Environ. Sci. Technol. 1998, 32, 2721-2726
Observations on Persistent Organic Pollutants in Plants: Implications for Their Use as Passive Air Samplers and for POP Cycling W E N D Y A . O C K E N D E N , * ,† EILIV STEINNES,‡ CLARE PARKER,† AND KEVIN C. JONES† Environmental Science Department, I.E.N.S., Lancaster University, Lancaster, LA1 4YQ, U.K., and Department of Chemistry, Norwegian University of Science and Technology, N-7034 Trondheim, Norway
Pine needle (Pinus sylvestris) and lichen (Hypogymnia physodes) samples from various remote sites across Norway have been analyzed for a range of persistent organic pollutants (POPs). Results have shown differences in accumulation between species, with higher concentrations being noted in the H. physodes than the P. sylvestris. This indicates that to use vegetation as a biomonitor, intraspecies and not interspecies comparisons in vegetation pollutant loading between sites are necessary. R/γ-HCH ratios were highest at colder northern sites, indicating increased distance from source areas and long-range atmospheric transport. Concentrations of PCBs 101, 118, 138, and 153 in H. physodes were found to be higher at lower temperatures. Trends between burdens of the other POPs in H. physodes or P. sylvestris and site temperature or latitude were not apparent. Plant/air partition coefficients indicate favored accumulation of PCBs in vegetation at lower temperatures and for higher chlorinated congeners.
refs 5-8). As the majority of a plant’s POP burden will have been sequestered from the air, it has been suggested that it should be possible to infer differences in atmospheric concentrations through differences in vegetation concentrations. There are problems with this approach. When trying to survey a large area, it is often necessary to compare different species. It is possible, however, that different species will sequester pollutants from the atmosphere at different rates and to different extents (9). Even plants of the same species are likely to have different growth rates and different lipid contents, depending on the habitat that they are growing in. These factors all serve to confound data interpretation. The aims of this study were to investigate the suitability of using vegetation as an atmospheric biomonitor and to see whether their POP burdens could be related to site latitude or mean annual temperature, to further understanding of the global behavior of these pollutants. Lichens and pine needles collected from rural sites across Norway were analyzed for a suite of polychlorinated biphenyl (PCB) congeners, p,p′-DDT and p,p′-DDE, hexachlorobenzene (HCB), and R- and γ-hexachlorocyclohexane (HCH). Lichen was chosen for the study as it has a large surface to volume ratio, depends on the atmosphere for delivery of nutrients, and lacks a surface cuticle, which it has been suggested can act as a selective barrier depending on a compound’s hydrophobicity (10). In addition, certain lichen species are particularly widespread and can be found in both temperate and remote polar zones. The surfaces of pine needles are covered in an epicuticular wax that minimizes evapotranspiration but will also accumulate vapor-phase POPs and trap particulates (2). These plant types are therefore interesting to compare in a study of this type. Norway covers a large latitudinal cross-section and has a low population density (most of the population resides in the south of the country) and corresponding low usage of many industrial chemicals. Studies have also shown that long-range atmospheric transport supplies much of the national chemical mass balance (11).
