Environ. Sci. Technol. lS89, 2 3 , 1138-1148
Seasonal Variation in the Atmospheric Concentration of Polychlorinated Biphenyl Congeners Jon B. Manchester-Neesvig and Anders W. Andren'
Water Chemistry Program, University of Wisconsin, Madison, Wisconsin 53706
Eighteen air samples were collected and analyzed for total polychlorinated biphenyls (PCBs) and individual congeners over a year in a remote site in the Great Lakes watershed. Collection consisted of gas and particle samples. Total PCB concentrations varied from 1.820 ng/m3 in the summer to 0.135 ng/m3 in the winter, with an average of 92% in the vapor phase. Sixty-six congeners were found in more than 50% of the gas and particle samples. These data were then used to gain insight with respect to long-term and seasonal time trends, source-receptor congener fractionation, and atmospheric residence times. No discernable reduction in atmospheric PCB levels is apparent during the last 7 years in this location. Congener patterns resemble, but are not identical with, those of Aroclor 1242. Calculations indicate that average residence time of PCB congeners is on the order of a few months. The short residence time combined with relatively constant annual average PCB levels indicates repeated cycling between earth and atmosphere before final removal from the environmentally mobile reservoir.
Introduction Polychlorinated biphenyls (PCBs) have been observed in soil, water, and sediments (I),as well as fish (2),insects ( 3 ) , tree bark ( 4 ) , and human tissue (5). In addition, several studies have measured the concentration of PCBs in air (6, 7). The apparent omnipresence of PCBs is due in part to their robust chemical nature and the fact that the atmosphere serves as an important pathway for the global transport of these compounds (8-11). Recent reports on the presence of PCBs in the snows of Antarctica (121, which has no local source of these compounds, is one additional piece of evidence indicating that the atmosphere readily distributes these semivolatile compounds (SOCs) around the world. As referenced above, several investigators have previously measured concentrations of atmospheric PCBs. Most of these studies have reported measurements made only for brief periods during the year, often during the warm summer months. Little attention has been given to the possible seasonal variation in atmospheric concentrations of PCBs (13). Moreover, because measurements are few and difficult to compare directly, little is known about the response time of the environment to efforts aimed at reducing the emission of these compounds. Finally, most early attempts to quantify atmospheric PCBs used packed-column chromatography and so could not resolve individual congeners; only estimates of the total PCBs in an air sample were determined. To advance the understanding of the environmental fate of PCBs, it is necessary to measure the concentrations of individual congeners. This is true because congeners differ greatly in toxicity (14,151. Congeners may also persist for different lengths of time in the environment due to fractionation as PCBs move between various environmental compartments. In addition, models that may be developed to explain the transport of individual PCB congeners bwed 1138 Environ. Sci. Technol., Vol. 23, No. 9, 1989
on physical and chemical properties of these compounds might then be extended to other unrelated compounds. While much progress has been made in understanding the fate and transport of PCBs, many questions remain unanswered regarding the behavior of PCBs in the atmosphere. For example: (1)Has the total concentration of atmospheric PCBs decreased since the ban on the use of PCBs became effective in 1979? (2) To what extent does the total concentration of PCBs in the air change from season to season over the course of a year? (3) Is the distribution of atmospheric PCB congeners similar to the distributions in the original commercial mixtures, or has physical fractionation, chemical weathering, or both affected some congeners more than others? (4) What are the residence times of PCB congeners in the atmosphere? This paper will address each of the above questions using information gathered during a 1-year study of the concentrations of atmospheric PCBs in a remote site in northern Wisconsin. This site was selected to minimize local effects so that a regional picture might be constructed.
Experimental Section Eighteen air samples were collected over an ll-month period from April 1984 to March 1985. All samples were taken in the Northern Highlands State Forest in northern Wisconsin. The sample site is in a remote area characterized by many small lakes and communities of less than 5000 inhabitants. The nearest industry is -200 km to the south. Sampling equipment was placed atop a 30-m-tall fiiespotting tower, which was situated on top of a 70-m-tall hill; air intakes were -50 m, on average, above the tree canopy. Thus, sampled air was representative of the bulk atmosphere, with less influence from the local boundary layer. Each air sample was fractionated into a particle phase and gas phase, which were collected sequentially with a system designed by Doskey and Andren (16). This system uses a modified General Metal Works Hi-Vol air sampler with a glass fiber filter (cleaned by ashing to 450 "C) to collect particles and a XAD-2 resin [cleaned by sequential extraction (17)] cartridge to retain gases. Gas-phase retention efficiencies have been discussed by Doskey and Andren (161, Bidleman et al. ( l a ) ,and Bouchertall and Duinker (19). The essential components of the air sampler (motor, flow controller, timer, resin cartridge, and filter holder) were removed from the aluminum shelter that normally houses these pieces and then assembled, with 10-cm pipe, into the small enclosure at the top of the fire tower. Thus, the sampler head (filter holder and resin cartridge) was suspended outside of the enclosure, while the motor and electronics of the sampler were isolated within. Sampled air was ducted away from the sampler after it exited the motor. Two complete air sampling systems were placed in the fire tower enclosure, and so two independent samples were collected on each sample date. By comparing the concentrations measured on a given date by each sampling system, it was possible to establish sampler precision for both the gas and particle samples.
