Sorptive Capacities of Nonpolymeric Plant Lipids ... - ACS Publications

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Article Cite This: Environ. Sci. Technol. XXXX, XXX, XXX−XXX

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Sorptive Capacities of Nonpolymeric Plant Lipids for Hydrophobic Chemicals Determined by Passive Dosing Damien Johann Bolinius,*,†,∥ Matthew MacLeod,† Francesco Iadaresta,† Jan Holmbäck,†,‡ and Annika Jahnke§ †

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Department of Environmental Science and Analytical Chemistry (ACES), Stockholm University, Svante Arrhenius väg 8, SE-114 18 Stockholm, Sweden ‡ Lipidor AB, Karolinska Institutet Science Park, Fogdevreten 2, SE-171 65 Solna, Sweden § Department Cell Toxicology, Helmholtz Centre for Environmental Research (UFZ), Permoserstr. 15, DE-04318 Leipzig, Germany S Supporting Information *

ABSTRACT: Vegetation plays an important role in the partitioning, transport, and fate of semivolatile hydrophobic organic chemicals (HOCs) in the environment. Leaf/air partition ratios (Kleaf/air) of HOCs are highly variable for different plant species. The differences cannot be fully explained by the fraction of lipids in the leaves or the thickness of the cuticle. Our goal was to elucidate the importance of nonpolymeric lipids in determining Kleaf/air. To do this, we extracted organic matter from 7 plant species using solvents that do not extract the polymeric lipids cutin and cutan, to yield extractable organic matter (EOM). We used passive dosing to determine the partition ratios of selected HOCs between the EOM of the leaves and our reference lipid, olive oil (KEOM/olive oil). In addition, we measured analogous partition ratios for three lipid standards. Proton nuclear magnetic resonance (NMR) spectroscopy was used to characterize the composition of lipids. Differences in KEOM/olive oil of two polychlorinated biphenyls and four chlorinated benzenes were below a factor of 2 in the plant species studied, indicating that the reported differences in Kleaf/air are not caused by differences in the sorptive capacities of nonpolymeric lipids or that our EOM is not representative of all nonpolymeric leaf lipids.

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PCBs.3,7,9−11 This variability was found to be related to neither the amount of lipids present in the plants7,12 nor the thickness of the cuticle,12 the waxy outer layer of the leaf. While it is possible that these differences are partly caused by the use of different methods, it has also been suggested that it could be due to differences in the quality and composition of the lipid storage compartment across plant species.7,12 Field measurements of concentration ratios between leaves and air for chemicals with log Koa larger than 9 are less variable between plant species.12 This observation is not unexpected, however, as the uptake of HOCs with high Koa into leaves is dominated by kinetically limited gaseous deposition and particle-bound deposition according to the model of McLachlan,13 and thus these chemicals are not expected to reach equilibrium between leaves and the atmosphere in the environment.

INTRODUCTION Vegetation plays an important role in the partitioning, transport, and fate of semivolatile hydrophobic organic chemicals (HOCs) in the environment.1 Sorption to leaves in particular has been found to influence the atmospheric cycling of semivolatile organic chemicals by two processes: (i) by acting as a sink for these chemicals from the atmosphere with subsequent transfer to soil,2,3 which reduces their Arctic contamination potential and increases their residence time in the environment;4,5 and (ii) as a vector for these chemicals to be transferred from the atmosphere into terrestrial food chains.6 A study that measured leaf/air partition ratios (Kleaf/air) of organic chemicals with logarithmic octanol/air partition ratios (log Koa) less than 9, using intact leaves in a fugacity meter, has shown variability of up to a factor of 20 between five grass species (for the same chemical).7 Kleaf/air values derived from deposition fluxes for a range of PCBs in nine tree species differed by less than a factor of 2.8 However, including other literature data for a variety of plant species, derived from deposition fluxes and empirical regressions, results in Kleaf/air values spanning 3 orders of magnitude for a range of © XXXX American Chemical Society

Received: October 8, 2018 Revised: December 18, 2018 Accepted: January 10, 2019

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DOI: 10.1021/acs.est.8b05656 Environ. Sci. Technol. XXXX, XXX, XXX−XXX

