Prioritisation of substances under the WFD: Results of the test run

1. Prioritisation of substances under the WFD: Results of the test run WG(E) 3, Brussels, 03/02/2008

2. General scheme of the prioritisation process: Choosing relevant parameters for prioritisation Defining the list of candidate substances Prioritisation algorithms Data processing: - data gathering - quality check - data aggregation - treatment of missing data

3. Defining a preliminary list of candidate substances • Defining a candidate list but also a manageable list. Decision rules adopted: • - Tier 1/Tier 2 substances monitored (i.e. according to the data collection results) by at least 25% of the MS (i.e. 2 out of 9 countries for the test run) • - Tier 3 substances of interested (i.e. according to the May 2007 questionnaire results) by at least 25% of the MS (i.e. 5 out of 21 for the the test run) • 201 substances or families of substances (377 individual substances, including the 41 WFD substances)

4. Data collection limited to easily accessible data sources?A first step!

5. 2nd step: use also of modelling data • Exposure predictions (predictions from releases, production data, sales data, multimedia models, etc.) • Effects predictions (prediction from (Q)SARs, read-accross)

6. PNEC for secondary Endocrine Disruption PEC in sediment PNEC for aquatic PNEC for benthic Maximum allowed PEC in water (monitoring) PEC in biota (monitoring) Drinking water criteria poisoning of predators Representativeness Water Solubility Biodegradability PEC (modelling) (monitoring) residues in food Vapour pressure CAS number organisms organisms Hydrolysis Production Releases log Kow Choose relevant parameters • Monitoring data in water • Monitoring data in sediment • Monitoring data in biota • Ecotoxicity for aquatic organisms • Ecotoxicity for benthic organisms • Oral toxicity for mammals/birds • Toxicity for humans • Kow, vapour pressure, persistence, bioaccumulation • Additional data for modelling (production, sales, releases, etc.)

7. Relevant parameters (1): for water 337 substances for which monitoring data have been provided for water (mainly whole water) PNECwater were established according to various sources: EU RAR, COMMPS, tentative PNECs from INERIS (based on AQUIRE, HSDB, other RAR, etc.). Cross-check with the ETOX database. Drinking water standards (98/83/EC and WHO quality guidelines) were also retrieved PNECwater are missing for 11 substances because of insufficient data: Metabolites: Deisopropyldeethylatrazine (DEIA), Hydroxyatrazin, Hydroxysimazine Some EP substances: Iopamidol, DTPA, 4,4'-biphenol Other: Dipropyl phtalate, Chloronaphtalene-2, 1,2-Dibromoethane (EDB), 3-Chlorotoluene, Tetrabutyltin (TTBT) Also specific problems: - how to establish PNEC for individual congeners of e.g. PCBs, PAHs, dioxins/furans - read-across allowed? -PNECwater for substances with varying toxicity (metals, but also organics e.g. chlorophenols)

8. PNECwater for PAHs PNECwater was estimated according to this equation for the following PAHs: 2-methylnaphtalene Perylen Benzo[e]pyrene 2-methylphenanthrene 3,6-dimethylphenanthrene Benzo[a]fluorene Methylnaphthalene 1-methylpyrene Dimethylnaphthalene Methylphenanthrener Methyl-2-Fluoranthene dibenzo(a,c)anthracene in sea water 1-Methylnaphtalin Benzofluoranthene

9. PNECwater for individual PCB congeners PNEC for sum of PCBs of 0.9 ng/L (FHI, draft factsheet) How to assess risk due to total PCBs when monitoring data are provided for only a few congeners?  average percentage of each congener in Arochlor 1248, 1254, 1260 (source US-EPA) was used to extrapolate the concentration of total PCBs from concentration of a these congeners. BUT not representative of the percentages in the environment: faster degradation of low chlorinated PCBs  relative enrichment of highly chlorinated PCB in the environment Extrapolation from low chlorinated congeners only, may underestimate the risk due to total PCBs. Extrapolation from highly chlorinated congeners only, may overestimate the risk due to total PCBs.

10. PNECwater for individual dioxin/furan congeners PNEC for sum of dioxin/furan of 0.38 pg eqTCDD/L (FHI, draft factsheet) How to assess risk due to total dioxins/furans when monitoring data are provided for only a few congeners?  average percentages of each congener in water were established according to a literature review* Representative review? monitoring results as µgcongener/L were converted as µg eq TCDD/L according to Toxic Equivalent Factors (TEF) from WHO, 1998 BUT is AhR binding the only mode of action ? What TEF? (also WHO, 2005, but not applied by the current EU legislation yet) * K. Srogi (2008) Levels and congener distributions of PCDDs, PCDFs and dioxin-like PCBs in environmental and human samples: a review. Environ Chem Lett 6:1–28

11. Relevant parameters (2): for sediment 296 substances for which monitoring data have been provided for sediment (2mm, 20µm, 63µm) PNECsed were found for 96 substances only (from EU RAR, COMMPS, etc). Most of them were calculated with the EqP approach  tentative PNECsed were recalculated from all the available PNECwater and using Koc estimated with KocWin. Not applicable for metals and polar substances  the option of using sediment quality benchmarks from other countries were investigated, but not retained

