Dechlorane Plus and Other Flame Retardants in Tree Bark from the

The geographical concentration gradient of Dechlorane Plus in pine tree bark ..... with map making and all the people who helped with tree bark sampli...
1 downloads 0 Views 835KB Size
Research Dechlorane Plus and Other Flame Retardants in Tree Bark from the Northeastern United States XINGHUA QIU AND RONALD A. HITES* School of Public and Environmental Affairs, Indiana University, Bloomington, Indiana 47405

Received August 15, 2007. Revised manuscript received October 10, 2007. Accepted October 18, 2007.

Previous work has shown that certain parts of the Great Lakes region are polluted with Dechlorane Plus (DP), a highly chlorinated flame retardant that was used as a replacement for Dechlorane/Mirex. It was suspected that a source of DP to the environment might be its manufacturing facility located in the city of Niagara Falls, New York. To confirm this source location and to determine DP’s spatial distribution, 26 tree bark samples were collected in triplicate from the northeastern United States, and the concentrations of DP and several brominated flame retardants (BFRs) were measured. Most concentrations of DP in tree bark were found to be much higher than those of the BFRs. The highest DP concentrations were >100 ng g-1 bark in the city of Niagara Falls, dropping rapidly with distance from the potential source. A simple one-dimensional, Gaussian diffusion model was used to explain the spatial distribution of DP and to locate the source. The calculated source location was 98%). BDE-209 from AccuStandard was certified with samples from both the National Institute of Standards and Technology (NIST) and Wellington Laboratories. All the solvents used for the extraction and cleanup procedures were residue-analysis grade. Sample Preparation. A previous method (12) was modified for this research. In brief, approximately 20–30 g of bark sample was cut into pieces of 30 ng g-1 bark (see Table 1) are from diluted samples. Quality Control. Several quality control criteria were used to ensure the correct identification and quantitation of the target compounds: (a) The GC retention times matched those of the standard compounds within ( 0.1 min. (b) The signalto-noise ratio was greater than 5:1. (c) The isotopic ratios for selected ion pairs were within ( 15% of the theoretical values. The recovery of surrogate standards (mean ( standard deviation) was 73 ( 11%, 69 ( 16%, and 64 ( 19% for BDE77, BDE-166, and 13C12-BDE-209, respectively. The recovery of matrix spiked samples was 88 ( 13%, 95 ( 5%, 100 ( 4%, 94 ( 8%, and 92 ( 16% for DP, BDE-47, BDE-99, BDE-209, and TBE, respectively. One procedural blank was also run with each batch of samples. All the compounds in the blank samples were undetected or less than 1% of the average value measured in tree bark samples, except BDE-47 and BDE-99, which were 4% and 6% of average concentration in tree bark samples, respectively (see Supporting Information). In this paper, concentrations have not been blank or recovery corrected.

Results and Discussion Concentrations of DP and BFRs in Tree Bark Samples. The concentrations of DP (reported as the sum of the syn- and anti-DP isomers), PBDEs (reported as the sum of the 17

congeners listed above), TBE, and DBDPE are given in Table 1. The concentrations were normalized to grams of tree bark; the percent lipid is also given in Table 1. These reported average concentrations and standard deviations for each target compound are from the triplicate bark samples collected at each site. Given that none of these flame retardants are directly applied to trees, it seems likely that all of these compounds accumulated in the tree bark by way of atmospheric transport. Figure 1 shows the location of the sampling sites and the corresponding concentrations of DP measured at each site. In general, the higher concentrations (>4 ng g-1 bark) were found in or around the Niagara Falls and Buffalo areas of New York state. The highest concentration (115 ng g-1 bark) was found in the Hyde Park neighborhood, a location which is ∼2 km away from OxyChem’s DP manufacturing facility. With increasing distance from this potential source location, the concentrations of DP in tree bark decreased rapidly, but DP was still detected at low levels (0.03–0.04 ng g-1 bark) in samples from Virginia, Maryland, and Indiana. Gaussian Diffusion Model for DP. It has been shown that concentrations of PCBs in tree bark decreased rapidly with increasing distance from Superfund sources; concentrations dropped by a factor of about 10 within 11 km (14) and by a factor of 40 within 14 km (13). In another study, PCB concentrations dropped by a factor of >1,000 within ∼7 km of a major PCB source (15). Safe et al. also found a rapid decrease in total PCDD/F levels in pine needles with increasing distance from a source, and the level of octachlorodibenzo-p-dioxin dropped by a factor of 6 within 1 km of the site’s perimeter (19). All of these studies indicated that vegetation could be used to generally locate pollutant sources. To describe the spatial distribution of toxaphene in tree bark more exactly and to pinpoint its source location, McDonald and Hites created a VOL. 42, NO. 1, 2008 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

