Environ. Scl. Technol. 1094, 28, 159-166
Partitioning of Semivolatile Organic Compounds between Air and Lolium multlflorum (Welsh Ray Grass) Johannes Tollst and Mlchael S. McLachlan'
Department of Ecological Chemistry and Geochemistry, University of Bayreuth, 95440 Bayreuth, FRG The kinetics and steady-state partitioning of semivolatile organic compounds between the gas phase and Lolium multiflorum were investigated using a solid-phase fugacity meter. This method proved to be very useful, providing precise measurements of the partitioning behavior and information on the size of the different storage compartmenta in the leaf. A fugacity model of the aidleaf exchange was assembled and applied to the data. A two-compartment model consisting of a small surface compartment and a large interior reservoir was employed. The twocompartment structure was necessary to describe the shortterm kinetics in the leaf. A good correlation was obtained between the leaflair partition coefficient and the octanoll air partition coefficient. ~~~~~
~~
Introduction The transport or organic contaminants between the atmosphere and vegetation is of interest for several reasons: (a) An understanding of the transport processes could enable us to use plants as biomonitors for atmospheric contaminants (1-3). (b) It seems likely that terestial vegetation plays an important role in the fate of many compounds (4). (c) Plants are key links in the agricultural food chains, which are the main pathways of human exposure (5) for many environmental pollutants. Persistent hydrophobic compounds show a particularly strong tendency to accumulate in the terrestrial environment and in human tissue. These compounds have been found to accumulate in moss (6),in tree bark (3, and particularly in the leaves of trees and grasses (1-3,8-12). There are several possible pathways for organic contaminants to enter leaves: (a) root uptake, (b) dry gaseous deposition, (c) dry deposition of particles, and (d) wet deposition. Several studies have demonstrated that root uptake and translocation of strongly hydrophobic organic compounds are negligible in a variety of plant species (1315). Recent work in our research group has shown that dry gaseous deposition is the main pathway of polychlorinated biphenyls and other organochlorine compounds to spruce needles (16). We have therefore chosen to examine this process in more detail. It is currently believed that dry gaseous deposition can be understood as a partitioning process between air and hydrophobic compartments in the leaf. A frequently used approach to describe environmental partitioning processes is the fugacity concept (17-20). The fugacity is related to the chemical potential and can be envisaged as the tendency of a chemical to escape from a particular medium. Equilibrium partitioning exists between two media if the fugacities of the compound in each medium are equal. Hence, the ability to determine fugacities in different media would be of value in investigations of partitioning phenomena.
A solid-phase fugacity meter was developed in our laboratory to determine the fugacity at the surface of solids (21). The fugacity determination is similar to a dynamic headspace analysis. Air is passed over a solid surface in a manner such that the air leaving the sample chamber is in chemical equilibrium with the sample surface. The concentration, c, in the gas exiting the sample chamber is measured, and the surface fugacity, f , is calculated using the relationship between the fugacity in a perfect gas mixture and the concentration (22): f = cRT/M (1) During testing of the solid-phase fugacity meter with artificially contaminated spruce needles, Horstmann and McLachlan (21)observed a decline of the surface fugacity with time. When however, the needles were first allowed to stand for several days, a constant but lower fugacity was measured. The authors suggested that the phenomenon was due to nonequilibrium conditions in the needles, that the contamination of the spruce needles in a gas chamber had induced a fugacity gradient between the needle surface and the interior, and that the fugacity measurements had monitored the equilibration process between the surface and the remainder of the needle. These observations indicated that, if a fugacity gradient is present, the fugacity meter could be used to investigate contaminant transport within leaves. In this work, we have utilized this phenomenon to investigate the exchange of hydrophobic compounds between the atmosphere and grass leaves. A grass culture was exposed to high air concentrations of several semivolatile organic compounds for a short period of time to create a fugacity gradient within the grass leaves. The decline of the surface fugacity with time was monitored with the fugacity meter. The results obtained were employed to develop a two-compartment fugacity model of the grass leaf.
Experimental Section
t Present address: Research Institute of Toxicology, University of Utrecht, Utrecht, The Netherlands.
