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EC number: 227-815-6 | CAS number: 5989-54-8
- Life Cycle description
- Uses advised against
- Endpoint summary
- Appearance / physical state / colour
- Melting point / freezing point
- Boiling point
- Density
- Particle size distribution (Granulometry)
- Vapour pressure
- Partition coefficient
- Water solubility
- Solubility in organic solvents / fat solubility
- Surface tension
- Flash point
- Auto flammability
- Flammability
- Explosiveness
- Oxidising properties
- Oxidation reduction potential
- Stability in organic solvents and identity of relevant degradation products
- Storage stability and reactivity towards container material
- Stability: thermal, sunlight, metals
- pH
- Dissociation constant
- Viscosity
- Additional physico-chemical information
- Additional physico-chemical properties of nanomaterials
- Nanomaterial agglomeration / aggregation
- Nanomaterial crystalline phase
- Nanomaterial crystallite and grain size
- Nanomaterial aspect ratio / shape
- Nanomaterial specific surface area
- Nanomaterial Zeta potential
- Nanomaterial surface chemistry
- Nanomaterial dustiness
- Nanomaterial porosity
- Nanomaterial pour density
- Nanomaterial photocatalytic activity
- Nanomaterial radical formation potential
- Nanomaterial catalytic activity
- Endpoint summary
- Stability
- Biodegradation
- Bioaccumulation
- Transport and distribution
- Environmental data
- Additional information on environmental fate and behaviour
- Ecotoxicological Summary
- Aquatic toxicity
- Endpoint summary
- Short-term toxicity to fish
- Long-term toxicity to fish
- Short-term toxicity to aquatic invertebrates
- Long-term toxicity to aquatic invertebrates
- Toxicity to aquatic algae and cyanobacteria
- Toxicity to aquatic plants other than algae
- Toxicity to microorganisms
- Endocrine disrupter testing in aquatic vertebrates – in vivo
- Toxicity to other aquatic organisms
- Sediment toxicity
- Terrestrial toxicity
- Biological effects monitoring
- Biotransformation and kinetics
- Additional ecotoxological information
- Toxicological Summary
- Toxicokinetics, metabolism and distribution
- Acute Toxicity
- Irritation / corrosion
- Sensitisation
- Repeated dose toxicity
- Genetic toxicity
- Carcinogenicity
- Toxicity to reproduction
- Specific investigations
- Exposure related observations in humans
- Toxic effects on livestock and pets
- Additional toxicological data
![](https://poisoncentres.echa.europa.eu/o/diss-blank-theme/images/factsheets/A-REACH/factsheet/print_environmental-fate-and-pathways.png)
Bioaccumulation: aquatic / sediment
Administrative data
Link to relevant study record(s)
- Endpoint:
- bioaccumulation in aquatic species, other
- Type of information:
- (Q)SAR
- Adequacy of study:
- key study
- Study period:
- 2011
- Reliability:
- 2 (reliable with restrictions)
- Rationale for reliability incl. deficiencies:
- other: Calculation with a validated QSAR (BCFBAF): l-limonene falls within the applicability domain of the (Q)SAR model, the prediction fits for the regulatory purpose, and the information is enough documented.
- Justification for type of information:
- 1. Relevance of the model
EPISUITE 4.0 (Syracuse Research Corporation, SRC) is reported as a usable valid model by ECHA (R6: QSARs and grouping of chemicals, May 2008).
2. Validation of the model
- Endpoint (OECD Principle 1)
Bioconcentration Factor (BCF)
- Algorithm (OECD Principle 2)
This method is based on the multiple-linear regression-derived equation which is used by the BCFBAF program to estimate the kM Biotransformation Half-Life with the following equation:
Log kM/Half-Life (in days) = 0.30734215*LogKow - 0.0025643319*MolWt - 1.53706847 + Σ(Fi*ni)
where LogKow is the log octanol-water partition coefficient, MolWt is the Molecular Weight, and Σ(Fi*ni) is the summation of the individual Fragment coefficient values (Fi) (from Appendix F, BCFBAF documentation) times the number of times the individual fragment occurs in the structure (ni). The -1.53706847 is the equation constant.
- Applicability domain (OECD Principle 3)
Training Dataset (421 Compounds)
- Molecular Weight:
o Minimum MW: 68.08 (Furan)
o Maximum MW: 959.17 (Decabromodiphenyl ether)
o Average MW: 259.75
- Log Kow:
o Minimum Log Kow: 0.31 (Benzenesulfonamide)
o Maximum Log Kow: 8.70 (Decabromodiphenyl ether)
The MW for the chemicals range from 136.24 to 208.35 g/mol. Thus, all chemicals fall within the applicability domain of the model. Chemicals of interest are simple molecules and all structural fragments appear to be present in the chemical domain of the QSAR model.
