Environ. Sci. Technol. 1999, 33, 4126-4133
Leaves as an Indicator of Exposure to Airborne Volatile Organic Compounds MICHAEL H. HIATT* U.S. Environmental Protection Agency, National Exposure Research Laboratory, Environmental Sciences Division, P.O. Box 93478, Las Vegas, Nevada 89193-3478
The concentration of volatile organic compounds (VOCs) in leaves is primarily a product of airborne exposures and dependent upon bioconcentration factors and release rates. The bioconcentration factors for VOCs in grass are found to be related to their partitioning between octanol and air equivalent to a relationship previously determined for PCBs. The rate that leaves release VOCs is dependent upon meteorological conditions and the enthalpy of phase change between air and plant. The enthalpy of phase change (∆HPA) for a compound in leaves is closely related to its enthalpy of vaporization. The BCF and ∆HPA for a compound vary among plants but are highly correlated to each other. The change in BCF by plant (and correlated change in ∆HPA) is likely due to differences in the amount of octanol-equivalent matter contained in their leaves. The concentration of airborne VOCs is predicted to maximize near dawn simultaneous with natural inversion patterns. A model incorporating this phenomenon with other meteorological data, ∆HPA, and BCF is a useful tool predicting concentrations of VOCs in leaves. Vegetation can be especially useful in capturing VOCs at the critical time that air exposures are greatest. How long a leaf might retain a compound after uptake is dependent on the compound, the leaf type, and the magnitude of the wind and temperature. During calm weather, leaves can be used as a record of these early morning exposures. However, windy conditions quickly clear leaves of their VOC content.
Introduction The presence of volatile organic compounds (VOCs) throughout the environment is well-documented. The ubiquitous nature of VOCs is substantiated by the detection of VOCs in leaves from the Mt. Everest tree line (1), seawater throughout the globe (2), and both sediments (3) and air (4) from Antarctica. It has been suggested that semivolatile compounds, such as polychlorinated biphenyls and pesticides, are transported to colder regions by global distillation (5), although additional studies are necessary to prove this hypothesis (6). Studies of the migration of more volatile compounds would certainly shed light on the ultimate destination of airborne organic compounds. Concurrent with the airborne movement of organic compounds is their foliar uptake. The amount of chemical that can be present in leaves is related to a bioconcentration * Phone: (702)798-2381; fax: (702)798-2142; e-mail: hiatt.mike@ epa.gov. 4126 9 ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 33, NO. 22, 1999
factor (BCF), which for lipophilic organic compounds has been shown to correspond to their partition coefficients between air and octanol (7-9) and to vary by plant type (7) and temperature (7, 10). While a portion of the lipophilic compounds may reside interior to the plant cuticle (11), the leaf may be considered as having only octanol-equivalent, aqueous, and gaseous compartments (12). This simplified leaf model accumulates the lipophilic compounds in the cuticle independent of routes (12). It cannot be assumed that the concentration of a compound in leaves would always reflect an equilibrium with air although the more volatile a compound is the more likely it is to be in equilibrium (13). The uptake of lipophilic semivolatile compounds by vegetation has been established as primarily leaf surface adsorption at a rate limited by atmospheric resistance (13). The lack of influence by route (stomata or cuticular surfaces) on uptake of lipophilic compounds has also been shown for semivolatile compounds (11). As passive diffusion has been identified as the primary force in moving these compounds, it is reasonable to assume the trends found describing semivolatile uptake by plants would describe the behavior of lipophilic VOCs. While VOCs would certainly diffuse more rapidly than semivolatiles, the relative importance of diffusion through the different media would remain. The purpose for this study was to observe the content of VOCs in leaves and air and to identify how the concentration in leaves might be explained in relation to their concentration in air and if these findings were consistent with investigations involving less volatile compounds. After establishing how the content of VOCs in leaves reflects exposure to airborne VOCs, a secondary goal of this work was to assess the limitations of using leaves as a means to measure an exposure of vegetation to VOCs. Expanding on this work, the analyses of leaves from remote sites will gauge whether the content of VOCs in leaves can indicate a pristine condition or, potentially, a sink. The impact of meteorological conditions on BCF and rates of equilibration is critical to the interpretation of results from the analysis of vegetation (14). The monitoring of vegetation in a natural environment provides an opportunity to assess the impact of meteorological conditions with theory. The drawback to this uncontrolled approach is that multiple variables are impacting leaf-air dynamics simultaneously, and the isolation of a single variable for study (i.e., air concentrations, temperature, laminar air flow) was not possible. Therefore, all variables had to be addressed simultaneously.
