Inhaltszusammenfassung

The quantification of risk (the likelihood and extent of adverse effects) is a prerequisite in regulatory decision making for plant protection products and is the goal of the Xplicit project. In its present development stage, realism is increased in the exposure assessment (EA), first by using real-world data on, e.g., landscape factors affecting exposure, and second, by taking the variability of key factors into account. Spatial and temporal variability is explicitly addressed. Scale depende...The quantification of risk (the likelihood and extent of adverse effects) is a prerequisite in regulatory decision making for plant protection products and is the goal of the Xplicit project. In its present development stage, realism is increased in the exposure assessment (EA), first by using real-world data on, e.g., landscape factors affecting exposure, and second, by taking the variability of key factors into account. Spatial and temporal variability is explicitly addressed. Scale dependencies are taken into account, which allows for risk quantification at different scales, for example, at landscape scale, an overall picture of the potential exposure of nontarget organisms can be derived (e.g., for all off-crop habitats in a given landscape); at local scale, exposure might be relevant to assess recovery and recolonization potential; intermediate scales might best refer to population level and hence might be relevant for risk management decisions (e.g., individual off-crop habitats). The Xplicit approach is designed to comply with a central paradigm of probabilistic approaches, namely, that each individual case that is derived from the variability functions employed should represent a potential real-world case. This is mainly achieved by operating in a spatiotemporally explicit fashion. Landscape factors affecting the local exposure of habitats of nontarget species (i.e., receptors) are derived from geodatabases. Variability in time is resolved by operating at discrete time steps, with the probability of events (e.g., application) or conditions (e.g., wind conditions) defined in probability density functions (PDFs). The propagation of variability of parameters into variability of exposure and risk is done using a Monte Carlo approach. Among the outcomes are expectancy values on the realistic worst-case exposure (predicted environmental concentration [PEC]), the probability p that the PEC exceeds the ecologically acceptable concentration (EAC) for a given fraction of habitats, and risk curves. The outcome can be calculated at any ecologically meaningful organization level of receptors. An example application of Xplicit is shown for a hypothetical risk assessment for nontarget arthropods (NTAs), demonstrating how the risk quantification can be improved compared with the standard deterministic approach. » weiterlesen» einklappen

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