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TECHNICAL REPORTS

Organic Compounds in the Environment

Characterization of the Pesticide Chlordane in Estuarine River Sediments

^a Department of Water Resources, St. Johns River Water Management District, P.O. Box 1429, Palatka, FL 32178-1429
^b Soil and Water Science Department, University of Florida, Gainesville, FL 32611-0290
^c USDA-ARS-STARS, 22271 Chinsegut Hill Road, Brooksville, FL 34601

^* Corresponding author (youyang{at}sjrwmd.com)

Received for publication July 16, 2004.

	ABSTRACT

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
Sediments are increasingly recognized as both carrier and potential source of contaminants in aquatic environments. This study investigated the characteristics and spatial distribution of total chlordane and its three most abundant compounds, including -chlordane, -chlordane, and trans-nonachlor, in sediments from the Cedar and Ortega rivers, Florida, USA, using geographic information system (GIS)-based kriging analyses and field measurements. Kriging analysis showed that two areas, one from the Cedar River area and the other from the northern end of the Ortega River area, were contaminated. The maximum concentrations of total chlordane, -chlordane, -chlordane, and trans-nonachlor in the sediments were, respectively, 101.8, 20.1, 26.3, and 19.2 µg/kg. A plot of total organic carbon (TOC)-normalized chlordane concentrations showed that effects of grain size on sediment chlordane contamination were negligible. A principal axis analysis further revealed that a linear correlation existed between -chlordane and total chlordane as well as between -chlordane and total chlordane, whereas no correlation existed between trans-nonachlor and total chlordane. Comparison of total chlordane concentration with Florida Sediment Assessment Guidelines showed that the Cedar River and the northern end of the Ortega River had total chlordane concentrations above the probable effect level (4.79 µg/kg), which could pose a potential risk to aquatic life.

Abbreviations: GIS, geographic information system • PAA, principal axis analysis • PEL, probable effect level • TEL, threshold effect level • TOC, total organic carbon

	INTRODUCTION

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
ORGANIC CONTAMINANTS are ubiquitous in surface environments throughout the world. Most of these contaminants are highly hydrophobic and persist in sediments of rivers and lakes long after their release. A well-known organic contaminant is the pesticide chlordane. Chlordane was widely used in the United States for both agricultural and residential applications from the time of its introduction in the 1940s through its suspension by the USEPA in 1988 (Ahrens et al., 1962; USEPA, 1990). As applied, chlordane was not a single compound but a mixture of more than 140 different related compounds known as technical chlordane. The three most abundant compounds of technical chlordane, cis- (or ) chlordane, trans- (or ) chlordane, and trans-nonachlor, could account for approximately 25% (Eitzer et al., 2001), 51% (Falandysz et al., 2001), or 95% (Mattina et al., 1999) of the technical chlordane, depending on manufacturer. Although a ban on chlordane application was imposed in the United States in 1988, this chlorinated hydrocarbon still exists in the environment and in biota (Falandysz et al., 2001; Bidleman et al., 2002). The lipophilic character of chlordane facilitates its accumulation and persistence in lipid-rich tissues of biota, and its biomagnification on the food chain is a major concern.

Several studies have been devoted to investigating the fate of chlordane in the soil, water, and air system. Eitzer et al. (2001) employed chiral gas chromatography in conjunction with ion trap mass spectrometry to measure the compositional chiral profiles of weathered soil residual chlordane. These authors found that biotic degradation and abiotic weathering of chlordane occurred in the soils used in their studies. Gundersen et al. (2000) reported that 5 of 10 Ohio River paddlefish egg samples exceeded the Food and Drug Administration's action limit for chlordane (0.3 µg/g).

Human activities such as agricultural, residential, and commercial pesticide applications are responsible for elevated technical chlordane levels in sediments from the Cedar and Ortega rivers located in the St. Johns River watershed, Florida. Technical chlordane entering the Cedar and Ortega rivers from upstream can remain in the water column adsorbed to suspended solids and can transport downstream with normal water flow. Restoration and protection of the Cedar and Ortega rivers have been a challenge. During its 1987 session, the Florida Legislature enacted the Surface Water Improvement and Management (SWIM) Act, which identified this segment of the St. Johns River as one of the areas of critical concern. To restore the environmental health of the rivers, the St. Johns River Water Management District (SJRWMD) is currently evaluating the feasibility of removing sediments and associated contaminants (e.g., heavy metals and hydrocarbons) by dredging. To ensure cost-effective remediation, a quantitative study of the contaminants including chlordane in the river sediments is crucial.

