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EC number: 231-943-8 | CAS number: 7779-88-6
- 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://chesar.echa.europa.eu/o/diss-blank-theme/images/factsheets/A-REACH/factsheet/print_ecotoxicological-information.png)
Endpoint summary
Administrative data
Description of key information
- at pH 6.0: 154 µg Zn/l (Daphnia magna)
- at pH 8.0: 41 µg Zn/l (Pseudokirchneriella subcapitata)
- at pH 6.0: 99 µg Zn/l (Pseudokirchneriella subcapitata)
- at pH 8.0: 11 µg Zn/l (Pseudokirchneriella subcapitata)
Ecotoxicity reference values (ERV)
The ERVs are based on the ecotoxicity of the Zn++ion. For deriving the ERVs for acute and chronic toxicity, all individual data were normalized towards two pH values (6 and 8), and, to further ensure conservatism, towards realistic worst-case conditions for DOC (2mg/L, the value also referred to in TD protocol (OECD 2001)). Water hardness was set at 40mg Ca/L which is the 50P of EU waters as described in the EU wide database FOREGs (Salminen 2005). It is noted that hardness is not relevant for zinc toxicity to the algae, which are often the most sensitive taxonomic group. By predicting the ecotoxicity for all individual values against exactly the same physicochemical conditions, all individual values could be considered for calculating the species geomean, according to ECHA guidance (ECHA 2017). This approach has the advantage that the sources of variability mentioned above are largely reduced, which enhances significantly the reliability and relevancy of the end result. The lowest geomean values for acute and chronic toxicity at pH 6 and 8 are selected as the ERV.
For data and full analysis, see document "Ecotoxicity Reference Value for Zinc for aquatic classification", IUCLID section 13.
ERVs for acute aquatic effect:
ERVs for chronic aquatic effect:
References
ECHA 2017. Guidance on the application of the CLP criteria, version 5, July 2017
OECD 2001. series on testing and assessment No 29: Guidance document on transformation/dissolution of metals and metal compounds in aqueous media. http://www.oecd.org/officialdocuments/publicdisplaydocumentpdf/?cote=env/jm/mono(2001)9&doclanguage=en
Salminen R. 2005. Geochemical Atlas of Europe. http://weppi.gtk.fi/publ/foregsatlas/
Additional information
- the data accepted for setting the acute aquatic reference value in the RA (ECB 2008, Annex 1.3.2a, table 1) were as such also accepted and used for the present analysis. Prescriptions from standard protocols were strictly followed, e.g. data from an acute Daphnia test exceeding 48 hrs were not used.
- Data that were rejected for use in the RA (ECB 2008, Annex 1.3.2a, table 2) were also not used for the present analysis. In this respect, data from studies that were accepted for use in the chronic database, but rejected for use in the acute toxicity database were reconsidered; this resulted in the acceptance of a few additional data.
- In accordance to the approach followed in the RA, acute data obtained in natural waters that contained e.g. significant amount of DOC, were not used. Exception to this rule were data obtained on the N.-American Great Lakes waters, which were used, in accordance to the RA.
- Fish data mentioned in the RA under “EHC 1996” were not used, since they were from a review, not from original study reports. These data are not influencing the outcome of the analysis, since they are all at the higher concentration level.
- More recent (obtained after 1996 to the present) short-term acute toxicity data on standard organisms were included in the database.
1. Aquatic toxicity: freshwater, short-term
Acute data - establishing the dataset
In accordance to the approach followed in the RAR, only acute data from standardised test protocols were considered in the analysis for setting the reference value for classification. This is possible because numerous data are available, and it ensures that the tests were performed under rather well defined and standard conditions.
Still, the quality and some aspects of relevancy should be checked in a critical way when using the extensive datasets from the open literature, available for zinc. It is e.g. important to know the conditions under which the organisms were tested and cultured, because these conditions may result in acclimatisation and deviating toxicity response. The information on these test conditions is often scarce in non-standardised test reports.
The short-term aquatic ecotoxicity data base for zinc was reviewed according to the following principles:
After checking and updating the data base, the data are normalized towards pH 6 and 8 and towards realistic worst-case conditions for DOC (2 mg/L) and a water hardness of 40 mg Ca/L. If 4 or more data points were available on a same species, the geomean of the normalized values was calculated and used for the analysis.
Acute data - results
The short-term acute aquatic toxicity database covers 59 species (5 algae, 29 invertebrates, 21 fish species, 3 amphibians and 1 aquatic plant). The full set of EC50 values are presented together with the pH and hardness of the test media in the document "Ecotoxicity Reference Value for Zinc for aquatic classification", IUCLID section 13.