Experimental Section Vacuum Distiller. Samples were analyzed using a vacuum distiller coupled with GC/MS. The vacuum distiller serves to remove analytes from a sample by volatilizing the analytes in a reduced pressure environment. A condenser column serves to condense most water that is also being volatilized at the reduced pressure. The material that passes through the condenser is cryogenically trapped in the vacuum distiller cryotrap. After the vacuum distillation is complete, the cryotrap is ballistically heated to volatilize the distillate while a helium carrier gas sweeps the trap transferring the analytes to the GC/MS via a transfer line. The direction of flow at the cryotrap is controlled by a 6-port valve. The vacuum distiller used in this study has been previously described in detail (7, 15). The principal components of the apparatus are a cryogenically cooled condenser (Associated Design & Manufacturing Company, Alexandria, VA), solenoid 10.1021/es990617k Not subject to U.S. copyright. Publ. 1999 Am. Chem.Soc. Published on Web 10/07/1999
valves (Peter Paul series 70 model 72 solenoid-action valves from Peter Paul Electronics Co., Inc., New Britain, CT), a 6-port Valco electronic actuated valve, and a cryofocusing trap (Specialty Fitting and Assembly, Cincinnati, OH). An Edwards vacuum pump (model 1) was used to supply vacuum to the distiller. Operation of the apparatus was controlled by a microprocessor (Bitstream Technologies, Inc., Las Vegas, NV). The temperature of the cryotrap 6-port valve was maintained at 150 °C (Valcon E rotor). All transfer lines were heated to 90 °C. The transfer line between the vacuum distiller and the GC was heated to 170 °C. A Pirani vacuum gauge (Edwards model 1000) was placed at the vacuum pump to monitor the integrity of the apparatus under vacuum. A nitrogen flushing of the condenser between distillations was by a line (5 psi nitrogen) connected at the top of the condenser column with a nitrogen vent at the bottom of the condenser. The sample chamber containing the spiked leaf sample (room temperature) was distilled under vacuum for 5 min. Water vapor was collected on the condenser column (5.0 ( 2.5 °C) while the fraction containing the analytes was collected in the cryoloop cooled with liquid nitrogen (-196 °C). The sample chamber valve closed at the completion of the vacuum distillation, and the cryoloop valve switched to allow the GC carrier gas to sweep the cryoloop and pass to the capillary column. The cryoloop temperature was ballistically heated to 120 °C to volatilize the distillate. The transfer of the distillate to the GC was complete after 3 min. The cryoloop valve was returned to its original position, and the cryoloop was heated to 200 °C for 7 min. After the sample was vacuum distilled, the condenser column was heated to 90 °C and flushed with nitrogen gas, while the nitrogen gas/condenser valve and vent valve were opened to remove most of the condensed material. After 3 min, the condenser-nitrogen gas line and vent valves were closed. The last step was an evacuation of the condenser for an additional 10-min period to remove any condensed water and contaminants that might remain after the nitrogen flushing. GC/MS Apparatus. A Hewlett-Packard mass spectrometer (model 5972) and gas chromatograph (HP5890 series II with model MJSC metal jet separator) with a 60 m × 0.53 mm i.d., 3.0-µm film thickness, VOCOL capillary column (Supelco, Bellefonte, PA) was used for the determination of analytes from the vacuum distillation apparatus. Gas chromatograph operating conditions were as follows: 3 min at 10 °C; 50 °C/min ramp to 40 °C; 5 °C/min ramp to 120 °C; 20 °C/min ramp to 220 °C; and isothermal at 220 °C for 3.4 min, resulting in a total run time of 28 min. The jet separator was held at 210 °C, and the transfer line was held at 280 °C. The injector was interfaced to the vacuum distillation apparatus by connecting the carrier inlet gas line to the cryoloop valve and then back to the injector. The injection or inlet temperature was 240 °C, and the inlet pressure was 10 psi. The mass spectrometer was operated in the selected ion mode (SIM) with 100 ms dwell on each ion being monitored (Table 1). The additional sensitivity gained by using SIM became necessary to consistently detect and measure the analytes. Leaf Analysis. Leaf samples of grass (mixed), mock orange (Pittosporum tobira), pine (Pinus eldavica), rosemary (Rosmarinus officinalis prostratus), and juniper (Juniperus sabina tamariscifolia) were analyzed. Before this study was completed, the juniper plants that were being monitored were removed during landscaping renovation, resulting in fewer plant species being investigated than initially planned. As in the previous study, leaf samples were collected at the University of NevadasLas Vegas campus. Leaves that were exposed to the wind and shaded during the sampling period were selected. Grass samples consisted of blades between 2 and 5 in. long and cut approximately 1 in. above
TABLE 1. Properties of Analytes and Surrogates Used for Quantitation retention relative timea quantitation secondary volatility (min) ion ion(s) (rKOA)b
Surrogates fluorobenzene 1,4-difluorobenzene toluene-d8 1,2-dibromoethane-d4 o-xylene-d10 bromobenzene-d5 1,2-dichlorobenzene 1,2,4-trichlorobenzene naphthalene-d8
9.91 10.06 13.02 15.44 17.81 20.05 22.65 24.75 25.03
benzene toluene tetrachloroethene ethylbenzene m,p-xylene 1,4-dichlorobenzene naphthalene
9.45 13.18 14.6 16.79 16.97 22.14 25.07
96 114 98 111 98 161 152 183 136
70 63 100 99 113 116 163 82 150 185 108
690 860 2 200 5 000 8 400 12 000 22 000 41 000 57 000
78 91 166 106 106 146 128
77 92 164 91 91 148 108
460 2 100 6 100 5 000 4 500 20 000 41 000
Analytes
a Retention times were determined using 60 m × 0.53 mm i.d., 3.0µm film thickness VOCOL column. Temperature program was 3 min at 10 °C, 50 °C/min ramp to 40 °C; 5 °C/min ramp to 120 °C; 20 °C/min to 220 °C and held at 220 °C to end of run. b Relative volatility values from ref 7.
