Foppe Smedes , Philipp Mayer · MMM01 NER01 NER02 NER05 NER06 NIV01 NIV02 RIK01 RIK02 RIK03 IHP01 IMA02IMA01 IEO01 IEO02 y = 1.009x + 6.96 R2 = 0.79 7 7.5 8 8.5 9 9.5 00.511.522.5

Linking Environmental Quality Standards and Passive samplingNORMAN expert meeting July, 2013, RECETOX, Brno, Czech Republic

Passive sampling in water related to biota

Foppe Smedes1,2, Philipp Mayer3

1 Deltares, Utrecht, The Netherlands2 RECETOX, Masaryk University, Brno, Czech Republic3 Department of Environmental Science, Aarhus University, Denmark

3-4 July 2013NORMAN meeting EQS and PS

RECETOX, Brno, Czech Republic

Can passive sampling predict concentrations in biota?



Can passive sampling predict concentrations in biota?

No



Can we predict concentrations in biota?

Biota is to variable



Lipid based concentrations in biota Two stations in the Western Scheldt

0

500

1000

1500

2000

2500

Ossenisse Valkenisse

PCB153

Shr

imp Pou

tS

ole

larg

e fe

mal

e

Bas

sA

reni

cola

mar

ina

Her

ring

0

500

1000

1500

2000

2500

Ossenisse Valkenisse0.0

0.2

0.4

0.6

0.8

1.0

1.2

Oss

enis

se/V

alke

niss

eRatio’s

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Oss

enis

se/V

alke

niss

eRatio’s

A/B

Sol

e la

rge

mal

e

Flou

nder

larg

e m

ale

Sol

e sm

all

Flou

nder

sm

all

Flou

nder

larg

e fe

mal

e

A B

Oss

enis

se/V

alke

niss

e

Ratio p

assiv

e sam

pling



Test with single organism

Passive samplersversus

“cogenetic” deployed mussels



Field - Mussel Frame



Lipid based log BAFs versus log Kow

y = 1.04x + 0.50

R 2 = 0.97

4

5

6

7

8

4 5 6 7 8

logKow

lipid

bas

ed lo

gBA

F

PCB170

PCB180 outliers

PAHsPCBsHCB

Monitoring by PS and deployed mussels in Dutch coastal waters (2001-2010)



PSTS 30 stations over Europe logCL in mussels versus logCwater

CB153

NIV03

UoQ02

UoQ01

FRS02

IFR01

MII01

MII02

MMM01

NER01

NER02

NER05NER06

NIV01

NIV02

RIK01RIK02

RIK03

IHP01

IMA02IMA01

IEO01

IEO02y = 1.009x + 6.96

R2 = 0.79

7

7.5

8

8.5

9

9.5

0 0.5 1 1.5 2 2.5

Log Cwater (pg/L)

Log

Cm

usse

l(pg

/kg

lipid

)



PSTS individual: CL mussels versus Cwater

Benz[a]pyrene

NIV03

UoQ02

UoQ01FRS02

IFR01

MII01

MII02

MMM01

NER01

NER02NER05

NER06NIV01

NIV02

RIK01RIK02

RIK03IHP01

IMA02IMA01

IEO01

IEO02

y = 1.3204x + 6.063R2 = 0.8599

7

8

9

10

11

12

0 1 2 3 4

Log Cwater (pg/L)

Log

Cm

usse

l(pg

/kg

lipid

)



ICES Passive Sampling Trial Survey (ICES PSTS)Avg logBAF (dw) versus logKow

0

1

2

3

4

5

6

7

8

0 1 2 3 4 5 6 7 8log KOW

log

BA

FPCB

PAH

log BAF= 0.82* log KOW -0.52



BAF at some individual Stations

Mouth of Seine (F)

y = 0.87x - 0.52R2 = 0.83

2

3

4

5

6

7

2 3 4 5 6 7 8logKow

logB

AF

PAHsCBs

Inner Galway (IRL)

y = 0.86x - 0.52R2 = 0.88

2

3

4

5

6

7

2 3 4 5 6 7 8logKow

logB

AF

PAHsCBs

Karmoy (N)

y = 1.07x - 0.52R2 = 0.92

2

3

4

5

6

7

8

2 3 4 5 6 7 8logKow

logB

AF

PAHsCBs

y = 0.87x - 0.52R2 = 0.83



End so on

It looks great but we stilllook at a log scale

Predictions from PS would still need to use (variable) literature BCF or BAFs

!!How to get around that?



Several ways to lipid based concentrationsB

iotic

Met

hods

A-b

iotic

Met

hods

Transform to model lipid basis

eqCP / Ksr,lip

Equil. concentration in the sampler

4

Sample inside the organism


eqCP / Ksr,lip

Analysis

Equilibrate sampler

with fish tissuePicture: U. Berger

2

Classical biomonitoring

Select length, age, sex

Homogenise

Analysis

Express conc.on lipid basis

CB / flip

Fishing

1

Analysis

Passive sampling in water

Freely dissilved conc.in the water phase

Transform to lipid basis

CW х BCF or Cw х BAF

3



Sampler-lipid partition coefficients (KP,L or KL,P)

• Not different for lipids

• Not affected by lipid uptake in the sampler

• No measurable temperature effect

• Are relatively small

and can therefore be accurately measured



Measured CLip mussel versus A-Biotic- lipid based concentrations averagedfor all stations and years

