Dispersion and transfer in the environment

To calculate dispersion and transfer of radioactive isotopes in the environment the meteorological conditions and hydrological data have to be defined. In the ideal situation the calculation of transport of radioactive material in the environment should be performed for all combinations of meteorological parameters which can occur in the site area. Seasonal and daily variations of meteorological conditions may essentially influence the distribution of the released radioactivity in the environment and concentration of radioisotopes in food. Usually the analysis of transport of radioisotopes involves several different pathways which can make the definition of reasonably conservative meteorological conditions a non-trivial exercise. It is normally expected for an NPP that meteorological and hydrological site-specific data will be used to define the characteristic dispersion conditions for radioactive release [19]. These data are to be collected every hour over a period of one year or longer and used in calculations either directly or with some preliminary statistical processing.

In this project a single set of meteorological data was provided to all participants. The data set includes 8760 records (1 record per hour) for each of 22 meteorological parameters. When needed a preliminary statistical processing of this meteorological array was performed independently based on the national approach.

The dispersion of the released material in the atmosphere, and its consecutive deposition into the soil is the first process to be considered in an accident consequence assessment (ACA). An ACA normally involves a series of calculations to estimate doses to population, to define possible associated mitigation actions and the resulting health effects and economic costs.

Calculation of the need for and effect of the emergency preparedness and response actions as well as evaluation of economic losses are outside the scope of this project.

Computer tools and models which are developed to analyse the dispersion and distribution of the radionuclides released from an NPP in an emergency model a major release of radioactivity transported over a very long distance, with variations in meteorological conditions and the time-profile defined for the source term.

For simulation of dispersion and deposition of released materials several models varying in the areas of application and having different advantages and drawbacks can be used. Early ACA tools have been based on the straight-line Gaussian plume dispersion model. More recent ACA programs have used the Gaussian puff model or trajectory models. Models using linear trajectories are applicable for travel distances up to a few tens of kilometres, and they become increasingly inaccurate or unreliable at longer distances. Models which are appropriate for use at longer distances may not be appropriate for use at short distances either because of assumptions they contain or because of their limited spatial resolution [20].

Different models or considerations may apply at different distances from the source of radioactive release. The early effects of radiation are assumed to be deterministic and may only occur when the dose received over a relatively short time period exceeds a certain threshold.

Such effects are mostly expected in the areas relatively close to the NPP assuming accidental releases of a significant amount of radioactive material. The late effects (i.e. stochastic effects) of radiation are assumed to appear at any dose and these can occur at any distance. The calculation of late health effects from exposure over extended periods of time is a complex problem involving the time variation of dose (including the time variation of intake and of the concentration in food after deposit for ingestion doses), the variation of risk with the age and

life-expectancy of the exposed individuals and the age distribution of the exposed population [20].

Transport and dispersion of substances in the atmosphere are mainly influenced by advection (wind) and processes such as turbulent diffusion. Depletion processes under wet and dry conditions, together with radioactive decay, also alter the content in the plume. The first approaches to solve this problem resulted in analytical solutions of the advection-dispersion process and are known as Gaussian type models.

Gaussian models can be applied in plain terrain and under steady state conditions, i.e. a uniform release with a constant rate, geometry, and altitude, and constant atmospheric conditions. A typical picture of a representation of the plume is shown in Figure 2. The geometry and thus the concentration pattern of the plume is described by Gaussian distributions. These parameters typically are the result of dispersion experiments and are site dependent.

FIG.2. Scheme of a Gaussian plume model

The basic Gaussian plume dispersion model (GPM) equation describes the downwind time integrated concentration  (x, y, z) in air resulting from a release of material from a point source located at (x=0, y=0, z=H): ·

𝜒(𝑥, 𝑦, 𝑧) = · 𝑒𝑥𝑝 − · 𝑒𝑥𝑝 −^{( )} + 𝑒𝑥𝑝 −^{( )} (1) Where Q is the quantity of material released (Bq), u is the mean wind speed (transport speed) in the downwind x direction (m/s) and H is the height of the plume centerline (m). y and z

(m) are the diffusion coefficients describing the plume spread in the horizontal and vertical crosswind directions y and z. Generally, the values of y and z depend on the travel time, on the atmospheric stability class³ [21], on the surface roughness, and on the release height [20].

Pasquill-Gifford atmospheric stability classes depend on the weather characteristics such as

3In the new generation Gaussian plume air dispersion model ADMS 5 the atmospheric boundary layer properties are characterised by the boundary layer depth, and the Monin-Obukhov length rather than in terms of the single parameter Pasquill-Gifford class. ADMS is an advanced code combining advantages of Gaussian and Lagrangian models and taking

Turbulence

Concentration of radionuclides

Distance from the source of release

wind speed, day solar insolation and night cloudiness and vary from very unstable (A class) to stable (F class).

