Trace Level Pesticide Detections in Arkansas Surface Waters

A pesticide survey of surface water was conducted in 1989, 1990, and 1991 in Lawrence, Mississippi, Phillips, and Jefferson counties in Arkansas to as...
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Environ. Sci. Technol. 1997, 31, 395-401

Trace Level Pesticide Detections in Arkansas Surface Waters S C O T T A . S E N S E M A N , * .† T E R R Y L . L A V Y , JOHN D. MATTICE, EDWARD E. GBUR, AND BRIGGS W. SKULMAN The Altheimer Laboratory, Pesticide Residue Research, University of Arkansas, Fayetteville, Arkansas 72704

A pesticide survey of surface water was conducted in 1989, 1990, and 1991 in Lawrence, Mississippi, Phillips, and Jefferson counties in Arkansas to assess nonpoint source water pollution. During these 3 years, 59-62 lake and river/ stream sites were sampled eight times and screened for 17 pesticides commonly used in Arkansas. Pesticides were extracted by solid-phase extraction (SPE) disks. Extracts were analyzed by gas chromatography-electron capture detection (ECD) and high-performance liquid chromatography-UV detection (LCUV). Detections were confirmed by gas chromatography-mass spectroscopy (MS) or co-chromatography. The 256 detections during the survey represented 14 pesticides. Metolachlor (25% of total detections), atrazine (22%), norflurazon (16%), and cyanazine (14%) were the most commonly detected compounds. A total of 5% of the total detections was above health advisories. Spring and summer samples provided 73% of the total pesticide detections. Rivers and streams were responsible for 62% of the detections. The highest number of repeated detections of the same pesticide at a site was for cyanazine (six of eight sampling periods).

Introduction Increasing dependence on pesticides to enhance crop yield and food quality has become an important environmental concern. More than 90% of the area in the United States planted in corn (Zea mays L.), soybeans (Glycine max L.), cotton (Gossypium hirsutum L.), and rice (Oryza sativa L.) received pesticide applications in 1990 (1). Emphasis has been placed on pesticide impact assessment of groundwater by point source contamination in the United States due to this dependence on pesticides because over 100 million Americans depend on groundwater as their primary source of drinking water (2). However, pesticide contamination by nonpoint sources has also become an issue. The United States Environmental Protection Agency (U.S. EPA) reported that 76% of lake area, 65% of stream distance, and 45% of estuarine area were affected by agricultural nonpoint source pollution (3). Depending on the hydraulic gradients, contaminated surface water may affect groundwater quality (4). Surface runoff is the main mechanism that contributes to pesticide contamination of surface water. Runoff has been defined as water containing dissolved or suspended matter that leaves a plot, field, or watershed in surface drainage (5). Specifically, pesticide runoff includes dissolved and sedimentadsorbed pesticide transported by water from a treated land surface (5). * Author to whom correspondence should be addressed. † Present address: Department of Soil & Crop Sciences, Texas A&M University, College Station, TX 77843-2474; e-mail: s-senseman@ tamu.edu.

