Uptake of Gaseous DDE in Spruce Needles - American Chemical

Uptake of Gaseous DDEin Spruce Needles. Heike Hauk, Gunther Umlaut, and Michael S. McLachlan*. Ecological Chemistry and Geochemistry, University of ...
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Environ. Sci. Technol. 1994,28, 2372-2379

Uptake of Gaseous DDE in Spruce Needles Heike Hauk, Gunther Umlauf, and Michael S. McLachlan"

Ecological Chemistry and Geochemistry, University of Bayreuth, 95440 Bayreuth, FRG The accumulation and desorption of gaseous DDE in spruce needles was investigated in two chamber experiments using Picea omorika and in a third using Picea abies. The P. omorika needles were divided into two fractions for analysis: the soluble cuticular lipids and the remaining needle. The data were used to parameterize a one-compartment (complete needle) and a two-compartment (surface, reservoir) plant model. The one-compartment model performed poorly, whereas the uptake and clearance behavior of the complete needle was described very well with the two-compartment model. However, the two model compartments did not correspond to the two needle fractions that were analyzed for P. omorika. The validation of the P. abies model using environmental data was quite successful, whereas the validation of the P. omorika model gave poor results. It was concluded that chamber experiments are not sufficient for describing the air/plant exchange of contaminants for which the halflife of the exchange process with the slowest leaf compartment is longer than the length of the experiment. Furthermore, model validation is essential if the results of chamber experiments are to be extrapolated to environmental conditions. Introduction

Plants play an important role in the fate of organic chemicals in the environment. The uptake of airborne pollutants into plants is an important pathway of contaminants into terrestrial ecosystems and is frequently the first step in food chain accumulation. This tendency to accumulate airborne pollutants also makes plants useful as biomonitors of the state of atmospheric contamination (1-7). Airborne pollutants can reach plant surfaces through wet deposition, dry deposition of particulate matter, and dry gaseous deposition. A major uptake mechanism for many hydrophobic, nonionic compounds is thought to be diffusive transfer from the gas phase to the leaf surface. Although much of the evidence in support of this hypothesis has been circumstantial to date, the dominant role of gaseous diffusion in the accumulation of DDE and PCB 101in spruce needles was recently demonstrated (8). Plant accumulation of gaseous contaminants has traditionally been investigated using uptake and depuration experiments. The plant is first placed in a contamination chamber containing elevated levels of the study compound in the gas phase and the increase in plant concentration with time is measured. Following this uptake phase, the plant is placed in a clean atmosphere, and the clearance or decrease in concentration with time is measured. Studies of this kind have been reported for azalea (9-11), spruce needles (12),and grass (13). In all cases, the whole leaf concentrations were measured, and the data were interpreted using a simple one-compartment model. A close examination of the published data revealed that in many cases a sudden decrease in the leaf concentration occurred between the end of the accumulation and the 2372

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first measurement in the clearance phase, a behavior that was neither discussed nor accounted for in the models employed to interpret the data. This indicated to us that there must be a rapid reversible process which leads to a fast initial desorption of the compound, in effect a second leaf compartment. The possibility that several leaf compartments could be participating in the uptake of lipophilic compounds has been mentioned in the literature. Gobas et al. (14) suggested that a two-compartment plant model might better describe their data on partitioning kinetics between aquatic macrophytes and water. Schreiber and Schonherr (15) identified two plant compartments in their spruce needle-water system, one of which they attributed to adsorption on the needle surface and the second to partitioning in the needle. Recently Tolls and McLachlan used a two-compartment model to describe the accumulation of a range of trace organics in a grass culture (16).A two-compartment leaf behavior was suggested for spruce needles by Reischl et al. ( 3 ) ,who proposed that these compartments could be delineated through solvent extraction. These authors had observed that the fraction of the total needle concentration of DDE that could be extracted with two 30-s washings with dichloromethane decreased with increasing age of the needle. These thoughts were pursued in the work presented here. A solvent extraction method was developed that gave a reproducible separation of the needle into two compartments defined by the method: soluble cuticular lipids (SCL) and remaining needle (RN). Two contamination experiments with spruce needles were then conducted usingp,p '-DDE. The SCL and RN were separately analyzed, yielding uptake and clearance curves for both compartments. A third experiment was conducted with another spruce species in which only the total needle concentrations were determined. The results were fitted with one- and two-compartment models of the needle. Materials and Methods

