Sources of Polycyclic Aromatic Hydrocarbons and

May 14, 2004 - at 36 sites in eastern Alaska during early spring. Concentrations of each polycyclic aromatic hydrocarbon. (PAH) varied by an order of ...
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Environ. Sci. Technol. 2004, 38, 3294-3298

Sources of Polycyclic Aromatic Hydrocarbons and Hexachlorobenzene in Spruce Needles of Eastern Alaska TIMOTHY S. HOWE,† SHANE BILLINGS,‡ AND RICHARD J. STOLZBERG* Department of Chemistry and Biochemistry, University of Alaska Fairbanks, Fairbanks, Alaska 99775-6160

The concentrations of phenanthrene, anthracene, fluoranthene, pyrene, benzo[a]anthracene, chrysene, and hexachlorobenzene (HCB) were measured in spruce needles at 36 sites in eastern Alaska during early spring. Concentrations of each polycyclic aromatic hydrocarbon (PAH) varied by an order of magnitude. Samples taken from near the city of Fairbanks had higher concentrations than samples taken from more rural areas. Anthropogenic activities near Fairbanks are most likely a source of PAHs. Variation in the concentration ratios of isomeric PAHs indicates the relative importance of combustion and petrogenic sources. The relative combustion contribution is largest in coastal samples and smallest near Fairbanks. In contrast, the concentration of HCB varied by only a factor of 2. Lipid content of needles and distance from the coast were the major factors correlated with the concentration of HCB.

Introduction There is extensive evidence that concentrations of some persistent organic pollutants (POPs) vary strongly with latitude (1-3). A review of the temperature dependence of the atmospheric concentration of semivolatile organic compounds has been published (4). While temperature is an important variable, transport of POPs in the atmosphere is a multivariate phenomenon (4). Experimental evidence indicates that other variables, including local and regional sources (5), removal by vegetation (6), and temporal variability (7), should be considered in constructing transport models. Models predict distinct concentration gradients for compounds that differ appreciably in volatility, chemical stability, and removal mechanisms (8). While direct, real-time measurement of POPs in the air is desirable, it is not always practical. Passive, time integrative methods of sampling are often used as an alternative (9). An especially convenient sampler of this type is vegetation (2, 10). There is a general assumption that the concentration of the analyte in the vegetation reflects the time-integrated concentration of analyte in the air. The details associated with this assumption have been elucidated in theory and in the field (11, 12). Uptake by plants is not only an analytical * Corresponding author phone: (907)474-7732; fax: (907)474-5640; e-mail: [email protected]. † Current address: Water and Environmental Research Center, University of Alaska Fairbanks. ‡ Current address: Northern Testing Laboratories, Fairbanks, AK. 3294

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convenience, it is an important factor in removing POPs from air masses that come in contact with them (6, 8). The objective of the current work is to identify sources of polycyclic aromatic hydrocarbons (PAHs) and hexachlorobenzene (HCB) in eastern Alaska. We report the concentrations of six PAHs (phenanthrene, anthracene, fluoranthene, pyrene, benzo[a]anthracene, chrysene) and HCB in spruce needles collected at 35 locations during a 4-day period in early spring. Multivariate data analysis suggests local sources for five of the PAHs. The major source of HCB appears to be long distance transport.