0013-936X/89/0923-1138$01.50/0
0 1989 American Chemical Society
Field blanks for the filter and resin collection media were determined by taking a clean filter and resin into the field and allowing ambient air to contact both for the duration of the sample period, while shielding each from atmospheric particles. Each blank was then returned to the lab and analyzed in the same manner as samples. Resin and filter samples and blanks were Soxhlet extracted with 350 mL of dichloromethane for 24 h. The extracts were transferred to 2 mL of hexane by using a Snyder column and a steam bath and then cleaned on a silicic acid chromatography column by a method described by Bidleman et al. (20). A Rotovap was used to concentrate the eluates and transfer all solutes to less than 1mL of isooctane. Finally, the cleaned and concentrated extracts were placed in a 1.0-mL volumetric flask (which also contained 100 pL of a 550 ng/mL solution of octachloronaphthalene as an internal standard) and brought to volume. A Hewlett-Packard 5840 gas chromatograph, equipped with an electron capture detector and DB-5 capillary column (30-m long X 0.25-mm i.d. X 0.25-pm film thickness), was used to analyze all samples. The chromatograph was calibrated with a master standard made by combining equal amounts of Aroclors 1242,1248,1254, and 1260. A temperature program, which began at 100 "C and increased by 1 OC/min until reaching 240 "C, successfully separated 103 peaks when the master standard was analyzed. Mullin et al. (21) have published relative retention time (RRT) data for all 209 PCB congeners. The validity of these RRT was determined by using a set of eight pure congeners. It was possible to replicate the published values with an error of 0.3-1 % While this error is small, it was not possible to use the published RRTs directly to identify the peaks in the master standard chromatogram, as RRTs for closely eluting congeners often differ by less than the observed error. Rather, a correction curve, based on the eight congeners, was generated. By use of this curve, observed RRTs in the master standard were corrected and then compared to the 209 possible published RRTs, and a small set of possible congeners was determined for each peak in the master standard. Finally, each small set of peaks was compared with published lists of congeners (22-24) in each Aroclor, and the single congener corresponding to a peak in the master standard was identified. With this technique, it was possible to identify 95 congeners in the master standard (25). The published lists of congeners in each Aroclor (referenced above), as well as unpublished proceedings from a PCB analysis workshop (Mullin, M. D., private communication), provide the weight percent of each congener in a given Aroclor. By multiplying the weight percents for an Aroclor by the concentration of that Aroclor used in this study, and then summing the contributions from each of the four Aroclors, it was possible to determine the amount of each congener in the master standard. These amounts were then divided by the corresponding GC signal, and the response factor of the internal standard, to produce relative response factors (RRFs) for each congener in the master standard. The RRFs were updated with each set of samples so as to reduce the error associated with GC drift. By use of the RRFs,the congeners in each sample were quantified. The congeners identified in the master standard, and the weight percents of each in each of the four Aroclors, are listed in Table I; congeners are listed in order of elution from a DB-5 column. The total PCB in each sample was calculated by summing the individual congener amounts for that sample. However, only those congeners that appeared in each of
.
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Figure 1. Total gas-phase PCB concentrations measured during the sampling period. Values indicated as zero represent missing data.
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the two samples on a given date, and then only those for which the range divided by the mean was less than 0.5, were taken as valid measurements and so included in the total and reported as observed. In general, 90% of the congeners in any sample fit the above criteria. The total PCB in each sample was also estimated by using a statistical algorithm known as C O ~ T A R(26). This program sums the distribution of congeners in the Aroclors so as to create a complex mixture that resembles the sample and then determines the concentration of PCB in the sample by comparison with the Aroclor complex mixture. Totals determined in this way deviated by at most 5% from the totals found by summing the congeners in a sample. Serial dilutions of standards made from pure PCB congeners were used to determine the limit of quantification (LOQ) for this study. The detection limit was relatively constant for various congeners; 500 fg of any congener produced approximately zero signal from the detector. When this value was combined with the average sample volume (1150 m3), a limit of quantification of 0.1 pg/m3 was established. Any congener that was observed at less than this concentration was not included in the calculation of the total PCBs and was reported as detected but not quantified. (See ref 25 for a more detailed discussion of the analytical procedure). Results The total concentration of PCBs in the gas phase and in the particle phase for each of the 18 sampling dates are presented in Figures 1 and 2. Note that the definition of gas and particle phases is an operational one; Doskey Environ. Scl. Technol., Vol. 23, No. 9, 1989
1139
m
Table I. Congeners Identified in the Master Standard for this Study IUPAC no. 4 7 6 8+5 19 18 17 24 27 16 32 26 25 28 + 31 33 53 51 22 45 46 52 43 49 48 + 47 44 42 41 71 64 40 103 67 100 63 74 70 + 76 66 95 91 56 60 84 89 101 99 119 83 97 81 87 85 136 110 82 151 135 144 107 149 118 134 114 131 146 153 105 141 130 176 137 138 158 129 178 175 187 + 182 183 128 167 185 174
+
+ +
+
+
+
1140
+ 132
namen
1242
