modelkey (511237-goce) is a research project funded by suggestions for the derivation of candidate...

MODELKEY (511237-GOCE) is a research project funded by

Suggestions for the derivation of candidate compounds for monitoring and prioritisation

Werner Brack, Jan Balaam, Nicole Bandow, Damia Barcelo, Rikke Brix, Edwin Foekema, Stefania Gottardo, Marja Lamoree, Pim

Leonards, Urte Lübcke-von Varel, Miroslav Machala, Isabel Munoz

Gracia, Claudia Schmitt, Mechthild Schmitt-Jansen, Katrin Schwab,

Peter von der Ohe, Kevin Thomas, Jana Weiss, Dick de Zwart


AA-EQS

Log TU Max Daphnia magna-4 -3 -2 -1 0

0

20

40

60

80

SP

EA

R [

%]

n = 30

Von der Ohe et al. 2009. IEAM 5

AF 1000 LC50

Motivation: Evidence of Toxic Stress

In all investigated river basins: Disappearance of sensitive species (SPEAR) with increasing contamination

Significant effects on invertebrate community at concentrations factor 1000 below acute LC 50 to Daphnia.

In agreement with AF 1000!


Motivation: Evidence of Toxic Stress

AA-EQS

Log TU Max Daphnia magna-4 -3 -2 -1 0

0

20

40

60

80

SP

EA

R [

%]

Chlorfenvinphos

Chlorpyrifos

Mesocosm-based EQS

However: be careful with EQS based on chronic or mesocosm data!

These data do not reflect species interactions and long term effects.

Values with AF<1000 relative to acute toxicity are not protective.

EQS 0.1 µg/LLC50 0.3 µg/L

EQS 0.03 µg/LLC50 1.25 µg/L


http://www.modelkey.org

50 mio known chemicals

5.00 10.00 15.00 20.00 25.00 30.00 35.000

500000

1000000

1500000

2000000

2500000

3000000

3500000

4000000

4500000

5000000

5500000

6000000

6500000

7000000

7500000

8000000

8500000

9000000

9500000

1e+07

Time-->

Abundance

TIC: WER046.D

thousands of compounds in real world samples

33 priority pollutants (WFD)

Motivation: The dilemma of complexity

How to define candidate compounds for monitoring and prioritisation?


Current Prioritisation Approach

1) Monitoring-based approach:

• Monitoring data from > 4 countries

• Prioritisation based on (P)EC/PNEC (arithmetic means)

• (P)EC>PNEC at > 10% of sites prioritisation

2) Modeling-based approach • Larger list of candidate compounds (different sources)

• Exposure assessment based on total production and use

• Hazard assessment based on experimental or QSAR data related to PBT and endocrine disruptor properties

• Risk score equal to 1 prioritisation, PEC/PNEC ranking


MODELKEY suggestion: Add field relevance-based approach

Monitoring data evaluation

(basin scale)

Prediction of Toxic Units

(TU) or Potentially Affected Fractions (PAF) of

communities

Correlation between species similarity

matrix and environmental

matrix

Effect-directed analysis in water, sediments and biota to identify

toxicologically relevant compounds

Site-specific investigations at

sources and sinks

Exposure modeling,

trophic magnification

Monitoring programs


Monitoring Data Evaluation

PO O

OH

O

CH3

Cl

Cl

PS

O

O

O

CH3

CH3N

+O

-

O

Compound n % sitesBis-(2-ethylhexyl)-phthalat 786 100

Chlorfenvinfos 9 100

Dichlorvos 11 100

Mevinfos 47 100

Parathion-ethyl 25 100PCB 77 25 100Azoxystrobin 187 99

2,4'-DDT 444 97

Chlorpyrifos 62 95

PCB 126 16 94

Diazinon 13 92

Tricyclohexyltin 22 91

Nonylphenol-1-ethoxylate 10 90

Example: Compounds with log TU > -3 (Daphnia magna) in Elbe

Priority pollutants P

O

OO

O

CH3

CH3

CH3

O

OCH3


Physical and chemical parameters (pH, water temperature, conductivity, oxygen concentration, nutrients) and 29 pharmaceuticals versus biological communities (diatom and invertebrate communities)

Multivariate statistical analysis: (RDA: redundancy analysis)

