Dataset for: SSDs Revisited: Part II - Practical Considerations in the Development and Use of Application Factors applied to Species Sensitivity Distributions
Posted on 2022-01-21 - 12:18 authored by Wiley Admin
Application Factors (AF) are routinely applied in the extrapolation of laboratory aquatic toxicity data to ensure protectiveness from exposure to chemicals in the natural environment. The magnitude of the AF is both a scientific and policy decision; however, in any case should be rooted in scientific knowledge so as to not be arbitrary. Information rich chemicals are often subjected to Species Sensitivity Distribution (SSD) analysis to transparently describe certain aspects of assessment uncertainty and are normally subjected to much smaller AF than screening information data sets. In this manuscript we describe a new set of tools useful to assess the quality of SSDs. Twenty-two data sets and 19 chemicals representing agrochemicals, biocides, surfactants, metals, and common wastewater contaminants were compiled to demonstrate how the tools can be used. “Add-one-In” and “Leave-one-out” simulations were used to investigate SSD robustness and develop quantitative evidence for the use of AFs. Theoretical new toxicity data were identified for add-one-in based on the expected probabilities necessary to lower the HC5 (5th percentile Hazard Concentration) by a factor of 2, 3, 5 or 10. Simulations demonstrate the basis for AFs in the range of 1 to 5 for well-studied chemicals with high quality SSDs. Leave-one-out simulations identify that the most influential values in the SSD comes from the extremes of the sensitive and tolerant toxicity values. Mesocosm and field data consistently demonstrate HC5s are conservative further justifying the use of small AFs for high quality SSDs.
CITE THIS COLLECTION
Belanger, Scott; Carr, Greg; Admin, Wiley (2022). Dataset for: SSDs Revisited: Part II - Practical Considerations in the Development and Use of Application Factors applied to Species Sensitivity Distributions. Wiley. Collection. https://doi.org/10.6084/m9.figshare.c.5803760.v1
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