- Uncertainty of the prediction (OECD Principle 4)
The following gives statistical information for the BCF model training and validation datasets (includes ionic and non-ionic compounds).
For the BCF training dataset;
Number = 527
R² = 0.833
std deviation = 0.502
avg deviation = 0.382
Arnot-Gobas BCF and BAF statistics for the kM biotransformation half-life of the training dataset are;
Number = 421
R² = 0.821
std deviation = 0.494
avg deviation = 0.383
Currently, BCFBAF has been tested on two external validation datasets (not including training datasets). The BCF model has been tested on 158 chemicals and the kM model for the Arnot-Gobas BAF tested using 211 chemicals. These validation datasets include a diverse selection of chemical structures that test the predictive accuracy of any model. They contain many chemicals that are similar in structure to chemicals in the training set, but also chemicals that are different from and structurally more complex than chemicals in the training set.
For the BCF validation dataset;
Number = 158
R² = 0.82
std deviation = 0.59
avg deviation = 0.46
Arnot-Gobas BCF and BAF statistics for the kM biotransformation half-life of the validation dataset;
Number = 211
R² = 0.734
std deviation = 0.602
avg deviation = 0.446
Uncertainty in the model predictions must be considered for model applications. The median confidence (uncertainty) factor for the database used to develop the model is about 5.5. A confidence factor of 5.5 suggests that 95% of the expected values for a biotransformation rate constant fall between 5.5 x kM and kM / 5.5 assuming a log normal distribution. This degree of uncertainty corresponds to approximately 1.5 orders of magnitude of variance in the distribution. The log MAE from the test set corresponds to a confidence factor of about 7 (~1.7 orders of magnitude variance in the distribution) and could also provide screening level guidance for the expected range of values for application of HLN, kM, and N estimates. This level of uncertainty (1.5 – 1.7 orders of magnitude) is also generally consistent with present estimates for intra- and inter-species and route of exposure variability (Arnot et al., 2008a).
The model contains a large set of unique structural fragments so that it can be broadly applicable to diverse chemical structures; however, these fragments do not reflect the entire domain of possible structural fragments for organic chemicals. The model is not expected to provide accurate results for all chemicals in all fish species and it is difficult to define precisely the domain of applicability. The model may not successfully predict biotransformation rates for substances that have molecular components that significantly affect biotransformation processes and were not included in model development. The database used to develop the model did not include many substances that appreciably ionize at physiological pH or larger molecules (molar mass >600); therefore, the model may not accurately predict values for such substances. The data set used to develop the model did not include metals or organometals, pigments or dyes, or perfluorinated substances and the model should not be used for these substances.
3. Adequacy of result for classification & labelling and/or risk assessment
The described equations aim at calculating BCF values (partition coefficient between soil and water) that are adequate for risk assessment and classification&labelling purposes. - Qualifier:
- according to guideline
- Guideline:
- other: ECHA guidance on QSAR (R6)
- Principles of method if other than guideline:
- The Arnot-Gobas model estimates steady-state bioconcentration factor (BCF; L/kg) and bioaccumulation factor (BAF; L/kg) values for non-ionic organic chemicals in three general trophic levels of fish (i.e., lower, middle, and upper). The model is described in Arnot et al. (2008a,b and 2009). Additional documentation can be found in the help files of EPI Suite v4. Appendix K of BCFBAF model documentation contains detailed equations and model descriptions for BAF calculations
- GLP compliance:
- no
- Remarks:
- Calculations
- Radiolabelling:
- no
- Details on sampling:
- None
- Vehicle:
- not specified
- Details on preparation of test solutions, spiked fish food or sediment:
- None
- Test organisms (species):
- no data
- Details on test organisms:
- No data
- Route of exposure:
- aqueous
- Lipid content:
- ca. 5 %
- Remarks on result:
- other: Lower trophic is for fish with about 5% lipid content
- Type:
- BCF
- Value:
- 864.8 L/kg
- Basis:
- whole body w.w.
- Details on kinetic parameters:
- Bio Half-Life Normalized to 10 g fish at 15 deg C : 3.531 days
- Details on results:
- 1. Relevance of the model
EPISUITE 4.0 (Syracuse Research Corporation, SRC) is reported as a usable valid model by ECHA (R6: QSARs and grouping of chemicals, May 2008).
2. Validation of the model
- Endpoint (OECD Principle 1)
Bioconcentration Factor (BCF)
- Algorithm (OECD Principle 2)
This method is based on the multiple-linear regression-derived equation which is used by the BCFBAF program to estimate the kM Biotransformation Half-Life with the following equation:
Log kM/Half-Life (in days) = 0.30734215*LogKow - 0.0025643319*MolWt - 1.53706847 + Σ(Fi*ni)
where LogKow is the log octanol-water partition coefficient, MolWt is the Molecular Weight, and Σ(Fi*ni) is the summation of the individual Fragment coefficient values (Fi) (from Appendix F, BCFBAF documentation) times the number of times the individual fragment occurs in the structure (ni). The -1.53706847 is the equation constant.
