A study of the atmospheric dispersion of a high release of krypton-85 above a complex coastal terrain, comparison with the predictions of Gaussian models (Briggs, Doury, ADMS4)

Atmospheric releases of krypton-85, from the nuclear fuel reprocessing plant at the AREVA NC facility at La Hague (France), were used to test Gaussian models of dispersion. In 2001-2002, the French Institute for Radiological Protection and Nuclear Safety (IRSN) studied the atmospheric dispersion of 15 releases, using krypton-85 as a tracer for plumes emitted from two 100-m-high stacks. Krypton-85 is a chemically inert radionuclide. Krypton-85 air concentration measurements were performed on the ground in the downwind direction, at distances between 0.36 and 3.3 km from the release, by neutral or slightly unstable atmospheric conditions. The standard deviation for the horizontal dispersion of the plume and the Atmospheric Transfer Coefficient (ATC) were determined from these measurements. The experimental results were compared with calculations using first generation (Doury, Briggs) and second generation (ADMS 4.0) Gaussian models. The ADMS 4.0 model was used in two configurations; one takes account of the effect of the built-up area, and the other the effect of the roughness of the surface on the plume dispersion. Only the Briggs model correctly reproduced the measured values for the width of the plume, whereas the ADMS 4.0 model overestimated it and the Doury model underestimated it. The agreement of the models with measured values of the ATC varied according to distance from the release point. For distances less than 2 km from the release point, the ADMS 4.0 model achieved the best agreement between model and measurement; beyond this distance, the best agreement was achieved by the Briggs and Doury models.     

Photochemical dispersion modeling: Review of model concepts and applications studies

Over the last decade, the development and application of sophisticated atmospheric models that simulate the transport and dispersion of ozone and its precursors have advanced rapidly. Further advancements are most likely to be found in more complete temporal and spatial characterization of photochemical smog formation processes via measurement. This paper provides an overview of the development of atmospheric photochemical dispersion models, first discussing in general terms the various physical processes occurring in the atmosphere that govern the formation, transport, and ultimate fate of ozone. Procedures for representing these physical processes in mathematical terms are presented next. Nearly all of the photochemical models in use today are derived from the semiempirical atmospheric diffusion equation, though theoretical formulations vary depending on which of the various terms in the pollutant mass balance equation are deemed significant for the application at hand. Examples of recent applications of the range of available photochemical model are presented, together with estimates of the accuracy of each generic modeling concept. Several topics warranting future research are identified, including the need to incorporate explicitly more of the stochastic (or probabilistic) nature of the atmosphere into the form of current photochemical model predictions (i.e., estimates of the variance and higher order moments of the predicted concentration distribution).     

A modelling study on 137Cs and 239,240Pu behaviour in the Alborán Sea, western Mediterranean

A model for simulating the dispersion processes of 137Cs and 239,240Pu in the Alborán Sea is described. The model consists of two hydrodynamic models: a 2D depth-averaged model and a two-layer model which provide tidal and geostrophic currents, respectively; a sediment transport model which provides suspended particle concentrations and sedimentation rates over the domain; and the radionuclide dispersion model including interactions of dissolved radionuclides with suspended particles and bed sediments. These processes are formulated using kinetic transfer coefficients. The hydrodynamic and sediment models are run and validated in advance, and their results are then used to simulate the dispersion of 137Cs and 239,240Pu, which are introduced from atmospheric fallout. Radionuclide concentrations in the water column and distributions in bed sediments have been compared with measurements in the sea. Both set of data are, in general, in agreement. The model has also been applied to calculate radionuclide fluxes through the Strait of Gibraltar. These computed fluxes have been compared with previous estimations as well.     

Modelling multiple dispersion of radionuclides through the environment

The migration of a contaminant through the environment is the result of the transport by a variety of biotic and abiotic carriers which move according to different dispersion mechanisms. Consequently, the patterns of the distribution of a pollutant in the environment cannot be ever explained on the basis of a single migration process or assuming that the concentrations of contaminant in the different kinds of carriers quickly reach the equilibrium condition. The present work discusses two examples (wash-off from catchments and transport through soils of radionuclides) that clearly demonstrate the inadequacy of “single dispersion” models to predict these patterns. On the contrary, models based on multiple dispersion can successfully simulate the particular features of the above mentioned processes. It was demonstrated that the time behaviour of radionuclide migration rates from catchment of different rivers vary within small ranges as a consequence of multiple dispersion. This result can be useful for the development of generic predictive models.     

