistent chemicals with different partitioning properties on the zone of emission. Chemical was emitted steadily into the atmosphere of one zone for 10 years. -0.5 > log KAW > -3, which also corresponds to a log KOW range of 5-8. These are typical multimedia chemicals with partitioning properties that allow for efficient exchange with both terrestrial and aquatic surfaces. It is this efficient air-surface exchange that allows for gradual transfer of these chemical to polar regions by means of repeated cycles of deposition and re-evaporation, often driven by seasonal and diurnal temperature changes. This transport process by multiple hops has been termed the “grass-hopper effect” and appears to be most pronounced for chemicals with a log KOA of around 8 and a log KAW of around -2. Less volatile chemicals (log KOA > 9.5) do not volatilize effectively after deposition to either water and soils and thus cannot undergo “multiple hops”. They have to reach the Arctic in one single atmospheric LRT event without ever being deposited along the way. Their ACP10 is thus similar to their ACP1 (Figure S1). Similarly, very water soluble substances (log KAW < -4) will be efficiently retained in the oceans and can neither undergo “grass-hopping”. However, for such substances, long range transport in oceans and rivers (step B in Figure 1) is potentially significant. The importance of LRT by ocean currents is well established for radionuclides (26), and has been found to be significant for the transfer of R-hexachlorocyclohexane to the Arctic in a study relying on the Globo-POP model (18). The combination of partitioning properties corresponding to the vertical bar of the inverted L of elevated ACP10 (hydrophobic, but intermediate volatility) is unusual, but may actually exist for selected synthetic substances such as some cyclic organosilicone compounds (27) or perfluorinated organic substances (28). Such chemicals can occur either in the gas phase or sorbed to solids, but are too water insoluble to partition into water to any significant extent. Their high log KOW may further indicate a potential for bioaccumulation, and it may be worthwhile to search for persistent chemicals with such properties in Arctic ecosystems. Interestingly, Weschler (29) noted more than 20 years ago that poly(dimethylsiloxane)s were among the major organic components in aerosol samples collected at Barrow, AK. A comparison of Figures 3 and 4D shows that highly chlorinated chlorobenzenes and small to intermediate PCBs lie in the partitioning space that displays a particularly high ACP10. These are indeed fairly persistent chemicals that are known to be transported and deposited in Arctic regions in significant quantities.
Influence of the Emission Medium on the Long-Term Potential for Arctic Contamination. The ACP10 of chemicals with a log KOW < 5 is virtually the same if a chemical is emitted into air and water (Figures 4E and S2). These substances are either so volatile that the rate of volatilization from water is not limiting their transfer to the Arctic, and/or they are transported northward in the aqueous phase. More hydrophobic chemicals (log KOW > 5) on the other hand are efficiently retained in source regions when emitted to water, leading to much reduced ACP10 values. In water such chemicals quickly sorb to organic matter and are transferred efficiently to freshwater sediments or the deep sea, thereby preventing wider dispersal. Analogously, chemicals with a log KOA of less than 6 have a ACP10 which is independent of whether they are emitted into air or soils (Figures 4D and S2) because they rapidly volatilize from soils. Less volatile chemicals (log KOA > 6) are much more efficiently retained in the soils into which they had been emitted and have again greatly reduced ACP10. The fact that air-emitted chemicals with a log KOA between 7 and 9 were found to undergo rapid air-soil exchange, whereas soil-emitted chemicals with log KOA > 6 were found to be effectively retained in the soils of emission requires some explanation. This discrepancy is due to the different environmental parameters assigned to cultivated and uncultivated soils in the Globo-POP model (15, 16). Cultivated soils, which are the recipients of soil emissions, have a relatively large depth (20 cm, except in high latitudes), reflecting the impact of cultivation practices. Air-emitted chemicals will mostly deposit onto uncultivated soils, which have a much larger extension and are assumed to be much shallower (5 cm, except in high latitudes). This greatly increases the extent of air-soil exchange of hydrophobic, semivolatile chemicals (log KOA between 6 and 9) with uncultivated soils relative to cultivated soil and thus of the chemicals emitted to air relative to soil-emitted chemicals. This was confirmed by performing additional ACP calculation with greatly reduced cultivated soil depths. Under such circumstances, hydrophobic semivolatile chemicals emitted to soils have much higher ACP10 values, that are approaching those of air-emitted PPCs with the same partitioning properties. It is also reflected in the sensitivity analysis for the hydrophobic and semivolatile chemical E, in which the uncultivated and cultivated soil depth were among the most influential parameters for VOL. 37, NO. 7, 2003 