9

33

pollutant at a point in space (x,y,z) (in these coordinates, x is the downwind direction, y is the crosswind direction, z is the vertical direction, and the source location is at the origin); Q is the source strength; u is the average wind speed; h is the height of the source; and σy and σz are the lateral and vertical diffusion coefficients, respectively. In this study, we assume that the source is near ground level, and thus, h ) 0. In fact, there is not much difference in the concentration-distance profile between a ground level source and a 100 m high source, when the distances from the source were >2 km (21). Thus, for a downwind ground site, eq 1 can be simplified to Cair(x, 0, 0) )

Q πuσyσz

(2)

The diffusion coefficients, σy and σz, are a function of the downwind distance, x, and are influenced by many factors, including atmospheric stability. Approximately, these coefficients can be expressed by σy ) γ1xa1

(3)

σz ) γ2xa2

(4)

where a1, a2, γ1, and γ2 are parameters describing the diffusion coefficients; these parameters will have different values depending on atmospheric stability, usually given by Pasquill’s turbulence type (22, 24). Combining eqs 2–4, we get Cair(x, 0, 0) )

(

)

Q x-(a1+a2) πuγ1γ2

(5)

In this study, the DP in tree bark was accumulated over the 5–10 years the bark sample was on the tree, and the annualized wind roses in the source region are relatively symmetrical (25). This suggests that, over a relatively long time period, DP is likely to be carried by air movement in all directions. Thus, it is reasonable to assume that all of our sampling sites are located downwind from the source, and we can replace the downwind distance, x, with the distance from the source to sampling site i, which is given by FIGURE 2. Concentrations (in ng g-1 bark) of DP in tree bark as a function of spherical Euclidian distance (in km) from the OxyChem plant in Niagara Falls, NY (top); concentrations of DP as a function of distance from the calculated source using eq 10 (middle); fanti value at each sampling site (using the distance from the OxyChem plant). The red dotted line indicates the isomeric composition of the commercial DP product. The errors shown are one standard deviation for triplicate samples. simple dilution model (12). This model also successfully explained the spatial distribution of PBDEs in North America (16). However, this model neglected the advective transport process of a pollutant as it moves through the atmosphere. We have improved on this simple dilution model by including advective transport. In this field, Gaussian diffusion models are widely used to describe the regional distribution of inert gaseous pollutants and aerosols (20–22). The theory of this model is based on the normal (or Gaussian) statistical distribution function. Briefly, for a continuous-point source of a certain pollutant, the spatial distribution can be described by (23) Cair(x, y, z) )

(

)

( ){ (

-y2 Q exp 2πuσyσz 2σy2

exp

)

-(z + h)2 + 2σz2

(

exp

-(z - h)2 2σz2

)}

(1)

where Cair(x,y,z) is the steady-state air concentration of a 34

9

ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 42, NO. 1, 2008

di ) 6373arccos[sin(lati)sin(latsor) + cos(lati)cos(latsor)cos(|loni - lonsor|)] (6) where lati and latsor are the latitudes of the sampling and source locations, respectively; loni and lonsor are the longitudes of the sampling and source locations, respectively; and the factor of 6373 converts from radians to kilometers. During a long period, the source strength, Q, the average wind speed, u, and γ1 and γ2 in eq 5 can be assumed to be constant. Thus, the concentrations of DP in tree bark as a function of distance from its source are given by Cbark,i ) Ka,barkCair,i ) Ka,bark