Experimental Section Sample Collection and Site Description. One- and 2-year old needles of white spruce (Picea glauca, n ) 13), black spruce (Picea mariana, n ) 16), and Sitka spruce (Picea sitchensis, n ) 6) were collected at 35 sites over 4 days in late March 1997 (Figure 1). Each sample was characterized by 26 variables describing geography, meteorology, ecotype, lipid content, proximity to recent forest fires, and region of the state (Supporting Information, Table S-1). Principal component analysis (PCA) (13) was used to classify the sites into five regions. At each site, duplicate samples of spruce needles, taken from 3 to 5 branches of two trees located 10-20 m from the edge of the road, were collected at approximately 1.5 m from the ground. The needles were stored at -10 °C. Sample Extraction and Cleanup. A frozen 10 g sample was ground to a powder and spiked with internal standards: acenaphthene-d10, phenanthrene-d10, chrysene- d12, and 2,4,5,6-tetrachloroxylene. The ground needles were Soxhlet extracted with 125 mL of hexane for 3 h, using a fill and drain time of 2 min. The volume of the initial extract was measured, and a 3 mL aliquot was used to determine lipid content (see below). The remainder of the extract was rotary evaporated to about 3 mL and further evaporated to approximately 1 mL under a gentle stream of nitrogen. The concentrate was chromatographed using 4 g of silica gel (40 µm particle size). The 20 mL of hexane and 20 mL of hexane/dichloromethane (1:1 v:v) fractions were combined, concentrated to approximately 0.3 mL under nitrogen, and transferred to an autosampler vial for analysis by gas chromatography with a mass selective detector (GC-MS). Water and Lipid Content. Water content of the needles was determined by measuring the weight loss of 10 g of needles heated to 55 °C for 24 h. The lipid content of the needles was determined by placing a 3 mL aliquot of the initial Soxhlet extract into a tared vial and letting the solvent evaporate at room temperature. The mass gain was considered the lipid content of the aliquot of needle extract, and this was used to calculate the lipid content for the entire sample. GC-MS Analysis. Sample extracts were analyzed on a Hewlett-Packard 5890 gas chromatograph with a 5972 mass selective detector. The separations were done with temperature programming, using a 30 m long × 0.25 mm i.d., 0.25 µm film thickness 5% phenyl column. A 1 µL portion was injected in splitless mode. The injection port and mass spectrometer transfer line temperatures were 300 °C. Each sample extract was analyzed twice, once for PAHs and once for HCB. Quantification was done using selected ion monitoring. Peak area for analytes and external standards were used to calculate concentration in the sample extract. Sample weights, water content, and recovery of internal standards were used to calculate concentration of analyte in the original spruce needles on a dry weight basis (Table 1). 10.1021/es034751n CCC: $27.50

 2004 American Chemical Society Published on Web 05/14/2004

FIGURE 1. Sample site locations. Rural interior sites are those not included in the four ovals. Quality Control Measures. Two trees at each sampling location were analyzed individually to estimate within-site variance. Duplicate analyses were made for each tree sampled to estimate overall analytical variance. A further 22 samples were augmented with known additions of analyte to determine percent recovery for the analysis procedure. For HCB, 20 of these had recovery in the range of 91-113%. For the six analyzed PAHs, average recovery varied from 92 to 98%, and 85% of the individual samples had recoveries in the range of 80-120%. The 8% of the samples that had recoveries of the internal standards outside of the range of 60-140% were excluded from data analysis. Extraction of needles was done in groups of six, and each group had a method blank. Data Analysis. PCA of the mean-centered and standardized sample descriptors was done to classify samples into five regions (Table 1, Figure 1). Coastal, Fairbanks, and Dalton Highway samples clustered well away from each other and the other groups. The Alaska Highway samples overlapped partially with the rural interior samples. Nonetheless, these samples were placed into two regions because of the geographic separation of the Alaska Highway samples in the far eastern part of the sampling area.

The duplicated analysis results from the two tree samples were averaged to give a single value for each analyte at each of the 35 sites. The data set, including descriptions of the sampling sites (X-variables) and the analyte concentrations (Y-variables), was analyzed by partial least squares (PLS) analysis (14). The X-variables were mean-centered and standardized. The logarithm of the PAH concentration or the logarithm of the PAH concentration normalized for lipid content of the needles was used as the response. Models made with untransformed and transformed data were similar. Fewer samples were flagged as outliers when the log transform was used, however. Models using HCB concentration, HCB concentration normalized for lipid content, and quotients of PAH concentrations were calculated with untransformed data. There was no observable advantage of making a log transform of these concentrations and concentration ratios, all of which covered a relatively small range of values. For all PLS analyses, significant X-variables were identified by “jack-knife” resampling (15). Analysis of variance (ANOVA) was done with log-transformed concentrations of PAHs. The transformation was done to homogenize the variances among samples. Pairwise multiple comparisons were evaluated using the Tukey test (16). The nonparametric Friedman rank order two factor VOL. 38, NO. 12, 2004 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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TABLE 1. Concentrations of PAHs and HCB (ng/g Dry Needle) in Spruce Needles sample