2. Aquatic chronic toxicity:
Chronic data - establishing the dataset
A vast database on chronic ecotoxicity of zinc to freshwater and marine organisms is available. Based on that, a Species Sensitivity Distribution (SSD) approach has been developed for the assessment of zinc in the freshwater and marine compartment, using the reliable species-specific chronic toxicity effects.
The chronic freshwater and marine toxicity dataset for zinc was checked according to the general criteria for data quality:
- toxicological endpoints, which may affect the species at the population level, are taken into account. In general, these endpoints are survival, development, hatching, growth and reproduction,
- whether or not toxicity values are considered chronic is not determined exclusively by exposure time, but also by the generation time of the test species, e.g., for unicellular algae and other microorganisms (bacteria; protozoa), an exposure time of four days or less already covers one or more generations thus for these type of species, chronic NOEC values may be derived from relatively short experiments. For PNEC derivation a full life-cycle test, in which all relevant toxicological endpoints are studied, is normally preferred to a test covering not a full life cycle and/or not all relevant endpoints. However, NOEC values derived from tests with a relatively short exposure time may be used together with NOEC values derived from tests with a longer exposure time if the data indicate that a sensitive life stage was tested in the former tests,
- test media should be relevant: both artificial and natural marine waters are selected,
- for freshwater tests pH, hardness and temperature should be reported. In case pH or hardness is not reported, the composition of the test medium or type of test medium should be provided. DOC should be measured or robustly estimated; for marine toxicity tests pH, salinity (preferably, although it is expected that pH (±8) /salinity (±30 ppt) does not substantially change in marine test media) and test temperature should be reported,
-for bioavailability normalization puroposes in the freshwater compartment, the physico-chemistry of the test media should be within the boundaries of the bioavailability models (pH 5.7 – 8.4, and Ca 4.8 – 156 mg/L; see Table 10),
- Zn concentrations should be measured in test media (or as a minimum in stock solutions),
- only the results of tests in which the organisms were exposed to zinc alone are used, thus excluding tests with metal mixtures,
- statistically derived EC10 or NOEC values are retained; in cases where both the NOEC and EC10 values are available from the same experiment, preference is given to the EC10. If the EC10 was used as NOEC equivalent, the EC10 should not be more than 3.2-times lower than the lowest concentration used in the test, and the confidence intervals should not be too wide (and it is proposed that the confidence interval should not exceed a factor of ±10),
- unbounded NOEC values (i.e., no effect was found at the highest or lowest concentration tested) are not used.
For the purpose of PNEC setting the lowest toxicity value for the most sensitive endpoint observed on the species is selected. The lowest value is determined on the basis of the geometric mean if more than one value for the same endpoint is available. An overview of these species-specific toxicity data for the freshwater compartment is given in Table 1, while Table 2 provides an overview for the marine environment. It should be emphasized that for freshwater PNEC derivation purposes, all individual chronic toxicity value are first normalized to the specific water chemistry of European surface waters using bioavailability models.
Freshwater:
The 41 distinct chronic species ecotoxicity values from 17 taxonomic groups that were used for the SSD in the present analysis are summarised in the CSR, and in table below. The “species mean” NOEC values used for PNEC derivation (freshwater PNECadd, aquatic), range from 13.9 to 1310 µg/l.