(

)

Q d -(a1+a2) ) K ′ di-(a1+a2) πuγ1γ2 i (7)

where Ka,bark is a bark-air partition coefficient, an idea that comes from vegetation-atmosphere partitioning (26) and is a function of the ambient atmospheric temperature (27). Here this coefficient will be considered a constant because all of the samples were exposed to DP during the same period and all were collected at the same time. Note that all of the constants in eq 7 are gathered together in the new constant, K′. Taking logarithms of both sides, we get log(Cbark,i) ) -(a1 + a2)log(di) + logK′

(8)

In fact, eq 8 is similar to the previously proposed radial

TABLE 2. Locations of Tree Bark Samples from Canada, Europe, and Asia, Sampling Dates, Concentrationsa of DP (fanti), PBDEs (BDE-209), TBE, and DBDPE (average ± standard deviation, in ng g-1 bark), and Lipid Fraction (% ± standard deviation) sampling site

sampling date

Southern Northwest Territories, Canada Halle, Germany Trieste, Italy Hanam, South Korea Shenzheng, China Hangzhou, China Tianjin, China

June2000 May 2005 April2005 April2005 May 2007 May 2007 May 2007

PBDEsb (BDE-209)

DP (fanti)

0.043 ( 0.009 (0.007)

NDc 0.032 ( 0.019 (0.73) 0.067 ( 0.032 (0.74) 1.4 ( 1.5 (0.77) 0.30 ( 0.16 (0.76) 0.23 ( 0.02 (0.70) 0.18 ( 0.12 (0.69)

1.8 ( 0.6 (1.6) 0.27 ( 0.01 (0.12) 8.1 ( 6.2 (6.5) 48 ( 22 (43) 21 ( 2 (19) 15 ( 7 (14)

TBE ND 0.006 ( 0.001 0.025 ( 0.005 1.8 ( 0.8 1.1 ( 1.2 0.08 ( 0.07 0.5 ( 0.2

DBDPE

lipids

ND

7.2 ( 1.3

ND ND 1.1 ( 1.4 30 ( 4 3.1 ( 0.9 2.9 ( 1.1

5.7 ( 0.6 2.0 ( 1.9 3.2 ( 0.3 2.9 ( 1.4 2.6 ( 0.02 4.3 ( 1.4

a Each concentration is the average of triplicate samples, except for Trieste, Italy, Hanam, South Korea, and Hangzhou, China, which are the average of duplicate samples. b PBDEs include BDE-28, 47, 99, 100, 153, 154, 183, 196, 197, 198, 201, 203, 204, 206, 207, 208, and 209. c ND, not detected; those not detected or partly detected in replicate samples were considered as “not detected”.

dilution model (12) log(Cbark,i) ) -2log(di) + const

(9)

The only difference is that the fixed exponent of 2 in the radial diffusion model has been replaced here with the variable exponent (a1 + a2), the value of which will depend mainly on atmospheric stability. Using Pasquill’s stability classes, a1 ranges from 0.59 (moderately stable conditions) to 0.90 (extremely unstable conditions), and R2 ranges from 0.50 (moderately stable conditions) to 1.38 (extremely unstable condition) (24). Thus, the exponent (a1 + a2) could range from 1.1 to 2.3, but for the most typical case (neutral conditions), (a1 + a2) would be ∼1.5. We have implemented this calculation in two ways: First, we assumed that the DP source was, in fact, the OxyChem manufacturing facility located in Niagara Falls at 43.077° N, 79.009° W. By fitting the log-transformed concentrations with log-transformed distances, we could determine the values of K′ and (a1 + a2). The results were K′ ) 102.5 and (a1 + a2) ) 1.33 with a correlation coefficient (r2) between the observed and expected values of 0.853; see Figure 2 (top). Second, we assumed that we did not know the location of the source, and we let the values of latsor and lonsor float or vary in eq 6 to calculate the various values of di. For each sample, we had measured Ci values (the concentrations of DP in the tree bark sample taken at sampling site i), and we had calculated di. We then minimized ξd as given by ξd )

