Relationships between Socioeconomic Indicators and Concentrations

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Environ. Sci. Technol. 1997, 31, 999-1003

Relationships between Socioeconomic Indicators and Concentrations of Organochlorine Pesticides in Tree Bark STACI L. SIMONICH† AND RONALD A. HITES* School of Public and Environmental Affairs and Department of Chemistry, Indiana University, Bloomington, Indiana 47405

This paper suggests that, barring very long-range transport, global environmental concentrations of organochlorine pesticides are proportional to the socioeconomic status of the country (or region) from which the samples were taken. We tested this hypothesis by the following experiment: Over 200 tree bark samples were collected from 32 countries (or isolated regions of countries) and analyzed for 22 pesticides, including active ingredients and degradation products. The Gross National Product per person and the Human Development Index of the various countries were used as socioeconomic indicators. Regression analysis indicated that hexachlorobenzene, trans-nonachlor, and dieldrin concentrations were highly correlated with the GNP per person and the Human Development Index. In general, the poorest counties, such as Togo, Ghana, and Uganda, showed the least amount of pesticide contamination in tree bark, while some industrialized countries, such as those in northern Europe, showed the highest levels of organochlorine pesticides.

Introduction Barring very long-range atmospheric transport, the environmental concentrations of organochlorine pesticides (such as endosulfan and DDT) should be proportional to the use of these compounds in the region where the samples are taken. For example, because most economically well-developed countries have banned the use of organochlorine pesticides, one might expect the current environmental concentrations of these compounds in these countries to be relatively low. In some of the less well developed countries, where organochlorine pesticides are still widely used (1, 2), one might expect the environmental concentrations of these compounds to be relatively high. In the very poorest countries, where the farmers cannot afford to purchase pesticides, one might expect the environmental concentrations of almost all pesticides to be very low. In essence, the organochlorine pesticide concentrations in the environment of a given country (or region) should depend on its socioeconomic status. This hypothesis has been explored by Calamari and coworkers, who have related the environmental concentrations of a few pesticides in vegetation to socioeconomic indicators (3, 4). They have shown that the concentrations of R- and † Present address: The Procter & Gamble Company, Environmental Science Department, 5299 Spring Grove Ave., Cincinnati, OH 452171087. * Corresponding author e-mail address: [email protected].

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 1997 American Chemical Society

γ-hexachlorocyclohexanes (HCHs) and hexachlorobenzene (HCB) in lichens, moss, mango leaves, and pine needles are related to the Gross National Product per person (GNPpp) of the country in which the samples were taken (3). In 23 countries, these authors found that the logarithm of the GNPpp was a linear predictor of the logarithm of the vegetation concentrations of these three compounds. These authors also tried to relate these concentrations to the Human Development Index (HDI) of the country in which the vegetation sample was collected, but the results were equivocal (3). In general, Calamari et al. (3, 4) showed that the vegetation in wealthy, industrialized countries is likely to have higher levels of some organochlorine pesticides as compared to vegetation in poorer countries. Our goal was to test this relationship for a wider range of organochlorine pesticides, which we have shown accumulate in tree bark (5), and for a wider range of locations. We also wanted to determine the relationship (if any) of these pesticide concentrations to the HDI. Specifically, we measured 22 pesticides, including active ingredients and degradation products in over 200 tree bark samples taken from 32 countries (or isolated regions of countries; for example, Hawaii) around the world. The pesticides were four hexachlorocyclohexanes (HCHs), hexachlorobenzene (HCB), pentachloroanisole (PCA) (a degradation product of pentachlorophenol), dieldrin, three endosulfans, six chlordanes, two endrins, aldrin, and p,p′DDT (and its degradation products p,p′-DDE and p,p′-DDD). Some of these compounds are still in use throughout the world (endosulfan), while others have been banned in almost all countries (DDT). We decided to use tree bark to study the global distribution of organochlorine pesticides because bark is an excellent accumulator of lipophilic organic pollutants from the atmosphere given its surface area and associated lipids (6, 7). Tree bark is also present throughout the world, and on average, it contains more lipids per unit area than other forms of vegetation (6, 7). Tree bark is also present at all times of the year, and since it is on the tree for 3-5 years (8), it integrates lipophilic organic pollutants over an extended time. These characteristics make tree bark an excellent sink for lipophilic organic pollutants even at low atmospheric concentrations (9).