The following table gives an overview of the geometric mean and most sensitive freshwater species-specific chronic K2-NOEC/EC10-values for zinc (values as reported in references; non-normalized for bioavailability)
Test organism | Taxonomic group | Endpoint | Geometric mean EC10/NOEC (µg/L) | Lowest EC10/NOEC (µg/L) |
Acipenser transmontanus | Fish (Acipenseridae) | Growth (length) | 195 | 104.2 |
Growth (weight) | 104.2 | |||
Mortality | 136.6 | |||
Alathyria profuga | Mollusc (Bivalvia) | Mortality | 29.6 | 29.6 |
Anuraeopsis fissa | Rotifer | Gross reproductive rate | 35.1 | 30.8 |
Life span | 31.8 | |||
Net reproductive rate | 30.8 | |||
Rate of population increase | 43.7 | |||
Brachionus calyciflorus | Rotifer | Growth Rate | 215.1 | 215.1 |
Brachionus rubens | Rotifer | Gross reproductive rate | 98.7 | 39.0 |
Life span | 68.9 | |||
Net reproductive rate | 39.0 | |||
Rate of population increase | 64.0 |
| ||
Bryocamptus zschokkei | Crustacean (Copepoda) | Mortality | 300.0 | 300.0 |
Reproduction | 300.0 |
| ||
Ceriodaphnia dubia | Crustacean (Cladocera) | Mortality | 87.1 | 51.8 |
Reproduction | 51.8 | |||
Chlorella sp. (isolate 12) | Alga (Chlorophyta) | Growth rate | 136.0 | 136.0 |
Cirrhinus mrigala | Fish (Cyprinidae) | Growth (weight) | 100.0 | 100.0 |
Cottus bairdi | Fish (Cottidae) | Biomass | 37.0 | 27.0 |
Growth (length) | 27.0 | |||
Growth (weight) | 37.0 | |||
Mortality | 69.6 | |||
Cucumerunio novaehollandiae | Mollusc (Bivalvia) | Mortality | 13.9 | 13.9 |
Cyprinus carpio | Fish (Cyprinidae) | Mortality | 1183.7 | 1183.7 |
Danio rerio | Fish (Cyprinidae) | Hatching | 666.1 | 666.1 |
Daphnia longispina | Crustacean (Cladocera) | Mortality | 1587.0 | 181.0 |
Reproduction (number of juveniles) | 181.8 | |||
Reproduction (brood size) | 181.0 | |||
Daphnia lumholtzi | Crustacean (Cladocera) | Mortality | 24.9 | 24.9 |
Reproduction | 42.8 |
| ||
Daphnia magna | Crustacean (Cladocera) | Intrinsic growth rate | 263.0 | 107.5 |
Mortality | 125.0 | |||
Reproduction | 107.5 | |||
Dreissenia polymorpha | Mollusc (Bivalvia) | Mortality | 382 | 382 |
Echyridella menziesii | Mollusc (Bivalvia) | Mortality | 148.2 | 148.2 |
Ephoron virgo | Insect Ephemeroptera | Mortality | 718.0 | 718.0 |
Euchlanis dilatata | Rotifer | Mortality | 31.0 | 31.0 |
Reproduction | 92.4 |
| ||
Gobiocypris rarus | Fish (Cyprinidae) | Mortality | 78.0 | 78.0 |
Hyalella azteca | Crustacean (Amphipoda) | Reproduction, | 42.0 | 42.0 |
Mortality | 42.0 |
| ||
Hyridella australis | Mollusc (Bivalvia) | Mortality | 15.4 | 15.4 |
Hyridella depressa | Mollusc (Bivalvia) | Mortality | 22.8 | 22.8 |
Hyridella drapeta | Mollusc (Bivalvia) | Mortality | 23.2 | 23.2 |
Jordanella floridae | Fish (Cyprinodontidae) | Growth | 26.0 | 26.0 |
Lampsilis siliquoidea | Mollusc (Bivalvia) | Growth (length) | 32.7 | 32.7 |
Mortality | 126.0 | |||
Lemna gibba | Plant (Araceae) | Frond numbers | 2120.0 | 1310.0 |
Growth (weight) | 1310.0 |
| ||
Lithobates chiricahuensis | Amphibia | Development | 62.0 | 62.0 |
Growth (length) | 62.0 | |||
Growth (weight) | 62.0 |
| ||
Lymnaea stagnalis | Mollusc (Gastropoda) | Development | 530.0 | 223.0 |
Growth Rate (length) | 506.8 | |||
Growth rate (weight) | 223.0 | |||
Microcystis aeruginosa | Cyanobacteria | Growth (cell density) | 1000.0 | 1000.0 |
Navicula pelliculosa | Alga ((Diatomaea) | Growth rate | 280.0 | 280.0 |
Oncorhynchus mykiss | Fish (Salmonidae) | Biomass | 150.0 | 150.0 |
Growth (length) | 300.0 | |||
Growth (weight) | 199.0 | |||
Mortality | 152.9 | |||
Phoxinus phoxinus | Fish (Cyprinidae) | Mortality, Growth | 50.0 | 50.0 |
Pimephales promelas | Fish (Cyprinidae) | Reproduction | 78.0 | 78.0 |
Planothidium lanceolatum | Cyanobacteria | Growth (cell density) | 234.0 | 234.0 |
Potamopyrgus jenkinsi | Mollusc (Gastropoda) | Growth | 72.0 | 72.0 |
Pseudokirchneriella subcapitata | Alga (Chlorophyta) | Growth Rate | 24.1 | 24.1 |
Salmo trutta | Fish (Salmonidae) | Hatching | 119.4 | 119.4 |
Salvelinus fontinalis | Fish (Salmonidae) | Hatching | 534.0 | 534.0 |
Velesunio ambiguus | Mollusc (Bivalvia) | Mortality | 28.9 | 28.9 |
The data in the above table (the geometric mean for the most sensitive endpoint) have been used for the construction of a Species Sensitivity Distribution (SSD) from which the median 5th percentile was derived. This value represents the HC5,50% with 5%-95%-confidence interval. The outcome of this analysis allows the derivation of the HC5,50% with 5%-95% confidence interval, and this value should be used for PNEC-derivation (i.e., PNECaquatic= HC5,50%/Assessment Factor). For the purpose of PNEC setting, the lowest value normalised for bioavailability for the most sensitive endpoint is selected for the freshwater compartment. The lowest value is determined on the basis of the geometric mean if more than one value for the same endpoint is available.