TABLE 2. Physical Properties of Leaves leaf
dry wt (%)
density (g/cm3)
surface (cm2/g)
diameter (cm)
length (cm)
grass mock orange pine rosemary
22.7 34.7 48.9 21.7
0.82a 0.90c 0.90c 0.90c
173 66 61 64
NAb NA 0.81 0.143
2 2 NA NA
a Value from ref 9. b Data not required to determine laminar flow boundary. c Estimated values.
the ground. The outer leaves approximately 2 ft aboveground were collected from mock orange. Pine needles were taken at heights between 5 and 7 ft and removed from outer whorls. Samples of rosemary were taken from raised containers at a height of 3 ft. The rosemary samples consisted of leaves and stems. The individual leaves of rosemary were not separated from the stem. Rather, the outer portions of the plant where the stems had new growth and were still green (not woody) were selected. Measurements of the leaves physical properties that were used in calculations are presented in Table 2. Fresh leaves (10 g wet weight) and 1 mL of water were placed in the sample vessel. The presence of water helped suppress the recovery of alcohols that would decrease chromatographic resolution. There were no attempts to mince or mix the sample. The samples were then spiked with 10 µL of methanol, containing surrogate compounds, directly into sample vessels (a 100-mL round-bottom flask fitted with a 15-mm O-ring connector), which were used to contain the samples during both vacuum spike and vacuum distillation. Equilibration of the surrogate compounds and the tissue was accomplished using overnight vacuum spiking as previously described (16). Samples were analyzed by vacuum distillation/gas chromatography/mass spectrometry (VD/GC/MS) the following day. The concentrations of the analytes in the leaves were determined using the surrogate-based matrix correction technique (16). For this study, the recoveries of the analytes from the matrix during a vacuum distillation were compared with the surrogates as a function of relative volatility between VOL. 33, NO. 22, 1999 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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octanol and air (RKOA). With the analyte recovery prediction, their responses were corrected for matrix effects, and then the concentration was determined. Three groups of surrogates were used. The first group of surrogates was used to determine the matrix effects for analytes with RKOA values below 5000. The surrogates in the first group were fluorobenzene, 1,4-fluorobenzene, toluened8, and 1,2-dibromoethane-d4. The second group of surrogates was used to predict recoveries for those analytes with RKOA values between 5000 and 22 000. The second group’s surrogates were 1,2-dibromoethane-d4, bromobenzene-d5, and 1,2-dichlorobenzene-d4. The third group of surrogates was used to predict the recovery of analytes with RKOA greater than 22 000. This group of surrogates was 1,2-dichlorobenzene-d4, 1,2,4-trichlorobenzene-d3, and naphthalene-d8. The list of RKOA values is presented in Table 1. The concentrations of volatile organic compounds were determined relative to the dry-weight of the leaves. The dry weight for leaves was determined as the weight after heating at 115 °C overnight. The samples were dried in the sample vessel after their vacuum distillation. The sample dry weight was used in the determination of the BCF. Air Analysis. Air samples were collected using a 1-L Erlenmeyer flask modified with an O-ring connector (15 mm). The Erlenmeyer flask was sealed using a cap made from a stainless steel O-ring connector (15 mm) attached to a stainless steel toggle valve with Swagelock fittings (Nupro 4BKT). Before sample collection, the flask and valve/cap were attached (1/4 in. Swagelock fittings) to a port on the vacuum distillation apparatus and evacuated. An air grab sample was then collected in the flask (disconnecting the O-ring connection), 5 µL of surrogate solution was added, and then the valve/O-ring cap was connected. The flask assembly was then reattached to the vacuum distiller for analyses. The air sample was evacuated from the flask (open cap-toggle valve), passed through the vacuum distiller condenser, and focused in the system cryotrap (-196 °C). The condenser was held at 90 °C during the sample transfer. After 5 min of collecting the analytes in the cryotrap, the valving was switched to desorb mode, and the cryotrap was heated to 100 °C, transferring the focused material to the GC/MS. The determination of analytes in the air samples was performed using external standard quantitation. Results were not corrected to STP. The concentrations of VOCs varied among the different days. Benzene, tetrachloroethene, ethylbenzene, 1,4-dichlorobenzene, and naphthalene concentrations ranged from less than 0.1 to 10 ng/L. Toluene varied between 1 and 113 ng/L, and the sum of m- and p-xylenes varied between 0.3 and 19 ng/L. Sample Collection. Samples were collected on 11 different days during the period of January-August 1998. Leaf and air samples were collected at roughly 1-h intervals