Environ. Sci. Technol. 1997, 31, 886-890
Influence of Temperature on the Plant/Air Partitioning of Semivolatile Organic Compounds PETER KO ¨ MP AND MICHAEL S. MCLACHLAN* Ecological Chemistry and Geochemistry, University of Bayreuth, 95440 Bayreuth, Germany
Dry gaseous deposition is the main pathway of many SOCs to vegetation. It can be understood as a partitioning process between the plant and the gas phase. In this paper, the temperature dependence of the partitioning of polychlorinated biphenyls between air and ryegrass (Lolium multiflorum) was investigated in the laboratory using a solidphase fugacity meter, and the results were incorporated into a mathematical model of plant uptake of SOCs. The measured plant/air partition coefficients were exponentially proportional to the reciprocal temperature, in agreement with theoretical expectations. The enthalpy of phase change (plant/air) was linearly proportional to the enthalpy of vaporization of the subcooled liquid, but the agreement between the two parameters was poor, the enthalpy of phase change (plant/air) being lower than the enthalpy of vaporization for the lower chlorinated PCBs and much higher for the higher chlorinated PCBs. The model simulations showed that under environmental conditions the temperature dependence of the partitioning coefficient does not influence the plant concentrations of most SOCs. The slow uptake/clearance kinetics prevent the plant/air system from reacting quickly to the new equilibrium state resulting from the temperature-induced change in the partition coefficient. Only for more volatile compounds such as trichlorobiphenyls or phenanthrene can the plant/air concentration ratio be expected to react to changes in temperature.
Introduction Dry gaseous deposition is the main pathway of many semivolatile organic compounds (SOCs) to aerial plant parts (1). This process plays an important role in the environmental fate of these compounds, affecting their scavenging from the atmosphere (2, 3), deposition to forest soils (4), and introduction into agricultural food chains and, thereby, human exposure (5). Dry gaseous deposition can be understood as the partitioning of a chemical between the gas phase and the plant, with these two phases striving toward an equilibrium described by a plant/air partition coefficient KPA. Preliminary laboratory measurements (6) suggest that temperature could have a large influence on this partition coefficient. A van’t Hoff-type equation, expressed here in its integrated form, provides a theoretical basis for expressing the temperature dependence.
[(
KPA(T) ) KPA(TR) exp
) ]
1 1 ∆HPA T TR R
(1)
where T is the ambient temperature (K), TR is a reference
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FIGURE 1. Schematic of the fugacity meter. temperature (K), R is the gas constant (mol-1 Pa m3 K-1), and ∆HPA is the enthalpy of phase change between the plant and the air (J mol-1). Evidence of a relationship of this kind has been reported from two field studies in which the concentrations of polycyclic aromatic hydrocarbons (PAHs) were measured in vegetation and air at different times during the growing season (7, 8). The authors obtained a semilogarithmic relationship between the quotient of the vegetation concentration divided by the gaseous air concentration and the reciprocal temperature. They attributed this to the influence of temperature on KPA. However, we are unaware of any controlled measurements of ∆HPA. In the absense of measured values, it was recently suggested that ∆HVAP, the enthalpy of vaporization for the subcooled liquid, could be substituted for ∆HPA, which is equivalent to assuming that the temperature dependence of KPA is identical to the temperature dependence of the vapor pressure of the subcooled liquid substance (9). In the work presented in this paper, the temperature dependence of KPA was investigated under controlled laboratory conditions using polychlorinated biphenyls (PCBs), with the goals of confirming the validity of eq 1 and obtaining measured values of ∆HPA. Ryegrass (Lolium multiflorum) was chosen for the measurements due to the comparatively large amount of information available about SOC partitioning in this plant species. The experimental results were subsequently incorporated into a mathematical model of dry gaseous deposition, which was employed to study the influence of the temperature dependence of KPA on the accumulation of SOCs in plants.
