Published in J. Environ. Qual. 32:1710-1716 (2003).
© 2003 ASA, CSSA, SSSA
677 S. Segoe Rd., Madison, WI 53711 USA
TECHNICAL REPORTS
Organic Compounds in the Environment
Spatial Distribution of DDT in Sediments from Estuarine Rivers of Central Florida
Ying Ouyang*,a,
Peter Nkedi-Kizzac,
Robert S. Mansellc and
Jim Y. Renb
a Department of Water Resources, St. Johns River Water Management District, P.O. Box 1429, Palatka, FL 32178-1429
b Department of Information Resources, St. Johns River Water Management District, P.O. Box 1429, Palatka, FL 32178-1429
c Soil and Water Science Department, University of Florida, Gainesville, FL 32611-0290
* Corresponding author (youyang{at}sjrwmd.com).
Received for publication July 1, 2002.
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ABSTRACT
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Sediments may act as both a carrier for and a potential source of contaminants such as toxic organics in aquatic environments. This study investigated the spatial distribution of the pesticide DDT [1,1,1-trichloro-2,2-bis(p-chlorophenyl)ethane] in sediments from the Cedar and Ortega Rivers located in the lower St. Johns River basin, Florida, USA, using field measurements and three-dimensional kriging analysis. High DDT concentrations were found near the junction of the Cedar and Ortega Rivers and at the north end of the Ortega River in the upper 0.5 m of the sediments, indicating that the sediment was enriched with DDT in the top layer although use of this chlorinated compound was banned in 1972. Further study revealed that the influence of sediment grain size or texture on DDT contamination was negligible in this river system and no linear correlations existed among DDT and its metabolites such as DDD [1,1-dichloro-2,2-bis(p-chlorophenyl)ethane] and DDE [1,1-dichloro-2,2-bis(p-chlorophenyl)ethylene]. Comparison of three-dimensional distribution of DDT content to the Florida sediment quality assessment guideline or probable effect level (PEL) showed several "hot spots" in the Ortega River sediments, where DDT contents exceeded the PEL value of 4.78 µg kg-1. Such contamination may pose a significant hazard to aquatic life.
Abbreviations: PEL, probable effect level • TOC, total organic carbon
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INTRODUCTION
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ORGANIC CONTAMINANTS are ubiquitous in aquatic ecosystems throughout the world. Most of these contaminants are highly hydrophobic and persist in sediments of rivers, streams, and lakes long after their release. One such organic contaminant is the pesticide DDT. Although a ban on most DDT manufacturing was imposed in 1972 in the United States, this chlorinated hydrocarbon compound still exists in the environment and in the biota (Swartz et al., 1994; Gillis et al., 1995; Kennish and Ruppel, 1996; Brown, 1997; Hoke et al., 1997). The lipophilic character of organic compounds such as DDT facilitates its accumulation and persistence in lipid-rich tissues of the biota, and its biomagnification on the food chain is a major concern (USEPA, 1987; Falandysz et al., 2001). Frequently, DDT co-occurs with its metabolites, namely DDE and DDD. Concentrations of DDD and DDE may exceed that of the parent compound (DDT) in highly contaminated sites (Brown, 1997; Murdoch et al., 1997; Lotufo et al., 2000). Tremendous effort has been devoted to characterizing the fate and toxicity of DDT and its daughter products to benthic organisms in freshwater and marine environments (Kennish and Ruppel, 1996; Jafvert et al., 1997; Lotufo et al., 2001; O'Shea et al., 2001). These studies have improved our understanding of DDT toxicity in aquatic ecosystems.
Human activities such as agricultural, residential, and commercial pesticide applications are responsible for elevated DDT levels in sediments from the Cedar and Ortega Rivers located in the lower St. Johns River basin, Florida, USA (Keller and Schell, 1993). The DDT entering the Cedar–Ortega River from upstream may remain in the water column adsorbed to suspended solids and may be transported downstream with normal water flow. As this DDT-laden fresh water mixes with more saline water of marine origin, chemical changes occur that result in deposition of the suspended solids and the associated DDT. In the past, little attention has been devoted to investigating sediment DDT contamination in the Cedar and Ortega Rivers. Recently, a field investigation was performed by the St. Johns River Water Management District (SJRWMD), Florida, USA to examine sediment-associated heavy metal and hydrocarbon contamination in the rivers (Durell et al., 2001). Their study has provided basic understanding of DDT contamination in the river sediments. However, one limitation of their study is that the spatial distribution of DDT in the sediments from these rivers is poorly defined.