-0.4 1.2

-0.6

1.0

Ibuprofen

Indomethacine

Propranolol

Temperature

A1A

A2A

A3A

LL1A

LL2A

LL3A LL4A

A1B

A2B

A3B

LL1B

LL2B

LL3B

LL4B

A1C

A2CA3C

LL1C

LL2C

LL3C

LL4C

-0.4 1.0

-0.6

0.8

TubificidaeEnchytraeidae Naididae

Other Ephemeroptera

Baetis

Caenis

Chironomus spp

Cricotopus sp

Cryptochironomus

Nanocladius

Orthocladiinae

Polypedilum Rheocricotopus

Stictochironomus

Tanytarsus

Tanypodinae

Muñ

oz e

t al

., 2

009,

ET

&C

28:

2706

-271

4

Monitoring: Correlation approach

Tubificidae

ChironomusGood correlation between the abundance and biomass of

several benthic invertebrates (Tubifex, Chironomus) and

pharmaceuticals (ibuprofen, propanolol, in

domethacine)

Causal pathway assessment, large scale monitoring


Site-specific: Effect Directed Analysis

• Site specific

• Endpoint specific

• Based on selected in vivo or in vitro biotests

• No a priori knowledge on or selection of compounds required

• Applicable to any matrix (water, sediments, biota, …)

• Site selection: integrative sink area or source area

environmentalcontamination

biologicalanalysis

biologicalanalysis

chemicalanalysis

fractionation

confirmation

toxicant


Effect Directed Analysis

Example: Sublethal effects by sediment contamination

Conventional sediment assessment: Focus on non-polar priority pollutants PAHs, chlorinated pesticides (DDT, HCH, HCB, aldrin, dieldrin…) and PCBs and PCDD/Fs



0

20

40

60

80

100

120

P1

P2

P3

P4

P5

P6

P7

P8

P9

P10

P11

P12

P13

P14

P15

P16

P17

P18

fractions

% o

f co

ntro

l

0

500

1000

1500

2000

2500

3000

3500

4000

P1

P2

P3

P4

P5

P6

P7

P8

P9

P1

0

P1

1

P1

2

P1

3

P1

4

P1

5

P1

6

P1

7

P1

8

pm

ol T

4 eq

/g d

ry s

edim

ent

0

5

10

15

20

25

30

35

40

P 1

P 2

P 3

P 4

P 5

P 6

P 7

P 8

P 9

P 1

0

P 1

1

P 1

2

P 1

3

P 1

4

P 1

5

P 1

6

P 1

7

P 1

8

% m

ax

imu

m i

nd

uc

tio

n

thyroid hormone disturbing potency

estrogenicity

tumor promotion (inhibition of GJIC)

0

10

20

30

40

50

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

nu

mb

er

of

po

sit

ive

we

lls

TA98

TA98 with metabolicactivation

mutagenicity

PCBs, PCDD/Fs, halogenated pesticides PAHs polar compounds

Polar compounds play a key ro

le for m

any hazards due to con-

taminated sediments! Even more if b

ioavailability is considered



Non-regulated compounds identified by EDA studies (algal toxicity, endocrine disuption, mutagenicity)

Examples from sedimentsO

benzanthrone

O

O

CH3

2-methylanthra-quinone

O

OH

Cl

Cl

Cltriclosan

NH

N-phenyl-2-naphthylamine

N+ O

-O

N+

O-

O

dinitropyrenes

O

Onandrolone

O

tonalide

O

traseolide

O

galoxolideCl

OP

O

OCl

O

Cl

tris(2-chloroisopropyl) phosphate


Conclusions

• Strong evidence on toxic stress indicators available

• Priority pollutants are poor predictors for adverse effects

• Mesocosm/chronic tox-based EQS with AF<1000 are not protective

• Powerful tools for deriving candidate compounds from monitoring data available (TU, msPAF, correlation)

• Include field-based evidences by EDA at selected sites in candidate compound identification

• New evidences on the importance of polar emerging pollutants for toxic stress

• Define and monitor priority effects together with priority pollutants


We still see only the tip of the iceberg!

Conclusions

Research needs: Analytical tools, databases and computer tools for

structure elucidation of difficult (polar, thermolabile, multifunctional….) unkowns.

Reliable tools for prediction of chromatographic retention, spectroscopic properties and effects

Combine EDA with strong biological diagnostic tools (omics)

Integrated approaches for compound prioritisation


Thanks a lot for your attention

modelkey (511237-goce) is a research project funded by suggestions for the derivation of candidate...

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