Experimental Section Sample Collection. We collected or had collected over 200 tree bark samples from 32 countries (or regions) between 1992 and 1995. The exact locations of these sites have been reported elsewhere (5, 10). Remote or rural sites were generally chosen for collection, and permission was obtained from land owners, park rangers, or other officials. Samples were collected as described previously (7). A 5 cm × 20 cm area of outer bark was chiseled off the tree, wrapped in aluminum foil, and stored in a plastic bag. Two to three sites were usually sampled at the same time, and 3-6 samples were collected from different species of trees at each site. A permit for importing tree bark samples into the United States was obtained from the United States Department of Agriculture, Animal and Plant Health Inspections Services. Samples were shipped by various worldwide carriers and were stored at -18 °C until extraction. Sample Extraction and Cleanup. Thirty to fifty grams (wet weight) of unground tree bark was spiked with an appropriate amount of six isotopically labeled internal standards (d6-γ-HCH, 37Cl6-heptachlor epoxide, d4-endosulfan I, 37Cl6-trans-nonachlor, d8-p,p′-DDE, and d8-p,p′-DDT) and Soxhlet extracted in 50% hexane in acetone for 24 h. All extracts were solvent exchanged to hexane and back-extracted

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TABLE 1. Average Concentrations (in ng/g of Tree Bark Lipids) of Pesticides in Tree Bark Taken from Various Countries and Regions from Around the Worlda N

rHCH

γHCH

Costa Rica 3 Togo 4 4 38 Belize 2 Ghana 4 Uganda 4 150 68 New Zealand 6 6 5 Ecuador 4 13 83 Spain 3 80 190 China 3 180 71 Sweden 3 160 150 Puerto Rico 4 19 58 Venezuela 9 24 250 Philippines 7 El Salvador 2 15 65 United Kingdom 3 33 410 Canada 4 580 160 Norway 5 880 180 Argentina 4 30 100 South Africa 5 77 140 Russia 4 360 460 Australia 14 25 27 South Korea 3 560 360 Denmark 4 430 860 Japan 8 250 130 United States 45 240 97 Iran 2 940 480 Brazil 6 660 880 Belgium 2 200 2000 Germany 3 370 3100 Netherlands 2 120 2000 India 9 2300 740 Romania 1 5700 13000

hep- oxytctendo endo endo HCB PCA epox chlor chlor chlor nona dieldrin I II sulf 2 6 9 12 4 20 22 26 8 50 14 18 11 21 57 56 100 31 13 27 23 59 160 120 46 66 93 58 180 120 25 370

2 7 15 49 150 16 9 28

4 53 7 19 110 2 6 43 7 64

20

1 14 4

8 4

60 12 62 23 10 14 14 18 30 26 37 95 25 42 126 132 23 36 119

15 6 22 4 50 16 100 43 57 9 36 39 42 26 11 54

4

3 1 3 11 16

1

62 17 26 21 16 160 42 42 71 43 76 54 89 540 400 33 80 100 150 130 96 250

6 60 3 20 1 2

24 30 64 1 33 11 6 28 25 33 340 190 15 37 72 10 55

1 1 16 5

1 2 5

16 9 1

75 12 7

3 18 25 6 14 6 23 8 8 5 7 18 19 19 380 220 7 29 18 30 28 43 26

10 58 100 9 110 66 17 12 38 40 8 170 13 110 110 220 19 160 150 180 190 48 220

DDT

DDE

DDD

1 6 2 2 1 14 12 15 8 4 14 6 4 17 54 21 7 5 62 4 6 4 32 170 68 12 10 60 79 200 22 13 47 6 2 2 14 170 120 6 3 23 18 83 37 48 270 31 6 4 42 94 53 15 38 29 540 26 110 160 280 86 21 30 260 15 22 6 71 11 16 2 35 5 510 160 420 36 38 33 150 120 200 590 22 20 87 160 96 360 41 44 110 940 130 690 130 220 1100 64 34 55 290 180 100 450 76 87 450 88 270 110 240 620 380 260 210 120 55 310 540 210 870 340 510 1200 300 330 450 380 770 1300 24 100 200 110 290 980 87 420 450 77 1100 3200 110 270 430 1500 1300 810 2200 180 100 300 12000 2700 13000