Restoration and protection of the Cedar and Ortega Rivers has challenged the SJRWMD. In 1987 the Florida Legislature enacted the Surface Water Improvement and Management 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 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 contaminants in the river sediments is crucial.
In this study, spatial distribution of DDT in sediments from the Cedar and Ortega Rivers was investigated using three-dimensional kriging estimation and field measurements. Specific objectives were to (i) characterize spatial distribution of DDT in the river sediments and its potential input sources, (ii) determine the influence of sediment grain size on DDT contamination, and (iii) estimate potential DDT risk to aquatic life using sediment quality assessment guidelines. In addition, the correlations among DDT and its metabolites such as DDD and DDE were evaluated.
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MATERIALS AND METHODS
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Study Site
The Cedar and Ortega Rivers are located in south-central Duval County and are tributaries of the lower St. Johns River in Florida, USA (Fig. 1)
. About one-third of land use in the river area is residential, while the rest consists of commercial–industrial and vacant land uses. Several industrial complexes comprised of petrochemical, electrical, and plastic industries are located in the area. Recent studies by the SJRWMD staff found that a large number of sampling sites from the rivers had organic and metal concentrations that exceeded the National Oceanic and Atmospheric Administration's "high" reference values (Durell et al., 2001), which could pose a significant threat to aquatic life.
Grab and core sediment samples were collected from three sampling depth intervals, namely 0 to 10, 11 to 56, and 57 to 125 cm, from 58 locations along the rivers during the period between February 1998 and February 1999 (Durell et al., 2001). A global position system (GPS) was employed to precisely identify each location following a modified version of the USEPA's Estuarine Monitoring and Assessment Program random sampling protocol (Summers et al., 1991). After collection, the samples were shipped to Battelle Marine Sciences Laboratory (Sequim, WA) for analyzing DDD, DDE, and DDT using Method 8081M (Durell et al., 2001).
Three-Dimensional Kriging Analysis
Spatial distribution of DDT in sediments from the Cedar and Ortega Rivers was determined by three-dimensional ordinary kriging estimation using the ISATIS model (Bleines et al., 2000). The three-dimensional ordinary kriging method is a weighted-linear-average estimator where the weights are chosen to minimize the estimated (kriged) variance. Data from a single data type are used to predict values of that data type at unsampled locations. Details for kriging analysis are published elsewhere (Cooper and Istok, 1988; American Society of Chemical Engineers, 1989; Isaaks and Srivastava, 1989; American Society for Testing and Materials, 1994; Rouhani et al., 1996; Goovaerts, 1999; Triantafilis et al., 2001; Ouyang et al., 2002). The ISATIS software, developed by Bleines et al. (2000), is a geostatistical tool that includes an extensive range of geostatistical methods combined with an efficient data management system.
Kriging procedures employed 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 DDT data collected from the Cedar and Ortega Rivers. A histogram plot of the data shows that DDT was abnormally distributed with a positive skew (Fig. 2a)
. Because of the abnormal distribution, a natural logarithmic transformation of the data was performed (Fig. 2b). In general, a normal distribution requirement in kriging analysis may not be so critical, but when the data set is very skewed or contains outliers, some kind of transformation is needed. A data structural analysis was performed to determine the spatial correlation of the DDT data, which included an experimental variogram, a structural variogram model, and cross-validation analyses. An experimental variogram is an estimation of the variogram based on sampling. Statistically, it is an inverse measure of the two-point covariance function for a stationary stochastic process as described by Eq. [1]:
 | [1] |
where h is the separation distance, x the location of a data point, and n the number pairs of data points separated by a distance more or less equal to h. The experimental variograms for DDT in the x and y directions are given in Fig. 3
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A variogram map was constructed to determine if the spatial correlation structure of the DDT data is dependent on direction. It is a useful tool for evaluation of anisotropy in data sets. A variogram map is calculated by laying the center of a grid over each data location one at a time. For each cell where data exist, the squared difference of the values between the center and the cell is accumulated. The average of the accumulated differences is the value for that cell of the variogram map (Chu et al. 1994; Boniol and Toth, 1999). If a variogram map from a data set shows high values along a direction (e.g., northwest or southeast), it implies that the spatial correlation of the data set is dependent on direction, such that an anisotropic model should be used to fit the experimental variogram. Since the spatially correlated distribution of the DDT data (Fig. 4) did not apparently depend on direction, an isotropic model was selected to fit the experimental variogram.
