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Statistical evaluation of chronic toxicity data on aquatic organisms for the hazard identification: the chemicals toxicity distribution approach
Authors:González-Doncel Miguel  Ortiz José  Izquierdo Juan J  Martín Bárbara  Sánchez Paloma  Tarazona José V
Institution:Laboratory for Ecotoxicology, Department of the Environment, National Institute for Agricultural and Food Research and Technology, A-6, Km 7.5, E-28040 Madrid, Spain. miguelgd@inia.es
Abstract:Presently, in the Globally Harmonised System of Classification and Labelling of Chemicals the classification of substances for long-term effects to aquatic life is based on acute toxicity in combination with degradation and/or bioaccumulation potential. Recently an OECD Working Group was created to develop the classification scheme to accommodate chronic toxicity data related to aquatic organisms for assigning a chronic hazard category. This study focuses on a new approach for setting chronic toxicity cut-off values based on Chemicals Toxicity Distributions (CTDs). A CTD is obtained through statistical fitting of the data used by regulatory bodies for setting hazard-based classifications. The CTDs were made using the lowest aquatic NOEC value of each chemical. A review of different toxicological sources reporting acute aquatic toxicities was carried out. Initially, the data were arranged according to the specific source and distributions for key taxonomic groups (i.e. fishes, crustaceans and algae) were evaluated separately. In most cases, no significant departures from normality were observed. Thereafter, a compiled database containing >900 values was developed and the CTDs were constructed for each taxonomic group. Significant deviation from normality (P < 0.05) was observed in the fishes and crustaceans' CTDs. However, this deviation was apparently produced by the presence of only seven values with NOECs <1 x 10(-5) mg l(-1), while high correlation between the data and the normal scores (r-values>or= 0.989) indicated that the data were samples from normal distributions. From these observations, potential cut-off values would allow quantitative estimations of the percentage of chemicals falling into each specific category. This approach results in a simple classification hazard scheme where most chemicals are covered in one of the categories, allowing a clear distribution of the chemicals among three categories for chronic toxicity.
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