Accumulation and Clearance Chambers. Two (1X 1 X 0.7 m) glass chambers were used, one for the contamination and the other for the clearance process. Each chamber was illuminated by six 65W true-light fluorescent tubes with a day-night rhythm of 15h of light and 9 h of darkness. The contamination system was assembled as follows: 540 g of sea sand (Merck) was mixed with 30 mL of a 1000 ppm standard solution of p,p '-DDE in n-hexanelacetone (1:l). The solvent was evaporated under vacuum overnight, The contaminated sand was filled into two columns, and these were installed in the contamination apparatus. A water jacket maintained a temperature of 40 "C in the columns. An airflow of 150 mL min-1 was passed through the sand columns. This highly contaminated air then entered the chamber where a fan mixed it with a flow of 40L min-l (experiments 1and 2) or 78 L min-l (experiment 3) room air. The room air was drawn into the contamination chamber through a glass fiber filter, which prevented 0013-936X/94/0928-2372$04.50/0

0 1994 American Chemical Society

the entrance of airborne particles. The air pressure in the chamber was kept slightly lower than in the laboratory to prevent contamination of the laboratory air. The air contamination was started 3 days before each experiment to allow the chamber surfaces to come into equilibrium with the air. A spruce tree was then placed in the middle of the chamber, and the soil was covered with aluminium foil to minimize soil contamination. In the first two experiments, two different 10-year-oldPicea omorika were used; in the third experiment, a 12-year-old Picea abies was used. The tree was watered every 2 days. The temperature was 20 f 1"C (experiment l ) , 22 f 2 "C (experiment2), and 24 f 1"C (experiment 3). The relative humidity ranged between 37 and 50%. Following the contamination phase, the tree was transferred to the clearance chamber. In this chamber, the air was cleaned at a rate of 160 L min-1 using an activated charcoal filter. The temperature was 30 f 1 "C (experiment I), 23 f 2 "C (experiment 2), and 24 f 1 "C (experiment 3). The air moisture ranged between 30 and 42%. Air Sampling and Workup. Air samples were collected using a double Florisil trap operating at a flow rate of 40 L min-l over 3 days. The sample volumes were measured with a gas flow meter connected in series between the sampling head and the pump. The first trap, which contained 18 g of Florisil covered with glass wool spiked with 1OOpL of a 1ppm 13C12-labeled p,p '-DDE internal standard solution,was transferred into a glass column and eluted with 400 mL of n-hexane. The second trap, 9 g of Florisil separated with glass wool from the first trap, was eluted with 250 mL of n-hexane. The extracts were concentrated to 2 mL with a rotary evaporator, transferred to 100-pL vials, and evaporated almost to dryness under a nitrogen stream. The residues were taken up in 100 pL of toluene. Plant Sampling and Workup. Approximately 10 g of 6-month-old needles (12-month-old needles in experiment 3) were collected by cutting branches off the tree. The branches were wrapped in aluminium foil and either worked up immediately in the laboratory or stored at -20 "C. Prior to extraction, the needles were removed from the branches by first freezing them in liquid nitrogen and subsequently dislodging them through mechanical agitation. SCL. A total of 5 g of fresh needles was extracted with 100 mL of dichloromethane for 10 min. A complete description of the solvent extraction method has been published elsewhere (17). After filtration over Na2S04, the SCL extract was spiked with 100 pL of a 1ppm 13C12labeled DDE internal standard solution and evaporated to 2 mL. The extract was cleaned up using a Florisil column (8.5 g of Florisil60-100 mesh, deactivated with 4% H2O). The column was eluted with 150 mL of n-hexane. The sample was again concentrated to 2 mL, transferred to a 100-pLvial, and carefully evaporated under a nitrogen stream almost to dryness. The residue was taken up in 100 pL of toluene. Remaining Needle. The preextracted needles from above were spiked with 100 pL of internal standard solution. A total of 70 mL of n-hexane was added, and the needles were ground with an Ultra-Turrax blender. The extract was placed in an ultrasonic bath for 10 min, after which time the supernatant was decanted. The ultrasonic