The grass cultures (Lolium multiflorum, var. Ninak) were sown and allowed to grow for 4-6 weeks prior to being used for the experiments, reaching a canopy density of ca. 1.6 kg/m2. Measurements of the projected surface of the grass leaves with a Licor Model 3100 area meter gave an average value of 4.4 m2/kg. The density of the grass leaves was 820 kg/m3, and the extractable lipids amounted to 0.32% (f0.04%) of the wet weight as determined by Soxhlet extraction (6 h) with petroleum ether (23). With an assumed average density of 1008 kg/ m3, the extractable lipids contributed approximately 0.35% to the total volume of the leaf. For modeling purposes, the relative volume of cutin was assumed to be 0.7% as suggested by Riederer (18). Hence, the relative volume of all lipid-like leaf constituents (total ether-extractable lipids + polymeric cutin) was estimated to be 1%of the total leaf volume. Soluble cuticular lipids, as determined
0 1993 American Chemical Soclety
Envlron. Scl. Technol., Vol. 28, No. I,1994 159
0013-936X/94/092&0159$04.50/0
by a 1-min extraction of the grass leaves with CH2C12, amounted to 0.15% (10.03%) of the leaf fresh weight, corresponding to a relative volume of 0.12%. The grass cultures were contaminated using the same gas chamber design as used previously (21). The temperature within the chamber varied between 16 and 18 "C. The compounds studied were pentachlorobenzene (QCB); hexachlorobenzene (HCB); a-hexachlorocyclohexane (a-HCH); 7-hexachlorocyclohexane (7-HCH); 2,4,4'-trichlorobiphenyl (PCB 28); 2,2',5,5'-tetrachlorobiphenyl (PCB 52); 2,2',4,5,5'-pentachlorobiphenyl (PCB 101); phenanthrene (Phen); anthracene (Anth); fluoranthene (Fla); pyrene (Pyr); 1,2,3,44etrachloronaphthalene (TCN); and 1-chloroanthracene (ClA). The contaminant concentrations exceeded those measured in normal ambient air by at least a factor of 500 for the chlorinated compounds. The concentrations of the polycyclicaromatic hydrocarbons could not be increased significantly above those in ambient air. The fugacity meter developed by Horstmann and McLachlan (21)for laboratory experiments was modified by increasing the size of the sample chamber to 530 mL and by using a water-jacketed gas wash bottle so that the whole apparatus was temperature controlled. In preliminary experiments, no particulate matter and very low contaminant levels on the post fugacity meter glass fiber filters were found. Thus, the filter and filter holder were eliminated from the apparatus. The operating conditions required to obtain an air/ surface equilibrium at the exit of the sample chamber were determined in a manner similar to that employed previously (21). Grass leaves were first contaminated in the contamination chamber and then allowed to equilibrate for 60 h a t room temperature in a sealed vessel. A series of fugacity measurements using a fully packed sample chamber (ca. 35 g of grass) was performed at 25 "C and 100% RH while the air velocity was varied. An air retention time of 20 s, corresponding to a linear air velocity of 0.013m/s through the filled sample chamber, was chosen. Subsequent continuous measurements at this flow rate with a reduced sample size yielded the same fugacities, Also, no increase of the fugacities was observed following an interruption of the measurements. It should be noted that, due to the plug flow design of the sample chamber, depletion of contaminant at the leaf surface as a result of the measurement will occur primarily in the sample material close to the entrance of the sample chamber. In this respect, the sampling chamber can be compared to an adsorber cartridge. Only after breakthrough of the sample chamber does the measurement itself disturb the contaminant behavior in the grass at the exit of the chamber and, thus, the fugacity measurement. Seven contamination experiments of varying length (2, 5, 12, 24, 48, 120, and 240 h) using the same air concentrations were performed. Immediately following the contamination, ca. 35 g of grass was cut, weighed, and introduced into the sample chamber of the fugacity meter. The series of surface fugacity measurements began with 10-L air samples taken 7,14.5,22.5, and 60 min after the end of the contamination. Thereafter, 45-L air samples were collected at 2, 5, 12, 24, 48, 120, and 240 h. The surface fugacity measurements were performed at 18 "C and 100% RH. In preliminary experiments, no decrease of the surface fugacities was observed over a period of 36 h following 160
Environ. Sci. Technol., Vol. 28, No. 1, le94
equilibration of the grass for 60 h. It was therefore concluded that degradation or incorporation of the study compounds was not significant within the time frame employed in these experiments. Visual inspection of the grass revealed no signs of wilting or other aging after 60 h in the sampling chamber. Prior to the surface fugacity measurements, the sample chamber was preconditioned in order to minimize initial sorption of the contaminants to the glass surface of the apparatus. To this end, a second grass culture was contaminated for the same length of time as the one which was to be measured. One hour before the scheduled end of the contamination, ca. 35 g of grass was cut from the preconditioning culture and introduced into the sample chamber. Air was passed over the grass for 30 min under the conditions