The purpose of this study was to investigate the characteristics and spatial distribution of pesticide chlordane in sediments from the Cedar and Ortega rivers, using GIS-based kriging analyses and field measurements. The specific objectives were to (i) examine the spatial distribution of -chlordane, -chlordane, and trans-nonachlor in the sediments from the Cedar and Ortega rivers using GIS-based kriging analysis and field measurements; (ii) characterize the relationships among the chlordane species; and (iii) determine the potential risk of the sediment chlordane to aquatic life using Florida Sediment Assessment Guidelines.

	MATERIALS AND METHODS

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
Study Site
The Cedar and Ortega rivers basin is located in south-central Duval County and is a tributary of the St. Johns River, Florida (Fig. 1) . It has been reported that about 4.1 to 5.6 m³/s of domestic and industrial wastewater, mainly from the City of Jacksonville, is being discharged into the Cedar and Ortega rivers and finally enters the St. Johns River (Watkins, 1992; Campbell et al., 1993; Ouyang et al., 2002). Approximately one-third of the land use in the basin is residential, while the rest of the basin consists of commercial and/or industrial, agricultural, wetland, and forest land uses. Several industrial complexes comprised of petrochemical, electrical, and plastic industries are located in this basin. Both water quantity and quality problems were observed in the Cedar and Ortega rivers basin (Bergman, 1992; Alexander et al., 1993; Ouyang et al., 2002).

View larger version (70K): [in this window] [in a new window]   Fig. 1. Location of the study area showing the Cedar and Ortega rivers watershed and sampling points (circles).

Surface sediment grab samples were obtained using precleaned stainless steel petite Ponar dredges. Precleaned glass trays were used to catch and retain surface dredge samples for processing and transfer. Stainless steel spoons were used to scoop the sediment samples from the glass trays into precleaned 500-mL glass jars with Teflon lids. Subsurface sediment core samples were collected using piston-core samplers, following the design developed by Livingstone (1955) and modified by Fisher et al. (1992). Piston-core samplers were used to obtain undisturbed sediment samples. After collection, the samples were stored at 4°C and shipped on ice to Battelle Marine Sciences Laboratory (BMSL), Sequim, WA, for chlordane analyses using Method 8081M and for total organic carbon (TOC) analyses using Method 9060 (USEPA, 1986). The TOC was converted by high temperature combustion to carbon dioxide and then measured by either infrared absorbance or by conversion to methane and subsequent flame ionization. Although detailed descriptions of sample analytical procedures are beyond the scope of this study, they can be found in Durell et al. (2001).

Kriging Analysis
Spatial distribution of -chlordane, -chlordane, and trans-nonachlor in the sediments from the Cedar and Ortega rivers was determined by ordinary kriging estimation using the ArcGIS geostatistical analyst tool (ESRI, 2001). The ordinary kriging is a weighted-linear-average estimator where the weights are chosen to minimize the estimated (kriged) variance. It uses data from a single data type to predict values of that same data type at unsampled locations. The details for mastering the art of kriging are published elsewhere (Cooper and Istok, 1988; American Society of Chemical Engineers, 1989; Isaaks and Srivastava, 1989; Rouhani et al., 1996; Goovaerts, 1999; Triantafilis et al., 2001; Ouyang et al., 2003).

Kriging procedures used in this study include: (i) preliminary data analysis, (ii) data structural analysis, and (iii) kriging estimation. Before kriging estimation, descriptive statistics were performed to examine the chlordane data collected from the Cedar and Ortega rivers. Histogram plots of the data showed that the three chlordane species were abnormally distributed, and therefore a natural logarithmic transformation of the data was performed. In general, a normal distribution requirement in kriging analysis may not be so critical, but when the data set is too skewed or contains outliers, some kind of transformation is needed.

A data structural analysis was performed to determine the spatial correlation of the chlordane data, including experimental variogram, structural variogram model, and cross-validation analyses. The experimental variogram is an inverse measure of the two-point covariance function for a stationary stochastic process. A variogram map was constructed to determine if the spatial correlation structure of the chlordane data is dependent on direction. Because the spatial correlation distribution of the chlordane data did not apparently depend on direction, an isotropic spherical model was selected to fit the experimental variogram. The model fitting procedure was performed graphically to find a structure that would be as close as possible to the experimental variogram curve.

Cross-validation is a general procedure that checks the compatibility between a set of data and a structural model. The difference between the measured value and the cross-validation estimated value is the estimation error, which gives an indication of how well the data value fits into the neighborhood of the surrounding data values. The cross-validation standardized errors between –2.5 and +2.5 represent robust data and indicate that a model can correctly predict the estimated values. In this study the cross-validation standardized errors are –0.01, 0.48, and –0.04 µg/kg, respectively, for -chlordane, -chlordane, and trans-nonachlor, indicating adequacy of the models and of the parameters.