Phen Anth Fluor

ak1230 8.1 0.2 ak1260 59.7a 9.7a ak1301 35.0 2.1 ak1345 18.3 0.8 ak1384 8.3 0.5 r4 38.9 0.4a r16 30.5 1.4 r31 13.1 1.1 s8 41.7 3.3 s42 25.4 1.9 s75 20.0 2.6 dal13 22.7 0.8 dal50 23.8 0.9 dal87 34.4 1.0 dal122 17.8 0.8 dal160 29.7 1.4 dal193 11.5 1.2 ell9 23.4 1.3 ell47 59.5 1.0 gold 56.6 1.3 p270 48.1 1.3 r309 25.2 0.8 r339 89.0 1.8 ak1418 33.0 1.3 p67 36.3 2.9 p107 23.8 0.6 p147 28.1 1.6 p187 19.5 0.5 p214 7.9 0.6 p230 25.2 0.6 r72 18.6 0.5 r109 40.4 2.2 r166 20.7 0.4 r207 28.8 1.4 r277 15.5 0.7

1.6 18.0 10.3 7.7 4.0 8.9 6.6 5.8 17.0 8.7 9.6 5.0 4.9 8.0 1.0 8.8 4.8 10.2 10.0 43.7 10.7 9.2 53.0 9.3 17.8 7.1 8.6 6.8 3.8 9.5 4.0 12.6 3.4 14.0 9.5

Chry

HCB

region

4.4 1.2 13.5 10.4 mb m 8.4 2.2 15.5 13.4 1.0 7.5 4.7 1.5 8.6 6.3 m m 5.3 1.1 10.3 6.5 2.0 2.4 16.4 3.0 14.5 6.7 1.7 9.2 5.5 1.6 m 2.3 1.0 2.7 4.3 m m 17.2 0.9 7.1 8.9 0.8 46.2a 8.4 1.4 m 3.8 1.2 4.8 8.2 1.3 5.5 4.4 2.2 53.5 38.9 3.2 23.0 14.3 1.2 57.3 14.7 2.8 10.5 35.7 6.2a 46.5 7.8 1.2 12.7 15.8 2.0 10.0 5.9 1.3 22.2 10.4 2.4 10.2 8.7 1.0 8.4 6.6 1.4 7.4 9.5 1.5 5.2 4.3 0.9 10.5 3.8 2.3 10.7 8.7 0.9 m 14.0 1.3 m 15.1 1.7 17.5

Pyr

BaA

0.59 0.77 0.70 0.52 0.61 0.73 m 0.67 0.92 0.88 0.65 0.83 1.11 0.76 1.10 m 0.67 0.60 m 0.91 m 0.68 0.85 0.75 0.59 0.72 0.50 0.64 0.59 0.59 0.80 0.65 0.89 0.65 0.72

AK Hwy AK Hwy AK Hwy AK Hwy AK Hwy coastal coastal coastal coastal coastal coastal Dalton Dalton Dalton Dalton Dalton Dalton Fairbanks Fairbanks Fairbanks Fairbanks Fairbanks Fairbanks rural interior rural interior rural interior rural interior rural interior rural interior rural interior rural interior rural interior rural interior rural interior rural interior

a These values were excluded as outliers when calculating PLS models. b m values are missing due to quality control defects.

ANOVA (17) was done to compare quotients of PAH concentrations. A single factor, fixed effect ANOVA model was used for evaluation of untransformed HCB data.

Results and Discussion PAHs. Concentrations of PAHs in spruce needles in eastern Alaska are highly variable (Table 1). Many of the concentrations are as low as or lower than any others reported for PAHs in evergreen needles (18-21). The concentrations of phenanthrene, anthracene, fluoranthene, and benzo[a]anthracene are strongly correlated (Supporting Information, Table S-2). In contrast, the concentrations of chrysene and pyrene are only moderately or poorly correlated with the concentrations of the other PAHs, with the exception of the chrysene-phenanthrene pair. The concentrations of the PAHs, excluding anthracene, were significantly greater in samples from the Fairbanks region than in samples taken from any other region (Table 2). In addition, coastal samples had significantly higher concentrations than those from the Dalton Highway region.

