the derivation of benchmarks

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David Copplestone (University of Stirling) The derivation of benchmarks

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The derivation of benchmarks. David Copplestone (University of Stirling). OBJECTIVES. What is a benchmark?. Why are benchmarks needed?. How are benchmarks derived?. How are benchmarks used?. INTRODUCTION. The need for benchmarks... ... a retrospective screening model example. - PowerPoint PPT Presentation

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Page 1: The derivation of benchmarks

David Copplestone

(University of Stirling)

The derivation of benchmarks

Page 2: The derivation of benchmarks

OBJECTIVESWhat is a benchmark?

Why are benchmarks needed?

How are benchmarks derived?

How are benchmarks used?

Page 3: The derivation of benchmarks

INTRODUCTION

The need for benchmarks...

... a retrospective screening model example

www.ceh.ac.uk/PROTECT

Page 4: The derivation of benchmarks

Fundamental to this approach is the necessity for the dose estimate to be

conservative

A Tier-1 screening model of risk to fish living in a radioactively contaminated

stream during the 1960s

This assures the modeler that the PREDICTED DOSES are LARGER

than the REAL DOSES

www.ceh.ac.uk/PROTECT

Page 5: The derivation of benchmarks

1) SOURCE TERM: used 1964 maximum release as a mean for calculations

2) EXPOSURE: assumed fish were living at point of discharge

3) ABSORPTION: assumed allfish were 30 cm in diameter

which maximized absorbed dose

4) IRRADIATION: behavior offish ignored, assumed theyspent 100% of time on bottom

sediments where > 90% of radionuclides are locatedCONTAMINATED

SEDIMENTS

54 59 64 69 74 79 840

1000

2000

3000

4000

5000To

tal 1

37

-Cs

Re

lea

sed

(G

Bq

)

Year

Conservative Assumptions forScreening Calculations

www.ceh.ac.uk/PROTECT

Page 6: The derivation of benchmarks

Resulting Dose Rates (mGy y-1)

www.ceh.ac.uk/PROTECT

Page 7: The derivation of benchmarks

www.ceh.ac.uk/PROTECT

Page 8: The derivation of benchmarks

www.ceh.ac.uk/PROTECT

Page 9: The derivation of benchmarks

www.ceh.ac.uk/PROTECT

Page 10: The derivation of benchmarks

…a BENCHMARK value

We need a point of reference; a known value to which we can compare…

Page 11: The derivation of benchmarks

www.ceh.ac.uk/PROTECT

Benchmarks values are concentrations, doses, or dose rates that are assumed to be safe based on exposure – response

information. They represent « safe levels » for the ecosystem

Benchmarks values are concentrations, doses, or dose rates that are assumed to be safe based on exposure – response

information. They represent « safe levels » for the ecosystem

Benchmarks are numerical values used to guide risk assessors at various decision points in a tiered approach

The derivation of benchmarks needs to be through transparent, scientific reasoning

Benchmarks correspond to screening values when they are used in screening tiers

Definition of benchmarks

Page 12: The derivation of benchmarks

www.ceh.ac.uk/PROTECT

Data on radiation effects for non-human speciesWildlife Group Morbidity Mortality

Reproductive capacity Mutation

Amphibians

Aquatic invertebrates

Aquatic plants

Bacteria

Birds

Crustaceans

Fish

Fungi

Insects

Mammals

Molluscs

Moss/Lichens

Plants

Reptiles

Soil fauna

Zooplankton

No data

To few to draw conclusions

Some data

Page 13: The derivation of benchmarks

Approaches to derive protection criteria

www.ceh.ac.uk/PROTECT

Page 14: The derivation of benchmarks

www.ceh.ac.uk/PROTECT

Page 15: The derivation of benchmarks

Historic reviews From literature reviews Earlier numbers derived by expert judgement

(different levels of transparency) Later numbers, more quantitative/mathematical Levels of conservatism? Often “maximally exposed individual” not

population... NCRP 1991 states use with caution if large

number of individuals in a population may be affected

Page 16: The derivation of benchmarks

A Quantitative approach

Used to derive the ERICA and PROTECT values

Consistent with EC approach for other chemicals

Page 17: The derivation of benchmarks

www.ceh.ac.uk/PROTECT

Effect (%)