Methods Introduction More than 80% of the Earth’s land surface is covered with vegetation, and typically vegetation has a surface area that is 6-14 times greater than the land it covers (1). In addition, this large surface area is often covered by a lipid-rich cuticle, suggesting that plants will play an important role in the global cycling and distribution of lipophilic persistent organic pollutants (POPs). There are several different routes through which vegetation may sequester such pollutants. These include (i) transfer from soil to plant roots and subsequent translocation within the plant xylem and (ii) deposition from the atmosphere (vapor and particulate phases) onto leaf surfaces with either subsequent absorption into the waxy plant cuticle or uptake through stomata and translocation via the phloem (2). The most important route of uptake will be dependent on a pollutant’s physicochemical properties, on the soil’s properties, and on the plant species. For lipophilic POPs, however, atmosphere to plant transfer has been shown to be the main accumulation pathway (3, 4). Vegetation has been used in a number of studies to attempt to assess regional/global distribution of POPs (e.g., * Corresponding author fax: (015424)593985. † Lancaster University. ‡ Norwegian University of Science and Technology. S0013-936X(98)00150-3 CCC: $15.00 Published on Web 08/12/1998
1998 American Chemical Society
Sampling. Sampling was carried out at eight rural sites across Norway (Figure 1) in the summer of 1994. Each of the sample sites was at or near a meteorological station in order that temperature information would be available for data interpretation. Site latitudes and longitudes and mean annual temperatures are shown in Table 1. In a study investigating the concentrations of a range of organochlorines (OCs) in pine needles, it was found that sampling direction and tree age did not influence the pollutant concentration. POP burdens were found to be affected by differences caused by changes in sampling height (12). Lichen and pine needle samples in this study were therefore collected at approximately 1.5 m above ground level. All samples were stored in solvent-cleaned glass jars with aluminum foil-lined lids and were frozen on return to the laboratory until extraction. Pine needles from the 1-2 year growth were collected from Scots pine (Pinus sylvestris). Needles were collected from six of the sampling locations (Figure 1, Table 1). The lichen Hypogymnia physodes was collected from the trunks of birch trees at all of the sampling locations. Large thalli of the lichen were collected, portions of which were likely to have been in excess of 25 years old. Extraction. Approximately 3 g of sample was weighed into cellulose Soxhlet extraction thimbles, which had previously been Soxhlet preextracted in dichloromethane for 4 h. VOL. 32, NO. 18, 1998 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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GPC columns (20 mm i.d.) were prepared from 6 g of Biobeads (S-X3) preexpanded in hexane/dichloromethane (1:1 v:v). Samples were quantitatively transferred to the GPC columns and eluted with a total of 46 mL hexane/dichloromethane (1:1 v:v), with the first 16 mL being discarded. Sample volume was again reduced to ca. 0.5 mL by rotary evaporation and blowdown under nitrogen. Samples were fractionated on silica columns [3 g of silica gel (grade as above) prefired at 350 °C for 16 h, slurry packed into 9 mm i.d. glass chromatography column with hexane]. Two fractions were collected: the first (F1; 33.5 mL of hexane) containing PCBs, HCB, and p,p′-DDE; the second (F2; 15 mL of hexane/dichloromethane, 1:1 v:v) containing R- and γHCH and p,p′-DDT. F1 volumes were reduced, and the samples were solvent exchanged into the final solvent for analysis [50 µL dodecane containing GC internal standardssPCB congeners 6, 208, and [13C12]PCB 141 for the PCB analysis and tetrachlorometa-xylene (TCMX) for the OCs]. The volume of F2 was reduced, and the sample was transferred into 100 µL isooctane containing the GC internal standard TCMX.
FIGURE 1. Location of vegetation sample sites.
TABLE 1. Mean Annual Temperatures and Coordinates for Vegetation Sample Sitesa site ref
latitude
longitude
mean annual temp (°C)
vegetation species sampled
A B C D E F G H
59°01′N 60°15′N 61°15′N 61°17′N 63°27′N 64°59′N 69°45′N 69°54′N
08°31′E 11°06′E 11°53′E 05°02′E 10°18′E 13°36′E 18°30′E 25°02′E
5.2 4.3 2.2 7.6 4.9 1.1 3.6 0.1
Pa& Lb P&L P&L P&L P&L L L P&L
a
Pine (Pinus sylvestris).
b
Lichen (Hypogymnia physodes).
