Jordi Vives i Batlle Centre for Ecology and Hydrology, Lancaster, 27 April 2010

 Key concepts  Kerma, absorbed dose, units, radiation weighting factor, absorbed fraction, dose conversion coefficient (DCC)  ERICA approach to absorbed fraction calculation  Reference habitats, organisms and shapes, Monte Carlo approach, sphericity, dependence with energy / size  ERICA DCCs for internal and external exposure  Internal and external DCC formulae, energy / size dependency, allometric scaling  Comparing ERICA with other tools  Special cases  Gases, inhomogeneous sources, non-equilibrium

 Kerma: sum of the initial kinetic energies of all the charged particles transferred to a target by non-charged ionising radiation, per unit mass  Absorbed dose: total energy deposited in a target by ionising radiation, including secondary electrons, per unit mass  Similar at low energy - Kerma am approximate upper limit to dose  Different when calculating dose to a volume smaller than the range of secondary electrons generated

 Units of absorbed dose (Grays) = Energy deposited (J kg -1 )  Only small amounts of deposited energy from ionising radiation are required to produce biological harm - because of the means by which energy is deposited (ionisation and free radical formation)  For example - drinking a cup of hot coffee transfers about 700 Joules of heat energy per kg to the body.  To transfer the same amount of energy from ionising radiation would involve a dose of 700 Gy - but doses in the order of 1 Gy are fatal  I Gy = 1 J kg -1 = keV ~ alphas

 Need to make allowance of such factors as LET or RBE in the description of absorbed dose  Equivalent dose = absorbed dose  radiation weighting factor (w r )  Units of equivalent dose are Sieverts (Sv)  No firm consensus - suggested values for w r :  1 for  and high energy (> 10keV)  radiation  3 for low energy (  10keV)  radiation  10 for  (non stochastic effects in the species) vs. 20 for humans (to cover stochastic effects of radiation i.e. cancer in an individual)

 Fraction of energy E emitted by a source absorbed within the target tissue / organism  Internal and external exposures of an organism in a homogeneous medium:  D int = k  A org (Bq kg -1 )  E (MeV)  AF(E)  D ext = k  A medium (Bq kg -1 )  E  [1-AF(E)]  k = 5.76   Gy h -1 per MeV Bq kg -1  If the radiation is not mono-energetic, then the above need to be summed over all the decay energies (spectrum) of the radionuclide  Some models make simplifying assumptions:  Infinitely large organism (internal exposure)  Infinitely small organism (external exposure)

 Defined as the ratio of dose rate per unit concentration in organism or the medium:  D int = k A org E AF(E) = DCC int  A org  D ext = k A medium E[1-AF(E)] = DCC ext  A medium  Units of  Gy h -1 per Bq kg -1  Concentration in organisms is concentration in the medium times a transfer function:  A org =A medium   (t)  In equilibrium, the transfer function is known as the “transfer factor”, TF

 The dose is the result of a complex interaction of energy, mass and the source - target geometry:  Define organism mass and shape  Consider exposure conditions (internal, external)  Simulate radiation transport for mono-energetic photons and electrons: absorbed fractions  Link calculations with nuclide-specific decay characteristics: Dose conversion coefficients  Only a few organisms with simple geometry can be simulated explicitly  In all other cases interpolation gives good accuracy

 The enormous variability of biota requires the definition of reference organisms that represent:  Plants and animals  Different mass ranges  Different habitats  Exposure conditions are defined for different habitats:  In soil/on soil  In water/on water  In sediment/interface water sediment

 Organism shapes approximated by ellipsoids, spheres or cylinders of stated dimensions  Homogeneous distribution of radionuclides within the organism: organs are not considered  Oganism immersed in uniformly contaminated medium  Dose rate averaged over organism volume

 Monte Carlo simulations of photon and electron transport through matter (ERICA uses MCNP code)  Includes all processes: photoelectric absorption, Compton scattering, pair creation, fluorescence

 Monte Carlo calculations are very time-consuming :  Long range of high-energy photons in air, a large area around the organism has to be considered  A large contaminated area has to be considered as source  Small targets get only relatively few hits  Probability ~ 1/source-target distance 2  Simulations require high number of photon tracks  Therefore, a two-step method has been developed :  KERMA calculated in air from different sources on or in soil  Dose to organism / dose in air ratio calculated for the different organisms and energies

ElectronsPhotons

 Represented by ellipsoidal shapes having the same mass as the spherical ones  AFs always less than those for spheres of equal mass.  Non-sphericity parameter:  = surface area of sphere of equal mass (S0) / surface area (S)  Derive re-scaling factors RF using the formula:  RF(  ) can be approximated by a single-parameter curve:  RF(  ) = 1 for large masses and low energies, and  for very small masses and high energies.  Ulanovsky and Pröhl (2006)

Absorbed fractions for electrons in different terrestrial organisms (Brown et al., 2003)

 For each radionuclide and reference organism energies and yields of all ,  and  emissions are extracted from ICRP(1983) and overall  and  AF's calculated as: where E i is energy (MeV) and p i denotes the fractional yield of individual emissions  For each radionuclide and reference organism energies and yields of all ,  and  emissions are extracted from ICRP(1983) and overall  and  AF's calculated as: where E i is energy (MeV) and p i denotes the fractional yield of individual emissions

 Occupancy factor :  External exposure :  Internal exposure :

DCCs for earthworm at various soil depths for monoenergetic photons. Assumes uniformly contaminated upper 50 cm of soil DCCs for various soil organisms at a depth of 25 cm in soil for monoenergetic photons. Assumes uniformly contaminated upper 50 cm of soil (density: 1600 kg/m³)

DCCs for mono-energetic photons for soil organisms as a function of photon energy (Brown et al., 2003)

