Elevated Levels of Polychlorinated Biphenyls in Plants, Air, and Soils

Mar 14, 2014 - Elevated Levels of Polychlorinated Biphenyls in Plants, Air, and Soils at an E‑Waste Site in Southern China and Enantioselective...
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Elevated Levels of Polychlorinated Biphenyls in Plants, Air, and Soils at an E‑Waste Site in Southern China and Enantioselective Biotransformation of Chiral PCBs in Plants She-Jun Chen,† Mi Tian,†,‡ Jing Zheng,§ Zhi-Cheng Zhu,†,‡ Yong Luo,∥ Xiao-Jun Luo,† and Bi-Xian Mai*,† †

State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China ‡ University of Chinese Academy of Sciences, Beijing 100049, China § Center for Environmental Health Research, South China Institute of Environmental Sciences, Ministry of Environmental Protection, Guangzhou 510655, China ∥ Guangdong Forestry Survey and Planning Institute, Guangzhou 510520, China S Supporting Information *

ABSTRACT: E-waste that contains polychlorinated biphenyls (PCBs) is moved across national boundaries, often from industrialized countries in the northern hemisphere, where the items were formerly used, to subtropical and tropical regions in southeastern Asia and Africa. As a result, there is a high likelihood that PCBs will be released into the environment from a primary source due to the elevated temperatures encountered in these lowlatitude regions. In the present study, PCBs and enantiomer fractions (EFs) of chiral PCBs (PCB 84, 95, 132, 136, 149, and 183) were analyzed in air, eucalyptus leaves, pine needles, and soil at an ewaste site and a rural site in southern China. The concentrations of PCBs at the e-waste site ranged from 7825 to 76330 pg/m3, 27.5 to 1993 ng/g, and 24.2 to 12045 ng/g in the air (gas plus particle), plant leaves, and soils, respectively. The atmospheric PCB composition profiles in the present study indicated relatively high abundances of penta- and hexa-PCBs, which were different from those previously observed in the air across China. The Clausius−Clapeyron regression analysis indicated that evaporation from local contaminated surfaces constitutes a primary emission source of PCBs in the air at the e-waste site. The chiral signatures of PCBs in the air at the e-waste site were essentially racemic (mean EFs = (0.484 ± 0.022)−(0.499 ± 0.004) in the gaseous phase) except for PCB 84 (0.420 ± 0.050), indicating that racemic sources dominate the PCB emission in the air. PCB chiral signatures in the soils ((0.422 ± 0.038)−(0.515 ± 0.016)) were similar to those in the air except for PCB 95. However, the chiral PCBs in the plants (especially the eucalyptus leaves) had significantly nonracemic residues ((0.368 ± 0.075)−(0.561 ± 0.045)) compared to those in the air and soil. This finding suggests that enantioselective biotransformation of these atropisomeric PCBs was very likely to occur in the plant leaves, possibly due to metabolism by cytochrome P-450 enzymes in leaves. To our knowledge, this is the first report on the enantioselective metabolism of chiral PCBs in plants under field conditions.

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INTRODUCTION

important secondary source of PCBs released into the atmosphere.6,7 PCBs were manufactured and used primarily in developed countries in the northern hemisphere. Nevertheless, the trans-boundary movement of electronic and electric waste (e-waste) from developed countries to developing regions and the primitive and unsafe recycling or disposal of e-waste in these regions in recent years have received increased

Polychlorinated biphenyls (PCBs) are a well-known class of manmade organic chemicals formerly used in a variety of industrial and commercial applications, including transformers, capacitors, and plasticizers.1 Although these chemicals have been banned for some decades, they are still of great concern because they continue to be detected in the environment, wildlife, and humans and because they are highly persistent and known to cause numerous harmful health effects.2 Recent research in North America and Europe has indicated that buildings, paints, and old appliances remain significant sources of PCBs,3−5 while contaminated soil and water represent an © 2014 American Chemical Society

Received: Revised: Accepted: Published: 3847

December 18, 2013 February 26, 2014 March 4, 2014 March 14, 2014 dx.doi.org/10.1021/es405632v | Environ. Sci. Technol. 2014, 48, 3847−3855

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attention.8 This movement has made these e-waste sites a potentially substantial inventory and emission source of PCBs. Consequently, in contrast to the significant decline of PCB levels in the atmosphere in North America and Europe,9,10 high environmental levels and elevated human body loading of these chemicals have been reported in some of the low-latitude regions of Africa and Asia.8,11 The warm climate in these lowlatitude regions increases the volatilization of PCBs from both primary (e-waste) and secondary (such as contaminated soils) sources,8 and it may lead to enhanced interface exchange of PCBs between environmental media and a potential for biotransformation. However, the environmental processes, fate, and impact of PCBs in warm regions are poorly understood. Vegetation is a key factor influencing the transport, cycling, and elimination of semivolatile organic compounds (SOCs) in the environment.12 In the past few decades, the air−vegetation exchange and plant−soil interaction of a variety of SOCs have attracted a considerable amount of research interest.13 In addition to the uptake inside plant tissues, plant metabolism of xenobiotic substances also plays an important role in the cleanup of environmental pollutants. PCB attenuation has been observed in soils planted with a variety of plants due to microbial degradation in the rhizosphere.14 Laboratory experiments showed that PCB congeners could be metabolized by plant cell cultures.15,16 Oxidation of PCBs to form various hydroxylated metabolites constitutes a major portion of the metabolism mechanisms that have been discovered.17 Additionally, studies have suggested that cytochrome P-450 (CYP450) enzymes, which are commonly found in animals, plants, insects, and micro-organisms, are involved in PCB transformation in plants.18 This implies that enantioselective metabolism of atropisomeric PCBs may occur in plant tissues due to the unique chirality of the enzyme’s active site. The enantiomeric composition of a chiral compound is only modified by biological transformation processes.19 There has been extensive proof of biotransformation of chiral PCBs due to CYP-450 enzymes in mammals.20,21 To date, however, there is little available information (from either laboratory experiments or field studies) on the enantioselective metabolism of organic compounds in plants.22 In the present study, we measured the concentrations of PCBs in the air, plants (eucalyptus leaves and pine needles), and soil at an e-waste site and a rural site in southern China. The enantiomer fractions (EFs) of several atropisomeric PCBs (PCB 84, 95, 132, 136, 149, and 183) in these environmental compartments were determined and compared to understand enantioselective biotransformation in plants in the natural environment. The emission sources of PCBs into the air at both of the sites were also elucidated.