- Applicability domain (OECD Principle 3)
Training Dataset (421 Compounds)
- Molecular Weight:
o Minimum MW: 68.08 (Furan)
o Maximum MW: 959.17 (Decabromodiphenyl ether)
o Average MW: 259.75
- Log Kow:
o Minimum Log Kow: 0.31 (Benzenesulfonamide)
o Maximum Log Kow: 8.70 (Decabromodiphenyl ether)
The MW for the chemicals range from 136.24 to 208.35 g/mol. Thus, all chemicals fall within the applicability domain of the model. Chemicals of interest are simple molecules and all structural fragments appear to be present in the chemical domain of the QSAR model.
- Uncertainty of the prediction (OECD Principle 4)
The following gives statistical information for the BCF model training and validation datasets (includes ionic and non-ionic compounds).
For the BCF training dataset;
Number = 527
R² = 0.833
std deviation = 0.502
avg deviation = 0.382
Arnot-Gobas BCF and BAF statistics for the kM biotransformation half-life of the training dataset are;
Number = 421
R² = 0.821
std deviation = 0.494
avg deviation = 0.383
Currently, BCFBAF has been tested on two external validation datasets (not including training datasets). The BCF model has been tested on 158 chemicals and the kM model for the Arnot-Gobas BAF tested using 211 chemicals. These validation datasets include a diverse selection of chemical structures that test the predictive accuracy of any model. They contain many chemicals that are similar in structure to chemicals in the training set, but also chemicals that are different from and structurally more complex than chemicals in the training set.
For the BCF validation dataset;
Number = 158
R² = 0.82
std deviation = 0.59
avg deviation = 0.46
Arnot-Gobas BCF and BAF statistics for the kM biotransformation half-life of the validation dataset;
Number = 211
R² = 0.734
std deviation = 0.602
avg deviation = 0.446
Uncertainty in the model predictions must be considered for model applications. The median confidence (uncertainty) factor for the database used to develop the model is about 5.5. A confidence factor of 5.5 suggests that 95% of the expected values for a biotransformation rate constant fall between 5.5 x kM and kM / 5.5 assuming a log normal distribution. This degree of uncertainty corresponds to approximately 1.5 orders of magnitude of variance in the distribution. The log MAE from the test set corresponds to a confidence factor of about 7 (~1.7 orders of magnitude variance in the distribution) and could also provide screening level guidance for the expected range of values for application of HLN, kM, and N estimates. This level of uncertainty (1.5 – 1.7 orders of magnitude) is also generally consistent with present estimates for intra- and inter-species and route of exposure variability (Arnot et al., 2008a).
The model contains a large set of unique structural fragments so that it can be broadly applicable to diverse chemical structures; however, these fragments do not reflect the entire domain of possible structural fragments for organic chemicals. The model is not expected to provide accurate results for all chemicals in all fish species and it is difficult to define precisely the domain of applicability. The model may not successfully predict biotransformation rates for substances that have molecular components that significantly affect biotransformation processes and were not included in model development. The database used to develop the model did not include many substances that appreciably ionize at physiological pH or larger molecules (molar mass >600); therefore, the model may not accurately predict values for such substances. The data set used to develop the model did not include metals or organometals, pigments or dyes, or perfluorinated substances and the model should not be used for these substances.
3. Adequacy of result for classification & labelling and/or risk assessment
The described equations aim at calculating BCF values (partition coefficient between soil and water) that are adequate for risk assessment and classification&labelling purposes. - Validity criteria fulfilled:
- not applicable
- Remarks:
- Calculations
- Conclusions:
- The calculated BCF is 864.8 L/kg wet/wet
- Executive summary:
The bioconcentration factor (BCF) of l-limonene in fish was estimated using the model of Arnot and Gobas (2003) which is reported as a usable valid model by ECHA (R6: QSAR and grouping of chemicals, May 2008). l-limonene feld in the applicability domain of this QSAR model and the other OECD principles are fulfilled. The calculation was ran using an experimental log Kow value of 4.38.
The calculated BCFof l-limonene was 864.8 L/kg wet/wet and this prediction is adequate for the purpose of risk assessment and classification and labelling.
- Endpoint:
- bioaccumulation in aquatic species, other
- Type of information:
- (Q)SAR
- Adequacy of study:
- key study
- Study period:
- 2011
- Reliability:
- 2 (reliable with restrictions)
- Rationale for reliability incl. deficiencies:
- other: Calculation with a validated QSAR (BCFWIN): l-limonene falls within the applicability domain of the (Q)SAR model, the prediction fits for the regulatory purpose, and the information is enough documented.
