Parameterization models for pesticide exposure via crop consumption

Fantke, P, Wieland, P, Juraske, R, Shaddick, G ORCID: https://orcid.org/0000-0002-4117-4264, Eva, Sevigné Itoiz, Friedrich, Rainer and Olivier, Jolliet 2012. Parameterization models for pesticide exposure via crop consumption. Environmental Science and Technology 46 (23) , pp. 12864-12872. 10.1021/es301509u

Full text not available from this repository.

Abstract

An approach for estimating human exposure to pesticides via consumption of six important food crops is presented that can be used to extend multimedia models applied in health risk and life cycle impact assessment. We first assessed the variation of model output (pesticide residues per kg applied) as a function of model input variables (substance, crop, and environmental properties) including their possible correlations using matrix algebra. We identified five key parameters responsible for between 80% and 93% of the variation in pesticide residues, namely time between substance application and crop harvest, degradation half-lives in crops and on crop surfaces, overall residence times in soil, and substance molecular weight. Partition coefficients also play an important role for fruit trees and tomato (Kow), potato (Koc), and lettuce (Kaw, Kow). Focusing on these parameters, we develop crop-specific models by parametrizing a complex fate and exposure assessment framework. The parametric models thereby reflect the framework’s physical and chemical mechanisms and predict pesticide residues in harvest using linear combinations of crop, crop surface, and soil compartments. Parametric model results correspond well with results from the complex framework for 1540 substance-crop combinations with total deviations between a factor 4 (potato) and a factor 66 (lettuce). Predicted residues also correspond well with experimental data previously used to evaluate the complex framework. Pesticide mass in harvest can finally be combined with reduction factors accounting for food processing to estimate human exposure from crop consumption. All parametric models can be easily implemented into existing assessment frameworks.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	?? VCO ??
Publisher:	American Chemical Society
ISSN:	1520-5851
Date of Acceptance:	8 November 2012
Last Modified:	07 Aug 2024 14:15
URI:	https://orca.cardiff.ac.uk/id/eprint/170737

Actions (repository staff only)

Edit Item