site were collected simultaneously using a high-volume air sampler from July 2007 to June 2008. Plant samples (n = 30 for each species), namely eucalyptus (Eucalyptus spp.) and masson pine (Pinus massoniana Lamb.), which are distributed extensively throughout the study area, were obtained in each air sampling session (except for December 2007 and May 2008). The leaf samples were taken from four to six trees (>2 m above ground level) at the beginning, middle, and end of each sampling session. Surface soil samples (0−5 cm) from farmland and unplanted land at the e-waste site and from farmland at the rural site were collected using a stainless-steel soil corer. Each of the soil samples was a combination of four or five subsamples randomly collected within an area of 100 m2. In addition, plant roots (n = 3 for each species) and associated rhizosphere soils were also collected. Sample Preparation and Instrumental Analysis. Air [polyurethane foam (PUF) plug and filter] and soil samples spiked with surrogates were Soxhlet extracted. The extracted samples were purified further using a multilayer alumina/silica column and then spiked with a known amount of internal standard before the instrument analysis was performed. Leaf samples were rinsed with purified water to remove surface particles, and then ground with anhydrous sodium sulfate prior to Soxhlet extraction. The plant extract was mixed with 60 mL concentrated sulfuric acid to remove lipids, and then liquid− liquid-extracted with hexane using a Teflon separatory funnel. The hexane extracts were then purified through a multilayer alumina/silica column. More details on the sample preparation are available in the Supporting Information. PCBs were quantified using an Agilent 6890 gas chromatograph coupled to a 5975B mass spectrometer with an electronimpact (EI) ion source (GC−EI-MS). A DB-5 MS (60 m × 0.25 mm i.d., 0.25 μm film thickness) capillary column was employed for separation. Enantiomer analysis was conducted using the above-mentioned Agilent GC-EI-MS. The enantiomers of atropisomeric PCBs were separated on a ChiraSilDex column (25 m × 0.25 mm ×0.25 μm) for PCB 95, 136, and 149 and on a BGB 172 column (30 m × 0.25 mm ×0.18 μm) for PCB 84, 132, and 183 (Figure S2, Supporting Information). Quality Control. Field blanks [PUF plugs and glass fiber filters (GFFs)] were prepared, and procedural blanks were run with each bath of the field samples to assess blank levels. Several PCBs (PCB 11, 26, 33, 37, 40, 71, 76, 103, 111, 128, 170, 175, 190, and 209) were found in the procedural and field blanks; however, their quantities were less than 5% of those in the field sample extracts, in most cases. The concentrations in the samples were blank-corrected. The recoveries of the surrogate standards (PCB 30, 65, and 204), were 76.9 ± 17.5%, 91.0 ± 15.5%, and 129 ± 32.7% for air samples and 91.1 ± 26.8%, 88.7 ± 24.8%, and 112 ± 32.9% for plant samples, respectively. The recoveries of 24 analytes in the spiked matrices were 70.1%−139% (standard deviations < 12.7%). The repeatability, evaluated by analyzing three plant sample replicates, had relative standard deviations within 0.34−19.7%. Reported concentrations were not surrogate-recovery-corrected. The method-detection limits, defined as a signal five times the noise level, varied between 0.01 and 0.04 ng/g dry weight for plant leaves and between 0.04 and 0.15 pg/m3 for air. Determination of EFs. Enantiomer composition (or chiral signature) was described by the EF, which is defined as the peak area of the first-eluting enantiomer divided by the sum of

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MATERIALS AND METHODS Sample Collection. Detailed information on the study sites and the sampling technology is provided in the Supporting Information. Air, leaves, and soil samples were collected from an e-waste site and a rural site in Qingyuan, southern China (Figure S1, Supporting Information). This site is one of the three largest e-waste dumping and recycling sites in China. Every year, approximately 700,000 tons of e-waste is processed using environmentally unsound techniques.23 The rural site is located in an agricultural base (approximately 25 km from the e-waste site) and has no e-waste recycling or industrial activities. Air samples (gas and particles, n = 60) from each 3848

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a

3849

range

n.d.−8.25 10.5−171 1.50−116 6.79−211 5.02−151 0.07−78.8 n.d.−31.1 n.d.−16.2 n.d.−1.56 25.4−775