specified above. This grass was removed from the sample chamber just prior to introducing the grass to be measured. Air concentrations in the contamination chamber were measured immediately before, 10min after beginning, and immediately prior to the end of each contamination experiment using a florisil trap dosed with an internal standard mixture. For experiments lasting longer than 24 h, one air sample per additional day was obtained. The concentrations in the grass were measured before and after each contamination. The grass was dosed with the internal standard mixture, extracted in hexane:acetone (l:l,v:v), and cleaned up on a florisil and on an octadecylsilane column. All samples were analyzed using HRGC/LRMS. The samples were quantified using the internal standard mixture which contained eight labeled isotopes of the compounds studied. Average recoveries ranged from 31% for QCB to 94% for PCB 101. Results and Discussion
Fugacity Measurements. The air conditions during the grass contamination were fairly constant, varying not more than 25% around the mean value with the exception of the 240-h exposure. In Figure 1,the ratios of the grass concentration at the end of each exposure period to the air concentration for that period ( C G / C A ) are plotted. The leveling off of the curve for the chlorinated benzenes (Figure la) indicates that these compounds are close to equilibrium after 240 h in the contamination chamber. No leveling off was observed for HCH isomers, PCB congeners, or TCN (Figure 1,panels b, c, and e, respectively). The quotient of the final and initial values of C G / C A gives an indication of the degree to which the grass was contaminated. The quotients for Phen and Anth were 16 and 50, respectively (Figure Id); whereas they were at least 65 for the other compounds. This poor response was due to the inefficiency of the contamination system, which did not generate air concentrations of Phen and Anth that were sufficiently higher than those measured in ambient air. In the following, we restrict the graphical presentation of the detailed results to PCB 52. The behavior of PCB 52 was typical for the substances studied. An example of the measured surface fugacity of PCB 52 on contaminated grass leaves is plotted against time in Figure 2. The asterisk represents the measured surface fugacity. The solid line is the curve fitted to the measured data according to eq 3 (see below).
0
1000
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750
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500 -
x 250
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-
o x
50
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250
x
100
time (h)
time (h)
’ QCB
* a-HCH
A 0
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x
x
% !
400 -
A
A
0 0
250
0
no
l1200 6O01
1
200
o yHCH
o HCB
1500 2ooo
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100
ZOO
150
250
I_
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250
time (h)
time (h)
* Phen
PCB23 o PCB52
A
Fla
o Anth 0
PYr
A PCB101
x
x
3000
2oooi x
0
x
1000 -
x 0
0
o 50
100
150
200
250
time (h)
’ CIA o TCN Flgure 1. (Panels a-e) Plot of the grass concentratlon at the end of an exposure period divided by the air concentratlon during that exposure (ccr/cA)vs the length of exposure for (a) QCB and HCB; (b) a-and -/-HCH; (c) PCB congeners 28, 52, and 101; (d) Phen, Anth, Fla, and Pyr; and (e) CIA and TCN.
The surface fugacity decreased until a constant value was reached. This behavior corresponds to that observed by Hortsmann and McLachlan (21)and is indicative of a nonequilibrium state within the grass leaf. As the decrease in fugacity was not related to the quantity of air sampled and the total amount of PCB 52 removed in the air accounted for a t most 5% of that present in the grass, this decrease cannot be due to depuration of the grass. It can, however, be explained by the transport of the compound
from the leaf surface into the interior of the leaf. The extrapolated end fugacity represents the equilibrium fugacity in the leaf. It increased with increasing duration of the contamination period, reflecting the increasing concentration in grass with increasing length of exposure in the contaminationchamber. The surfacefugacitycurves of the chlorobenzenes were flat following the last four expositions, a behavior that one would expect as the grass had already reached equilibrium. Envlron. Scl. Technol., Vol. 28, No. 1, 1994 161
is given by the product of its volume and its fugacity capacity 2. When there is a fugacity gradient between the compartments, a flux of chemical in the direction of the fugacity gradient results. The flux of chemical is the product of the fugacity difference c f -~ fs or fs - fR) and the conductance between the compartments. The mass balances of the two leaf compartments are described by eq 2a and 2b. In this paper we are primarily interested in interpreting plant concentrations, not in calculating mass flows. Hence, we have normalized the mass balance equations with respect to the leaf volume to simplify the discussion of the model development:
f (nPa) 1400 -
1200h I
1ooop 000 -:
P
600Ir
0
~
0
L_L p p
40
20
60
UszSX dfs = -dSR(fS - f R ) + dAS(f, - fs)
time (h)
(2a)
Figure 2. Plot of the measured and calculated fugacity of PCB 52 at the grass surface vs time followlng contamination for 24 h.
