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Presentation on theme: "  Dispersion models available in the ERICA Tool  Other types of dispersion models that are available  Key parameters that drive."— Presentation transcript:


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))

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


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

6  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 a) H > 2.5H B (no building effects) b) H  2.5H B & x > 2.5A B ½ (airflow in the wake zone) c) H  2.5H B & x  2.5A B ½ (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 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

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

11  Model assumes constant meteorological and topographical conditions along plume trajectory  Prediction accuracy 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

12  Freshwater  Small lake (< 400 km 2 )  Large lake (≥400 km 2 )  Estuarine  River  Marine  Coastal  Estuarine  No model for open ocean waters

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 K d 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

14  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. If x on the same bank side and  Lz = 7D the radionuclide Condition for mixing is (y-y 0 )<<3.7x concentration in water is assumed to be undiluted L z = distance to achieve full vertical mixing K d = 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

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  Assumes equilibrium e.g. water/sediment K d


18  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

19 Compartmental - marine model (continuous discharge) Radial grid - atmospheric model

20  Marine model (DORIS) => improvement  Has long-range geographical resolution - allows for offshore scenarios e.g. marine platform discharges  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



23  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)

24  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.

25 Finite differences Compartmental

26  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

27  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

28  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

29 2 km grid  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

30 Residual flow field (12 month MIKE21 simulation / averaged wind conditions) Bathymetry for MEAD grid: resolution 2 km - 2 km

31 Distribution of fine grained bed sediment Distribution of suspended particles (modelled)

32 60 Co in winkles 137 Cs in cod / plaice 99 Tc in crab 241 Am in mussels Could be used to derive CFs for use in ERICA

33 Predicted distribution of 137 Cs in seawater in 2000 Predicted distribution of 137 Cs in bed sediments in 2000

34  Extra modules in MIKE21  More complex water quality issues e.g. eutrophication  Wave interactions  Coastal morphology  Particle and slick tracking analysis  Sediment dynamics  ModelMaker biokinetic models  Dynamic interactions with sediment  Speciation  Dynamic uptake in biota


36  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)

37  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)

38  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)

39  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


41  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

42  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

43  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



46  Convert rainfall over the catchment to river flow out the catchment  Represent the processes illustrated, however in two possible ways:  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

47  Integrated groundwater - surface water solution  Advanced rainfall runoff model with extensive process representation  Intense parameter demand  One of the more widely used models  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 , CRC Press. ISBN:

48  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


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