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Environmental Science & Technology Field observations indicate that HOCs taken up by leaves are found in the cuticle and in the inner leaf.14 Imaging studies using two-photon excitation microscopy have shown that the cuticles of leaves do not form an impenetrable barrier for HOCs. Organic chemicals have been shown to move rapidly into the inner compartments of the leaves.15 The sorptive capacity of the cuticle is thought to be largely dominated by cutin,16 a polymeric lipid that constitutes 20−80% of the leaf on a weight basis.17 Cutin in the cuticle has been shown to be in a liquid-like viscous state that can accommodate HOCs.18 However, the 1−3 orders of magnitude variability between the sorptive capacities of intact leaves from different species is not reflected in cuticle/water partition ratios (Kcuticle/water) from isolated cuticles (including cutin) of different plant species. Variability in Kcuticle/water collected from the literature was below a factor of 2.5, and a good fit was obtained when plotting log Kcuticle/water against log Kow.19,11,20 Therefore, under the assumption that cutin dominates the sorptive capacity of the cuticle, it is possible that the previously observed 1−3 orders of magnitude difference in Kleaf/air between species is due to the variability in equilibrium partitioning to other compartments than cutin. Our goal in this study was to elucidate the importance of the composition of nonpolymeric lipids in determining the capacity of leaves to sorb HOCs. We performed a total solvent extraction21 of homogenized leaves of 7 plant species and compared the sorptive capacities of the extractable organic matter (EOM) we obtained to each other and to three lipid standards, namely digalactosyldiacylglycerol, L-α-phosphatidylcholine, and nonacosane. Our extraction method yielded solvent-soluble waxes and lipids from both the outer and the internal leaf compartments. It does not extract the polymeric lipids cutin and cutan which require more elaborate extraction methods.22 Thus our method allows us to focus on the potential role of the nonpolymeric lipids in the EOM on the variability in Kleaf/air. The EOM and lipid standards were loaded with several model chemicals (PCBs and chlorobenzenes with different degrees of chlorination) by passive dosing via headspace from spiked olive oil, and the chemical concentrations were determined in all phases. Then partition ratios for HOCs between EOM and olive oil (KEOM/olive oil) and between the lipid standards and olive oil (Klipid/olive oil) were derived and compared. In addition, we analyzed the lipid composition of each extract and the lipid standards using proton nuclear magnetic resonance (1H NMR) spectroscopy, to assess correlations between the molecular composition of the EOM or lipids and their sorptive capacities.

Stable isotope-labeled analogs of some of the model chemicals were used as internal standards: For the PCBs, we used 13C12-labeled PCBs 3, 31, 101, 153, and 170, and for the chlorobenzenes, we included 13C6-labeled 1,2-di-, 1,2,3,4-tetra-, and hexachlorobenzene. As lipid standards (Table 1) we selected nonacosane, L -α-phosphatidylcholine (PC), digalactosyldiacylglycerol (DGDG), olive oil, and octanol. An estimate based on the results from the 1H NMR analysis of the DGDG standard indicated that at least 80% of this standard was DGDG and that the remaining 20% consisted of water and phospholipids other than PC. Olive oil was used as a proxy for storage lipids (triglycerides). Table 1. Information about the Lipid Standards Used in This Study Name Nonacosanea

L-α-phosphatidylcholine

(PC) Digalactosyldiacylglycerol (DGDG) Olive oil a

Octanol

Type

Supplier

Long chain paraffin (plant wax component) Membrane lipid in plants and animals Membrane lipid in higher plants Storage lipid (99% triglycerides23) Proxy for lipids24

Sigma-Aldrich (Missouri, U.S.) Type XVI-E, from egg yolk. Sigma-Aldrich (Missouri, U.S.) Enriched from oat lipids. Scotia LipidTeknik (Norberg, Sweden) ICA AB. (Solna Sweden) Sigma-Aldrich (Missouri, U.S.)

a

No results were obtained for nonacosane and octanol, due to the limitations of the passive dosing setup. See the chapter on time trends in the results section for more information.

Leaf Extraction. The leaves selected for this study were sampled from plants in Bergianska Trädgården, a botanical garden associated with Stockholm University, Sweden. We selected three deciduous trees [Alnus glutinosa (European alder), Fagus sylvatica (European beech), and Quercus rubra (northern red oak)], two coniferous species [Picea abies (Norway spruce) and Pseudotsuga menziesii (Douglas fir)], one grass species [Phragmites australis (common reed)], and one shrub [Rhododendron ponticum (common rhododendron)]. These plant species were selected based on their availability and differences in the appearance and structure of their foliage. The structure of epi-cuticular waxes for instance has been shown to be related to the chemical composition of these waxes.25 The leaves were sampled between the 12th of August and the 5th of September of 2015. Caution was taken to exclude leaves with visible damage and to avoid trees with leaves that had begun to senesce. For the evergreen species (Picea abies, Pseudotsuga menziesii, and Rhododendron ponticum), only leaves from previous growing seasons were taken. The motivation for this procedure is that the lipid composition between younger and older needles can differ significantly.26 Before extraction, 30−110 leaves (depending on the size of the leaves) were cut from their branches using scissors and transported to the lab on ice. A representative subsample of leaves of each species was taken for fresh weight and dry weight determination. The dry weight of the leaves was determined by drying the leaves in an oven at 30−60 °C until a constant weight was reached. The EOM of the leaves was obtained using the modified “Jensen” total solvent extraction method for biota samples (see Text s1 in the Supporting Information).21 To prevent the

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MATERIAL AND METHODS Chemicals. A list of the solvents used, including information regarding their vendors and purities, is given in the Supporting Information (SI, Table s1). The HOC model chemicals used in this study included 9 polychlorinated biphenyls (PCBs 3, 4, 28, 52, 101, 118, 138, 152, 180) and 6 chlorobenzenes (CBs: mono-, 1,2-di-, 1,2,4-tri-, 1,2,3,4-tetra-, penta-, and hexachlorobenzene) (SI, Table s2). These chemicals were chosen not only to test the limits of achieving equilibrium in the passive dosing approach via headspace over the course of the experiment and the purge-and-trap extraction method applied in this study but also because most of them are expected to reach equilibrium with leaves in the environment according to the interpretive framework of McLachlan.13 B