The fact that a significant fugacity gradient was established within the grass leaf during contamination indicates that the major resistance to contaminant uptake lies somewhere below the leafs surface. If the main resistance was at the leafs surface, the distribution of contaminant within the leaf would occur faster than the contaminant could be adsorbed from the air. In this case there would be a marked drop in fugacity between the air and the leaf surface, but no significant fugacity gradient would arise within the leaf. Isolating this leaf from the air and measuring the surface fugacity, one would expect a constant value well below the air fugacity level. When, however, the main resistance is below the surface, then the air and surface fugacities will be similar while the fugacity drop will occur between the surface and the leaf interior. If this leaf is isolated and the surface fugacity is monitored, the surface fugacity will drop with time as the contaminant on the surface continues to migrate through the region of resistance to the leaf interior. This latter scenario corresponds to the behavior observed in this study. The surface fugacity decrease and the accompanying equilibration in the leaf were rapid in all experiments. If, as discussed above, the major resistance lies below the leafs surface, then the governing resistances must be the same for both the uptake and the equilibration processes. However, the equilibration process is considerably more rapid than the uptake kinetics (comparing Figure IC and 2). Hence, the amount of a compound that has to flow in order to lower the fugacity at the surface must be much less than the amount necessary to increase the fugacity of the whole leaf by the same amount. This implies that the surface has a relatively low capacity for contaminant compared to the whole leaf. In summary, the results suggest that the grass leaf behaves as a two-compartment system. A large storage compartment in the interior of the leaf is covered by a surface compartment, which has a much smaller capacity for the compound. A mathematical model based on this interpretation was assembled and evaluated using the data. Model Development. The model of the grass leaf is based on the fugacity concept (17). It assumes that the leaf consists of two well-mixed compartments aligned in series with the atmosphere. Chemical transport occurs as diffusion between the atmosphere (A) and the surface compartment (S)and between the surface and the reservoir (R)compartments. The storage capacity of a compartment 162 Environ. Sci. Technol., Vol. 28, No. 1, 1994
where us, U R , ~ S Rand , AS are the compartment volumes and leaf conductances normalized with respect to fresh leaf volume. Equations 2a and 2b represent a system of inhomogeneous differential equations which can be solved. However, the solution is very complex and not particularly helpful in interpreting the experiment results. There are, however, two special cases of the solution that are more useful. Consider the case in which there is no net transfer between the atmosphere and the surface compartments of the leaf, i.e., the air and the surface compartment are in equilibrium. This is the situation at the exit of the sample chamber in the fugacity meter. In this case fA fs in eq 2a is zero, the differential equation system becomes homgeneous, and the solution is readily determined: fsct, = (fso - fEq) ~
x P ~ Q s R-I-~fEq I
(3)
where
and f~~ is the grass surface fugacity at equilibium. Equation 3 describes the decrease of the surface fugacity with time as measured using the fugacity meter. To obtain QSRand fEg, the measured course of the surface fugacity with time was fitted to eq 3 using nonlinear least-squares regression with QSR and fEq as the free parameters and fs as the fixed parameter. The choice of fs was complicated by inconsistent results in the first one or two fugacity values, a behavior that was attributed to fluctuations in the contamination chamber concentrations just prior to sampling. Thus, we set fs to the highest surface fugacity measured (the first value for the 2-, 5-, and 12-hexposures, the second for the 24- and 48-h exposures, and the third for the 120- and 240-h exposures) and discarded the preceding values. The line in Figure 2 is the regression curve. A good fit to the data was obtained in this and all other cases. The calculated mean values of QsR for PCB 52 are plotted in Figure 3 together with the 69% confidence intervals. QSR should be the same in all experiments if the leaf behaves as two well-mixed compartments. There is some indication that QSRdecreases with increasing duration of contamination. This would be expected if the reservoir compartment was not well-mixed. If this were the case, the fugacity adjacent to the interface between the two
I
I I
C
I -
Mean
1
69% CI
1
1.00
1
0.75
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-
0.25 -
'7
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0 L-0
150
200
100
50
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250
time (h) Flgure 3. Values of Q8R for PCB 52 including the 69% contldence Interval as determined following seven different contamination expealments.
