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. 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.)
CAS number
PEC in water (monitoring)
PEC in sediment
(monitoring)
PEC in biota (monitoring)
PNEC for aquatic
organisms
PNEC for benthic
PNEC for secondary
poisoning of predators
Maximum allowed
residues in food
Drinking water criteria
Water Solubility
log Kow
Vapour pressure
Biodegradability
Hydrolysis
Production
Releases
PEC (modelling)
Representativeness
Endocrine Disruption

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

19. Every substance will be ranked
TIER 3 substances
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. i.e. when quantified, the substance should demonstrate a risk
Legend
calculated only from analyses >DL
all analyses, replacing less-than values by DL/2
Only substances fulfilling both Risk1>1 and Risk2>1 are presented
i.e. when quantified, the substance should demonstrate a risk
i.e. widespread risk
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