Spatial distribution of the three chlordane species was determined by the GIS geostatistical analyst tool. The kriging domain used in this study was 3000 x 6000 m, which encompassed the entire Cedar and Ortega rivers. The kriging grid intervals were X = 100 m and Y = 100 m. Table 1 presents the major kriging parameters used in this study. It should be noted that the sediment samples were collected from the rivers, while the kriging domain has been extended from the river to the nearby land surface. This was done because the GIS geostatistical analyst tool requires a rectangle kriging domain. This raised the question regarding the acceptability of using kriging to estimate chlordane contents in areas outside the riverbed, because no soil samples were collected from the land surface. In this study, the kriging neighborhood search radius used was about 200 m, which was much less than the modeled variogram ranges (Table 1). The range is the maximum distance over which the data exhibit spatial correlation. The cross-validation standardized errors of –0.01 for -chlordane, 0.48 -chlordane, and –0.04 µg/kg, and trans-nonachlor further confirmed that the kriging estimations were acceptable although the kriged domain has been extended to the nearby land surface. In addition, the kriging-estimated chlordane contents in the land surface were not used for interpretation in this study.

	RESULTS AND DISCUSSION

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

View larger version (42K): [in this window] [in a new window]   Fig. 2. Spatial distribution of kriging-estimated chlordane concentrations (µg/kg).

To exclude variations due to physical properties of particles such as grain size differences and to better compare site-to-site variations in sediment chlordane contamination, normalization of sediment chlordane concentrations was performed in this study. In general, conservative elements such as Al, Fe, Se, Rb, and Li are used to normalize heavy metals, whereas organic carbon content is used to normalize hydrocarbons (Grant and Middleton, 1988).

In this study, the chlordane data were normalized with TOC. This was accomplished by dividing the chlordane concentrations by TOC concentrations at each sampling location (Fig. 3) . The TOC contents were obtained from the same sediment samples as those of chlordane using Method 9060 (USEPA, 1986). Detailed description of sample analysis procedures for TOC can be found in Durell et al. (2001).

View larger version (22K): [in this window] [in a new window]   Fig. 3. Total organic carbon (TOC)-normalized chlordane concentrations as a function of distance in the X direction (easting).

Relationships among Chlordane Species
Plots of -chlordane, -chlordane, and trans-nonachlor against total chlordane using linear regression and principal axis analyses are given in Fig. 4 . The total chlordane consists of all of the individual chlordane compounds measured from the sediment samples. A first glance at the linear regression analysis shows that there is a very good linear correlation between -chlordane and total chlordane (R² = 0.94; Fig. 4a), a somewhat linear correlation between -chlordane and total chlordane (R² = 0.71; Fig. 4b), and no linear correlation between trans-nonachlor and total chlordane (R² = 0.02; Fig. 4c). However, a residual analysis shows that the linear regression lines shown on Fig. 4 have more or less nonconstant variances and thereby could violate the following linear regression assumption: the error terms should have the same variance at each value of the predictor variable (SAS Institute, 2000). In the past, scientists often used regression lines to characterize scattergrams. These regression lines may not be appropriate for correlation analysis when both variables are random (Sokal and Rohlf, 1995).

View larger version (28K): [in this window] [in a new window]   Fig. 4. Relationships between three chlordane compounds and total chlordane obtained using linear regression and principal axis analysis.

The correlations among the chlordane species were investigated using a t test with a 1% level of significance (i.e., = 0.01). With the t values of 38.32, 15.38, and 1.45, respectively, for -chlordane vs. total chlordane, -chlordane vs. total chlordane, and trans-nonachlor vs. total chlordane as compared with the t critical region (2.39), we rejected the hypothesis of zero correlation for -chlordane vs. total chlordane and -chlordane vs. total chlordane, but accepted the hypothesis of zero correlation for trans-nonachlor vs. total chlordane. Results imply that the degradations of -chlordane and -chlordane were in proportion to that of total chlordane in this river system although this was not true for trans-nonachlor. It is apparent that the metabolized pathways of trans-nonachlor were different from those of -chlordane and -chlordane in this river system even though the exact reasons remain unknown.