time (h)
Figure 4. Plot of fEqlfAvs tlme for PCB 52. The asterisks represent the measured values; the solid line is the function obtained by nonlinear regression.
Table 1. Values for Kinetic Coefficients QSRand QASR~ QSR
mean (h-l) HCB CY-HCH ?-HCH PCB 28 PCB52 PCB 101 Phen Anth ClA TCN
6.23 1.12 7.47 x 8.85 X 4.36X 2.79 X 5.70 X 8.18 X 5.97 1.03
QASR
srel( % )
10-l
159 52 47 46 40
10-1
77
10-1
62 80 154 90
10-1 10-1
10-1
(h-l)
69% c.i. (%)
3.71 X 1.09 x 10-2 6.00 x 10-3 1.57 X 8.90X le 5.60 X 1.04 X 4.52 X le2 2.63 X 1.94X 1P2
8 7 15 4 9 14 31 45 34 27
[
400
t*
* *
*
200 1 100
(4)
where
QASR= ~ A S R / V G % (4a) Equation 4 describes the increase in the normalized equilibration fugacity in the leaf as a function of time during the contamination, assuming that f A is constant for a specific contamination experiment and fEq is zero at
* *
t
0' 0
compartments would be higher than the average fugacity in the reservoir compartment in the induced nonequilibrium state. The fugacity gradient across the interface would thus be reduced, slowing down the equilibration process. This in turn would be reflected in a lower QSR value. This effect would be relatively small as long as the fugacity gradient across the interface is large. It would become more important as the gradient decreases, i.e., as the length of contamination increases. The arithmetic means and the relative standard deviations of QSR are listed for all of the compounds in Table 1. The relative standard deviation is less than 100% for almost all compounds investigated, which indicates that the assumption of well-mixed compartments is reasonable. The second special case involves making the assumption that the capacity of the surface compartment VSZSis much smaller than the capacity of the reservoir compartment UGR. The initial interpretation of the experimental results indicated that this was the case. The solution is then given by eq 4, where dAsR represents the inverse of the sum of the resistances dAs-l and dsR-l, and VGZGis the sum of V ~ and R VSZS: = - expkQAsRt1
500
300 ;
For QSR, srd is the standard deviation of seven determinations while for QMR 69% cui.is the 69% confidence interval.
fEq(t)lfA
ZG ( m o l P a - 1 m-3)
I
I
50
100
150
200
250
time ( h ) Figure 5. Plot of
Z, for PCB 52 vs the duration of contarnination.
