Title

Modeling volatilization emissions of soil-applied pesticides under agricultural field conditions

Document Type

Article

Publication Date

12-1-2022

Abstract

Pesticides can volatilize from treated soil to the atmosphere causing increased environmental pollution and human exposure. Exposure assessment to airborne pesticides requires reasonable predictions of pesticide emissions. Understanding the volatilization behavior due to changes in environmental conditions can help in assessing the risk uncertainty and designing better mitigation strategies. In this study, we developed a mechanistic model that can be used to predict the hourly volatilization emissions from pesticide-treated soil at different environmental conditions. Pesticide properties and local environmental conditions drive the transport processes at the soil-air interface within the model. The numerical model simultaneously calculates the soil fluxes of heat, moisture, and pesticide at the soil-air interface with inputs of hourly meteorological data. The initial condition of pesticide concentration in soil is obtained from the applied mass during treatment. The numerical model was compared with an analytical model and with field observations for a soil injected fumigant and two surface applied pesticides. The model performance of 14 pesticides under stagnant conditions against the Jury's analytical model showed reasonable agreement with values for the coefficient of determination (R2) ranging from 0.76 to 0.99. The model was a good predictor of the field-scale volatilization of a fumigant (1,3-dichloropropene) application when compared to observations (R=20.8). Both the timing of the peak and the temporal variability of the measured volatilization of the fumigant were captured by the model when the fumigant was incorporated at a depth of 46 cm in the soil column. The model also showed reasonable agreement with the measured volatilization of two surface-treated pesticides, though site-specific meteorological data was unavailable for these observations. The results indicate that the modeling approach could be a useful tool to evaluate the impact of location-specific meteorological conditions on the field volatility of pesticides and determine the emissions for risk assessment.

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