Modelling the environmental dispersion of radionuclides

1. Modelling the environmental dispersion of radionuclides Jordi Vives i BatlleCentre for Ecology and Hydrology, Lancaster, 26th November 2010

2. Dispersion models available in the ERICA Tool Other types of dispersion models that are available Key parameters that drive dispersion models for radioactivity in the environment Applicability to different scenarios/circumstances (e.g. release directly to a protected site/end of pipe concentrations (e.g. mixing zones)) Lecture plan

3. Often the receptor is not at a point of emission but is linked via an environmental pathway (dilution) Need to predict media concentrations when (adequate) data are not available What reasons to use models? • To conduct authorisation-based assessments for the protection and conservation of species listed under the EC Birds and Habitats Directives

4. Part I - Dispersion modelling in ERICA

5. Designed to minimise under-prediction (conservative generic assessment) A default discharge period of 30 y is assumed (estimates doses for the 30th year of discharge) IAEA SRS Publication 19

6. Atmospheric dispersion Gaussian plume model version depending on the relationship between building height, HB & cross-sectional area of the building influencing flow, AB Assumes a predominant wind direction and neutral stability class Key inputs: discharge rate Q & location of source / receptor points (H, HB, AB and x)

7. Conditions for the plume a) H > 2.5HB (no building effects) b) H 2.5HB & x > 2.5AB½(airflow in the wake zone) c) H  2.5HB & x  2.5AB½(airflow in the cavity zone). Two cases: source / receptor at same building surface not at same surface (a) (b) (c) Not generally applicable at x > 20 km

8. Basic dispersion equation Importance of Release Height

9. Wind speed and direction 10 minute average from 10 m wind vane & anemometer Release height Precipitation 10 minute total rainfall (mm) from tipping bucket Stability or degree of turbulence (horizontal and vertical diffusion) Manual estimate from nomogram using time of day, amount of cloud cover and global radiation level Atmospheric boundary layer (time-dependent) Convective and or mechanical turbulence Limits the vertical transport of pollutants Key parameters

10. Based on the recommendations of the Working Group on Atmospheric Dispersion (NRPB-R91, -R122, -R123, -R124) Gaussian plume model Meteorological conditions specified by: Wind speed Wind direction Pasquill-Gifford stability classification Implemented in PC CREAM R91 aerial dispersion model

11. Model assumes constant meteorological and topographical conditions along plume trajectory Prediction accuracy < 100 m and > 30 km limited Source depletion unrealistic (deposition modelling & transfer factors are uncertain) Developed for neutral conditions Does not include Buildings Complex terrain e.g. hills and valleys Coastal effects R91 - model limitations

12. Freshwater Small lake (< 400 km2) Large lake (≥400 km2) Estuarine River Marine Coastal Estuarine No model for open ocean waters Surface water dispersion

13. Based on analytic solution of the advection diffusion equation describing transport in surface water for uniform flow conditions at steady state Processes included: Flow downstream as transport (advection) Mixing processes (turbulent dispersion) Concentration in sediment / suspended particles estimated from ERICA Kd at receptor (equilibrium) Transportation in the direction of flow No loss to sediment between source and receptor In all cases water dispersion are assumed critical flow conditions, by taking the lowest in 30 years, the rate of current flow The only difference between RNs in predicted water concentrations as material disperses is physical half-life. Processes and assumptions

14. Rivers and coastal waters The river model assumes that both river discharge of radionuclides such as water harvesting is done in some of the banks, not in the midstream The estuary model is considered an average speed of the current representative of the behaviour of the tides. Lz= distance to achieve full vertical mixing If x on the same bank side and  Lz = 7D the radionuclide Condition for mixing is (y-y0)<<3.7x concentration in water is assumed to be undiluted Kd = Activity concentration on sediment (Bq kg-1) Activity concentration in seawater (Bq L-1)

15. Assumes a homogeneous concentration throughout the water body Expected life time of facility is required as input Small lakes and reservoirs

16. Simple environmental and dosimetric models as well as sets of necessary default data: Simplest, linear compartment models Simple screening approach (robust but conservative) Short source-receptor distances More complex / higher tier assessments: Aerial model includes only one wind direction Coastal dispersion model not intended for open waters e.g. oil/gas marine platform discharges Surface water models assume geometry (e.g. river cross-section) & flow characteristics (e.g. velocity, water depth) do not change significantly with distance / time End of pipe mixing zones require hydrodynamic models Assumes equilibrium at assessment location - Kd Limitations of IAEA SRS 19

17. Effects of using these models on dose • Uncertainty associated with the application of aquatic SRS models: • Models generally conservative. • From factor of 2 to 10 difference with respect to a dynamic model. • Uncertainty associated with the application of a Gaussian plume model for continuous releases: • About a factor of 4 or 10 for a flat and complex terrain respectively. • At distances < 2.5 times the square root of the frontal area of the building, the model provides conservative results. • For distances of about 2.5 the above, the model tends to underpredict for wind speeds above 5-m s-1.