Experimental Section The solid-phase fugacity meter approach was used to investigate plant/air partition coefficients at different temperatures. The fugacity meter measures the concentration of a chemical in air in equilibrium with a solid surface. Since the equilibration of SOCs within the plant is much more rapid than the transport to the plant, equilibrium partitioning can be measured after only brief periods of contamination (10). This is a big advantage of the fugacity meter method over classical uptake experiments, in which the plants must be exposed to contaminated air for periods of months before a partitioning equilibrium is approached. The heart of the fugacity meter is a glass column in which the plant material is packed. An air stream is then passed through the column in such a way that an equilibrium between the surface of the vegetation and the air is established (see Figure 1). This air is then collected and analyzed for SOCs, as is the vegetation in the column. The quotient of the concentrations in the vegetation and the air gives the plant/air partition coefficient on the condition that a contaminant equilibrium between the surface of the vegetation and the interior of the vegetation
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1997 American Chemical Society
was present. The fugacity meter method is described in detail elsewhere (10, 11). Grass Contamination. In this experiment, the vegetation was contaminated with PCBs before the fugacity measurements to ensure that a wide range of compounds could be detected in the air after only relatively short periods in the fugacity meter. Ryegrass (L. multiflorum) cultures were placed in a contamination chamber containing high levels of gaseous PCBs (a unit mixture of Aroclors 1248, 1254, and 1260). Frequent air samples were taken with Florisil traps to monitor the performance of the contamination system. After 75 h of contamination, the grass leaves were cut and allowed to equilibrate for 50 h at room temperature in a sealed vessel before being packed into the sample chamber of the fugacity meter. This period of time has been found to be sufficient for the establishment of an interior equilibrium within ryegrass (10). At this point, a portion of the grass was removed and at least three samples were analyzed to obtain the grass concentrations for the calculation of the partition coefficients. Fugacity Meter. A modified version of the fugacity meter described in ref 10 was used. The sample chamber was increased in volume to increase the temperature range of the apparatus. Fugacity measurements were conducted at six temperatures between 5 and 50 °C. All measurements were performed at a relative humidity of 100%. The air concentrations were determined by collecting the PCBs at the outlet of the sample chamber on a Florisil trap spiked with internal standard (six 13C12-labeled PCB congeners). A minimum of three air samples were collected and analyzed at each temperature. Analytical Methodology. The Florisil traps were eluted with n-hexane/diethyl ether (4:1). Grass (3-5 g fresh weight) was spiked with a known amount of a 13C12-labeled internal standard solution and extracted in n-hexane/acetone (1:1). The grass extracts were dried using Na2SO4 and cleaned up on a Florisil and a C18 column. All samples were concentrated to 30 µL and analyzed using a Varian 3400 gas chromatograph fitted with a J&W Durabond-5 30 m column coupled to a mass spectrometer (Finnigan MAT 8230) operating in EI mode at 70 eV and a resolution of 2000. Two masses in the M+ isotope cluster were monitored for each analyte and each internal standard. The following temperature program was used: 60 °C for 3 min; 10 °C/min to 300 °C and hold for 3 min; 20 °C/min to 320 °C.
Results and Discussion Demonstration of Plant/Air Equilibrium. The presence of an equilibrium between the air leaving the sample chamber and the surface of the plant leaves was verified by varying the residence time of the air in the sample chamber. The absence of such an equilibrium is reflected in decreasing air concentrations with decreasing residence times. Before every experiment it was verified that the air concentration did not decrease when the air flow rate through the sample chamber was increased beyond the value used to measure KPA. A residence time of 70 s was found to be sufficient at high temperatures (T > 20 °C), while at lower temperatures (T e 20 °C) 30 s was adequate. Reproducibility of the Measurements. Three parallel grass samples were analyzed. The standard error of the measurements ranged from 0.9 to 32%, lying under 15% in 83% of the cases. Mass balance calculations indicated that the amount of chemical removed with the air stream during the fugacity measurements did not influence the grass concentrations. A minimum of three fugacity measurements were conducted at each temperature. The standard error for a given compound and temperature ranged from 0.3 to 45%, lying under 20% in 85% of the cases. In summary, the reproducibility of the measurements of KPA was very good.
