MODARIA Working Group 4 Analysis of radioecological data in IAEA - - PowerPoint PPT Presentation

Working Group 4 Analysis of radioecological data in IAEA Technical Reports Series publications to identify key radionuclides and associated parameter values for human and wildlife assessment

MODARIA

IAEA Parameter value compilations

Objectives

Using the recent data compilations:

• To identify the most important radionuclides,

pathways and parameter values – For different source terms – For different exposure situations

• Identify data gaps which matter
• Which key radionuclides require a process

based approach to modelling Consider both human and wildlife

Approach

• Analyse data quantity and quality
• Use freely available tools and/or other models
• Develop a set of criteria to evaluate importance of

parameter values

• Source terms
• Magnitude and importance of total, external and internal

dose

• Sensitivity of internal and external dose estimates due to

variability of environmental parameter values

Builds on, and compliments:

• Model based Sensitivity analysis
• Sensitivity EMRAS II WG

Using TRS publications - identify

• Which parameter values may be assumed to be

generically representative

• Which parameter values are not generically

representative as they vary significantly due to

• Ecosystems, agricultural practices, climate
• Physico – chemical form, soil characteristics
• Life cycle stages
• Data quality and quantity
• Which parameter values need more attention
• Variability – which number to use?

Variation in transfer coefficient and CR values

IAEA 2010 TRS 472

AMean: 6.1 x10-3, SD: 6.3 x10-3, n: 288, Median: 4.6 x 10-3, Kurtosis: 43.4, p-Value: 0.005 AMean: 1.1 x 10-1, SD: 1.2 x 10-1, n: 119, Median: 8.4 x 10-2, Kurtosis: 8.8, p-Value: 0.005

Deriving parameter values

Time, resources, access QC procedures Rejected sources, Untraceable data. Inappropriate data, Untested analogues, Rarely new data Decreased transparency

For a screening assessment

Increased conservatism

Look for data

Compile data and find gaps Look again, find derived values

Fill gaps

Assessment

Data quality and quantity False positives Increased costs

.... simplification:

Most approaches use concentration ratios (CR)

)) m (Bq air

• r

) dry weight kg (Bq soil ), l (Bq water (filtered media ion concentrat Activity weight) fresh kg (Bq body whole biota in ion concentrat Activity CR

3

• 1
• 1
• 1



IAEA wildlife TRS status

• Submitted early 2011 (publication ‘pending’)
• CRwo-media values given
• Generic Freshwater, Marine, Terrestrial and

Brackish water ecosystems

• Summarises CRwo-media data for >800 wildlife-

element combinations

• Values from the initial submitted text available

from: http://www.wildlifetransferdatabase.org/

IAEA outputs

• TRS transfer to wildlife
• TRS paper in press
• Online database
• Numerous associated

papers from EMRAS I and II

Wildlife Group CR wo-soil (Bq kg-1 fw whole organism /Bq kg-1 dw soil) References AM AMSD GM GMSD Min Max N Ag (Silver) Grasses and herbs 2.9E+0 3.7E+0 1.8E+0 2.7E+0 2.8E-3 9.8E+0 13 162, 212 Lichens and bryophytes 3.0E-2 3.4E-2 2.0E-2 2.5E+0 1.2E-2 1.3E-1 12 348 Shrub 2.1E-2 9.1E-3 1.9E-2 1.5E+0 1.2E-2 3.3E-2 5 348 Al (Aluminium) Lichens and bryophytes 1.1E-1 1.1E-1 7.1E-2 2.4E+0 1.0E-2 4.2E-1 32 348, 355 Shrub 1.9E-2 1.8E-2 1.4E-2 2.2E+0 2.9E-3 1.2E-1 119 347, 348 Am (Americium) Amphibian 1.3E-1 3.4E-2 1.3E-1 1.3E+0 1.0E-1 1.5E-1 22 486 Annelid 1.8E-1 3.0E-1 9.0E-2 3.2E+0 5.2E-2 1.1E+0 13 171, 486, 488 Arachnid 5.7E-2 6.2E-2 3.8E-2 2.4E+0 2.2E-2 1.3E-1 20 170, 488 Arthropod 1.1E-1 2.9E-1 4.0E-2 4.2E+0 1.3E-3 2.0E+0 82 170, 172, 223, 382, 407, 488 Arthropod - detritivorous 9.6E-2 7.5E-2 7.6E-2 2.0E+0 2.0E-2 2.2E-1 29 170, 172, 223, 488 Bird 3.2E-2 1.6E-2 2.8E-2 1.6E+0 1.9E-2 3.8E-2 3 486 Grasses and herbs 1.0E-1 2.9E-1 3.4E-2 4.4E+0 3.6E-3 3.0E-1 65 177, 250, 486 Grasses 1.0E-1 2.9E-1 3.5E-2 4.4E+0 3.6E-3 3.0E-1 63 177, 250, 486 Lichens and bryophytes 1.2E+0 1.7E+0 6.9E-1 2.9E+0 2.0E-1 3.2E+0 3 382, 486 Mammal 3.2E-2 1.0E-1 9.8E-3 4.7E+0 2.6E-4 1.7E-1 139 172, 184, 197, 221, 245, 407, 488 Mammal - Herbivorous 5.4E-2 2.0E-1 1.4E-2 5.2E+0 2.6E-4 1.7E-1 27 184, 407, 488 Mammal - Omnivorous 3.0E-2 5.4E-2 1.5E-2 3.3E+0 3.7E-4 4.5E-2 84 221, 245, 488 Mammal - Rangifer spp.+ 2.0E-1 2.4E-1 1.3E-1 2.6E+0 1.6E-1 2.2E-1 9 197 Gastropod 1.4E-1 1.4E-1 1.0E-1 2.2E+0 5.1E-2 2.0E-1 13 486, 488 Reptile - carnivorousa 6.4E-2 3.9E-2 5.5E-2 1.8E+0 1.0E-3 8.6E-2 16 407, 486