The model fitting procedure was performed graphically to find a structure as close as possible to the experimental variogram curve (Fig. 5)
. The variogram reaches a sill or population variance of the investigated data when the y axis levels off. A jump up in the y axis from the origin of the variogram plot is the nugget, which represents microscale variations and/or measurement errors (Boniol and Toth, 1999). A range is a parameter of a variogram model that represents a distance beyond which there is little or no autocorrelation among variables.
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 (C) and the cross-validation estimated value (C*) is the estimation error (C - C*), which gives an indication of how well a data value fits into the neighborhood of 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 (Fig. 6) . In this study the DDT cross-validation standardized error is 0.096 µg kg-1, indicating adequacy of the model and parameters. The major kriging parameters used in this study are presented in Table 1.
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Fig. 6. Relationship between the cross-validation standardized error and the estimated ln DDT concentration.
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Sediment Quality Assessment
Although kriging estimates provide useful information on spatial distribution of DDT 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, a Florida sediment quality assessment guideline or probable effective level (PEL) was employed to assess the sediment quality based on the kriged DDT concentrations. The PEL, as defined by MacDonald et al. (1996), is the lower limit of the range of contaminant concentrations that are usually or always associated with adverse biological effects. The PEL can be postulated by:
 | [2] |
where EDS is the 50th percentile concentration in the effect data set, and NEDS is the 85th percentile concentration in the no-effect data set. A more detailed description of the numerical sediment quality assessment guidelines and the PEL development can be found in MacDonald et al. (1996).
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RESULTS AND DISCUSSION
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Spatial Distribution of DDT
Spatial distributions of DDT concentrations in sediments from the Cedar and Ortega Rivers at the sediment depths of 0.1, 0.5, 1, and 1.5 m are shown in Fig. 7
. High concentrations of DDT occurred near the junction of the Cedar and Ortega Rivers (around x = 430.5 km) and at the north end of the Ortega River at the sediment depths of 0.1 and 0.5 m. The highest DDT concentration (about 12 µg kg-1) was found at the north end just beneath the sediment surface (z = 10 cm). Results indicate that at least two DDT contaminated source zones were identified, one from the junction of the Cedar and Ortega Rivers and the other from the north end of the Ortega River. Although the specific sources of DDT contamination are unknown, some typical input sources could include applications of DDT from residential, agricultural, commercial, and golf course areas, while the highest DDT concentration at the north end of the Ortega River may be the result of an additional DDT load from the Fishwier Creek (Fig. 1). The Fishwier Creek area was recently identified as a hydrocarbon-contaminated area by the St. Johns River Water Management District.
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Fig. 7. Spatial distribution of kriged DDT concentrations at sediment depths of 0.1, 0.5, 1.0, and 1.5 m.
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The DDT concentrations in the sediments decreased from the 0.5- to 1.0-m depths (Fig. 7). For instance, the DDT concentration was about 5.0 µg kg-1 at the north end of the Ortega River at z = 0.5 m and was only 2.5 µg kg-1 at z = 1.0 m. Results show that DDT is still enriched near the top layer of the sediments (i.e., above 0.5 m) although its application was legally banned since 1972 for the purpose of environmental protection. This probably occurred because the lipophilic character of DDT facilitated accumulation and persistence of this pesticide in this organic matter–rich aquatic environment (USEPA, 1987; Falandysz et al., 2001). Recent field measurements show that the average naturally occurring total organic carbon (TOC) in the sediments from the area is about 133 mg kg-1 (Durell et al., 2001).
Existing field measurements provide information on DDT contamination of sediment at the specific sampling sites, but unsampled locations limit the overall usefulness of the data. Therefore, the spatial distribution of the DDT across the rivers cannot be thoroughly determined by field measurements alone. A three-dimensional distribution of DDT content in sediments from the Cedar and Ortega Rivers estimated by kriging analysis is given in Fig. 8 . This figure further illustrates that the highest DDT concentrations were located within "hot spots" at the north end of the Ortega River. This finding is very useful for implementing environmental remediation practices such as sediment dredging.
Total Organic Carbon–Normalized DDT
The influence of sediment grain size or texture on sediment contamination often shows an inverse correlation. This can cause difficulties in distinguishing real differences in contamination from artifacts caused by variations in sediment grain size or texture (Grant and Middleton, 1998). Approaches to circumvent these difficulties involve normalizing contaminant concentrations based on concentrations of a conservative element, organic carbon content, or the proportion of the sediment smaller than 63 µm in diameter. The purpose of normalized sediment DDT concentrations with TOC was to test if the sediment texture has any influence on DDT contamination. If the DDT concentration was influenced by the sediment texture or grain size, then a location with high DDT concentration would not necessarily indicate that this location is more contaminated because the effect of sediment texture is excluded. In this study, sediment TOC contents measured from the Cedar and Ortega Rivers were used to normalize the sediment DDT concentrations measured from the same area. This was accomplished by dividing the measured DDT concentration (µg kg-1) with the measured TOC concentration (µg kg-1) at each location (note that the unit of measured TOC was in mg kg-1 and was converted to µg kg-1 before normalization).
