Registration Dossier

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Please be aware that this old REACH registration data factsheet is no longer maintained; it remains frozen as of 19th May 2023.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

Administrative data

Endpoint:
toxicity to terrestrial plants: long-term
Type of information:
(Q)SAR
Adequacy of study:
key study
Study period:
2019
Reliability:
2 (reliable with restrictions)
Rationale for reliability incl. deficiencies:
results derived from a valid (Q)SAR model and falling into its applicability domain, with adequate and reliable documentation / justification
Justification for type of information:
Detailed information covering the calculation model, compositional data used as input, validity, applicability and adequacy of the result are in the attached document.

The registered substance is a complex mixture whose constituents within the mixture have variable physicochemical properties. Therefore, a modeling framework is needed to account for the bioavailability of the constituents in the mixture, which was then used to predict the toxicity of the substance as a whole.

The target lipid model (TLM) is a framework that relates toxicity to the physicochemical properties of a nonpolar organic constituent. The TLM, and HC5, have been applied to soils and sediment using equilibrium partitioning (EqP) model. This framework utilizes organic carbon partition coefficients (KOC) to convert aquatic based effect levels (CW) to bulk soil- and sediment-based effect levels. The combined TLM-EqP framework was validated previously for soil and sediment acute and chronic toxicity endpoints. The constituents in this substances are within the scope of the TLM and EqP frameworks.

Data source

Referenceopen allclose all

Reference Type:
publication
Title:
Refinement and validation of TLM-derived HC5 values. Independent review.
Author:
McGrath JA, Di Toro DM, Fanelli CJ
Year:
2015
Bibliographic source:
HDR, Mahwah, NJ
Reference Type:
publication
Title:
Extension and validation of the target lipid model for deriving predicted no-effect concentrations for soils and sediments
Author:
Redman AD, Parkerton TF, Paumen ML, McGrath JA, den Haan K, DiToro DM
Year:
2014
Bibliographic source:
Envrionmental Toxicology and Chemistry Vol. 33, No. 12, pp. 2679-2687 (2014)

Materials and methods

Principles of method if other than guideline:
The target lipid model (2015) as described in the cited reference was used to determine aquatic effect levels following an estimation of initial loading of the registered substance and its constituents in the substrate. A full explanation of the calculation method is provided in the 'attached justification'. For model description and justification of QSAR prediction: see fields 'justification for type of information' and 'attached justification'

Test material

1
Reference substance name:
1,2-Benzenedicarboxylic acid, tridecyl ester, manuf. of, by-products from
EC Number:
271-080-4
EC Name:
1,2-Benzenedicarboxylic acid, tridecyl ester, manuf. of, by-products from
Cas Number:
68515-39-9
Molecular formula:
none available
IUPAC Name:
1,​2-​Benzenedicarboxylic acid, tridecyl ester, manuf. of, by-​products from
Specific details on test material used for the study:
The registered substance is a UVCB substance consisting of a number of hydrocarbon and oxygenated hydrocarbon components, covering a wide range of carbon numbers and structures. The relevant components were determined based on the best available analytical data and process knowledge (see dossier sections 1.2 Composition and 1.4 Analytical methods). The representative structures and relative mass balance for each group of constituents are presented in the attached document.

Test organisms

open allclose all
Species:
Avena sativa
Plant group:
Monocotyledonae (monocots)
Species:
Brassica rapa
Plant group:
Dicotyledonae (dicots)

Results and discussion

Effect concentrationsopen allclose all
Species:
Brassica rapa
Duration:
21 d
Dose descriptor:
EC10
Effect conc.:
1.56 mg/kg soil dw
Nominal / measured:
nominal
Conc. based on:
test mat.
Basis for effect:
growth
Remarks on result:
other: Chronic endpoints estimated using typical acute-to-chronic ratio of 5
Species:
Brassica rapa
Duration:
14 d
Dose descriptor:
LC50
Effect conc.:
7.8 mg/kg soil dw
Nominal / measured:
nominal
Basis for effect:
seedling emergence
Species:
Avena sativa
Duration:
21 d
Dose descriptor:
EC10
Effect conc.:
2.42 mg/kg soil dw
Nominal / measured:
nominal
Basis for effect:
growth
Remarks on result:
other: Chronic endpoints estimated using typical acute-to-chronic ratio of 5
Species:
Avena sativa
Duration:
14 d
Dose descriptor:
LC50
Effect conc.:
12.1 mg/kg soil dw
Nominal / measured:
nominal
Conc. based on:
test mat.
Basis for effect:
seedling emergence

Applicant's summary and conclusion

Validity criteria fulfilled:
yes
Conclusions:
(Q)SAR estimations for the registered substance resulted in EC10 values of 1.56 and 2.42 mg/kg dw for Brassica rapa and Avena sativa, respectively, and LC50 values of 7.8 and 12.1 mg/kg dw for Brassica rapa and Avena sativa, respectively.
Executive summary:

The registered substance is a complex mixture whose constituents within the mixture have variable physicochemical properties. Therefore, a modeling framework is needed to account for the bioavailability of the constituents in the mixture, which was then used to predict the toxicity of the substance as a whole. The target lipid model (TLM) has been applied to aquatic toxicity and is considered fit for purpose. The target lipid model (TLM) and HC5, have been applied to soils and sediment using equilibrium partitioning (EqP) model. Further, an exposure assessment was performed using representative constituents, and RCR values of the individual constituents were summed to estimate the RCR values for the registered substance. RCR values below 1 were safely achieved for soil, freshwater and marine sediments, indicating a low level of risk to these environmental compartments. As such, modeled data are considered fit for purpose.