Table 1. Needle Properties ratio of fresh to dry weight amount of SCL (mg g' dry weight) surface area (cm2 g' dry weight) density of fresh needles (g m-3) density of SCL (g m-3)

2.6 f 0.12

32 f 1.7 (P.omorika), 15 EL: 1.5 (P.abies) 200 f 15 920 000 f 8200 1047 000 f 2400

extraction was repeated twice with 50 mL of n-hexane. The combined fractions were dried over Na2S04, concentrated to 2 mL with a rotary evaporator, and cleaned up using the Florisil column described above. The sample was again concentrated to 2 mL, transferred to a 100-pL vial, and carefully evaporated under a nitrogen stream almost to dryness. The residue was taken up in 100 pL of toluene. Total Needle. The method was the same as for the remaining needle. Needle Properties. After extraction, the needles were dried at 105 "C for 24 h to determine the dry weight. The SCL content was measured by extracting an aliquot of the needles with dichloromethane for 10 min. The extract was concentrated with a rotary evaporator and air dried under a fume hood until the weight was constant. The surface area was measured using a projection method described by Schulze et al. (18). The density of the needles was determined by displacement of water. The density of the SCL was determined by dropping disks of SCL into NaCl solutions of different densities. Analysis. All samples were analyzed on a GC/MSD (Hewlett-Packard GC5890/MSD5970) in split/splitless mode using an HP Ultra2 capillary column (25 m, 0.32 mm i.d., 0.52 gm film thickness) and helium as the carrier gas. The injector and transfer line temperatures were 280 "C, and the oven temperature program was as follows: 100 "C, 1min isothermal, 10 "C min-I up to 300 "C, 5 min isothermal. Quantification was done in the SIM mode using the response factors obtained from a mixture of a native reference standard and the internal standard solution. DDE was not detected in either the method blanks or in the second Florisil trap mounted to detect breakthrough. The recovery of the internal standard was between 80 and 100%. The detection limit was ca. 0.8 ng/g of dry needle matter. Results and Discussion

Experimental Results. The measured needle properties are summarized in Table 1. The results of the two experiments with P. omorika are plotted in Figures l a and 2a. There is excellent agreement between the parallel samples of the SCL and RN fractions in experiment 1. The mean normalized difference [= 2(C1- Cz)/(C1+ CZ)] between the parallel SCL and RN samples was 10% and 17% , respectively. A rapid increase in the SCL concentration at the beginning of the accumulation phase was accompanied by an initial decrease in the air concentration in both experiments. Thereafter the air level recovered, although the initial concentration measured before introducing the tree was not again attained. Multiplying the increase in needle concentration of 30 ng/g dry weight (dw) measured in the first 30 h by an estimated total needle fresh weight of 300 g yields 3.5 pg of DDE that was adsorbed by the tree Environ. Scl. Technol., Vol. 28, No. 13, 1994

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Flgure 1. (a)Measured concentrations of p , p ’ W E In air, Soluble cuticular lipas (SCL).and remaining needle (RN)of P. onwrka durlng experiment 1. Parallelsamples of the SCL and RN fractions were analyzed. (b) Comparlson of the measured concentrations of WE Inthe needles of experiment 1 with the model predictions. The onecompartment model was used wkh dm = 3.4 mol Pa-’ h-’ m3 and b$JN = 9850 mol Pa-’. The two. compartment mcdel was used with the parameters for P. omorika listed in Table 2.

