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EC number: 229-355-1 | CAS number: 6486-23-3
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- Ecotoxicological Summary
- Aquatic toxicity
- Endpoint summary
- Short-term toxicity to fish
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- Short-term toxicity to aquatic invertebrates
- Long-term toxicity to aquatic invertebrates
- Toxicity to aquatic algae and cyanobacteria
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- Additional toxicological data

Bioaccumulation: aquatic / sediment
Administrative data
Link to relevant study record(s)
- Endpoint:
- bioaccumulation in aquatic species: fish
- Type of information:
- (Q)SAR
- Adequacy of study:
- key study
- Study period:
- From AUG to SEP 2011
- Reliability:
- 2 (reliable with restrictions)
- Rationale for reliability incl. deficiencies:
- other: The applied model fulfils the OECD principles for QSAR-models. The submission substance is in the applicability domain of the model. Evaluation of sufficiently similar compounds with experimental data increases the confidence in the calculated BCF.
- Justification for type of information:
- This summary justification relates primarily to the dissolved fraction of organic pigments that (a) do not contain metals and do not represent salts, (b) are poorly soluble in water and n-octanol, (c) have a molecular weight > 200 g/mol and (d) have no surface modification that may change the properties of the substance (poorly soluble organic pigments (PSOPs) hereafter). The full justification, the sections referred to as well as the references are provided in the justification document attached in section 13.2.
1. The criteria of the nanomaterial definition have no scientific basis.
With respect to the upper limit of 100 nm, Commission Recommendation 2011/696/EU states that ‘there is no scientific evidence to support the appropriateness of this value’. With respect to the 50% threshold, a review of this Commission Recommendation states that ‘(s)ince the EC definition of nanomaterial should not be related to hazard or risk considerations, the selection of a threshold is essentially a policy choice and should be justified as such’ (Rauscher et al., 2015). Given the lack of a scientific basis of the criteria for the nanomaterial definition, it is inconceivable why a justification for using a physico-chemical property as a reason for waiving a bioaccumulation study is required in the case of nanoforms of PSOPs, while this is not required for bulk forms of PSOPs (see section 2.1 for more details).
2. The information provided is relevant for the dissolved fraction of PSOPs.
For an assessment of bioaccumulation in the pelagic phase, solubilities in water and n-octanol and calculated log KOW values as well as QSAR estimates based on these log KOW values are adequate with respect to the truly dissolved fraction of PSOPs. In fact, the solubility in n-octanol may represent overestimates due to the large pore size used for separating particulate and dissolved fractions in the ETAD (Ecological and Toxicological Association of Dyes and Organic Pigments Manufacturer) method commonly applied to organic pigments in combination with the lower tendency to aggregate/agglomerate in n-octanol compared to water. This potentially results in a comparatively high fraction of small particles in the ‘dissolved’ fraction . Consequently, the log KOW values calculated from the solubilities in water and n-octanol may represent overestimates and therefore tend to be conservative.
3. A low potential for bioaccumulation is indicated for most PSOPs.
Based on the critical body burden (CBB) approach, the solubility in n-octanol is lower than the CBB threshold indicating a low bioaccumulation potential for most PSOPs. Using the data in Table R.11-14 of ECHA (2017b), 88% of the 33 organic pigments listed show a low potential for bioaccumulation in fish. After exclusion of three salts, this fraction increases to 90% (27/30 organic pigments). In a more extensive selection of PSOPs that has a focus on nanoforms of organic pigments (see section 1.2 for more details) and is based on data from REACH registration dossiers evaluated by Stratmann et al. (2020), 70 of the 85 PSOPs (82%) show a low potential for bioaccumulation in fish according to the CBB approach. If PSOPs with a solubility in n-octanol ≥ 1 mg/L are excluded, this fraction increases to 97% (70/72 PSOPs), indicating that almost all PSOPs with a very low solubility in n-octanol have a low potential for bioaccumulation in fish. Due to the potential overestimate in determining the solubility in n-octanol at least in some of these data (see above), the CBB approach is not further elaborated here.
Nonetheless, the CBB approach covers the dissolved and the undissolved fraction and the data indicating a low potential for bioaccumulation for most PSOPs would therefore apply to nanoforms of PSOPs as well. While the CBB approach is not applied here for reasons discussed above, PSOPs largely consist of agglomerates/aggregates which further limits their bioavailability to fish and therefore their bioaccumulation potential in fish.
