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Please be aware that this old REACH registration data factsheet is no longer maintained; it remains frozen as of 19th May 2023.

The new ECHA CHEM database has been released by ECHA, and it now contains all REACH registration data. There are more details on the transition of ECHA's published data to ECHA CHEM here.

Diss Factsheets

Ecotoxicological information

Endpoint summary

Administrative data

Description of key information

QSAR results (K1) are available to assess the aquatic toxicity of the registered substance.

 To assess the short-term toxicity to aquatic invertebrate, algae and fish, three reliable QSAR results are available.The QSAR predictions (iSafeRat holistic approach v1.7 and v1.8) has been validated to be compliant with the OECD recommendations for QSAR modeling (OECD, 2004) and predict the ecotoxicological values which would be expected when testing the substance under experimental conditions in a laboratory following OECD Guidelines. The ecotoxicological predictions were determined using a validated QSAR for the Mode of Action in question, (MOA 1 or MechoA 1.1, non-polar narcosis) (Bauer et al. 2018). This QSAR is based on validated data for training sets for which the concentrations of the test substance had been determined by chemical analyses over the test period. According to these predictions, ecotoxicological data are the following:

- aquatic invertebrates: 48h-EC50 based on mobility was determined to be 1.0 mg/L (95% CL: 0.37 - 2.87 mg/L),

- algae: 72-h ErC50 based on growth rate was determined to be 0.92 mg/L (95% CL: 0.29 - 2.87 mg/L),

- fish: 96-h LC50 based on mortality was determined to be 0.87 mg/L (95%CL: 0.26 - 2.9 mg/L),

To assess the toxicity to microorganisms, one QSAR study is available on the registered substance wih a 30-180 min EC50 of THDCPD to activated sludge greater than the water solubility value within the exposure period of the test.

The substance falls within the applicability domain of the model.

Bauer F., Thomas, P., Fouchard S., Neunlist S., 2018. High-accuracy prediction of mechanisms of action using structural alerts. Computational Toxicology 7:36 -45

Additional information