1.50/0.50 44.1/33.7 22.1/13.9 54.7/32.6 45.6/35.3 11.5/2.73 5.23/2.82 2.00/0.04 0.47/0.25 187/138

range 0.45−12.5 5.91−331 3.46−37.5 7.02−59.3 4.98−50.8 0.26−14.0 n.d.−6.01 n.d.−2.23 n.d.−1.11 27.1−191

range

3.99/3.60 60.4/30.4 15.1/9.64 30.0/27.8 15.7/8.07 4.38/2.71 1.85/0.95 0.53/0.31 0.45/0.34 105/87.5

mean/median

460/110 962/714.5 491/297 203/99.7 67.0/56.5 17.8/11.9 0.17/n.d. 3.39/n.d. 6.94/6.40 2210/2113

mean/median

17.3/4.77 85.0/26.4 145/40.1 228/78.8 168/55.9 88.5/11.9 16.3/3.17 2.51/0.81 0.54/0.37 750/213

mean/median

farmland soil 0.69−170 2.69−615 2.9−1149 6.01−1145 4.30−652 1.44−1189 0.98−198 0.28−22.3 n.d.−2.33 24.2−3552

range

particle + gas 47.4−2711 118−2845 37.7−1782 5.54−857 11.1−152 3.35−53.1 n.d.−1.60 n.d.−28.5 0.93−11.0 271−4655

range

1876/1573 8652/8476 7146/5255 5205/3394 2075/1434 372/233 121/53.3 110/84.3 56.5/34.3 25612/20896 rural site

mean/median

particle + gas 642−5275 2431−21231 1837−23412 671−21661 190−6975 37.1−979 n.d.−383 2.83−531 8.91−160 7825−76330

pine needle

25.8/12.6 190/147 146/94.3 198/148 96.2/78.0 25.3/19.1 11.1/7.82 4.95/3.14 3.13/1.94 670/478

mean/median

pine needle 1.98−89.2 6.39−526 6.61−445 10.3−505 4.87−298 0.89−74.6 n.d.−35.0 n.d.−20.0 n.d.−12.9 27.5−1993

range

mean/median

eucalyptus leaf

4.51/2.55 75.5/35.0 56.5/54.8 179/124 72.7/59.9 22.9/16.8 5.55/5.40 2.66/1.85 1.21/1.07 369/377

mean/median

eucalyptus leaf

0.29−12.9 16.7−402 12.9−97.7 30.7−751 5.05−172 5.34−63.0 1.41−11.4 n.d.a−8.85 n.d.−2.71 88.0−635

Not detectable.

di-CBs tri-CBs tetra-CBs penta-CBs hexa-CBs hepta-CBs octa-CBs nona-CBs deca-CBs ∑PCBs

di-CBs tri-CBs tetra-CBs penta-CBs hexa-CBs hepta-CBs octa-CBs nona-CBs deca-CBs ∑PCBs

range

E-waste site

range 0.36−0.89 1.84−4.07 0.43−3.69 1.09−2.13 0.64−1.00 0.13−0.43 n.d.−0.25 n.d.−0.12 0.04−0.07 4.94−12.3

0.62/0.60 2.93/2.88 1.61/1.31 1.77/1.84 0.85/0.89 0.27/0.25 0.07/0.04 0.03/0.01 0.05/0.04 8.22/8.15

mean/median

farmland soil

106/46.1 603/283 972/390 891/619 657/357 310/153 232/110 88.4/24.9 26.5/8.55 3886/2130

mean/median

bare land soil 5.36−499 15.7−2120 20.5−4047 16.2−2935 12.6−2015 5.67−1762 3.30−1345 1.39−432 0.50−124 81.3−12045

range

Table 1. Summary of Concentrations of PCBs in Air (pg/m3), Soils (ng/g dw), Eucalyptus Leaves, and Pine Needles (ng/g dw) from E-Waste and Rural Sites in South China

Environmental Science & Technology Article

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Figure 1. Box plots of EFs of chiral PCB 84, 95, 132, 136, 149, and 183 in the air, eucalyptus leaves, pine needles, farmland, and bare land soil at the e-waste site. The dashed lines indicate a racemic EF of 0.5.

phases) at the e-waste site ranged from 7825 to 76330 pg/m3 (averaged 25612 pg/m3), which is 12 times higher than those measured at the rural site (271−4655 pg/m3, averaged 2210 pg/m3). The levels in the present study were much higher than the recently reported PCB concentrations in urban (averaged 350 pg/m3) and rural (230 pg/m3) air across China.26 The PCB levels were also higher than those in the air of Taizhou (another large e-waste dismantling site in China), with an average of 12400 pg/m3, and those in the ambient air previously measured at superfund sites in the United States (with average concentrations of 270−4900 pg/m3).27−29 This indicates that primitive e-waste dismantling may represent a significant emission source of PCBs in the atmosphere in regions that receive e-waste. The PCB homologue compositions at the e-waste and rural sites were substantially similar. They were dominated by tri-, tetra-, penta-, di-, and hexa-PCBs (Figure S3, Supporting Information), demonstrating a strong influence of an e-waste source on the rural site. This atmospheric PCB profile (Figure S4, Supporting Information) was shifted toward higher molecular weight (HMW) congeners (penta- and hexa-PCBs)

the peak areas of both enantiomers on the enantioselective chromatographic column.24 The first eluting enantiomer is (−) enantiomers for PCB 84, 132, 136, and 149, while the (+) or (−) forms of the enantiomers are not identified for PCB 95 and 183. The enantiomer analysis was validated by a racemic daily checking standard (Aroclor mixture), and the mean EFs (n = 30) varied from 0.499 ± 0.001 to 0.500 ± 0.001 for all compounds. A conservative measure of EF precision of 0.032 (the 95% confidence interval) was used for statistical comparisons of sample and standard EFs.25 Statistics. A one-way ANOVA or t-test was used to analyze the significant differences between data groups (significance level α = 0.05). The statistical analysis was performed using the statistical package SPSS 16.0 (SPSS, Inc.).