during this period. This lies in the same order of magnitude as the 3.6 fig that the air supply delivered, assuming that the initial concentration of 50 ng/m3 was maintained. Thus in the first hours the tree adsorbed a large fraction of the compound that was introduced into the chamber. This explains the initial decrease in the air concentration and indicates thatthe initialuptake of DDE in needles is limited by transport to the needle surface and not by a resistance within the needle itself. Following the initial sharp increase, the SCL concentrations continued to rise a t a slower rate while the RN levels responded sluggishly. The beginning of the clearance phase was marked by a very rapid decrease in the SCL concentration. Within about 1 day, it fell to less than one-third of the level measured a t the end of the accumulation. Thereafter the SCL values decreased very slowly (see Figure la). The concentrations in the RN fraction did not display an abrupt change a t the beginning of the clearanceand decreasedveryslowly. The last several 2374

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RN values in experiment 1 could not be determined. The results of the experiment with P. abies are plotted in Figure 3. In this case, only the total needle concentrations were determined. The behavior was similar to that observed for P. omorika when the SCL and RN values were added together. The sharp decrease in concentration a t the beginning of the clearance phase that we suspectedhad been overseen in earlier studies was clearly demonstrated in all three experiments. The two very different slopes observed during the clearance phase suggestthat the accumulation of DDE in the needles is governed by a t least two different compartments. The fact that the sharp decrease a t the beginning of the clearancephase was restricted to the SCL fraction further supports this hypothesis. However, for P. omorika, these two compartments do not correspond to the two compartments defined by the extraction method, namely, SCL and RN. If this were the case, then the concentration in the SCL compartment should de-

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crease to nearly 0 at the beginning of the clearance, given that the faster clearance rate is orders of magnitude faster than the slow clearance from the RN compartment. The fact that the SCL concentration plateaued at ca. 20% of the initial clearance value (see Figure la) indicates that this fraction contained not only the fast reacting compartment but also part of a slower reacting one. As a consequence,the chemical fractionation, which was useful to confirm the existence of a fast surface compartment, was disregarded for the modeling of the data. Instead the total needle concentrations were employed. Modeling t he Results. The fugacity modeling concept was used to interpret the data (19).This approach has many advantages. In this work, the ease in identifying the temperature dependence of the various model components proved to be particularly useful. Since plants come in all shapes and sizes, we did not find i t advantageous to follow the conventional fugacity modeling approach and define a unit tree or unit needle. Instead the mass balance equations were normalized with respect to needle

volume. The main consequence is that the conventional D value becomes a d value, or the amount of D associated with 1m3of needles. The d values and 2 values then have the same frame of reference, namely, compartment volume, which adds an elegant dimension to the fugacity modeling of compartments such as plants that are present in the environment in great numbers. This approach also has distinct advantages when evaluating multicompartment plant models. The data were first modeled using a partitioning model with one needle compartment and linear first-order kinetics. The model is defined by

where 2 is the fugacity capacity (moll m-3 Pa-l), u is a compartment volume normalized to the whole needle volume (= 1m3 mS for this one-compartment model), f is fugacity (Pa), t i s time (h), d is the fugacity conductance between two compartments normalized to the whole needle Environ. Sd.Technol., Vol. 28, No. 13, 1994 2375

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volume, Le., a fugacity conductivity (moll Pa-l h-' m-3), and the subscripts A and N refer to air and needle. Invoking the two resistance theory, dAN is defined as dAN = (l/kAaANZA + ~ / ~ N ~ A N Z N ) - ' ( 2 ) where k is the mass transfer coefficient (ml h-l) and a is the interfacial surface area between two-compartments normalized to the whole needle volume (m2m-3). This model was fitted to the data for P. omorika using the approach that has often been employed in other studies. The time constant, which reduces to kNaN/uN when the dominant resistance is in the needle, was fitted using the clearance data from experiment 1, ignoring the initial rapid drop in the needle concentration. The fugacity capacity of the needle ZNwas then determined by optimizing the fit during the uptake phase of the same experiment. The air fugacities were obtained by linear interpolation between the measured values, whereby the initial air fugacity in the accumulation chamber was set to the 76-h value. As the air concentration of 3.2 ng/m3measured over the first 3 days of the clearance was due to the large amount of DDE that desorbed from the needles in the first hours, a linear decrease was assumed from 6.2 ng/m3 at the beginning of the clearance to 0.12 ng/m3 after three days. A needle/air bioconcentration factor (ZN/ZA)of 2.4 X 107 and a fugacity conductivity of 3.4 moll Pa-' h-l m-3 were obtained. The modeling results and the measured needle concentrations from experiment 1 are plotted in Figure Ib. The model does a poor job predicting the experimental values, with a root mean square deviation from the measured values of 81% . The accumulation is first underpredicted and then overpredicted. The clearance data are vastly overpredicted, largely because the model cannot account for the abrupt drop in needle concentration a t the beginning of the clearance. The model fit for experiment 2, which is not shown here, is even worse for the same reason. This demonstrates that a onecompartment needle model is inadequate for describing the behavior of DDE. A two-compartmentmodel of the needle was then tested. In this model a well-mixed surface compartment (S) and 2376

