One of the aims of the European project LIFE-COMBASE is to build a computational tool to predict the acute toxicity for aquatic organisms of biocidal active substances and its environmental degradation products. A database was implemented compiling toxicity data for these substances in organisms of the freshwater/marine and sewage treatment plant compartments. The goal of this study is to analyze the compiled data to identify the possible hazard of these compounds for the aquatic compartments. Several official and scientific databases were consulted. Data from 196 biocidal substances and 206 environmental metabolites were collected for the taxonomic groups, including fish, invertebrates, algae and sewage treatment plant (STP) microorganisms. Substances were categorized for their toxicity in four groups, considering values of L(E)C50, according to EU Regulation (EC) No 1272/2008. >50% of the parent were located in category 1 (L(E)C50 ≤ 1 mg/L) for fish, invertebrates and algae, indicating a high toxicity for the freshwater/marine compartments. However >60% were not toxic for STP microorganisms. Metabolites were mainly less toxic than the parent compounds, but 22-36% presented the same toxicity and ~6% were more toxic. No toxicological information was found for ~50% of the metabolites for fish, invertebrates and algae, reaching the 96% for the microorganisms. In addition, information on toxicity to the STP microorganisms was only found for 40% of the parent compounds. The high percentage of toxic metabolites and the scarcity of data for these compounds indicate the need to further study their impact in the aquatic compartments.
Acute hazard of biocides for the aquatic environmental compartment from a life-cycle perspective.
D. Hernández-Moreno,M. Blázquez,Óscar Andreu-Sánchez,A. Bermejo-Nogales,M. Fernández-Cruz
Published 2019 in Science of the Total Environment
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- Publication year
2019
- Venue
Science of the Total Environment
- Publication date
2019-03-25
- Fields of study
Biology, Medicine, Chemistry, Environmental Science
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Semantic Scholar, PubMed
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