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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emission to air and cultivated soil, respectively (Tables 2 and S1). Sensitivity of Model Results to Changes in Environmental Input Parameters. Atmospheric mixing parameters, global temperatures, energies of phase transfer, and sea ice cover were among the most influential parameters for the ACP of all five chemicals (Table 2). The atmospheric diffusivities determine the rate of meridional air exchange and thus the rate of chemical movement in the atmosphere. They appear to be particularly important for quantifying the transport to the Arctic occurring as the results of a single episodic LRT event rather than “grass-hopping”. Accordingly, they are more important in controlling the short term (ACP1) than the long-term contamination potential (ACP10) of all five chemicals (Table S1). They are also much more important for the ACP10 of the “single-hop” chemicals A and B than for the other three chemicals that can undergo revolatilization after being deposited from the atmosphere (Table 2). Because of the importance of step A3, factors that influence deposition in the Arctic have a strong impact on the ACP. The ocean makes up more than 71% of the Arctic zone and depending on the season between 42 and 83% of it is ice-covered. Sea ice cover in the Globo-POP model limits the extent of diffusive gas exchange with the polar oceans but is assumed to not affect the other deposition processes. Its influence is thus largest for chemicals C and D which are deposited to oceans primarily in gaseous form. The ACP10 of these two chemicals was also sensitive to the diffusive airwater mass transfer coefficient over the oceans. It is the interaction between global temperature differences and the temperature-dependent gas phase/condensed phase partitioning that should control the extent of “cold condensation” (30, 13), and the strong sensitivity to ambient temperatures and energies of phase transfer thus confirms the importance of this process for the enrichment of persistent organic chemicals in the Arctic. It is especially the ACP of the hydrophobic and semivolatile chemical E and to a lesser extent of the multimedia chemical D and the water soluble substance B, which is sensitive to these two parameters. Apart from the few parameters that were important for all chemicals, the ACP of the five chemicals was sensitive to very different sets of parameters, reflecting the different environmental processes and pathways which determine their environmental fate. Not surprisingly, the ACP of the multimedia chemical D shows sensitivity to the largest number of input parameter, reflecting the multitude of fate processes that such chemicals undergo. Chemicals with such partitioning properties are the lighter PCDD/Fs, intermediate PCBs, DDE, and hexachlorobenzene. The ACP of the water soluble chemical B was rather sensitive to the meridional eddy diffusivities in the surface ocean, confirming that its northward transport occurs with marine currents. To identify for which chemicals this transport process is of importance we calculated the sensitivity to this parameter for the entire chemical space (not shown). The results suggest that oceanic transport starts to become an important pathway for chemicals with log KAW < -1.5 and log KOW < 6, which includes substances such as the hexachlorocyclohexanes and many other pesticide chemicals. The hydrophobic, but semivolatile chemical E partitions easily between gas phase and solid phases (Figure 3), and its ACP is very dependent on the properties of soils (moisture content, depth, air-side mass transfer coefficient over soil, solid-phase diffusion in soil, organic carbon content) and atmospheric particles. When emitted to the atmosphere the ACP of the particlesorbed chemical A was sensitive to parameters influencing the rate of transport and deposition of atmospheric particles, such as the atmospheric mixing rates, precipitation rates, 1350
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particle scavenging ratios, and dry particle deposition velocities (Table 2). Its ability to reach the Arctic is clearly controlled by the LRTP of the atmospheric particles to which it sorbs. When emitted to surface media, the ACP for chemical A became insensitive to virtually all environmental input parameters (see Table S1), suggesting that the chemical is simply retained in soil and sediment. If such a chemical is present in the Arctic, it means that it either had been emitted to the atmosphere or it had been used within the Arctic itself. Perhalogenated aromatic hydrocarbons such as octachlorodibenzo-p-dioxin, decabromodiphenyl ether, and decachlorobiphenyl are among the chemicals with such partitioning properties. Effect of Emission Location. It is of interest to establish to what extent the results presented so far are influenced by the generic zonal distribution of the emissions, namely by the assumption that most of the chemical is used in the heavily populated zones of the northern hemisphere. Figure 5 shows the ACP10 for five chemicals emitted to the atmosphere of one zone. Two types of behavior emerge: For chemicals B (“water-soluble”) and A (“particle sorbed”), the potential for significant enrichment in the Arctic is very