Multivariate data analysis identifies structure in the data set in addition to regional differences. PLS analysis shows three additional factors that are correlated with the concentration of fluoranthene (Table 3, Supporting Information Figure S-1). The concentration was highest in samples near recent forest fires and lowest at high elevations and far from the city of Fairbanks (Figure 2). Models made with the phenanthrene, benzo[a]anthracene, and pyrene data were similar to the fluoranthene model (Table 3). Distance from Fairbanks, elevation, proximity to forest fire, Dalton Highway sample region, and Fairbanks sample region are significant variables that appear repeatedly. Models calculated using the concentration of these four PAHs normalized for lipid content of the needles were inferior to those calculated using just the concentration. The lipid-normalized models were viewed as inferior because they accounted for a smaller amount of variance, and they included lipid content as part of the model, with a negative regression coefficient. The model using chrysene concentration data differs from the models made for the other PAHs. The major factor contributing to the model is the lipid content of the spruce needles. The only other significant component of the model identifies Dalton Highway samples as having especially low concentrations. When the chrysene concentration is normalized for lipid content of the needles, the PLS model (Table 3) is similar to that for the previously discussed PAHs. High values are observed in the Fairbanks region and near forest fire locations, and low values are observed in the Dalton Highway region and at increasing distances from the city of Fairbanks. Taken together, these data indicate sources of fluoranthene, phenanthrene, benzo[a]anthracene, pyrene, and chrysene near the city of Fairbanks. These results are consistent with local activities that may produce PAHs from either combustion or petrogenic sources. Fairbanks is a major transportation center for northern Alaska, there are three coal-burning electrical generating plants near the city, many homeowners burn wood as a source of residential heat, and diesel-range fuel is produced at a refinery in the area. The role of forest fires is ambiguous, due to the high correlation between radial distance from Fairbanks and forest fires. The concentrations observed in samples taken along the Dalton Highway, a major truck route to the oil fields at Prudhoe Bay, are as low or lower than samples taken in other regions. The PLS model for anthracene differs significantly from those calculated for the other five PAHs. The model is dominated by factors that distinguish the six coastal samples, which have high concentrations of anthracene, from the noncoastal samples. Because neither “radial distance from Fairbanks” nor “Fairbanks region” is a significant factor in the model, Fairbanks does not appear to be a strong source for anthracene (Table 3). PAHs may have either combustion or petrogenic sources. It is possible to identify the relative importance of these sources by calculating a quotient of concentrations of isomeric PAHs which differ in stability (22-24). For the three quotients examined, petrogenic sources give a small quotient, while combustion sources give a large quotient. Consistent

TABLE 2. Average Concentrations (and Standard Deviation)a of PAHs and HCB in the Five Geographic Regions region

Phen

Anth

Fluor

Pyr

BaA

Chry

HCB

Fairbanks coastal rural interior Alaska Highway Dalton Highway

50 (24) 28 (11) 25 (9) 17 (13) 23 (8)

1.2 (0.3) 2.1 (0.9) 1.1 (0.8) 0.9 (0.8) 1.0 (0.2)

23 (20) 9 (4) 9 (5) 8 (6) 5.4 (2.8)

19 (14) 8 (4) 9 (4) 8 (4) 7 (5)

2.1 (0.8) 1.9 (0.7) 1.5 (0.5) 1.5 (0.5) 1.1 (0.2)

33 (23) 9 (5) 11 (5) 11 (4) 5 (2)

0.8 (0.1) 0.8 (0.1) 0.7 (0.1) 0.6 (0.1) 0.9 (0.2)

a Values are the concentration in ng/g dry weight (and standard deviation of concentration). Values excluded in Table 1 as PLS outliers were also excluded in calculating means and standard deviations.

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TABLE 3. Summary of PLS Models (-) significant factorsa

Y-variable

(+) significant factorsa

Radial Distance Fbxb,c, Dalton, Elevation Radial Distance Fbx, , Elevation , Dalton, , c, Latitude, Black Spruce Log Pyr , , LATABS Log Chry Dalton, Log (Chry/Lipid) Radial Distance Fbx, Dalton, LATABS Log Anth Elevation, Radial Distance Anc, Upland, Interior HCB Temperature, Fairbanks Vector HCB/lipid Latitude, Black Spruce

Log Fluor Log Phen Log BaA

Fire, Fairbanks, 〈Coast〉d Fire, Fairbanks, Lipid, Bottomland Fire, Fairbanks Lipid, Bottomland Fire, Fairbanks, Fairbanks Vector, Coast, LATABS, Precipitation, Temperature, Sitka Spruce Lipid, LATABS, Latitude, Dalton

a (+) concentration is positively correlated with the level of the variable; (-) concentration is negatively correlated with the level of the variable. Variables in bold are significant repeatedly in PAH models. c Distance from the center of the cities of Fairbanks or Anchorage. d Factors in are significant at the 90% probability level. Others are significant at the 95% level. b

FIGURE 2. Logarithm of fluoranthene concentration as a function of distance from the city of Fairbanks. Legend: regression line: y ) -0.0019x + 1.23 (R2 ) 0.29, standard error of slope ) 0.0007).