from 7:00 a.m. to 11:00 a.m. At each hour, a sample of air and leaves was collected. In this study, the collection of samples on a given day is referred to as a sampling event, and the time between successive samples is referred to as an interval. During a sampling event, only two plant species were sampled as they were within several feet of each other, and the sampling of leaves and air could be completed within 10 min. Mock orange was directly adjacent to grass at one sampling location, and pine was adjacent to rosemary at the other sampling location. There were six sampling events undertaken to investigate pine and rosemary leaves and five sampling events investigating grass and mock orange leaves. Meteorologic data used in this study were collected from the Los Alamos National Laboratory NEWNET station located at University of Nevada at Las Vegas. The data can be accessed on the Internet at (htpp://newnet.jdola.lanl.gov/datasframe.asp?number)0214). Every 15 min, meteorological readings of temperature, average wind speed, and wind 4128
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direction were recorded by the station less than 100 yd from both sampling locations. The 7:00-11:00 a.m. sampling period was selected, as it was the most likely to provide the greatest changes in air concentrations. It was typical for concentrations of VOCs in air to maximize and then drop quickly during this period. This pattern is standard for the Las Vegas Valley as early morning air inversions are quickly dispersed as the morning temperature increases. The greater the change in VOC concentrations in air, the greater the potential to observe an impact on leaf concentrations. Initial sampling events (one for the grass and mock orange sampling and one for the pine and rosemary sampling) were designed to determine BCF. For those sampling events, one sample of air and leaves were taken at 5:30 a.m. prior to the time before the concentration of VOCs would be at a maximum (approximately 7:30 a.m.). This sampling pattern was used to detect if the concentration of VOCs in leaves reflected current air concentrations or a prior exposure. If the concentration of VOCs in air was maximum and the concentration of VOCs in leaves increased from the 5:30 leaf sample, then the BCF could be determined. If the leaf concentration did not increase, it would be established that the concentrations of VOCs in leaves were greater than equilibrium (the leaves would be releasing VOCs), and a determination of BCF would be biased by a previous exposure. For both of the initial sampling events, the samples did increase, and BCF values were determined. The remaining sampling events were designed to collect samples during the periods when the leaves would be releasing VOCs. During the sample events, there were typically five sample sets (leaves and air samples) collected. These sample collections resulted with 23 intervals that could be used to evaluate concentrations of VOCs in air and pinerosemary leaves. There were 19 intervals for the evaluation of VOCs in air and grass-mock orange leaves. The determination of release rates over an interval was not always useful, and criteria had to be established. The first criterion that was used was that the concentration of the VOC in air had to drop 25% or more over the interval. This requirement was intended to minimize the impact of bias from analytical variability (less than 10%) or an exposure spike from a minor random source. This criterion was the most restrictive and resulted in the rejection of 54% of all the intervals (for all plants and all compounds). Another criterion was that the wind direction did not vary more than 90° during the interval. This limitation was a means to eliminate using intervals when the change in air concentration of VOCs could not be considered as uniform during the interval. This criterion eliminated the use of 11% of the intervals. It was also necessary that the VOC concentration in leaves had to show a decline over the interval. If the concentration in leaves increased while the concentration in air decreased, a determination of release rates would not be reliable. Two possible conditions would result in these observations and would result in erroneous calculations of release rates. One was that while the concentration in air would drop, it would still be so elevated (while the concentration in leaves less than its equilibrium concentration) that the leaves continued to uptake the VOC. The second possibility was that the concentration of a VOC in air increased as a spike (intermittent source) after the start of an interval and had subsided by the end of the interval. This criterion was not met for 11% of the intervals. The final precondition that was used was an instrumental sensitivity criterion. This requirement was that the analyte had to have a response (GC/MS) greater than 3 times background. This criterion eliminated few data (6%), with most rejections (80%) due to a low concentration of benzene in leaves.