A plot of normalized DDT concentration with distance in the x direction (lateral) is given in Fig. 9
. This figure reveals that the normalized DDT concentration increased slightly with distance in the x direction (excluding the outlier). In other words, the normalized DDT content increased from the Cedar River to the Ortega River. This trend was similar to that of the DDT content without TOC normalization. Results indicate that the influence of sediment grain size or texture on DDT concentrations was negligible in this river system. Therefore, the sediment of the Ortega River was indeed more contaminated.
Sediment Quality Estimation
Agricultural, residential, and commercial pesticide applications in the past are responsible for elevated DDT levels in sediments from the Cedar and Ortega Rivers. The DDT loaded into rivers from contaminated sources tends to associate with suspended solids and be convectively transported downstream with normal water flow. Restoration and protection of rivers is, therefore, a challenge. To ensure cost-effective remediation of sediment DDT, an investigation of the potential risk of DDT to aquatic life in the Cedar and Ortega Rivers is crucial. Figure 10
shows a plot of DDT concentration distribution against a sediment quality assessment guideline or PEL. The DDT concentrations above the PEL of 4.78 µg kg-1 are displayed in dark black. It is apparent from the plot that several hot spots with DDT concentrations exceeded the PEL value within the upper 50 cm of sediment in the Ortega River. These hot spots could pose potential risk to aquatic life although they are not the highest DDT-contaminated spots in the world. It has been reported that the total DDT concentrations in the sediments from Havel and Spree Rivers in Germany are up to 4200 to 8100 µg kg-1 (Schwarzbauer et al., 2001).
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Fig. 10. Three-dimensional view of kriged DDT distribution in the Cedar and Ortega Rivers. The dark black color represents the DDT concentrations exceeding the probable effect level (PEL) value (4.78 mg kg-1).
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Finally, plots of DDD and DDE against DDT are given in Fig. 11 . As indicated by the correlation coefficients (R2), no linear correlations existed among DDT and its metabolites. A similar result was obtained between DDD and DDE (Fig. 11c). It is apparent that the degradation pathways among these species were different in this river system although the exact reasons remain unknown.
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CONCLUSIONS
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Three-dimensional kriging analysis was performed to characterize spatial distribution of DDT concentrations in the Cedar and Ortega Rivers located in the lower St. Johns River basin, Florida, USA, using the ISATIS model and field measurements. The analysis procedures included preliminary data analysis, data structure analysis, and kriging estimation.
High DDT concentrations were found near the junction of the Cedar and Ortega Rivers and at the north end of the Ortega River. Results reveal that DDT remains enriched near the top layer of the sediments at the base of the river although the use of this chlorinated compound was banned in 1972. Although specific sources of DDT contamination are unknown historically, typical input sources probably include applications of DDT from surrounding residential, agricultural, commercial, and golf course areas.
The influence of sediment grain size or texture on DDT concentrations was examined by normalizing DDT concentration with TOC concentration. Results show that sediment grain size or texture has a negligible effect on DDT contamination in this river system.
A plot of DDT concentration distribution against a Florida sediment quality assessment guideline shows that there were several hot spots with DDT concentrations exceeding the PEL value (4.78 µg kg-1) for the upper 0.5 m of sediment in the Ortega River. These hot spots could pose a potential risk to aquatic life. This finding should be very useful to environmental scientists, water resource planners, regulators, decision-makers, engineers, and resource managers. This study further reveals that no linear correlations existed among DDT and its metabolites such as DDD and DDE. It is apparent that the degradation pathways among these species were different although the exact reasons remain unknown.
The temporal distribution of DDT was not included in this study partially because the major goal was to understand the spatial distribution of DDT, and partially because of the lack of time series field measurements needed for such a study. Further study is warranted to examine the influence of major climatic, hydrogeological, and biological conditions on the seasonal and annual spatial distributions of sediment DDT in these rivers.
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NOTES
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Florida Agricultural Experiment Station Journal Series no. R-09427.
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TOP
ABSTRACT
INTRODUCTION
