Pesticides transport

The documented occurrence of pesticides in surface water is indicative that mnoff is an important pathway for transport of pesticide away from the site of appHcation. An estimated 160 t of atra2ine, 71 t of sima2ine, 56 t of metolachlor, and 18 t of alachlor enter the Gulf of Mexico from the Mississippi River annually as the result of mnoff (47). Field appHcation of pesticides inevitably leads to pesticide contamination of surface mnoff water unless mnoff does not occur while pesticide residues remain on the surface of the soil. The amount of pesticides transported in a field in mnoff varies from site to site. It is controUed by the timing of mnoff events, pesticide formulation, physical—chemical properties of the pesticide, and properties of the soil surface (48). Under worst-case conditions, 10% or more of the appHed pesticide can leave the edge of the field where it was appHed. 

Sorbed pesticides are not available for transport, but if water having lower pesticide concentration moves through the soil layer, pesticide is desorbed from the soil surface until a new equiUbrium is reached. Thus, the kinetics of sorption and desorption relative to the water conductivity rates determine the actual rate of pesticide transport. At high rates of water flow, chances are greater that sorption and desorption reactions may not reach equihbrium (64). NonequiUbrium models may describe sorption and desorption better under these circumstances. The prediction of herbicide concentration in the soil solution is further compHcated by hysteresis in the sorption—desorption isotherms. Both sorption and dispersion contribute to the substantial retention of herbicide found behind the initial front in typical breakthrough curves and to the depth distribution of residues. 

Another consideration when planning field fortification levels for the matrices is the lowest level for fortification. The low-level fortification samples should be set high enough above the limit of quantitation (LOQ) of the analyte so as to ensure that inadvertent field contamination does not add to and does not drive up the field recovery of the low-fortification samples. Setting the low field fortification level too low will lead to unacceptably high levels of the analyte in low field spike matrix samples if inadvertent aerial drift or pesticide transport occurs in and around where the field fortification samples are located. Such inadvertent aerial drift or transport is extremely hard to avoid since wind shifts and temperature inversions commonly occur during mixer-loader/re-entry exposure studies. 

Onishi, Y. Wise, S.E. "Mathematical Model, SERATRA, for Sediment - Contaminant Transport in Rivers and its Application to Pesticide Transport in Four Mile and Wolf Creeks in Iowa EPA-600/3-82-045, U.S. Environ. Prot. Agency, Environ. Research Lab. Athens, Georgia,1982 p. 56. 

Young, G.K. Alward, C.L., Calibration and Testing of Pesticide Transport Models. Presented at Iowa State University Conference on Ag. Management and Water Quality. 1981. 

Watson, J., and P. Baker. (1990). Pesticide transport through soils. Tucson, Arizona Cooperative Extension, College of Agriculture, University of Arizona. 

Fig. 12.18A shows the results of an experiment using " C-labeled paraquat adsorbed on a clay mineral (Li-montmorillonite) suspension through a soil column. When the suspension medium was distilled water, 50% of the pesticides penetrated beyond 12 cm. Under these conditions, clay remains dispersed and pestieide is readily transported through the soil. However, for a suspension medium with an electrolyte concentration of 1 mM CaCl, paraquat remains in the upper 1 cm layer. The high calcium concentration results in rapid immobilization of the clay in the soil through flocculation, and consequently little pesticide transport occurs. 

Perhaps most easy to overlook are spatial and temporal dependencies. For example, the hydrologic component of the pesticide root zone model-exposnre analysis modeling system (PRZM-EX AMS) treats mnltiple field plots over whole watersheds as independent, nnconpled, simple, 1-dimensional flow systems. In reality, the field plots are coupled systems that exhibit complex 3-dimensional water flow and pesticide transport (US SAP 1999). These higher order processes introduce spatial dependencies that may need to be considered in the assessment. Temporal autocorrelations are also likely when assessing exposure. 

Isensee, A.R. and A.M. Sadeghi (1993). Impact of tillage practice on runoff and pesticide transport. J. Soil Water Cons., 48 523-527. 

Leonard, R.A., G.W. Langdale, and W.G. Fleming (1979). Herbicide runoff from upland Piedmont watersheds - data and implications for modeling pesticide transport. J. Environ. Qual., 8 223-229. 

Baker, D.B. (1998). Sediment, Nutrient, and Pesticide Transport in Selected Great Lakes Tributaries. Report to Great Lakes National Program Office, US Environmental Protection Agency, Region 5. Tiffin, OH Water Quality Laboratory, Heidelberg College. 

Arora, K., S.K. Mickelson, and J.L. Baker (2003). Effectiveness of vegetated buffer strips in reducing pesticide transport in simulated runoff. Am. Soc. Agric. Eng., 46(3) 635-644. 

The yellow carotene binding protein of M. sexta hemolymph is a more complicated case. Carotenes are extrerraTTy water-insoluble materials. They share this property with several other natural products including sterols, fats and hydrocarbons, all of > hich are important to insects. This property is also shared by many xenobiotics, including pesticides. Transport of hydrophobic materials within the aqueous compartments of living organisms, e.g. blood or hemolymph, is accomplished by lipoproteins. Extensive... 

Runoff pesticide transport was predicted within an order of magnitude and, after site specific calibration, within a factor of 3. 

Figure 1. Processes affecting water movement and pesticide transport in various environmental zones.

A number of quick-test techniques have been used widely to estimate the extent of sorption of pesticides to soils, and these estimates are often used in pesticide transport models. The most commonly used technique is to determine the ratio of distribution of a chemical, often at one concentration, between the solution and soil solid phases (K-) or simply the distribution between water and octanol phases CK ). The use of K, as an index of adsorption assumes that the stribution ratio is constant over a range of concentrations of the chemical in the soil. In other words, the amount of chemical adsorbed increases linearly with that remaining in the solution. The linear relationship may be valid over a narrow... 

Pesticide transport by surface runoff and soil erosion is a function of time lag between rainfall and application the chemical nature and persistence of the pesticide the hydrological, soil, and vegetative characteristics of the field and the method and target of application (43). Wauchope (44) found that unless severe rainfall occurred shortly after pesticide application, total losses for the majority of pesticides due to runoff were less than 0.5% of the amount applied in most cases, although single-event losses from small plots or watersheds can be much greater. 

This list is by no means an exhaustive one, but it reveals the multifarious interactions of the factors involved that affect all the processes. What we have attempted in this presentation was to point out some of the difficulties and pitfalls one should be aware of in any attempt to model pesticide transport as well as other factors affecting the fate of pesticide in the environment. While modeling can be an important tool for estimation of pesticide movement and fate in the environment, the current lack of knowledge of the mechanisms and interactions of factors and processes affecting pesticide behavior in the environment has led to assumptions and simplifications in the systems to be modeled. Errors either in estimation simplifications or inherent in the assumptions are difficult to quantify. Moreover, errors associated with inputs for each factor or process in the model can be compounded by errors in subsequent interactions. Thus predictive values obtained from many current models must all be accepted with caution if they are to be used for assessment purposes. 

Soils can be characterized in many ways, depending, for example, on whether primary concern relates to agronomic applications, engineering utility, or soil genesis. From the standpoint of predicting pesticide transport, a series of physical, chemical, and biological... 

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