S0013-936X(96)00244-1 CCC: $14.00

 1997 American Chemical Society

Relative losses of pesticides in agricultural runoff have been quantified to assess contamination potential. Studies have indicated that pesticide loss from runoff has ranged from 98% purity) were used to prepare fortification and standard solutions. The extracted samples were subjected to gas chromatography (GC) and high-performance liquid chromatography (LC) for identification/quantitation. All analytes were co-identified and quantified by GC and LC. Compounds determined by GC were analyzed by a Shimadzu GC-14A equipped with an electron capture detector (ECD). The 2-µL injected sample was split to two columns, each 0.53 mm × 15 m, containing SPB-5 and SPB-608 stationary phases, respectively. The temperature program was 180 °C for 2 min, increased at 1 °C min-1 to 190 °C for 0 min, increased at 2 °C min-1 to 220 °C for 7 min. Injector and detector temperatures were 250 and 300 °C, respectively. The flow rate through the column was 4 mL min-1. The LC analyses were performed by injecting the sample via a 50-µL loop while pumping mobile phase through a Whatman C18 Partisphere column. The mobile phase consisted of 40% methanol, 45% deionized water, and 15% pH 7 buffer mixture and was pumped at a flow rate of 2 mL min-1. The pH 7.4 buffer was made by mixing 244 mL of 0.067 M Na2HPO4 plus 156 mL of 0.067 M KH2PO4. Pesticides were detected with an Isco 2250 UV variable wavelength detector set at 225 or 254 nm with sensitivity set at 0.05 absorbance units full scale (AUFS). The GC-ECD and LCUV provided primary screening techniques. If a pesticide was detected by either of these techniques, confirmation was attempted with gas chromatography-mass spectroscopy (MS). Most of the pesticides were confirmed by injecting the sample into a Varian 3400 gas chromatograph equipped with Saturn II mass spectrometer detection device. A 1-µL injection in ethyl acetate was made with a septum programmable injector (SPI) in which the temperature could be altered to allow better resolution for the selected pesticides. The temperature program set for the SPI injector was 70 °C initially for 0.25 min, increased to 260 °C at 180 °C min-1, and then held for 2 min before cooling back to 70 °C. The column used was a 0.25 mm × 30 m capillary DB-5 with a temperature program of 70 °C for 0.25 min to 300 °C at a rate of 10 °C min-1, and then held for 4 min for a 28-min run time. The transfer line temperature was set at 260 °C. The analytes were ionized by electron impact. Pesticide detections were confirmed by matching the retention time and library mass spectrum of a pesticide standard to those of the unconfirmed analyte. Not all of the pesticides were confirmed with MS. Benomyl, fluometuron, and imazaquin were confirmed by co-chromatography with LCUV detection set at 254 nm wavelength absorbance. Statistical Evaluation. Descriptive statistics of detected concentrations were calculated by SAS (16). Output included quartiles of concentrations detected and percentage of nondetections for each pesticide. Separate analyses were

TABLE 1. Characteristics of Pesticides Analyzed in Surface Water Monitoring Studya

pesticide

chemical name

alachlor atrazine azinphos-methyl

2-chloro-N-(2,6-diethylphenyl)-N-methoxymethyl)acetamide 6-chloro-N-ethyl-N′-(1-methylethyl)-1,3,5-triazine-2,4-diamine S-(3,4-dihydro-[4-oxobenzo[d]-1,2,3]-triazin-3-ylmethyl) O,O-dimethyl phosphorodithioate methyl 1-(butylcarbamoyl)benzimidazol-2-ylcarbamate 1,2,3,6-tetrahydro-N-(trichloromethylthio)phthalimide 2-[[4-chloro-6-(ethylamino)-1,3,5-triazin-2-yl]amino]-2-methylpropanenitrile N,N-dimethyl-N′-[3-(trifluoromethyl)phenyl]urea 2-[4,5-dihydro-4-methyl-(1-methylethyl)-5-oxo-1H-imidazol-2-yl]-3-quinoline carboxylic acid O,O-dimethyl O-4-nitrophenyl phosphorothioate 2-chloro-N-(2-ethyl-6-methylphenyl)-N-2-methoxy-1-methylethyl)acetamide 4-amino-6-(1,1-dimethylethyl)-3-(methylthio)-1,2,4-triazin-5(4H)-one 4-chloro-5-(methylamino)-2-[3-(trifluoromethyl)phenyl]-3(2H)-pyridazinone N-(1-ethylpropyl)-3,4-dimethyl-2,6-dinitrobenzenamine O-4-bromo-2-chlorophenyl O-ethyl S-propyl phosphorothioate N-3,4-(dichlorophenyl)propanamide 6-chloro-N,N'-diethyl-1,3,5-triazine-2,4-diamine 2,6-dinitro-N,N-dipropyl-4-(trifluoromethyl)benzenamine

benomyl captan cyanazine fluometuron imazaquin methyl parathion metolachlor metribuzin norflurazon pendimethalin profenofos propanil simazine trifluralin a

water solubility (mg L-1)

soil half-life (d)

soil sorption (Koc)

240 33 29

15 60 10

170 100 1000

2 5 170 110 600

240 3 14 85 60

1900 200 190 100 20

24 530 1220 28 0 28 200 6 0

14 90 40 90 90 8 1 60 60

5000 200 60 600 5000 2000 149 130 8000

Data extracted from Wauchope et al. (17). These data represent values taken at 20-25 °C.