where BCF is expressed as ng/kg leaf dry weight to ng/L air. As it was not feasible to collect air samples more frequent than an hourly basis, it was necessary to assume that the
BCF determined in this study. e One d
2.9(6) 2.0(5) 1.8(3) 3.2(6) 2.4(8) 1.8(2) 2.5(7) 35.3 38.1 37.3 37.3 37.3 35.3 36.0 206 3056 1648 2158 2052 7441 15875 NA 14000 6000 5400 8100 11000 7000 10000 70000 NA 66000 34000 2.6(6) 1.5(5) 0.5(3) 1.2(5) 0.9(4) 1.8(4) 1.1(2) 35.4 34.1 35.6 37.9 39.0 38.8 37.5 98 574 485 2093 1978 5995 17446 NA 2300 1800 440 80 1800 1300 1300 1100 6200 NA 13000 10000 0.3(3) 0.6(4) (1) 1.8(4) 3.8(5) 1.9(5) 1.2(5) 31.0 29.9 36.0 31.1 33.2 32.8 34.9 150 315 382 954 1089 2856 14472 NA 590 230 350 320 1600 900 2200 1500 5200 3100 39000 22000 0.5(3) 1.5(7) 6.6(2) 2.0(6) 0.5(3) 0.2(3) 1.0(6) 32.7 32.7 31.9 33.6 32.1 29.4 32.9
dev avg dev avg II dev avg deve avg IId dev avg
136 244 190 235 299 2731 6792
dev II
avg
dev
avg
I ∆HPA (kJ/mol) I ∆HPA (kJ/mol) I ∆HPA (kJ/mol) Ic
NAf 200 70 220 190 350 240 420 200 2700 300 5800 600
dev avg II
rosemary BCF pine BCF mock orange
BCF
grass BCFa
a Bioconcentration factor for analyte (ng/kg leaf dry weight to ng/L air) for 20 °C. b Enthalpy of vaporization at the compound boiling point from ref 21. c BCF reported in ref 7. sigma deviation. The number of replicates to determine ∆HPA are in parentheses. Value is blank for results based on one determination. f NA, not determined.
(2)
30.7 33.2 34.7 35.6 35.7 38.8 38.1
k1/k2 ) BCF
benzene toluene tetrachloroethene ethylbenzene m,p-xylenes 1,4-dichlorobenzene naphthalene
where cl is the concentration of a VOC in leaves as ng/kg dry weight, k1 is the uptake rate in h-1, k2 is the release rate in h-1, and ca is the concentration in air as ng/L(18). The release of VOCs from leaves is at a much slower rate than their uptake, with the ratio of uptake-to-release rates expressed as
compound
(1)
Hvbb (kJ/mol)
dcl /dt ) k1ca - k2cl
TABLE 3. Bioconcentration Factors and Enthalpy of Phase Change for VOCs in Leaves
Bioconcentration Factors. In a previous study, the BCFs for the VOCs used in this study were determined. That study took both air and leaf samples early in the morning at the time when the concentration of VOCs in air was predicted to be the greatest. Noted in that publication was a potential high bias in the determination of BCF values as the study did not ensure that the concentration of a compound in the leaves was not biased from a previous exposure. For this study, BCF values (concentration of VOC on a dry-weight basis as compared to concentration in air) were determined from sampling events where leaves were shown to not reflect a concentration of VOC from an exposure prior to the sampling event. The BCF values were then determined using the samples collected when the air concentration was maximized. The BCF values were standardized to 20 °C by factoring the impact of compound vapor pressure changes (8), and their values are presented in Table 3. While it is useful to report BCF in terms of dry weight of leaves, it is noted that in a later discussion the BCF is converted to a volume of leaves basis for the determination of the enthalpy of phase change between plant and air. The BCF values determined in this study compare closely to previous work (8) for the leaves with the exception of rosemary. It appears that the earlier rosemary BCFs were biased high, potentially by a residual content of VOCs from previous days’ exposures. The BCF values for grass determined by this study as well as those that had been determined for PCBs in grass (10) are presented in Table 4. The VOC data are seen to follow the same trend established using just the PCB data (Figure 1). The correlation of BCF to KOA for PCBs in grass had been shown to be log BCF ) 1.0928 log KOA - 2.5258 with r 2 ) 0.9906. The additional VOC data indicate that the range of compounds that can be described by a linear relationship of BCF to KOA can be expanded. The resultant relationship of BCF to KOA is changed little with log BCF ) 0.9728 log KOA - 1.517 (r 2 ) 0.9909). This revised relationship should be a useful guide to predict the BCF for a wide range of organic compounds that would be expected to be transported via air. The higher BCF value for some VOCs in pine and rosemary is likely due to the presence of organic matter (i.e., oils, lipids, and waxes) in their leaves that can dissolve greater amounts of VOCs as compared to grass. Grass has a reported 1% lipid content (cutin being 0.7%) by leaf volume (9), whereas conifer needles have been reported to have just essential oils up to 1% dry weight or 0.44 vol % (17). In contrast, for the least volatile VOCs, the BCF appears to vary less among the plants studied. These data suggest (with some risk) that for a lipophilic compound that is semivolatile, such as the PCBs and pesticides, its BCF will tend to be less a variable among different plant types. Release Rates. The change in concentration of a compound in leaves in response to its concentration can be expressed as