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reservoir compartment (R) are aligned in series with the atmosphere (A). Chemical transport occurs as diffusion between the atmosphere and the surface compartments and between the surface and reservoir compartments. The mass balances of the two needle compartments are then:

The conductances are once again treated using the tworesistance model:

The temperatures in the chambers varied between 20 and 30 "C. Horstmann (20) showed that the surface fugacity of DDE in P. abies needles increases by a factor of 2 when the temperature is increased from 20 to 30 OC. The fugacity capacity decreases by a corresponding amount. The values of 2 s and ZRwere corrected for the mean chamber temperature on the basis of these results. Since d S R is a function of 2 s and ZR,it was corrected in the same way. The initial uptake in the needles was shown above to be limited by an atmospheric resistance and not by a resistance in the needle. Hence AS is dominated by ZA (see eq 5) and is, therefore, not a strong function of temperature. The influence of temperature on the other variables (kA,k s , kR, ZA)is much smaller, and no correction was applied. Two models were parameterized, one for P. omorika using the results of experiments 1 and 2, and one for P. abies using the results of experiment 3. The optimized parameters are listed in Table 2, and the modeling results are plotted in Figures lb, 2b, and 3. The model does an excellent job describing the experimental results. The root mean square deviation is 15% for experiment 1 , 2 3 % for experiment 2, and 5.7% for experiment 3. The two experiments with P. omorika are described well using the same model.

Table 2, Fugacity Conductivities (mol Pa-' h-' m-3) and Products of Normalized Compartment Volume and Fugacity Capacity (mol Pa-' m-5) for DDE in Spruce Needles Optimized with Two-Compartment Model at 20 'C

dAs dsR

vszs VRZR

P. omorika

P. abies

25.5' 0.787 336 2260

96.2' 2.97 581 17 100

Note that dAs was a function of the turbulence conditions in the chamber and is likely different in an outdoor environment.

Validation of the Models with Environmental Data. Two sets of environmental data were used to test the models, In the first case, P. abies trees were investigated at a site in Niirnberg, 80 km south of Bayreuth. Samples of needles were collected every 2 weeks between August 1,1990, and January 11,1991. Only the fresh growth (38.5 months old) was sampled. Air samples were collected continuously, and the gaseousand particle-bound fractions were separately analyzed on a weekly basis (21). The gas phase concentrations of DDE ranged between 5.9 and 31 pglm-3 with a mean level of 14 pgl m-3. The fraction associated with particles increased from summer to winter, but was low, on the average 5% of the gas-phase levels. The P. abies model was run using the initial needle concentration, the measured gas-phaseconcentrations, and the average weekly temperatures along with the temperature correction for the fugacity capacity described in ref 20. Since the time frame of the study was long, the model behavior was not significantly affected by the magnitude of dAs, and hence the value obtained in the chamber experiment was employed. The predicted and measured needle concentrations are plotted in Figure 4. The model overpredicts the needle concentration for almost the whole study, intersecting the measured levels only at the end of the experiment. Whereas the model follows the measured increases in needle concentration quite well, it fails to reflect the observed decreases. However, despite these shortcomings, the results are quite satisfactory for a model of a complex environmental process. The models were further tested using data from 6-month-old P. abies and P. omorika needles that were collected in October 1989 from trees growing adjacent to each other on the campus of the University of Bayreuth (22). As no air data were available, it was only possible to compare the relative concentrations as predicted by the models and as measured. The P. abies and P. omorika models were both run for the period from April to October using the same constant temperature and gas-phase concentration and an initial needle concentration of zero. The predicted concentration for P. omorika was a factor of 3.7 lower than the level predicted for P. abies. However, the measured concentrations of DDE and a range of other SOC in P. omorika were 1.5 times higher than in P. abies, The discrepancy between the predicted and measured concentration ratio was a factor of 6. In view of the relatively good results obtained for P, abies from the first validation exercise, it appears that the P. omorika model greatly underpredicts the uptake of DDE, despite the fact that the experimental data base for this model was much stronger. Discussion. The results clearly demonstrate that a one-compartment model is inadequate for describing the