time 0. When fEq/fA is plotted against the duration of contamination for PCB 52 (Figure 41, the anticipated exponential curve is obtained. The data points on these curves were fitted to eq 4 using nonlinear regression (28) to obtain QASR. The solid line in Figure 4 shows the fit R are obtained for PCB 52. The values of Q ~ obtained given in Table 1along with the 69% confidence intervals. Model Parametrization. There are four unknowns in the two-compartment model described by eq 2a and 2b: us&, URZR,d A s , and ~ S R .Three of these parameters can be determined using the curve fits to the special cases of the analytical solution presented above, while the fourth, dAS, can be determined. To do this, we first calculate the total capacity and conductance of the leaf VGZGand d m R before dealing with the compartment values. VGZG.The total specific capacity of the grass leaf V&G is the sum of the capacities of the individual compartments (vsZs and VGR). VG is by definition 1, and ZG can be calculated using (5) Seven values of fEq were available for each compound from the extrapolated end points of the fugacity equilibration curves. The resulting ZGvalues for PCB 52 are plotted in Figure 5. There was no apparent relationship between the time of exposure and the total leaf fugacity capacity. Hence ZGwas defined as the arithmetic mean. The mean values and relative standard deviations srel of V&G are listed in Table 2. The Srel values were less than 35% for most compounds, indicating that the reproducibility of zG
cG/fEq
Envlron. Sci. Technol., Vol. 28, No. 1, 1994 163
Table 2. Estimates of Model Parameters d ~ s~,A S R ,~ S R ,VG&, and v&, Relative Size of VSZSwith Respect to VGZG dm
dAsR
the Relative Standard Deviation of
dSR
(mol Pa-' h-1 m-3)
(mol Pa-' h-1 m-9)
(mol Pa-1 m-3)
VSZS
(%)
(mol Pa-' m-9)
(u5%)/(vdG) x 100 (%)
79 76 76 74 69 66 82 82 78 76
1.03 1.26 1.36 3.82 2.91 3.95 1.92 4.23 17.1 8.07
1.04 1.29 1.39 4.07 3.06 4.25 1.97 4.50 23.2 9.24
11 28 116 226 243 327 704 185 94 650 416
17 25 21 25 16 22 45 33 34 60 35
0.17 1.15 1.85 4.69 7.03 15.2 3.48 5.53 3.90 8.94
0.61 0.99 0.82 1.89 2.15 2.16 1.88 5.88 0.60 2.15
this method of determining the fugacity capacity is very good. The total concentration in the grass leaf increases with the length of exposure. Thus, the seven measurements of ZG following different lengths of exposure represent determinations of the leaf capacity at seven different leaf concentrations. The absence of any trend in the values of ZG indicates that the leaf capacity is independent of concentration over the two orders of magnitude studied here. The partitioning isotherm is linear in the range studied. Thus, an extrapolation of the results to lower concentrations should be possible. dAsR. The overall conductance of the leaf dAsR was calculated from eq 4a using the values of U$G obtained above and the QASR values from Table 1. The results are given in Table 2. dAS and d s R . As was previously discussed, the fact that a fugacity gradient was established within the leaf indicates that the conductance between the surface and reservoir compartments ( d S R ) was much lower than the aidsurface conductance ( d A s ) . Thus, it can be assumed that d A R = dsR.
It would, however, be interesting to have estimates of d ~ to s complete the model. To do this, it is assumed that the limiting component of dAS is the air resistance. The definition of dAS is given by
AS = ~ A Z A ~ G
(6) The values of ZAand the area of the leaf per unit volume of grass UG are known. The mass transfer coefficient in the laminar boundary layer of the leaf k A can be estimated according to Nobel (24): kA
= D*A/1
(6a)
where D*Ais the diffusion coefficient in the air and 1 is the averagethickness of the undisturbed laminar boundary layer above the leaf. The former was calculated (251, and the latter was conservatively estimated to be 0.2 mm using an empirical relation given by Nobel (24). The resulting values of d A s are listed in Table 2. The conductance in the laminar boundary layer of the leaf, dAS, is larger than dAsR by ca. 1 order of magnitude. With dAsR and dAS being known, d S R could be calculated from the equation for conductances in series. The results are presented in Table 2. The two conductivities dAsR and d S R are almost equal for most of the compounds. Hence, the results reached using this numerical approach are in agreement with the conclusion deduced from the fugacity measurements. 164
