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The 2nd Prioritisation Exercise under the Water Framework Directive: Monitoring, Modelling

based approaches and Outcome Raquel N. Carvalho, Dimitar Marinov, Robert Loos, Dorota Napierska, Isabella

Sanseverino Gunther Umlauf and Teresa Lettieri

WG chemicals Meeting Brussels, 15-16 December 2016

Overview Introduction to the Monitoring and Modelling based approaches. Criteria for selection of the top ranked substances from monitoring

based exercise. Criteria for selection of the substances from modelling exercise.

Factsheets’ preparation of the selected substances from the two

exercises.

Conclusions and Recommendations Derivation of QS for ten selected substances based on SG-R

comments: Current status of the dossiers (II part)

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Splitting into modeling and monitoring processes

Monitoring based exercise 326 substances (5%) Modeling based exercise

6197 substances (95%)

INITIAL LIST 6523 substances

Overall Exercise

STE approach Screening Risk score Risk Assessment Phase

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extenttemporalspatial FFFScore

Range of Scores: between 0 and 3

STE method combines the frequencies of Spatial, Temporal and Extent of PNEC exceedances per sampling site

Background

STE approach is built on the idea for chemicals prioritisation at river basin scale proposed by Peter von der Ohe et al. (2011)

JRC includes a new factor (Temporal factor)

Monitoring based exercise: STE approach

What is STE ?

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• The risk is evaluated (by a statistical analysis of measured concentrations (MEC) vs. toxicological threshold (PNEC)) considering:

How large (wide) is the impact spatially

How frequently the exceedances happen

What is the scale (size) of the exceedance

• The spatial, temporal and extent factors are not interconnected since they evaluate substances from different perspectives

• The spatial, extent and temporal factors are summed in a single (representative) assessment score (STE score) that allows to rank (order) substances

Robustness and sensitive analysis was performed (JRC technical report uploaded in CIRCABC (https://circabc.europa.eu/w/browse/daf15c7e-0e53-41da-8238-c62b4b2acabf )

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STE Features

Data set as disaggregated

PNEC/EQS value (as first criteria the lowest)

Minimum Criteria Outlier Removal Sc2-PNECQC (remove all data if LOD and LOQ/2> PNEC) Quality check again and again

PNEC/EQS refinement for substance highly ranked

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STE score Risk

classification Risk rank

≥ 2.4 and ≤3 Very high 1

≥ 1.8 and < 2.4 High 2

≥ 1.2 and < 1.8 Intermediate 3

≥ 0.6 and < 1.2 Low 4

< 0.6 Very low 5

extenttemporalspatial FFFScore

Range of Scores: between 0 and 3

Risk Classification and STE score

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Exclusion of PAHs, 2-Hydroxyatrazine, ethion

STE approach

Exclusion of substances:

• Prioritised substances (PAHs)

• Banned substances (ethion)

• Associated to prioritised substances

326 substances

MONITORING BASED EXERCISE

Spatial, Temporal and Extent of PNEC exceedances

Short list monitoring (STE score ≥ 1.8): 21 substances

Environmental matrix (surface water – whole

water and dissolved, sediment, biota)

Data quality check

Short list of 14 substances to be further scrutinised , factsheets

were prepared as potential candidates for EQS derivation

Monitoring Based Exercise Flow Chart Monitoring data

from 4 MS or more, no less than 10 sites,

and 51 samples PNEC availability

Distribution of the 326 substances in each class

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Exclusion of PAHs, 2-Hydroxyatrazine, ethion

STE approach

Exclusion of substances:

• Prioritised substances (PAHs)

• Banned substances (ethion)

• Associated to prioritised substances

326 substances

MONITORING BASED EXERCISE

Spatial, Temporal and Extent of PNEC exceedances

Short list monitoring (STE score ≥ 1.8): 21 substances

Environmental matrix (surface water – whole

water and dissolved, sediment, biota)

