MODARIA Working Group 4

Transcription

1 MODARIA 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

2 IAEA Parameter value compilations

3 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

4 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

5 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?

6 Variation in transfer coefficient and CR values AMean: 6.1 x10-3, SD: 6.3 x10-3, n: 288, Median: 4.6 x 10-3, Kurtosis: 43.4, p-value: 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: IAEA 2010 TRS 472

7 Deriving parameter values For a screening assessment False positives Increased costs Assessment Look for data Time, resources, access Compile data and find gaps QC procedures Data quality and quantity Increased conservatism Decreased transparency Fill gaps Look again, find derived values Rejected sources, Untraceable data. Inappropriate data, Untested analogues, Rarely new data

8 ... simplification: Most approaches use concentration ratios (CR) -1 CR Activity concentration in biota whole body (Bq kg fresh weight) Activity concentration media (filtered water (Bq l ),soil (Bq kg dry weight) or air (Bq m 3 ))

9 IAEA wildlife TRS status Submitted early 2011 (publication pending ) CR wo-media values given Generic Freshwater, Marine, Terrestrial and Brackish water ecosystems Summarises CR wo-media data for >800 wildlifeelement combinations Values from the initial submitted text available from:

10 TRS transfer to wildlife TRS paper in press Online database Numerous associated papers from EMRAS I and II IAEA outputs

11 TABLE CONCENTRATION RATIO (CR wo-soil ) VALUES FOR WILDLIFE GROUPS IN TERRESTRIAL ECOSYSTEMS 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 , 212 Lichens and bryophytes 3.0E-2 3.4E-2 2.0E-2 2.5E+0 1.2E-2 1.3E Shrub 2.1E-2 9.1E-3 1.9E-2 1.5E+0 1.2E-2 3.3E Al (Aluminium) Lichens and bryophytes 1.1E-1 1.1E-1 7.1E-2 2.4E+0 1.0E-2 4.2E , 355 Shrub 1.9E-2 1.8E-2 1.4E-2 2.2E+0 2.9E-3 1.2E , 348 Am (Americium) Amphibian 1.3E-1 3.4E-2 1.3E-1 1.3E+0 1.0E-1 1.5E Annelid 1.8E-1 3.0E-1 9.0E-2 3.2E+0 5.2E-2 1.1E , 486, 488 Arachnid 5.7E-2 6.2E-2 3.8E-2 2.4E+0 2.2E-2 1.3E , 488 Arthropod 1.1E-1 2.9E-1 4.0E-2 4.2E+0 1.3E-3 2.0E , 172, 223, 382, 407, 488 Arthropod - detritivorous 9.6E-2 7.5E-2 7.6E-2 2.0E+0 2.0E-2 2.2E , 172, 223, 488 Bird 3.2E-2 1.6E-2 2.8E-2 1.6E+0 1.9E-2 3.8E Grasses and herbs 1.0E-1 2.9E-1 3.4E-2 4.4E+0 3.6E-3 3.0E , 250, 486 Grasses 1.0E-1 2.9E-1 3.5E-2 4.4E+0 3.6E-3 3.0E , 250, 486 Lichens and bryophytes 1.2E+0 1.7E+0 6.9E-1 2.9E+0 2.0E-1 3.2E , 486 Mammal 3.2E-2 1.0E-1 9.8E-3 4.7E+0 2.6E-4 1.7E , 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 , 407, 488 Mammal - Omnivorous 3.0E-2 5.4E-2 1.5E-2 3.3E+0 3.7E-4 4.5E , 245, 488 Mammal - Rangifer spp E-1 2.4E-1 1.3E-1 2.6E+0 1.6E-1 2.2E Gastropod 1.4E-1 1.4E-1 1.0E-1 2.2E+0 5.1E-2 2.0E , 488 Reptile - carnivorous a 6.4E-2 3.9E-2 5.5E-2 1.8E+0 1.0E-3 8.6E , 486

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

13 ICRP Transfer compilation

14 Data gaps

15 Animal products Element Human foodchain Beef Sheep meat Ag 1 Goat meat Pork Poultry Egg Cow milk Goat milk Sheep milk Am Ba Be 1 Ca St Cd Ce Cl 1 Co Cr Cs Fe St St I La 3 Mn St 1 Mo Na St 1 Nb Ni Np 1 P St St St Pb St Pu n/a 1 Ra 1 11 Ru S St Sb 2 3 Se Sr Te Th 6 3 U W 7 Y 1 1 Zn St St Zr

16 Wildlife: eg. terrestrial Radionuclide 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 Grasses & Herbs Shrub Lichens & Bryophytes Annelid Tree Mammal Mollusc Arthopod Bird Reptile Amphibian Arachnid n 10 n>10<20 n>20<100 n 100

17 ICRP RAPs CR values Based on data

18 Need to fill data gaps? So an argument for lots more data collection?? more CR wo-media values? more mechanistic approach? 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 CR wo-soil values CR wo-soil =1 values

19 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 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 1.5E-3 1.2E-3 9.0E-4 Mammal deer internal external 6.0E-4 3.0E-4 1.5E-3 1.2E-3 Mammal rat internal external 0.0E+0 6.5E-3 9.0E-4 6.0E-4 3.0E-4 0.0E+0

20 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 3.0E-3 2.4E-3 internal Earthworm 3.5E-2 1.8E-3 1.2E-3 6.0E-4 0.0E+0

21 Outcome: Big variation in importance of internal compared with external exposure direct comparison of internal dose estimates for RAPs limited by o small number of CR wo-soil values o few data for many CR wo-soil values so difficult to identify RAP CR wo-soil values as low or high priority for further data collection. eg. the relatively high internal 241 Am dose in Earthworm partially due to a high CR wo-soil value with n=1

22 But no data for many combinations ASSUME CR WO-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

23 Low priority? contribution of internal dose to the total dose rate <30%. Terrestrial RAP Criteria for exclusion assuming CR wo-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 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-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 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 internal dose rate is below 1E-4 µgy h -1

24 high priority? eg High internal dose - > 80% of the total when CR=1 Internal rates >1E-4 µgy h -1 Terrestrial RAP CR wo-soil =1, internal exposure >80% of total weighted absorbed dose Earthworm Am-241, Cd-109, Ce-141, Cf- 252, Cl-36, Cm , I- 125, Np-237, Ru-106, Pa-231, Pb-210, Po-210, Pu , Ra-226, Se-79, Te-129m CR wo-soil =1, internal weighted absorbed dose rate > 1E-4 µgy h -1 per Bq kg -1 soil dw Am-241, Ba-140, Ce-144, Cf- 252, Cl-36, Cm , Cs , Eu-154, I-131, Ir- 192, La-140, Nb-94, Np-237, Pa-231, Pb-210, Po-210, Pu , Ra , Ru- 106, Sb-124, Sr-89-90, Te- 129m-132, Th , U

25 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

26 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

27 Who? Modellers Experimentalists Those carrying out assessments for humans and wildlife Innovators!