and the
(mol Pa-' h-' m-9)
UOZG
QCB
HCB wHCH ./-HCH PCB 28 PCB 52 PCB 101 Phen Anth Cl.4 TCN
V&J,
Envlron. Sci. Technol., Vol. 28, No. 1, 1994
Srd
URZRand vszs. As was previously mentioned, the rapid equilibration of contaminant fugacity gradients within the leaf in comparison to the uptakelclearance kinetics is an indication that VRZR>> USZS.If we assume this to be the case, eq 3a can be simplified to = ~SRIVSZS (7) The values of QSRand d S R from Tables 1and 2 were used to calculate vsZs. The results are listed in Table 2. The size of the surface compartment VSZS relative to the total leaf capacity U&G (see Table 2) ranges between 0.6 and 2.2% WiththeexceptionofAnth (5.9%). Thus, thesurface compartment does not contribute significantly to the total capacity of the leaf, and the assumption made in eqs 4 and 7 was justified. Model Results. It is thought that the uptake of hydrophobic compounds by plant leaves is a partitioning process between the leaf material and the surrounding medium. Hence, it has been suggested by several authors that the plantlair partition coefficient of a hydrophobic compound should correlate with the quotient of its 1-octanol/water partition coefficient (Kow) and its di(18,20,26,27).This mensionless Henry'slaw constant (H) hypothesis was examined using the results obtained in this study. As all of the compounds under investigation are hydrophobic with values of log KOWranging from 3.8 to 6.4,it was assumed that the uptake of the compounds occurred exclusively in the lipid-like constituents of the leaf. The amount of lipid-like material was estimated by adding the 0.7% cutin reported to be a typical value by Riederer (18) to the 0.3 % extractable lipids measured in the grass leaves, resulting in a lipid volume fraction of 1% The total leaf fugacity capacity on a lipid base 21,is then 100 times larger than the capacity on a whole leaf basis ZG(see Table 2). In Figure 6, the plant/air partition coefficients on a lipid basis (ZL/ZA)are plotted against the quotients of Kow and H,the values of which are listed in Table 3. This quotient is labeled KOA,the 1-octanollair partition coefficient, in accordance with ref 35. A linear regression of log z L / z A against log KOAyields a slope of 0.91 and an intercept of 0.68 with a correlation coefficient of 0.901 (solid line in Figure 6). For the equation log & / Z A = log KOA(broken line), the correlation coefficient decreases to 0.892. A statistical difference between the slopes, as tested using the t-test, does not exist at the 99 % confidence level. Thus, a simple model, namely, that the lipid-like materials in Lolium multiflorum behave as if they were 1-octanol, does a good job predicting the air/plant partitioning for the compounds analyzed in this study. QSR
.
*x*
''Oil
* 2 leaf compartments D 1leaf
6.5
1 :./
0.50
!#
- log Z,/ZA=0.91.10g %,+0.68
rZ=0.90 r2=0.89
&A
,
,
I
,
,
7.0
7.5
8.0
8.5
@KOA
*,
0.00
0
6.5
6.0
6.0
log 'L/'A=log
cornpartmen!
1
2
3
time (h)
Flgure 7. Calculatedtime course of the leaf concentrationof PCB 52 after a 0.5-h expositionfollowed bya 2.5-hdepurationperiod NTIplOying the two- and the one-compartment models of the grass leaf.
'
Figure 6. Log-log plot of the plant llpid/air partition coefficient (ZL/ZA) vs the octanol/air partition coefficient (KoA).
Table 3. Physical Chemical Properties, Octanol/Air Partition Coefficients, and Plant Lipid/Air Partition Coefficients of Compounds Studied compd
log KOW
H (25 "C) (mol Pa-' m3)
log KOA (25 "C)
lOg(zL/zA) (18 "C)
QCB HCB CY-HCH Y-HCH PCB 28 PCB 52 PCB 101 Phen Anth C1A TCN
5.0" 5.5" 3.8' 3.8* 5.8d 6.1d 6.4d 4.6f 4.5f 5.38 6.2f
85.0a 139.0'' 0.7' 0.3c 31.6e 47.6d 35.5d 3.6f 1.g 2.0h 60.0h
6.45 6.74 7.35 7.65 7.63 7.82 8.25 7.41 7.76 8.2 7.82
6.44 6.83 7.45 7.74 7.77 7.90 8.23 7.65 7.36 8.39 8.00
From ref 29. From ref 30. From ref 31. d From ref 32. e From ref 33. f From ref 28. g Estimated accordingto ref 25 usingKow values of the carbon skeleton from ref 28. Estimated according t o ref 34 using H values for Anth and 2,3-dimethylnaphthalene from ref 28.