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RESULTS AND DISCUSSION Concentrations, Compositions, and Emission Sources. The concentrations of di- to deca-PCBs (171 congeners) in the air, eucalyptus leaves, pine needles, and top soil at the e-waste and rural sites are summarized in Table 1. The total concentrations of these PCBs in the air (gas and particle 3850

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PCBs were essentially racemic or near-racemic (mean EFs ranged from 0.484 ± 0.022 to 0.499 ± 0.004 in the gaseous phase and from 0.476 ± 0.013 to 0.497 ± 0.006 in the particles), except for PCB 84, which was enriched with the second eluting enantiomer, with EFs of 0.420 ± 0.050 in the gaseous phase and 0.456 ± 0.038 in the particle phase. Nonracemic EFs for PCB 132 (0.484 ± 0.022) were also observed in a number of gaseous samples. This finding indicates that racemic sources dominate the emission of PCBs in the atmosphere of the e-waste area. As mentioned above, two main categories of emission sources (emission during e-waste recycling and weathering and evaporation from the contaminated surfaces) are responsible for the occurrence of PCBs in the atmosphere at the e-waste site. These two sources are naturally racemic or near-racemic. The PCB chiral signatures in the soil showed near-racemic chiral signatures (mean EFs = (0.475 ± 0.019)−(0.515 ± 0.016)), except for PCB 84, which clearly shifted from racemic (EF = 0.432 ± 0.063). These results are similar to those in the air (p > 0.059), except for PCB 95 (p < 0.001). We also found greater deviations from racemic in the farmland soil than in the bare land soil, in agreement with the larger microbial biomass in farmland soil than in bare land.36 This finding also suggests the occurrence of enantioselective aerobic degradation of these congeners in the soil. PCB EFs in soil have been measured in a variety of locations around the world.37−42 Scatter plots of PCB EFs and concentrations in soils reported in the literature and in the present study are shown in Figure S7 (Supporting Information). The soil PCB concentrations in the present study were higher than those from other locations, but the EFs were generally more racemic than others. This finding is consistent with previous observation that nonracemic EFs appeared to be increasingly probable in soil with relatively low PCB concentrations.40 Nevertheless, a more likely explanation is that the EFs in the literature were mostly from developed countries where previously used PCBs have stayed in the soil for decades, while a significant proportion of the PCBs in the soils in the present study was newly released. The concentration alone may have a small influence on the degree of enantioselective degradation of PCBs in soil. It is worthwhile to note that unlike the similarity in the EFs between soil and air in the present study, the EFs of PCB 95, 136, and 149 in soils in the UK’s West Midlands all deviated more from the racemic than those in the air.41 The work from this group found that PCBs volatilizing from urban background soil exert a discernible influence only at the soil−air interface (around 3 cm).38 However, volatilization from highly contaminated soil such as that at this e-waste site may play an important role in the EFs of airborne PCBs. However, despite the similarity of the air and soil EFs, we cannot rule out the possibility that other significant nonracemic sources may be present in the air in this area. In contrast to those in the air, all chiral PCB congeners measured in the eucalyptus leaves had significantly nonracemic residues, with mean EFs ranging from 0.414 ± 0.051 to 0.561 ± 0.045. The eucalyptus leaves were enriched with the firsteluting enantiomers for PCB 95, 136, and 149 and with the second-eluting enantiomer for PCB 84, but the EFs of PCB 132 and 183 varied in both directions. It has been evidenced that gaseous uptake from ambient air is responsible for the SOCs in foliage.43,44 However, we observed significant differences (p < 0.001) in the EFs of PCB 95, 136, and 149 between the

compared to those in the air across China, but it showed a greater proportion of lower molecular weight congeners than those observed in the urban air in Europe and North America.26 This result implies that the e-waste at this site may have various origins, both foreign and domestic. Conversely, the manners in which PCBs were released into the environment (probably a combination of emission from obsolete electrical equipment, volatilization from contaminated surfaces, and incineration of ewaste at the e-waste site), and the sampling techniques (e.g., passive vs active air sampling) and/or the numbers of congeners included in different studies could also influence the PCB composition profiles. Ambient temperature is a key factor influencing the air concentrations of SOCs.30 The Clausius−Clapeyron (C−C) equation (ln P = m/T + b), in which air SOC concentrations expressed as partial pressure are plotted against reciprocal temperature, has been used to indicate the sources of SOCs in the air (evaporation from local surfaces vs advection of air masses). A steeper slope and significant temperature dependence indicate air concentrations controlled by evaporation from surfaces. 30−32 The C−C plot (Figure S5, Supporting Information) suggests that temperature-driven evaporation from local contaminated environmental compartments (such as soil, water, vegetation, and recycled e-waste residues stacked in the fields) is an important factor controlling the air concentrations of PCBs at the e-waste site in warmer seasons. In winter, emission during e-waste recycling (during activities such as shredding and burning) may be the major source of PCBs in the air. At the rural site, in contrast, only a small part of the variations in concentrations can be explained by temperature (Figure S6, Supporting Information). PCBs in the air at this site are largely due to regional atmospheric transport. This finding was in good agreement with the result for brominated flame retardants in this region.32 The concentrations of PCBs in the plants at the e-waste site ranged from 88.0 to 635 ng/g and from 27.5 to 1993 ng/g, with average concentrations of 369 and 670 ng/g in eucalyptus leaves and pine needles, respectively. The average concentrations were only approximately two and six times higher than those at the rural sites. There was no significant difference in the PCB concentrations between the two species (p > 0.800), although interspecies differences in the leaf lipid content and the specific area have been observed.33 The plant PCB compositions were similar between the two species, but they were somewhat different between the two sites, with a greater accumulation of high molecular weight congeners compared to the air (Figure S2, Supporting Information). The soil PCB concentrations at the e-waste site were 81.3− 12045 ng/g (averaged 3886 ng/g) in the bare land soils and 24.2−3552 ng/g (averaged 750 ng/g) in the farmland soils, which is much higher than those in the farmland soils at the rural site (4.94−12.3 ng/g, averaged 8.22 ng/g). The profiles of PCBs in the soils were generally similar to those in the plants (Figure S2, Supporting Information). This result supports the transfer of PCBs among the air, soil, and plant leaves in the studied area because the partition processes were dominantly dependent on the organic matter content of soil particles or leaves and the physicochemical properties of PCBs.34,35 PCB Chiral Signatures at the e-Waste Site. The concentrations of PCB 84, 95, 132/153, 136, 149, and 183 in the air, plants, and soil are summarized in Table S1 (Supporting Information). The EFs are shown in both Figure 1 and Table S2 (Supporting Information). In the air, the chiral signatures of 3851

