Statistically based soil climate exposure scenarios for aquatic pesticides fate modelling and exposure assessment in the Pampa Region of Argentina

Although pesticides are used intensively in Argentina's Pampa region, the possibility of performing an environmental risk assessment (ERA) remains limited due to the absence of readily available databases to run pesticide fate models and the lack of standardized realistic worst‐case scenarios. The a...

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Detalles Bibliográficos
Autores principales: Brodeur, Celine Marie, D'andrea, María Florencia, Dip, Cecilia
Formato: info:ar-repo/semantics/artículo
Lenguaje:Inglés
Publicado: Wiley 2022
Materias:
Acceso en línea:http://hdl.handle.net/20.500.12123/13125
https://setac.onlinelibrary.wiley.com/doi/abs/10.1002/ieam.4656
https://doi.org/10.1002/ieam.4656
Descripción
Sumario:Although pesticides are used intensively in Argentina's Pampa region, the possibility of performing an environmental risk assessment (ERA) remains limited due to the absence of readily available databases to run pesticide fate models and the lack of standardized realistic worst‐case scenarios. The aim of the present study was to further advance capacities for performing probabilistic ERAs in the Pampa region by dividing and parameterizing the region into functional soil–climate mapping units (SCU) and defining statistically based, worst‐case soil–climate exposure scenarios. Results obtained demonstrate that the SCU selected for a specific modeling exercise should depend on the dissociation constant (Kd) of the pesticide evaluated and whether short‐ or long‐term pesticide fate modeling and risk assessment are needed. Four regionally representative SCUs were specifically identified for modeling the fate of pesticides with low, high, and intermediate values of Kd. Fate modeling of pesticides with an intermediate Kd requires the use of a different SCU for short‐ versus long‐term pesticide modeling, whereas this distinction is not necessary for pesticides with both low and high Kd. The current definition of realistic, worst‐case, soil–climate scenarios represents a crucial step toward better pesticide fate modeling and exposure assessment in Argentina's Pampa region.