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2,4-dichlorophenoxyacetic acid (2,4-D) is a widely used herbicide with agricultural and nonagricultural applications. In the United States in 2001, 2,4-D ranked fifth among all pesticides in pounds of active ingredient applied in the agricultural market sector (28–33 million lb), the number one pesticide applied in both the home and garden market sector (8–11 million lb), as well as the industry, commercial and government market sector (16–18 million lb) (Donaldson et al. 2004). Studies of health outcomes related to chronic exposure to 2,4-D exposure have shown inconsistent results (Bukowska 2003; Burns et al. 2001; Figgs et al. 2000; Garabrant and Philbert 2002; Garry et al. 2001; Zahm et al. 1990), which may be attributed largely to difficulties with exposure characterization. Unlike studies of industrial pesticide manufacturing workers, which often use personnel and industrial hygiene records to reconstruct exposure histories, epidemiologic studies of herbicide exposure in farmers, farmworkers, and farm families have generally relied on self-reported activity-based questionnaires to estimate exposure potential. The validity of questionnaire data for determining exposures within the agricultural populations has not been established, but a few studies that have addressed the issue indicate the validity is variable (Blair et al. 2002; Engel et al. 2001). Farmers report general pesticide usage practices with reasonable reliability, but the validity of reporting specific chemicals is problematic (Blair and Zahm 1993; Engel et al. 2001). The magnitude of exposure has especially been difficult to quantify for farm family members, including the primary applicator. Pesticide use is clearly the primary determinant of exposure for applicators, but characterizing exposure intensity within populations of applicators is difficult. Notable efforts to improve exposure estimates are often based on other exposure surrogates (Dosemeci et al. 2002). However, developing valid exposure models based on these surrogates is an elusive undertaking; such models must be developed with relevant biological monitoring data (Acquavella et al. 2006; Arbuckle et al. 2002). To better characterize exposure from herbicide use, we present biomonitoring results from the Farm Family Exposure Study (FFES) evaluating 2,4-D exposure in farm family members following a single application as part of usual farm practice.

We used urinary biological monitoring to characterize chlorpyrifos (O,O-diethyl-O-(3,5,6-trichloro-2-pyridinyl) phosphororthioate) exposure to farm family members from Minnesota and South Carolina who participated in the Farm Family Exposure Study. Five consecutive 24-h urine samples were obtained from 34 families of licensed pesticide applicators 1 day before through 3 days after a chlorpyrifos application. Daily 3,5,6-trichloro-2-pyridinol (TCP) urinary concentrations characterized exposure profiles of the applicator, the spouse, and children aged 4-17 years. Self-reported and observed determinants of exposure were compared to the maximum postapplication TCP concentration. All participants had detectable (or = 1 microg/l) urinary TCP concentrations at baseline. Applicators' peak TCP levels occurred the day after the application (geometric mean (GM) = 19.0 microg/l). Postapplication TCP change from baseline in the spouses and children was negligible, and the only reliable predictor of exposure was assisting with the application for children aged 12 years and older. The applicators' exposure was primarily influenced by the chemical formulation (GM = 11.3 microg/l for granular and 30.9 microg/l for liquid), and the number of loads applied. Repairing equipment, observed skin contact, and eating during the application were moderately associated TCP levels for those who applied liquid formulations. Estimated absorbed doses (microg chlorpyrifos/kg bodyweight) were calculated based on TCP excretion summed over the 4 postapplication days and corrected for pharmacokinetic recovery. The GM doses were 2.1, 0.7, and 1.0 microg/kg bodyweight for applicators, spouses, and children, respectively. Chlorpyrifos exposure to farm family members from the observed application was largely determined by the extent of contact with the mixing, loading, and application process.

