How to assess effects data sets for metals hazard identification and risk characterization.

Transcription

1 How to assess effects data sets for metals hazard identification and risk characterization. OECD Meeting, 7-8 September 2011 K Delbeke

2 Aims Metal characteristics, critical to assessing environmental effects for metals Metal-specific data-screening: data-quality, data relevance and data screening Data -aggregation for data-rich substance How to read-across between soluble compounds, sparingly soluble compounds and metals 2

3 Metal-specific characteristics Metals are natural elements and therefore naturally present in all environmental compartments. The metal chemical speciation changes during extraction, use, geological cycling. Some metals are essential. Fe, Mn, Zn, Cu, Co, Mo = essential for all living organisms Metal homeostasis: active internal concentrations remain constant at varying external concentrations - Organisms will vary the metal intake and elimination rates - Cellular & intracellular components will bind metals (eg binding to metallo-proteins) to be transported, stored or detoxified Metal bio-availability and toxicity is related to the metal species and physico-chemical properties of the environment 3 Some metal compounds have been intensively studied

4 Data rich and data poor... Issue: Metals are present in a variety of chemical forms (soluble compounds, sparingly soluble compounds, metals, alloys and integrated in complex inorganic minerals (eg concentrates)) and appear in various physical forms (powders or as massive forms) Number of ecotoxicity studies for Me - bearing substances Me, alloys,... : No data Sparingly soluble (MeO) No or few data Soluble - MeCl 2 4 Soluble - MeSO4

5 Read-across from soluble metal ions Is read-across possible? The release of metal-ions is driving the observed ecotoxicity. CLP guidance : The ecotoxicity of soluble inorganic metal compounds depends on the physico-chemical properties of the medium, irrespective of the original metal species released to the environment. 5 Reading across metal compounds can therefore be done by comparing the soluble metal ion concentration (μg Me/L) causing the ecotoxicity effect and translating this towards the compound under investigation.

6 Read-across from soluble metal ions EPA states in the AWQC guidance document: The toxic metal should be added in the form of an inorganic salt having relatively high solubility. Nitrate salts are generally acceptable; chloride and sulphate salts of many metals are also acceptable. For this reason, testing is usually done with a readily soluble salt where the toxicity of the anionic component is not likely to overshadow the cation. For the most part, testing is generally done with chloride or nitrate salts. 6

7 Data compilation = Read across between soluble Me-compounds Practical outline of the basic data-compilation Express L(E)C50 or NOECs as soluble µg Me/L All soluble ecotox data MeSO4 Me Cl... Express L(E)C50, NOEC as µg Me/L = large initial databases (eg >5000 Cu values)...data relevance, data reliability?...data aggregation for ERVs and PNEC 7

8 Data screening Apply agreed data screening criteria Me-species : Tests from soluble compounds Natural, essential: culture conditions without acclimation to high concentrations nor metal deficient conditions Quality and relevance: GLP and NON-GLP, Standard and nonstandard tests but: Test set-up sufficiently described (eg static, feeding...) OECD guideline quality criteria (eg <20% mortality) Relevant endpoints: survival, growth, hatching and/or reproduction Clear dose-responses from measured concentrations... Appropriate statistics Bio-availability : information on ph, Hardness and DOC of test media if bioavailbility is incorporated 8

9 Ecotoxicity Data treatment Data compilation Data quality and relevance screening Data normalization (see P. Van Sprang) Endpoint and species specific data aggregation Multi-species Data aggregation ERV derivation PNEC derivation 9

10 Endpoint and Species-specific data aggregation Grouping of selected data IF : Several values for same toxicological endpoint: geometric mean for that endpoint (e.g., chronic NOEC reproduction of D. magna). For one species, different life stages (e.g., adult & larvae) and/or toxicological endpoints (e.g., reproduction & growth) are available: select lowest value or geometric mean/endpoint and life stage Acclimation/adaptation is important =>group test results on the similarity of the background in the culture medium with the background of the environment under evaluation 10 Bioavailability is critical => Incorporate it (see P. Van Sprang)

11 PNEC derivation Freshwater Ecosystem protection Single-species laboratory tests Field Ecotoxicological data Information available L(E)C50 short-term tox tests NOEC for 1 long-term tox test Lowest NOEC for long-term toxicity tests of 2 trophic levels Lowest NOEC for long-term toxicity tests of 3 species of 3 trophic levels Assesment factor PNEC= depending on the uncertainty analysis 11 Statistical extrapolation method Mesocosm 1-5 Case by case EURAS