Regression model

100 %

50 %

10 %

ContaminantConcentration

Observed data

NOEC: No observed effect concentration

LOEC: Lowest observed effect concentration

Exposure-response relationship from ecotoxicity tests

…based on available ecotoxicity data; (i.e. Effect Concentrations; EC) typically EC50 for acute exposure

conditions and EC10 for chronic exposures

Methods recommended by European Commission for estimating predicted-no-effects-concentrations for chemicals

How to derive « safe levels »

EC10 EC50

Page 18: The derivation of benchmarks

Effect (%)

Regression model

100 %

50 %

10 %

EC10

ED10

EDR10

Concentration (Bq/L or kg)Dose (Gy)Dose Rate (µGy/h)

EC50

ED50

EDR50

Observed data

NOEC: No observed effect concentration

LOEC: Lowest observed effect concentration

Exposure-response relationship from ecotoxicity tests(specific to stressor, species, and endpoint)

....adapted for radiological conditions....

How to derive « safe levels »

Page 19: The derivation of benchmarks

www.ceh.ac.uk/PROTECT

Deriving benchmarks for radioecological risk assessments

i.e. screening values thought to be protective of the structure and function of generic

freshwater, marine and terrestrial ecosystems.

Two methods have been developed• Fixed Assessment (Safety) Factors

Approach• Species Sensitivity Distribution Approach

Page 20: The derivation of benchmarks

www.ceh.ac.uk/PROTECT

Fixed assessment factor method

Main underlying assumptions In the frame of this approach, extrapolations are made from:

•The ecosystem response depends on the most sensitive species

•Protecting ecosystem structure protects community function

•Acute to chronic•One life stage to the whole life cycle•Individual effects to effects at the population level•One species to many species•One exposure route to another•Direct to indirect effects•One ecosystem to another•Different time and spatial scales

PNEV = minimal Effect Concentration / Safety Factor

Page 21: The derivation of benchmarks

www.ceh.ac.uk/PROTECT

Fixed assessment factor method

Main underlying assumptions In the frame of this approach, extrapolations are made from:

•The ecosystem response depends on the most sensitive species

•Protecting ecosystem structure protects community function

•Acute to chronic•One life stage to the whole life cycle•Individual effects to effects at the population level•One species to many species•One exposure route to another•Direct to indirect effects•One ecosystem to another•Different time and spatial scales

PNEV = minimal Effect Concentration / Safety Factor

The safety factor method is highly conservative as it implies the

multiplication of several worst cases

Page 22: The derivation of benchmarks

www.ceh.ac.uk/PROTECT

The approach used to derive no-effects values

STEP 1 – quality assessed data are extracted from the FREDERICA database

STEP 2 – A systematic mathematical treatment is applied to reconstruct dose-effect relationships and derive critical toxicity endpoints. For chronic exposure, the critical toxicity data are the EDR10

Page 23: The derivation of benchmarks

www.ceh.ac.uk/PROTECT

STEP 3 –

The hazardous dose rate (HDR5) giving 10% effect to 5% of species is estimated The final PNEDR is then obtained by applying an additional safety factor (typically from 1 to 5) to take into account remaining extrapolation uncertainties

The predicted no-effect dose rate (PNEDR) evaluation

Page 24: The derivation of benchmarks

www.ceh.ac.uk/PROTECT

• The 5% percentile of the SSD defines HDR5 (hazardous dose rate giving 10% effect to 5% of species)

• HDR5 = 82 μGy/h

SSD for generic ecosystem at chronic external γ-radiation (ERICA)

• PNEDR used as the screening value at the ERA should be highly conservative

• SF = 5 • PNEDR ≈ 10 μGy/h

PNEDR = HDR 5% / SF

Page 25: The derivation of benchmarks

www.ceh.ac.uk/PROTECTBest-Estimate Centile 5% Centile 95%

Vertebrates Plants Invertebrates

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0.1 1 10 100 1000 10000 100000 1000000 10000000