Samples were mixed thoroughly with approximately 15 g of anhydrous sodium sulfate and were spiked with a [13C12]PCB recovery standard. The recovery standard contained [13C12]PCBs 28, 52, 101, 138, 153, 180, and 209 in isooctane, and 2.5 ng of each congener was spiked into each sample. Samples were extracted for 4 h in a Soxhlet extractor unit in dichloromethane. Sample volume was reduced to approximately 10 mL using rotary evaporation, and the sample was then split, with approximately 10% being taken for extractable lipid determination and the remainder being cleaned up and analyzed for the target compounds. Cleanup. The fraction of sample for target compound analysis was reduced to approximately 2 mL by blowdown under nitrogen, and samples were then cleaned up using alumina/silica gel chromatography followed by gel permeation chromatography (GPC) and silica gel fractionation. Alumina/silica columns were prepared [25 mm i.d.; 9 g of silica gel (Merck grade 60) topped with 6 g of neutral alumina, both prefired at 350 °C for 16 h] and washed through with 100 mL of dichloromethane. Samples were quantitatively transferred to the column and eluted with 150 mL of hexane/dichloromethane (1:1 v:v). Eluent volume was reduced by rotary evaporation and blowdown under nitrogen to ca. 0.5 mL. 2722
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Analysis. PCBs. F1 samples were analyzed for PCBs by GC-MSD (Fisons MD-800), EI+ source in SIM mode. Two microliters of each sample was injected in the splitless mode on a 50 m × 0.18 mm CPSil-8 column. The oven temperature was as follows: 100 °C for 2 min, 20 °C min-1 to 140 °C, 4 °C min-1 to 200 °C, 200 °C for 13 min, 4 °C min-1 to 300 °C, and 300 °C for 10 min. The injector was set at 250 °C, source set at 250 °C, and interface set at 300 °C. Two masses were monitored per homologue group. A split seven-point calibration (two ranges) was carried out using an internal standard method. The following PCB congeners were screened: 18, 28, 30, 31, 33, 37, 44, 47, 49, 52, 54, 60, 61, 66, 74, 77, 81, 82, 87, 101, 104, 105, 110, 114, 118, 119, 123, 126, 128, 138, 141, 149, 151, 153, 156, 157, 167, 169, 170, 180, 183, 185, 187, 188, 189, 191, 193, 194, 202, 204, 205, 206, and 209. Congeners 6, 208, and [13C12]PCB 141 were used as injection internal standards. OCs. F1 and F2 samples were analyzed for OCs on a Hewlett-Packard 5890 GC using dual-column ECD (HP-5MS and HP-50+ columns, each 60 m × 0.25 mm and 25 µm phase thickness). N2 was used as makeup gas, and He was used as the carrier gas, with flow rate maintained at 1.9 mL min-1 using constant pressure control. The oven temperature program was as follows: 100 °C for 2 min, 30 °C min-1 to 130 °C, 2 °C min-1 to 250 °C, 4 °C min-1 to 290 °C, and 290 °C for 10 min. The injector was set at 250 °C, and detectors were set at 300 °C. A six-point calibration was carried out using an internal standard method, with TCMX as the injection internal standard. F1 extracts were analyzed for HCB and p,p′-DDE, and F2 extracts were analyzed for R- and γ-HCH, and p,p′-DDT. Water and Lipid Content. A subsample of approximately 3 g of the original vegetation was dried at 105 °C until constant weight was obtained and the water content determined. The fraction of the original extract, which was taken for lipid determination, was dried under nitrogen until constant weight was obtained, and the extractable lipid content was determined as a percentage of the sample dry weight. Quality Assurance. All samples were spiked with a [13C12]PCB recovery standard prior to extraction, and any sample with recovery below 70% was excluded. Results are not corrected for recovery. Inclusion rates for laboratory (procedural) blanks, certified reference materials, and triplicate sample extraction were 20%, 10%, and 10%, respectively. Limits of quantification for all samples were conservatively taken to be 1 pg on column for PCBs and OCs.
