Relationship between physicochemical properties and maximum residue levels and tolerances of crop-protection products for crops set by the USA, European Union and Codex

A review of the factors that influence pesticide residues in pollen and nectar: Future research requirements for optimising the estimation of pollinator exposure

In recent years, the impact of Plant Protection Products (PPPs) on insect pollinator decline has stimulated significant amounts of research, as well as political and public interest. PPP residues have been found in various bee-related matrices, resulting in governmental bodies worldwide releasing guidance documents on methods for the assessment of the overall risk of PPPs to different bee species. An essential part of these risk assessments are PPP residues found in pollen and nectar, as they represent a key route of exposure. However, PPP residue values in these matrices exhibit large variations and are not available for many PPPs and crop species combinations, which results in inaccurate estimations and uncertainties in risk evaluation. Additionally, residue studies on pollen and nectar are expensive and practically challenging. An extrapolation between different cropping scenarios and PPPs is not yet justified, as the behaviour of PPPs in pollen and nectar is poorly understood. Therefore, this review aims to contribute to a better knowledge and understanding of the fate of PPP residues in pollen and nectar and to outline knowledge gaps and future research needs. The literature suggests that four primary factors, the crop type, the application method, the physicochemical properties of a compound and the environmental conditions have the greatest influence on PPP residues in pollen and nectar. However, these factors consist of many sub-factors and initial effects may be disguised by different sampling methodologies, impeding their exact characterisation. Moreover, knowledge about these factors is ambiguous and restricted to a few compounds and plant species. We propose that future research should concentrate on identifying relationships and common features amongst various PPP applications and crops, as well as an overall quantification of the described parameters; in order to enable a reliable estimation of PPP residues in pollen, nectar and other bee matrices.

A hierarchical Bayesian model for extreme pesticide residues

The number of residue measurements in an individual field trial, carried out to provide data for a pesticide registration for a particular crop, is generally too small to estimate upper tails of the residue distribution for that crop with any certainty. We present a new method, using extreme value theory, which pools information from various field trials, with different crop and pesticide combinations, to provide a common model for the upper tails of residue distributions generally. The method can be used to improve the estimation of high quantiles of a particular residue distribution. It provides a flexible alternative to the direct fitting of a distribution to each individual dataset, and does not require strong distributional assumptions. By using a hierarchical Bayesian model, our method also accounts for parameter uncertainty. The method is applied to a range of supervised trials containing residues on individual items (e.g. on individual apples), and the results illustrate the variation in tail properties amongst all commodities and pesticides. The outputs could be used to select conservative high percentile residue levels as part of a deterministic risk assessment, taking account of the variability between crops and pesticides and also the uncertainty due to relatively small datasets.