2,2’-DCB 2,4-DCB 2,3’-DCB 2,4’-DCB 2,2’,6-TCB 2,2’,5-TCB 2,2‘,4-TCB 2,3,6-TCB 2,2’,3-TCB 2,4’,6-TCB 2,3’,5-TCB 2,3’,4-TCB 2,4,4’-TCB 2’,3,4-TCB 2,2’,5,6’-TeCB 2,2’,4,6’-TeCB 2,3,4’-TCB 2,2’,3,6-TeCB 2,2’,3,6’-TeCB 2,2’,5,5’-TeCB 2,2’,3,5-TeCB 2,2’,4,5’-TeCB 2,2’,4,5-TeCB 2,2’,3,5’-TeCB 2,2’,3,4’-TeCB 2,2’,3,4-TeCB 2,3,4’,6-TeCB 2,2‘,3,3‘-TeCB 2,2’,4,5’,6-PCB 2,3’,4,5-TeCB 2,3,4’,5-TeCB 2,4,4’,5-TeCB 2,3‘,4’,5-TeCB 2,3’,4,4’-TeCB 2,2’,3,5’,6-PCB 2,2’,3,4’,6-PCB 2,3,3’,4’-TeCB 2,2’,3,3’,6-PCB 2,2’,3,4,6’-PCB 2,2’,4,5,5’-PCB 2,2’,4,4’,5-PCB 2,3’,4,4’,6-PCB 2,2’,3,3’,5-PCB 2,2’,3’,4,5-PCB 3,4,4’,5-TeCB 2,2’,3,4,5’-PCB 2,2‘,3,4,4‘-PCB 2,2’,3,3’,6,6’-HCB 2,3,3’,4’,6-PCB 2,2’,3,3‘,4-PCB 2,2’,3,5,5’,6-HCB 2,2’,3,3’,5,6’-HCB 2,3,3’,4’,5-PCB 2,2’,3,4’,5’,6-HCB 2,3‘,4,4’,5-PCB 2,2’,3,3’,5,6-HCB 2,3,4,4’,5-PCB 2,2’,3,3’,4,6-HCB 2,2’,3,4’,5,5’-HCB 2,2’,4,4’,5,5’-HCB 2,2’,3,4,5,5’-HCB 2,2’,3,3’,4,5’-HCB 2,2’,3,3’,4,6,6’-HeCB 2,2’,3,4,4’,5-HCB 2,2’,3,4,4’,5’-HCB 2.3,3’,4,4’,6-HCB 2,2’,3,3’,4,5-HCB 2.2’.3.3’,5,5’.6-HeCB . . . , . 2,2’,3,3’,4,5’,6-HeCB 2,2’,3,4’,5,5’,6-HeCB 2,2’,3,4,4’,5’,6-HeCB 2,2’,3,3’,4,4’-HCB 2,3’,4,4’,5,5’-HCB 2,2’,3,4,5,5’,6-HeCB 2,2’,3,3’,4,5,6’-HeCB
3.36 0.31 0.91 12.32 1.01 8.35 2.72 0.46 2.33 2.64 0.97 0.50 23.05 5.37 0.62 0.14 1.07 0.68 0.36 2.33 0.21 1.79 2.34 3.36 1.03 1.83 0.31 0.72 0.01 0.06 0.07 1.35 3.66 3.64 0.60 0.17 3.14 0.44 0.13 0.44 0.27 0.04 0.07 0.25 0.04 0.26 0.25 0.06 0.66 0.19 0.05 0.10 0.02 0.15 0.17 0.01 0.01 0.03 0.07 0.62
Environ. Sci. Technol., Vol. 23, No. 9, 1989
0.03
0.04 0.04 0.03 0.09 0.03 0.03 0.06 0.05 0.11 0.05 0.03 0.04 0.03 0.08
Aroclor weight percents 1248 1254 1.06 0.04 0.11 0.87 0.35 4.54 1.08 0.13 0.82 1.61 0.33 0.10 20.33 2.80 0.90 0.20 0.66 0.82 0.43 3.85 0.26 2.98 4.17 5.25 1.45 3.14 2.61 1.03 2.14 0.10 0.11 2.85 7.13 7.66 1.27 0.40 5.81 1.08 0.06 1.19 0.84 0.06 0.12 0.64 0.11 0.66 0.82 0.08 1.90 0.49 0.09 0.15 0.07 0.34 0.61 0.14 0.01 0.04 0.14 1.70 0.06 0.06 0.05 0.04 0.29 0.05 0.05 0.08 0.06 0.13 0.10 0.07 0.05 0.04 0.12
1.13 0.05 0.11 0.28 0.19 0.15 0.10 0.08 0.08 0.11 0.08 0.06 0.29 0.11 0.10 0.05 0.03 0.08 0.10 4.21 0.08 0.90 0.26 2.32 0.11 0.09 0.51 0.11 0.29 0.02 0.03 0.62 4.41 1.10 6.78 1.05 0.59 4.24 1.61 7.06 2.49 0.12 0.44 2.40 0.37 3.14 1.44 1.05 9.61 0.96 0.93 1.53 0.31 5.93 2.83 0.42 0.25 0.17 2.43 10.51 0.82 0.68 0.06 0.54 5.85 0.90 0.55 0.12 0.07 0.41 0.40 1.92 0.31 0.05 0.52
1260 1.08 0.04 0.11 0.27 0.18 0.15 0.10 0.08 0.08 0.11 0.08 0.06 0.27 0.11 0.09 0.05 0.03 0.08 0.09 0.25 0.08 0.07 0.18 0.09 0.05 0.09 0.04 0.06 0.09 0.02 0.03 0.06 0.06 0.09 2.63 0.06 0.09 0.24 0.34 2.46 0.05 0.05 0.05 0.11 0.06 0.32 0.05 1.55 1.38 0.05 3.05 2.14 0.03 8.68 0.20 0.98 0.03 0.09 2.71 11.82 1.89 0.43 0.56 0.04 5.23 0.63 0.15 1.20 0.28 4.88 3.28 0.52 0.19 0.75 4.34
Table I (Continued) IUPAC no.
name”
1242
177 171 + 156 173 200 172 + 197 180 193 191 199 170 198 201 203 + 196 189 195 207 194 205 206
2,2‘,3,3’,4’,5,6-HeCB 2,2‘,3,3’,4,4‘,6-HeCB 2,2’,3,3’,4,5,6-HeCB 2,2’,3,3’,4,5’,6,6’-OCB 2,2’,3,3’,4,5,5’-HeCB 2,2’,3,4,4’,5,5’-HeCB 2,3,3’,4’,5,5’,6-HeCB 2,3,3’,4,4’,5’,6-HeCB 2,2‘,3,3‘,4,5,6,6’-0CB 2,2‘,3,3‘,4,4’,5-HeCB 2,2’,3,3’,4,5,5’,6-OCB 2,2’,3,3’,4’,5,5’,6-OCB 2,2’,3,4,4’,5,5’,6-OCB 2,3,3’,4,4’,5,5’-HeCB 2,2’,3,3’,4,4’,5,6-0CB 2,2’,3,3’,4,4’,5,6,6’-NCB 2,2’,3,3’,4,4’,5,5’-OCB 2,3,3’,4,4’,5,5’,6-0CB 2,2‘,3,3‘,4,4‘,5,5’,6-NCB
0.03 0.06 0.12 0.08 0.10 0.17 0.04 0.02 0.02 0.22 0.04 0.10 0.07 0.03 0.11 0.02 0.06 0.02 0.04
Aroclor weight percents 1248 1254 0.18 1.56 0.17 0.11 0.22 1.24 0.06 0.03 0.03 1.24 0.06 0.09 0.08 0.04 0.16 0.03 0.06 0.03
0.05 0.11 0.16 0.11 0.13 0.44 0.06 0.03 0.03 0.33 0.05 0.13 0.17 0.04 0.20 0.03 0.16 0.03 0.06
0.06
1260 1.57 1.72 0.73 0.11 1.09 12.07 0.54 0.10 0.22 6.51 0.16 3.30 4.72 0.15 3.12 0.07 2.12 0.05 0.87
“ D = di, T = tri, Te = tetra, P = penta, H = hexa, He = hepta, 0 = octa, and N = nona. Table 11. Measured Atmospheric ref
PCB Concentrations Year
Harvey and Steinhauer (9)
1973
Bidleman and Olney (IO)
1973
Bidleman et al. (27) Giam et al. (11) Doskey and Andren (6)
1976-1979 1977 1977
Eisenreich et al. (7)
1978 1979 1980 1978 1979 1981 1982
Tanabe et al. (12)
mean, ng/m3
n
range
location
0.3 1.0 4.6 0.1 0.5 5.3 3.1 0.4 7.7 3.0 1.0 1.5 0.9 1.0 7.0 7.1 0.12 0.09
4 6 2 5 8 4 37 10 2 7 8 13 8 8 26 10 2 2
0.5-0.15 0.6-1.6 3.9-5.3 0.05-0.06 0.2-0.65 2.1-9.4
Bermuda George8 Bank Vineyard Sound Grand Banks Bermuda Rhode Island South Carolina Gulf of Mexico Madison Milwaukee Lake Michigan Lake Superior Lake Superior Lake Superior Minneapolis Minneapolis Antarctica Antarctica
and Andren (16) have discussed the practical limitations of particle- and gas-phase PCB collection. As can be seen from a comparison of the two time series, .the gas phase accounts for, on average, 92% of the PCBs in the atmosphere (the range is 83-97%). Thus, the time series for the total atmospheric concentration of PCBs is nearly identical with that of the gas phase. By comparing the two gas samples for a given sampling date, the average error in measurement of total gas concentration was found to be f10.8% and the relative standard deviation was 7.7%. The amount of PCBs associated with particles was much smaller and, thus, was more difficult to quantify. To improve accuracy, the two particle samples for each date were combined in all but three cases. From these three cases, the error in measurement of total particle concentrations was estimated to be about f20%. I t is apparent from the time series that total gas-phase PCB concentrations, and hence total atmospheric PCB concentrations, vary by a factor of 13 during the year, from 0.135 to 1.820ng/m3. Total particle-bound PCB concentrations are somewhat more stable, but also vary ---fold for all sampling dates, from 0.013to 0.090 ng/m3. Total particle-bound PCB concentrations, normalized to total suspended particulate (TSP)concentration, range from 0.6 to 5.1 pg/g. Annual average concentrations may also be
0.13-0.79 7.3-8.1 0.8-5.0 0.6-1.5 0.9-3.5 0.4-1.4 0.1-2.5 1.3-20 4.3-9.1 0.06-0.18 0.08-0.10
calculated from these data. Thus, the annual average gas-phase concentration is 0.483 ng/m3, the annual average particle-bound concentration is 0.032 ng/m3, the annual average TSP-normalized particle-bound concentration is 2.5 pg/g, and the annual average total concentration is 0.546 ng/m3. Ninety-five congeners were included in the master standard and might have been identified in any sample. Ninety-two of the 95 possible congeners appeared in at least one gas or particle sample. Sixty-six congeners were found in more than 50% of the gas and particle samples and 48 congeners were in more than 80% of gas and particle samples. A set of 30 congeners was consistently found in every gas and particle sample. Three congeners (IUPAC no. 43, 167,and 200) were found in gas samples but never in particle samples. The three congeners were present in the gas phase at very low concentrations and were probably present in particle samples at levels below the detection limit. Ten congeners appeared in particle samples but were never found in gas samples (IUPAC no. 114,130,131, 136, 172 + 197,189,199,206,207). All of these congeners have five or more chlorines (all but 114 have six or more) and are heavy compounds relative to other PCBs. Most likely, these congeners are present at undetectable levels in the Environ. Sci. Technol., Vol. 23, No. 9, 1989