TABLE 4.1 1 CONCENTRATION RATIO (CRwo-soil) VALUES FOR WILDLIFE GROUPS IN TERRESTRIAL ECOSYSTEMS

ICRP RAPs

RAP Family Bee Apidea Brown Seaweed Fucaceae Crab Cancridae Deer Cervidae Duck Anatidae Earthworm Lumbricidae Flatfish Pleuronectidae Frog Ranidae Pine Tree Pinaceae Rat Muridae Trout Salmonidae Wild Grass Poaceae 12 RAPs 39 elements

ICRP Transfer compilation

Data gaps

Human foodchain

• Animal products

Element Beef Sheep meat Goat meat Pork Poultry Egg Cow milk Goat milk Sheep milk Ag 1 Am 1 1 1 1 2 Ba 2 1 2 1 15 3 1 Be 1 Ca 3 2 1 15 12 St Cd 8 1 2 8 1 1 Ce 1 1 6 1 Cl 1 Co 4 2 2 2 4 1 2 Cr 3 2 1 Cs 58 41 11 22 13 11 288 28 28 Fe 4 1 2 7 St St I 5 1 2 3 4 104 24 7 La 3 Mn 2 1 1 2 3 4 St 1 Mo 1 1 3 7 4 Na 2 1 1 2 7 St 1 Nb 1 1 1 1 1 1 Ni 2 2 1 Np 1 P 1 1 1 St St St Pb 5 2 15 St 1 1 4 2 Pu 5 2 2 n/a 1 Ra 1 11 Ru 3 2 1 1 6 S 3 1 12 St Sb 2 3 Se 1 4 4 12 2 Sr 35 25 8 12 7 9 154 21 4 Te 1 1 1 1 11 1 1 Th 6 3 U 3 2 2 2 3 1 W 7 Y 1 1 Zn 6 6 2 3 4 8 St St Zr 1 1 1 1 6 1

Wildlife: eg. terrestrial

Radionuclide Grasses & Herbs Shrub Lichens & Bryophytes Annelid Tree Mammal Mollusc Arthopod Bird Reptile Amphibian Arachnid Cs Pb Am Sr Cd Pu Ni U Po Ru Mn Th Cl Co Se Sb Ce Eu I Tc Ag Cm Zr Nb Np P S Te n≤10 n>10<20 n>20<100 n≥100

ICRP RAPs CR values Based on data

Need to fill data gaps?

weighted absorbed dose

• Magnitude of internal dose
• Proportion of internal dose

Evaluated for terrestrial RAPs

• ERICA Tool tier 2
• Defaulting weighting factors (low beta 3; alpha 10)

– ICRP RAP CRwo-soil values – CRwo-soil =1 values

• more CRwo-media values ?
• more mechanistic approach ?

So – an argument for lots more data collection??

0.0E+0 3.0E-4 6.0E-4 9.0E-4 1.2E-3 1.5E-3 Cs-136 Cs-134 Cs-137 Pu-241 Am-241 Cs-135 Pu-238 Pu-239 Pu-240 Sr-89 Sr-90

μGy/h per Bq/kg dw soil

Mammal deer

internal external

0.0E+0 3.0E-4 6.0E-4 9.0E-4 1.2E-3 1.5E-3

Th-231 Th-234 Th-228 Co-60 Co-58 Ra-228 Cs-136 Cs-134 Th-227 Cs-137 Co-57 U-235 Am-241 Pb-210 Ra-226 Th-230 Th-232 U-234 U-238 Pu-241 Cs-135 Po-210 Pu-238 Pu-239 Pu-240 Sr-89 Sr-90

μGy/h per Bq/kg dw soil

Mammal rat

internal external

6.5E-3

0.0E+0 6.0E-4 1.2E-3 1.8E-3 2.4E-3 3.0E-3

Nb-95 Nb-94 Eu-152 Eu-154 Mn-54 Sb-124 Ce-141 Sb-125 Cs-136 Cs-134 Ce-144 Cs-137 I-132 I-131 I-133 Se-75 Zn-65 I-125 I-129 Ni-59 U-235 Sr-89 Cd-109 Pb-210 Cl-36 Am-241 Cs-135 Ni-63 Po-210 Se-79 Sr-90 U-234 U-238

μGy/h per Bq/kg dw soil

Earthworm internal

3.5E-2

Outcome:

• Big variation in importance of internal compared

with external exposure

• direct comparison of internal dose estimates for

RAPs limited by

• small number of CRwo-soil values
• few data for many CRwo-soil values
• so difficult to identify RAP CRwo-soil values as low or

high priority for further data collection.