Dose rate (µGy/h)

Percentage of Affected Fraction

5%

HDR5 = 17 µGy/h [2-211] PNEDR=10 µGy/h

(SF of 2)

EDR10 and 95%CI: Minimum value per species

Generic ecosystem SSD for chronic external γ-radiation (PROTECT)

Page 26: The derivation of benchmarks

www.ceh.ac.uk/PROTECT

…a BENCHMARK value

We need a point of reference; a known value to which we can compare…

10 μGy/h * 24 h / d = 240 μGy/d = 0.2 mGy /d

Page 27: The derivation of benchmarks

Reminders…

The PNEDR: is a basic generic ecosystem screening value Can be applied to a number of situations

requiring environmental and human risk assessment

Be aware of: PNEDR was derived for use only in Tiers 1 and

2 of the ERICA Integrated Approach Use for incremental dose rates and not total

dose rates which include background

Page 28: The derivation of benchmarks

www.ceh.ac.uk/PROTECT

Background radiation exposure for ICRP RAPs (weighted dose rates)

Marine organisms – 0.6 - 0.9 μGy/h (Hosseini et al., 2010)

Freshwater organisms – 0.4 – 0.5 μGy/h (Hosseini et al., 2010)

Terrestrial animals and plants – 0.07-0.6 μGy/h (Beresford et al., 2008)

Page 29: The derivation of benchmarks

www.ceh.ac.uk/PROTECT

Background radiation exposure for ICRP RAPs

Marine organisms – 0.6 - 0.9 μGy/h (Hosseini et al., 2010)

Freshwater organisms – 0.4 – 0.5 μGy/h (Hosseini et al., 2010)

Terrestrial animals and plants – 0.07-0.6 μGy/h (Beresford et al., 2008)

Derived screening dose rate (10 μGy/h) is more than 10 times these background values

Page 30: The derivation of benchmarks

Furthermore... The hazardous dose rate definition means that

95% of species would be protected at a 90% effect

However, there may be keystone species among that are unprotected at the 10% level and the effect on the 5% may be > 10%

Some keystone species will be more radiosensitive than others

Page 31: The derivation of benchmarks

Generic screening dose rate ERICA (default) and R&D128 assume a single

(generic) screening dose rate (i.e. application of predicted no effect dose rate) applicable across all species and ecosystems Advantage = simple PROTECT objective to consider scientifically

robust determination of (generic) screening dose rate(s)

What are limiting organisms for the 63 radionuclides considered in ERICA?

Page 32: The derivation of benchmarks

Limiting organisms Marine ecosystem ERICA Tool – generic screening dose rate

0

2

4

6

8

10

12

14

16

18

20

Phyto

plan

kton

Zooplan

kton

Vascu

lar p

lant

Mac

roalg

ae

Anem

one/

cora

l

Moll

usc

Polyc

haet

e wor

mBird

Mam

mal

Reptile

Page 33: The derivation of benchmarks

Limiting organisms Freshwater ecosystem ERICA Tool – generic screening dose rate

0

5

10

15

20

25

30

Phyto

plan

kton

Moll

usc

Gat

ropo

d

Inse

ct la

rvae

Vascu

lar p

lant

Zooplan

kton

Amph

ibian Bird

Page 34: The derivation of benchmarks

Limiting organisms Terrestrial ecosystem ERICA Tool – generic screening dose rate

0

5

10

15

20

25

Soil/D

etrit

ivoro

us in

vert

Flying

inse

ct

Gas

tropo

d

Lich

en

Gra

ss/h

erb

Shrub

Tree

Mam

mal

Bird

Reptile

Page 35: The derivation of benchmarks

Generic screening dose rate

Application of generic screening dose rate: Identifies the most exposed organism group

Does not (necessarily) identify the most ‘at risk’ (relative radiosensitivity not taken into account)