Epidemiologists often assess lifetime pesticide exposure by questioning participants about use of specific pesticides and associated work practices. Recently, Dosemeci and colleagues proposed an algorithm to estimate lifetime average exposure intensity from questionnaire information. We evaluated this algorithm against measured urinary pesticide concentrations for farmers who applied glyphosate (n = 48), 2,4-D (n = 34), or chlorpyrifos (n = 34).Algorithm scores were calculated separately based on trained field observers' and farmers' evaluations of application conditions. Statistical analyses included nonparametric correlations, assessment of categorical agreement, and categorical evaluation of exposure distributions.Based on field observers' assessments, there were moderate correlations between algorithm scores and urine concentrations for glyphosate (r = 0.47; 95% confidence interval [CI] = 0.21 to 0.66) and 2,4-D (0.45; 0.13 to 0.68). Correlations were lower when algorithm scores were based on participants' self-reports (for glyphosate, r = 0.23 [CI = -0.07 to 0.48]; for 2,4-D, r = 0.25 [-0.10 to 0.54]). For chlorpyrifos, there were contrasting correlations for liquid (0.42; 0.01 to 0.70) and granular formulations (-0.44; -0.83 to 0.29) based on both observers' and participants' inputs. Percent agreement in categorical analyses for the 3 pesticides ranged from 20% to 44%, and there was appreciable overlap in the exposure distributions across categories.Our results demonstrate the importance of collecting type of pesticide formulation and suggest a generic exposure assessment is likely to result in appreciable exposure misclassification for many pesticides.

Field monitoring and scenario-based modelling were used to assess exposure of small ditches in the UK to the herbicide sulfosulfuron following transport via field drains. A site in central England on a high pH, clay soil was treated with sulfosulfuron, and concentrations were monitored in the single drain outfall and in the receiving ditch 1 km downstream. Drainflow in the nine months following application totalled 283 mm. Pesticide lost in the first 12.5 mm of flow was 99% of the total loading to drains (0.5% of applied). Significant dilution was observed in the receiving ditch and quantifiable residues were only detected in one sample (0.06 µg litre−1). The MACRO model was evaluated against the field data with minimal calibration. The parameterisation over-estimated the importance of macropore flow at the site. As a consequence, the maximum concentration in drainflow (2.3 µg litre−1) and the total loading to drains (0.76 g) were over-estimated by factors of 2.4 and 5, respectively. MACRO was then used to simulate long-term fate of the herbicide for each of 20 environmental scenarios. Resulting estimates for concentrations of sulfosulfuron in a receiving ditch were weighted according to the prevalence of each scenario to produce a probability distribution of daily exposure. Copyright © 2004 Society of Chemical Industry

A new regulatory approach is needed to characterize peak pesticide concentrations in surface waters over a range of watershed scales. Methods now in common use rely upon idealized edge-of-field scenarios that ignore scaling effects. Although some watershed-scale regulatory models are available, their complexity generally prevents them from being used duringthe pesticide registration decision process, even though nearly all exposure to both humans and aquatic organisms can occur only at this scale. The theory of fractal geometry offers a simpler method for addressing this regulatory need. Mandelbrot described rivers as "space-filling curves" (Mandelbrot, B. B. The Fractal Geometry of Nature; Freeman: New York, 1983), a class of fractal objects implying two useful properties we exploit in this work. The first is a simple power-law relationship in which log-log plots of maximum daily concentrations as a function of watershed area tend to be linear with a negative slope. We demonstrate that the extrapolation of such plots down to smaller watersheds agrees with edge-of-field concentrations predicted using the Pesticide Root Zone Model, but only when the modeling results are properly adjusted for use intensity within the watershed. We also define a second useful property, "scale-invariant dispersion", in which concentrations are well described by a single analytical solution to the convective--dispersion equation, regardless of scale. Both of these findings make it possible to incorporate the effect of watershed scale directly into regulatory assessments.

Glyphosate is the active ingredient in Roundup agricultural herbicides and other herbicide formulations that are widely used for agricultural, forestry, and residential weed control. As part of the Farm Family Exposure Study, we evaluated urinary glyphosate concentrations for 48 farmers, their spouses, and their 79 children (4-18 years of age). We evaluated 24-hr composite urine samples for each family member the day before, the day of, and for 3 days after a glyphosate application. Sixty percent of farmers had detectable levels of glyphosate in their urine on the day of application. The geometric mean (GM) concentration was 3 ppb, the maximum value was 233 ppb, and the highest estimated systemic dose was 0.004 mg/kg. Farmers who did not use rubber gloves had higher GM urinary concentrations than did other farmers (10 ppb vs. 2.0 ppb). For spouses, 4% had detectable levels in their urine on the day of application. Their maximum value was 3 ppb. For children, 12% had detectable glyphosate in their urine on the day of application, with a maximum concentration of 29 ppb. All but one of the children with detectable concentrations had helped with the application or were present during herbicide mixing, loading, or application. None of the systemic doses estimated in this study approached the U.S. Environmental Protection Agency reference dose for glyphosate of 2 mg/kg/day. Nonetheless, it is advisable to minimize exposure to pesticides, and this study did identify specific practices that could be modified to reduce the potential for exposure.