• eg. the relatively high internal 241Am dose in

Earthworm partially due to a high CRwo-soil value with n=1

ASSUME CRWO-SOIL =1

• used to conservatively assess the relative

importance of internal dose

• Assumed occupancy factors which minimized

external dose

• Not always conservative

– so some element-RAP combinations excluded

But no data for many combinations

Low priority ?

Terrestrial RAP Criteria for exclusion assuming CRwo-soil=1 internal weighted absorbed dose <30% of total internal weighted absorbed dose rate < 1E-4 µGy h-1 per Bq/kg dw soil Deer none Ca-45, Cr-51, I-125, I-129, Ni-59, Ni-63, Pu-241, Se-79, Tc-99 Rat none Ca-45, Cr-51, Co-57, Co-58, I-125, I-129, Mn-54, Nb-95, Ni-59, Ni-63, Ru-103, Sb-125, Se-75, Se-79, Tc-99, Zn-65 Duck none Ca-45, Cd-109, Cr-51, Cs-135, I-125, I-129, Mn-54, Nb-95, Ni-59, Ni-63, Pu-241, Se-75, Se-79, Tc-99, Zn-65 Pine tree none Ca-45, Cr-51, Co-57, I-125, I -129, Ni-59, Ni-63, Pu-241, Se-79, Tc-99 Frog Co-58, Mn-54, Zn-65 Ca-45, Cd-109, Co-57, Co-58, Cr-51, Eu-152, I-125, I-129, Mn-54, Nb-95, Ni-59, Ni-63, Pu-241, Ru-103, Sb- 125, Se-75 Se-79, Tc-99, Zn-65, Zr-95 Wild grass Co-58, Co-60, Mn-54,Nb-95 Ca-45, Ce-141, Co-57, Co-58, Co-60, Cr-51, Eu-152, I-125, I-129, Mn-54, Nb-95, Ni-59, Ni-63, Pu-241, Ru-103, Zr-95 Bee Ag-110m, Co-58, Co-60, Cs-136, Mn-54, Nb-95, Se-75 Ag-110m, Ca-45, Ce-141, Co-57, Co- 58, Co-60, Cr-51, Cs-134, Cs-135, Cs-136, Eu-152, I-125, I-129, Mn- 54, Nb-95, Ni-59, Ni-63, Pu-241, Ru- 103, Sb-125, Se-75, Se-79, Tc -99, Zr- 95 Earthworm Ag-110m, Co-58, Co-60, Cs-136, , Eu-152, I-132, La-140, Mn-54, Nb- 95, Nb-94, Sb-124, Zr -95 Ag-110m, Ca-45, Ce-141, Co-57, Co-58, Co-60, Cr-51,Cs-135, Eu-152, I-125, I-129, Mn-54, Nb-95, Ni-59, Ni-63, Pu-241, Ru-103, Sb-125, Tc- 99, Zr-95

contribution

• f internal

dose to the total dose rate <30%. internal dose rate is below 1E-4 µGy h-1

high priority ? eg

High internal dose - > 80% of the total when CR=1 Internal rates >1E-4 µGy h-1

Terrestrial RAP CRwo-soil=1, internal exposure >80% of total weighted absorbed dose CRwo-soil =1, internal weighted absorbed dose rate > 1E-4 µGy h-1 per Bq kg-1 soil dw Earthworm Am-241, Cd-109, Ce-141, Cf- 252, Cl-36, Cm-242-243-244, I- 125, Np-237, Ru-106, Pa-231, Pb-210, Po-210, Pu-238-239- 240, Ra-226, Se-79, Te-129m Am-241, Ba-140, Ce-144, Cf- 252, Cl-36, Cm-24-243 -244, Cs-134-137, Eu-154, I-131, Ir- 192, La-140, Nb-94, Np-237, Pa-231, Pb-210, Po-210, Pu- 238-239-240, Ra-226-228, Ru- 106, Sb-124, Sr-89-90, Te- 129m-132, Th-227-228-230- 231- 232-234, U-234-235-238

For radionuclide/organism combinations :

• we can provisionally, on the basis of % internal

dose or (relative) dose rates,

– identify those which no longer need to be considered – identify high priority combinations

• identify those for which more mechanistic data

are justified

• Criteria for evaluation are arbitrary can be

changed

Application

• Identification and prioritization of key

radionuclides which justify process based approach

• To enable (eg)
• Spatial and temporal predictions of foodchain

contamination

• Identification radioecological sensitivity
• Optimisation of soil based remedial actions

Focusing of limited resources

Who?

• Modellers
• Experimentalists
• Those carrying out assessments for humans

and wildlife

• Innovators!