Quantitative modelling of human health risks arising from pesticide use in Irish agriculture

Abstract

Pesticides have been identified as a growing concern due to the risk they pose to human health. Risk models can be used to predict pesticide concentrations in drinking water and analyse the associated health risks and hence allow for informed decision making and risk management. However, the majority of pesticide models currently in use are deterministic in nature, and do not reflect the inherent uncertainties and variabilities in pesticide transmission. Probabilistic-based approaches offer a powerful tool in this context as they can account for uncertainty and variability through the use of statistical input parameters to produce distributions of pesticide concentrations and health risks. This study develops a model which enables probabilistic assessment of risk posed to human health from pesticide runoff into water supplies. A Monte-Carlo-based approach was applied to enable the analysis of the probabilities of exceedance of chronic exposure levels to humans arising from the modelled transport of pesticides to drinking water. This model is applied to an Irish case study to allow for the identification of pesticides that could pose significant risks to drinking water. This may inform the implementation of risk mitigation measures to reduce pesticide pollution at source and/or identification of less harmful pesticides for use.