- Justification for type of information:
- 1. Relevance of the model
EPISUITE 4.0 (Syracuse Research Corporation, SRC) is reported as a usable valid model by ECHA (R6: QSARs and grouping of chemicals, May 2008).
2. Validation of the model
- Endpoint (OECD Principle 1)
Bioconcentration Factor (BCF) and Bioaccumulation Factor (BAF)
- Algorithm (OECD Principle 2)
This model classifies a compound as either ionic or non-ionic. Ionic compounds include carboxylic acids, sulfonic acids and salts of sulfonic acids, and charged nitrogen compounds (nitrogen with a +5 valence such as quaternary ammonium compounds). All other compounds are classified as non-ionic.
Training Dataset Included:
466 Non-Ionic Compounds
61 Ionic Compounds (carboxylic acids, sulfonic acids, quats)
Methodology for Non-Ionic was to separate compounds into three divisions by Log Kow value as follows:
Log Kow < 1.0
Log Kow 1.0 to 7.0
Log Kow > 7.0
Non-ionic compounds are predicted by the following relationships:
For Log Kow 1.0 to 7.0 the derived QSAR estimation equation is:
Log BCF = 0.6598 Log Kow - 0.333 + Σ correction factors
(n = 396, r2 = 0.792, Q2 = 0.78, std dev = 0.511, avg dev = 0.395)
For Log Kow > 7.0 the derived QSAR estimation equation is:
Log BCF = -0.49 Log Kow + 7.554 + Σ correction factors
(n = 35, r2 = 0.634, Q2 = 0.57, std dev = 0.538, avg dev = 0.396)
Certain super-hydrophobic chemicals (Log Kow >7.0) selected from the empirical database had reported BCF values with measured water concentrations that exceed water solubility limits. These BCF values were corrected based on estimates of water solubility limits (Arnot and Gobas, 2006).
For Log Kow < 1.0 the derived QSAR estimation equation is: All compounds with a log Kow of less than 1.0 are assigned an estimated log BCF of 0.50 (same as in BCFWIN).
Ionic compounds are predicted as follows:
log BCF = 0.50 (log Kow < 5.0)
log BCF = 0.75 (log Kow 5.0 to 6.0)
log BCF = 1.75 (log Kow 6.0 to 7.0)
log BCF = 1.00 (log Kow 7.0 to 9.0)
log BCF = 0.50 (log Kow > 9.0)
Metals (tin and mercury), long chain alkyls and aromatic azo compounds require special treatment.
- Applicability domain (OECD Principle 3)
The estimation domain for BCF model is based on the number of instances given for each correction factor in any of the 527 training set compounds (the minimum number of instances is of course zero, since not all compounds had every correction factor). The minimum and maximum values for molecular weight and log Kow are listed below.
Training Dataset Included:
466 Non-Ionic Compounds
61 Ionic Compounds (carboxylic acids, sulfonic acids, quats)
Training DataSet (527 Compounds)
- Molecular Weight
o Minimum MW: 68.08 (Furan)
o Maximum MW: 991.80 Ionic: (2,7-Naphthalenedisulfonic acid, 4-amino-5-hydroxy-3,6-bis[[4-[[2-(sulfooxy)ethyl]sulfonyl]phenyl]azo]-, tetrasodium salt)
o Maximum MW: 959.17 Non-Ionic: (Benzene, 1,1 -oxybis[2,3,4,5,6-pentabromo-)
o Average MW: 244.00
- Log Kow
o Minimum Log Kow: -6.50 Ionic: (2,7-Naphthalenedisulfonic acid, 4-amino-5-hydroxy-3,6- bis[[4-[[2-(sulfooxy)ethylsulfonyl]phenyl]azo]-, tetrasodium salt)
o Minimum Log Kow: -1.37 Non-Ionic: (1,3,5-Triazine-2,4,6-triamine)
o Maximum Log Kow: 11.26 (Benzenamine, ar-octyl-N-(octylphenyl)-)
- Uncertainty of the prediction (OECD Principle 4)
The following gives statistical information for the BCF model training and validation datasets (includes ionic and non-ionic compounds).
For the BCF training dataset;
Number = 527
R² = 0.833
std deviation = 0.502
avg deviation = 0.382
For Non-ionic compounds with Log Kow in the range 1.0 to 7.0
n= 396,
r² = 0.792,
Std. Dev.= 0.511,
Ave. Dev. = 0.395
3. Adequacy of result for classification & labelling and/or risk assessment
The BCFBAF program estimation of bioaccumulation coefficient in aquatic organisms of organic chemical is adequate for risk assessment and classification & labelling. - Qualifier:
- according to guideline
- Guideline:
- other: R6: ECHA guidance on QSARs
- Deviations:
- no
- Principles of method if other than guideline:
- The BCFBAF Program updates the BCF estimation methodology of the BCFWIN program by using an updated and better evaluated BCF database for selecting training and validation datasets (Arnot et al. 2003, 2006, 2008a, 2008b, 2009). The same regression methodology used to derive the original BCFWIN method was used to derive the BCFBAF model for estimating BCF. The BCFBAF program estimates BCF of organic chemicals using the chemical’s Log Kow. .