Examination of model uncertainty and parameter interaction in a global carbon cycling model (GLOCO)

Simulation models play an important role in understanding the causes and consequences of climate change. In order to make full use of these models, it is necessary to establish the magnitude and sources of uncertainty associated with their predictions. This information can be used to achieve a better understanding of the simulated systems, to increase the reliability of model predictions, to guide field surveys and laboratory experiments, and to define realistic values that should be used in scientific, economic, and political discussions of future conditions. In this paper, a new tree-structured density estimation technique that extends the ability of Monte Carlo-based analyses to explore parameter interactions and uncertainty in complex environmental models was applied. The application of the technique is demonstrated using the GLOCO global carbon cycle model. The paper demonstrates that there are numerous distinct parameter combinations that can meet fairly stringent calibration criteria, and they are concentrated in relatively small subsets of the parameter space. These different subsets can be viewed as representing different ecological systems that achieve the same calibration or performance goals in fundamentally different ways. It is also shown that the simulated responses of these systems to future environmental change can lead to different conclusions regarding the interaction between factors affecting environmental processes, such as the growth of vegetation. Together, these results show how the tree-structured density estimation technique can be applied to gain a broader understanding of model performance and of ecosystem responses to change.     

An operative lagrangian model for simulating radioactivity dispersion in the Strait of Gibraltar

GISPART (GIbraltar Strait PARticle Tracking model) is a three-dimensional particle tracking code to simulate the dispersion of radionuclides in the Strait of Gibraltar. It consists of a hydrodynamic module that is run off-line to determine tidal constants and residuals in the domain. This information is stored in several files that are read by the dispersion module to reconstruct water movements. The dispersion module uses a lagrangian approach. Thus, a radionuclide release is simulated by a number of particles, whose paths are computed individually. Radionuclide concentrations are obtained from the density of particles per water volume unit. Some examples of results are shown. The model is also available on-line.     

The dispersion of 99Tc in the Nordic Seas and the Arctic Ocean: a comparison of model results and observations

The radionuclide (99)Tc had been discharged from the nuclear reprocessing facility in Sellafield (UK) into the Irish Sea in increased amounts in the 1990s. We compare the simulated dispersion of (99)Tc in surface water as calculated by a hydrodynamic model and an assessment box model with field-observations from 1996 to 1999 to study concentrations, pathways and travel times. The model results are consistent with the observations and show the typical pathway of dissolved radionuclides from the Irish Sea via the North Sea along the Norwegian Coast. Subsequently the contaminated water separates into three branches of which the two Arctic branches bear the potential for future monitoring of the signal in the next decades. The results of the hydrodynamic model indicate a large variability of surface concentrations in the West Spitsbergen Current which has implications for future monitoring strategies. According to the observed and simulated distributions we suggest an improved box model structure to better capture the pattern for concentrations at the surface.     

Carbon-14 transfer into rice plants from a continuous atmospheric source: observations and model predictions

Carbon-14 ((14)C) is one of the most important radionuclides from the perspective of dose estimation due to the nuclear fuel cycle. Ten years of monitoring data on (14)C in airborne emissions, in atmospheric CO(2) and in rice grain collected around the Tokai reprocessing plant (TRP) showed an insignificant radiological effect of the TRP-derived (14)C on the public, but suggested a minor contribution of the TRP-derived (14)C to atmospheric (14)C concentrations, and an influence on (14)C concentrations in rice grain at harvest. This paper also summarizes a modelling exercise (the so-called rice scenario of the IAEA's EMRAS program) in which (14)C concentrations in air and rice predicted with various models using information on (14)C discharge rates, meteorological conditions and so on were compared with observed concentrations. The modelling results showed that simple Gaussian plume models with different assumptions predict monthly averaged (14)C concentrations in air well, even for near-field receptors, and also that specific activity and dynamic models were equally good for the prediction of inter-annual changes in (14)C concentrations in rice grain. The scenario, however, offered little opportunity for comparing the predictive capabilities of these two types of models because the scenario involved a near-chronic release to the atmosphere. A scenario based on an episodic release and short-term, time-dependent observations is needed to establish the overall confidence in the predictions of environmental (14)C models.     

Calculation of the depletion of airborne pollutant plumes through dry deposition processes

The depletion of airborne pollutant plumes resulting from dry deposition on ground surfaces should be taken into account when estimating pollutant concentrations in air at distances downwind from their sources. This can be done by using a reduced release rate instead of the actual release rate for the pollutant in atmospheric dispersion equations. The reduced release rate is the actual rate of release multiplied by a depletion fraction. Depletion fractions for use with the Gaussian atmospheric dispersion equation of Pasquill and Gifford were calculated by numerical integration for downwind distances ranging from 35 to 90 000 m for release heights from 1 to 400 m, and they are tabulated for convenient interpolation for intermediate values of distance and release height. Pasquill atmospheric stability categories A-G are included. The listed values are for a deposition velocity of 0.01 m/s and a wind speed of 1 m/s but can be easily converted to apply to other deposition velocities and wind speeds. The tabulated values may be applied for downwind distances close enough to the point of release that the Gaussian model may be assumed to be realistic and where the vertical dispersion of the plume has not yet been significantly affected by the overlying atmospheric lid.     

