Science Inventory

Advancing Fifth Percentile Hazard Concentration Estimation Using Toxicity-Normalized Species Sensitivity Distributions

Citation:

Dhond, A. AND M. Barron. Advancing Fifth Percentile Hazard Concentration Estimation Using Toxicity-Normalized Species Sensitivity Distributions. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, 56(23):17188-17196, (2022). https://doi.org/10.1021/acs.est.2c06857

Impact/Purpose:

This subproduct is a manuscript for peer reviewed publication. The purpose is to advance hazard estimation using the species sensitivity distribution approach. The impact is the research reported in this publication is a substantial advancement to hazard estimation by allowing for more accuracte and less uncertain fifth percentile hazard quotients (HC5). The paper also presents a novel method for estimating uncertainty in HC5 using leave one out cross valication. Together these two new approach methods should substantially improve hazard esetimation for data limited chemicals.

Description:

The species sensitivity distribution (SSD) is an international approach to hazard estimation using the probability distribution of toxicity values that is representative of the sensitivity of a group of species to a chemical. Application of SSDs in ecological risk assessment has been limited by insufficient taxonomic diversity of species to estimate a statistically robust fifth percentile hazard concentration (HC5). The toxicity-normalized SSD (SSDn) approach1, modified to include all possible normalizing species, was used to estimate HC5 values for groups of carbamate and organophosphorous insecticides. Mean and variance of single chemical HC5 values were computed for each chemical using leave-one-out variance estimation and compared to SSDn and conventionally estimated HC5 values. SSDn-estimated HC5 values showed low uncertainty and high accuracy compared to single-chemical SSDs when including all possible combinations of normalizing species within the chemical-taxa grouping. The SSDn approach is recommended for estimating HC5 values for compounds with insufficient species diversity for HC5 computation or high uncertainty in estimated single-chemical HC5 values.