total pesticide 23 100 140 210 450 460 520 530 570 570 660 700 750 1000 1100 1100 1300 1400 1500 1700 2400 2600 2900 2900 3400 3700 5200 5600 6500 7100 9900 48000

a Abbreviations: R-HCH, R-hexachlorocyclohexane; γ-HCH, γ-hexachlorocyclohexane; HCB, hexachlorobenzene; PCA, pentachloroanisole; hepepox, heptachlor epoxide; oxy-chlor, oxychlordane; t-chlor, trans-chlordane; c-chlor, cis-chlordane; t-nona, trans-nonachlor; endo I, endosulfan I; endo II, endosulfan II; endo sulf, endosulfan sulfate; N, number of samples. In addition to these compounds, β- and δ-hexachlorocyclohexane and endrin aldehyde were also occasionally present but at such low levels to prevent quantitation. Heptachlor, aldrin, and endrin were not detected in any of the samples. Blank entries indicate that the compound was not detected at that location.

2-10 times with HPLC-grade water until the water fraction was no longer turbid. This removed polar interferents and improved the subsequent silica gel separation. The extract was then reduced to 1 mL in volume and purified using 25 cm long silica gel columns (deactivated with 1% water by weight). The pesticides were eluted from the column using 50 mL of hexane, 75 mL of 50% hexane in CH2Cl2, and 75 mL of CH2Cl2. Hexachlorobenzene eluted in the hexane fraction, and the majority of the other pesticides in the 50% hexane in CH2Cl2 fraction. All fractions were combined for analysis. Recoveries of known amounts of pesticides were 76-84% for the entire procedure. Reagent blanks (no tree bark) were analyzed with every other set of extractions, and the blank experiments were free of pesticides. Sample Analysis. Extracts were analyzed by electron capture, negative ionization, gas chromatographic mass spectrometry on a Hewlett Packard 5989A instrument. The instrument was equipped with a 30 m × 250 µm i.d. (0.25 µm film thickness) J&W Scientific (Folsom, CA) DB-5 fused silica capillary column. The ion source was maintained at 125 °C and at a CH4 pressure of 0.43 Torr (direct source reading). One microliter of the sample was injected splitless for 0.9 min after being concentrated to 200 µL under a gentle stream of N2. The gas chromatograph (GC) temperature program conditions were as follows: 40 °C held for 1 min, ramped at 30 °C/min to 130 °C, ramped at 3 °C/min to 241 °C, and ramped at 30 °C/min to 285 °C, and held for 10 min. The GC column head pressure was regulated at 15 psi. The instrumental detection limit ranged from 2 to 500 pg depending on the electron capture cross section of the analyte. The moisture and lipid contents of the tree bark samples were determined

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according to ref 7. The moisture content ranged from 2 to 70% by weight, and lipids ranged from 0.2 to 3% by weight. Statistical Analysis. Excel (Microsoft Corp., Seattle, WA) and Sigma Plot (Jandel Corp., San Rafael, CA) were used for the statistical analyses.