FIGURE 2. ln KPA vs inverse temperature for PCB 52 in ryegrass. The diamonds give the measured mean values; the error bars give the standard deviation of the measured KPA values. Temperature Dependence of the Plant/Air Partition Coefficient (KPA). KPA was measured at six different temperatures between 5 and 50 °C. An exponential relationship was obtained between KPA (v/v) and the reciprocal temperature, as shown for PCB 52 in Figure 2. The correlations between ln KPA and 1/T were highly significant, with r2 ranging between 0.9606 and 0.9955 (see Table 1). This finding was in agreement with the theoretical expectations (see eq 1). The temperature dependence of KPA was very strong. The partition coefficient decreased by between a factor of 30 (for some dichlorobiphenyls) and as much as 2000 (for some octachlorobiphenyls) when the temperature increased from 5 to 50 °C. This indicates that vegetation/air equilibrium partition coefficients are highly variable under environmental conditions as a result of temperature fluctuations. Both the magnitude of the partition coefficient and the magnitude of the temperature dependence increased with increasing molecular weight of the PCBs. This is illustrated in Figure 3, where the regression lines calculated for the equation of the form log KPA ) A + B/T are plotted for a range of PCB congeners (the values of A and B are given in Table 1). The plot of log KPA vs 1/T gives a family of nonintersecting lines, with the slope increasing with the molecular weight of the PCBs. The enthalpy of phase change (plant/air) ∆HPA was calculated according to the equation
∆HPA ) 2.303RB
(2)
where R is the gas constant (mol-1 Pa m3 K-1), B is given in Table 1, and the factor of 2.303 arises from the transformation from common to natural logarithms. In Table 1, the values for ∆HPA are listed along with the enthalpies of vaporization for the subcooled liquid ∆HVAP calculated from ref 12. In Figure 4, ∆HPA is plotted against ∆HVAP. The correlation between the two enthalpies is highly significant, with r2 ) 0.9681. However, the slope of the linear regression is 2.6675, which is clearly different from 1 and shows that the enthalpies of vaporization and plant/air phase change are clearly different. For those PCBs with less than four chlorine atoms ∆HPA is somewhat lower than ∆HVAP, while for those with more than four chlorine atoms ∆HPA is considerably higher than ∆HVAP. This indicates that for the larger more lipophilic PCBs the interactions with the plant are considerably stronger than the interactions with the pure liquid. The approach mentioned in the Introduction of substituting ∆HVAP for ∆HPA in eq 1 can lead to very misleading results. Influence of Physical-Chemical Properties on KPA. It has been proposed in a number of modeling papers on plant/ air partitioning that plants can be viewed as a mixture of water, air, and octanol, with the uptake of hydrophobic compounds being attributed to partitioning into the octanol fraction of the plant (9, 13-15). Experimental evidence
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TABLE 1. Summary of Measurements of KPA as Function of Temperature PCB substitution pattern
IUPAC No.