Since chronic toxicity of Zn depends on the physico-chemistry of the test medium, all chronic toxicity data (i.e., NOEC/EC10 values) from the database were normalized to the various combinations of specific physico-chemical conditions occurring in European surface waters, as reflected by the conditions monitored in the individual monitoring sites from the FOREGs database (http://weppi.gtk.fi/publ/foregsatlas/index.php). All freshwater chronic toxicity data were normalized to each of the different environmentally relevant water chemistries documented in this extensive dataset (see BOX 1). After this bioavailability normalization, the geometric mean value of the most sensitive endpoint per species is used as input data for the calculation of the HC5,50% related to each of the different physico-chemistries occurring in the FOREGs dataset. The distribution of all these HC5,50% values is finally used for setting the PNEC value for Zn. The different steps in this process are described in more detail in the background document.
For each sampling site from the FOREGs database, a separate normalized SSD is constructed through fitting of the log-normal transformed normalised toxicity data to 7 different distributions, ie. cauchy, exponential, gamma, log-normal, logistic, normal, weibull and gumbel. Best fitting statistic such as Anderson-Darling was used to select the best fitting distribution for each of the 546 datapoints from the FOREGs database, after which HC5,50% values were derived for each sampling site from the FOREGs database. In the last step, a distribution of all 546 bioavailabilty normalized HC5,50%’s were plotted and the 10th percentile of that distribution is proposed as final HC5,50% value (Figure 2), resulting in a value of 14.4 µg Zn/L (as normalised dissolved value). The 10th percentile is proposed to represent reasonable worst-case conditions of bioavailability in PNEC derivation in analogy with the use of the 90th percentile of reasonable worst-case setting in the PEC derivation (ECHA 2008).
Based on the weight of evidence from the different considerations provided by the extensive uncertainty analysis, combined with the inherent conservatism resulting from the setting of the HC5,50% value with reference to realistic worst case conditions of bioavailability, an Assessment Factor of 1 on the HC5,50% is applied for the derivation of the PNEC, resulting in a PNECfreshwater of 14.4 µg Zn/L.
For a detailed discussion on the uncertainty related to the SSD and the HC5, and the derivation of the PNEC, seethe background document on environmental risk assessment of zinc in the aquatic compartment, attached to section 13 of IUCLID.
Marine:
The 32 distinct chronic species ecotoxicity values from 18 taxonomic groups that were used for the SSD in the present analysis are summarised in the CSR, and in table below. The “species mean” NOEC values used for PNEC derivation (freshwater PNECadd, aquatic), range from 4.2 to 2074 µg/l.
The following table gives an overview of the geometric mean and most sensitive marine species-specific chronic NOEC/EC10-values for zinc (all values Klimish 2 score)
Test organism | Taxonomic group | Endpoint | Geometric mean EC10//NOEC (µg/L) | Lowest EC10//NOEC (µg/L) |
Allorchestes compressa | Crustacean (Amphipoda) | Mortality | 63.0 | 63.0 |
Apostichopus japonicus | Echinoderm (Holothuroidea) | Mortality | 444.0 | 18.8 |
Growth rate (weight) | 18.8 |
| ||
Capitella capitella | Annelid (Polychaeta) | Reproduction | 108 | 108.0 |
Ceramium tenuicorne | Macrophyte (Rhodophyta) | Growth (length) | 11.9 | 11.9 |
Conticriba weissflogii | Alga (Thalassiosirales) | Growth rate | 430.0 | 430.0 |
Cryothecomonas armigera | Alga (Cryomonadida) | Growth rate | 366.0 | 366.0 |
Crassostrea gigas | Mollusc (Bivalvia) | Mortality | 254.0 | 192.9 |
Growth (length) | 192.9 |
| ||
Etroplus suratensis | Fish (Cichlidae) | Mortality | 1480.0 | 1480.0 |
Evechinus chloroticus | Echinoderm (Echinacea) | Growth (length) | 10.0 | 9.7 |
Development | 9.7 |
| ||
Gaimardia trapesina | Mollusc (Bivalvia) | Mortality | 2074.0 | 2074.0 |