TABLE 2. Concentration of Contaminants in Pinus sylvestris Samplesa concentration (pg/g dry weight) compd
A
B
C
D
E
H
PCB 28 PCB 52 PCB 101 PCB 118 PCB 153 PCB 138 PCB 180 tri-CBa tetra-CB penta-CB hexa-CB hepta-CB HCB R-HCH γ-HCH p,p′-DDE p,p′-DDT lipidb
10 31 37 10 17 39 22 160 270 70 96 22 680 310 660 130 51 8.3
89 53 58 35 30 52 22 160 270 150 140 22 770 960 1000 33 55 17
67 49 47 34 38 53 28 130 360 130 140 49 1500 1600 1400 61 57 9.1
180 67 75 27 52 62 38 400 400 150 260 38 1100 690 1300 100 21 6.1
170 85 110 57 100 110 56 470 470 290 380 83 2100 2600 1900 150 75 8.5
42 130 84 73 65 98 42 450 350 320 240 65 750 440 110 18 11 18
FIGURE 2. Comparison of mean PCB homologue group and OC concentrations in Pinus sylvestris and Hypogymnia physodes. (Note log scale on concentration axis). Error bars show range of values. PCB homologue groups defined in Table 2. the lipophilic nature of a plant cuticle (13, 14). Therefore, the effective lipid content of the pine needles may be greater than is measured by this method. PCBs and OCs. Figure 2 shows the mean and ranges of concentrations of each of the PCB homologue groups and the OC pesticides for the lichen and the pine needles. For all compounds, the H. physodes burdens greatly exceeded those of the P. sylvestris. The concentrations in Figure 2 are expressed in picogram per gram dry weight. It has been suggested that it may be possible to correct for species differences by expressing pollutant concentrations on a per milligram of lipid basis (1, 15). However, as noted above, the extractable lipid contents of the pine needles and the lichens were similar, so the differences in pollutant concentrations are just as great if correction for lipid content is made. As mentioned above, the effective lipid content of the pine needles is likely to be greater than is measured by the solvent extractability method. If the effective lipid content were to be considered instead of the actual lipid content, the pollutant concentration difference between lichen and pine needle samples is likely to be even more pronounced. The pine needle samples in this study were taken from the 1-2 year growth. The H. physodes thalli sampled, however, could easily have been in excess of 25 years old and may well have been as old as 50 years. It is likely, therefore,
a PCB homologue groups: tri-CB, sum of congeners 18, 28, 30, 31, 33, and 37; tetra-CB, sum of congeners 44, 47, 49, 52, 54, 60, 61, 66, 74, 77, and 81; penta-CB, sum of congeners 82, 87, 101, 104, 105, 110, 114, 118, 119, 123, and 126; hexa-CB, sum of congeners 128, 138, 141, 149, 151, 153, 156, 157, 167, and 169; hepta-CB, sum of congeners 170, 180, 183, 185, 187, 188, 189, 191, and 193; octa-, nona-, and deca-CB (congeners 194, 202, 204, 205, 206, and 209) were below limit of quantification. b Lipid content given in mg/g.
Results and Discussion Species Differences. Tables 2 and 3 show mean concentrations (pg g-1 on a dry weight basis) of the ICES (International Council for the Exploration of the Seas) PCB congeners (PCBs 28, 52, 101, 118, 138, 153, and 180), the sum of the PCB homologue groups, and the OCs at each site for the pine needle and lichen samples, respectively. Octa-, nona-, and deca-CB concentrations were below limits of quantification in all cases. Extractable lipid contents are also shown. Lipid Content. The extractable lipid contents of the P. sylvestris (mean 11.2 mg g-1; range 6.1-18 mg g-1) and the H. physodes (mean 12.0 mg g-1; range 5.5-19 mg g-1) were found to be similar. It has been suggested that the cutin in plant cuticles may also act as a lipid, but as a polymer, this is not solvent extractable. Cutin may make up over 70% of
TABLE 3. Concentration of Contaminants in Hypogymnia physodes Samples concentration (pg/g dry weight)
a
compd
A
B
C
D
E
F
G
H
PCB 28 PCB 52 PCB 101 PCB 118 PCB 153 PCB 138 PCB 180 tri-CB tetra-CB penta-CB hexa-CB hepta-CB HCB R-HCH γ-HCH p,p′-DDE p,p′-DDT lipida
93 110 200 230 380 460 190 230 580 860 1300 440 1800 1700 3900 500 740 19
220 130 210 340 350 380 170 590 650 960 1200 370 1900 420 2500 600 540 16
400 230 450 380 670 670 250 1300 1100 1600 2200 630 2700 3200 4600 1100 900 19
160 97 68 46 86 96 69 600 1200 220 330 120 1600 1100 670 120 80 11
190 120 190 350 320 430 170 590 720 1000 1100 400 4400 1800 2900 390 410 7.5
120 110 180 280 300 380 150 270 600 900 1100 350 2500 3100 1800 320 1000 10
230 120 160 190 190 240 92 540 570 680 710 210 4800 3400 3300 390 420 9.3
110 320 580 720 780 900 250 450 1000 2700 2700 590 3800 4200 1600 590 1500 5.5
Lipid content given in mg/g. PCB homologue groups defined in Table 2.