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Figure 2. Box plots and vertical point plots (circles) of EFs of chiral PCB 84, 95, 132, 136, and 149 in the air, eucalyptus leaves, pine needles, and farmland soil at the rural site. The horizontal line across each panel indicates a racemic EF of 0.5. The enantiomers of PCB 183 were not detected in eucalyptus leaves.

Borlakoglu and John (1989) found that PCBs can increase significantly microsomal protein concentrations and CYP-450linked enzyme activities in plant tissues, although the microsomal protein concentrations were much lower than those in the rat livers.46 The PCB EFs in the eucalyptus leaves and pine needles provided evidence for the enantioselective biotransformation in these species. The degrees of deviation from racemic for the four PCBs decreased in order of PCB 84 (0.414 ± 0.051) > 95 (0.561 ± 0.045) > 136 (0.539 ± 0.040) > 149 (0.527 ± 0.031) > 183 (0.494 ± 0.023) in the eucalyptus leaves. This observation was generally in agreement with the rates of metabolism of PCBs by P450 isoenzymes found by Borlakoglu et al., which decrease with increasing molecular mass and with an increasing number of meta−para hydrogen atoms.47 Specifically, PCB 84, with the same hydrogen atoms in two meta−para positions and molecular masses as PCB 95, showed a similar deviation from racemic to PCB 95. PCB 136 with higher molecular masses and PCB 149 with hydrogen atoms only in one meta−para position deviated less from racemic. PCB 183, having the highest molecular weight and no

eucalyptus leaves and air. These disparities were probably not caused by the uptake of eucalyptus leaves from the atmosphere because SOCs are believed to enter plant foliage primarily via sorption into the cuticle or transfer through stomata,12 both of which are physicochemical processes that would not change the enantiomer compositions. This finding indicated that enantioselective biotransformation of these PCB congeners was very likely to occur in eucalyptus leaves in the studied area. There were no significant differences in the chiral signatures of PCB 84, 132, and 183 (p > 0.317) between the eucalyptus leaves and air, which may be due to the lower rate of enantioselective metabolism (e.g., for PCB 183) in eucalyptus leaves or faster air−plant exchange (e.g., for PCB 84). Nonracemic chiral signatures were also observed in the pine needles, although the EFs (from 0.368 ± 0.075 to 0.509 ± 0.068) deviated less from racemic for most PCBs compared to those in the eucalyptus leaves. It has been reported that the metabolism of xenobiotics in plants resembles that of a mammalian liver,45 possibly as a result of enantioselective interaction with CYP-450 enzymes. 3852

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0.022−0.499 ± 0.004). The EFs in the plants exhibited larger (such as for PCB 95 in both species and for PCB 136 and 149 in eucalyptus leaves) or comparable deviations from racemic relative to those in the air. The EFs of many PCBs in the plants showed slightly larger deviations from racemic at the rural site than the e-waste site (Table S2, Supporting Information), but the differences were not significant (p > 0.057), except for PCB 132 in pine needles (p = 0.043). This observation likely implied that air−plant exchange may have a more important effect on the air EFs at the rural site than at the e-waste site because of the lower atmospheric PCB level. PCB 84, 95, and 132 were measured in the farm soils around the rural site, with mean EFs of 0.465 ± 0.049, 0.483 ± 0.021, and 0.490 ± 0.033, respectively. The EFs in the soil were not significantly different from those in the air (p > 0.108) as well as from the EFs in the soils at the e-waste site (p > 0.209). This finding implies that the overall source of PCB to the air at the rural site is more nonracemic than the e-waste site. Atmospheric transport from the e-waste site and exchange with local plants and soil constitute the primary source of atmospheric PCBs at this rural site. The less substantial emission of fresh racemic PCBs at the rural site is likely responsible for the greater deviations from racemic in the air. The differences in the enantioselective biotransformation of PCBs in eucalyptus leaves between the e-waste and rural sites were likely small, as indicated by the EF directions. However, it is not clear why pine needles at the rural site were mostly enriched with second eluting enantiomers of PCB 132, while at the e-waste site enrichment with both enantiomers was observed. Considering the high forest coverage rate (∼68%) in the studied area, vegetation may represent a considerable nonracemic source of chiral PCBs in the air via air−plant exchange and in the soil via defoliation. This influence would be appreciable in areas where there are no significant PCB emissions. However, precisely because of the interaction of PCBs among these media, an attempt to apportion the sources of the PCBs released from vegetation and soil into the air were impossible using the chiral signature technique. The results in the present study have implications for people’s preferential exposure to different PCB atropisomers, which show differential toxicity,19 via vegetable and grain consumption compared to people in a non-e-waste region. In addition, our findings indicate that there are interspecies differences in the metabolizing of PCB atropisomers, for which the mechanisms are unknown. Therefore, further research on the metabolic mechanisms of enantioselective transformation of PCBs in plant tissues, as well as on the potential health risk of exposure to different PCB atropisomers, is encouraged.