Aa
Ba
r2
log KPA (25 °C)
log KOAb (25 °C)
∆HPA (kJ/mol)
∆HVAPc (kJ/mol)
(2,2′); (2,6) (2,4′); (2,3) (2,2′,5) (2,2′,3); (2,4′,6) (2,4′,5); (2,4,4′) (2,2′,5,5′) (2,3,3′,4) (2,3′,4′,6); (2,3,4′,6) (2,2′,3,5′,6) (2,2′,3,3′,6); (2,2′,3,4′,5); (2,2′,4,5,5′) (2,3,3′,4′,6) (2,2′,3,4′,5′,6) (2,2′,4,4′,5,5′) (2,3,3′,4,4′,6); (2,2′,3,4,4′,5′) (2,2′,3,4′,5,5′,6) (2,2′,3,4,4′,5,5′) (2,2′,3,3′,5,5′,6,6′) (2,2′,3,4,4′,5,5′,6); (2,2′,3,3′,4,4′,5,6′)
4 + 10 8+5 18 16 + 32 31 + 28 52 44 71 + 64 95 84 + 90 + 101 110 149 153 158 + 138 187 180 202 203 + 196
-4.768 -6.534 -7.119 -5.831 -8.844 -9.307 -8.542 -9.680 -9.843 -10.602 -11.834 -12.057 -13.135 -14.013 -13.020 -14.456 -11.557 -15.756
2833 3416 3688 3367 4302 4524 4372 4699 4795 5110 5597 5686 6095 6442 6123 6728 5685 7182
0.9759 0.9947 0.993 0.9863 0.9955 0.9922 0.9858 0.9856 0.9846 0.9832 0.9754 0.9646 0.9737 0.9727 0.9504 0.9661 0.9606 0.9607
4.73 4.92 5.25 5.46 5.58 5.86 6.12 6.08 6.24 6.54 6.94 7.01 7.31 7.59 7.52 8.11 7.51 8.33
6.56 6.98 7.12 7.18 7.61 7.73 7.78 7.89 8.04 8.23 8.58 8.68 9.09 9.15 9.25 9.72 9.28 9.91
54.2 65.4 70.6 64.5 82.4 86.6 83.7 90.0 91.8 97.8 107.2 108.9 116.7 123.3 117.2 128.8 108.8 137.5
69.7 72.2 75.4 75.4 77.9 80.8 81.0 81.0 84.2 85.8 86.6 89.8 91.4 92.1 94.0 96.5 92.9 100.4
a Coefficients of the equation log K b Calculated using the equation K PA ) A + B/T. OA ) KOWRT/H. The KOW values were taken from ref 22; the H (Henry’s law constant) values were from ref 23. c Calculated using the equation ∆HVAP ) mL × 2.303R. The mL values were taken from ref 12.
FIGURE 4. Enthalpy of phase change vs the enthalpy of vaporization of the subcooled liquid for a range of PCB congeners in ryegrass.
FIGURE 3. log KPA vs inverse temperature for a range of PCB congeners in ryegrass. The lines represent the regression curves of the measured data. supporting this model has been reported for azalea (15, 16) and ryegrass (9, 10). This hypothesis is expressed in eq 3, which describes a linear relationship between KPA and KOA measured for ryegrass (10).
KPA ) 0.01KOA
(3)
where 0.01 is a plant-specific constant that is in effect that fraction of the plant volume which behaves as 1-octanol (KPA is defined on a volume/volume basis). The relationship between these two parameters was examined for this data set by plotting the measured values of log KPA interpolated to 25 °C against log KOA (see Figure 5). An excellent correlation was found (r2 ) 0.99), providing further evidence that KOA is indeed a good predictor of KPA. In comparison with earlier measurements of KPA for ryegrass (10), it was possible to extend the validated range of the relationship between KPA and KOA by 2 orders of magnitude, from a log KOA of 8 to a log KOA of 10.
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FIGURE 5. log KPA vs log KOA for a range of PCB congeners in ryegrass. While an excellent correlation between KPA and KOA was obtained, the relationship between the two parameters is not linear. When the equation from Figure 5 is substituted into eq 1, the following equation is obtained.