12. Quality criteria for sediment. e.g. for some PAHs or VOCs

13. Quality criteria for sediment: e.g. for some pesticides

14. Quality criteria for sediment: e.g. for some metals

15. Relevant parameters (3): for biota & secondary poisoning 101 substances for which monitoring data have been provided for biota (fish, molluscs) But concentrations in biota can also be estimated from concentrations in water and from BCF PNECoral were established according to various sources: legislation, EU RAR, tentative PNECs from INERIS (based on HSDB, EDPSD, other RAR, etc.) Chronic toxicity, carcinogenic, reproductive, endocrine effects were taken into account in order to cover both wildlife and human health Qualitative information from C&L (Annex I or alternatively Danish EPA QSAR estimates) were retrieved (needed to run the COMMPS algorithm). Additional/complementary information on carcinogenicity/mutagenicity can also easily be found in the ISSCAN database PNECoral are missing for 11 substances because of insufficient information: Benzo[a]fluorene, 1-methylpyrene, Dimethylnaphthalene, Methylphenanthrene, Benzofluoranthene, Benzo(a)anthracene, Perylen, Benzo[e]pyrene, 3,6-dimethylphenanthrene Dibutyltin Molybdenum Also specific problems: - how to establish PNEC for individual congeners of e.g. PCBs, PAHs, dioxins/furans - read-across allowed? - PNECoral for metals (bioavailable fraction? essential fraction?)

16. PNECoral for individual PCB congeners PNECoral for sum of PCBs of 4.8 µg/kg fish ww is proposed in the FHI draft factsheet Several options were investigated: Assuming PNECoral for sum of PCBs of 4.8 µg/kg fish ww, and using average percentage of each congener in typical Arochlor mixtures (see. method. for PNECwater)  Most conservative approach and can be applied for all congeners Approach used for the test run Using toxicity results compiled by EFSA for some congeners  does not take into account the sum of effects of each congener Using MRL in food for dioxin-like PCBs (expressed as TEF)*, and relying on the hypothetical percentages of each congener in fish (from literature)†  Applicable only for dioxin-like congeners † COMMISSION REGULATION (EC) No 1881/2006 of 19 December 2006 setting maximum levels for certain contaminants in foodstuffs * K. Srogi (2008) Levels and congener distributions of PCDDs, PCDFs and dioxin-like PCBs in environmental and human samples: a review. Environ Chem Lett 6:1–28

17. Data processing Plausibility check (elimination of outliers):  analyses with associated DL beyond 90th percentile of all the DL for the substance were discarded Aggregation: PEC1 and PEC2 for each substance were calculated as the 90th percentile of the station means  PEC1: calculated only from analyses >DLidentification of demonstrated risk  PEC2: all analyses, replacing less-than values by DL/2identification of widespread risk  PEC3: based on max measurementidentification of local risk

18. Priority setting Metals COMMPS Risk ratios Algorithm tested: Risk ratios for water, sediment, biota. COMMPS For metals: Tentative risk ratios. Comparison between PEC and background concentrations

19. TIER 3 substances Every substance will be ranked EP substances TIER 1 substances TIER 2 substances Metals

20. Results The purpose is not to propose the definitive list, but to test the procedure (i.e. test run) Only preliminary results Conclusions may vary according to additional data/information

21. calculated only from analyses >DL all analyses, replacing less-than values by DL/2 i.e. when quantified, the substance should demonstrate a risk i.e. widespread risk Only substances fulfilling both Risk1>1 and Risk2>1 are presented Legend Substances for which more than 90% of the measurements are < DL are said to be of poor determination (poor deter.) Substances already considered by the proposal for a daughter directive on EQS are highlighted in blue and said to be WFD subst.

22. Risk ratios for aquatic life Calculated as PECwater / PNECwater Risk ratios should be interpreted in view of the Assessment Factors (AF) used for the PNEC derivation Substances highlighted in red are substances for which risk for aquatic life can be concluded with quite high confidence and are substances not covered by the daughter directive proposal

23. How to conclude when PNEC << DL ? For some substances (e.g. pyrethroids) PNEC are far below the determination limit In such cases, risk cannot be excluded. Further investigation should be recommended for such substances

24. Risk ratios for drinking water Production of drinking water may become an issue when the raw water is too highly contaminated (depends on the treatment efficiency)

25. Risk ratios for sediment Data were submitted as different analysed fractions: 2mm, 20µm, or 63 µm Risk ratios were calculated for each of the available fractions The most conservative risk is presented here

26. Risk ratios for biota Data were submitted as different biota: mussels, molluscs or fish Risk ratios were calculated for each of these biota The most conservative risk is presented here

27. Risk ratios for biota (2) To supplement the dataset, concentrations in biota can also tentatively be estimated from concentrations in water and from BCF Risk ratios as (PECwater.BCF) / PNECoral can be calculated (results only presented for substances with BCF>1000) Highly bioaccumulable compounds (i.e. highly hydrophobic) tends to be poorly determined in water  approach not recommended

28. COMMPS outputs Top 40 for water Top 40 for sediment

29. Metals in water Exceedances of PEC according to the background concentration (90th percentile, from FOREGS ) and according to the tentative PNEC were investigated

30. Metals in sediment

31. Metals in biota

32. Summary These substances show high evidence of risk to or via the aquatic environment. May not be a widespread problem though New evidence may lead to the identification of additional substances of concern Preliminary results only (i.e. test run)

33. Follow-up - March 2008: closing date for data submission - Spring 2008: update the manageable list collect effect data for new candidates re-do the ranking - October 2008 (WG E-4): presentation of the final results