Epidemiologic studies rely on participants' recall to classify their exposure to specific pesticides. As exposure classification evolves, an important issue is whether the recall of pesticide application details can be used to derive measures of exposure intensity or cumulative exposure. A preliminary analysis of biomonitoring data for farmers before, during, and after a pesticide application suggests variation for different pesticides in the proportion with detectable urinary concentrations, urinary levels, and patterns of uptake and elimination. These findings, and the limited predictive modeling done to date, suggest that chemical-specific differences need to be considered in exposure classification schemes. An analysis of biomonitoring data for farm spouses and children found few with appreciable changes in the urinary concentration after a pesticide application. These findings point to the need to validate assumptions about exposures in studies of people who are not directly involved in pesticide application.

Biomonitoring was used to assess the combined dermal, oral, and inhalation exposure associated with the agricultural use of Harness Plus, an emulsifiable concentrate formulation of the herbicide acetochlor. Twenty Spanish farmers handled and applied acetochlor to maize in the spring of 2003, following the product label recommendations. Open- and closed-cabin applications were equally represented. Urine was collected during six consecutive days, starting the day prior to application. Daily composites were analyzed for 2-ethyl-6-methyl-aniline, a common chemophore representing the major urinary acetochlor metabolites. All applicators showed detectable concentrations in urine after application. Although, the open-cabin applicators treated fewer hectares, they showed significantly higher exposure compared to the closed-cabin applicators (average exposure: 0.004 and 0.002 mg/kg bw/day, respectively). Linear regression analysis suggested that untracked incidents had a significant impact on the total exposure. Other events that may have contributed to the observed exposure are repair of faulty equipment, accidental spillages, splashes, and inadequate use of protective gloves. The average margins of exposure (MOE) for farmers ranged from 23,000 (open cabin) to about 44,000 (closed cabin). For professional applicators the MOEs were 10-fold lower. These MOEs clearly indicate that no adverse health effects should be expected from agricultural acetochlor applications.

We thank Mage for his comments. In our article on glyphosate in the Farm Family Exposure Study (FFES) (Acquavella et al. 2004), we used 24-hr urinary creatinine to assess the completeness of daily samples over 5 days for the 48 participating farmers. We erred by summarizing the results as micrograms per deciliter instead of micrograms per day. Using an expected daily excretion of 566 μg/day as the lower end of the normal range (Bingham et al. 1988; Forman 2003), only four 24-hr urine samples over 5 days were below that lower limit. Therefore, the completeness of urine collection for the applicators was exceptional. Further details of the urine collection and our assessment of completeness can be found in a related article (Baker et al. 2005). Mage criticizes us for not subtracting preapplication urine values in our assessment of systemic dose related to on-study applications. Indeed, seven of the applicators had detectable glyphosate in their urine on the day before their on-study application (Acquavella et al. 2004). Values were 1.1, 2.6, 3.9, 5.3, 8.3, 9.8, and 15.4 ppb. We intentionally did not correct for these initial values for two reasons. First, from an epidemiologic and public health standpoint, it is instructive to know the total dose for farmers during and after an application, which, for example, could then be compared to levels of toxicologic significance. Second, the overestimate caused by this practice is trivial for glyphosate in both an absolute and relative sense. Consider that glyphosate has a U.S. Environmental Protection Agency (EPA) reference dose of 2 mg/kg/day (U.S. EPA 1999), and the highest systemic dose we estimated in our study was 0.004 mg/kg/day. The requested corrections would be to the ten thousandths of a milligram per kilogram per day or less. Last, Mage calls the fact that we only evaluated one application per farm family a limitation that may vitiate our study. That is a strong indictment for a study that comprehensively assessed exposure for farm families related to a single application of three pesticides to an extent not seen before. We agree that characterizing intraperson variation in absorbed pesticide dose over several seasons would provide valuable information, but that was not the objective of the FFES. Nevertheless, Mage’s claim that we cannot reject the possibility that all 47 applicators have the same exposure distribution is refuted by our observations that absorbed dose was related to specific practices (e.g., not wearing gloves) and by similar findings in the literature that practices dictate absorbed dose (e.g., Arbuckle et al. 2002).