∑ [K ′ d

-(a1+a2)

i

- Ci]2

(10)

i

This is the approach used previously (12, 16). With the assistance of the Solver feature of Excel, the fitted variables for the DP data set were obtained. The results were K′ ) 102.7, (a1 + a2) ) 1.42, latsor ) 43.124° N, and lonsor ) 78.953° W, with an r2 between the observed and expected values of 0.872; the result is shown in Figure 2 (middle). This fitted location is less than 7 km northeast of the OxyChem plant. Despite the uncertainties of this approach, we can surely conclude that DP’s source is located in Niagara Falls, New York. In this research, the calculated exponent (R1+R2) was ∼1.4, which suggests an average atmospheric stability between neutral conditions [(R1+R2) ) 1.49] and slightly stable conditions [(R1+R2) ) 1.30] (24) over a long time period. This value was less than that observed for the distribution of PBDEs in tree bark (1.73), which was based on a point source located in southern Arkansas (16). This difference might suggest, on average, that the atmospheric conditions are less stable in the central United States than in the northeastern United States, although other factors, such as additional sources and different topographic conditions, cannot be excluded. Technical DP has two conformational isomers: syn (Ushaped) and anti (chair-shaped) (6). The fractional abun-

dance (fanti) of the anti isomer (defined as the concentration of the anti isomer divided by the sum of the concentration of syn and anti isomers) is 0.75 in the technical product as measured in our laboratory. Incidentally, although there are three industrial formulations of the technical DP product, they differ only in the particle size and not in composition (28). The spatial distribution of fanti in tree bark is shown in Figure 2 (bottom) as a function of distance from the source. There is no obvious trend of fanti values with the increasing distance. The average fanti in all the tree bark samples is 0.76, which is close to that in the technical product and suggests that the two isomers have the same atmospheric persistence. This observation is different from the fate of these two isomers in sediment, where the anti isomer was found to be the more persistent (9). Other Brominated Flame Retardants. PBDEs, TBE, and DBDPE are brominated flame retardants, which are manufactured in the southcentral United States (16). Thus if these compounds are present in tree bark collected in the northeastern United States, they should have arrived there by long-range atmospheric transport from the manufacturing plants and by local use. Table 1 shows that the average concentrations of PBDEs, TBE, and DBDPE in our samples are 1.9, 0.11, and 0.28 ng g-1 bark, respectively (or 55, 3.2, and 8.5 ng g-1 lipid, respectively). These concentrations were much lower than those observed near the manufacturing plants in Arkansas (16), suggesting that-unlike DP-there is no strong point source for these BFRs in the northeastern United States. Within our data set, relatively high concentrations of BFRs were observed in tree bark from urban/suburban areas near Cleveland, Ohio and near Buffalo-Niagara Falls, New York. For instance, the highest concentration of TBE was found in bark from Cleveland, and the highest concentration of PBDEs was found in bark from Niagara Falls. Nevertheless, at most sites in the northeastern United States, the concentrations of DP were from 1 to 2 orders of magnitude higher than all of the BFRs combined; this is especially true in Niagara Falls. This observation is consistent with the relatively high concentrations of DP and relatively low concentrations of all other BFRs that we observed in a sediment core from Lake Ontario (9). DP and BFRs in Tree Bark Samples from Other Countries. To evaluate the global impact of DP and BFRs, we obtained and analyzed tree bark samples from other countries; the sampling information and results are shown in Table 2. DP was not detected in tree bark from the southern Northwest Territories in Canada; however, DP was detected in all the other samples from Europe and Asia. In Germany and Italy, DP concentrations were similar to the lowest concentrations we measured in bark from the northeastern United States; in China and Korea, DP concentrations were nearly 1 order of magnitude higher than the lowest conVOL. 42, NO. 1, 2008 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