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or gel phase aggregation state.28 The waxes that were extracted from the leaves were assumed to be in an amorphous crystalline state.18 The state which the lipids are in is important to consider since it can have a large impact on their sorptive capacities. The crystallinity of lipids has been shown to be inversely proportional to their uptake capacity for HOCs.29 Sample Extraction and GC/MS Analysis. Sample extraction and cleanup were done using the purge-and-trap technique described in earlier studies.23,30 A major benefit of the purge-and-trap method is that it makes it possible to achieve an excellent simultaneous cleanup of the sample during extraction while ensuring a low risk of contamination. After retrieval of the vials from the dosing jars, 2 mL of DCM were added to redissolve the EOM or lipid standard and mixed using a Pasteur pipet. Then, 100 μL of this solution were transferred to a glass test tube together with 100 ng of the labeled internal standards and a small Teflon-coated magnetic stir bar. The test tube was then sealed with a rubber stopper to which two tubings with one ENV+ solid-phase extraction cartridge (Biotage AB, Sweden) each were connected. Incoming nitrogen was precleaned on a 50 mg ENV+ cartridge before entering the test tube while the outgoing nitrogen including the analytes was passed through and collected on a sampling cartridge containing 10 mg of ENV+. The system was operated at room temperature for 1 h until the DCM had evaporated. Then it was heated to 70 °C for another 4 h. Immediately after this, the 10 mg sampling cartridges were eluted with 1 mL of n-hexane. The volumetric standards, 100 ng of PCB 53 and aldrin in 10 μL of toluene, were added to the sample extracts on the day preceding analysis. The samples were analyzed using a gas chromatograph (Trace 1310, Thermo Scientific, U.S.) with a 30 m 5% phenylmethylpolysiloxane column (0.25 mm i.d./0.25 mm film thickness, TG-5SilMS, Thermo Scientific, U.S.) coupled to a single quadrupole mass spectrometer (ISQ LT, Thermo Scientific, U.S.). The acquisition was carried out using selected ion monitoring (SIM) where two ions for each analyte were used for quantification and qualification purposes, respectively (see Table s2). The recoveries for each analyte are given in Figure s2, and a detailed description of the GC/MS method can be found in Text s2. Calculation of Acceptor/Donor Partition Ratios. The status of the equilibration process in each jar was determined by testing for significant differences in the ratio of the analyte concentration in the EOM or lipid standard acceptors and the olive oil donor over time. For this purpose, we compared the 95% confidence intervals of the measurements. This observation shows that these data were not statistically significantly different from 1. For those model chemicals that reached equilibrium during the 2-week exposure, the average concentration ratio was taken from all replicates that were not significantly different at the 95% confidence level. This means that the faster a chemical reached equilibrium, the more replicates were included for the determination of the partition ratio. If equilibrium was not reached during the exposure time, the partition ratios were estimated by extrapolation using a one-phase association curve that was fitted to the experimental data in GraphPad Prism (eq 1) as described earlier:11,23

extracts from degrading during storage, the antioxidant butylhydroxytoluene (BHT, Sigma-Aldrich, Missouri, U.S.) was added to the extraction solvents at a concentration of 0.01%. In preparation for this extraction, the main nerve was removed from the leaves, the entire batch was cut into small pieces and mixed, and then 3 replicates of 10 g of leaf material each were processed. The combined extracts were blown down at room temperature under a stream of nitrogen until they were dry (visual inspection) and then were stored for 1−2 nights in a desiccator containing silica gel until they reached constant weight. This weight was then used to calculate the yield of each extract. Volatile substances, which could originally have been present in the EOM extract, may have been lost during these solvent evaporation steps. The EOM samples were redissolved in methyl tert-butyl ether (MTBE) containing 0.01% BHT and stored at −20 °C in the freezer until further use (see Text s1 for more information). Passive Dosing System. The passive dosing system used in this study is a modification of that used previously by Jahnke et al.27,23 in which samples are dosed via the headspace in closed jars using spiked olive oil as a donor matrix (Figure s1 and TOC). The experimental setup consisted of one 500 mL amber glass jar (Wares of Knutsford, Cranage, U.K.) for each matrix. The jar contained spiked donor oil at the bottom and 12 vials (5 mL, Thermo Fisher Scientific, Stockholm, Sweden) to hold the EOM or lipid samples to be dosed. In this study, in order to increase the transfer rates of chemicals from the donor oil to the leaf EOM and lipid standards, a fan (Arctic, Switzerland) was installed in the lid of the jar using polyurethane-based glue (Sikaflex, U.S.), and was run continuously during the experiments at 6 V. Another modification of the method compared to that described by Jahnke et al. was that the sample vials were placed on a metal wire frame to avoid direct contact with the donor oil and to increase the contact area between headspace air and the donor oil. Separating the vials from the donor oil also reduced losses of donor oil associated with the removal of the vials from the system for analysis over time. The donor oil was prepared by spiking 70 mL of olive oil with 5 to 36 mg of standard chemicals and stirring in the dark for 2 weeks with a Teflon-coated magnetic stir bar. A glass fiber filter was placed on the bottom of each jar (n = 12), and 5 mL of the donor oil were added to the filter to spread the oil more evenly and to increase the contact area between the oil and the headspace air. The passive dosing systems were then left to pre-equilibrate at room temperature with the fans running for 2 months to reduce the potential of the fans and glue to compete with the EOM for the sorption of HOCs during the dosing experiment. Between 4.8 and 41 mg of the EOM or lipid standards were dissolved in MTBE and dichloromethane (DCM), centrifuged to precipitate potential particulate matter, and added to each vial, and the solvent was left to evaporate in a fume hood. The weight of each sample was then recorded, and the sample vials were placed on the frames in the jars. Triplicate samples of the EOM were taken at 0 h (i.e., before exposure to the olive oil donor started) and after 24 h, 72 h, 1 week, and 2 weeks of exposure. All samples were processed as described below immediately upon sampling. The temperature in the fume hood, located in an airconditioned lab, was not measured during the experiment, but was later determined to be consistently 20 ± 0.5 °C. At this temperature, we assumed that the lipid standards of PC and DGDG as well as the leaf extracts were in an amorphous solid