- GLP compliance:
- no
- Remarks:
- Calculations
- Radiolabelling:
- no
- Details on sampling:
- None
- Vehicle:
- not specified
- Details on preparation of test solutions, spiked fish food or sediment:
- None
- Test organisms (species):
- no data
- Details on test organisms:
- None
- Route of exposure:
- aqueous
- Test type:
- not specified
- Water / sediment media type:
- not specified
- Hardness:
- no data
- Test temperature:
- no data
- pH:
- no data
- Dissolved oxygen:
- no data
- TOC:
- no data
- Salinity:
- no data
- Details on test conditions:
- no data
- Lipid content:
- ca. 5 %
- Remarks on result:
- other: Dataset median about 5%
- Key result
- Type:
- BCF
- Value:
- 360.5 L/kg
- Basis:
- whole body w.w.
- Details on kinetic parameters:
- No kinetic parameter
- Metabolites:
- no data
- Results with reference substance (positive control):
- not applicable
- Details on results:
- 1. Relevance of the model
EPISUITE 4.0 (Syracuse Research Corporation, SRC) is reported as a usable valid model by ECHA (R6: QSARs and grouping of chemicals, May 2008).
2. Validation of the model
- Endpoint (OECD Principle 1)
Bioconcentration Factor (BCF) and Bioaccumulation Factor (BAF)
- Algorithm (OECD Principle 2)
This model classifies a compound as either ionic or non-ionic. Ionic compounds include carboxylic acids, sulfonic acids and salts of sulfonic acids, and charged nitrogen compounds (nitrogen with a +5 valence such as quaternary ammonium compounds). All other compounds are classified as non-ionic.
Training Dataset Included:
466 Non-Ionic Compounds
61 Ionic Compounds (carboxylic acids, sulfonic acids, quats)
Methodology for Non-Ionic was to separate compounds into three divisions by Log Kow value as follows:
Log Kow < 1.0
Log Kow 1.0 to 7.0
Log Kow > 7.0
Non-ionic compounds are predicted by the following relationships:
For Log Kow 1.0 to 7.0 the derived QSAR estimation equation is:
Log BCF = 0.6598 Log Kow - 0.333 + Σ correction factors
(n = 396, r2 = 0.792, Q2 = 0.78, std dev = 0.511, avg dev = 0.395)
For Log Kow > 7.0 the derived QSAR estimation equation is:
Log BCF = -0.49 Log Kow + 7.554 + Σ correction factors
(n = 35, r2 = 0.634, Q2 = 0.57, std dev = 0.538, avg dev = 0.396)
Certain super-hydrophobic chemicals (Log Kow >7.0) selected from the empirical database had reported BCF values with measured water concentrations that exceed water solubility limits. These BCF values were corrected based on estimates of water solubility limits (Arnot and Gobas, 2006).
For Log Kow < 1.0 the derived QSAR estimation equation is: All compounds with a log Kow of less than 1.0 are assigned an estimated log BCF of 0.50 (same as in BCFWIN).
Ionic compounds are predicted as follows:
log BCF = 0.50 (log Kow < 5.0)
log BCF = 0.75 (log Kow 5.0 to 6.0)
log BCF = 1.75 (log Kow 6.0 to 7.0)
log BCF = 1.00 (log Kow 7.0 to 9.0)
log BCF = 0.50 (log Kow > 9.0)
Metals (tin and mercury), long chain alkyls and aromatic azo compounds require special treatment.
- Applicability domain (OECD Principle 3)
The estimation domain for BCF model is based on the number of instances given for each correction factor in any of the 527 training set compounds (the minimum number of instances is of course zero, since not all compounds had every correction factor). The minimum and maximum values for molecular weight and log Kow are listed below.