hydrogen atom in the meta−para position, displayed the lowest deviation from racemic of these PCBs. Interestingly, Warner et al. recently observed enantioselective metabolism of all the chiral PCBs in vitro by CYP-450 enzymes except for PCB 183.20 The exception in the plant leaves was that PCB 132, which has one hydrogen atom in the meta−para position and a molecular weight equal to PCB 136, exhibited a large deviation from racemic and the EFs varied in both directions. An early study found that soils enriched with pine needles or eucalyptus leaves induced enhanced AROCLOR 1242 degradation, possibly because of the presence of terpenes, a class of organic compounds produced by a variety of plants.48 Singer et al. provided evidence for enantioselective biotransformation of PCBs by bacteria after induction by two terpenes in a growth medium.49 The authors concluded that the cosubstrate may induce an isoenzyme shifting the enantioselectivity of PCBs. The result also indicates that eucalyptus leaves may have a higher capability of enantioselectively metabolizing these atropisomeric PCBs than pine needles do. It is worth noting, however, that air−plant exchange processes may also have an important influence on the similarities and differences in the EFs between the air and leaves. For instance, a fast exchange rate will favor the equilibrium of EFs between the air and the plants. Our previous study indicated that pine needles are more prone to absorbing SOCs from gaseous deposition than eucalyptus leaves due to the larger specific leaf area of pine needles.33 The chiral signatures in the eucalyptus leaves and pine needles were unlikely affected via uptake from the soil by plant roots and subsequent translocation into the foliage. First, early studies have demonstrated that the contribution from the soil is negligible for SOCs in tree foliage with log KOW > 5.50 Second, the EFs in the plant roots and rhizosphere soils differed clearly from those in the leaves, especially for eucalyptus leaves (Figure S8, Supporting Information). A recent study conducted by Zhai et al.22 observed enantioselective metabolization of PCB 95 inside poplar that was exposed to hydroponic solutions. The poplar removed the first-eluting enantiomer of PCB 95, especially in the middle and bottom xylem, with final EFs of 0.307 ± 0.051 and 0.449 ± 0.012, respectively. This is opposite to the enantioselective preference inside the eucalyptus leaves in the present study (mean EF = 0.561 ± 0.045). The difference could be ascribed to differing metabolism mechanisms (e.g., interaction with different enzymes). PCB 136 remained nearly racemic in most parts of the poplars after the same exposure duration, suggesting that this congener is more difficult to be enantioselectively biotransformed than PCB95 in this species, whereas in our study enantioselectivity of PCB136 was also found in the plants. Nonracemic EFs of PCB 95 (average 0.468 and 0.484) were also observed in grass by Desborough and Harrad in their recent study, but biotransformation in grass was not thought likely on the weight of evidence.38 PCB Chiral Signatures at the Rural Site. The concentrations of these chiral congeners are given in Table S1 (Supporting Information). The EFs of the PCBs at the rural site are shown in Figure 2 and Table S2 (Supporting Information). Although significant differences in the EFs in the air (gaseous phase) between the two sites were observed only for PCB 132 and 149 (p < 0.013), it seems that the chiral signatures of these PCBs in the air at the rural site (with mean EFs between 0.445 ± 0.063 and 0.501 ± 0.006) were more nonracemic compared to those at the e-waste site (0.484 ±

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ASSOCIATED CONTENT

S Supporting Information *

Detailed sample collection, chemicals, sample preparation, instrumental analysis, and additional figures and tables. This material is available free of charge via the Internet at http:// pubs.acs.org.