∆HPA (kJ/mol)
Results and Discussion
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TABLE 4. Physical Properties for Volatile and Semivolatile Compounds and Their Enthalpy of Phase Change between Air and Grass BCFa
KOAb
∆Hvapc
∆HPAd
compound
log (25 °C)
log (25 °C)
(kJ/mol)
(kJ/mol)
benzene tetrachloroethene toluene m,p-xylene ethylbenzene 1,4-dichlorobenzene naphthalene PCB 4 + 10e PCB 8 + 5 PCB 18 PCB 16 + 32 PCB 31 + 28 PCB 52 PCB 44 PCB 71 + 64 PCB 95 PCB 84 + 90 + 101 PCB 110 PCB 149 PCB 153 PCB 158 + 138 PCB 187 PCB 180 PCB 202 PCB 203 + 196
2.04 2.17 2.28 2.36 2.25 3.29 3.63 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
2.59 2.61 3.17 3.65 3.59 4.03 4.21 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
39.7 38.0 33.8 42.2 49.0 42.5 54.2 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
32.7 31.9 32.7 32.1 33.6 29.4 32.9 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
a Bioconcentration factor for analyte (µg/kg leaf dry weight to µg/L air). The first seven compound values are from this study, and the remainder are from ref 10. b The first seven octanol air partition coefficients are from ref 15. The remainder are from ref 10. c The first seven heat of vaporization values are from ref 21. The remainder are from ref 10. d The first seven enthalpy of phase change between air and grass were from this study, and the remainder are from ref 10. e IUPAC number.
change in a VOC concentration in air over an interval t (approximately 1 h) was gradual. A simplification that made integration of eq 1 more palatable was the BCF over an interval was considered to be a constant and equal to the BCF for the temperature at the beginning of the interval. Integrating eq 1 over time t and substituting Bk2 for k1 yields
cl t ) cl o e-k2t + BCF(rk2-1 e-k2t - cao e-k2t + rt -1
rk2
+ cao) (3)
where cl t is equal to the concentration (ng/kg dry weight) of a compound in the leaf at the end of the interval t, cl o is equal to the concentration at the start, cao is the concentration in air at the start of the interval in ng/L, and r is the rate the concentration in air changes over the time interval (cat ) rt + cao). The analyses of air and leaf samples at the start and end of interval, t, provide the empirical data necessary to determine the uptake and release rates. It was found that, when the VOC concentrations in air and leaves were near equilibrium, the determined rates were unreliable or the equation was not solvable. Therefore, rates were only determined when the concentration of VOCs in leaves was not near equilibration with air (greater than 5% difference). As these sample collections were done on different days over an 8-month period, the determined rates reflected significantly different meteorological conditions. The release rates required an elaboration to incorporate these meteorological variables in order to compare results. In this work, the release of VOCs by leaves is related to the enthalpy (∆HPA) of phase change between the plant and air (10). The Arrhenius equation 4130
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k2 ) Ae-∆HPA/RT
(4)
was used to describe this dependence of the rate of release on this energy and the influence of temperature. This equation also provides a simple approach for addressing the other variables affecting release rates (with ∆HPA in kJ mol-1, the gas constant R in units of kJ mol-1 K-1, temperature T in Kelvin, and the frequency term A in units of h-1). Because A is a geometric term describing diffusion of compounds through a boundary of air surrounding a volume of leaf, eq 4 is in terms of leaf volume. Therefore, the determination of k2 by eq 3 must be in terms of volume (BCFv is ng/L leaves per ng/L air, and concentrations of VOCs in leaves are in ng/L leaves). The frequency term was equated to be the ability of a chemical to pass through the laminar flow boundary to the surface of the leaves, corresponding to the mass transfer coefficient times leaf surface area (MTC S) in ref 12. This term was determined by
A ) [Da/(Lc)]S
(5)
where Da is the diffusion coefficient for a chemical in air in cm2/h at temperature T, Lc is the thickness (in cm) of the laminar flow boundary at the leaf’s surface, and S is the leaf surface per unit volume (cm-1). The diffusion coefficients for the VOCs at the temperature of sampling were calculated using the Fuller, Schettler, and Giddings estimation method (19). Wind speed and the geometric shape of a leaf govern the thickness of the laminar flow boundary. The laminar boundary thickness (in mm) surrounding flat leaves (mock orange and grass) is described by