12 Criteria for statistical extrapolation method Taxonomic requirements For the freshwater SSD: ideally at least 8 taxonomic groups containing at least 10 NOECs for different species (London workshop, 2001). 12 Taxonomic groups Fish (usually tested species like salmons, bluegill, channel catfish, etc.) A second family in the phylum Chordata (fish, amphibian, etc.) A crustacean (e.g. cladoceran, copepod, ostracod, isopod, amphipod, crayfish etc.) An insect (e.g. mayfly, dragonfly, damselfly, stonefly, caddisfly, mosquito, midge, etc.) A family in a phylum other than Arthropoda or Chordata (e.g. Rotifera, Annelida, Mollusca, etc.) A family in any order of insect or any phylum not already represented Algae Higher plants

13 Comparison SSD criteria : EU versus US EPA Fish EU Requirement Second family in the phylum Chordata Crustacean Insect A family in a phylum other than Arthropoda or Chordata A family in any order of insect of any phylum not already represented Algae Higher plant US EPA Requirement the family Salmonidae in the Class Osteichthyes A second family of fish in the Class Osteichthyes (preferably a commercially or recreationally important warm-water species) A third family in the phylum Chordata Planktonic crustacean Insect A family in a phylum other than Arthropoda or Chordata A family in any order of insect, or any phylum not already represented. Benthic crustacean

14 14 Species sensitivity distribution for statistical extrapolation : SSD A Species Sensitivity distribution (SSD) = cumulative distribution function of the acute L(E) C50 or chronic NOEC/L(E)C50 test results

15 cumulative distribution Curve fitting and HC Curve fitting From Goodness-of-fit tests are formal statistical tests Eg : Andersen-Darling (A-D) test because it places more emphasis on tail values. 0 1,0 10,0 100,0 1000,0 NOEC Me-ion concentration (µg/l) HC5-50 = 5th percentile of a chronic toxicity distribution = concentration considered to be protective for most species in a community. 15

16 Influence of Curve-fitting on HC5-50 Me-ion Interval of species mean NOEC values Example - Non-normalised scenario HC5-50 with 5% and HC5-50 with 5% and 95% CI 95% CI using the best using the log normal curve fit fitting (µg/l) ( ) Pearson V (µg/l) 6.1 ( ) log-normal Conclusion -Several curves are adequate from goodness-of-fit tests - Curve-fitting influences the HC5-50 and Confidence Intervals 16 Pragmatic approach mostly used : - Log normal distribution curve - If fit unacceptable with the log-normal distribution, then apply a best-fitting distribution

17 PNEC derivation Me-ion HC5-50 PNEC Remaining Uncertainty (Uncertainty around HC5, mesocosm & field evidence...) Build-in conservativism Realism (compare to background, essentiality levels) 17

18 Hazard /risk read across soluble metal ions Effects: PNEC Me-ion PNEC compound = PNEC ion * Mwt compound /Mwt ion ERV Me-ion ERV compound = ERV ion * Mwt compound /Mwt ion RC : >1 : risk Classification: >1 : hazardous? Exposure : Me ion release from actual use µg Me-ion/L Classification cut-off values 18

19 Hazard /risk read-across metals & sparingly soluble metal compounds For poorly soluble metal compounds and metals the measured releases or release rates of the metals need to be accounted for. Me release massive material <<<metal release soluble compound (e.g., < 0.001%) PNEC Me-ion = µg Me-ion/L >1 : risk Acute and chronic ERV Me-ion >1 : hazard Me ion release from actual use = measured µg Me-ion/L Me ion release from Transformation/dissolution µg Me-ion/L 19

20 Conclusions Metal-specific characteristics are important for the hazard assessments of metals Hazard identification of metals, metal compounds and complex metal containing substances (alloys and concentrates) are related to the toxicity of the metal ions, the release of the metal ions and the fate of these metal ions. The toxicity of the metal ions and the release of these ions from the metal bearing substances are therefore used as a basis for the readacross. Such read-across allows for robust hazard assessments of metal bearing substances/mixtures that have no toxicity data (e.g., read-across from copper compounds to copper alloys). 20 Adequate effects assessments of metals include appropriate data selection, grouping of the data and a weight-of-evidence approach for the derivation of reference values for hazard identification and safe threshold values for risk characterization.