9

35

centrations in the northeastern United States. This latter observation suggests that there may be Asia-specific sources of DP to the environment. In all these “foreign” samples, the fanti was 0.73 on average, which is close to that measured in technical DP (0.75). This indicates a similar fate of the two DP isomers in the atmosphere. PBDEs, TBE, and DBDPE were also detected in most of the samples from Europe and Asia. It is notable that the concentrations of PBDEs (especially BDE-209) and DBDPE were high in tree bark samples from China, especially in those from Shenzheng (see Table 2). For instance, BDE-209 was found in tree bark from Shenzheng at a concentration of 43 ng g-1 bark (or ∼1500 ng g-1 lipid), which was similar to the BDE-209 concentration measured in tree bark collected near its manufacturing facility in Arkansas (16). BDE-209 is now produced in China; in fact, between the years 2000 and 2005, BDE-209 production increased from 10,000 to ∼30,000 t (29). It is interesting to note that Shenzheng is located in the Pearl River Delta, which is the largest electronic and telecommunication equipment manufacturing region in China. It is perhaps not too surprising that high concentrations of BDE-209 are detected in tree bark and in other environmental media, such as sediment (30), from this region.

Acknowledgments This work was supported by the Great Lakes National Program Office of the U.S. Environmental Protection Agency (Grant GL995656, Melissa Hulting, Project Officer). We also thank Marta Venier for her assistance with map making and all the people who helped with tree bark sampling.

Supporting Information Available Tables of analytical data by sample. This material is available free of charge via the Internet at http://pubs.acs.org.

Literature Cited (1) Hites, R. A. Polybrominated diphenyl ethers in the environment and in people: A meta-analysis of concentrations. Environ. Sci. Technol. 2004, 38, 945–956. (2) Ikonomou, M. G.; Rayne, S.; Addison, R. F. Exponential increases of the brominated flame retardants, polybrominated diphenyl ethers, in the Canadian arctic from 1981 to 2000. Environ. Sci. Technol. 2002, 36, 1886–1892. (3) Renner, R. In U.S, flame retardants will be voluntarily phased out. Environ. Sci. Technol. 2004, 38, 14A. (4) Birnbaum, L. S.; Staskal, D. F. Brominated flame retardants: Cause for concern. Environ. Health. Perspect. 2004, 112, 9–17. (5) Kaiser, K. L. E. Pesticide report: The rise and fall of Mirex. Environ. Sci. Technol. 1978, 12, 520–528. (6) Hoh, E.; Zhu, L. Y.; Hites, R. A. Dechlorane Plus, a chlorinated flame retardant, in the Great Lakes. Environ. Sci. Technol. 2006, 40, 1184–1189. (7) Tomy, G. T.; Pleskach, K.; Ismail, N.; Whittle, D. M.; Helm, P. A.; Sverko, E.; Zaruk, D.; Marvin, C. H. Isomers of Dechlorane Plus in Lake Winnipeg and Lake Ontario food webs. Environ. Sci. Technol. 2007, 41, 2249–2254. (8) Gauthier, L. T.; Hebert, C. E.; Weseloh, D. V. C.; Letcher, R. J. Current-use flame retardants in the eggs of herring gulls (Larus argentatus) from the Laurentian Great Lakes. Environ. Sci. Technol. 2007, 41, 4561–4567. (9) Qiu, X. H.; Marvin, C. H.; Hites, R. A. Dechlorane Plus and other flame retardants in a sediment core from Lake Ontario. Environ. Sci. Technol. 2007, 41, 6014–6019.