 External DCCs decrease with size due to the increasing self-shielding, especially for low energy g-emitters  Small organism DCCs from high-energy photons higher for underground organisms, & vice versa for larger organisms  External exposure to low-energy  emitters is higher for organisms above ground, due to lack of shielding by soil  DCCs for internal exposure to  -emitters (esp. high- energy) increase with mass due to the higher absorbed fractions  For  and  -emitters, the DCCs for internal exposure are virtually size-independent

 Vives i Batlle et al. (2004)

 International comparison of 7 models performed under the EMRAS project: EDEN, EA R&D 128, ERICA, DosDimEco, EPIC-DOSES3D, RESRAD- BIOTA, SÚJB  5 ERICA runs by different users: default DCCs, ICRP, SCK-CEN, ANSTO, K-Biota  67 radionuclides and 5 ICRP RAP geometries  Internal doses: mostly within 25% around mean  External doses: mostly within 10% around mean  There are exceptions e.g.α and soft β-emitters reflecting variability in AF estimations ( 3 H, 14 C…)  ERICA making predictions similar to other models

 Estimate ratio of average (ERICA) to average (rest of models)  Skewed distribution centered at 1.1  Fraction < 0.75 = 40%  Fraction > 1.25 = 3%  Fraction between 0.75 and 1.25 = 57%  Worst offenders (< 0.25): 51 Cr, 55 Fe, 59 Ni, 210 Pb, 228 Ra, 231 Th and 241 Pu  Worst offenders (>1.25): 14 C, 228 Th  Conclude reasonably tight fit (most data < 25% off)

 Same ratio method for external dose in water  Two data groups at < 0.02 and ~ 1.32  Fraction < 0.5 = 37%  Fraction > 1.5 = 13%  Fraction between 0.5 and 1.5 =50 %  Worst offenders (< 0.02): 3 H, 33 P, 35 S, 36 Cl, 45 Ca, 55 Fe, 59,63 Ni, 79 Se, 135 Cs, 210 Po, 230 Th, 234,238 U, 238,239,241 Pu, 242 Cm  Worst offenders (>1.25): 32 P, 54 Mn, 58 Co, 94,95 Nb, 99 Tc, 124 Sb, 134,136 Cs, 140 Ba, 140 La, 152,154 Eu, 226 Ra, 228 Th  Still acceptable fit (main data < 50% “off”)

 The following formulae can be used for radionuclides whose concentration is referenced to air: 3 H, 14 C, 32 P, 35 S, 41 Ar and 85 Kr

TadpoleEarthwormFrog Rat CrabDuck TroutFlatfishDeer Distributed source Central point Eccentric point Data from Gómez-Ros et al. (2009)

Central point TadpoleEarthwormFrog Rat CrabDuck TroutFlatfishDeer Distributed source Eccentric point Data from Gómez-Ros et al. (2009)

 Internal dose negligible: Ar and Kr CFs set to 0  No deposition but some migration into soil pores  Assume pore air is at the same concentration as ground level air concentrations  assume a free air space of 15%, density = 1500 kg m -3, so free air space = m 3 kg -1 & Bq m -3 (air) * = Bq kg -1 (wet)  Hence, a TF of for air (Bq m -3 ) to soil (Bq kg -1 wet)  For plants and fungi occupancy factors set to 1.0 soil, 0.5 air (instead of 0)  Biota in the subsurface soil and are exposed only to 41 Ar and 85 Kr in the air pore spaces  External DCCs for fungi are those calculated for bacteria (i.e. infinite medium DCCs)

- i N L RR+h Conceptual representation of irradiated respiratory tissue Simple respiratory model for 222 Rn daughters  At equilibrium:

 Use CO 2 as analogue entering plant, while water and O 2 exit through the stomata  A full process dose model representing gas exchange through plant stomata is the next logical developmental step  Assume whole plant exchanges gases

TB: Full tracheobronchial epithelium; L: Full lung; WB: Whole body; S TB RM and S B RM : Area of tracheobronchial tree or bronchial epithelium; a: Axis of cylinder representing the plant; R wf  :Weighting factor  Animal dose factors (  Gy h -1 per Bq m -3 ):  Plant dose factors:

 Each sub-model contains the decay chain of radon: 222 Rn  218 Po  214 Pb  214 Bi  214 Po

 Organisms can retain activity for a long time after it has been dispersed from an environment.  Requires assessment tools based on a dynamic approach  Time-dependent dose rates can be integrated over period following the intake of radioactivity (lifetime)

 Brown J., Gomez-Ros J.-M., Jones, S.R., Pröhl, G., Taranenko, V., Thørring, H., Vives i Batlle, J. and Woodhead, D, (2003) Dosimetric models and data for assessing radiation exposures to biota. FASSET (Framework for Assessment of Environmental Impact) Deliverable 3 Report under Contract No FIGE-CT , G. Pröhl (Ed.).  Gómez-Ros, J.M., Pröhl, G., Ulanovsky, A. and Lis, M. (2008). Uncertainties of internal dose assessment for animals and plants due to non- homogeneously distributed radionuclides. Journal of Environmental Radioactivity 99(9):  Ulanovsky, A. and Pröhl, G. (2006) A practical method for assessment of dose conversion coefficients for aquatic biota. Radiation and Environmental Biophysics 45:  Vives i Batlle, J., Jones, S.R. and Gómez-Ros, J.M. (2004) A method for calculation of dose per unit concentration values for aquatic biota. Journal of Radiological Protection 24(4A): A13-A34.  Vives i Batlle, J., Jones, S.R. and Copplestone, D. (2008) Dosimetric Model for Biota Exposure to Inhaled Radon Daughters. Environment Agency Science Report – SC060080, 34 pp.