1141
gas phase and are almost completely associated with particles in the atmosphere.
Discussion Time Trends in Atmospheric PCB Concentrations. Table I1 lists the results from several previous studies of atmospheric concentrations of PCBs. No previous comparable data exist for individual congeners. It is apparent from this table that the concentration of PCBs in remote areas is less than 0.5 ng/m3. This value increases to -1.0 ng/m3 in rural areas and is greater than 1ng/m3 in urban areas. Thus, the table indicates a possible correlation between atmospheric PCB concentrations and population density, such as was observed by Harvey and Steinhauer (9) off the Atlantic coast of the United States. Two of the studies listed (6, 7) reported values for atmospheric PCB concentrations measured in the same region as the sample site of this study (western Great Lakes Basin) and -7 years earlier. Both studies reported similar values for total atmospheric PCB concentration of -1.0 ng/m3. Comparison of the values measured in this study with those measured previously provides an indication of overall trends in the atmospheric concentration of PCB. The average value for total atmospheric PCB concentration measured in this study is -0.5 ng/m3. A direct comparison of this value with the previously measured concentration, 1.0 ng/m3, would indicate a decrease of 50% overall. However, the earlier studies measured concentrations only during the warmest parts of the year, when atmospheric concentrations are greatest. If the values measured in this study during the summer are compared with the previous values, it is observed that current atmospheric PCB concentrations bracket those measured 7 years earlier. Thus, although severe restrictions on the use and disposal of these compounds have been implemented nationwide, no drastic decrease in overall atmospheric PCB concentrations was observed between 1977 and 1984. Seasonal Variations. Results shown in Figures 1 and 2 indicate that the concentrations of PCBs in both the gas and particle phases are not constant over the year, but rather vary in a nonrandom manner. Thus, total PCB gas concentrations reach a maximum in the summer of 1.8 ng/m3, decrease to minimum values (-0.15 ng/m3) in the winter, and are at similar midrange values in the spring and fall (-0.5 ng/m3). Moreover, the values observed in the spring of 1984 are similar to the values in the spring of 1985. The total PCB gas concentration seems to exhibit a single annual cycle. [Similar observations have been made at three sampling sites in Bloomington, IN (281.1 In contrast, total particle-bound PCB concentrations display two maxima and two minima over 1year; maximum concentrations (-0.050 ng/m3) are observed during both the summer and winter, while minimum concentrations ( 0.010 ng/m3) occur during the spring and fall. As with the gas phase, particle-bound concentrations are similar in the spring of 1984 and the spring of 1985. The relatively smooth annual cycle in both gas and particle-bound PCB concentrations seems to follow the similarly smooth variation in annual air temperatures. This phenomenon is examined by plotting gas and particle concentrations versus the average temperature on each sampling date. Figure 3 is a plot of total PCB gas concentration versus average temperature. A quadratic correlation is observed; gas-phase concentration increases exponentially as temperature increases linearly. This plot provides some explanation for the shape of the time series plot for gas-phase concentrations. The peak in the time series plot occurs in summer when temperatures are greatest, and the min-
-
N
1142
Envlron. Sci. Technol., Vol. 23, No. 9, 1989
1200
I
1000 O
200
L
#
O L -20
-10
0 10 Air Temperature ("C)
20
30
Figure 3. Total gas-phase PCB concentrations versus average air temperature during sampling period. Line represents the best-fit quadratic curve. Note: Three sample dates have been excluded due to confounding effects from rain or snow.
5-
4t 3-
11,
04 -20
-10
0 10 Air Temperature ( " C )
20
0
Figure 4. Total particle-bound PCB concentrations normalized by TSP versus average air temperature during sampling period. Line represents the best-fit quadratic curve.
imum is associated with the coldest samples. Spring and fall gas concentrations are between summer and winter values, as are temperatures. The observed exponential increase in PCB gas concentration with increasing temperature is very similar to the manner in which vapor pressure increases with temperature (29). Thus, given a source of PCBs, the extent to which PCBs enter the atmosphere may be controlled by vapor pressure, which increases with temperature. The time series plot for particle-bound PCB concentrations is complex (a detailed analysis of the partitioning of PCBs is being published elsewhere). However, when concentrations are normalized to total suspended particulate concentration and plotted with temperature, a simple pattern emerges (Figure 4). Like the gas-phase concentrations, particle-bound concentrations show a strong quadratic correlation with temperature. However, unlike the gas phase, the plot of particle concentrations exhibits a minimum just above 0 "C. Thus, the amount of PCBs associated with particles is relatively large at both low and high temperatures and is small at temperatures just above the freezing point of water. The temperature dependence of particle-bound concentrations can explain the shape of the time-series plot of these concentrations. Two minima appear in the time series during spring and fall when average sample temperatures are near 0 "C. The two maxima in the time-series plot occur in the summer and winter, when the sample temperatures are at high and low extremes, respectively. The increasing trend observed in the particle-bound concentration and temperature plot below 0 "C provides evidence that gas-particle partitioning is inversely related
40 500
1
300
\
EU L
TS7
lil loo
20
I
10
R 0
67
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IUPAC 52
I
IUPAC 1181
0
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Sampling D a t e Flgure 5. Gas-phase concentrations of individual PCB congeners. Values indicated as zero represent missing data.