What does this mean for the assessment Likely to be conservative

May be overly so Propose wildlife group specific benchmark

dose rates

Page 36: The derivation of benchmarks

ICRP Approach

Page 37: The derivation of benchmarks

Effects

As part of ICRP 108, effects considered No dose ‘limits’ but still need something to

compare to …background …derived consideration reference levels

www.ceh.ac.uk/PROTECT

Page 38: The derivation of benchmarks

DCRLs

Derived Consideration Reference Levels

“A band of dose rate within which there is likely to be some chance of deleterious effects of ionising radiation occurring to individuals of that type of RAP (derived from a knowledge of expected biological effects for that type of organism) that, when considered together with other relevant information, can be used as a point of reference to optimise the level of effort expended on environmental protection, dependent upon the overall management objectives and the relevant exposure situation.”

Page 39: The derivation of benchmarks

DCRLs

Series1

0.001

0.01

0.1

1

10

100

1000

Deer Rat Duck

Frog Trout Flatfish

Bee Crab Earthworm

Pine tree

Grass Seaweed

mG

y/d

Background level

Page 40: The derivation of benchmarks

Application

Provision of advice on how to use the RAP framework

Likely to use ‘representative organism’ concept

Page 41: The derivation of benchmarks

Representative OrganismReference Animals and Plants

‘Derived consideration reference levels’ for environmental protection

REPRESENTATIVE ORGANISMS

Radionuclide intake and external exposure

Planned, emergency and existing exposure situations

Page 42: The derivation of benchmarks

Integration

Integrating the ICRP systems of protection for humans and non-human species Consider ethics and values Consider how principles of justification,

optimisation etc apply to both humans and non-human species

Consider the principles used in chemical risk assessment/protection

Page 43: The derivation of benchmarks

What is a benchmark?

www.ceh.ac.uk/PROTECT

In radiation protection, usually applied as the incremental dose ABOVE background

Benchmarks are numerical values used to guide risk assessors at various decision points

in a tiered approach

Page 44: The derivation of benchmarks

How are benchmarks derived? Quantitative approach eg chemicals

Safety factor, SSD

ICRP – will use DCRL values Are they benchmarks?

Currently summarise where biological effects are likely to occur

C5 is working on how the DCRLs can be incorporated into the wider ICRP system of radiological protection

Page 45: The derivation of benchmarks

www.ceh.ac.uk/PROTECT

Summary

Range of methods for deriving benchmarks Range of benchmarks proposed Be careful with the wording around the

benchmark What does it reflect?

Look for clear, well documented benchmark values

Watch this space for further developments!

Page 46: The derivation of benchmarks

Caveats... Adapted text in the older documents from NCRP (1991), IAEA (1992) and UNSCEAR (1996) is given

below:

NCRP Aquatic organisms: it appears that a chronic dose rate of no greater than 0 .4 mGy h−1 to the maximally exposed individual in a population of aquatic organisms would ensure protection for the population. If modelling and/or dosimetric measurements indicate a level of 0.1 mGy h−1, then a more detailed evaluation of the potential ecological consequences to the endemic population should be conducted

IAEA Terrestrial organisms: irradiation at chronic dose rates of 10 mGy d−1 and 1 mGy d−1 or less does not appear likely to cause observable changes in terrestrial plant and animal populations respectively. Aquatic organisms: it appears that limitation of the dose rate to the maximally exposed individuals in the population to <10 mGy d−1 would provide adequate protection for the populations

UNSCEAR Terrestrial plants: chronic dose rates less than 400 μGy h−1 (10 mGy d−1) would have effects, although slight, in sensitive plants but would be unlikely to have significant deleterious effects in the wider range of plants present in natural plant communities. Terrestrial animals: for the most sensitive animal species, mammals, there is little indication that dose rates of 400 μGy h−1 to the most exposed individual would seriously affect mortality in the population. For dose rates up to an order of magnitude less (40–100 μGy h−1), the same statement could be made with respect to reproductive effects. Aquatic organisms: for aquatic organisms, the general conclusion was that maximum dose rates of 400 μGy h−1 to a small proportion of the individuals and, therefore, a lower average dose rate to the remaining organisms would not have any detrimental effects at the population level