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that the lichen samples could have lived through the peak in production of the pollutants examined. The peak in production of PCBs, for example, was in the late 1960s/early 1970s (i.e., approximately 30 years ago). Consequently, the lichen will have had the time to have ‘sampled’ more air than the pine needles, and in the past, this air is likely to have been more contaminated than contemporary air. McLachlan et al. (3) have suggested that the kinetic constraints to plant uptake of pollutants from air can be viewed as resulting from a ‘plant-side’ resistance and an ‘airside’ resistance. The air-side resistance is much the greater of the two, particularly for pollutants with high octanol/air partition coefficients (KOA). These workers have hypothesized that some plants growing in the field may effectively not ‘see’ sufficient air for plant/air equilibrium to be achieved. Pine needles do most of their growing in their first summer, remain dormant in the winter, and then do not grow much over subsequent summers. Due to the air-side resistance (i.e., the rate of supply of the pollutant) the 2-year-old P. sylvestris needles sampled here may not be at equilibrium with the gas phase of the air. The lichen, however, being much longer lived, is more likely to have reached or be approaching equilibrium with the atmospheresparticularly for pollutants with relatively low octanol/air partition coefficients (KOA), such as the lower chlorinated PCBs, HCB, and the HCHs. Although air-side resistance may be greater than plantside resistance, physiological differences in the plants may have also affected their pollutant concentrations. For example, lack of a cuticle in the lichen samples would make them less selective to the uptake of gaseous species, while the waxy cuticle of the pine needles could have hindered transfer of POPs into inner lipid-rich portions of the needles. In addition, the lichen has a much larger effective surface area than the pine needles, which may have affected uptake. It is interesting to note that higher concentrations in lichens (and mosses) as compared with pine needle samples have also been observed for heavy metals (16). The ratio in the pollutant concentrations between the two species varies between sites. Therefore, it is not possible to apply a conversion factor to the vegetation in order to predict the concentration in one species from the concentration of the other. There are also differences in the PCB profiles of the vegetation species investigated. Pine needle samples are dominated by the lower chlorinated PCBs. Tetra-chlorinated biphenyl, for example, constitutes between 25 and 45% of the total PCB concentration, while hexa-chlorinated biphenyl constitutes between 15 and 20% of total PCB. Tetrachlorinated biphenyls make up between 10 and 20% of the total PCB content of the lichen samples. Penta- and hexachlorinated biphenyls are much more important in the H. physodes profile, with each typically constituting 25-35% of the total PCB concentration. High proportions of higher chlorinated PCBs have been noted in lichen samples from other areas, e.g., Ontario (10), France (17), and Norway (18). As lichen samples are relatively long-lived, it is possible that the lighter congeners may have attained equilibrium with the vapor phase of the air, while there may have been simultaneous continued uptake of the heavier compounds. Vegetation will have a larger capacity for the heavier compounds and will therefore need to sample more air (and thus need more time) before equilibrium is achieved. This may result in the observed relative dominance of heavier compounds when the congener profile is compared with that of pine needle samples. In addition, contemporary air concentrations are likely to be less than they were when portions of the lichen samples first emerged (25-50 years ago). Older tissue may therefore have originally been approaching higher equilibrium concentrations of PCBs as 2724