Cacceptor Colive oil C

= KEOM/olive oil(1 − e(−kt ))

(1)


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Environmental Science & Technology where Cacceptor is the concentration measured in the EOM or lipid standards and Colive oil is the concentration measured in the spiked olive oil (donor oil) (ng/g), KEOM/olive oil is the partition ratio between EOM and olive oil, k is the rate constant (h−1), and t is time (h). Quality Assessment/Quality Control. As a first quality control, ion ratios for each compound in all samples were compared to those found in the calibration standards, and data points with ratios that differed by more than 15% were excluded. The method detection limit (MDL) and method quantification limit (MQL) were derived from the nondosed samples of each matrix (EOM and lipid standards; n = 36), method blanks (n = 15), and a solvent blank (n = 1). The MDL was calculated as the average concentration in these samples and blanks + 3 times the standard deviation of the samples and blanks, while the MQL was calculated as the average + 9 times the standard deviation. If analytes were detected in less than three of the samples and blanks, as was the case for PCB 180, the MQL was calculated as 10 times the average concentration measured in these samples and blanks. If no analytes were detected in the samples and the blanks, then the lowest point in the calibration curve was used as MQL. Data points below the MDL were excluded, but those above MDL and below MQL were kept for subsequent data analysis (indicated with hollow circles in Figure S5). As a quality control of the dosing method and our calculations, one passive dosing system was dedicated to measuring olive oil as a control matrix. Identically as for the EOM extracts and lipid standards, samples were analyzed in triplicates at 0 h, 24 h, 72 h, 1 week, and 2 weeks of exposure to the donor oil. As the donor oil and olive oil samples were from the same batch, the equilibrium partition ratios measured for these acceptor/donor olive oil pairs were expected to be one. Analysis of Lipid Composition. The EOM samples and lipid standards were characterized using a screening method based on 1H NMR spectroscopy and a subsequent multivariate analysis for discrimination. Similar approaches have been used in metabolomic studies where a multivariate analysis of NMR spectra has become increasingly important and common. The metabolomic analysis generates unique fingerprinting, where hundreds of compounds and their variation in different samples can be used for instance for the identification of apple cultivars,31 or discrimination of Hippophaë species.32 In this study the spectra were divided into chemical shift regions in order to describe features of the different lipid molecular structures, and the signals detected in each region were integrated to give quantitative information about the presence of these features expressed in microequivalents per gram (μEq/g). Each region encompasses a signal or a group of signals typical of molecular structures, such as methylene groups in hydrocarbon chains (1.24 ppm), methylene groups bound to heteroatoms (low field 4.0−4.85 ppm, high field 3.3−4.0 ppm), allylic protons (2.04 ppm), or aromatic protons (5.5−8.2 ppm). In some cases, the EOM sample spectra were too complex to assign all signals, but the different regions could nevertheless be assumed to reflect the electronic environment of 1H atoms and thereby serve as a description of the functional groups present in the molecules in the sample mixture. For an obtained spectrum it was in some cases possible to identify a specific signal that belonged to a class of compounds, e.g. PC (3.19 ppm), DGDG (4.87 ppm), and phytosterols

(0.67 ppm), while in other cases they were more general, e.g. the carbon chain of acyl lipids (1.24 ppm). The corresponding signal ranges are summarized in Table s3. The EOM sample (1.5−3.0 mg) and 3 mg of the internal standard, decamethylcyclopentasiloxane (Sigma-Aldrich, Missouri U.S.), were dissolved in 600 μL of a mixture of deuterated chloroform-d and methanol-d4 (1:1 by volume) and transferred to a 5 mm NMR tube. The 1H NMR spectra were acquired at 500 MHz on a Bruker DMX-500 spectrometer (Bruker Daltonics Scandinavia AB, Solna, Sweden). A standard 30° pulse sequence with 40 scans, a 3.17 s acquisition time, and a 5 s relaxation delay was used. Principal Component Analysis. Principal component analysis (PCA) is a method to compress multivariate data to its most dominant influencing factors, which can be used to visualize variability and similarity among samples, and to represent the most important information that is available.33 In order to visualize differences and similarities between the EOM and lipid matrices, PCA analysis was used on the 1H NMR data (data matrix in Table s3, Figure s3). The PCA analysis was performed using The Unscrambler (Camo software A.S., Norway); see Figure s4. The total integrals of selected chemical shift ranges were mean-centered and standard deviation-scaled before the PCA analysis was done.