Training Dataset Included:
466 Non-Ionic Compounds
61 Ionic Compounds (carboxylic acids, sulfonic acids, quats)
Training DataSet (527 Compounds)
- Molecular Weight
o Minimum MW: 68.08 (Furan)
o Maximum MW: 991.80 Ionic: (2,7-Naphthalenedisulfonic acid, 4-amino-5-hydroxy-3,6-bis[[4-[[2-(sulfooxy)ethyl]sulfonyl]phenyl]azo]-, tetrasodium salt)
o Maximum MW: 959.17 Non-Ionic: (Benzene, 1,1 -oxybis[2,3,4,5,6-pentabromo-)
o Average MW: 244.00
- Log Kow
o Minimum Log Kow: -6.50 Ionic: (2,7-Naphthalenedisulfonic acid, 4-amino-5-hydroxy-3,6- bis[[4-[[2-(sulfooxy)ethylsulfonyl]phenyl]azo]-, tetrasodium salt)
o Minimum Log Kow: -1.37 Non-Ionic: (1,3,5-Triazine-2,4,6-triamine)
o Maximum Log Kow: 11.26 (Benzenamine, ar-octyl-N-(octylphenyl)-)
- Uncertainty of the prediction (OECD Principle 4)
The following gives statistical information for the BCF model training and validation datasets (includes ionic and non-ionic compounds).
For the BCF training dataset;
Number = 527
R² = 0.833
std deviation = 0.502
avg deviation = 0.382
For Non-ionic compounds with Log Kow in the range 1.0 to 7.0
n= 396,
r² = 0.792,
Std. Dev.= 0.511,
Ave. Dev. = 0.395
3. Adequacy of result for classification & labelling and/or risk assessment
The BCFBAF program estimation of bioaccumulation coefficient in aquatic organisms of organic chemical is adequate for risk assessment and classification & labelling. - Validity criteria fulfilled:
- not applicable
- Remarks:
- Calculations
- Conclusions:
- The calculated BCF is 360.5 L/kg wet/wet
- Executive summary:
The bioconcentration factor (BCF) of l-limonene in fish was estimated using the model of Meylan & al. (1999) which is reported as a usable valid model by ECHA (R6: QSAR and grouping of chemicals, May 2008). l-limonene feld in the applicability domain of this QSAR model and the other OECD principles are fulfilled. The calculation was ran using an experimental log Kow value of 4.38.
The calculated BCFof l-limonene was 350.5 L/kg wet/wet and this prediction is adequate for the purpose of risk assessment and classification and labelling.
- Endpoint:
- bioaccumulation in aquatic species, other
- Type of information:
- (Q)SAR
- Adequacy of study:
- key study
- Study period:
- 2011
- Reliability:
- 2 (reliable with restrictions)
- Rationale for reliability incl. deficiencies:
- other: Calculation with a validated QSAR (OASIS): l-limonene falls within the applicability domain of the (Q)SAR model, the prediction fits for the regulatory purpose, and the information is enough documented.
- Justification for type of information:
- 1. Relevance of the model
EPISUITE 4.0 (Syracuse Research Corporation, SRC) is reported as a usable valid model by ECHA (R6: QSARs and grouping of chemicals, May 2008).
2. Validation of the model
- Endpoint (OECD Principle 1)
Bioconcentration Factor (BCF)
- Algorithm (OECD Principle 2)
Fi stands for the set of mitigating factors: metabolism, molecular size, ionization, Fw is the organism water content, FWS is water solubility factor, and a and n are model parameters.
a = 2.24E-07 +/- 1.428
n = 0.746 +/- 0.04997
Fw = 9.15 +/- 5.843
- Applicability domain (OECD Principle 3)
The following classes of chemicals are included in the training set: alkanes, alkenes, mono and diaromatic hydrocarbons, polycyclic aromatic hydrocarbons (PAH), polychlorinated dibenzofuranes (PCDF), polychlorinated dibenzodioxines (PCDDO), polychlorinated biphenyles (PCB), cycloalkanes and cycloalkenes, chloraromatic chemicals, perfluorinated acids (PFA) with 6 to 13 difluoromethylene functions in the chain, chlorinated biphenyl esters, aliphatic esters, chlororganic chemicals, aliphatic and aromatic N-containing compounds, polycyclic aromatic N-containing compounds, organotin compounds, sulfur-containing heterocyclic compounds. Functional groupings in these classes of chemicals “cover” the chemicals of interest.
The model applicability domain consists of three layers: general parametric requirements, structural domain characterized via atom-centered fragments (ACFs) confined within their first neighbors, mechanistic component of the domain. The domain of the general parametric requirements included the range of variation of hydrophobicity (log KOW) and molecular weight (MW) of chemicals in the training set. Respectively, chemicals with MW from 16 to 1131.3 and log KOW in the range of -3.89 and 16.07 are assigned to belong to the domain of the general requirements. The MW for the chemicals range from 136.24 to 208.35 g/mol.