TABLE 2. Analyte Mean Percentage Recovery, Standard Error, Method of Detection, and Lower Limit of Quantitation As Determined by Laboratory Quality Control Samples Fortified at 20 µg L-1 in Surface Water Survey

pesticide alachlor atrazine azinphos-methyl benomyl captan cyanazine fluometuron imazaquin methyl parathion metolachlor metribuzin norflurazon pendimethalin profenofos propanil simazine trifluralin

mean standard recoverya errora (%) (%) 83 88 89 80 72 88 98 89 83 86 87 85 78 80 87 85 79

3 2 4 3 6 2 2 5 3 5 2 2 6 3 3 3 3

method of detectionb

LLQc (µg L-1)

ECD, MS LCUV, MS LCUV, MS LCUV ECD, MS ECD, LCUV, MS LCUV LCUV ECD, MS ECD, MS ECD, LCUV, MS ECD, LCUV, MS ECD, MS ECD, MS ECD, LCUV, MS LCUV, MS ECD, MS

0.1 0.1 0.3 0.4 0.2 0.1 0.4 1.0 0.2 0.1 0.1 0.3 0.1 0.2 0.2 0.1 0.1

a Mean recovery and standard error were calculated from values obtained from quality control samples fortified to a concentration of 20 µg L-1. b ECD, gas chromatography-electron capture detection; MS, gas chromatography-mass spectroscopy; LCUV, high-performance liquid chromatography-UV detection. c LLQ, lower limit of quantitation is defined as the level at which a pesticide was detected and quantified with co-chromatography and then confirmed with either MS or co-chromatography.

done for (1) all data combined in the 3-yr survey, (2) each county, (3) each sampling period, and (4) type of surface water sitesslakes (standing water) versus rivers and streams (running water).

Results and Discussion Analytical Methodology. The mean percentage recovery and standard error for each pesticide analyzed in the extraction method are listed in Table 2 along with the lower limit of quantitation (LLQ) and method(s) of detection. The LLQ was defined as the level at which a pesticide was detected and quantified using co-chromatography, then confirmed with either MS or co-chromatography assuming a 3:1 signal to

noise ratio. Mean recoveries ranged from 72.2 to 98.2% for pesticide analytes. The LLQ for the pesticide analysis ranged from 0.1 to 1 µg L-1. Total Pesticide Detections. Of the 8245 possible detections of the 485 samples collected in the 3-yr period, 256 detections of 14 pesticides were confirmed by MS or cochromatography (Table 3). Metolachlor was detected most often representing 64/256 or 25% of the total detections and was found in 64/485 or 13% of the samples. Atrazine was detected 56 times in surface water samples and represented 22% of the detections. Norflurazon (16% of total detections), cyanazine (14%), and fluometuron (8%) were detected at least 20 times in the surface water sampled. All of these compounds have been detected in other monitoring studies (11-15). Several reasons exist why the multiple detections of these compounds are expected. First, these herbicides are typically applied on bare soil in the spring such that more active ingredient is available in soil solution for plant uptake. This corresponds to increases in both plant availability and the probability of loss through surface runoff. Secondly, the herbicides metolachlor, cyanazine, atrazine, and norflurazon either were or are presently recommended on multiple crops in Arkansas, thereby increasing their frequency of use and the probability of being detected in surface water. Third, these herbicides are applied at higher rates as compared with newer herbicide chemistry (e.g., imidazolinones and sulfonylureas) and are relatively persistent with reported halflives of up to 3 months (17). Subsequently, combining these factors with water sampling during peak herbicide-use periods, it perhaps would be more surprising if these compounds were not detected. From an environmental standpoint, it is encouraging that detections of these compounds were not more frequent and that the concentrations detected did not exceed LHALs in more than 5% of the samples. Fourteen detections or approximately 5% of the 256 total detections were quantified at levels above health limits (Table 3). Seven of the 14 concentrations above the LHAL were from atrazine. The other pesticides detected above health limits were alachlor, cyanazine, methyl parathion, and simazine. Methyl parathion, norflurazon, pendimethalin, and propanil concentrations ranged from 2.7 to 3.5 µg L-1 at the 75th percentile, meaning that 75% of the concentrations detected did not exceed these levels. Seventy-fifth percentiles of the other six pesticides detected did not exceed 2.0 µg L-1,