Results and Discussion The pesticide concentrations in tree bark are reported in nanograms of pesticide per gram of lipid. As we have shown previously, these units tend to minimize the variability among various tree species (7). The concentrations of the various pesticides are given in Table 1. Each concentration represents the average of the samples taken in a given country (or region). Note that the number of samples at a given location ranged from 1 in Romania to 45 in the United States. The last column of Table 1 is simply the total of the concentrations of each pesticide (or degradation product) given in the preceding 16 columns. Table 1 has been rank ordered by increasing total pesticide concentration in the bark samples. All of the pesticides measured in this study are ubiquitous on a global scale except for heptachlor, aldrin, and endrin, all of which degrade to other compounds (11, 12). On average, the DDTs, the HCHs, and the endosulfans were present in relatively high concentrations. The HCHs are used as pesticides either as the pure γ-isomer (commonly known as lindane) or as a technical mixture of different isomers. The use of the technical mixture is restricted in most developed countries, while lindane is not (1). The HCHs are commonly used on sugar cane, rice, and tomatoes and as a seed treatment (13, 14). Endosulfan is one of the last hexachlorocyclo-

TABLE 2. Socioeconomic Indicators for the Various Countries from Which Tree Bark Samples Were Collected

Costa Rica Togo Belize Ghana Uganda New Zealand Ecuador Spain China Sweden Puerto Rico Venezuela Philippines El Salvador United Kingdom Canada Norway Argentina South Africa Russia Australia South Korea Denmark Japan United States Iran Brazil Belgium Germany Netherlands India Romania

symbol

Human Development Index (HDI)

Gross National Product per person (GNPpp in $US)

CR To Bz Gh Ug NZ Ec Sp Ch Sw PR Ve Ph ES UK Ca Nw Ar SA Ru Au SK De Ja US Ir Br Bl Ge Ne In Ro

0.848 0.311 0.666 0.382 0.272 0.907 0.718 0.888 0.644 0.928 0.925 0.820 0.621 0.543 0.919 0.932 0.928 0.853 0.650 0.858 0.926 0.859 0.912 0.929 0.925 0.672 0.756 0.916 0.918 0.923 0.382 0.729

1 960 390 2 220 450 170 12 300 1 070 13 970 470 27 010 6 590 2 910 770 1 170 17 790 20 710 25 820 6 050 2 670 2 510 17 260 6 790 26 000 28 190 23 240 2 200 2 770 20 880 23 030 20 480 310 1 130

TABLE 3. Correlation Coefficients (r) between Logarithm of Individual Pesticide Concentrations in Tree Bark (see Table 1) versus Gross National Product per Person (GNPpp) and the Human Development Index (HDI) on a Country-by-Country Basisa GNPpp compound

all data

Ro, In, CR omitted

HDI all data

Ro, In, CR omitted

R-hexachlorocyclohexane 0.093 0.300 0.028 0.284 γ-hexachlorocyclohexane 0.136 0.304 0.074 0.282 hexachlorobenzene 0.596 0.788 0.519 0.718 pentachloroanisole 0.372 0.497 0.279 0.471 heptachlor epoxide 0.088 0.177 0.065 0.103 oxychlordane 0.283 0.270 0.264 0.293 trans-chlordane 0.356 0.499 0.183 0.347 cis-chlordane 0.261 0.347 0.105 0.222 trans-nonachlor 0.426 0.546 0.407 0.569 dieldrin 0.478 0.602 0.443 0.608 endosulfan I 0.278 0.426 0.232 0.425 endosulfan II 0.237 0.349 0.161 0.330 endosulfan sulfate 0.247 0.362 0.175 0.350 DDT -0.519 -0.130 -0.431 -0.149 DDE -0.010 0.165 0.046 0.265 DDD -0.042 0.359 0.035 0.404 a Those r values that are significant at the 99% confidence level are indicated in bold face.

pentadiene pesticides remaining in widespread use (13); the technical mixture of endosulfan contains approximately 70% endosulfan I and 30% endosulfan II (15). Endosulfan is used on most crops, including rice and fruit (13). Endosulfan sulfate comes from the environmental oxidation of endosulfan I and II.

