Toxicology Letters 2012-08-13

Integration of biological monitoring, environmental monitoring and computational modelling into the interpretation of pesticide exposure data: introduction to a proposed approach.

Claudio Colosio, Federico M Rubino, Athanasios Alegakis, Eugenio Ariano, Gabri Brambilla, Stefan Mandic-Rajcevic, Francesca Metruccio, Claudio Minoia, Angelo Moretto, Chiara Somaruga, Aristidis Tsatsakis, Roberta Turci, Francesca Vellere

Index: Toxicol. Lett. 213(1) , 49-56, (2012)

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Abstract

Open field, variability of climatic and working conditions, and the use of complex mixtures of pesticides makes biological and environmental monitoring in agriculture, and therefore risk assessment and management, very complicated. A need of pointing out alternative risk assessment approaches, not necessarily based on measures, but simple, user-friendly and reliable, feasible also in the less advanced situations and in particular in small size enterprises, arises. This aim can be reached through a combination of environmental monitoring, biological monitoring and computational modelling. We have used this combination of methods for the creation of "exposure and risk profiles" to be applied in specific exposure scenarios, and we have tested this approach on a sample of Italian rice and maize herbicide applicators. We have given specific "toxicity scores" to the different products used and we have identified, for each of the major working phases, that is mixing and loading, spraying, maintenance and cleaning of equipment, the main variables affecting exposure and inserted them into a simple algorithm, able to produce "exposure indices". Based on the combination of toxicity indices and exposure indices it is possible to obtain semiquantitative estimates of the risk levels experienced by the workers in the exposure scenarios considered. Results of operator exposure data collected under real-life conditions can be used to validate and refine the algorithms; moreover, the AOEL derived from pre-marketing studies can be combined to estimate tentative biological exposure limits for pesticides, useful to perform individual risk assessment based on technical surveys and on simple biological monitoring. A proof of principle example of this approach is the subject of this article.Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.