The next step to improve the Gaussian type of model to account for the changing atmospheric conditions, was the introduction of the so called “Gaussian puff” model. Here the plume is represented by puffs which can vary depending on the turbulence conditions of the atmosphere and the wind direction. The continuous release is replaced by a consecutive release of many puffs; however, the geometry of the puff is still described by Gaussian functions (see Figure 3).

Nevertheless, the puffs can follow trajectories of a 3-D wind field which can be time dependent.

FIG.3. Scheme of a Gaussian puff model

FIG.4. Scheme of a particle model

The next step in advanced dispersion modelling is the so called “Lagrangian” particle models, which represent the plume via a large number of independent particles which move along individual trajectories determined by the wind field and the turbulence of the atmosphere (see

Distance from the source of release

Concentration of radionuclides Turbulence

Distance from the source of release

Random motion + wind force

Figure 4). The distribution of the particles in a grid cell gives a stochastic representation of the concentration. The turbulent diffusion is described as an uncorrelated random walk process assuming a mean state and superimposed fluctuations. Velocity fluctuations are computed from eddy diffusivities or defined through parameterizations using the Monin-Obukhov-theory. This independence of individual particles also allows complex meteorological situations to be represented; for example, changes of the wind direction with height resulting in opposite wind directions at ground level and close to the top of the boundary layer.

Besides the above-mentioned types, another gridded model type is used. The so called

“Eulerian” models also solve the general equation for the transport of matter in turbulent fluids, the advection – diffusion differential equation. However, the solution is based on a particular grid. The input is the output of a numerical weather prediction system; thus, Eulerian codes are preferably used for long range dispersion calculations corresponding to the resolution of the numerical weather data.

Reviews of existing transport and dispersion models can be found in Refs [22, 23]. In terms of operability, probabilistic assessment codes so far use Gaussian type of models (e.g. COSYMA and MACCS), however, COSYMA has been further developed by Public Health England (PHE) to integrate the NAME [24] Lagrangian model of the UK Met Office (the PACE code).

For non-nuclear applications, Lagrangian models have been used for a long time. For example, the AUSTAL2000 model is the German standard for probabilistic assessments for licensing of industrial installations [25]. Decision support systems for nuclear emergencies such as the RODOS system [26] also comprise Lagrangian models. In its 2014 release, probabilistic assessment capabilities are also included which allow use of advanced dispersion models for weather data covering several years and providing results that can be evaluated statistically outside the system.

2.2.4. Exposure pathways

The routes by which radiation or radionuclides can reach humans and cause exposure, i.e.

exposure pathways, depend on the scenario of release, and the pathways of exposure from radioactive release may differ essentially in comparison to normal operation releases. An indicative list of exposure pathways for potential exposure scenarios is provided in Ref [6]:

 External irradiation:

- from the source;

- from the plume;

- from the deposition on skin;

- from the deposition on the ground or other surfaces;

 Inhalation:

- from the plume;

- of resuspended material;

 Intakes of radionuclides:

- from fresh and processed food and water;

- due to the inadvertent ingestion of radionuclides deposited on ground or other surfaces.

Contributions to the total dose from different exposure pathways depend on the scenario of release (source term and transport in environment), location and characteristics / habits of individuals, and potential implementation of protective measures.

In this project the distribution of population in the affected area was set up in the beginning of the exercise and used in every national study along with corresponding requirements applicable in a given country. Implementation of protective measures was considered as relevant by the different modellers.

Age is one of the major characteristics of individuals who may be affected by accidental exposure which determines essential differences in the radiological consequences. Infants may be more exposed than adults via intakes of certain radionuclides due to the inadvertent ingestion and inhalation of resuspended contaminated material [27]. Infants may be more vulnerable to the irradiation of the thyroid gland due to the incorporation of radioactive iodine isotopes, which could potentially be released in a nuclear reactor accident [6].

The scope of consideration of individual characteristics of population groups involved in the assessment of potential exposures, and national criteria used in the assessment study to identify the most exposed group of individuals, may vary in different countries. Sometimes specific groups of the most vulnerable individuals need to be selected for dose estimation in advance, while in other cases the distribution of doses or risks among larger affected population groups may involve dose estimations for specific locations (e.g. the nearest village, the biggest town nearby etc.), or calculation of dose distribution for all population groups using the predefined fixed net covering the whole emergency area with the nodes distributed in all directions and in different distances from the release source.

In this project national experts used their national recommendations and requirements on consideration of habits and individual characteristics of population groups and the representative (most exposed) person identification.