18. Part II: PC CREAM as a practical alternative for dispersion modelling

19. Consequences of Releases to the Environment Assessment Methodology A suite of models and data for performing radiological impact assessments of routine and continuous discharges Marine: Compartmental model for European waters (DORIS) Seafood concentrations => Individual doses => Collective doses. Aerial: Radial grid R-91 atmospheric dispersion model with (PLUME) with biokinetic transfer models (FARMLAND) Ext. & internal irradiation => foodchain transfer (animal on pasture e.g. cow & plant uptake models) => dose Collective dose model PC CREAM

20. Marine and aerial dispersion Radial grid - atmospheric model Compartmental - marine model (continuous discharge)

21. Marine model (DORIS) => improvement Has long-range geographical resolution Incorporates dynamic representation of water / sediment interaction Aerial model (PLUME) => no improvement Still a gaussian dispersion model unsuitable for long distances (though it has been used in that way) Also assumes constant meteorological conditions Does not correct for plume filling the boundary layer Must use a better model e.g. Lagrangian particle dispersion - NAME Degree of improvement of the models

22. Part III: Other alternative dispersion models

23. Marine modelling

24. Allow for nonequilibrium situations e.g. acute release into protected site Advantages: Resolves into a large geographical range Results more accurate (if properly calibrated) Disadvantages: Data and CPU-hungry (small time step and grid sizes demand more computer resources) Run time dependent on grid size & time step Requires a more specialised type of user Post-processing required for dose calculation (use as input to ERICA) Geographically-resolving marine models

25. Input requirements: Bathymetry, wind fields, tidal velocities, sediment distributions, source term Type of output: a grid map / table of activity concentration (resolution dependent on grid size) All use same advection/dispersion equations, differences are in grid size and time step Types of model: Compartmental: Give average solutions in compartments connected by fluxes. Good for long-range dispersion in regional seas. Finite differences: Equations discretised and solved over a rectangular mesh grid. Good for short-range dispersion in coastal areas Estuaries a special case: Deal with tides (rather than waves), density gradients, turbidity & c. Model characteristics

26. Model characteristics Finite differences Compartmental

27. Long-range marine models (regional seas): POSEIDON - N. Europe (similar to PC-CREAM model but redefines source term and some compartments - same sediment model based on MARINA) MEAD (in-house model available at WSC) Short-range marine models (coastal areas): MIKE21 - Short time scales (DHI) - also for estuaries Delft 3D model, developed by DELFT TELEMAC (LNH, France) - finite element model COASTOX (RODOS PV6 package) Estuarine models DIVAST ( Dr Roger Proctor) ECoS (PML, UK) - includes bio-uptake Readily available models

28. As seen previously (PC-CREAM section of the lecture) Area of interest divided into large area boxes and transfer at boundaries is dependent on the parameters in the adjacent boxes Contains sediment transport project (MARINA project) Simple, quick, easy to use radionuclide transport model Continuous discharge Time variable discharge Continuous leaching of an immersed solid material Post processing for annual dose to humans is intrinsic, hence only minor coding required for determination of dose to biota POSEIDON

29. Two-dimensional depth averaged model for coastal waters Location defined on a grid - creates solution from previous time step Hydrodynamics solved using full time-dependent non-linear equations (continuity & conservation of momentum) Large, slow and complex when applied to an extensive region Suitable for short term (sub annual) assessments A post processor is required to determine biota concentrations and dose calculations DHI MIKE 21 model

30. Applies advection - dispersion equations over an area and time Generates activity concentration predictions in water and sediment Has been combined with the ERICA methodology to make realistic assessments of impact on biota Marine Environmental Advection Dispersion (MEAD) 2 km grid

31. Bathymetry for MEAD grid: resolution 2 km - 2 km MEAD input data - water Residual flow field (12 month MIKE21 simulation / averaged wind conditions)

32. MEAD input data - sediment Distribution of fine grained bed sediment Distribution of suspended particles (modelled)

33. MEAD output - Cumbrian coast 137Cs in cod / plaice 60Co in winkles 99Tc in crab 241Am in mussels Could be used to derive CFs for use in ERICA