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TABLE 3. Summary of Pesticide Analyses of Lake and River/Stream Surface Water from 485 Samples Collected at Eight Collection Dates in Mississippi, Lawrence, Phillips, and Jefferson Counties in Arkansas from 1989 to 1991 pesticide detected alachlor atrazine benomyl cyanazine fluometuron methyl parathion metolachlor metribuzin norflurazon pendimethalin profenofos propanil simazine trifluralin total

no. of no. of detections total no. of b -1 detections in rivers and no. of nondetectsa quartiles of detected concentrations (µg L ) LHALc detections in lakes streams detections (%) min lower median upper max (µg L-1) gLHAL 5 26 0 16 12 0 19 4 12 0 2 0 1 0 97

4 30 3 20 8 1 45 6 28 7 0 1 4 2 159

9 56 3 36 20 1 64 10 40 7 2 1 5 2 256

98.2 88.5 99.4 92.6 95.9 99.8 86.8 97.9 91.8 98.6 99.6 99.8 99.0 99.6

0.1 0.1 0.5 0.1 0.4

0.3 0.4 0.4 0.6

0.7 0.6 1.1 0.9 0.9

1.2 1.2 1.1 1.9

0.1 0.1 0.3 0.1 0.3

0.3 0.2 0.7 0.1

0.7 0.9 1.8 0.9

1.4 1.4 3.2 3.1

0.1 0.4

0.2

0.9

1.9

4.3 10.5 1.2 16.6 5.2 3.5 20.0 1.6 11.5 7.3 0.7 2.7 7.5 1.3

2d 3 NAe 10f 90 2 100 200 NA NA NA NA 4 2

2 7 NA 2 NA 1 0 0 NA NA NA NA 1 0 13

a Percent nondetects, defined as [1 - (total no. of detections/total samples analyzed)] × 100. b Quartiles: min, minimum concentration detected; lower, concentration that is higher than 25% of the concentrations detected; median, concentration that is higher than 50% of the concentrations detected or the median concentration; upper, concentration that is higher than 75% of the concentrations detected; max, maximum concentration detected. c LHAL, Lifetime Health Advisory Level (14, 22). d Value represents the maximum contaminant level rather than the LHAL for alachlor. This value is an enforceable level set by the Environmental Protection Agency for drinking water standards (14, 22). e NA, data not available. f During the study, the LHAL was lowered from 10 to 1 µg L-1. Since 10 µg L-1 was the level for the duration of the study, it was the LHAL reported.

TABLE 4. Average Hectares Harvested of Soybean, Cotton, Rice, Corn, and Sorghum in Four Counties of Arkansas Where Surface Water Was Monitored during 1989-199a county

total no. of detections

soybean

cotton

Jefferson Phillips Mississippi Lawrence total

80 65 81 30 256

40 867 77 933 107 867 36 900 263 567

34 033 38 200 62 500 0 134 733

a

17 833 8 167 6 833 24 233 57 067

1 400 5 167 9 467 7 967 24 001

corn

total

1 567 533 933 0 3 033

95 700 130 000 187 600 69 100 482 400

Data extracted from refs 18-20.

indicating that most of the detections were found at relatively low concentrations and below the LHAL. Pesticide Detections in Each County. The number of pesticide detections were sorted and graphed for each county. The highest number of pesticide detections occurred in Mississippi County where 81 detections were found in eight sampling periods (Table 4). Eighty detections were found in Jefferson County. Six detections were above the LHAL and represented the highest number of detections above the LHAL in any of the four counties studied. Of 128 samples collected in Phillips County, there were 65 detections of 12 pesticides during the survey. Norflurazon was the most commonly detected compound, representing approximately 13% of total detections from Phillips County (data not shown). Lawrence County had the fewest detections in surface water with 30 detections or approximately 12% of the total detections. Of the four counties in the survey, Lawrence County contained the smallest area of cropland harvested for the five major crops of Arkansas that include soybean, cotton, rice, corn, and sorghum (Table 4). Assuming 90% of the agricultural land in this county received pesticide applications, as was estimated in 1990 (1), Lawrence County would have had the least amount of pesticide applied and, therefore, a lower probability of pesticide detections in surface water. The most commonly detected compounds in Lawrence County were atrazine and metolachlor. These herbicides are commonly used for preemergence weed control in corn and sorghum. Virtually no corn is produced in Lawrence County, but it had the second highest harvested sorghum area of Arkansas counties in 1991 and the fourth highest in 1989 and