to temperature. The fact that particle-bound concentrations increase above 0 "C may be due to the greatly increased gas-phase concentrations associated with high temperatures. The above discussion has considered only the total gas and particle atmospheric PCB concentrations. While these values provide a general idea of the behavior of PCBs in the air, a more detailed picture emerges when the concentrations of individual PCB congeners are examined. Time series plots for congeners in gas and particle samples were constructed for the 48 congeners that occurred in more than 80% of the samples. Four examples of these plots are shown in Figures 5 and 6. All of the plots for gas-phase congeners resemble the time-series plot for total gas-phase concentrations. All congeners were most plentiful during summer months and reached minimum values during the winter, with intermediate values in the spring and fall. The simple annual pattern is apparent in all congeners examined, despite the fact that the congeners differ in amount in any one sample by as much as 2 orders of magnitude. All time-series plots for particle-bound congener concentrations exhibited the pattern presented by the particle-bound total concentrations. Thus, maximum concentrations of congeners on atmospheric particles occur twice during the year, once in the summer and again in the winter. Concentrations of particle-bound congeners reach minimum values in the spring and fall. The pattern is discernable in all inspected congeners, though it is most apparent in those congeners that could be collected and analyzed at levels above the limit of quantification.
Gas-phase and particle-bound concentrations for the 48 congeners that occurred in at least 80% of the samples were plotted with sample temperature for each congener. Four examples of these plots are shown in Figures 7 and 8. As with the time-series plots, the shapes of the gasphase and particle-bound congener concentration and temperature plots are similar to the same plots for total gas and total particle-bound concentrations. The quadratic fits to the gas-phase congener concentrations are very good. Averaged over all plotted congeners, the correlation coefficient is 0.86 and one-third of the congeners have correlation coefficients greater than 0.90. The high degree of correlation provides strong evidence that, if a source exists, the gas-phase concentration of PCB congeners is regulated by ambient temperature. Particle-bound congener concentrations fit quadratic curves, when plotted versus temperature, with an average correlation coefficient of 0.74. Also, like the total particle-bound concentrations, a minimum is observed in every congener plot at 4 f 2 "C. Congener Fractionation. A complete description of the congener distribution of any sample would be given by listing the weight percents of all congeners in the sample. However, such lists are difficult to compare directly because of the large number of congeners. Distributions are better summarized by adding the weight percents of congeners of a given chlorine level. Table I11 lists the weight percent of each chlorine level for average gas and particle samples, where the average is taken over all 18 samples collected during the year. The chlorine level weight percents for the four Aroclors used in the master Environ. Sci. Technol., Vol. 23, No. 9, 1989
1143
2.0
IUPAC 52
IUPAC 28+31
1
15-
10
1 .o
E
5
0.5
m
0
0.0
r\3
\
E
0 L
m
I
0.3
0
.-0
IUPAC 118
T
0.2
CL
0.1
0.0
Sampling D a t e Flgure 6. Particiabound concentrations of individual PCB congeners. Values indicated as zero represent missing data.
300
20
0
Congener 28+31
/! I
250
16
12
150
;
o
o
\
E m m
O
4
8 4
o
l -20
-1 0
0
10
20
30
W
L
3-
0,
~
-10
0
10
20
I
30
Congener 153+105+132
Congener 118
0 0
a --
.-
a.
-20 10-
2 --
1
--
0,
6 -4
--
O T
:
I
Flgure 7. Gas-phase concentrations of individual PCB congeners versus average air temperature during sampling period. Lines represent the best-fit quadratic curves. 1144
Environ. Sci. Technol., Vol. 23, No. 9, 1989
1.2-
0.12
1 .o -.
--
0
0
0.8
d
I
0
E
?
0.2
c3 \ C
0.0 -20 -10 0.028 0 Cong ner 118
" L
z
n
v
.o 0.021i L
I
1
10
0
20
I
0.00 -I 30 -20 -10 0 0.15Congener 153+105+132
10
20
I
20
30
O
u\
0
0.03 --
0, 0 .
0.000 1 -20
-10
0
0
10
0
OO 0
0.001 1 -20
20
-10
0
0
0
10
Air Temperature ( " C ) Flgure 8. Particlsbound concentrationsof individual PCB congeners normallzed by TSP versus average air temperature during sampling period. Lines represent the best-fit quadratic curves.
Table 111. Weight Percent by Chlorine Level for Samples and Aroclors C1 no.
annual av vap. part.
0
0
1 2 3 4 5 6 7 8 9 10
0 21 43 16 14 3 1 0 0 0
0 0 18 29 17 25 6 4 1 0 0
summer av vap. part. 0
0 17 50 18 10 3 1
0 0 0
0 0 28 42 18 6 5 2 0 0 0
standard are also given in Table 111. It is apparent from Table I11 that both the average gas sample and the average particle sample have congener distributions that are similar to, but not identical with, the distribution of congeners in Aroclor 1242. However, many heavier congeners not found in Aroclor 1242 appear in small concentration in the gas and particle samples, indicating Aroclor sources other than 1242. Both of these findings are in agrement with COMSTAR results. Table I11 also lists the chlorine level weight percents for average summer and winter gas and particle samples. These numbers were generated by averaging the weight percents of congeners in the August and September samples to produce summer gas and particle values. Average amounts of congeners from November and December samples were used to create winter gas and particle sample values. The average temperature of the summer samples was 19.6 O C , while the winter samples represent an average temperature of -9.3 OC. Only congeners that appeared in all averaged summer samples or all averaged winter samples were included. The congener distributions of both of the average sum-
winter av vap. part. 0
0 33 32 21 10 3 0 0 0 0
1242
Aroclors 1248 1254
0 0 12 46 21 7 11 2 1 0
0
0
0
0 17 48 28 4 1 1 1 0
0 2 33 51 12 3 2
0 2
0
1 16 45 35 6 1 0
0
0
0
0
1
1260 0 0 2 1 2 8 40 40 14 1 0
mer samples and both of the average winter samples are similar and most resemble the distribution of those found in Aroclor 1242. However, heavier congeners are also present, particularly in the winter particle sample, indicating contributions from other Aroclors. While it is clear that all samples of both the gas and particle-bound phases contain mostly congeners found in Aroclor 1242, subtle differences exist between winter and summer samples. To further explore these differences, residual plots were calculated for gas and particle samples. This was done by subtracting winter gas sample congener weight percents from summer gas sample congener weight percents and by subtracting winter particle sample congener weight percents from summer particle sample congener weight percents, respectively. Overall, residual congener weight percents oscillated about zero, indicating that summer and winter gas or particle samples were similar. However, several congeners did not follow the trend. Specifically, congeners IUPAC no. 137,158,174,177, and 183 were present in the summer gas sample but were absent from the winter gas sample. Moreover, congeners IUPAC no. 107,114,128,153 + 105 Environ. Sci. Technol., Voi. 23, No. 9, 1989
1145
Table IV. Summer and Winter Congener Weight Percent Variation IUPAC no. 107 114 153 137 158 183 128 174 177 195
summer gas
winter particle 0.16 0.16 2.02
+ 105 + 132 0.06 0.07 0.14
0.16 0.17 0.04 0.74
" Diagnostic 1254.