Data quality check

Short list of 14 substances to be further scrutinised , factsheets

were prepared as potential candidates for EQS derivation

Monitoring Based Exercise Flow Chart Monitoring data

from 4 MS or more, no less than 10 sites,

and 51 samples PNEC availability

CIRCABC : https://circabc.europa.eu/w/browse/52c8d8d3-906c-48b5-a75e-53013702b20a (report)

12 Permethrin is missing since the PNEC was refined in the factsheet/ dossier while Selenium and Cr6+ PNEC were modified in the factsheet

Monitoring Based Exercise Flow Chart

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Exclusion of PAHs, 2-Hydroxyatrazine, ethion

STE approach

Exclusion of substances:

• Prioritised substances (PAHs)

• Banned substances (ethion)

• Associated to prioritised

substances

326 substances

MONITORING BASED EXERCISE

Short list monitoring (STE score ≥ 1.8): 21 substances Environmental matrix

(surface water – whole water and dissolved,

sediment, biota) Data quality

check

Short list of 14 substances to be further scrutinised ,

factsheets were prepared as potential candidates for EQS

derivation

Monitoring data from 4 MS or more,

no less than 10 sites, and 51 samples

PNEC availability

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Factsheets

Splitting into modelling and

monitoring processes

The Modelling-based exercise

Screening phase

Risk assessment

Final Ranking

Modelling based exercise

Initial list of substances

Substances are scored by hazard and exposure

Exposure assessment score

Ha

zard

ass

ess

me

nt

sco

re

4 3 2 1 0

Class 4 (5.6 to <= 7.0) 1 1 2 3 5

Class 3 (4.2 to < 5.6) 1 2 2 3 5

Class 2 (2.8 to < 4.2) 2 2 3 4 5

Class 1 (1.4 to < 2.8) 3 3 4 4 5

Class 0 (0.0 to < 1.4) 5 5 5 5 5

1 Substances are ranked based on the position in the matrix. Lower is the score in the matrix higher is the concern of the substance.

Screening risk score 1-2

The highest screening risk scores are biased toward industrial substances because of the high tonnage

Screening risk score 3-4

The screening risk scores 3 is still biased toward industrial substances

Screening risk score 5

Criteria for modelling based exercise

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6197 substances

MODELLING BASED EXERCISE

Screening phase Exposure

and hazard score

Risk assessment phase (RQ)

High RQ Monitoring data from ≥ 3 MS High STE scores

Screening risk score

Additional criteria (driven mainly by the

hazard properties)

PEC and PNEC derivation;

PNEC could be derived for 33 substances

Supporting info: STE scores

Short list modelling: 10 substances

Short list modelling

Short list of 4 substances to be further scrutinised. Factsheets were prepared as potential candidates for

EQS derivation

Addition of the STE score to the monitoring data

Further research of additional monitoring data

A final list of 53 candidate substances was obtained

Three additional steps (criteria) were applied to the screening phase ( 445 to 131 and then from 131 to 53

excluding the banned /not approved substance )

CIRCABC: https://circabc.europa.eu/w/browse/85b46283-9353-4e67-bf56-e4d18b32cba (report) https://circabc.europa.eu/w/browse/208181cc-8bff-43e1-af7c-3a0d6b0e649f (Annexes)

Criteria for modelling based exercise

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6197 substances

MODELLING BASED EXERCISE

Screening phase Exposure

and hazard score

Risk assessment phase (RQ)

High RQ Monitoring data from ≥ 3 MS High STE scores

Screening risk score

Additional criteria (driven mainly by the

hazard properties)

PEC and PNEC derivation;

PNEC could be derived for 33 substances

Supporting info: STE scores

Short list modelling: 10 substances

Short list modelling

53 substances

Short list of 4 substances to be further scrutinised. Factsheets were prepared as potential candidates for

EQS derivation

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Bias in the distribution of the substances

Initial list of 53 substances

Final list of 33 substances having a PNEC value

Selection

by PNEC

availability

Criteria for modelling based exercise

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6197 substances

MODELLING BASED EXERCISE

Screening phase Exposure

and hazard score

Risk assessment phase (RQ)