398

average hectares harvested rice sorghum

9

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1990 (18-20). Three of the seven detections of atrazine above the LHAL were in Lawrence County (data not shown). Pesticide detections tabulated for each county correlated well with the crops harvested and pesticides most likely used on those crops. The greater land area in row crops in Mississippi, Jefferson, and Phillips counties make these counties more susceptible than Lawrence County to pesticide contamination from surface runoff (Table 4). Mississippi County had the most harvested area of the five major Arkansas crops with 187 600 ha followed by Phillips (130 000 ha), Jefferson (95 700 ha), and Lawrence (69 100 ha) counties. The same trend was seen with the percentage of surface area of soybeans and cotton to the total land area harvested of the five major crops. Soybeans and cotton represented 91% of the harvested land of the five crops in Mississippi County where the most pesticide detections occurred. Phillips (89%), Jefferson (78%), and Lawrence (58%) had lower percentages of land in these crops. From these data, the probability of trace level pesticide contamination could be directly related to not only the total land area associated with crop production but also the area planted in specific crops, potentially representing a more intense pesticide program. Pesticide Detections during Each Sampling Period. Eleven pesticide detections were confirmed during the early spring sampling of 1989 (Figure 1). The fewer detections were probably due to the early spring sample collections made before the majority pesticide applications. Forty-two detections of nine pesticides occurred during the second sampling period. More detections during this sampling period were consistent with the timing of preemergence and postemer-

FIGURE 1. (A) Amount of rainfall (cm) recorded from March to November at weather stations in the four counties where surface water was sampled, and (B) total pesticide detections of lake and rivers/streams at the eight sampling periods during the study. The actual dates when samples were collected included (1) March 17April 8, 1989; (2) July 6-20, 1989; (3) October 14-November 8, 1989; (4) June 13-July 20, 1990; (5) October 4-20, 1990; (6) May 10-23, 1991; (7) July 20-26, 1991; and (8) November 5-11, 1991. gence pesticide applications and substantial rainfall in June 1989 (Figure 1). Of the 62 samples collected during the second sampling period, almost 25% contained quantifiable levels of norflurazon. In June-July 1990, 29 pesticide detections were confirmed with four detections above the LHAL (Figure 1). Twenty-two detections were confirmed in the fall. The summer sampling in 1990 showed 15 fewer detections than the sampling at a similar date the previous year. During this sampling period, rainfall was below the norm in all counties, which may have resulted in less runoff from pesticide-applied fields, thereby reducing the number of pesticide detections. The largest number of detections in samples collected during the spring (51 detections) and summer (53 detections) of 1991 was probably due to greater rainfall, particularly during April where the 28-48 cm of rainfall represented a 17-34 cm departure above the normal rainfall in these counties (Figure 1). Atrazine was the most commonly detected compound of the analytes tested in both the spring and summer sampling periods (data not shown). Although 41% of the total number of detections in the survey was from samples collected during spring and summer of 1991, only three detections were above the LHAL. These data suggested that more detections were not indicative of elevated concentrations that might cause adverse health effects if consumed. The fall of 1991 sampling produced more detections than any of the previous fall collections with 34 detections of eight pesticides. This was consistent with above average rainfall before sampling (Figure 1).

