Modelling air pollution around nuclear power plants: validation of dispersion models using tracer data.

The Sostanj exercise of the Modelling and Data for Radiological Impact Assessments I Urban Environments Working Group took advantage of a set of measurement data from a 1991 tracer experiment to test atmospheric dispersion models for emissions from point sources over complex terrain. The data set included emissions of SO2from the stacks of the Sostanj Thermal Power Plant in Slovenia, measurements of the SO2at a number of locations in the surrounding area up to 7 km from the plant, and meteorological data from several monitoring stations, all as measured half-hour average values. Two sets of meteorological conditions were modelled: (a) a simple situation with a strong wind blowing from a point source directly towards a monitoring station; and (b) a complex situation involving a temperature inversion and convective mixing. The modelling results enable the assessment of the capabilities of various dispersion models in handling both complex terrain and complex meteorological situations.

Urban working groups in the IAEA's model testing programmes: overview from the MODARIA I and MODARIA II programmes.

The IAEA's model testing programmes have included a series of Working Groups concerned with modelling radioactive contamination in urban environments. These have included the Urban Working Group of Validation of Environmental Model Predictions (1988-1994), the Urban Remediation Working Group of Environmental Modelling for Radiation Safety (EMRAS) (2003-2007), the Urban Areas Working Group of EMRAS II (2009-2011), the Urban Environments Working Group of (Modelling and Data for Radiological Impact Assessments) MODARIA I (2013-2015), and most recently, the Urban Exposures Working Group of MODARIA II (2016-2019). The overarching objective of these Working Groups has been to test and improve the capabilities of computer models used to assess radioactive contamination in urban environments, including dispersion and deposition processes, short-term and long-term redistribution of contaminants following deposition events, and the effectiveness of various countermeasures and other protective actions, including remedial actions, in reducing contamination levels, human exposures, and doses to humans. This paper describes the exercises conducted during the MODARIA I and MODARIA II programmes. These exercises have included short-range and mid-range atmospheric dispersion exercises based on data from field tests or tracer studies, hypothetical urban dispersion exercises, and an exercise based on data collected after the Fukushima Daiichi accident. Improvement of model capabilities will lead to improvements in assessing various contamination scenarios (real or hypothetical), and in turn, to improved decision-making and communication with the public following a nuclear or radiological emergency.

Integrated system for population dose calculation and decision making on protection measures in case of an accident with air emissions in a nuclear power plant.

The accidents in Chernobyl and Fukushima remind us that nuclear power plants should continuously invest resources in improving safety and in risk management. This paper presents the methodology for developing a measuring and modelling system with a high degree of automation, which enables predicting the effects of the spreading of radionuclides from the nuclear power plant to the atmosphere. The end result is the calculated population doses in the event of an accidental release, which is an essential piece of information needed by first responders to take proper action. The key challenge addressed by this methodology is how to build a system so that its operation is maximally automated, ongoing and in real time. Moreover, in a way that "fresh", normalized results for the hypothetically most probable types of emissions are always available to operators. The principle that normalized, fresh results are always automatically available to operators is the only real assurance that they will almost surely be available in the event of an accident and panic. This way, we can avoid performing complex model calculations at the operator's request when the accident is already taking place. The methodology divides the building of the system into key modules, which are substantiated and described. The theoretical section is followed by a description of implementation on the example of the Measuring and Modelling System at the Krsko Nuclear Power Plant (in Slovenia). The system has been tested in regular nuclear emergency exercises and rated excellent by IAEA inspections; it has been operating automatically, continuously and in real time for many years. The availability of automatic results is counted for the last two years. Measurements and diagnostic modelling results were available for more than 96% and forecasts were available in more than 91% of all half-hour intervals.

Relative doses instead of relative concentrations for the determination of the consequences of the radiological atmospheric releases.

Radiological atmospheric releases require population dose calculation for proper determination of preventive measures. The old concept of relative concentrations requires long lasting constant emission which is not realistic. The proposed concept of the "relative doses" is the generalization and expansion of the known concept of relative concentrations. Relative doses allow an evaluation of the general non-stationary pollutants emission under the real weather conditions over complex terrain. Relative doses can be calculated even before the actual source term - quantified emission - is known. The relative impact is also very useful for considering the possible impact of an accident scenario on the surroundings for various meteorological situations. This is applied for environmental impact assessments which require long term statistical evaluation. The method has a practical possible application for realistic dose assessment of effectiveness of additional protection achieved by installation of Passive Containment Filtered Venting Systems (PCFVS). PCFVS is considered an obligatory safety upgrade after the Fukushima accident.

Nonlinear data assimilation for the regional modeling of maximum ozone values.

We present a new method of data assimilation with the aim of correcting the forecast of the maximum values of ozone in regional photo-chemical models for areas over complex terrain using multilayer perceptron artificial neural networks. Up until now, these types of models have been used as a single model for one location when forecasting concentrations of air pollutants. We propose a method for constructing a more ambitious model: a single model, which can be used at several locations because the model is spatially transferable and is valid for the whole 2D domain. To achieve this goal, we introduce three novel ideas. The new method improves correlation at measurement station locations by 10% on average and improves by approximately 5% elsewhere.

Improving of local ozone forecasting by integrated models.

This paper discuss the problem of forecasting the maximum ozone concentrations in urban microlocations, where reliable alerting of the local population when thresholds have been surpassed is necessary. To improve the forecast, the methodology of integrated models is proposed. The model is based on multilayer perceptron neural networks that use as inputs all available information from QualeAria air-quality model, WRF numerical weather prediction model and onsite measurements of meteorology and air pollution. While air-quality and meteorological models cover large geographical 3-dimensional space, their local resolution is often not satisfactory. On the other hand, empirical methods have the advantage of good local forecasts. In this paper, integrated models are used for improved 1-day-ahead forecasting of the maximum hourly value of ozone within each day for representative locations in Slovenia. The WRF meteorological model is used for forecasting meteorological variables and the QualeAria air-quality model for gas concentrations. Their predictions, together with measurements from ground stations, are used as inputs to a neural network. The model validation results show that integrated models noticeably improve ozone forecasts and provide better alert systems.