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RESULTS Quality Assessment/Quality Control. Method Detection and Quantification Limits. The MDLs and MQLs are given in Table s4. Monochlorobenzene, the most volatile compound in our study, could not be detected in any of the samples. Furthermore, the least volatile compounds with the longest equilibration times, PCBs 101, 118, 138, 153, and 180, were only detectable in the dosed EOM samples after 1 week (PCB 101) or 2 weeks (PCBs 118, 138, 153, and 180) of exposure. Outliers. One replicate measured at 72 h for Picea abies was considered to be an outlier and was removed from the data set (Text s3). Recoveries. The average recoveries for the isotope-labeled internal standard compounds in the purge-and-trap extraction ranged from 91% (1,2,3,4-tetrachlorobenzene) to 9.9% (PCB 170). There was a clear drop in the recoveries for the less volatile chemicals, caused by their decreasing extraction yield in the purge-and-trap system. The recoveries of chemicals for which KEOM/olive oil and Klipid/olive oil could be determined (see section on sorptive capacities below) were between 72% (hexachlorobenzene) and 88% (1,2 dichlorobenzene). Precision and Accuracy. For those chemicals for which KEOM/olive oil and Klipid/olive oil could be determined, the replicates of the olive oil donor samples (n = 5) had a relative standard deviation of 3.9% (PCB 4) to 11.6% (hexachlorobenzene). Measured concentrations for these chemicals were within a factor of 1.5 of the nominal concentrations. Controls. In the passive dosing system with the olive oil control, PCBs 3 and 4 as well as di-, tri-, tetra-, penta-, and hexachlorobenzene reached an experimental Kolive oil/olive oil of on average 0.89 (stdev = 0.082). For all model chemicals but PCB 4, the 95% confidence intervals included 1 which is a confirmation that equilibrium for these analytes has either been reached or, in the case of hexachlorobenzene, extrapolated accurately (Figure s5, Table s5). For PCB 4, the 95% confidence interval for Kolive oil/olive oil ranged from 0.50 to 0.99. D


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Figure 1. Results from the PCA analysis with score (A) and loading (B) plots for principal components 1 and 2, explaining 50% and 18% of the observed variation in the data, respectively. Plant species that are underlined appeared to differ from the others. Results for principal components 3 and 4 are given in Figure s4. See Table s3 for descriptions of the molecular structures.

Figure 2. Ratios of the concentrations in EOM and olive oil measured for six of the chemicals over time for Alnus glutinosa. The dots represent the measured concentration ratios, and the broken lines are one phase association curves that were fitted to the data using GraphPad Prism. Similar plots for the other chemicals and matrices can be found in Figure s5. PCBs 3, 4, and 28 are mono-, di-, and trichlorinated, respectively.

leaf extracts for the first principal component, which explained half of the observed variation in the data (Figure 1). Nonacosane was excluded from the PCA analysis, as it only provided two signals in the NMR analysis resulting in a PCA plot with nonacosane on one end and all the other lipid standards and EOM bulked on the other. Roughly one-third of the molecular structures detected using NMR were only detected in the leaf extracts but not in the lipid standards (Table s3). The differences in the lipid composition of the leaf extracts were more difficult to evaluate, as the separation between the species was less pronounced. The species that appeared to be different based on the PCA analysis were Picea abies, Pseudotsuga menziesii, and Rhododendron ponticum which are underlined in Figure 1 A (see also Figure s4, for principal components 3 and 4). Kinetics of Chemical Uptake into the EOM and Lipid Standards. Equilibrium of the compounds between the donor oil and the EOM or lipid standards was reached within 2 weeks

EOM Composition of the Leaves. The EOM yields were 2.0−3.9% and 4.5−9.9% of the fresh and dry weight of the leaves, respectively. The leaf samples in this study contained 52−63% water (see Table s6 for more details). Differences between the plant species observed in the molecular structures of the EOM detected by NMR analysis (Table s3, Figure s3) were much higher than in samples from, e.g., seeds,34 indicating differences in their composition. An example of these differences is unsaturated terpenes (e.g., pinene) which are present in Picea abies and frequently have a signal around 5.1 ppm. This signal is included in the range classified as “olefinic branched”, and the content of terpenes is reflected in a relatively high value for this feature in Picea abies. Another example is represented by doubly allylic protons, typical of polyunsaturated fatty acids, which were especially abundant in Phragmites australis. The PCA of the 1H NMR data showed a clear distinction between the well-defined lipid standards and the more complex E


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Figure 3. Measured partition ratios between the lipid standards and olive oil, and between EOM from leaves of 7 plant species and olive oil. The horizontal lines represent the mean values for all analytes of Klipid/olive oil for the respective lipid standards and of KEOM/olive oil from all 7 species, excluding the values that were generated by extrapolation, marked with an asterisk. The bars represent the 95% confidence intervals based on both the uncertainties in the measurements in the lipid or EOM and those in the donor oil. Individual values can be found in Table s5.