L ) 4.0(l/v)1/2
(6)
where l is the mean length in the downwind direction in m, v is the wind speed in m/s, and the factor 4.0 has units of mm s1/2 (20). The laminar boundary thickness (mm) surrounding cylindrical leaves (pine and rosemary) is described using
L ) 5.8(d/v)1/2
(7)
where d is the leaf diameter in m, v is the wind speed in m/s, and the 5.8 factor has units of mm s1/2 (20). Table 2 lists the values for physical properties of leaves necessary to solve eqs 6 and 7. With the measurement of wind speed and temperature from the NewNet station, A can be calculated. With values for k2 (calculated from eq 3) and A, the ∆HPA can be determined by eq 3. Their results are presented in Table 3. One generalization would be that the ∆HPA for all the VOCs in this study is approximately equal to the heat of vaporization at the boiling point (∆HPA ) f Hvb where f ) 0.92 ( 0.10, 0.93 ( 0.07, 1.05 ( 0.06, and 1.04 ( 0.09, respectively, for grass, mock orange, pine, and rosemary). It was also found that the ∆HPA for a compound varies among the plants as does the BCF. The correlation of ∆HPA to BCF was 0.002, 0.79, 0.53, 0.63, 0.88, 0.57, and 0.90 for benzene, toluene, tetrachloroethene, ethylbenzene, m,p-xylenes, 1,4-dichlorobenzene, and naphthalene, respectively. It is reasonable to expect that the ∆HPA correlates to the content of an octanolequivalent matter as does the BCF. The fact that benzene does not fit this pattern is most likely due to the difficulty of measuring the compound in leaves and distinguishing its response from background. The averages of the ∆HPA results for VOCs in grass are presented in Table 4. Included in Table 4 are ∆HPA values determined for PCBs in grass (10). A linear relationship of ∆HPA to Hvap that was determined for PCBs is no longer linear
FIGURE 1. Log BCF at 25 °C vs log KOA at 25 °C for lipophilic compounds in grass.
FIGURE 2. ∆HPA vs ∆Hvap for lipophilic compounds in grass. when the VOC data are included (Figure 2). Such an inconsistency had been considered likely with a suggestion that the more lipophilic a compound is, the interaction with grass is greater than its interaction with the pure liquid (10). While a trend is not readily observable with just the VOC ∆HPA to Hvap data Figure 2 indicates a nonlinear relationship. The equation ∆HPA ) 30.7 + 138.02/(1+(Hvap/85.74)-7.065) is accurate over the range of analytes with r 2 ) 0.99. Leaves as Passive Samplers. The concentration of VOCs in leaves reflects their concentration in air, BCF and ∆HPA values, leaf geometry, and meteorological conditions. All these factors must be considered when evaluating the concentration of a VOC in leaves in terms of an airborne exposure. The changes in meteorological conditions over a day influence the concentrations of VOCs in leaves throughout the day. Therefore, how the meteorological conditions change is a critical factor that must also be considered. The following discussion focuses on how well leaves would be expected to retain VOCs uptaken during an early morning exposure.
In order that the impact of the these factors can be discussed a pattern for how VOC concentrations in air and meteorological parameters change is defined. That is at 7:00 a.m. the concentration of VOCs in air are maximum and the temperature is at a minimum, and at noon the concentration of VOCs in air would be at a minimum and the temperature at its maximum. The changes between maxima and minima are at an even rate. The wind speed is taken to be a constant throughout the day. An additional pattern is considered to represent an extreme where there is a significant change in wind direction that introduces air flow with negligible VOC content. This condition is simulated by making the concentration of VOCs in air negligible 1 h after their maximum at 7:00 a.m. With these patterns, eq 3 can be used to incrementally determine the concentration of VOCs in leaves. The influence of temperature on how well leaves retain VOCs is evaluated using two temperature ranges. One temperature range represents a cold day (0-10 °C) and one represents a warm day (20-30 °C). Three wind speeds (0.5, VOL. 33, NO. 22, 1999 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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FIGURE 3. Effects of wind velocity on the concentration of toluene in pine needles respective to its concentration at 7:00 a.m. when the content of toluene in air is greatest. The temperature increases from 0 to 10 °C over the 5-h period. Air(I) is a trend where the toluene content in air steadily decreases from a maximum at 7:00 a.m. to 1/10 maximum at noon. Air(II) is a condition where after the 7:00 a.m. maximum the content of toluene in air is negligible at 8:00 a.m.