34. MEAD - Long-range results Predicted distribution of 137Cs in seawater in 2000 Predicted distribution of 137Cs in bed sediments in 2000

35. Extra modules in MIKE21 More complex water quality issues e.g. eutrophication Wave interactions Coastal morphology Particle and slick tracking analysis Sediment dynamics More complex process models • ModelMakerbiokineticmodels • Dynamic interactions withsediment • Speciation • Dynamic uptake in biota

36. River and estuary modelling

37. Advantages: Large geographical range Consider multiple dimensions of the problem (1 - 3D) Considers interconnected river networks Results more accurate (if properly calibrated) Disadvantages - same as marine models: Data hungry Run time dependent on grid size & time step Requires a more specialised type of user CPU-hungry (as time step and grid size decreases it demands more computer resources) Post-processing required for dose calculation (use as input to ERICA) River and estuary models

38. Input requirements: Bathymetry, rainfall and catchment data, sediment properties, network mapping, source term Type of output: activity concentration in water and sediment, hydrodynamic data for river All use same advection/dispersion equations as marine but differences in boundary conditions Generally models solve equations to: Give water depth and velocity over the model domain. Calculate dilution of a tracer (activity concentration) Model characteristics

39. Can be 1D, 2D or 3D models 1D river models: River represented by a line in downstream direction - widely used 2D models have some use where extra detail is required 3D models are rarely used unless very detailed process representation is needed Off-the-shelf models: MIKE11 model developed by the DHI, Water and Environment (1D model) VERSE (developed by WSC) MOIRA (Delft Hydraulics) Research models: PRAIRIE (AEA Technology) RIVTOX & LAKECO (RODOS PV6 package) Common models

40. MIKE11 - Industry standard code for river flow simulation River represented by a line in downstream direction River velocity is averaged over the area of flow Cross sections are used to give water depth predictions Can be steady flow (constant flow rate) or unsteady flow Use of cross sections can give an estimate of inundation extent but not flood plain velocity Example - MIKE 11

41. Aerial modelling

42. Advanced models: ADMS, AERMOD Gaussian in stable and neutral conditions Non-Gaussian (skewed) in unstable conditions Continuous turbulence data rather than simplified stability categories to define boundary layer Model includes the effects on dispersion from: Buildings Complex terrain & coastal regions ADMS a good choice New-generation plume models

43. Modified Gaussian plume model Gaussian in stable and neutral conditions Skewed non-Gaussian in unstable conditions Boundary layer based on turbulence parameters Model includes: Meteorological preprocessor, buildings, complex terrain Wet deposition, gravitational settling and dry deposition Short term fluctuations in concentration Chemical reactions Radioactive decay and gamma-dose Condensed plume visibility & plume rise vs. distance Jets and directional releases Short to annual timescales UK ADMS

44. Meteorological data (site specific & Met Office) Wind speed, wind direction, date, time, latitude, boundary layer height, cloud cover Boundary Layer Height Height at which surface effects influence dispersion ADMS calculates boundary layer properties for different heights based on meteorology Monin-Obukhov Length Measure of height at which mechanical turbulence is more significant than convection or stratification ADMS calculates M-O length based on meteorology and ground roughness ADMS input parameters

45. Types of output

46. Terrestrial (biosphere) modelling

47. Convert rainfall over the catchment to river flow out the catchment Represent the processes illustrated, however in two possible ways: Catchment modelling • Simple “black box” type model such as empirical relationship from rainfall to runoff (cannot be used to simulate changing conditions) • Complex physically based models where all processes are explicitly represented

48. Integrated groundwater - surface water solution Advanced rainfall runoff model with extensive process representation Intense parameter demand One of the more widely used models Example model - MIKE SHE • A good choice when the close linkage of surface water and ground water is important to the study Graham, D.N. and M. B. Butts (2005) Flexible, integrated watershed modelling with MIKE SHE. In Watershed Models, Eds. V.P. Singh & D.K. Frevert Pages 245-272, CRC Press. ISBN: 0849336090.

49. ERICA uses the IAEA SRS 19 dispersion models to work out a simple, conservative source - receptor interaction SRS 19 have some shortcomings PC-CREAM can be used as an alternative suite of dispersion models There are further off-the-shelf models performing radiological impact assessments of routine and continuous discharges ranging from simple to complex Key criteria of simplicity of use and number of parameters need to be considered Conclusions

50. Links to alternative models