Sorptive Capacities of the Lipid Standards and EOM. Based on the 95% confidence intervals of the KEOM/olive oil and Klipid/olive oil measurements, a significant difference was observed between the KEOM/olive oil and the Klipid/olive oil of PC, DGDG, and olive oil (Figure 3). The sorptive capacity of the second most abundant membrane lipid in higher plants (after monogalactosyldiacylglycerol, MGDG), DGDG, was on average lower than that of the standard storage lipid olive oil by a factor of 2.1, but higher than that of the standard membrane lipid, PC, by a factor of 1.7. In most cases, the values for KEOM/olive oil across the leaf extracts of the 7 plant species fell between DGDG and olive oil. These data did not differ significantly between EOM extracts, based on the 95% confidence intervals of the measurements. Only in a few cases for PCB 3 and trichlorobenzene did we observe significant differences in KEOM/olive oil with values measured for the extracts of the coniferous species (Picea abies and Pseudotsuga menziesii) significantly larger than those of the other plant species. On average KEOM/olive oil was 0.59 for the leaf extracts.

of exposure for half of the compounds that were tested (Table s7 and Figure s5). In the case of di- and trichlorobenzene, it was already reached within 24−72 h of exposure, and the same holds true for tetra- and pentachlorobenzene in some matrices. These results showed a clear improvement on the kinetics reported using the original method in which equilibrium for tetra- and pentachlorobenzene could not be reached within 9 days of exposure.23 For pentachlorobenzene in other matrices and hexachlorobenzene, equilibrium was not reached, and the plateau value was hence estimated by extrapolation using GraphPad Prism as described above. For PCBs 28 and 52, a similar extrapolation was attempted but the uncertainties of the resulting plateau values were too large so that these analytes are not discussed further. Based on the time to equilibrium, the uptake kinetics between the plant species differed more strongly for the less volatile chemicals (Table s7). Samples taken at 24 h were excluded from further analysis for nonacosane, PC, DGDG, octanol, olive oil, and Picea abies, due to quantification issues with the internal standards that prevented accurate determination of the concentrations. Octanol proved to be too volatile for the passive dosing system used in this study, as most of it was lost from the sample vials within 24 h. It is likely that a fraction of the octanol was taken up by the olive oil donor while another part was lost to the headspace and from there to the fume hood upon the opening of the jars. We also did not find any samples above MDL for nonacosane, which is likely due to its crystalline structure that resulted in low sorptive capacities for HOCs and reduced uptake kinetics. A representative example of the uptake plots for selected analytes into the EOM of Alnus glutinosa is given in Figure 2.

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DISCUSSION Quality Assessment/Quality Control. The nondetects of the most volatile (monochlorobenzene) and least volatile (the higher chlorinated PCBs) chemicals were likely attributable to both the experimental setup and the extraction method. Monochlorobenzene might have escaped the system during the preloading period and every time that the jars were opened as well as during the extraction process. For PCBs 101 to 180, their relatively low volatility means that they likely did not reach detectable concentrations in the final extracts due to (i) the slow mass transfer from the donor matrix into the headspace to the sample vials in the passive dosing system and F


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homogenized leaves of Euonymus japonicas compared to isolated cuticles that were kept intact.20 However, this effect might have been dominated by the role of cutin, as its crystallinity has been shown to be influenced by the presence of waxes and carbohydrates in the cuticle.16 Waxes and carbohydrates function as antiplasticizers (decreasing plasticity, making a matrix stiffer) and plasticizers (increasing plasticity, making a matrix more fluid-like) for the cutin, respectively.16 We recently reported fugacity capacities and Kleaf/water values for PCBs 3 and 4 for intact, dry rhododendron leaves from the same plant used in this study.11 We converted these partition ratios into KEOM/olive oil by (i) calculating Kleaf/olive oil as the product of Kleaf/water and Kwater/storage lipid (using literature data,37 adjusted for temperature, eq 2) and (ii) normalizing to the fraction of EOM in the rhododendron leaves (8.5%, Table s6, eq 3). Kolive oil/storage lipid was assumed to be equal to 1. KEOM/olive oil was calculated for the minimum and maximum values reported for Kleaf/water and then averaged.