TABLE 5. Predicted Relative Concentrations of VOCs in Pine and Grass 3 h after Maximum Air Concentrations under Varying Conditions T (°C)
leaf pine
0-10 0-10 0-10 20-30 20-30 20-30 grass 0-10 0-10 0-10 20-30 20-30 20-30
wind (m s-1) 0.5 1.0 5.0 0.5 1.0 5.0 0.5 1.0 5.0 0.5 1.0 5.0
benzene Ia IIb 0.78 0.74 0.73 0.75 0.76 0.78 0.73 0.73 0.75 0.77 0.78 0.79
0.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
toluene I II 1.13 1.09 0.95 0.96 0.89 0.77 1.05 0.99 0.83 0.86 0.80 0.74
0.59 0.48 0.19 0.20 0.10 0.01 0.39 0.27 0.05 0.06 0.02 0.00
tetrachloroethene I II 1.14 1.14 1.04 1.04 0.98 0.82 1.01 0.94 0.79 0.82 0.77 0.74
0.72 0.63 0.36 0.35 0.23 0.04 0.30 0.18 0.02 0.03 0.01 0.00
ethylbenzene I II
m,p-xylene I II
1.11 1.13 1.14 1.13 1.09 0.96 1.02 0.95 0.80 0.82 0.77 0.73
1.06 1.08 1.13 1.13 1.14 1.08 0.94 0.87 0.74 0.77 0.74 0.73
0.86 0.81 0.62 0.60 0.49 0.20 0.33 0.21 0.03 0.04 0.01 0.00
0.93 0.90 0.80 0.78 0.70 0.45 0.18 0.09 0.00 0.01 0.00 0.00
1,4-dichlorobenzene I II 1.11 1.13 1.14 1.14 1.10 0.96 0.77 0.72 0.69 0.71 0.71 0.73
0.87 0.82 0.65 0.63 0.52 0.23 0.03 0.01 0.00 0.00 0.00 0.00
naphthalene I II 1.14 1.16 1.12 1.11 1.06 0.89 1.09 1.02 0.83 0.87 0.79 0.68
0.83 0.77 0.55 0.54 0.42 0.14 0.48 0.36 0.10 0.12 0.05 0.00
a Concentration of analyte in air maximizes at 7:00 a.m. and gradually minimizes to 1/10 of maximum concentration at noon. The resultant value is the fraction of analyte that remains at 10:00 a.m. b Concentration of analyte in air maximizes at 7:00 a.m. and immediately becomes negligible. The resultant value is the fraction of analyte that remains at 10:00 a.m.
1.0, and 5.0 m s-1) are considered. The minimum concentration of VOC in air is taken to be 1/10th its maximum. Starting with negligible concentrations of VOCs in leaves on day 1, eq 3 is used to predict the concentrations over 7 days. Seven days were characterized to avoid an influence by an arbitrary starting concentration of VOCs in leaves for day 1. The concentrations of VOCs in leaves for day 7 are those being evaluated. The effects of wind speed and the two patterns of VOC concentrations in air are presented in Figure 3. This figure illustrates how the concentration of toluene in pine needles varies on a cold day for the different wind speeds and the two air concentration patterns. This figure shows that while wind speed can have a significant effect, a “clean” wind (possibly from a different direction) can clear the leaves of toluene quite rapidly. One characteristic observed in Figure 3 is that the relative concentration of toluene in pine needles still increases while the concentration of toluene air is dropping. This increase 4132
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is because with the gradual changing air concentration pattern, the content of toluene in air gradually increases from the previous days low (noon) until 7:00 a.m. and the content of toluene in the pine needles does not reach equilibration with the air at 7:00 a.m. In fact the lag is such that for the 0.5 m/s wind speed (and therefore slower uptake rates) the content of toluene in pine needles continues to increase until 9:00 a.m. It is apparent from Figure 3 that if leaves are expected to retain VOCs over a morning, a calm day (low wind speed and steady direction) is preferred. Likewise, the concentration of VOCs in leaves on a windy day would be very time dependent and less reliable. An interpretation of this figure would be that the concentration of toluene in pine would not be expected to vary from its 7:00 a.m. concentration by more that 10% on a cold day when the winds are less than 1 m s-1. The 10:00 a.m. concentrations of the VOCs in grass and pine are presented in Table 5 as relative to their concentrations at 7:00 a.m. From this table, it can be seen that the VOC
content in leaves can be representative of airborne content during a predictable morning inversion. If the concentration of VOCs in air change gradually during a morning (a reasonable assumption if wind is not gusting and changing directions), the loss of VOC over 3 h would be expected to be less than 50% on even a warm windy day. Under calm conditions, the concentration of VOCs in leaves hours after a peak exposure can be useful in measuring that peak exposure. The data in Table 5 also indicate that, if there is a rapid change in air concentration, the VOCs could be quickly cleared, especially for grass. The use of leaves to measure airborne exposure requires the knowledge of meteorological conditions. While leaves can provide a useful record of an early morning exposure, they can be quickly cleared of VOCs by gusting conditions. The use of leaves to measure exposure to a morning high requires morning sampling. How well the samples represent a peak exposure is dependent on plant type, compound, temperature, and wind conditions. It would be unlikely that meteorological conditions would justify using leaves to measure exposures after early morning.
Acknowledgments The U.S. Environmental Protection Agency (EPA), through its Office of Research and Development (ORD), funded and performed the research described. This manuscript has been subjected to the EPA’s review and has been approved for publication. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.
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Received for review May 28, 1999. Revised manuscript received September 3, 1999. Accepted September 7, 1999. ES990617K
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