36

9

ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 42, NO. 1, 2008

(10) Gouin, T.; Harner, T.; Blanchard, P.; Mackay, D. Passive and active air samplers as complementary methods for investigating persistent organic pollutants in the Great Lakes basin. Environ. Sci. Technol. 2005, 39, 9115–9122. (11) Simonich, S. L.; Hites, R. A. Relationships between socioeconomic indicators and concentrations of organochlorine pesticides in tree bark. Environ. Sci. Technol. 1997, 31, 999–1003. (12) McDonald, J. C.; Hites, R. A. Radial dilution model for the distribution of toxaphene in the United States and Canada on the basis of measured concentrations in tree bark. Environ. Sci. Technol. 2003, 37, 475–481. (13) Meredith, M. L.; Hites, R. A. Polychlorinated biphenyl accumulation in tree bark and wood growth rings. Environ. Sci. Technol. 1987, 21, 709–712. (14) Hermanson, M. H.; Hites, R. A. Polychlorinated biphenyls in tree bark. Environ. Sci. Technol. 1990, 24, 666–671. (15) Hermanson, M. H.; Johnson, G. W. Polychlorinated biphenyls in tree bark near a former manufacturing plant in Anniston, AL. Chemosphere 2007, 68, 191–198. (16) Zhu, L. Y.; Hites, R. A. Brominated flame retardants in tree bark from North America. Environ. Sci. Technol. 2006, 40, 3711– 3716. (17) Sturaro, A.; Parvoli, G.; Doretti, L. Plane tree bark as a passive sampler of polycyclic aromatic hydrocarbons in an urban environment. J. Chromatogr. 1993, 643, 435–438. (18) Clarkson, P. J.; Larrazabal-Moya, D.; Staton, I.; McLeod, C. W.; Ward, D. B.; Sharifi, V. N.; Swithenbank, J. The use of tree bark as a passive sampler for polychlorinated dibenzo-p-dioxins and furans. Int. J. Environ. Anal. Chem. 2002, 82, 843–850. (19) Safe, S.; Brown, K. W.; Donnelly, K. C.; Anderson, C. S.; Markiewicz, K. V.; McLachlan, M. S.; Reischl, A.; Hutzinger, O. Polychlorinated dibenzo-p-dioxins and dibenzofurans associated with wood-preserving chemical sites: biomonitoring with pine needles. Environ. Sci. Technol. 1992, 26, 394–396. (20) Overcamp, T. J. A general Gaussian diffusion-deposition model for elevated point sources. J. Appl. Meteorol. 1976, 15, 1167– 1171. (21) Pasquill, F. The estimation of the dispersion of windborne material. Meteorol. Mag. 1961, 90, 33–49. (22) Gifford, F. A. Chapter 3: An outline of theories of diffusion in the lower layers of the atmosphere. In Meteorology and Atomic Energy; U.S. Atomic Energy Commission, 1968. (23) Seinfeld, J. H.; Pandis, S. N. Chapter 18: Analytical solutions for atmospheric diffusion. The Gaussian plume equation and other. In Atmospheric Chemistry and Physics;John Wiley & Sons, Inc.: New York, 1998. (24) Klug, W. A method for determining diffusion conditions from synoptic observations. Staub-Reinhalt. Luft 1969, 29, 14–20. (25) National Oceanic and Atmospheric Administration. Climatic Atlas of the United States; 1983. (26) Simonich, S. L.; Hites, R. A. Vegetation-atmosphere partitioning of polycyclic aromatic hydrocarbons. Environ. Sci. Technol. 1994, 28, 939–943. (27) Simonich, S. L.; Hites, R. A. Organic pollutant accumulation in vegetation. Environ. Sci. Technol. 1995, 29, 2905–2914. (28) OxyChem Chemical Segment Homepage. http://www.oxy.com/ OXYCHEM/Products/dechloranep ¯lus/dechloranep ¯lus.htm. (Accessed March 8, 2006). (29) Zhou, Z. M. Implement of Administrative Measure on the Control of Pollution Caused by Electronic Information Products and the exemption of deca-BDE mixture. Flame Retard. Meter. Technol. 2006, 4, 15–16 (in Chinese). (30) Mai, B. X.; Chen, S. J.; Luo, X. J.; Chen, L. G.; Yang, Q. S.; Sheng, G. Y.; Peng, P. A.; Fu, J. M.; Zeng, E. Y. Distribution of polybrominated diphenyl ethers in sediments of the Pearl River Delta and adjacent South China Sea. Environ. Sci. Technol. 2005, 39, 3521–3527.

ES072039A