A particle-tracking method for simulating the dispersion of non-conservative radionuclides in coastal waters.

A particle-tracking method has been used to simulate the dispersion of non-conservative radionuclides in the sea. Three dimensional turbulent diffusion and the interactions between water, suspended matter and bottom sediments are simulated using a stochastic method. Kinetic transfer coefficients, as in finite difference models, are used to describe the transfers between the liquid and solid phases. Deposition of suspended matter and erosion of sediment are also included in the model. The method has been applied to simulate the dispersion of 137Cs and (239,240)Pu in the English Channel and the results have been compared with those of a finite difference model. The results from both techniques are, in general, in good agreement.     

Short and long term dispersion patterns of radionuclides in the atmosphere around the Fukushima Nuclear Power Plant

The Chernobyl accident and unfortunately the recent accident at the Fukushima 1 Nuclear Power Plant are the most serious accidents in the history of the nuclear technology and industry. Both of them have a huge and prolonged impact on environment as well as human health. Therefore, any technological developments and strategies that could diminish the consequences of such unfortunate events are undisputedly the most important issues of research. Numerical simulations of dispersion of radionuclides in the atmosphere after an accidental release can provide with a reliable prediction of the path of the plume. In this study we present a short (one month) and a long (11 years) term statistical study for the Fukushima 1 Nuclear Power Plant to estimate the most probable dispersion directions and plume structures of radionuclides on local scale using a Gaussian dispersion model. We analyzed the differences in plume directions and structures in case of typical weather/circulation pattern and provided a statistical-climatological method for a “first-guess” approximation of the dispersion of toxic substances. The results and the described method can support and used by decision makers in such important cases like the Fukushima accident.     

Data assimilation for short range atmospheric dispersion of radionuclides: a case study of second-order sensitivity

This article presents the application of variational data assimilation to a simple Gaussian plume model for radionuclides. Adjoint modeling is applied to the model in order to minimize discrepancies between contamination observations and model outputs. The interest of such an approach is to get a better estimation of some parameters such as emissions or dispersion parameters. A second-order analysis is also performed to assess the sensitivity of the optimized parameters to some poorly known parameters. Sensitivity with respect to network design is also done.     

Data assimilation for short range atmospheric dispersion of radionuclides: a case study of second-order sensitivity

This article presents the application of variational data assimilation to a simple Gaussian plume model for radionuclides. Adjoint modeling is applied to the model in order to minimize discrepancies between contamination observations and model outputs. The interest of such an approach is to get a better estimation of some parameters such as emissions or dispersion parameters.A second-order analysis is also performed to assess the sensitivity of the optimized parameters to some poorly known parameters. Sensitivity with respect to network design is also done.     

Public health benefits of compliance with current E.U. emissions standards for municipal waste incinerators: a health risk assessment with the CalTox multimedia exposure model

The Angers municipal solid waste incineration plant, in operation since 1974, was upgraded in 2000 to comply with new European standards. This article discusses the risks associated with past and present emissions from the incinerator and its nearby furnace. Emissions of SO(2), HCl, particulate matter, lead, mercury, cadmium and dioxins were studied. We characterised the risks associated with exposure via inhalation and ingestion of locally grown products, before and after the upgrade. Emissions were estimated from regulatory measurements, and ambient air concentrations estimated with a Gaussian dispersion model. The CalTox multimedia model was used to calculate concentrations in the food chain. Food intake rates came from a nationwide survey. Inhalation exposure to respiratory irritants produced a hazard ratio less than 1 in all scenarios, except for SO(2) in the immediate neighbourhood of the incinerator, before the change in furnace fuel and in case of high-pressure weather conditions. The individual excess risk of cancer was less than 10(-6) and the hazard ratios for metals were less than 1. Before compliance, the average dioxin exposure attributable to the incinerator accounted for roughly one quarter of the average total exposure from traffic and other combustion activities. Although the corresponding hazard ratio was less than 1, the individual lifetime excess risk, assuming no change in emissions, was 2 x 10(-4). After compliance, all hazard ratios and future individual lifetime excess risks appear minimal. These results are consistent with environmental data and other studies, but many uncertainties remain, such as intermedia transfer coefficients for dioxins. Nevertheless compliance has vastly reduced the probability of health effects.     

