Fish acute toxicity of nine nanomaterials: Need of pre-tests to ensure comparability and reuse of data.

Fish acute toxicity tests are commonly used in aquatic environmental risk assessments, being required in different international substances regulations. A general trend in the toxicity testing of nanomaterials (NMs) has been to use standardized aquatic toxicity tests. However, as these tests were primarily developed for soluble chemical, issues regarding particle dissolution, agglomeration or sedimentation during the time of exposure are not considered when reporting the toxicity of NMs. The aim of this study was to characterize the NM behaviour throughout the fish acute test and to provide criteria to assay the toxicity of nine NMs based on TiO, ZnO, SiO, BaSO, bentonite, and carbon nanotubes, on rainbow trout following OECD Test Guideline (TG) nº203. Our results showed the importance of conducting a preliminary test (without fish) when working with NMs. They provide valuable information on, sample monitoring, agglomeration, sedimentation, dissolution, actual concentrations of NMs, needed to design the test. Among the NMs tested, only bentonite nanoparticles were stable during the 96-h pre-test and test in aquarium water. In contrast, the remaining NMs exhibited considerable loss and sedimentation within the first 24 h. The high sedimentation observed for almost all NMs highlights the need of consistently measuring the concentrations throughout the entire duration of the fish acute toxicity test to make reliable concentration-response relationships. Notable differences emerged in LC50 values when using actual concentrations as nominal concentrations overestimated concentrations by up to 85.6%. Among all NMs tested, only ZnO NMs were toxic to rainbow trout. A flow chart was specifically developed for OECD TG 203, aiding users in making informed decisions regarding the selection of test systems and necessary modifications to ensure accurate, reliable, and reusable toxicity data. Our findings might contribute to the harmonization of TG 203 improving result reproducibility and interpretability and supporting the development of read-across and QSAR models.