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FIGURE 3. r/γ-HCH ratio in Pinus sylvestris samples. supplied by the air and then re-released the less chlorinated congeners back to the atmosphere if the air concentrations have fallen. This could also explain the observed shift in the congener profile to favor dominance of the heavier compounds. For pine needle samples, vapor phase to plant transfer has been found to be the principle accumulation pathway (19). For lichen samples, accumulation from particulate dry and wet deposition has been found to be an important route for metals (20). Presumably, therefore, it may also be important for POPs, with uptake from percolating rainwater and dry particles causing a shift in PCB homologue profile to favor heavier particle-bound species. In this study, two taxonomically very distinct plant species have been investigated, which is likely to exaggerate interspecies differences. A separate study, however, has shown that there are large differences in the PCB and OC pesticide burdens (on a unit dry weight and unit lipid basis) of the two lichen species H. physodes and Parmelia olivacea collected from the same site (21). This difference could result from differences in uptake rates between species or it could be because lichen samples of different ages may have been collected. These observations place an extremely important consideration on the use of plants as biomonitors. Ideally comparisons will only be made between plants of the same species and same age, but this sets limits on the scale over which biomonitoring studies can be conducted. Calamari et al. (5) compared concentrations of OCs in lichens from cold and temperate regions with concentrations in mango leaves from tropical regions. Higher concentrations of HCB were found in the lichen samples. This difference was attributed to global fractionation. However, in light of the above findings, it is possible that species differences may have also played a role in the differences observed. Clearly, in this study the lichen and the pine samples should be considered separately in order to try to discern any spatial trends. Spatial Differences. Pinus sylvestris. (a) PCBs. It is not possible to discern any trends between either absolute or relative concentration and mean annual site temperature. Correction for lipid content does not make trends any more apparent. (b) OCs. As with PCBs, it is hard to discern trends between absolute OC concentrations and site location on a dry weight or lipid corrected basis. R/γ HCH ratios, however, are greater at northern colder sites than they are in warmer southern regions (Figure 3). R-HCH has a higher Henry’s law constant and vapor pressure than γ-HCH, making R-HCH more prone to atmospheric transport. It has also been suggested that the γ-HCH isomer may be photolytically degraded to the R-isomer (22). Additionally, the concentration of HCHs has been shown to be higher in northern than in tropical oceans (23), and air/water fugacity ratios have shown net fluxes of
a
b
FIGURE 4. Temperature dependence of log pseudo-plant/air partition coefficient for (a) Pinus sylvestris and (b) Hypogymnia physodes. R-HCH to be out of the Bering and Chuckchi Seas (24). The increasing R/γ ratios with increasing latitude, or decreasing temperature, seen here are therefore indicative of increasing distance from contemporary source regions of lindane (γHCH), the influence of long-range atmospheric transport, and possibly the closer proximity to northern oceans which could be acting as an atmospheric source of R-HCH (24). Hypogymnia physodes. (a) PCBs. A slight trend of increasing concentration with decreasing temperature can be seen. This trend is statistically significant (>95%) for PCBs 101, 118, 138, and 153 and may suggest an increase in partitioning to the surface at lower temperatures. Trends in relative concentrations of these compounds with temperature are less apparent. (b) OCs. As with pine needles, higher R/γ-HCH ratios are seen in northern samples than southern samples, again suggesting long-range transport. No other trends can be seen between concentrations of OCs and latitude or temperature. Plant/Air Partitioning. To try to discern latitudinal trends, it is important to consider factors other than temperature that will affect a plant’s pollutant loading. Clearly, differences in air concentrations will also be important. Data are available for atmospheric concentrations of PCBs with four or more chlorines at four of the sample sites (sites C, D, F, and H) (25). The ratio of plant to air concentrations gives a pseudo-plant/air partition coefficient (KPA) (correction for plant lipid volume is required to get the actual partition coefficient). Figure 4, panels a and b, shows KPA against mean annual site temperature for the P. sylvestris and H. physodes samples, respectively, for PCBs 52, 101, 138, and 180. In all cases, decreasing plant to air concentration ratios are seen with increasing temperature. Lower temperatures therefore favor
FIGURE 5. Plot of log pseudo-plant/air partition coefficient versus log KOA for (a) Pinus sylvestris and (b) Hypogymnia physodes. KOA values have been calculated and corrected for site mean annual temperature using equations by Harner and Bidleman (26) and Falconer and Bidleman (27).