short- and medium-term behavior of DDE in spruce needles. This is particularly important for the interpretation of uptake and clearance experiments. The use of a one-compartment model can lead to very different estimates of the kinetics and partition coefficients than a twocompartment approach. In view of this fact, it would be prudent to reexamine the results of previous studies with respect to the applicability of the one-compartment models that were employed. The multicompartment behavior of the needles also has implications for their use as biomonitors. One portion of the needle reacts within hours to changes in environmental conditions, whereas a second compartment takes months to react. If one could analytically separate these twocompartments, one would have a measure of both the longterm contamination of the atmosphere as well as the contamination present in the air at the time of sampling. The method of separation tested in this paper was, unfortunately, not successful, but this idea may be worth pursuing. The very fast kinetics for a significant fraction of the needle storage capacity also mean that caution may be required in handling needles after sampling. Although the surface compartment makes up a relatively small fraction of the total storage capacity, it takes a long time for the inner compartment to approach equilibrium, and hence the surface compartment contains a significant fraction of the contaminant load in young needles. Thus, the concentration of semivolatile organics in needles may increase or decrease significantly if exposed to air for relatively short periods of time. The air temperature at the time of sampling may also be relevant, since the concentration in the surface compartment would be significantlylower after several hours at a high temperature than during a cold spell, assuming that the air concentration was the same. The results of the second validation experiment indicate that the two spruce species show different uptake behavior. Interestingly, the fugacity capacities of the surface compartment (Table 2) are quite similar, with P. omorika having a somewhat lower value although the soluble cuticular lipid content was more than twice as high as in P. abies. While there is apparently no correlation between the capacity of the surface compartment and the soluble cuticular lipid content, the structure and nature of the cuticular components likely play an important role in determining the differences in uptake behavior. The mixed results of the model validation are disappointing, but not necessarily surprising. One explanation for the poor behavior of the P. omorika model could be the variation in behavior between different individuals. From our experience this variation is generally less than f50% ,however, and thus cannot explain the much larger deviations that were observed. It is also possible that certain key aspects of the contaminant uptake are not accounted for in the model or that the properties of the needles were different in the chambers and outdoors or change so rapidly with age that the needle properties measured in the chamber experiments were relevant for only a small portion of the period of exposure. However, we consider the largest error to lie in the extrapolation of an experiment of several hundred hours to predict the behavior in a plant that requires many thousand hours to reach equilibrium. A plant is not a well-mixed organism, and it is possible that it cannot be modeled as such. Jt Environ. Sci. Technol., Vol. 28,

