Environ. Sci. Technol. 2005, 39, 3455-3463
PCBs and Selected Organochlorine Compounds in Italian Mountain Air: the Influence of Altitude and Forest Ecosystem Type FODAY M. JAWARD,† A N T O N I O D I G U A R D O , * ,‡ LUCA NIZZETTO,‡ CHIARA CASSANI,‡ FRANCESCA RAFFAELE,§ ROSSELLA FERRETTI,| AND KEVIN C. JONES† Department of Environmental Science, Institute of Environmental and Natural Sciences, Lancaster University, Lancaster, LA1 4YQ, United Kingdom, Environmental Modelling Group, Department of Structural and Functional Biology, University of Insubria, Via J. H. Dunant 3, 21100 Varese VA, Italy, Department of Environmental Science, University of Milan - Bicocca, Milan, Italy, and Department of Physics, University of L’Aquila, L’Aquila, Italy
Passive air samplers (polyurethane foam disks) were deployed on an altitudinal transect in the rural Italian Alps to investigate the potential influence of forest cover on air concentrations. Samplers were exposed over two periods, each of several weeks, either in clearings or in forests. In the first period, there was high leaf coverage (high leaf area index, LAI); in the second, the LAI was low after the autumnal leaf fall. PCBs sequestered in the PUF generally declined with altitude, for example, in the clearings PCBs28, 52, 90/101, 118, and 138, all showed statistically significant declines (p < 0.05). The mass of HCB sequestered increased with altitude, evidence of cold condensation. Ratios of the forest:clearing concentrations were calculated; this ratio expresses the filtering ability of forests to deplete air concentrations compared to the adjacent clearings. During the high LAI sampling period, these depletion factors ranged between 0.93 and 0.54 and were inversely correlated with temperature-corrected log KOA. This relationship was not observed during the low LAI sampling period. The depletion factors were normalized using the LAI to give a density independent depletion factor (DIDF). The slopes of the correlations with KOA were comparable for broadleaf or coniferous forests at different altitudes, suggesting that leaf surfaces determine the exchanges with air. Broadleaf forests at 1000 and 1400 m showed similar behavior, while a conifer forest at 1800 m gave depletion factors which were higher by about a factor of 2. It is suggested that DIDF can be used in regional environmental fate models to estimate the contribution of forests to contaminant fate. * Corresponding author phone: +39-0332-421544; +39-0332-421554; e-mail:
[email protected]. † Lancaster University. ‡ University of Insubria. § University of Milan - Bicocca. | University of L’Aquila. 10.1021/es048160o CCC: $30.25 Published on Web 04/08/2005
2005 American Chemical Society
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Introduction Persistent organic pollutants (POPs) can undergo long-range atmospheric transport (LRAT) and temperature-dependent air-surface exchange (1), leading to the suggestion that mountain environments may receive POPs via cold condensation processes, in much the same way as latitudinal transfers to polar regions have been the focus of global redistribution studies (e.g., refs 2-6). However, an understanding of the potential for mountain regions to act as sinks is complicated, because there are many variables which will affect the delivery and retention of POPs in alpine systems. These include complex meteorology; gradients in soil and vegetation properties between valley flood plains and mountain peaks; potential sources of POPs in the generally more populated valleys, compared to the slopes/peaks; intermittent snow/ice coverage; and so forth. In alpine systems, forests may represent an important compartment, capable of intercepting the movement of POPs to higher altitudes and retaining them in organic matter rich forest soils (7-9). Vegetation acts as an intermediate compartment for exchange of POPs between the atmosphere and soils, with potential implications for global cycling (5, 10, 11). Experimental observations show that forest canopies can filter POPs from the atmosphere and increase contaminant deposition to the forest floor (7, 8). A model on this effect was developed by considering the ratio between predicted deposition fluxes under canopies and in clearings (12). Simulations predicted that airborne chemicals with log KOA between 7 and 11 (octanol-air partition coefficient is the ratio of the solute concentration in air versus octanol when the octanol-air system is at equilibrium) and KAW > -6 may undergo a pronounced filtering by the forests (air-water partition coefficient is the ratio of the solute concentration in air versus water when the air-water system is at equilibrium). So far, the number of field measurements quantifying this effect is very limited, and the magnitude, variability, and mechanisms of this process are not well characterized. Deposition to vegetation is a key process occurring at the air-soil interface, but a temperaturedependent volatilization to the atmosphere has been observed (13, 14). Thus, vegetation appears to be a dynamic compartment, capable of influencing contaminants in the surrounding environment (10). The purpose of this study was to assess atmospheric concentrations of PCBs and selected OC compounds from two separate sampling campaigns in Mont Mars (7001800 m above sea level), a part of the European Alps in Italy, using a passive air sampling network to determine the atmospheric contamination profile. Europe has seen widespread past and ongoing usage and emission of POPs. The principal altitudinal gradients/variables of interest in the alpine ecosystem were temperature, the changes in vegetation (notably forest) type, and the origins of air masses. Polyurethane foam (PUF) samplers, used widely in a range of recent studies (e.g., refs 15-19), were deployed to integrate air concentrations over periods of several weeks. In addition, conventional active high volume (hi-vol) air samplers were deployed simultaneously at one of the sites to compare with atmospheric profiles/concentrations derived from the passive samplers.