KPA ) 0.0030KOA1.0928 exp
[(
) ]
∆HPA 1 1 T 298.15 R
(4)
The fact that the exponent on KOA is greater than 1 suggests
that ryegrass is a less polar storage medium for lipophilic organic compounds than 1-octanol (17, 18). However, there is considerable uncertainty associated with the calculated KOA values, and this precludes any fundamental conclusions as to the validity of the proposed linear relationship between KPA and KOA. It is believed that the measured values of KOA now beginning to emerge in the literature (19) and further measurements of KPA for different plant species should shed more light on the suitability of 1-octanol as a model for the SOC storage properties of plants. Impact of the Temperature Dependence of KPA on the Accumulation of SOCs in Plants. A mathematical model was developed to investigate the influence of the pronounced temperature dependence of the plant/air partition coefficient on the accumulation of SOCs by plants. The model developed in ref 9 for ryegrass served as the basis for this work. The governing equation describing plant uptake through dry gaseous deposition is
(
)
dcP cP ) kAPaAP cA dt KPA
FIGURE 6. Enthalpy of phase change vs log KOA for a range of PCB congeners in ryegrass
(5)
where cP is the volume-based plant concentration (mol m-3), cA is the gaseous air concentration (mol m-3), aAP is the specific surface area of the grass (m2 m-3), t is time (h), and kAP is the air/plant mass transfer coefficient referenced to the air phase (m h-1), which can be determined using
1 1 1 ) + kAP kAS kSPKPA
(6)
Here kAS is the air-side mass transfer coefficient describing transport from the free atmosphere to the plant surface and kSP is the plant-side mass transfer coefficient describing transport from the plant surface to the place of contaminant storage. To investigate the influence of the temperature dependence of KPA on the accumulation of SOCs in plants, consider the following scenario in which an equilibrium situation is perturbed by a change in temperature: At 25 °C ryegrass is in equilibrium with the SOCs in the atmosphere. The air concentration remains constant, but the temperature drops to 15 °C. How does the concentration in the ryegrass react to this perturbation? To answer this, eq 5 must be solved. Since cA is constant and the plant is initially in equilibrium with the air,
cA ) cP0/KPA0
(7)
where cP0 is the initial plant concentration and KPA0 is the plant/air partition coefficient at 25 °C. Substituting into eq 5 and integrating, the following equation for the ratio of the grass concentration to the initial concentration as a function of time is obtained.
(
) [
]
KPA KPA -kAPaAP cP ) + 1exp t cP0 KPA0 KPA0 KPA
(8)
As expected, cP/cP0 tends toward a value equal to the ratio of the new and old partition coefficients, approaching this new equilibrium state exponentially at a rate determined by the kinetics of transport to the plant. KPA0 (KPA at 25 °C) can be estimated using the equation in Figure 5. Hence KPA in the exponential term of eq 8 can be defined using
KPA ) 0.0030KOA1.0928(KPA/KPA0)
(9)
According to eq 1 the ratio of the partition coefficients is equal to
FIGURE 7. Model simulation of the change in ryegrass concentration with time following a temperature drop from 25 to 15 °C for a plant initially in equilibrium with the air, given that the air concentration remains constant.
[( ) ]
KPA 1 1 ∆HPA ) exp KPA0 T T0 R
(10)
In order to obtain a solution to eq 8 that is a function of just one chemical property, ∆HPA was plotted against the log octanol/air partition coefficient KOA (see Figure 6). A good linear relationship was observed (r2 ) 0.97). Substituting for T0 (298.15 K), T (288.15 K), and R, and defining ∆HPA according to the equation in Figure 6, eq 10 becomes
KPA/KPA0 ) exp(0.332 log KOA - 1.393)
(11)
Substituting eqs 9 and 11 into eq 8, one obtains a relationship for cP/cP0 that is a function of only time and KOA. Measured values of aAP (7200 m3/m2) and kSP (2.8 × 10-6 m h-1) for ryegrass were available from the literature (10). To calculate kAS, a gaseous deposition velocity to the plant canopy of 1 mm/s was used, somewhat higher than the 0.6 mm/s that has been reported for the deposition of SOC to pasture grass (5). This was divided by twice the leaf area index (set to 5), which yielded a value of 0.36 m h-1 for kAS. In Figure 7 cP/cP0 is plotted against log time for different values of KOA. It can be seen that the maximum value of cP/cP0 increases with increasing KOA, ranging from 1.8 at a log KOA of 6 to 3.5 at a log KOA of 8. This is due to the increase in the enthalpy of phase change with increasing KOA. The time required before a notable change in plant concentration occurs also increases with increasing KOA. Whereas the levels of a compound with a log KOA of 6 are predicted to increase by 50% within 55 h, a similar increase