A box model for calculation of collective dose commitment from radioactive waterborne releases to the baltic sea

To meet the new regulations of maximum yearly releases from Swedish nuclear power plants issued by the Swedish National Radiation Protection Institute, and to make realistic calculations of collective dose commitment derived from radionuclides discharged to the Baltic Sea, a box model AQUAPATH-BALTIC has been developed. The model calculates radionuclide concentrations in 25 boxes for discharges into given compartments and takes into consideration the dispersion rates of the water masses, the sediment-water interaction and radioactive decay. The calculated concentrations in water and sediment at steady state are then used to evaluate individual and collective intakes of activity and external exposures. The radiation doses to the global population following discharges to the Baltic Sea are also calculated.     

Forecasting the consequences of accidental releases of radionuclides in the atmosphere from ensemble dispersion modelling.

The RTMOD system is presented as a tool for the intercomparison of long-range dispersion models as well as a system for support of decision making. RTMOD is an internet-based procedure that collects the results of more than 20 models used around the world to predict the transport and deposition of radioactive releases in the atmosphere. It allows the real-time acquisition of model results and their intercomparison. Taking advantage of the availability of several model results, the system can also be used as a tool to support decision making in case of emergency. The new concept of ensemble dispersion modelling is introduced which is the basis for the decision-making application of RTMOD. New statistical parameters are presented that allow gathering the results of several models to produce a single dispersion forecast. The devised parameters are presented and tested on the results of RTMOD exercises.     

Model simulations of the fate of 14C added to a Canadian shield lake

Carbon-14 was added to the epilimnion of a small Canadian Shield lake to investigate primary production and carbon dynamics. The nature of the spike and subsequent monitoring allowed the investigation of both short-term and longer-term processes relevant to evaluating impacts of accidental and routine releases and of solid waste disposal. Data from this experiment were used in the BIOMOVS II program as a validation test for modelling the fate of the ¹⁴C added to the lake. Four models were used: (1) a simple probabilistic mass balance model of a lake; (2) a relatively complex deterministic model; (3) a complex deterministic model; and (4) a more complex probabilistic model. Endpoints were ¹⁴C concentrations in water, sediment and lake whitefish over a thirteen year period. Each model produced reasonable predictions when compared to the range of the observed data and when uncertainty in model predictions is taken into consideration. The simple lake model did not account for internal recycling of ¹⁴C and, in this respect, its predictions were not as realistic as those of the more complex models for concentrations in water. However, the simple model predictions for the ¹⁴C inventory remaining in lake sediment were closest to the observed values. Overall, the more complex probabilistic model was the most accurate in simulating ¹⁴C concentrations in water and in whitefish but it overestimated ¹⁴C retention in the lake sediments, as did the other complex models. Choice of parameter values for transfer rate to sediment and gaseous evasion are important in influencing model predictions. Although predicted concentrations of ¹⁴C in fish of dynamic models were more accurate than those using equilibrium bioconcentration factors typically used in assessments, large variability in observed ¹⁴C concentrations in whitefish emphasizes the need for a better understanding of the important processes that influence these contaminant concentrations.     

On the sensitivity of a marine dispersion model to parameters describing the transfers of radionuclides between the liquid and solid phases

The sensitivity of a marine dispersion model for non-conservative radionuclides, previously developed and validated for the English Channel, to parameters describing the exchanges between the liquid and solid phases (suspended matter and bottom sediments) has been studied using a Monte Carlo method. A probability distribution is assigned to each parameter. They are sampled to obtain a set of model parameters and a model run is carried out. This process is repeated to obtain a distribution of model outputs. Partial correlation coefficients are calculated to assess the relative influence of each parameter on model output. Errors are also assigned to model results. Three situations are studied: an instantaneous release of radionuclides, a continuous release and the case of a contaminated sediment behaving as a long-term source of radionuclides. Calculations have also been carried out for two radionuclides with different geochemical behaviour: (137)Cs and (239,240)Pu. The results indicate that all parameters are relevant, depending on the phase we are interested in obtaining the result and on the source term (instantaneous, continuous or due to sediments). However, parameters that are, in general, more influential are kinetic rates, mixing depth in the sediment and mean radius of suspended and sediment particles. This suggests that including several particle sizes in future radionuclide dispersion models could lead to an improvement in model results. Differences have also been found with respect to the relevance of some parameters depending on the geochemical behaviour of the radionuclide.