Aroclor 1254 1260 0.29" 0.24" 9.96 0.51" 0.85 0.38 1.82 0.49 0.17 0.05
0.03 0.03 11.03 0.04 0.59 3.06b 0.49 4.05 1.47 2.91b
*Diagnostic 1260.
+
132, and 195 were observed in winter particle samples but were not found in summer particle samples. All of these congeners are present in Aroclors 1254,1260,or both, but are not present (or are only minor components) in Aroclors 1242 or 1248. Also, several of the congeners are diagnostic for Aroclor 1254 or 1260; a diagnostic congener is present in one Aroclor 1254 or 1260; a diagnostic congener is present in one Aroclor at a concentration about 1 order of magnitude greater than in any other Aroclor. The results are summarized in Table IV. The results in Table IV suggest that small differences exist between summer and winter sources of atmospheric PCBs. The winter particle sample contained congeners found only in Aroclor 1254, and the congeners were not present in summer particle samples. Also, congeners suggesting Aroclor 1260 as a source were found in the summer gas sample but not in the winter gas sample. It is not clear what causes the shift in PCB particle samples. However, the appearance of congeners from Aroclor 1260 in the summer gas sample may be due to increased temperatures, which allow greater transport of less-volatile heavy congeners. Despite the evidence for small seasonal changes in the source of atmospheric PCBs, it must be emphasized that all samples, particle and gas, summer and winter, contained by far the greatest number of congeners from Aroclor 1242. The differences indicated above, though present, amount to only -1% of the total mass of PCBs in a given sample. Atmospheric Residence Times of PCBs. The fact that atmospheric PCB concentrations vary in a cyclic manner over the course of a year, and moreover, vary from sample to sample over several weeks, suggests that these compounds are being removed and replenished within time scales that are reasonably short (30, 3I)-on the order of a few weeks or months (see below). Details and relative importance of the various removal mechanisms have been published elsewhere (32,33). The scenario that emerges is that once introduced to the atmosphere, PCBs will be removed via wet and dry deposition processes, the relative importance of each process being a function of locality and season (Le., proximity to point sources, amount and frequency of rain or snow, temperature, and aerosol size distribution and concentration). Once deposited onto soil, vegetation, add water bodies, PCBs may be reintroduced back into the atmosphere, most likely via volatilization. Although annual volatilization rates have been estimated for Lakes Michigan and Superior (34,35), it is presently not known what fraction of the atmospheric PCBs in the Great Lakes basin is due to this source. This cycle may be repeated a number of times before permanent removal to bottom sediments of lakes and oceans (I). The extent 1146
Environ. Sci. Technoi., Vol. 23, No. 9, 1989
of microbial or chemical degradation for media of low PCB concentrations is still unknown. Because of the strong functionality of PCB vapor pressure with temperature (29), volatilization is enhanced in the summer months. Low temperatures and snow cover in temperate latitudes cause a lower input flux in the winter months. Superimposed on this seasonal cycle is the continued release of PCBs into the atmosphere from landfills (36). In addition, many products that previously used PCBs (paper products, capacitors, transformers, hydraulic equipment) are still in service and may be releasing these compounds to the atmosphere. Junge (30) described a method for calculating the residence times of trace gases in the atmosphere using the spatial and temporal variations observed in the mixing ratio of a given gas. The resulting equation is T6(m) = 0.14 (years), where T is the residence time and 6(m) is the relative standard deviation of measurements, varying in location and time, of the mixing ratio. Several assumptions are implicit in this equation: (1)The gas should be at steady-state concentrations in the atmosphere if observed over an appropriate time period. Junge suggested 1year as a suitable time. (2) The standard deviation about the mean amount of the source of the gas must be much greater than the standard deviation of the sink for the gas. This is generally true if a gas originates at only a few points but is removed at many points. (3) The error in measurement must be much smaller than the space and time variance of the mixing ratio. The above assumptions are valid for the congeners measured in this study. Thus, while the concentrations vary over 1 year, steady-state values are appropriate for times greater than 1year. Also, several researchers have noted a decrease in average PCB levels as distance from population centers increases (6,9), implying large variability in sources of PCBs; sinks for PCBs are assumed to be much more uniform. Finally, the absolute error in measurement of PCB concentrations was about one-tenth of the smallest concentration measured in this study. Measurements in this study vary in time but are all taken in the same location. Therefore, the calculated residence times are regional rather than global. An alternate method has been suggested for calculating the residence times of gases that partition to atmospheric particles (31). The important parameter in this method is 4, the partition ratio, defined as the fraction of total gas in a given volume that is associated with particles. If the average northern hemisphere residence time of atmospheric particles is taken as 6 days (37), then the residence time of a gas with partition ratio (b is 614 (days). Both methods described above were used to calculate the residence times of -30 congeners that appeared in every sample collected in this study. The results are displayed in Figure 9. If the results in Figure 9 are averaged across all the congeners, it is apparent that the two methods agree in the predicted average residence time for congeners within a factor of -2. Thus, the method based on standard deviation predicts an average residence time of -60 days, while the method based on partitioning suggests a residence time of 100 days. Considering the uncertainty in each method, these values are very similar. Therefore, the average residence time of atmospheric PCB congeners is on the order of a few months, rather than days or years. This prediction is consistent with the idea that PCBs cycle many times between the earth's surface and the atmosphere.
-
x
IUPAC # Flgure 9. Atmospheric residence times of individual PCB congeners calculated by the standard deviation method of Junge (30) (+) and by the partitiondependent method of Junge ( 3 1 ) (0).