- Uncertainty of the prediction (OECD Principle 4)
n=706 chemicals,
r2= 0.85,
S2 = 0.27,
RSS=175.5
3. Adequacy of result for classification & labelling and/or risk assessment
The described equations aim at calculating BCF values (bioaccumulation coefficient in aquatic organisms), they are therefore adequate for derivation of BCF (endpoint value) and completion of endpoint 5.4.1 of IUCLID dossier. - Qualifier:
- according to guideline
- Guideline:
- other: ECHA guidance on QSAR (R6)
- Principles of method if other than guideline:
- The Laboratory of Mathematical Chemistry of the Bourgas “Prof. As. Zlatarov” University team developed several models that are recommended for use by ECHA. One of these models is OASIS. The POP (persistent organic pollutant) profiler of OASIS is used to classify chemicals according to their persistence (P), bioaccumulation (B), and acute/chronic toxicity (T). The OASIS_Forecast module is used for predicting the toxicity endpoints (e.g., fish, daphnia, algae). This is the only available expert system that predicts the PBT properties of chemicals accounting for their stable degradants. The POPs framework advances hazard identification by integrating a metabolic simulator that generates metabolic maps for each parent chemical. Both the parent chemicals and plausible metabolites are systematically evaluated for their bioaccumulation and toxicity profile. The base-line BCF model provides predictions of the maximum bioaccumulation potential based on passive diffusion while considering a series of mitigating factors such as molecular size, ionization and fish liver metabolism (Dimitrov et al. 2005; 2010). The performance of this system for assessing PBT properties of chemicals has been used for categorization of chemicals on Canada’s Domestic Substances List, US EPA, Environment Canada, NITE, Japan, Danish EPA and major industries. Environment Canada customized the interface of OASIS for the Existing Chemicals Program. This shell program is called OASIS Canadian POPs. Version 1.1.11 of this program was used for predicting the BCF (“BCF_all mitigating factors” taking into consideration metabolism and maximum cross-sectional diameter (Dmax) which is a measure of bioavailability– discussed below)
- GLP compliance:
- no
- Remarks:
- Calculations
- Specific details on test material used for the study:
- Details on properties of test surrogate or analogue material (migrated information):
None - Radiolabelling:
- no
- Details on sampling:
- None
- Vehicle:
- not specified
- Details on preparation of test solutions, spiked fish food or sediment:
- None
- Test organisms (species):
- no data
- Route of exposure:
- aqueous
- Key result
- Type:
- BCF
- Value:
- 1 022 L/kg
- Basis:
- whole body w.w.
- Details on results:
- 1. Relevance of the model
EPISUITE 4.0 (Syracuse Research Corporation, SRC) is reported as a usable valid model by ECHA (R6: QSARs and grouping of chemicals, May 2008).
2. Validation of the model
- Endpoint (OECD Principle 1)
Bioconcentration Factor (BCF)
- Algorithm (OECD Principle 2)
Fi stands for the set of mitigating factors: metabolism, molecular size, ionization, Fw is the organism water content, FWS is water solubility factor, and a and n are model parameters.
a = 2.24E-07 +/- 1.428
n = 0.746 +/- 0.04997
Fw = 9.15 +/- 5.843
- Applicability domain (OECD Principle 3)
The following classes of chemicals are included in the training set: alkanes, alkenes, mono and diaromatic hydrocarbons, polycyclic aromatic hydrocarbons (PAH), polychlorinated dibenzofuranes (PCDF), polychlorinated dibenzodioxines (PCDDO), polychlorinated biphenyles (PCB), cycloalkanes and cycloalkenes, chloraromatic chemicals, perfluorinated acids (PFA) with 6 to 13 difluoromethylene functions in the chain, chlorinated biphenyl esters, aliphatic esters, chlororganic chemicals, aliphatic and aromatic N-containing compounds, polycyclic aromatic N-containing compounds, organotin compounds, sulfur-containing heterocyclic compounds. Functional groupings in these classes of chemicals “cover” the chemicals of interest.
The model applicability domain consists of three layers: general parametric requirements, structural domain characterized via atom-centered fragments (ACFs) confined within their first neighbors, mechanistic component of the domain. The domain of the general parametric requirements included the range of variation of hydrophobicity (log KOW) and molecular weight (MW) of chemicals in the training set. Respectively, chemicals with MW from 16 to 1131.3 and log KOW in the range of -3.89 and 16.07 are assigned to belong to the domain of the general requirements. The MW for the chemicals range from 136.24 to 208.35 g/mol.
- Uncertainty of the prediction (OECD Principle 4)
n=706 chemicals,
r2= 0.85,
S2 = 0.27,
RSS=175.5
3. Adequacy of result for classification & labelling and/or risk assessment
The described equations aim at calculating BCF values (bioaccumulation coefficient in aquatic organisms), they are therefore adequate for derivation of BCF (endpoint value) and completion of endpoint 5.4.1 of IUCLID dossier. - Validity criteria fulfilled:
- not applicable
- Remarks:
- Calculations
- Conclusions:
- The bioconcentration factor was estimated by calculation at 1022 L/kg wet/wet.