High RQ Monitoring data from ≥ 3 MS High STE scores

Short list of 4 substances to be further scrutinised. Factsheets were prepared as potential candidates

for EQS derivation

Screening risk score

Additional criteria (driven mainly by the

hazard properties)

PEC and PNEC derivation; PNEC could be derived for

33 substances Supporting info: STE

scores (HIGH)

Short list modelling: 10 substances

Short list modelling

53 substances

Selection of 10 substances ( High RQ and STE score)

SUBSTANCE PEC µg/L

FOCUS Step 3

PEC µg/L

ECETOC

PEC µg/L

Human

pharma

formula

PNEC µg/L RQ PEC RQ MEC p95

RQ PEC /

RQ MEC

p95

Monitored STE score

Drinking

water

Deltamethrin 0.36 0.001 0.0000031 116097 16129 7.2 YES 3

Pyridaben 10.40 0.00047 22132 53 416 YES 2.41

Dimoxystrobin 16.42 0.0032 5196 8 657 YES 2.13

Teflubenzuron 4.62 0.0012 3847 21 185 YES 2.28

Diflubenzuron 13.62 0.0040 3406 6.25 545 YES 2.09

Bifenthrin 0.05 0.00002 2705 1250 2.2 YES 3

Etofenprox 8.3 0.0054 1531 1.85 827 YES 1.52

Esfenvalerate 0.06 0.0001 634 500 1.27 YES 2.56

Triasulfuron 1.5 0.0032 484 15.6 31 YES 2.18

Fenpyroximate 4.4 0.010 440 NO

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Factsheets

Factsheets

Circulated in July to the SG-R for comments

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Factsheets

Upon consultation with SG-R (collection of comments and feedback on the factsheets), the following criteria were applied to eliminate from the short-list substances which: • are not authorised / are banned in the EU (Fenthion,

Azinphos-ethyl, Mevinphos, Parathion) • for which quality of monitoring data is pure/not

sufficient (Lambda-Cyhalothrin, Teflubenzuron) • for which PNEC changed (Barium, Chromium6+)

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Outcome of the 6Th SG-R: Table of confidence A summary table showing the certainty (Low, Medium and High) of the data quality, PNEC (AF)

To derive the EQS Derivation

To draft a dossiers for all substances

Conclusions (I) A new method (STE) has been developed and implemented in the monitoring based exercise process to improve the selection process. In the modelling exercise, additional criteria were implemented to ensure selection of substances from different classes. In the modelling exercise, data collections for hazard properties were collected for more than 2500. CIRCABC: https://circabc.europa.eu/w/browse/daf15c7e-0e53-41da-8238-c62b4b2acabf

Conclusions (II) Total 10 substances were identified, Omethoate was already shortlisted in the previous exercise. Permethrin, Deltamethrin, Malathion, Uranium and Selenium were identified as substances highly ranked but not taken forward in the previous exercise (most probably due to lack of data) As new substances: Nicosulfuron, Silver, Esfenvalerate and Bifentrhin

Information from WG Chem 2014-03-17-18 (10) Prioritisation Scoping Report amended March 2014

Remarks/ Recommendations(I)

Data Quality: It is essential

EQS Harmonitasion: it is urgent

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Differences in EQS/PNEC values

Min.: 0.0002 (RO) Max.: 0.02 (DE)

Min.: 0.05 (NL) Max.: 20 (PL)

Remarks/ Recommendations (II)

To Stakheolders: Share the ecotox data in time

My Acknowledgements

Dorota Napierska

Dimitar Marinov

Robert Loos

Nicola Chirico

Isabella Sanseverino Gunther Umlauf

Helen Clayton Sub-Group of Experts

(SG-R)

Stéphanie Schaan

European Chemical Agency (ECHA) European Environmental Agency (EEA)

Lidia Ceriani Alessio Ippolito

NORMAN (EMPODAT)

Database Pesticide (Czech Republic) State Agency of Medicines, (Republic of Latvia) INFARMED (Portugal) the Federal Environment Agency (Germany) DHI group (Denmark)

Raquel Carvalho