(ii) the clear drop in recoveries of the labeled PCBs with increasing degree of chlorination in the purge-and-trap extraction system (Figure s2). EOM Composition of the Leaves. Our 1H NMR method provided a qualitative description of the lipid composition in the bulk extracts, but due to the complexity of the leaf EOM, the assignment of molecular structures is not unambiguous. More detailed information would require fractionation steps and consequently much larger amounts of sample; hence, it fell outside the scope of our study. A recently published detailed analysis of the lipid composition of rhododendron leaves used 25 kg of leaves and more than 600 L of solvents.35 In contrast, our NMR screening approach can be used to characterize profiles of each extract quickly and qualitatively. In our study it was used to indicate that there were differences in the lipid composition between the plant species (Figures 1, s3, and s4). Sorptive Capacity of the Lipid Standards and EOM. Inherent to the method used to extract the leaf lipids, it is possible that the most volatile substances originally present in the EOM might have been lost together with the extraction solvents during the drying of the samples. In this study, we assume that these losses do not have an impact on the sorptive capacities of the EOM. To the best of our knowledge, this is the first report of partition ratios of HOCs for DGDG. Triglycerides and PC are commonly used to derive lipid-normalized concentrations in animals.29 In contrast, DGDG is an important building block in leaf chloroplasts and together with MGDG makes up roughly 75% of the total amount of membrane lipids in leaves of higher plants.36 It has also been shown to replace phospholipids in plants grown under phosphate deprivation.36 As the DGDG standard was shown to contain only 80% DGDG with the remaining 20% consisting of water and phospholipids (other than PC), the sorptive capacity of pure DGDG is likely to be up to 12% higher than that determined in our study, based on our measurements for Klipid/olive oil (Table s5), ignoring the sorptive capacity of water for HOCs and assuming that other phospholipids have a similar Klipid/olive oil as PC (see Text s4).29 Keeping in mind the large variability reported in Kleaf/air values for different species from the literature (factors of 2 to 1000),3,7−11 it is interesting that much smaller interspecies variability (a factor of up to 2) has been found in this study in the values for KEOM/olive oil obtained from needles and leaves that differed considerably in their appearance and lipid composition. These findings indicate that the observed variability in Kleaf/air values is not dependent on the composition of the solvent-extractable lipids in leaves. However, the EOM does not contain the polymeric lipid cutin, which is thought to be a major component in the cuticle for the sorption of HOCs.18,20 In a study of the uptake of phenanthrene into isolated cuticles of Photinia serrulata, it was shown that a 32.6% higher cutin content in the adaxial (upper) cuticle compared to the abaxial (lower) cuticle was correlated with 2-fold higher concentrations of phenanthrene.18 This study however only looked at one species and one chemical. Our results also do not rule out the possibility that rather than the composition of the EOM, it is the structure of the lipids in the cuticle that influences the sorptive capacities of the leaves as the homogenization of the leaves and their subsequent solvent extraction clearly disrupts their structure. It has been demonstrated for PAHs that leaf/water partition ratios (Kleaf/water) decreased by a factor 3.7 to 190 for

Kleaf/olive oil = Kleaf/water × K water/storage lipid × K storage lipid/olive oil KEOM/olive oil = Kleaf/olive oil × EOM fractionRhododendron

(2) (3)

This conversion resulted in KEOM/olive oil values for PCBs 3 and 4 that differed only by factors of 1.9 (±1.1, 95% confidence interval) to 4.8 (±4.0) from those measured in this study. This similarity provides an indication that the EOM does give a reasonable representation of that fraction of the leaf that is available for the uptake of PCBs 3 and 4. More measurements are needed, however, of Kleaf/olive oil and KEOM/olive oil for the same plant species to confirm this hypothesis. Estimated values for Koctanol/olive oil were calculated by taking the product of Kow (from Epiweb 4.1 for chlorobenzenes and Schenker et al.38 for PCBs) and Kwater/storage lipid37 and assuming Kolive oil/storage lipid = 1.37 These estimated values were a factor of 1.56 (±0.57, 95% confidence interval) larger than KEOM/olive oil measured in this study for di-, tri-, tetra-, penta-, and hexachlorobenzene and PCBs 3 and 4. The KEOM/olive oil measured for the different types of leaves in this study were also similar to those measured by Jahnke et al.23 for several extracts of animal lipids (0.43−0.84 for tri- and tetrachlorobenzene, respectively). These animal extracts were shown to consist mainly of triglycerides using NMR analysis and hence to be much simpler in their lipid composition than the EOM obtained from leaves. It is possible that the EOM, being a “bulk lipid” that contains a variety of lipids, waxes, and coeluting compounds, does not vary substantially across species and kingdoms and might be approximated by the use of octanol.29 Our study provides evidence that the differences observed in the literature for Kleaf/air from different plant species are likely not due to differences in the composition of the extractable lipids. More studies are needed to investigate the potential role of the cutin fraction. A possible strategy is measuring the fugacity capacities of isolated cuticles from a large range of plant species of which the extractable lipids have previously been removed and then relating these to fugacity capacities of intact leaves. The dosing for this setup could be done using a fugacity meter39,7 or a “sandwich” in two layers of loaded silicone.11,20 G