FIGURE 1. Concentrations of hexachlorobenzene (HCB), transnonachlor, and dieldrin in tree bark (ng/g lipid) versus the gross national product per person. The country symbols are given in Table 2. Data for Costa Rica, India, and Romania have not been plotted or included in the regression. Bark samples from poorly developed countries (such as Togo, Ghana, and Uganda) show very low levels of pesticides. On the other hand, economically well developed countries such as the United States, Japan, Germany, and the Netherlands show relatively high levels of pesticides. Three countries, Costa Rica, India, and Romania, appear to be out of place in this sequence. India (with an average 9900 ng of total pesticides/g of tree bark lipid) is poorly developed, but our data indicate that large amounts of organochlorine pesticides are used. This is consistent with other authors’ findings for other environmental matrices (3, 16) and reports of chemical usage (1, 2). The tree bark from Romania had a very high total pesticide concentration of 48 000 ng/g of lipid. Although the Romanian data represent only one sample taken from Sibiu, a relatively large city, it seems possible that the former Communist regime in this country encouraged the excessive use of pesticides. Presumably the samples from Costa Rica were so low because they were taken from a remote rain forest (Guanacaste National Park). We further analyzed these data by constructing plots of the logarithm of each concentration given in Table 1 versus both the Gross National Product per person (17, 18) and the Human Development Index (HDI) (19) on a country-bycountry basis. The HDI is an index that accounts for national income, life expectancy, and educational level. These

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FIGURE 3. Absolute values of the average latitudes of the sampling sites within the countries versus GNPpp and HDI. The country symbols are given in Table 2.

FIGURE 2. Concentrations of hexachlorobenzene (HCB), transnonachlor, and dieldrin in tree bark (ng/g lipid) versus the human development index. The country symbols are given in Table 2. Data for Costa Rica, India, and Romania have not been plotted or included in the regression. socioeconomic data for the countries from which the bark samples were taken are given in Table 2. These two socioeconomic parameters are both measures of the level of development of a given country, and as expected, these two parameters are strongly correlated to one another (log of GNPpp vs HDI gives r ) 0.91). The logarithm of the pesticide concentration was plotted versus the GNPpp and HDI because previous analyses of these data have indicated that they are log-normally distributed (5, 10). In each case, a correlation coefficient was determined. As discussed above, Costa Rica, India, and Romania were substantial outliers; thus, correlation coefficients were also determined after omitting data from these three countries. The correlation coefficients are given in Table 3. The 99% significance level for a correlation coefficient calculated with 25 degrees of freedom is r ) 0.487; values higher than this level are given in bold in Table 3. For statistical robustness, we used the 99% confidence limit and we required correlations to be significant for both the GNPpp and HDI regressions. The only compounds that met these conditions were HCB for the complete data set and HCB, trans-nonachlor, and dieldrin for the data set omitting Costa Rica, India, and Romania. Plots of the latter three cases are shown in Figures 1 and 2 for GNPpp and HDI, respectively. Calamari et al. (3) found a good relationship between R-HCH, γ-HCH, and the sum of R- and γ-HCH and the GNPpp

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(r ) 0.47, 0.60, and 0.57, respectively). We did not find such a relationship; our correlation coefficients were all not significant for R-HCH, γ-HCH, and the sum of R- and γ-HCH, both with and without the outliers, for either GNPpp or HDI. We have no explanation for this difference except to note that the samples were taken from a different set of countries than Calamari et al. (3) and that a different type of vegetation was analyzed in each study. We did, however, find a good correlation between R- and γ-HCH concentrations and the absolute values of the latitudesa correlation due to the global distillation effect that we have reported previously (5, 10). Like Calamari et al. (3), we found a very high correlation of HCB concentrations in tree bark with socioeconomic parameters. In fact, the correlation coefficients are similar for the two studies. Calamari et al. (3) found r ) 0.76 for GNPpp; we found r ) 0.79 for the GNPpp correlation and r ) 0.72 for the HDI correlation; see Figures 1 and 2. The strength of this relationship is striking, and we suspect that it is due to two factors: First, HCB is both a pesticide (a fungicide) and an industrial cyclic intermediate; thus, its use may be more highly linked to the socioeconomic status of a given country than more specialized pesticides. Second, HCB seems to be transported through the atmosphere to colder, higher latitudes (5), and since there is a secondary relationship between the absolute value of latitude and socioeconomic status (see Figure 3), one would expect to see an enhanced correlation between the latter indicators and environmental concentrations of volatile compounds such as HCB. Neither Calamari’s study (3) nor this study found relationships between the socioeconomic indicators and the concentrations of any of the DDT-like compounds in vegetation. On the other hand, Calamari et al. (3) found that countries with a GNPpp of less than about $1000 had an increasing DDT/DDE ratio as compared to more welldeveloped countries. We observed no such relationship (r < 0.28).