Materials and Methods Air Sampling, Extraction, and Analysis. The PUF disk samplers have been described previously (e.g., refs 15-19). They were deployed in sheltered chambers, as shown in VOL. 39, NO. 10, 2005 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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TABLE 1. Forest Species Composition and Leaf Area Index (LAI) ( Standard Deviation at Each Site Measured in Sampling Period C1
site name
dominant species (estimated relative abundance)
LAI (m2 m-2)
Fontainemore (700 m asl) Chuchal (1010 m asl) chestnut tree (33%) 3.86 ( 0.27 hazel tree (33%) maple (33%) Caumarial (1420 m asl) beech (90%) 4.78 ( 0.17 spruce (10%) Leretta (1790 m asl) larch (95%) 1.74 ( 0.23 spruce (5%)
FIGURE 2. Model configuration: domain 1 (D1) at resolution of 27 km; domain 2 (D2) at resolution of 9 km; domain 3 (D3) at resolution of 3 km. The black dot indicates the Lys Valley. The model topography is in gray bold lines (c.i. ) 500 m). FIGURE 1. Sampling sites and experimental design. Jaward et al. (16). PUF disks were transferred to the sampling locations in sealed, solvent-cleaned brown glass jars. The samplers were only assembled at the deployment sites to avoid contamination during transit. The sampling involved two separate campaigns, C1 and C2. To be able to compare sequestered amounts between the two sampling campaigns, care was taken to deploy, store, and extract the PUF disks in exactly the same way. In C1, a total of 39 samplers were successfully deployed for 52 days (from September 1 to October 22, 2003) at 13 sites. Campaign C2 consisted of 36 samplers deployed for 33 days (from October 22 to November 23, 2003) at 12 sites. The sampling location and experimental design is shown in Figure 1. Sampling sites were chosen at four different altitudes (700, 1000, 1400, and 1800 m asl). All sites were located within a few km along the east side of the Lys Valley (Valle d’Aosta, Italy) (Figure 1) to try to normalize exposure conditions. Each site, with the exception of the one at 700 m, included forested and meadow areas (from now on called clearings). Forest areas were characterized by different vegetal associations, each one representative of the particular altitude as described in Table 1. Sampling at 700 m was performed in a meadow inside the small village of Fontainemore. All the other sampling sites were away from direct exposure to local sources or human activity. Samplers were deployed in triplicate at each site in each campaign. At the end of the deployment period, the PUF disks were retrieved, resealed in their original solvent-cleaned brown glass jars at the sampling locations, and returned by courier to Lancaster University. During the deployment of passive samplers in campaign C2, a conventional active high volume (hi-vol) air sampler 3456
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was deployed simultaneously at one of the sites (1400-m clearing). Active air samples of ∼330-600 m3 of air were collected over ∼3-4 days per sample, aspirated through a glass fiber filter (GFF) to remove particles from the air stream. The gas-phase compounds were trapped on two polyurethane foam (PUF) plugs contained in an aluminum cylinder. This site also had 18 PUF disks placed randomly in an area of ∼300 m2, to assess within-site variability and sampler reproducibility. After sampling, the PUF plugs and GFFs were returned by courier to Lancaster University in solvent-rinsed glass jars. On receipt in Lancaster, they were stored frozen until extraction. The PUF plugs and GFFs from each hi-vol sampling site were combined. The hi-vol samples and PUF disks were Soxhlet extracted using DCM. Prior to extraction, each sample was spiked with a range of 13C12-labeled PCB congeners (13C12 PCB 28, 52, 101, 138, 153, and 180) to monitor the extraction and cleanup procedures which have been described elsewhere (16). Samples were reduced to a final volume of 25 µL under a gentle stream of nitrogen and solvent exchanged to 25 µL of dodecane containing PCB-30 and 13C12 PCB-141 as internal standards. The samplers were analyzed for PCBs and OC compounds by GC-MS on a Fisons MD800 operated in electron ionization mode using selected ion monitoring (see refs 20, 21 for details). A total of 29 PCB congeners (PCB-18, PCB-22, PCB-28, PCB-31, PCB-41/46, PCB-44, PCB-49, PCB-52, PCB-60/56, PCB-70, PCB-74, PCB-87, PCB-90/101, PCB-95, PCB-99, PCB-105, PCB-110, PCB-118, PCB-132, PCB-138, PCB-141, PCB-149, PCB-151, PCB-153, PCB-158, PCB-174, PCB-180, PCB-183, and PCB-187) and 5 OC compounds (HCB, o,p′-DDT, o,p′-DDE, p,p′-DDE, and p,p′-DDT) regularly detected in samples were quantified using an internal
TABLE 2. Summary of Results (pg day-1). Average Temperatures (°C) at Each Sampling Time Are Also Reported
average T
700-Ca C1 12.9
700-C C2 6.5
1000-F C1 11.3
1000-F C2 3.5
1000-C C1 12
1000-C C2 3.9
1400-F C1 8.3
1400-F C2 1.6
1400-C C1 8.9
1400-C C2 1.6
1800-F C1 7.1
1800-F C2 0.6
1800-C C1 8.1
1800-C C2 1.8
PCB 28 PCB 52 PCB 90/101 PCB 118 PCB 138 PCB 153 PCB 158 PCB 180 HCB p,p′-DDE p,p′-DDT
30 42 40 23 22 20 2 5 120 19 14
23 20 14 7.2 6 6 1 1.3 120 13 6
17 16 12 4.2 6 7