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(5) MacLeod, M. On the influence of forests on the overall fate of semi-volatile organic contaminants. Stoch Environ. Res. Risk Assess. 2003, 17 (4), 256−9. (6) McLachlan, M. S. Bioaccumulation of Hydrophobic Chemicals in Agricultural Food Chains. Environ. Sci. Technol. 1996, 30 (1), 252− 9. (7) Kömp, P.; McLachlan, M. S. Interspecies variability of the plant/ air partitioning of polychlorinated biphenyls. Environ. Sci. Technol. 1997, 31 (10), 2944−2948. (8) Nizzetto, L.; Pastore, C.; Liu, X.; Camporini, P.; Stroppiana, D.; Herbert, B.; et al.et al. Accumulation Parameters and Seasonal Trends for PCBs in Temperate and Boreal Forest Plant Species. Environ. Sci. Technol. 2008, 42 (16), 5911−6. (9) Bacci, E.; Calamari, D.; Gaggi, C.; Vighi, M. Bioconcentration of organic chemical vapors in plant leaves: experimental measurements and correlation. Environ. Sci. Technol. 1990, 24 (6), 885−889. (10) Su, Y.; Wania, F.; Harner, T.; Lei, Y. D. Deposition of Polybrominated Diphenyl Ethers, Polychlorinated Biphenyls, and Polycyclic Aromatic Hydrocarbons to a Boreal Deciduous Forest. Environ. Sci. Technol. 2007, 41 (2), 534−40. (11) Bolinius, D. J.; MacLeod, M.; McLachlan, M. S.; Mayer, P.; Jahnke, A. A passive dosing method to determine fugacity capacities and partitioning properties of leaves. Environ. Sci.: Processes Impacts. 2016, 18 (10), 1325−32. (12) Böhme, F.; Welsch-Pausch, K.; McLachlan, M. S. Uptake of Airborne Semivolatile Organic Compounds in Agricultural Plants: Field Measurements of Interspecies Variability. Environ. Sci. Technol. 1999, 33 (11), 1805−13. (13) McLachlan, M. S. Framework for the Interpretation of Measurements of SOCs in Plants. Environ. Sci. Technol. 1999, 33 (11), 1799−804. (14) Wang, Y. Q.; Tao, S.; Jiao, X. C.; Coveney, R. M.; Wu, S. P.; Xing, B. S. Polycyclic aromatic hydrocarbons in leaf cuticles and inner tissues of six species of trees in urban Beijing. Environ. Pollut. 2008, 151 (1), 158−64. (15) Wild, E.; Dent, J.; Thomas, G. O.; Jones, K. C. Visualizing the Air-To-Leaf Transfer and Within-Leaf Movement and Distribution of Phenanthrene: Further Studies Utilizing Two-Photon Excitation Microscopy. Environ. Sci. Technol. 2006, 40 (3), 907−16. (16) Chen, B.; Li, Y.; Guo, Y.; Zhu, L.; Schnoor, J. L. Role of the Extractable Lipids and Polymeric Lipids in Sorption of Organic Contaminants onto Plant Cuticles. Environ. Sci. Technol. 2008, 42 (5), 1517−23. (17) Holloway, P. J. Plant Cuticles: Physicochemical Characteristics and Biosynthesis. In Air Pollutants and the Leaf Cuticle; Percy, K. E., Cape, J. N., Jagels, R., Simpson, C. J., Eds.; Springer Berlin Heidelberg: Berlin, Heidelberg, 1994; pp 1−13. (18) Li, Q.; Chen, B. Organic Pollutant Clustered in the Plant Cuticular Membranes: Visualizing the Distribution of Phenanthrene in Leaf Cuticle Using Two-Photon Confocal Scanning Laser Microscopy. Environ. Sci. Technol. 2014, 48 (9), 4774−81. (19) Riederer, M. Estimating partitioning and transport of organic chemicals in the foliage/atmosphere system: discussion of a fugacitybased model. Environ. Sci. Technol. 1990, 24 (6), 829−837. (20) Kim, S.-J.; Lee, H.; Kwon, J.-H. Measurement of partition coefficients for selected polycyclic aromatic hydrocarbons between isolated plant cuticles and water. Sci. Total Environ. 2014, 494−495, 113−8. (21) Jensen, S.; Häggberg, L.; Jörundsdóttir, H.; Odham, G. A Quantitative Lipid Extraction Method for Residue Analysis of Fish Involving Nonhalogenated Solvents. J. Agric. Food Chem. 2003, 51 (19), 5607−11. (22) Deshmukh, A. P.; Simpson, A. J.; Hadad, C. M.; Hatcher, P. G. Insights into the structure of cutin and cutan from Agave americana leaf cuticle using HRMAS NMR spectroscopy. Org. Geochem. 2005, 36 (7), 1072−85. (23) Jahnke, A.; Holmbäck, J.; Andersson, R. A.; Kierkegaard, A.; Mayer, P.; MacLeod, M. Differences between Lipids Extracted from Five Species Are Not Sufficient To Explain Biomagnification of

ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.est.8b05656.

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List of solvents used, vendors and purities; List of analytes and the ions that were used for identification and quantification; Results from the NMR analysis of the different EOM samples and lipid standards; MDLs and MQLs for the compounds analyzed in this study; Values for Klipid/olive oil and KEOM/olive oil; Weight fraction of the EOM; Time needed to reach equilibrium for the compounds and EOM matrices; Schematic of the passive dosing system; Recoveries of the 13C labeled internal standards; Overview of the variability of the structural features detected in the EOM of the leaves; Score and loading plots for principal components 3 and 4; Uptake trends for analytes with samples above MDL within 1 week of exposure; Jensen total solvent extraction method; Method used for the GC/MS analysis; Outlier for Picea abies at 72 h; Calculation used to estimate KDGDG/olive oil (PDF)

AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. ORCID

Damien Johann Bolinius: 0000-0002-6301-0068 Matthew MacLeod: 0000-0003-2562-7339 Present Address ∥

Baltic Sea Centre, Stockholm University, SE-114 18 Stockholm, Sweden. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This research was funded by the Swedish Research Council Vetenskapsrådet (VR), Project Number 2011-3890, “Investigating thermodynamic controls on the cycling of persistent organic chemicals in forest systems”, by a collaboration grant from the Department of Environmental Science and Analytical Chemistry, Stockholm University and by Lipidor AB, Sweden. We acknowledge Gunvor Larsson from Bergianska Trädgården for help with identifying the plant species and Amelie Kierkegaard, Michael McLachlan, Philipp Mayer, and Margaretha Adolfsson Erici for advice on the experimental setup and helpful discussions. We also thank the four anonymous reviewers, whose critical comments helped to improve the quality of this paper significantly.

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REFERENCES

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