Our correlations of socioeconomic indicators with transnonachlor and dieldrin are new (see Figures 1 and 2) and were not observed by Calamari et al. because they did not measure these compounds. Incidentally, the tree bark concentrations of neither of these compounds were related to the absolute value of latitude (r < 0.21). It is curious that the other hexachlorocyclopentadiene compounds (heptachlor epoxide through endosulfan sulfate) show no correlation to either of the socioeconomic indicators. In addition, there is no relationship for the other pesticides to either of the socioeconomic indicators. This may indicate that some countries have a preference for a given pesticide (for example, endosulfan in Brazil), a preference which is more related to the crops grown in that country than to its overall economy. Figures 1 and 2 show, as noted above, that some of the poorest countries, such as Togo, Ghana, and Uganda, show the least amount of HCB, trans-nonachlor, and dieldrin pesticide contamination in tree bark, while some industrialized countries, such as northern Europe, show high levels of organochlorine pesticides. In the latter countries, these compounds have been (in most cases) banned for many years. These results suggest that the environment is slow to rid itself of these compounds. On the other hand, in regions where these compounds were never used, the environment is only slightly contaminated with these particular pesticides.

Acknowledgments We thank the many colleagues and friends who helped with the collection of the samples.

Literature Cited (1) Voldner, E. C.; Li, Y. F. Sci. Total Environ. 1995, 160/161, 201210. (2) Public Health Impact of Pesticides used in Agriculture; World Health Organization: Geneva, 1990; pp 24-32.

(3) Calamari, D.; Tremolada, P.; Notarianni, V. Environ Sci. Technol. 1995, 29, 2267-2272. (4) Calamari, D.; Tremolada, P.; DiGuardo, A.; Vighi, M. Environ Sci. Technol. 1994, 28, 429-434. (5) Simonich, S. L.; Hites, R. A. Science 1995, 269, 1881-1854. (6) Simonich. S. L.; Hites, R. A. Nature 1994, 370, 49-51. (7) Simonich, S. L.; Hites, R. A. Environ. Sci. Technol. 1994, 28, 939943. (8) Zimmermann, M. H.; Brown, C. L. Trees: Structure and Function; Springer-Verlag: New York, 1971. (9) Hermanson, M. L.; Hites, R. A. Environ. Sci. Technol. 1990, 24, 666-671. (10) Simonich, S. L. Doctoral Thesis, Indiana University, 1995. (11) Anderson, D. J.; Hites, R. A. Atmos. Environ. 1989, 23, 20632066. (12) Buser, H. R.; Muller, M. D. Environ. Sci. Technol. 1993, 27, 12111220. (13) Insect Control Guide; Meister Publishing Co.: Willoughby, OH, 1995. (14) Farm Chemicals Handbook Meister Publishing Co.: Willoughby, OH, 1995. (15) Burgoyne, T. W.; Hites, R. A. Environ. Sci. Technol. 1993, 27, 910-914. (16) Iwata, H.; Tanabe, S.; Sakai, N.; Tatsukawa, R.; Environ. Sci. Technol. 1993, 27, 1080-1098. (17) World Bank Development Report; The World Bank, Oxford University Press: New York, 1994. (18) World Agriculture: Trends and Indicators, 1970-1991; U.S. Department of Agriculture: Washington, DC, 1993). (19) Human Development Report 1994; United Nations Development Programme, Oxford University Press: New York, 1994.

Received for review May 6, 1996. Revised manuscript received November 5, 1996. Accepted December 5, 1996.X ES9604020 X

Abstract published in Advance ACS Abstracts, February 15, 1997.

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