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Please be aware that this old REACH registration data factsheet is no longer maintained; it remains frozen as of 19th May 2023.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

Environmental fate & pathways

Bioaccumulation: aquatic / sediment

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Administrative data

Link to relevant study record(s)

Description of key information

Standard Bioaccumulation studies for this endpoint are intended for monoconstituent substances and are not appropriate for petroleum UVCB substances. In accordance with Annex XI Section 1.3 the endpoint has been fulfilled using QSAR calculations for representative hydrocarbon structures that comprise the hydrocarbon blocks used to assess the environmental risk of this substance with the PETRORISK model (see the representative structures from the PETRORISK Product Library in the report attached in IUCLID section 13.2). As such, testing is not scientifically necessary.

 

The estimated BCF values of the constituents of this substance range from 11.75 to 4,786 L/kg and 6.91 to 2,040 L/kg Regression based estimation and Arno-Gobas method (upper trophic) (5% lipid normalisation), respectively.

 

QSAR predictions of bioaccumulation of gasoline have also been provided to support the read-across from gasoline to registration substance.

Key value for chemical safety assessment

Additional information

The bioconcentration factor (BCF) values of representative constituents of registration substance has been estimated using BCFBAF model, which uses methodology described by Arnot-Gobas et al. (2003, 2006, 2008). The estimated BCF values of representative constituents range from 11.75 to 4,786 L/kg and 6.91 to 2,040 L/kg Regression based estimation and Arno-Gobas method (upper trophic) (5% lipid normalisation), respectively. The predicted BCFs for hydrocarbons are generally overly conservative since biotransformation is not quantitatively taken into account. Therefore, indirect exposure and resulting risk estimates predicted are likely to be overestimated.