While the average residence times predicted by each method are similar, the two methods do not agree in the trends predicted for residence times with respect to increasing chlorine content of the congeners. Thus, the standard deviation method suggests that congener residence time is independent of chlorine content, while the partitioning method predicts that residence times should decrease as chlorine content (and, therefore, molecular weight) increases. The discrepancy in predicted congener trends is most likely due to the different assumptions used in each method. The partitioning method assumes that removal of PCB congeners occurs only via particle-associatedremoval, while the standard deviation method makes no a priori assumptions regarding the nature of removal processes. Congener distributions in all 18 samples collected in this study were very similar, and no depletion of heavy congeners relative to light congeners was observed. The relative depletion of heavy congeners might be expected from the relatively short residence times predicted by the partitioning method. The fact that these congeners are not depleted suggests that processes other than particleassociated removal may also be important in controlling the fate of atmospheric PCBs. Conclusions
A method was developed to identify and quantify almost 100 PCB congeners in atmospheric samples, with a procedural limit of detection of 0.1 pg/m3. Eighteen samples were collected over 11months, and from these collections, it was possible to determine temporal trends in both total atmospheric concentrations and the concentrations of individual PCB congeners in the particle-bound and gas phases. This data set provides the first long-term measurements of atmospheric PCBs on an individual congener basis. Gas-phase concentrations range between 0.135 and 1.820 ng/m3, while particle-bound PCBs range between 0.013 and 0.090 ng/m3. Gas-phase concentrations exhibited a yearly cycle with one maximum, while particle concentrations displayed an annual cycle with two maxima. Annual average total atmospheric PCB concentration in 1984, at the study site, was -0.55 ng/m3. The greatest concentrations observed in this study occurred in the summer, and measured average summer values of 1.0 ng/m3 are similar to those determined in earlier studies. Thus, during the last 7 years, no drastic reduction in at-
mospheric PCBs is apparent in the remote areas of the Great Lakes basin. No data are currently available that permit a rigorous statistical examination of the year to year trends. Ninety-two of 95 possible congeners were observed in at least one atmospheric sample; 48 congeners were in more than 80% of the samples; and 30 congeners were in every sample. Ten congeners were found only in particle, and not gas, samples. The ratios of concentrations of the 48 most prevalent congeners most resemble, but are not identical with, those found in Aroclor 1242. Slight differences in congener distributions were observed between winter and summer samples. However, the congeners that differed contribute only -1% of the total mass of any one sample. Overall, the congener distributions were surprisingly similar between seasons, despite different air trajectories. Two different methods were used to calculate the residence times of the PCB congeners consistently observed in this study. The two methods agree within a factor of -2 and suggest that the average residence time of PCB congeners is on the order of a few months. The relatively short residence time implies that PCBs are repeatedly cycled between earth and atmosphere before final removal. Finally, results presented in this study show the usefulness of long-term data bases for research purposes. This type of information will, together with laboratory and modeling studies, permit a more rigorous examination of environmental fate and transport of contaminants. Furture studies on the behavior of PCBs and other compounds in the atmosphere should incorporate sampling strategies that discern whether degradation by photolysis, hydroxyl radical reactions, or both are important. The mechanisms and rates of vapor-phase transfer across air/soil, &/water, and air/snow interfaces must also be evaluated. Registry No. PCB 19,38444-73-4; PCB 18, 37680-65-2;PCB 17, 37680-66-3; PCB 16,38444-78-9; PCB 25, m i 2 - 3 7 - 3 ; PCB 28,7012-37-5; PCB 31,16606-02-3; PCB 33,38444-86-9; PCB 53, 41464-41-9; PCB 22,38444-85-8; PCB 46,41464-47-5; PCB 52, 49,41464-40-8; PCB 48,41464-40-8; PCB 47, 3 ~ 9 3 - 9 9 - 3PCB ; 2437-79-8; PCB 74, 32690-93-0; PCB 70, 32598-11-1; PCB 76, 70362-48-0; PCB 66, 32598-10-0; PCB 95, 38379-99-6; PCB 91, 68194-05-8; PCB 97,41464-51-1;PCB a7,3a3a0-02-a; PCB 85, 65510-45-4; PCB iio,3a3ao-o3-9;PCB 151, mx3-63-5;PCB 135, 52744-13-5;PCB 144,68194-14-9;PCB 149,38380-04-0; PCB 118, ; 105, 32598-14-4;PCB 132, 31508-00-6;PCB 153, 3 ~ a - 2 7 - iPCB 38380-05-1; PCB 141, ~2712-04-6; PCB 187, m ~ 3 - 6 a - 0 PCB ; 182, 60145-23-5;PCB 174,38411-25-5;PCB 180,35065-29-3;PCB 107, 70424-68-9; PCB 114,74472-37-0;PCB 137,35694-06-5;PCB 158, 74472-42-7;PCB 183, ~ ~ 6 3 - 6 9 -PCB 1 ; 128, 38380-07-3; PCB 177, 52663-70-4; PCB 195, E"-78-2.