- Executive summary:
The bioconcentration factor (BCF) of l-limonene in fish was estimated using the EPISUITE 4.0 (Syracuse Research Corporation, SRC) which is reported as a usable valid model by ECHA (R6: QSAR and grouping of chemicals, May 2008). l-limonene feld in the applicability domain of this QSAR model and the other OECD principles are fulfilled. The calculation was ran using an experimental log Kow value of 4.38.
The calculated BCF of l-limonene was1022 L/kg wet/wet and this prediction is adequate for the purpose of risk assessment and classification and labelling.
Referenceopen allclose all
Results from EPIWIN
===========================================================
Whole Body Primary Biotransformation Rate Estimate for Fish:
===========================================================
------+-----+--------------------------------------------+---------+---------
TYPE | NUM | LOG BIOTRANSFORMATION FRAGMENT DESCRIPTION | COEFF | VALUE
------+-----+--------------------------------------------+---------+---------
Frag | 2 | Methyl [-CH3] | 0.2451 | 0.4902
Frag | 3 | -CH2- [cyclic] | 0.0963 | 0.2888
Frag | 1 | -CH - [cyclic] | 0.0126 | 0.0126
Frag | 3 | -C=CH [alkenyl hydrogen] | 0.0988 | 0.2965
Frag | 3 | -C=CH [alkenyl hydrogen] | 0.0000 | 0.0000
L Kow| * | Log Kow = 4.38 (user-entered ) | 0.3073 | 1.3462
MolWt| * | Molecular Weight Parameter | | -0.3494
Const| * | Equation Constant | | -1.5058
============+============================================+=========+=========
RESULT | LOG Bio Half-Life (days) | | 0.5478
RESULT | Bio Half-Life (days) | | 3.531
NOTE | Bio Half-Life Normalized to 10 g fish at 15 deg C |
============+============================================+=========+=========
Biotransformation Rate Constant:
kM (Rate Constant): 0.1963 /day (10 gram fish)
kM (Rate Constant): 0.1104 /day (100 gram fish)
kM (Rate Constant): 0.06209 /day (1 kg fish)
kM (Rate Constant): 0.03491 /day (10 kg fish)
Arnot-Gobas BCF & BAF Methods (including biotransformation rate estimates):
Estimated Log BCF (upper trophic) = 2.963 (BCF = 917.8 L/kg wet-wt)
Estimated Log BAF (upper trophic) = 2.969 (BAF = 931.1 L/kg wet-wt)
Estimated Log BCF (mid trophic) = 2.953 (BCF = 896.6 L/kg wet-wt)
Estimated Log BAF (mid trophic) = 2.976 (BAF = 945.2 L/kg wet-wt)
Estimated Log BCF (lower trophic) = 2.937 (BCF = 864.8 L/kg wet-wt)
Estimated Log BAF (lower trophic) = 2.988 (BAF = 973.7 L/kg wet-wt)
Results from EPIWIN
=============================
BCF (Bioconcentration Factor):
=============================
Log Kow (experimental): 4.38
Log Kow used by BCF estimates: 4.38 (user entered)
Equation Used to Make BCF estimate:
Log BCF = 0.6598 log Kow - 0.333 + Correction
Correction(s): Value
No Applicable Correction Factors
Estimated Log BCF = 2.557 (BCF = 360.5 L/kg wet-wt)
Description of key information
Key studies: Calculated values of BCF have been performed using three validated models and the geometric mean value of 683.1 L/kg w/w is used for risk assessment and classififcation&labelling purposes.
Key value for chemical safety assessment
- BCF (aquatic species):
- 683 L/kg ww
Additional information
Bioaccumulation factor has been calculated according to 3 commonly used QSAR models.
Chemical Name |
CAS RN |
SMILES |
Log Kow |
Meylan et al. (1999) (Regression- Based Method) BCF |
Arnot-Gobas model (2003) with Biotransformation (upper trophic range) BCF
|
OASIS Canadian POPs BCF |
L- LIMONENE |
5989-54-8 |
C(=CCC(C(=C)C)C1)(C1)C |
4.38 |
361 L/kg ww |
918 L/kg ww |
1022 L/kg ww |
An estimated BCF of 683 L/kg ww was calculated for l-limonene, using a log Kow of 4.53 and the geometric mean value of three validated QSARs results as recommended in ECHA guidance R7c.
This value is indicative of the potential to bioaccumulate for classification purposes. Indeed, according to a classification scheme, a BCF suggests a potential for bioconcentration in aquatic organisms if:
- BCF > 500 under the GHS CLP (Regulation EU No 286/2011)
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.
Reproduction or further distribution of this information may be subject to copyright protection. Use of the information without obtaining the permission from the owner(s) of the respective information might violate the rights of the owner.
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