A low bioaccumulation potential is therefore suggested by the low solubility as well as the expected low dissolution rate in water, which is the reason why PSOPs are considered to be essentially not bioavailable. The assumption of very low or no bioavailability and therefore a low bioaccumulation potential is supported by the absence of mammalian toxicity following repeated exposure and the absence of chronic ecotoxicity demonstrated for the submission substance.
Overall, the information provided indicates a low potential for bioaccumulation of the submission substance. The information provided relates to the dissolved fraction of the substance, but additional considerations suggest that the conclusion may also be valid for the undissolved fraction. - Guideline:
- other: REACH guidance on QSARS R.6, May 2008
- Principles of method if other than guideline:
- 1) CAESAR QSAR model for bioconcentration factor (BCF) in fish:
Estimation methodology
Two models, Model A and Model B, have been used to build hybrid model, Model C. In the proposed approach, the outputs of the individual models (Model A and B) were used as inputs of the hybrid model. Model A was developed with a Radial Basis Function Neural Network (RBFNN) using an heuristic method to select the optimal descriptors; Model B was developed with a RBFNN using genetic algorithm for the descriptors selection. RBFNN (Wan and Harrington, 1999) was used with a Matlab function for building the models. In-house software made as a PC-Windows Excel macro was used to combine Models A and B within the Model C, using the equations defined in 4.2 of QMRF.
Input paramter: SMILES Code
For information on references and details on the model please see attached QMRF!
2) US EPA EPI SuiteTM module BCFBAF:
To support the reliable (reliability category 2) BCF from CAESAR, EPI Suite TM v4.1 (EPA, 2011) model BCFBAF (v3.01, September 2010) has been used for BCF calculation.
Input parameters: SMILES Code, log Kow (log Kow = 2.9)
Estimation methodology: Published and described in Meylan et al. (1999) for BCFWIN and updated for BCFBAF by better evaluated BCF-database as described in the program´s help file. The model is based on linear regression of log BCF against log KOW for the training set compounds. Aromatic azo compounds receive special treatment as log BCFs for compounds of log KOW between -0.02 and 9.55 were all (n=15) in the range of 0.48 and 1.82. Therefore, a value of 1.0 is assigned for all aromatic azo compounds (mean of the 15 recommended values of the training set).
3) Arnot & Gobas (2003) bioconcentration model:
To support the reliable (reliability category 2) BCF from CAESAR the Arnot & Gobas (2003) mechanistic model for assessment of the bioaccumulation potential of organic compounds in aquatic food webs was applied. The model is based on rate constants for uptake, elimination (over gills), fecal egestion (as function of dietary uptake) and growth dilution. Furthermore, the fraction of freely dissolved chemical in water is taken into account. For these constants and parameters simple relationships were developed based on default environmental parameters, assumptions on lipid content and organism weight and log Kow (sole substance specific input paramter). The model is easily transformed from bioaccumulation (including food) to bioconcentration (accumulation from the water phase only) by setting the food web biomagnification factor to zero. Calculation was performed via transformation in MS Excel spreadsheet.
Literature:
Wan and Harrington, 1999. J.Chem.Inf.Comput.Sci., 39, 1049-1056.
EPA, Environmental Protection Agency (2011)
Estimation Programs Interface Suite¿ for Microsoft® Windows, v 4.10.
Online: http://www.epa.gov/oppt/exposure/pubs/episuite.htm, accessed March 2011
U.S. Environmental Protection Agency, Washington, DC, USA
Meylan, W.M.; Howard, P.H.; Boethling, R.S.; Aronson, D.; Printup, H.; Gouchie, S. (1999)
Improved method for estimating bioconcentration/bioaccumulation factor from octanol/water partition coefficient
Environmental Toxicology and Chemistry, 18, 664-672
Arnot, J.A.; Gobas, F.A.P.C. (2003)
A generic QSAR for assessing the bioaccumulation potential of organic chemicals in aquatic food webs
QSAR & Combinatorial Science, 22, 337-345 - GLP compliance:
- no
- Details on estimation of bioconcentration:
- For calculation via CAESAR BCF-model v. 1.0.0.11 see attached QMRF and QPRF!