Literature Cited National Academy of Sciences Polychlorinated Biphenyls National Academy of Sciences: Washington, DC, 1979. Boon, J. P.; Duinker, J. C. Aquat. Toxicol. 1985, 7,119-34. Bush,B.; Simpson, K. W.; Shane, L.; Koblintz, R. R. Bull. Environ. Contam. Toxicol. 1985,34, 96-105. Meredith, M. L.; Hites, R. A. Environ. Sci. Technol. 1987, 21, 709-12. Focardi, S.; Fossi, C.; Leonzio, C.; Romei, R. Bull. Environ. Contam. Toxicol. 1986, 36, 644-50. Doskey, P. V.; Andren, A. W. J. Great Lakes Res. 1981,7, 15-20. Eisenreich, S. J.; Looney, B. B.; Hollod, G. J. In Physical Behavior of PCBs in the Great Lakes; Mackay, D., Paterson, s.,Eisenreich, s.J., Simmons, M., Eds.; Ann Arbor Science: Ann Arbor, MI, 1983; pp 115-25. Sodergren, A. Nature 1972,236, 395-7. Harvey, G. R.; Steinhauer, W. G . Atmos. Environ. 1974, 8,777-82. Bidleman, T. F.; Olney, C. E. Science 1974, 183, 516-8. Environ. Sci. Technol., Vol. 23, No. 9, 1989
1147
Environ. Sci. Technol. 1989, 23, 1148-1 154
Giam, C. S.; Atlas, E.; Chan, H. S.; Neff, G. S. Atmos. Environ. 1980, 14, 65-9. Tanabe, S.; Hidaka, H.; Tataukawa,R. Chemosphere 1983, 12, 277-88. Bidleman, T. F. Environ. Sci. Technol. 1988, 22, 361-7. Safe, S. CRC Crit. Rev. Toricol. 1984, 13, 319-93. Poland, A.; Glover, E. Mol. Pharmacol. 1977,13,924-38. Doskey, P. V.; Andren, A. W. Anal. Chim. Acta 1979,110, 129-37. Hunt, G.; Pangaro, N. Anal. Chem. 1982,54, 369-72. Bidleman, T. F.; Burdick, N. F.; Westcott, J. W.; Billings, W. N. In Physical Behavior of PCBs in the Great Lakes; Mackay, D., Paterson, S., Eisenreich, S. J., Simmons, M., Eds.; Ann Arbor Science: Ann Arbor, MI, 1983; pp 15-48. Bouchertall, F.; Duinker,J. C. Anal. Chim. Acta 1986,185, 369-75. Bidleman,T. F.; Matthews, J. R.; Olney, C. E.; Rice, C. P. J. Assoc. Off. Anal. Chem. 1978, 61, 820-8. Mullin, M. D.; Pochini, C. M.; McCrindle, S.; Romkes, M.; Safe, S. H.; Safe, L. M. Environ. Sci. Technol. 1984, 18, 468-76. Albro, P. W.; Parker, C. E. J. Chromutogr. 1979,169,161-6. Albro, P. W.; Corbett,J. T.; Schroeder,J. L. J. Chromatogr. 1981,205, 103-11. Onuska, F. I.; Kominar, R. J.; Terry, K. A. J. Chromatogr. 1983, 279, 111-8. Manchester,J. N. M.S. Thesis, Water Chemistry Program, University of Wisconsin-Madison, 1988. Burkhard, L. P.; Weininger, D. Anal. Chem. 1987, 59, 1187-90. Bidleman, T. F.; Christensen,E. J.; Harder, H. W. In Atmospheric Pollutants in Natural Waters; Eisenreich, S. J., Ed.; Ann Arbor Science: Ann Arbor, MI, 1981; pp 481-508. Hites, R. A. University of Indiana-Bloomington, personal communication.
Burkhard,L. P.; Armstrong, D. E.; Andren, A. W. J. Chem. Eng. Data 1984,29, 248-50. Junge, C. E. Tellus 1974,26,477-87. Junge, C. E. In Advances in Environmental Science and Technology; Suffet, I. H., Ed.; John Wiley & Sons: New York, 1977; Part 1, Vol. 8, pp 7-25. Andren, A. W. In Physical Behavior of PCBs in the Great Lakes; Mackay, D., Paterson, S., Eisenreich, S. J., Simmons, M., Eds.; Ann Arbor Science: Ann Arbor, MI, 1983; pp 127-40. Eisenreich, S. J. In Sources and Fates of Aquatic Pollutants; Hites, R. A., Eisenreich, S. J., Eds.; Advances in Chemistry 216; American Chemical Society: Washington, DC, 1987; pp 393-469. Swackhamer, D. L.; Armstrong, D. E. Environ. Sci. Technol. 1986,20,879-83. Strachan, W. M. J.; Eisenreich, S. J. Mass Balancing of Toxic Chemicals in the Great Lakes: The Role of At-
mospheric Deposition. International Joint Commission workshop report, Scarborough, Ontario, Canada, 1986. Murphy, T. J.; Formanski, L. J.; Brownawell, B.; Meyer, J. A. Environ. Sci. Technol. 1985, 19, 942-6. Lambert, G.; Sanak, J.; Polian, G. In Precipitation Scavenging, Dry Deposition, and Resuspension;Pruppacher, H. R., Semonin, R. G.; Slinn, W. G. N., Eds.; Elsevier: New York, 1983; Vol. 2, pp 1352-8. Received for review August 26,1988.Revised munuscript received April 25,1989. Accepted May 15,1989. This research was funded by the University of Wisconsin Sea Grant Program under grants from the National Sea Grant Program, National Oceanic and Atmospheric Administration, US.Department of Commerce, and from the State of Wisconsin. Federal Grant NABOO-AAD-ooo86, Project RIMW-28. We also acknowledge the Wisconsin Department of Natural Resources for allowing us the use of the observation tower.
Collection and Determination of Solanesol As a Tracer of Environmental Tobacco Smoke in Indoor Air Michael W. Ogden" and Katherlne C. Malolo R. J. Reynolds Tobacco Company, Research and Development, Winston-Salem, North Carolina 27 102
Methodology for the gas chromatugraphic determination of solanesol in the particulate fraction of environmental tobacco smoke (ETS) aerosol is presented. Sampling is performed by drawing air through Fluoropore membrane filters with personal sampling pumps. Samples are prepared by extracting filters, evaporating the extract to dryness, and derivatizing the residue with N,O-bis(trimethylsily1)trifluoroacetamide (BSTFA) followed by analysis on short, thin-film capillary columns with either flame ionization or mass spectrometric detection. Limit of detection is estimated at 0.2 pg/m3 for 2-h sample duration at 2 L/min. Results obtained from sampling in an environmental chamber indicate that solanesol is 2-3 % by weight of respirable suspended particles (RSP) attributable to ETS from commercial cigarettes. Consequently, the solanesol/RSP weight ratio can be used to apportion total RSP into ETS and non-ETS contributions. This approach was used to correctly predict the ETS contribution to a mixture of RSP from cigarette, candle, and oil lamp sources with an error of 10%. Introduction
Environmental tobacco smoke (ETS) is an aged, dilute mixture of sidestream and exhaled mainstream smoke from combustion of tobacco products such as cigarettes 1148
Environ. Sci. Technol., Vol. 23,
No. 9, 1989
and cigars. Since ETS has been implicated as one of a number of sources impacting on indoor air quality, there exists a need to develop methods that estimate the concentration of ETS in the indoor environment. In the past, a variety of tracers of environmental tobacco smoke have been used, including nicotine, carbon monoxide, respirable suspended particulate matter (RSP), nitrogen oxides, nitrosamines, and aromatic hydrocarbons (1). With the exception of nicotine, all of these potential tracers suffer from either a lack of specificity or extremely low concentrations, which makes their detection and quantitation difficult, unreliable, or expensive. Although total RSP concentration can be reliably determined, it too is not specific to tobacco smoke. Nicotine, however, is very characteristic of all Nicotiana species and should enter the indoor environment only from tobacco sources. As a result, the most reliable current estimates of ETS concentration are based on measurements of vapor-phase nicotine and RSP, and numerous methods have been developed for these determinations. The methods developed and currently in use in our laboratory have been described (2,3), tested ( 4 ) ,and are in routine use in a number of laboratories. Attempts to estimate the contribution of ETS to indoor air quality through the use of these two parameters are not
0013-936X/89/0923-1148$01.50/0
0 1989 American Chemical Society