Galeolaria caespitosa | Annelid (Polychaeta) | Fertilization | 134.8 | 134.8 |
Haliotis diversicolor supertexta | Mollusc (Gastropoda) | Growth rate (length) | 64.0 | 64.0 |
Haliotis iris | Mollusc (Gastropoda) | Development | 4.2 | 4.2 |
Haliotis rufescens | Mollusc (Gastropoda) | Development | 15.3 | 15.3 |
Harpacticus sp. | Crustacean (Copepoda) | Mortality | 122.6 | 122.6 |
Holmesimysis costata | Crustacean (Mysida) | Mortality | 7.1 | 7.1 |
Hyale longicornis | Crustacean (Amphipoda) | Mortality | 970.0 | 970.0 |
Hydroides elegans | Annelid (Polychaeta) | Development (larvae settlement) | 23.2 | 23.2 |
Development (from eggs to trochophore larvae) | 37.0 |
| ||
Macrocystis pyrifera | Macroalga (Lessoniaceae) | Growth (length of germination tubes) | 190.2 | 190.2 |
Melita awa | Crustacean (Amphipoda) | Mortality | 480.0 | 480.0 |
Melita matilda | Crustacean (Amphipoda) | Mortality | 230.0 | 230.0 |
Mysidopsis juniae | Crustacean (Mysida) | Growth (length) | 75.0 | 64.5 |
Mortality | 64.5 |
| ||
Mytilus galloprovincialis | Mollusc (Bivalvia) | Development | 54.0 | 54.0 |
Mytilus trossolus | Mollusc (Bivalvia) | Development | 48.0 | 48.0 |
Neanthes arenaceaodentata | Annelid (Polychaeta) | Reproduction | 108.5 | 108.5 |
Nitzschia closterium | Alga (Bacillariales) | Growth | 85.5 | 85.5 |
Penaeus monodon | Crustacean (Decapoda) | Mortality | 8.6 | 8.6 |
Phaeocystis antarctica | Alga (Phaeocystales) | Growth rate | 450.0 | 450.0 |
Pleurochrysis roscoffensis | Alga (Syracosphaerales) | Growth rate | 100.0 | 100.0 |
Sepia officinalis | Mollusc (Cephalopoda) | Growth rate (length) | 53.0 | 53.0 |
Mortality | 185.0 |
| ||
Strongylocentrotus purpuratus | Echinoderm (Echinacea) | Development | 29.0 | 29.0 |
Thalassiosira pseudonana | Alga (Thalassiosirales) | Growth (cell density) | 350.0 | 350.0 |
Tigriopus angulatus | Crustacean (Copepoda) | Mortality | 1190.8 | 1190.8 |
The data in the above table(the geometric mean for the most sensitive endpoint) have been used for the construction of a Species Sensitivity Distribution (SSD) from which the median 5th percentile was derived. This value represents the HC5,50% with 5%-95%-confidence interval. The outcome of this analysis allows the derivation of the HC5,50% with 5%-95% confidence interval, and this value should be used for PNEC-derivation (i.e., PNECaquatic= HC5,50%/Assessment Factor). For the purpose of PNEC setting the lowest toxicity value for the most sensitive endpoint is selected for the marine compartment. The lowest value is determined on the basis of the geometric mean if more than one value for the same endpoint is available.
The SSD was constructed through fitting of log-normal transformed toxicity data to 7 different distributions using the bootstrapping method, ie. exponential, gamma, log-normal, logistic, normal, weibull, and gumbel. The outcome of this analysis allows the derivation of the HC5,50% with 5%-95% confidence interval, and this value should be used for PNEC-derivation (i.e., PNECaquatic= HC5,50%/ Assessment Factor). Using this analysis, the Weibull distribution was defined as the optimal distribution considering the Anderson-Darling goodness-of-fit statistics, which emphasizes the tails of the distributions. The HC5,50% (± 95%CL) that was associated with this distribution was 7.2 µg Zn/L (95%CL: 4.4– 12.5 µg Zn/L; see Table 16). Application of an assessment factor between 1 and 5 on this HC5,50% results in the final PNEC for zinc in the aquatic environment. The value of this assessment factor depends on the uncertainty analysis. Based on the weight of evidence from all the different considerations provided by this extensive analysis an Assessment Factor of 1 on the HC5,50% is applied for the derivation of the marine water PNEC, resulting in a PNECmarine of 7.2 µg Zn/L.
For a detailed discussion on the uncertainty related to the SSD and the HC5, and the derivation of the PNEC, see the background document on environmental risk assessment of zinc in the aquatic compartment, attached to section 13 of IUCLID.
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