TABLE 4. Equations for Straight Line Plots Displayed in Figure 5 Pinus sylvestris site C D F H
gradient
intercept
R2 (P)
0.52 0.35
-3.63 -1.78
0.89 (0.000) 0.50 (0.049)
0.50
-3.17
0.80 (0.003)
Hypogymnia physodes gradient
intercept
R2 (P)
0.43 0.53 0.52 0.36
-1.60 -3.50 -3.00 -0.75
0.96 (0.000) 0.88 (0.000) 0.71 (0.001) 0.52 (0.012)
accumulation in the plant. The ratio of plant to air is greater for more chlorinated congenerssi.e., increasing chlorination or lower vapor pressure also favors accumulation in the plant. Figure 5 shows log KPA for the full range of PCBs detected in this and the air study (25) plotted against log of their KOA. In Figure 5, KOA has been corrected for mean annual temperature at the sites using equations from Harner and Bidleman (26) and subcooled liquid vapor pressure (PL) from Falconer and Bidleman (27). Straight lines are obtained at all sites for both lichen and pine needle samples (equations given in Table 4). Straight lines on this type of plot suggest that plant/air partitioning can be described by an equilibrium/fugacity approach, with the partitioning being dominated by sorption to hydrophobic plant surfaces (10, 28). If octanol were an ideal surrogate for plant lipid, then the slopes should be equal to 1. The slopes of the plots in Figure 5 are 0.35-0.53 (Table 4). This suggests that either octanol is not an ideal surrogate or that there are other plant components in addition to the plant lipid that are influencing the partitioning (e.g., cutin in the cuticle of the pine needles). A VOL. 32, NO. 18, 1998 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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gradient of less than 1 has been seen for log KPA-log KOA plots for various vegetation types in other field studiesse.g., 0.16-0.52 (mean 0.37) for PCBs in grass (29); 0.22-0.34 for PCBs and OC pesticides in lichen (10); and 0.48 for polyaromatic hydrocarbons (PAHs) in needles, leaves, and tree bark (2). Paterson et al. (30) and Tolls and McLachlan (31) have carried out controlled laboratory exposure experiments on the uptake of various hydrophobic organic chemicals by azalea and of PCBs, dioxins, and furans by Welsh ray grass, respectively. The study on azalea gave a slope on the log KPA-log KOA plot of 0.91, and the Welsh ray grass gave a slope of 1.0. Differences between slopes for the controlled experiments and the field-conducted experiments could have been due to a number of factors, including higher than realistic contaminant concentrations and relatively short exposure periods in the controlled work. In the field studies, fluctuations in temperatures and air concentrations may affect pollutant uptake. The vegetation pollutant loading in the field may also be influenced by POPs in the atmospheric particulate phase; in the laboratory experiments, contaminants would only be expected to be present in the vapor phase. Additionally, in the field, plants will lose some of the pollutant loading as a result of natural shedding of outer portions of the ‘leaf’ (32, 33). In summary, different plant species accumulate POPs differently, so to justifiably make comparisons of vegetation pollutant burdens between sites it is necessary to collect samples of the same (or possibly taxonomically very similar) species and age; this study shows that it is insufficient to merely correct for lipid contents. However, it is difficult, if not impossible, to collect the same plant species on a large regional/global scale, which would be desirable to investigate environmental pollutant behavior. An alternative would be to deploy a ‘pseudo-leaf’ as a passive sampler at different sites. Work on U.S. Geological Survey-designed semipermeable membrane devices has shown that they have great potential for deployment as passive atmospheric monitors of POPs over large ranges in latitude, thereby acting as pseudo-leaves (25). Concentrations of PCBs and OCs were found to be higher in lichen samples than in pine needles, and it is suggested that this be due to differences in plant age and perhaps physiology and uptake mechanisms. Concentrations of PCBs in H. physodes were found to increase with decreasing temperature, but no consistent trends were seen between PCB concentrations in P. sylvestris and site temperature. Pseudo-plant/air partition coefficients, however, indicate favored accumulation of PCBs in vegetation at lower temperatures and favored plant accumulation for less volatile congeners. R/γ-HCH ratios were found to be higher in plant samples from colder northern areas than in samples from further south. This is indicative of increasing distance from source regions of lindane (R-HCH), long-range atmospheric transport, and closer proximity to northern oceans that have been shown to be outgassing R-HCH (24). No other trends in OC concentrations of the vegetation samples were observed. It should be noted that although this study has tried to relate plant POP concentrations to temperature, temperature may actually be masking other effects, such as differences in plant growth rates, ages (in the case of lichen), snow cover, and even actual atmospheric concentrations. Much more work is needed before vegetation can be used as a monitor for precisely inferring atmospheric concentrations or behavior of POPs on regional/global scales.
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Acknowledgments Collection of vegetation samples was funded by the Royal Society. We are also grateful to Frank Wania for help with sample collection and for many useful discussions on the GF hypothesis and Andrew Peters for help with the OC analysis.
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Received for review February 13, 1998. Revised manuscript received June 12, 1998. Accepted June 22, 1998. ES980150Y
