Jordi Vives i Batlle Centre for Ecology and Hydrology, Lancaster, 1 st – 3 rd April 2014 Radiation dosimetry for animals and plants

 Key concepts  Radioactivity, 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 Lecture plan

Introduction

Role of dosimetry in assessment

ERICA exposure scenarios  Plant geometry: is it a root or is it a stem?  Height above ground for grass & herbs - cm to m

Key concepts

Atoms and atomic structure  Atoms are the smallest quantities of an element that preserve all of its chemical properties.  Essential components of all atoms:  Proton (m = 1 unit, charge = +1 unit)  Neutron (m = 1 unit, charge = 0)  Electron (m = 5.48 × units, charge = -1 units)  Mass unit: 1.67 x kg - Charge: =1.6 × C  Electrons surround the nucleus, equal in number to the protons (atomic number Z).  Atoms have a small positively charged nucleus comprised of protons (Z) plus neutrons (N)

Radioactive decay  Spontaneous process by which an atomic nucleus of an unstable atom loses energy by emitting ionizing particles (ionizing radiation).  Activity is the rate at which its atoms are undergoing transformation (rate at which individual emissions of radiation occur).  Expressed in units of Becquerels (Bq) where one Becquerel equates to one atom transformation per second.

Henri A. Becquerel (1896) - radiation from U salts expose film. Marie Curie (ca 1898) - radiation from thorium, polonium, radium – 2 Nobel prizes! Ernest Rutherford (ca 1903) - alpha radiation as helium nuclei. The great discoverers

Time   Activity            Radioactive decay occurs as a statistical exponential rate process. The number of atoms likely to decay (dN/dt) is proportional to the number (N) of atoms present. The proportionality constant, l, is the decay constant. Half-life = 0.693/ Law of radioactive decay

 α rays - most massive, positive charge (helium nuclei)   rays - negative charge, same as electron, arise from weak interaction   rays - no electric charge, quanta of electromagnetic radiation Radioactive isotopes found in nature emit three types of radiation: All three types can excite and ionise atoms. Marie Curie’s apparatus shows deflection of  rays from Ra Different types of radiation

 Biological effects result directly from energy loss as radiation passes through tissue.  Formation of ions and free radicals (radiolysis). Damage effect at sub-cellular level. Reaction with chromosomes and damage to DNA strands. Biological effects of radiation

 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 an approximate upper limit to dose  Different when calculating dose to a volume smaller than the range of secondary electrons generated Kerma and absorbed dose

 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 how 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 Units and their significan ce

 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) Radiation weighting factor

 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 conservative assumptions:  Infinitely large organism (internal exposure)  Infinitely small organism (external exposure) Absorbed fraction (AF)

 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  Where A = activity concentration, E = energy and AF(E) = absorbed fraction  Constant k adjusted to give dose units of  Gy h -1  Concentration in organisms as a function of time, c(t), is concentration in the medium times a transfer function:  A org =A medium  c(t)  In equilibrium, the transfer function is known as the ‘concentration ratio”, CR Dose conversion coefficient

 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 Strategy for dose calculation

Calculation of AFs: the ERICA approach

 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 Reference habitats & organisms

 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 Reference organism shapes

Image from N. Semioschkina, Germany So The world looks like this…

 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 approach

 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 Problems and limitations

ElectronsPhotons Spherical AFs v. mass & energy For alpha and beta <10 keV the absorbed fraction is ~1

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

 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).  The absorbed fraction for the non-spherical body is the absorbed fraction of the “equivalent sphere” multiplied by a re-scaling factor. Non-spherical bodies

Calculation of DCCs: ERICA database

 For a radionuclide with various ,  or  decay transitions we make the following groupings having the same radiation weighting factor:  Low energy  (energy 10 keV) +  ; and   Then for each category we sum all transitions (represented by sub-index i) of probability p i :  The total DCC is: Internal DCC formulas

 It’s nearly the same except we replace AF by 1 - AF:  The total DCC is: External DCC formulas

 Occupancy factor :  External exposure :  Internal exposure : Calculation of dose rates

 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 and 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 DCCs versus size and energy

 Data from Vives i Batlle et al. (2004)  Data shows smooth dependency of DCC with area/volume DCC correlation with size

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) External DCCs for soil organisms

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

Comparing ERICA with other tools

 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 Intercomparison analysis

 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) Internal dosimetry comparison

 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”) External dosimetry comparison

Special cases outside the ERICA approach

 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 Approach for gases

Inhomogeneous distributions  Only a few nuclides homogeneously distributed: 3 H, 14 C, 40 K, 137 Cs  Many concentrate in specific organs e.g. Green gland ( 99 Tc), Thyroid ( 129,131 I), Bone ( 90 Sr, 226 Ra), Liver ( 239 Pu), Kidney ( 238 U)  Data from Gómez-Ros et al. (2009) Shows moderate influence in organ position within ellipsoid for various animals

 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) Argon and krypton

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

 Each sub-model contains the decay chain of radon: 222 Rn  218 Po  214 Pb  214 Bi  214 Po  Incorporates internal, surface and external dose ICRP radon model for plants

 ERICA makes many assumptions and simplifications  Geometry greatly simplified by using ellipsoids  Homogeneous distribution in uniformly contaminated medium - organs not considered (some tests done)  Only a few organisms with simple geometry can be defined  Size interpolation works only within predefined mass ranges:  to 550 kg for animals above ground  to 6.6 kg for animals in soil  to 2 kg for birds  1E-06 to 1000 kg for aquatic organisms  Otherwise use Table 10 in ERICA help file to estimate the uncertainty Summary – ERICA key features

 There are some things ERICA cannot do  Limitations on which reference organisms appear under which ecosystems e.g. cannot calculate DCC for marine bird in air  Do conservative run for bird on water or sediment  Plant geometries in ERICA are unrealistic - root versus stem. Variable height above ground for grasses.  They do not really represent whole-organisms  The grass geometry is taken from the ICRP Wild Grass RAP - no ‘in soil’ dose rates are estimated, but only dose above ground.  If you are concerned create an organism to represent your plant (e.g. leaf) and compare DCC values to the default grass.  Gaseous radionuclides are beyond the scope of the tool and require specialised models Summary – what ERICA can’t do

References  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 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.  Vives i Batlle, J., Barnett, C.L., Beaugelin-Seiller, K., Beresford, N.A., Copplestone, D., Horyna, J., Hosseini, A., Johansen, M., Kamboj, S., Keum, D-K., Newsome, L., Olyslaegers, G., Vandenhove, H., Vives Lynch, S. and Wood, M. (2011) Absorbed dose conversion coefficients for non-human biota: an extended inter-comparison of data. Radiation and Environmental Biophysics 50(2):