Several points are evident by assessing the pesticide analysis data of each sampling period. First, rainfall amounts prior to sample collection were consistent with more pesticide detections at those sampling periods. This suggested that more water-soluble and sediment-bound pesticides were collected due to higher volumes of agricultural runoff and that pesticides were detected periodically as pulses due to intermittent rainfall as Thurman et al. (15) discussed. Secondly, samples collected during the spring and summer accounted for 73% of the total pesticide detections although the samples collected during these periods represented approximately 63% of the total samples collected during the survey. These data supported findings by other researchers that more pesticide loading to rivers occurs earlier in the growing season when most of the pesticides are applied (8, 11-13, 15). Finally, the remaining 27% of the detections from fall sample collections supports conclusions from other researchers, who stated that some pesticides persist during the year in soil or water and may be stored in alluvial aquifers during the spring and summer months (15, 20). Ultimately, these pesticides contribute to surface water contamination at later sampling intervals. Comparisons of Pesticide Detections between Water Sources. Of the 222 lake samples collected, nine pesticides were detected a total of 97 times representing 38% of the total detections (Table 3). Atrazine was detected in approximately 12% of the samples analyzed. The remaining eight pesticides were detected at a frequency of 0.4-8.6%. Atrazine was detected above the LHAL in three of the lake samples, and cyanazine was detected above the LHAL once. In rivers and streams, 159 pesticide detections represented 62% of the total detections in the study (Table 3). Metolachlor was detected 45 times (17% detection) in rivers and streams. Ten of the 159 river and stream detections were above LHALs and represented 71% of the concentrations that exceeded the LHALs in the study. These data indicate that the streams sampled may be more susceptible to pesticide contamination by agricultural runoff than most of the lake sites tested. These results are not surprising considering the vast agricultural land area in the four counties studied that is divided by rivers and smaller tributaries. Exposure to more agricultural land and confluence with other potentially contaminated water bodies upstream would result in a greater probability of pesticide contamination in water from surface runoff. In contrast, the lake sites studied were generally more protected from agricultural surface runoff than most of the streams tested. Several lake sites were in public-access parks where levees had been engineered to prevent agricultural runoff from entering. Also, in the author’s observations, a lower percentage of the area surrounding lakes received pesticide applications and, consequently, was subjected to less contaminated runoff. Specific Sites with Repeat Detections. Repeated detections of the same compound occurred at several sites during the 3-yr survey. Four examples are shown in Table 5. The same pesticide was never detected at a specific site at all eight sampling periods. Lake Dick in Jefferson County had the highest number of repeated detections of a specific pesticide with six cyanazine detections out of eight samplings. These data suggest that contamination was not chronic but, at times, frequent. Few sites in the survey demonstrated this type of contamination, yet the sites that showed frequent detections may require further screening and implementation of pollution prevention measures depending on the pesticide levels and the surface water use. Decreasing concentrations with time were not evident at sites where repeated concentrations of the same pesticide were detected. This finding disputes earlier work with larger water sheds where higher concentrations were detected in the spring and then decreased toward the fall (11, 12). This trend was demonstrated at a few specific sites but was not

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3b 4 5 6 7 8

Period 2, July 6-20, 1989; period 3, October 14-November 8, 1989; period b a No detections were found in samples from collection dates 1 and 2 at Mississippi County sites nor for period 1 at Jefferson County sites. 4, June 13-20, 1990; period 6, May 10-23, 1991; period 7, July 20-26, 1991; period 8, November 5-11, 1991. c ND, not detected.

ND ND ND ND ND 0.8 ND ND ND 0.9 ND ND 0.4 ND ND 1.2 16.6 3.2 0.3 1.0 0.9 ND 1.4 ND ND ND 0.4 ND 3.2 ND 0.1 1.2 ND 1.0 0.7 7.0 NDc 10.5 ND 0.6 6.4

perioda

3.0 ND 9.1 0.1 0.6 0.6

ND ND ND 1.2 1.1 0.3

ND ND ND 0.4 0.5 0.2

ND 5.2 ND 1.1 ND ND

ND ND 0.3 ND ND 0.3

ND 1.1 ND 6.3 0.7 ND

9.7 ND ND 1.7 ND 0.4 ND

5.5 ND 0.5 2.4 ND 1.4 ND

fluometuron (µg L-1) cyanazine (µg L-1) norflurazon (µg L-1) metolachlor (µg L-1) cyanazine (µg L-1) metolachlor (µg L-1) fluometuron (µg L-1) cyanazine (µg L-1) atrazine (µg L-1)

metolachlor (µg L-1)

alachlor (µg L-1)

Crooked Lake Mississippi County

norflurazon (µg L-1)

location

Bayou Imbeau Jefferson County

atrazine (µg L-1)

Lake Dick Jefferson County

metolachlor (µg L-1) 9

unnamed lake Mississippi County

TABLE 5. Examples of Concentrations of Pesticides Detected Multiple Times at Specific Collection Dates and Specific Sites during Surface Water Survey (1989-1991) 400

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a common trend. Several reasons exist for the results of this study not corroborating conclusions from earlier work. First, larger bodies of surface water were reported in earlier work. These larger water bodies acted as intermediate sinks since they were confluent with numerous smaller tributaries that may have contained pesticides. Therefore, pesticide detections tended to be more constant making temporal concentration comparisons easier. In our study, the sites sampled were tributaries and lake sites that may eventually feed an intermediate sink, such as the Mississippi River, but they were distributed through varying landscapes, soils, and runoff sites with different site-specific characteristics. These sites were closer to the origin of the pesticide applications causing more erratic fluctuations in pesticide concentrations after rainfall. This hypothesis agrees with Goolsby et al. (12) where larger concentrations were detected in smaller tributaries leading to the Mississippi River. Although high concentrations were detected at some sampling periods in this study, concentrations typically did not remain at these levels the next sampling period. No pesticides were detected in six of the 33 rivers/streams and in five of the 29 lakes sampled in the four-county area at any of the sampling periods. These values suggest that 82 and 83% of the respective streams and lakes were affected by nonpoint source pollution. From national estimates by the U.S. EPA (3), 65 and 76% of streams and lakes, respectively, were said to have been affected by agricultural runoff and provide values comparable to results found in this study if the assumption is made that “affected” means a temporary low-level pesticide contamination of the water source.