I t should be noted that the plantiair partition coefficients were measured at a lower temperature (18 "C)than the KOAvalues (25 "C). The KOAvalues are higher at 18 "C,which will result in a shift of the curve in Figure 6 to the right. This highlights the need for measurements of the temperature dependence of the leaf/air partitioning phenomenon. Good correlations with Kow have been reported for cuticle/water (36) and plant/water (37) partitioning. The experimental work dealing with plantiair partitioning is sparser. Reischl (38) reported a nonlinear relationship between KOAand plant/air partition coefficients measured for spruce needles. This contrasts with the near-linear relationship obtained by Bacci and co-workers from contamination experiments with azalea leaves (39). The results reported in this paper are further support for the hypothesis that plantiair partitioning is linearly related to KOA. Most mathematical models of the behavior of organic contaminants in plants assign the leaf a single lipophilic compartment (19, 20, 39, 40). The results of this study indicate that a two-compartment model would be more appropriate for Lolium multiflorum. Model calculations were performed to investigate the differences between the
predictions of the one- and the two-compartment models. The reaction of the leaf to a step increase and a step decrease in the gaseous concentration was simulated for PCB 52 using the model parameters in Table 2. The results are shown in Figure 7. There is a significant difference between the two models for short uptake periods. The two-compartment model predicts a faster uptake and depuration than the one-compartment model. The reason for this behavior is that the high conductance between air and the surface compartment allows the surface of the grass leaf to react readily to changes in atmospheric concentration. This is reflected in a 99.4% saturation of the surface compartment after a 30-min exposure. The differences between the models decrease with increasing length of exposure. The importance of the much smaller surface compartment diminishes as more compound diffuses into the reservoir compartment. The two models yield virtually identical results for exposure simulations lasting several days. Hence, a one-compartment model would be adequate for modeling tasks with time scales in the order of several days. However, a two-compartment model is necessary for problems with shorter time scales such as the buffering effect of vegetation on atmospheric contaminants following an accident or the effect of daily temperature fluctuations on aidplant distribution of organic substances. This study demonstrated that the fugacity meter is a valuable tool for investigating the exchange of semivolatile organic contaminants between the air and plant surfaces. By combining the measurement of the uptake kinetics in a contamination chamber with measurements in the fugacity meter, it was possible to parameterize a twocompartment model of the grass leaf. The fugacity meter allows a rapid and reliable determination of the total fugacity capacity of the leaf and also supplies information about different plant compartments that influence the transport kinetics. If employed in combination with a simple clearance experiment, it is no longer necessary to perform uptake experiments. This is an important advantage as uptake experiments are typically subject to large errors and difficult to conduct due to the necessity to maintain both a constant contaminant level in the gas phase and constant plant characteristics over long periods of time. The results of this study reinforce the hypothesis that vegetation plays an important role in the fate of lipophilic Environ. Sci. Technol., Vol. 28, No. 1, 1994 165
organic compounds in the environment, The combination of high storage capacity a n d high specific surface area with correspondingly rapid kinetics make plants effective sinks as well as sources of gaseous lipophilic contaminants.
Symbols concentration (mol m a ) conductance (mol Pa-' h-1 m3) normalized to fresh leaf volume diffusion coefficient (m2h-l) fugacity (Pa) equilibrium fugacity of the grass leaves (Pa) maw transfer coefficient (m h-1) partition coefficient thickness of the diffusive boundary layer (m) molecular mass (g mol-1) gas constant (8.314 J K-I mol-') kinetic coefficient (h-1) temperature (K) volume normalized to fresh leaf volume fugacity capacity (mol Pa-' m-3)
C
d
D* f fEq
k K 1 M R
8 T V
2
(16) Hutzinger, 0.;Reissinger, M.; Hauk, H.; Reischl, A.;
Schweitzer, S.; Umlauf, G. Schlussbericht BMFT Forschungsvorhaben 0743124-7, 1992. (17) Mackay, D. Environ. Sci. Technol. 1979, 13, 1218-1224. (18) Riederer, M. Environ. Sci. Technol. 1990, 24, 829-837. (19) Paterson, S.;Mackay, D.; Gladman, A. Chemosphere 1991, 23, 539-565. (20) Schramm, X.W.; Reischl, A.; Hutzinger, 0. Chemosphere 1987,16, 2653-2663. (21) Horstmann, M.; McLachlan, M. S. Environ. Sci. Technol. 1992,26, 1643-1649. (22) Prausnitz, J. M.; Lichtenthaler, R. N.; de Azevedo, E. G.
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Subscripts
A
air grass (both compartments) lipid-like leaf constituents reservoir compartment surface compartment initial value
G
L R S 0
1988,4, 191-216.
16, 2647-2652.
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166 Envlron. Scl. Technol., Vol. 28, No. 1, 1994
Received for review June 15, 1993. Revised manuscript received September 24, 1993. Accepted September 27,1993.' ~~
Abstract published in Advance ACS Abstracts, November 1, 1993.