FIGURE 3. Anthracene/(anthracene + phenanthrene) as a function of distance from the city of Fairbanks. Legend: regression line: y ) 9.5 × 10-5x + 0.024 (R2 ) 0.30, standard error of slope ) 3.4 × 10-5).

TABLE 4. Average (and Standard Deviations) of the PAH Concentration Quotients in the Five Geographic Regions AK Hwy Anth/(Anth + Phen)a Fluor/(Fluor + Pyr)b BaA/(BaA + Chry)

coastal

Dalton

0.045 0.077 0.047 (0.015) (0.026) (0.023) 0.41 0.56 0.52 (0.12) (0.06) (0.13) 0.12 0.22 0.15 (0.03) (0.16) (0.11)

rural Fairbanks interior 0.028 (0.014) 0.48 (0.17) 0.12 (0.08)

0.042 (0.019) 0.46 (0.08) 0.13 (0.06)

a The two values not included in the PLS model were excluded from averages. b The three values not included in the PLS model were excluded from averages.

between-region differences are observed for these three quotients (Table 4). The quotients for the coastal samples are significantly larger than those for Fairbanks, rural interior, and Alaska Highway samples. Therefore, the relative combustion contribution is larger in coastal samples than in samples from the three regions with lower quotients. The relatively high combustion contribution (or relatively low petrogenic contribution) may explain why the model for anthracene differs from the models for the other PAHs. When the quotient anthracene/(anthracene + phenanthrene) is used as the response, and the six coastal samples are excluded, a strong PLS model with two active variables emerges: Fairbanks region and radial distance from the city of Fairbanks. The quotient is lowest in the Fairbanks region, and it increases with increased distance from the city of Fairbanks (Figure 3). Thus, the relative importance of petrogenic sources decreases with increased distance from the urban center. HCB. The concentrations of HCB (Table 1) and the relatively homogeneous distribution of concentrations are comparable to measurements made by others in evergreen needles, primarily in Europe (5, 10, 19, 25, 26). Analysis of the data by region (Table 2) shows that the average concentration observed at Dalton Highway sites is 50%

FIGURE 4. a. HCB concentration as a function of latitude. Legend: ) samples south of 63.5°, regression line: y ) -0.06x + 4.4 (R2 ) 0.28, standard error of slope ) 0.024) O samples north of 63.5°, regression line: y ) 0.13x - 7.9 (R2 ) 0.52, standard error of slope ) 0.04). b. HCB concentration/lipid content as a function of latitude (ordinate values are 1000 * concentration HCB (ng/g)/lipid content (mg/10 g sample). greater than the averages observed at the Alaska Highway sites. There is strong latitudinal variation in the concentration of HCB in spruce needles. Good models result when either HCB concentration or HCB concentration adjusted for lipid content of the needles is used as the response. The crest of the Alaska Range at approximately 63.5° N latitude enters strongly into the models. When a PLS model is calculated using the concentration of HCB as the response, the lipid content of the spruce needles and variables related to latitude are significant factors (Table 3). There is a strong positive correlation between HCB concentration and lipid content. VOL. 38, NO. 12, 2004 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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In addition, the concentration of HCB varies systematically with latitude, with samples at intermediate latitude having the lowest concentrations (Figure 4a). When a model is calculated using the lipid normalized concentration of HCB, latitude dominates the model (Table 3). Values are highest at low latitude and decrease regularly at higher latitude (Figure 4b). The common thread in both models is that the concentration of HCB and the lipid normalized concentration of HCB both decrease strongly from the coast northward to the crest of the Alaska Range. This trend is consistent with models that predict the removal of an appreciable fraction of POPs from the atmosphere by vegetation (6, 8, 27). Given the gradient of lipid normalized concentration away from the coast, the major source of HCB appears to be long distance transport.

Acknowledgments Forest fire data were supplied by Mary Lynch, U.S. Bureau of Land Management, Fairbanks.

Supporting Information Available Tables with the sample site descriptions and Spearman rank order correlations of PAH concentrations and a figure of PLS loading weights for the log concentration fluoranthene model. This material is available free of charge via the Internet at http://pubs.acs.org.

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Received for review July 11, 2003. Revised manuscript received March 11, 2004. Accepted March 23, 2004. ES034751N