Further investigations on testing the significance of the differences between correlation coefficients among the three chlordane species were performed by a Z transformation of the correlation coefficients. The advantage of this transformation is that whereas correlation coefficients are distributed in skewed fashion for values of 0 ( is the parametric correlation coefficient from a population), the values of Z are approximately normally distributed and are a basic statistical assumption for t test. Detailed explanations of this kind of analysis can be found in Sokal and Rohlf (1995). With the t values of 5.86 and 13.38, respectively, for -chlordane vs. -chlordane and -chlordane vs. trans-nonachlor greater than the t critical region (2.39), we rejected the hypothesis of equal correlation coefficients. Therefore, the differences in correlation coefficients for -chlordane vs. -chlordane and -chlordane vs. trans-nonachlor were significant.

Potential Risk of Chlordane
Although kriging estimates provide useful information on spatial distribution of chlordane concentrations from sediments in the Cedar and Ortega rivers, these estimates alone do not provide an adequate basis for assessing the sediment quality problems. In this study, Florida Sediment Quality Assessment Guidelines were employed to assess the sediment quality based on the kriged chlordane concentrations.

Table 2 lists the number of samples, the mean, median, minimum, and maximum concentrations, and the standard deviations for total chlordane, -chlordane, -chlordane, and trans-nonachlor. The total chlordane concentrations were compared with the sediment quality assessment guideline (i.e., the threshold effect levels or TEL) for Florida coastal waters (MacDonald et al., 1996). The value of TEL for total chlordane and the number of samples exceeding TEL are also presented in Table 2. The TEL, as defined by MacDonald et al. (1996), is the upper limit of the range of sediment contaminant concentrations dominated by no effect data entries. Within this range, concentrations of sediment-associated contaminants are not considered to represent significant hazards to aquatic organisms. The TEL can be calculated by:

[1]

where EDS – L is the 15th percentile concentration in the effect data set, and NEDS – M is the 50th percentile concentration in the no effect data set. An elaborate description of the numerical sediment quality assessment guidelines and the TEL development can be found in MacDonald et al. (1996). As shown in Table 2, about 90% of the sediment samples for total chlordane had concentrations exceeding the TEL value.

[2]

where E is the 50th percentile concentration in the effect data set and NE is the 85th percentile concentration in the no effect data set. A detailed description of the numerical sediment quality assessment guidelines and the PEL development can be found in Macdonald et al. (1996).

Figure 5 shows the total chlordane distribution in the sediments from the Cedar and Ortega rivers with total chlordane concentrations above the PEL (4.79 µg/kg) value in dark black. It is clear from the figure that the Cedar River and the northern end of the Ortega River were found to have total chlordane concentrations above the PEL value. This could pose a potential risk to aquatic life although the concentrations do not represent the highest chlordane-contaminated spots in the environment. In our study, the highest total chlordane concentration in the river sediment is about 101 µg/kg, whereas the total chlordane concentration found in the soils from house foundations in Louisiana was up to 14464 µg/kg (Delaplane and La Fage, 1990).

View larger version (35K): [in this window] [in a new window]   Fig. 5. Total chlordane distribution in sediments from the Cedar and Ortega rivers. Chlordane concentrations above the probable effect level (4.79 µg/kg) are displayed in black.

	CONCLUSIONS

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

To exclude variations due to physical properties of particles such as grain size differences and to better compare site-to-site variations in sediment chlordane contamination, normalization of sediment chlordane concentrations with TOC was performed in this study. Result indicated that effects of grain size on sediment chlordane contamination were negligible because the normalized chlordane concentrations were consistent with those of kriging estimations.

Plots of -chlordane, -chlordane, and trans-nonachlor against total chlordane using linear regression and principal axis analyses show that good linear correlations existed among -chlordane, -chlordane, and total chlordane, whereas no linear correlation existed between trans-nonachlor and total chlordane. Results reveal that the degradations of -chlordane and -chlordane were in proportion to that of total chlordane in this river system although this was not true for trans-nonachlor. It is apparent that the metabolized pathways of trans-nonachlor were different from those of -chlordane and -chlordane in this river system even though the exact reasons remain unknown. Our study further revealed that the Cedar River and the northern end of the Ortega River had total chlordane concentrations above the PEL value (4.79 µg/kg), which could pose a potential risk to aquatic life.

	NOTES

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
Florida Agric. Exp. Stn. Journal Ser. R-10458.

	REFERENCES

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 

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This Article Abstract Figures Only Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Related articles in JEQ Similar articles in this journal Similar articles in ISI Web of Science Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via ISI Web of Science (1) Citing Articles via Google Scholar Google Scholar Articles by Ouyang, Y. Articles by Sigua, G. C. Search for Related Content PubMed PubMed Citation Articles by Ouyang, Y. Articles by Sigua, G. C. Agricola Articles by Ouyang, Y. Articles by Sigua, G. C. Related Collections Statistics Chlorinated Hydrocarbons Spatial Variability Organic Compounds