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Corresponding Author

*Phone: +86-20-85290146. Fax: +86-20-852907 06. E-mail: [email protected]. 3853

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Notes

(18) Singer, A. C.; Crowley, D. E.; Thompson, I. P. Secondary plant metabolites in phytoremediation and biotransformation. Trends Biotechnol. 2003, 21, 123−130. (19) Lehmler, H. J.; Harrad, S. J.; Huhnerfuss, H.; Kania-Korwel, I.; Lee, C. M.; Lu, Z.; Wong, C. S. Chiral polychlorinated biphenyl transport, metabolism, and distribution: A review. Environ. Sci. Technol. 2010, 44, 2757−2766. (20) Warner, N. A.; Martin, J. W.; Wong, C. S. Chiral polychlorinated biphenyls are biotransformed enantioselectively by mammalian cytochrome P-450 isozymes to form hydroxylated metabolites. Environ. Sci. Technol. 2009, 43, 114−121. (21) Wu, X. A.; Pramanik, A.; Duffel, M. W.; Hrycay, E. G.; Bandiera, S. M.; Lehmler, H. J.; Kania-Korwel, I. 2,2′,3,3′,6,6′-Hexachlorobiphenyl (PCB 136) is enantioselectively oxidized to hydroxylated metabolites by rat liver microsomes. Chem. Res. Toxicol. 2011, 24, 2249−2257. (22) Zhai, G. S.; Hu, D. F.; Lehmler, H. J.; Schnoor, J. L. Enantioselective biotransformation of chiral PCBs in whole poplar plants. Environ. Sci. Technol. 2011, 45, 2308−2316. (23) QYQCG (Qing Yuan Qing Cheng Government). Recycled copper from Qingyuan influencing the copper price in the world. http://www.qingcheng.gov.cn/info/3477 (accessed 2 September 2010). (24) Harner, T.; Wiberg, K.; Norstrom, R. Enantiomer fractions are preferred to enantiomer ratios for describing chiral signatures in environmental analysis. Environ. Sci. Technol. 2000, 34, 218−220. (25) Wong, C. S.; Mabury, S. A.; Whittle, D. M.; Backus, S. M.; Teixeira, C.; DeVault, D. S.; Bronte, C. R.; Muir, D. C. G. Organochlorine compounds in Lake Superior: Chiral polychlorinated biphenyls and biotransformation in the aquatic food web. Environ. Sci. Technol. 2004, 38, 84−92. (26) Zhang, Z.; Liu, L. Y.; Li, Y. F.; Wang, D. G.; Jia, H. L.; Harner, T.; Sverko, E.; Wan, X. N.; Xu, D. D.; Ren, N. Q.; Ma, J. M.; Pozo, K. Analysis of polychlorinated biphenyls in concurrently sampled Chinese air and surface soil. Environ. Sci. Technol. 2008, 42, 6514−6518. (27) Han, W. L.; Feng, J. L.; Gu, Z. P.; Wu, M. H.; Sheng, G. Y.; Fu, J. M. Polychlorinated biphenyls in the atmosphere of Taizhou, a major e-waste dismantling area in China. J. Environ. Sci. 2010, 22, 589−597. (28) Hermanson, M. H.; Hites, R. A. Long-term measurements of atmospheric polychlorinated-biphenyls in the vicinity of superfund dumps. Environ. Sci. Technol. 1989, 23, 1253−1258. (29) Vorhees, D. J.; Cullen, A. C.; Altshul, L. M. Exposure to polychlorinated biphenyls in residential indoor air and outdoor air near a Superfund site. Environ. Sci. Technol. 1997, 31, 3612−3618. (30) Hoff, R. M.; Brice, K. A.; Halsall, C. J. Nonlinearity in the slopes of Clausius-Clapeyron plots for SVOCs. Environ. Sci. Technol. 1998, 32, 1793−1798. (31) Wania, F.; Haugen, J. E.; Lei, Y. D.; Mackay, D. Temperature dependence of atmospheric concentrations of semivolatile organic compounds. Environ. Sci. Technol. 1998, 32, 1013−1021. (32) Tian, M.; Chen, S. J.; Wang, J.; Zheng, X. B.; Luo, X. J.; Mai, B. X. Brominated flame retardants in the atmosphere of e-waste and rural sites in southern China: Seasonal variation, temperature dependence, and gas-particle partitioning. Environ. Sci. Technol. 2011, 45, 8819− 8825. (33) Tian, M.; Chen, S.-J.; Wang, J.; Luo, Y.; Luo, X.-J.; Mai, B.-X. Plant uptake of atmospheric brominated flame retardants at an e-waste site in southern China. Environ. Sci. Technol. 2012, 46, 2708−2714. (34) Tasdemir, Y.; Salihoglu, G.; Salihoglu, N. K.; Birgul, A. Air-soil exchange of PCBs: Seasonal variations in levels and fluxes with influence of equilibrium conditions. Environ. Pollut. 2012, 169, 90−97. (35) Barber, J. L.; Thomas, G. O.; Kerstiens, G.; Jones, K. C. Study of plant-air transfer of PCBs from an evergreen shrub: Implications for mechanisms and modeling. Environ. Sci. Technol. 2003, 37, 3838− 3844. (36) Yu, Z. H.; Wang, G. H.; Jin, J.; Liu, J. D.; Liu, X. B. Soil microbial communities are affected more by land use than seasonal variation in restored grassland and cultivated Mollisols in Northeast China. Eur. J. Soil Biol. 2011, 47, 357−363.

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This study was financially supported by the National Science Foundation of China (Nos. 41273115, 41121063, 41230639, and 41073078) and the Guangdong Natural Science Foundation (S2011010006081). This is contribution No. IS1841 from GIGCAS.