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for a compound with a log KOA of 9 is expected only after 5000 h. This effect is due to the enormous storage capacity of the plant for compounds with high KOA values. For these chemicals there is so much substance in the plant compared to the air at the initial equilibrium state in the scenario that it takes the plant a very long time to “see” enough air (and hence airborne chemical) to be able to notably increase its concentration. The transport of chemical to the leaf surface is the factor limiting uptake. In reality, for compounds with high KOA values, this theoretical initial equilibrium state will likely never be approached since most leaves do not live long enough (9). Being far from equilibrium, temperature-induced changes in the partition coefficient will have no influence on the accumulation of the chemical in the plant. Returning to Figure 7, it is interesting to note that the time to respond to the change in partition coefficient decreases consistently from log KOA ) 10 to log KOA ) 8, but that the kinetics are very similar for log KOA values of 6 and 7. This effect is due to a change in the dominant resistance governing the uptake kinetics. Whereas the air-side resistance dominates at higher KOA values, the two resistances are approximately equal at a log KOA of 7, and at a value of 6, the plant side resistance dominates (see eq 6). For the latter case, the exponential term in eq 8 reduces to kSPaAPt. Therefore, as long as kSP remains independent of the physicalchemical properties of the compound, the plot for log KOA ) 6 represents an upper bound for the kinetic response of the plant. The essence of Figure 7 is that only for relatively volatile SOCs can plant concentrations be expected to respond to temperature-induced changes in KPA. For instance, only for compounds with a log KOA less than 8.1 (which corresponds to tetra- to pentachlorobiphenyl) will a decrease in the average temperature of 10 °C cause a 50% change in plant concentrations within one month. For chemicals with higher KOA values, the response times are so long that the process will be irrelevant for the environment in most situations. Although this conclusion is based on a model for one plant species (ryegrass) and one family of chemicals (PCBs), we believe it to be widely applicable to SOC accumulation in plants. The essential factor responsible for this behavior, the very high capacity of plants to store compounds with high KOA values, has been documented for a range of chemicals in several plant species (15, 20). The second important factor, the air-side resistance, is not expected to be very much lower for other plants, with the possible exception of free-standing plants exposed to very turbulent atmospheric conditions. A high value of kAS was purposely used in developing Figure 7 to reduce the likelihood of overestimating this resistance. The results of this study contradict ref 7, where it was reported that the seasonal trends in the quotients of the vegetation and gaseous air concentrations of PAHs were the result of changes in the levels in the vegetation caused by temperature-induced changes in the plant/air partition coefficients. Phenanthrene, the most volatile PAH in the study, has a log KOA of 7.41 (10), which lies within the range where this process might be expected to influence the plant concentrations. However, the five-ring PAHs studied have log KOA values in the order of 10-12 (21), a range for which an influence of temperature-induced changes in KPA on plant concentrations can be ruled out. The interpretation in the earlier work was based on the assumption that a partitioning equilibrium between the air and vegetation existed at all times. This assumption cannot be correct, as illustrated by the long equilibration times in Figure 7. The seasonal trends in the
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concentrations in vegetation which the authors attributed to the temperature-induced changes in KPA were likely due to a combination of effects such as growth dilution, decrease in dry matter content of leaves in late autumn, and erosion of SOCs from the surface of the vegetation (a process which was recently reported for polychlorinated dibenzo-p-dioxins and dibenzofurans on needles (4)). This combined with a source/ meteorology-driven summer minimum in gaseous PAH concentrations causes a seasonal trend in the quotient of the plant and gaseous concentrations. However, this is not related to a seasonal trend in plant/air partition coefficients. This example illustrates the difficulties in understanding the complex behavior of SOCs in the plant/air system.
Acknowledgments Financial support for this study was provided by the German Federal Ministry of Education, Science, Research and Technology.
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Received for review July 8, 1996. Revised manuscript received October 25, 1996. Accepted October 30, 1996.X ES960590U X
Abstract published in Advance ACS Abstracts, January 15, 1997.