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may be that the spruce needles contain further compartments that were not observed due to the limited length of the experiments. Furthermore, the parameterization of the model is primarily determined by the slope of the clearance curve for the reservoir compartment. Since this is so shallow, the model is extremely sensitive to experimentalianalytical error in this area. For both species, the value of ZR could be varied by more than a factor of 5 without much affecting the fit of the model to the experimental data. Rather than questioning the poor results for the P. omorika model, we believe that the good results for the P. abies model were fortuitous. The experience in this study shows that the contamination chamber approach is not sufficient for modeling contaminant uptake in plants with kinetic half-lives much longer than the length of the experiment. The problems addressed above are relevant to a significant body of literature on the uptake of organic contaminants in aerial plant parts. For instance, anumber of current models of plant uptake are based on contamination chamber experiments that were conducted with azalea (11,23). While these experiments were certainly ground-breaking, half-lives of semivolatile organic compounds in azalea were estimated to be typically 12002200 h (9), similar to those obtained for spruce in this study. Furthermore, the two-compartment behavior that was apparent in many of the azalea experiments was not accounted for in the one-compartment model used to interpret the results. Although the resulting “azalea model” (11)may, by good fortune, be a good description of the contaminant interactions with azalea leaves, this cannot be concluded from the chamber experiments and needs to be verified using other methods. The difficulties encountered validating the models of DDE uptake in spruce are a reminder that all models based on laboratory experiments are laboratory models until they have been validated in the environment. We are unaware of any models of plant uptake of atmospheric SOC that have been properly validated. Simplistic approaches are likely to be of limited use. For instance, during the first validation experiment, the ratio of the DDE concentration in the needles to the average concentration in the gas phase 2378

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during the week preceding sampling of the needles varied by a factor of 20. In view of this result for one species in one location, recent suggestions that atmospheric concentrations of SOC can be reliably estimated from the contaminant concentration in almost any plant material using the azalea model (24)must be considered premature. Acknowledgments

We thank Anja Freiberger for her assistance in the laboratory as well as Dr. Michael Reissinger and Dr. Arthur Reischl for their support with the chamber experiments. This work was supported by the German Federal Ministry of Research and Technology. Literature Cited (1) Buckley, E. H. Science 1982, 216, 520-522. (2) Gaggi, C.; Bacci, E.; Calamari, D.; Fanelli, R. Chemosphere 1985, 14, 1673-1686. (3) Reischl, A,;Reissinger, M.; Hutzinger, 0.Chemosphere 1987, 16, 2647-2652. (4) McLachlan, M. S.; Reischl, A.; Reissinger, M. In Man and his Ecosystem; Brasser, L. J., Mulder, W. C., Eds.; Proceedings of the 8th World Clean Air Congress; Elsevier: Amsterdam, 1989; vol. 2, pp 87-92. (5) Reischl, A.; Reissinger, M.; Thoma, H.; Hutzinger, 0.

Bioindikation luftgetragener Dioxine und Furane mit Hilfe von Fichtennadeln; Final report to the Bavarian State Ministry for Development and Questions of the Environment on Grant 6490-953-93037; University of Bayreuth: Bayreuth, 1991. (6) Calamari, D.; Bacci, E.; Silvano, F.; Gaggi, C.; Morosini, M.; Viehi. M. Environ. Sci. Technol. 1991, 25, 1489-1495. (7) SaTe, S.; Brown, K. W.; Donnelly, K. C.; Anderson, C. S.; Markiewicz, K. V.; McLachlan, M. S.;Reischl, A.; Hutzinger, 0. Environ. Sci. Technol. 1992, 26, 394-396. (8) Umlauf, G.; Hauk, H.; Reissinger, M. Environ. Sci. Pollut. Res. Int., in press. (9) Bacci, E.; Gaggi, C. Chemosphere 1987, 16, 2515-2522. (10) Bacci, E.; Calamari, D.; Gaggi, C.; Vighi, M. Environ. Sci. Technol. 1990,24, 885-889. (11) Bacci, E.; Cerejeira, M. J.;Gaggi, C.; Chemello, G.; Calamari, D.; Vighi, M. Chemosphere 1990,21, 525-535. (12) Reischl, A.; Reissinger, M.; Thoma, H.; Hutzinger, 0. Chemosphere 1989, 19,467-474.

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Received for review April 22, 1994. Revised manuscript received August 17, 1994, Accepted August 30, 1994,"

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Abstract published in Advance ACS Abstracts, October 1,1994.

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