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REFERENCES

(1) Cook, J. W. Some chemical aspects of polychlorinated biphenyls (PCBs). Environ. Health Persp. 1972, 1, 3−13. (2) Cok, I.; Hakan Satiroglu, M. Polychlorinated biphenyl levels in adipose tissue of primiparous women in Turkey. Environ. Int. 2004, 30, 7−10. (3) Diamond, M. L.; Melymuk, L.; Csiszar, S. A.; Robson, M. Estimation of PCB stocks, emissions, and urban fate: Will our policies reduce concentrations and exposure? Environ. Sci. Technol. 2010, 44, 2777−2783. (4) Robson, M.; Melymuk, L.; Csiszar, S. A.; Giang, A.; Diamond, M. L.; Helm, P. A. Continuing sources of PCBs: The significance of building sealants. Environ. Int. 2010, 36, 506−513. (5) Jartun, M.; Ottesen, R. T.; Steinnes, E.; Volden, T. Painted surfaces - important sources of polychlorinated biphenyls (PCBs) contamination to the urban and marine environment. Environ. Pollut. 2009, 157, 295−302. (6) Zhang, L.; Lohmann, R. Cycling of PCBs and HCB in the surface ocean-lower atmosphere of the open Pacific. Environ. Sci. Technol. 2010, 44, 3832−3838. (7) Li, Y. F.; Harner, T.; Liu, L. Y.; Zhang, Z.; Ren, N. Q.; Jia, H. L.; Ma, J. M.; Sverko, E. Polychlorinated biphenyls in global air and surface soil: Distributions, air-soil exchange, and fractionation effect. Environ. Sci. Technol. 2010, 44, 2784−2790. (8) Breivik, K.; Gioia, R.; Chakraborty, P.; Zhang, G.; Jones, K. C. Are reductions in industrial organic contaminants emissions in rich countries achieved partly by export of toxic wastes? Environ. Sci. Technol. 2011, 45, 9154−9160. (9) Venier, M.; Hites, R. A. Time trend analysis of atmospheric POPs concentrations in the Great Lakes region since 1990. Environ. Sci. Technol. 2010, 44, 8050−8055. (10) Schuster, J. K.; Gioia, R.; Sweetman, A. J.; Jones, K. C. Temporal trends and controlling factors for polychlorinated biphenyls in the UK atmosphere (1991−2008). Environ. Sci. Technol. 2010, 44, 8068−8074. (11) Xing, G. H.; Chan, J. K. Y.; Leung, A. O. W.; Wu, S. C.; Wong, M. H. Environmental impact and human exposure to PCBs in Guiyu, an electronic waste recycling site in China. Environ. Int. 2009, 35, 76− 82. (12) Barber, J. L.; Thomas, G. O.; Kerstiens, G.; Jones, K. C. Current issues and uncertainties in the measurement and modelling of airvegetation exchange and within-plant processing of POPs. Environ. Pollut. 2004, 128, 99−138. (13) Collins, C.; Fryer, M.; Grosso, A. Plant uptake of non-ionic organic chemicals. Environ. Sci. Technol. 2006, 40, 45−52. (14) Gerhardt, K. E.; Huang, X. D.; Glick, B. R.; Greenberg, B. M. Phytoremediation and rhizoremediation of organic soil contaminants: Potential and challenges. Plant Sci. 2009, 176, 20−30. (15) Mackova, M.; Macek, T.; Ocenaskova, J.; Burkhard, J.; Demnerova, K.; Pazlarova, J. Biodegradation of polychlorinated biphenyls by plant cells. Int. Biodeter. Biodegr. 1997, 39, 317−325. (16) Chroma, L.; Moeder, M.; Kucerova, P.; Macek, T.; Mackova, M. Plant enzymes in metabolism of polychlorinated biphenyls. Fresen. Environ. Bull. 2003, 12, 291−295. (17) Coleman, J.; Blake-Kalff, M.; Davies, E. Detoxification of xenobiotics by plants: chemical modification and vacuolar compartmentation. Trends Plant Sci. 1997, 2, 144−151. 3854

dx.doi.org/10.1021/es405632v | Environ. Sci. Technol. 2014, 48, 3847−3855

Environmental Science & Technology

Article

(37) Cui, Z. J.; Xu, H. Y.; Wang, X.; Liu, J. Spatial distribution and enantiomeric signature of chiral polychlorinated biphenyls in soils of Jinan, China. Environ. Eng. Sci. 2012, 29, 758−764. (38) Desborough, J.; Harrad, S. Chiral signatures show volatilization from soil contributes to polychlorinated biphenyls in grass. Environ. Sci. Technol. 2011, 45, 7354−7357. (39) Jamshidi, A.; Hunter, S.; Hazrati, S.; Harrad, S. Concentrations and chiral signatures of polychlorinated biphenyls in outdoor and indoor air and soil in a major U.K. conurbation. Environ. Sci. Technol. 2007, 41, 2153−2158. (40) Koblickova, M.; Ducek, L.; Jarkovsky, J.; Hofman, J.; Bucheli, T. D.; Klanova, J. Can physicochemical and microbial soil properties explain enantiomeric shifts of chiral organochlorines? Environ. Sci. Technol. 2008, 42, 5978−5984. (41) Robson, M.; Harrad, S. Chiral PCB signatures in air and soil: Implications for atmospheric source apportionment. Environ. Sci. Technol. 2004, 38, 1662−1666. (42) Wong, F.; Robson, M.; Diamond, M. L.; Harrad, S.; Truong, J. Concentrations and chiral signatures of POPs in soils and sediments: A comparative urban versus rural study in Canada and UK. Chemosphere 2009, 74, 404−411. (43) Cousins, I. T.; Mackay, D. Strategies for including vegetation compartments in multimedia models. Chemosphere 2001, 44, 643− 654. (44) Zhang, X. M.; Schramm, K. W.; Henkelmann, B.; Klimm, C.; Kaune, A.; Kettrup, A.; Lu, P. C. A method to estimate the octanol-air partition coefficient of semivolatile organic compounds. Anal. Chem. 1999, 71, 3834−3838. (45) Sandermann, H. Plant-metabolism of xenobiotics. Trends Biochem. Sci. 1992, 17, 82−84. (46) Borlakoglu, J. T.; John, P. Cytochrome-P-450-dependent metabolism of xenobiotics - a comparative-study of rat hepatic and plant microsomal metabolism. Comp. Biochem. Physiol. 1989, 94c, 613−617. (47) Borlakoglu, J. T.; Wilkins, J. P. G. Correlations between the molecular structures of polyhalogenated biphenyls and their metabolism by hepatic microsomal monooxygenases. Comp. Biochem. Physiol. 1993, 105c, 113−117. (48) Hernandez, B. S.; Koh, S. C.; Chial, M.; Focht, D. D. Terpeneutilizing isolates and their relevance to enhanced biotransformation of polychlorinated biphenyls in soil. Biodegradation 1997, 8, 153−158. (49) Singer, A. C.; Wong, C. S.; Crowley, D. E. Differential enantioselective transformation of atropisomeric polychlorinated biphenyls by multiple bacterial strains with different inducing compounds. Appl. Environ. Microb. 2002, 68, 5756−5759. (50) Burken, J. G.; Schnoor, J. L. Predictive relationships for uptake of organic contaminants by hybrid poplar trees. Environ. Sci. Technol. 1998, 32, 3379−3385.

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