dependent on it being emitted within or close to the Arctic. These two chemicals are single-hop chemicals, i.e., they cannot revolatilize and therefore need to reach the Arctic before being deposited from the atmosphere. Being transported into the Arctic atmosphere is of course more likely when they have a shorter distance to travel. This is also consistent with the earlier observation that the ACP10 of chemicals A and B was very dependent on the atmospheric transport coefficients. For chemical E (“hydrophobic and semivolatile”), on the other hand, the amount in the Arctic after 10 years is virtually independent of the original zone of emission, indicative of its mode of transport by multiple hops. Quite predictably, the multimedia chemical D and the volatile water soluble chemical C show a behavior between these two extremes. This implies that changes in the zonal distribution of the emissions would not drastically change the ACP10 calculated for chemicals in the upper part of the chemical space in Figure 4 (log KAW > -1) but would have a strong impact on the results in the lower half (log KAW < -2). If emissions occur to media other than the atmosphere (not shown), the zone of emission becomes much more important in determining the ACP10 of all chemicals, because they tend to be retained much more strongly within the original zone of emission. The ACP10 displayed in Figure 5 can be interpreted as transfer efficiencies of a chemical to the Arctic from a particular zone of emission. From the transfer efficiencies for all 10 zones for a particular chemical, an ACP could be calculated for any zonal emission distribution by simple linear superposition. Continued Emissions vs Emission Pulse. Sometimes it is of interest to establish whether concentrations of chemicals can increase in remote regions after emissions have ceased. This determines the lag time between emission reductions in source regions and the maximum risk to receptors in remote regions. To investigate the global fate of a time-limited emission pulse, a scenario with 1 year of steady emissions followed by 9 years of no emissions was calculated for all physical-chemical property combinations and all three emission scenarios. The zonal distribution of the emissions was again based on the global population distribution. The ACP1+9 derived from these calculations (Figure S4 in the Supporting Information), in particular the dependence of arctic contamination on the partitioning properties and the mode of emission, were very similar to the ACP10 results. ACP1+9 represents a scenario where a 1-year long pulse emission of a PPC is allowed to approach a global steadystate distribution over a 9-year period. ACP10, on the other
hand, represents a scenario where a steady-state emission of a PPC is occurring for an extended period of time during which again a steady-state distribution is being approached. The similarity is therefore not surprising and confirms that ACP10 is not only a reliable indicator of the long-term arctic contamination potential but also can measure the delayed ACP. ACP10 is preferable over ACP1+9, because the latter has limited applicability for nonpersistent chemicals.
Acknowledgments The paper has benefited greatly from a thoughtful review by Dr. M. MacLeod from the University of California in Berkeley. I would like to thank Alexander Wong for helping with earlier versions of the presented calculations and the Northern Contaminants Program of the Canadian Department of Indian Affairs and Northern Development for funding this work.
Supporting Information Available Results of the sensitivity analysis (Table S1) and ACP10/ACP1 and ACP1+9 as a function of log KAW, log KOA, and mode of emission (Figures S1-S4). This material is available free of charge via the Internet at http://pubs.acs.org.
Note Added After ASAP This paper was released ASAP on 02/28/2003 with an error in ref 28. The correct version was posted on 03/04/2003.
Literature Cited (1) Rodan, D.; Pennington, D. W.; Eckley, N.; Boethling, R. S. Environ. Sci. Technol. 1999, 33, 3482-3488. (2) Mackay, D.; Webster, E.; Beyer, A. et al. Defining the bioaccumulation, persistence, and transport attributes of priority chemicals. In Persistent, Bioaccumulative, and Toxic Chemicals; Lipnick, R., Jansson, B., Mackay, D., Petreas, M., Eds.; American Chemical Society Symposium Series No. 773; 2001; Vol. II, pp 14-28. (3) van de Meent, D.; McKone, T. E.; Parkerton, T.; Matthies, M.; Scheringer, M.; Wania, F.; Purdy, R.; Bennett, D. H. Persistence and transport potential of chemicals in a multimedia environment. In Evaluation of Persistence and Long-Range Transport of Organic Chemicals in the Environment, Proceedings of a SETAC Pellston Workshop, Fairmont Hot Springs, BC, Canada, 13-19 July 1998; Klecˇka, G., Mackay, D., Eds.; SETAC Press: Pensacola, FL, 2001; pp 169-204. (4) Scheringer, M.; Hungerbu ¨ hler, K.; Matthies, M. Environ. Sci. Pollut. Res. 2001, 8, 150-155. (5) van Pul, W. A. J.; de Leeuw, F. A. A. M.; van Jaarsveld, J. A.; van der Gaag, M. A.; Sliggers, C. J. Chemosphere 1998, 37, 113-141. (6) Bennett, D. H.; McKone, T. E.; Matthies, M.; Kastenberg, W. E. Environ. Sci. Technol. 1998, 32, 4023-4030. (7) Beyer, A.; Mackay, D.; Matthies, M.; Wania, F.; Webster, E. Environ. Sci. Technol. 2000, 34, 699-703.