For supporting estimation via BCFBAF program v. 3.01 input parameters were SMILES code and experimental log Kow (log Kow = 2.9).
For detailed information on supporting BCF-calculation via Arnot & Gobas (2003) model see below section "Any other information on materials and methods including tables"! - Key result
- Type:
- BCF
- Value:
- 10 L/kg
- Basis:
- whole body w.w.
- Calculation basis:
- other: SMILES-Code
- Remarks on result:
- other: Key: CAESAR QSAR model for BCF in fish v. 1.0.0.11
- Remarks:
- Conc.in environment / dose:OTHER: QSAR
- Type:
- BCF
- Value:
- 10 L/kg
- Basis:
- whole body w.w.
- Calculation basis:
- other: SMILES-Code and log Kow
- Remarks on result:
- other: Supporting: BCFBAF model v. 3.01 as part of US EPA´s EPI SuiteTM v. 4.1 (EPA, 2011)
- Remarks:
- Conc.in environment / dose:OTHER: QSAR
- Type:
- BCF
- Value:
- 85.6 L/kg
- Basis:
- whole body w.w.
- Calculation basis:
- other: log Kow; 10.7% lipid content (upper trophic level organisms); default parameters
- Remarks on result:
- other: Supporting: Arnot & Gobas (2003) model on bioconcentration
- Remarks:
- Conc.in environment / dose:OTHER: QSAR
- Type:
- BCF
- Value:
- 40.6 L/kg
- Basis:
- whole body w.w.
- Calculation basis:
- other: log Kow, 5% lipid content (most experimental fish species); default parameters
- Remarks on result:
- other: Supporting: Arnot & Gobas (2003) model on bioconcentration
- Remarks:
- Conc.in environment / dose:OTHER: QSAR
- Details on results:
- For calculation via CAESAR BCF-model v. 1.0.0.11 see attached QPRF!
For supporting estimation via BCFBAF program v. 3.01:
Applicability domain
Currently there is no clearly defined model domain however molecular weight and log Kow-ranges of the training set are given to be compared to the target compound. The submission substance is well in-between these limits.
Results:
The output of BCFBAF was as follows:
- Log Kow used by BCF estimates: 2.90 (user entered)
- Equation Used to Make BCF estimate:
Log BCF = 1.00 (Aromatic Azo Specification)
- Correction(s): Value
Aromatic Azo compound 0.000
- Estimated Log BCF = 1.000 (BCF = 10 L/kg wet-wt)
For supporting estimation via Arnot & Gobas (2003) model:
Applicability domain
According to Arnot and Gobas (2003) application for a wide range of organic substances is possible. Caution is required when applied for charged or ionic substances as well as surface active chemicals. For substances showing considerable dissociation information regarding uptake and bioaccumulation via the respiratory surface of aquatic organism is currently lacking.
As the submission substance is neither charged or dissociated nor a surface active chemical, it is in the applicability domain of the model.
Results
See above section Results and discussions - Bioaccumulation factor. The results are based on a metabolic transformation rate of zero (i.e. no metabolism assumed). Calculations were performed for upper trophic level organisms with a rather high lipid content of 10.7% as well as for standard test fish species with an avarage lipid content of about 5%. Whereas the lipid content is an important parameter determining the size of the resulting BCF value temperature and organism weight are only of marginal influence on BCF. - Validity criteria fulfilled:
- yes
- Remarks:
- According to the OECD PRINCIPLES FOR THE VALIDATION, FOR REGULATORY PURPOSES, OF (QUANTITATIVE) STRUCTURE-ACTIVITY RELATIONSHIP MODELS, OECD 2004
- Conclusions:
- To estimate BCF of the submission substance by QSAR, besides the key study (reliability category 2) performed using the CAESAR BCF model v. v. 1.0.0.11 supporting calculations were performed using BCFBAF v. 3.01 and the Arnot & Gobas (2003) model on bioconcentration. The following results were achieved:
BCF according to CAESAR (key study): 10 L/kg whole body wet weight
BCF according to BCFBAF (supporting study): 10 L/kg whole body wet weight
BCF according to Arnot & Gobas model, upper trophic level (10.7% lipid content): 85.6 L/kg whole body wet weight
BCF according to Arnot & Gobas model, standard test fish species (5% lipid content): 40.6 L/kg whole body wet weight - Executive summary:
According to REACH Guidance R.7c section 7.10.3.1 on tests according to OECD 305 states that this test might not provide a reliable BCF for compounds with low aqueous solubility (i.e. below ~10 to 100 micro-g/L). The submission substance is of extremely low water solubility. As such, a test according to OECD 305 would most certainly not result in reliable BCF data. According to the same guideline section, dietary studies are only recommended for compounds with log Kow > 6 (2.9 for the submission substance). According to R.7.10.5. describing the hierarchy of preferred data sources to determine a potential for bioaccumulation, predicted data from validated QSAR models are on rank 3 (rank 1 and rank 2: reliable BCF data from fish and invertebrates, respectively) and preferred over in vitro data. Step 3B "evaluation of non-testing data" states that "QSARS based on Kow are generally recommended if Kow is a good predictor of bioconcentration". This is the case for the application of CAESAR BCF-model on the submission substance. In accord with the here presented data the guidance states that good correlation of experimental and calculated data for analogues "increases the confidence in the BCF prediction for the substance" (see attached QPRF). According to the guidance, calculated BCF-data based on log Kow are regarded as an upper estimate which may be corroborated or reduced by strong and weak indicators as specified in table R.7.10-6. If no such indicators exist, the use of a BCF predicted from Kow is recommended (see Fig. R.7.10-1 of guidance R.7C). As the model fulfils the OECD principles for QSAR-models with algorithm and used experimental data for model build and validation being freely available; as the submission substance is in the applicability domain of the model and evaluation of sufficiently similar compounds with experimental data increase the confidence in the calculated BCF for the submission substance according to REACH guidance R.7.C; the calculated BCF value is adequate for PBT/vPvB assessment (first tier) and risk assessment (first tier) for the submission substance.
Results according to calculation via CAESAR model (key, reliability category 2; BCF = 10 L/kg ww) are in excellent agreement with the supporting results from BCFBAF program ( BCF = 10 L/kg ww).
The Arnot and Gobas BCF-model is in general conservative as it assumes no metabolism (included in regression based models via training data set) and in particular as a relatively high lipid content of upper trophic organisms is assumed. The model is independent from a training data set and the data quality thereof, as it is based on several relatively simple mechanistical assumptions relating on few environmental and organism specific parameters and the KOW of the compound in question. It is therefore completely different from regression based models dependent on the empirical database used for the regression. Furthermore as outlined by Arnot and Gobas (2003), regression based models tend to "arrive at an 'average' BCF value, allowing for a relatively large number of occurrences where the actual BCF is greater than the BCF predicted values".
Taken into account the very different methodological approach and the conservative nature of the value, the deviation by 0.94 log units of the BCF-value derived according to the Arnot-Gobas model (10.7% lipid content upper trophic level) from the log BCF of 0.98 according to CAESAR is modest and may be regarded as an upper confidence limit of the value derived by CAESAR. This is substantiated by lowering the organism lipid content to 5% (most standard test fish species) resulting in a log BCF of 1.61 (i.e. a deviation from the CAESAR derived value of 0.63 log units).
Reference
Description of key information
To estimate BCF of the submission substance by QSAR, besides the key study (reliability category 2) performed using the CAESAR BCF model v. v. 1.0.0.11 supporting calculations were performed using BCFBAF v. 3.01 and the Arnot & Gobas (2003) model on bioconcentration. The following results were achieved:
BCF according to CAESAR (key study): 10 L/kg whole body wet weight
BCF according to BCFBAF (supporting study): 10 L/kg whole body wet weight
BCF according to Arnot & Gobas model, upper trophic level (10.7% lipid content): 85.6 L/kg whole body wet weight
BCF according to Arnot & Gobas model, standard test fish species (5% lipid content): 40.6 L/kg whole body wet weight
Key value for chemical safety assessment
Additional information
Information on Registered Substances comes from registration dossiers which have been assigned a registration number. The assignment of a registration number does however not guarantee that the information in the dossier is correct or that the dossier is compliant with Regulation (EC) No 1907/2006 (the REACH Regulation). This information has not been reviewed or verified by the Agency or any other authority. The content is subject to change without prior notice.
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