Literature Cited (1) Agricultural Chemical Usage 1990 Field Crops Summary; U.S. Department of Agriculture; U.S. Government Printing Office: Washington, DC, 1991; USDA/NASS/ERS 282-964/40207. (2) Water Quality: Agriculture’s role; Task force report 120; Council for Agricultural Science and Technology: 1992; ISSN 0194-4096.. (3) National water quality inventory, report to Congress; U.S. Environmental Protection Agency, Office of Drinking Water: Washington, DC, 1986. (4) Hicks, D. W.; Asmussen, L. E.; Perkins, H. F. In Agronomy abstracts; American Society of Agronomy: Madison, WI, 1987; p 27. (5) Leonard, R. A. In Pesticides in the Soil Environment: Processes, Impacts, and Modeling; Cheng, H. H., Ed.; SSSA Book Series 2; Soil Science Society of America: Madison, WI, 1990; pp 303350. (6) Carroll, B. R.; Willis, G. H.; Graves, H. B. J. Environ. Qual. 1981, 10, 497-500. (7) Hall, J. K.; Hartwig, N. L. J. Environ. Qual. 1978, 7, 63-68. (8) Schottler, S. P.; Esenreich, S. J.; Capel, P. D. Environ. Sci. Technol. 1994, 28, 1079-1089. (9) Witt, W. W.; Sander, K. W. Potential of surface contamination from three triazine herbicides; Research Report 171; Water Resources Research Institute: Lexington, KY, 1988. (10) Wauchope, R. D. J. Environ. Qual. 1978, 7, 459-472. (11) Pereira, W. E.; Rostad, C. E. Environ. Sci. Technol. 1990, 24, 14001406. (12) Goolsby, D. A.; Coupe, R. C.; Markovchick, D. J. Distribution of selected herbicides and nitrate in the Mississippi River and its major tributaries, April through June 1991. Water Resour. Invest. U.S. Geol. Surv. 1991, No. 91-4163, 35. (13) Pereira, W. E.; Hostettler, F. D. Environ. Sci. Technol. 1993, 27, 1542-1552. (14) Drinking water regulations and health advisories; U.S. Environmental Protection Agency, Office of Drinking Water: Washington, DC, 1991. (15) Thurman, E. M.; Goolsby, D. A.; Meyer, M. T.; Kolpin, D. W. Environ. Sci. Technol. 1991, 25, 1794-1796. (16) SAS Institute. SAS language and proceduressVersion 6; SAS Institute: Cary, NC, 1988. (17) Wauchope, R. D.; Buttler, T. M.; Hornsby, A. G.; AugustijnBeckers, P. W. M.; Burt, J. P. Rev. Environ. Contam. Toxicol. 1992, 123, 1-164.

(18) Arkansas Agricultural Statistics 1989; Arkansas Agricultural Statistics Service. Arkansas Agricultural Experiment Station, University of Arkansas: 1990; Report Series 316. (19) Arkansas Agricultural Statistics 1990. Agricultural Statistics Service. Arkansas Agricultural Experiment Station, University of Arkansas: 1991; Report Series 320. (20) Arkansas Agricultural Statistics 1991. Agricultural Statistics Service. Arkansas Agricultural Experiment Station, University of Arkansas: 1992; Report Series 323. (21) Squillace, P. J.; Thurman, E. M.; Furlone, E. T. Water Resour. Res. 1993, 29, 1719-1729.

(22) Drinking Water Health Advisory: Pesticides; U.S. Environmental Protection Agency, Office of Drinking Water Health Advisories; Lewis Publishers: Chelsea, MI, 1989; 819 pp.

Received for review March 4, 1996. Revised manuscript received August 29, 1996. Accepted September 20, 1996.X ES960244C X

Abstract published in Advance ACS Abstracts, December 1, 1996.

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