Fate model pesticides

Tejada AW, Varca LM, Calumpang SMP, et al. 1997. Fate of pesticides in a model rice paddy ecosystem. In Environ Behav Crop Prot Chem Proc Int Symp Use Nucl Relat Tech Stud Environ Behav Crop Prot Chem 1996, Int Atom Energy Agency Vienna, Austria pp. 265-278. 

Because of the requirements of regulations for certain chemicals such as pesticides, extensive data usually exist on partitioning properties and reactivity or half-lives of active ingredients. In some cases these data have been peer-reviewed and published in the scientific literature, but often they are not generally available. A reader with interest in a specific pesticide can often obtain additional data from manufacturers or from registration literature, including accounts of chemical fate under field application conditions. Frequently these data are used as input to pesticide fate models, and the results of these modeling exercises may be available or published in the scientific literature. 

Model ecosystems have been used for about 8 years to measure the distribution and fate of pesticides in the aquatic environment. Over that period of time numerous design changes have evolved that have increased the versatility of the ecosystem and improved simulation of environmental conditions. In our laboratory, we have used the static model ecosystem primarily to model the pond or small lake environment, and to simulate the likely rates and modes of pesticide entry (1). More recently, we have developed larger systems capable of providing sufficient biomass for accumulation and dissipation rate determinations (2) and for metabolic studies (3). 

FOCUS] Forum for Coordination of Pesticide Fate Models and Their Use. 2001. Report prepared by the FOCUS Working Group on Surface Water scenarios FOCUS Surface Water scenarios in the EU evaluation process under Dir. 91/414/EEC, SANCO/4802/2001-rev. 2 final May 2003, p 238. 

Adriaanse PI. 1996. Fate of pesticides in field ditches the TOXSWA simulation model. No. 90. Wageningen (The Netherlands) Winand Staring Institute. 

FOCUS groundwater scenarios in the EU review of active substances" - The report of the work of the Groundwater Scenarios Workgroup of FOCUS (FOrum for the Co-ordination of pesticide fate models and their USe), Version 1 of November 2000. EC Document Reference Sanco/321/2000 rcv.2,202pp. 

FOCUS, Leaching models and EU registration. Final report of the work group - Forum for the coordination of pesticide fate models and their use funded by the European Commission, The European Crop Protection Association and COST Action 66,1995, Deo. 4952A I/95. 

Few studies have been carried out on the fate of pesticides in tropical ecosystems. If reported, they often lack an appropriate assessment of the processes that affect fate and factors influencing those processes imder specific conditions. Due to the complexity of the environmental problems, modeling is seen as an essential tool in resolving them. 

A.W. Tejada, L.M. Varca, S.M.F. Calumpang, C.M. Bajet, M.J.B. Medina, Fate of Pesticides in a Model Rice Paddy Ecosystem, in Proceedings of a Symposium Environmental Behavior of Crop Protection Chemicals, IAEA-SM-343/33, Viena, Austria, 1997, pp. 265-278. 

Padilla F., LaFrance P., Robert C., and ViUeneuve J. (1988) Modeling the transport and the fate of pesticides in the unsaturated zone considering temperature effects. Ecol. Model. 44, 73-88. 

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. 

A major advantage to models such as PRZM or PESTANS is that they are transportable they can simulate a variety of situations with simple changes in weather input and parameters. More Importantly, however, is the fact that in most situations, 90% or more of applied pesticide would have runoff, volatilized, been taken up by the plant, or otherwise decayed before any of it leaches below the root zone. It makes sense, therefore, to develop the capability to predict the fate of pesticides in the root zone, and hence determine the potential for pesticides to contaminate ground water. 

Forum for the Co-ordination of Pesticide Fate Models and their Use Individual-based models Level of concern... 

Probabilistic risk assessment through pesticide fate modeling for evaluating management practices to prevent pesticide runoff from paddy fields (S. H. Vu, Tokyo Univ. of Agric. Tech., Japan)... 

J. Dressel, C. Beigel, Estimation of standardized transformation rates of a pesticide and its four soil metabolites from field dissipation studies for use in environmental fate modeling, Proc. BCPC Conference - Weeds 119-126 (2001). 

Al ough alachlor is no longer used in the U.S., the three chemical compounds have very similar structural (Figure 1) and chemical properties. Alachlor degradataion data may be useful as a model for this chemical class. Caution must be used in interpolating these data however since the ESA metabolite of metolachlor is formed more slowly and at lower concentrations in soil (18). The objective of this study was to compare atrazine and alachlor sorption, mineralization, and degradation potential, processes that are major contributors to the environmental fate of pesticides, from surface soil to aquifer sediments in laboratoiy studies. In addition, ctegradation of alachlor was compared under aerobic and anaerobic conditions. 

The solubility of methyl parathion is not sufficient to pose a problem in runoff water as determined by an empirical model of Wauchope and Leonard (1980). Some recent monitoring data, however, indicate that methyl parathion has been detected in surface waters (Senseman et al. 1997). In a study to determine the residue levels of pesticides in shallow groundwater of the United States, water samples from 1,012 wells and 22 springs were analyzed for methyl parathion. No methyl parathion was detected in any of the water samples (Kolpin et al. 1998). In a study of water from near-surface aquifers in the Midwest, no methyl parathion was detected in any of the water samples from 94 wells that were analyzed for pesticide levels (Kolpin et al. 1995). Leaching to groundwater does not appear to be a significant fate process. 

Output from the soil erosion, pesticide fate, and economics submodels may not be needed for ET landfill cover evaluation and design they can be disregarded without affecting other components of the model estimate. 

Simple models are used to Identify the dominant fate or transport path of a material near the terrestrial-atmospheric Interface. The models are based on partitioning and fugacity concepts as well as first-order transformation kinetics and second-order transport kinetics. Along with a consideration of the chemical and biological transformations, this approach determines if the material is likely to volatilize rapidly, leach downward, or move up and down in the soil profile in response to precipitation and evapotranspiration. This determination can be useful for preliminary risk assessments or for choosing the appropriate more complete terrestrial and atmospheric models for a study of environmental fate. The models are illustrated using a set of pesticides with widely different behavior patterns. 

The quantitative water air sediment interaction (Qwasi) model was developed in 1983 in order to perform a mathematical model which describes the behavior of the contaminants in the water. Since there are many situations in which chemical substances (such as PCBs, pesticides, mercury, etc.) are discharged into a river or a lake resulting in contamination of water, sediment and biota, it is interesting to implement a model to assess the fate of these substances in the aquatic compartment [34]. 

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