(8) Scheringer, M. Environ. Sci. Technol. 1996, 30, 1652-1659. (9) Scheringer, M. Environ. Sci. Technol. 1997, 31, 2891-2897. (10) Beyer, A.; Matthies, M. ESPR -Environ. Sci. Pollut. Res. 2001, 8, 173-179. (11) Scheringer, M.; Wegmann, F.; Fenner, K.; Hungerbu ¨ hler, K. Environ. Sci. Technol. 2000, 34, 1842-1850. (12) Wania, F.; Mackay, D. Ambio 1993, 22, 10-18. (13) Wania, F.; Mackay, D. Environ. Sci. Technol. 1996, 30, 390A396A. (14) Wania, F. ESPR - Environ. Sci. Pollut. Res. 1999, 6, 11-19. (15) Wania, F.; Mackay, D. Sci. Total Environ. 1995, 160/161, 211232. (16) Wania, F.; Mackay, D. The global distribution model. A nonsteady-state multi-compartmental mass balance model of the fate of persistent organic pollutants in the global environment; Technical Report and Computer Program; 2000; 21 pp (www.utsc.utoronto.ca/∼wania). (17) Wania, F.; Mackay, D.; Li, Y.-F.; Bidleman, T. F.; Strand, A. Environ. Toxicol. Chem. 1999, 18, 1390-1399. (18) Wania, F.; Mackay, D. Environ. Toxicol. Chem. 1999, 18, 14001407. (19) Lakaschus, S.; Weber, K.; Wania, F.; Bruhn, R.; Schrems, O. Environ. Sci. Technol. 2002, 36, 138-145. (20) Wania, F.; Daly, G. L. Atmos. Environ. 2002, 36, 5581-5593. (21) UNEP/GRID. Sioux Falls, Global Population Distribution Database, Gridded Global Population Distribution (http:// grid2.cr.usgs.gov/data/download.html). (22) Li, N.; Wania, F.; Lei, Y. D.; Daly, G. L. J. Phys. Chem. Ref. Data In press (accepted Nov. 29, 2002). (23) Seth, R.; Mackay, D.; Muncke, J. Environ. Sci. Technol. 1999, 33, 2390-2394. (24) Goss, K. U.; Schwarzenbach, R. Environ. Sci. Technol. 2000, 34, 1-9. (25) Smith, J. N.; Ellis, K. M.; Jones, E. P. J. Geophys. Res. 1990, 95, 1693-1701. (26) Hertwich, E. G. Environ. Sci. Technol. 2001, 35, 936-940. (27) Mazzoni, S. M.; Roy, S.; Grigoras, S. Eco-relevant properties of selected organosilicon materials. In The Handbook of Environmental Chemistry Vol. 3 Part H. Organosilicon Materials; Chandra, G., Ed.; Springer-Verlag: Heidelberg, 1997. (28) Ellis, D. A.; Cahill, T. M.; Mabury, S. A.; Cousins, I.; Mackay, D. Partitioning of organofluorine compounds in he environment. In The Handbook of Environmental Chemistry Vol. 3 Part N. Organoflurines; Neilson, A., Ed.; Springer-Verlag: Heidelberg, 2002. (29) Weschler, C. J. Atmos. Environ. 1981, 15, 1365-1369. (30) Mackay, D.; Wania, F. Sci. Total Environ. 1995, 160/161, 25-38. (31) Troll, C. Seasonal climates of the earth. The seasonal course of natural phenomena in the different climatic zones of the earth. In World Maps of Climatology; Landsberg, H. E., Lippmann, H., Paffen, K. H., Troll, C., Rodenwaldt, E., Jusatz, H., Eds; Springer Verlag: Berlin, Germany, 1966.
Received for review August 1, 2002. Revised manuscript received January 2, 2003. Accepted January 23, 2003. ES026019E
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