PCB153, All years and all stations

1 to 1

y = 0.1366x

R2 = 0.2179

0

200

400

600

800

1000

1200

0 2000 4000 6000 8000 10000A‐Biotic lipid based µg/kg

C‐mussel lipid based

µg/kg

Autumn

Winter

Pyrene, All years and all stations

y = 0.3384x

R2 = 0.8695

0

500

1000

1500

2000

2500

0 1000 2000 3000 4000 5000 6000 7000A‐Biotic lipid based µg/kg


µg/kg

Error bars represent the standard deviation over 10 years data



Ratio of measured CLip in mussels and CAL from PS

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0P

hen

Pyr

Flu

Chr

y

BaA

BbF

BkF

BaP

Bgh

iPe

DB

ahA

InP 28 31 44 49 52 101

105

118

138

153

170

180

187

WinterAutumn



Ratio of measured CLip and CAL uit PS for Eel and Roach

Eel and Roach at 3 freshwater stations

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

HCB 28 52 101 118 153 180

EelRoach

PCBs

skip



A-biotic obtained logKAL,W versus logKOW

y = 1.18x ‐ 0.19R² = 0.97

3

4

5

6

7

8

3 4 5 6 7 8LogKow

PAH PRC

PCB OCP

A-b

iotic

lipi

d-w

ater

par

titio

n co

effic

ient

s

Calculated from Kpw and KLP



Ratio of CLip in mussel with C-octanol

0.0

1.0

2.0

3.0

4.0

5.0

6.0P

hen

Pyr Flu

Chr

y

BaA

BbF BkF

BaP

Bgh

iPe

DB

ahA

InP 28 31 44 49 52 101

105

118

138

153

170

180

187

WinterAutumn



Can we predict concentrations in biota?

So, although biota is still to variable

passive sampling can givea prediction for

a lipid based concentration that biota would have if they were in equilibrium with their

environment



Several ways to lipid based concentrationsClassical

biomonitoring

Select length, age, sex

Homogenise

Analysis


CB / flip

Fishing

1

Bio

tic M

etho

ds

A-b

iotic

Met

hods


eqCP / Ksr,lip

Equil. concentration in the sampler

4

Sample inside the organism


eqCP / Ksr,lil

Analysis

Equilibrate sam

with fish tissuePict: U.Be

pler

rger,Janhke 2009

2

Analysis

Passive sampling in water

Freely dissilved conc.in the water phase

Transform to lipid basis

CW х BCF or Cw х BAF

3



Availability Not always GoodAnimal wellfare Not really YesStationary No guarantees YesImmortal No YesEqual for species, age, sex, size

No (No)b Yes

Independent of stress? No YesProxy for exposure

(chemical activity)More or

less,not for lean

Yes (Yes) Yes

Includes compounds that metabolize?

No No Yes

Quality standards available?

Yes Yes (biota?) Yes (biota?)

Transfer to model lipid basis

eqCP / Ksr,lip

4


eqCP / Ksr,lip

4


eqCP / Ksr,lil

2


eqCP / Ksr,lil

2


CB / flip

1


CB / flip

1

Transfer to lipid basis

CW х BCF or Cw õ BAF

3

Transfer to lipid basis

CW х BCF or Cw õ BAF

3



Is there a future for an A-Biotic exposure level

Advantages Worldwide comparableDifferent waters Fresh and saline water, toxic, anoxic, porewater

Relevant for uptake by exposure of organismsMetabolisation not included# Not mortal

# Also exposure data for compounds not found in the biota



Thank you for your attention



Bioakkumulation in aquatischen Systemen: Methoden, Monitoring, Bewertung6./7. Marz 2013 in Koblenz

Lipid based logBAF using results of passive sampling versus logKowSome fresh water organism

3

4

5

6

7

8

3 4 5 6 7 8

Log

BA

F

PCBs

HCB

4,4-DDE

BDEs

Zebra mussel

3

4

5

6

7

8

3 4 5 6 7 8

PAKs

3

4

5

6

7

8

3 4 5 6 7 8

Log Kow

Log

BA

F

Roach

3

4

5

6

7

8

3 4 5 6 7 8

Log Kow

Log

BA

F

3

4

5

6

7

8

3 4 5 6 7 8

Log Kow

Log

BA

F Li

piod

Eel

3

4

5

6

7

8

3 4 5 6 7 8

Log

BA

F Li

pid

PCBs

HCB

4,4-DDE

BDEs

3

4

5

6

7

8

3 4 5 6 7 8

PAKsPAKs



Measured CLip mussel versus A-Biotic lipid based conc2004 station : 2 ,Autumn

PCB028

PCB101PCB118

PCB138

PCB153

PCB170PCB180

PCB187

1 to 1y = 0.3015x

R2 = 0.9851

0

50

100

150

200

250

300

350

400

0 500 1000 1500

A‐Biotic lipid based µg/kg


µg/kg

2004 station : 2 ,Autumn

90

1 to 1

Pyr

Flu

Fen

ChrBkF

bghiPe

BbF

BaP BaA

y = 0.241x

R2 = 0.3487

0

50

100

150

200

250

300

350

400

450

0 500 1000 1500 2000



µg/kg

2007 station : 5 ,winter

PCB018PCB028

PCB101

PCB118

PCB138

PCB153

PCB170

PCB180

PCB187

1 to 1 y = 0.1289x

R2 = 0.9664

0

100

200300

400

500

600

700800

900

1000

0 2000 4000 6000 8000



µg/kg

2007 station : 5 ,winter

266

1 to 1 Pyr

Flu

FendbahA

ChrbghiPeBaPBaA

y = 0.4727x

R2 = 0.934

0

500

1000

1500

2000

2500

0 1000 2000 3000 4000 5000



µg/kg

Wadden Sea

Western Scheldt

Documents

Foppe Smedes , Philipp Mayer · MMM01 NER01 NER02 NER05 NER06 NIV01 NIV02 RIK01 RIK02 RIK03 IHP01 IMA02IMA01 IEO01 IEO02 y = 1.009x + 6.96 R2 = 0.79 7 7.5 8 8.5 9 9.5 00.511.522.5