Tools for harmonized data collection at exposure situations with naturally occurring radioactive materials (NORM).

Naturally occurring radioactive materials (NORM) contribute to the dose arising from radiation exposure for workers, public and non-human biota in different working and environmental conditions. Within the EURATOM Horizon 2020 RadoNorm project, work is ongoing to identify NORM exposure situations and scenarios in European countries and to collect qualitative and quantitative data of relevance for radiation protection. The data obtained will contribute to improved understanding of the extent of activities involving NORM, radionuclide behaviours and the associated radiation exposure, and will provide an insight into related scientific, practical and regulatory challenges. The development of a tiered methodology for identification of NORM exposure situations and complementary tools to support uniform data collection were the first activities in the mentioned project NORM work. While NORM identification methodology is given in Michalik et al., 2023, in this paper, the main details of tools for NORM data collection are presented and they are made publicly available. The tools are a series of NORM registers in Microsoft Excel form, that have been comprehensively designed to help (a) identify the main NORM issues of radiation protection concern at given exposure situations, (b) gain an overview of materials involved (i.e., raw materials, products, by-products, residues, effluents), c) collect qualitative and quantitative data on NORM, and (d) characterise multiple hazards exposure scenarios and make further steps towards development of an integrated risk and exposure dose assessment for workers, public and non-human biota. Furthermore, the NORM registers ensure standardised and unified characterisation of NORM situations in a manner that supports and complements the effective management and regulatory control of NORM processes, products and wastes, and related exposures to natural radiation worldwide.

A methodology for the systematic identification of naturally occurring radioactive materials (NORM).

Naturally occurring radioactive materials (NORM) are present worldwide and under certain circumstances (e.g., human activities) may give radiation exposure to workers, local public or occasional visitors and non-human biota (NHB) of the surrounding ecosystems. This may occur during planned or existing exposure situations which, under current radiation protection standards, require identification, management, and regulatory control as for other practices associated with man-made radionuclides that may result in the exposure of people and NHB. However, knowledge gaps exist with respect to the extent of global and European NORM exposure situations and their exposure scenario characteristics, including information on the presence of other physical hazards, such as chemical and biological ones. One of the main reasons for this is the wide variety of industries, practices and situations that may utilise NORM. Additionally, the lack of a comprehensive methodology for identification of NORM exposure situations and the absence of tools to support a systematic characterisation and data collection at identified sites may also lead to a gap in knowledge. Within the EURATOM Horizon 2020 RadoNorm project, a methodology for systematic NORM exposure identification has been developed. The methodology, containing consecutive tiers, comprehensively covers situations where NORM may occur (i.e., minerals and raw materials deposits, industrial activities, industrial products and residues and their applications, waste, legacies), and thus, allows detailed investigation and complete identification of situations where NORM may present a radiation protection concern in a country. Details of the tiered methodology, with practical examples on harmonised data collection using a variety of existing sources of information to establish NORM inventories, are presented in this paper. This methodology is flexible and thus applicable to a diversity of situations. It is intended to be used to make NORM inventory starting from the scratch, however it can be used also to systematise and complete existing data.

General model for estimation of indoor radon concentration dynamics.

A known relationship exists between high radon concentrations and lung cancer, and therefore, the indoor radon quantification is important, and it is beneficial to have a model to estimate indoor concentration. The work is focused on the development of an INDORAD (INDOor RAdon Dynamic) model for estimation of indoor radon dynamics, with time-dependent meteorological parameters and adjustable soil and building properties being considered. This model is based on a systemic approach, where the flows of material between compartments are considered, without a spatial resolution. This approach allowed to simplify the mathematical processing and enabled to consider together all known sources of indoor radon. The developed model was put in use in a laboratory building where soil constitutes major source of radon. The results (radon concentrations) from the model were compared to an existing data set from Saelices el Chico in a soil with high concentration of 226Ra. The outcome of the validation implies that INDORAD could predict radon concentrations satisfactorily. Suggestions for future updates of the model to improve indoor radon estimations are provided.

Spanish experience on modeling of environmental radioactive contamination due to Fukushima Daiichi NPP accident using JRODOS.

Since the Chernobyl Nuclear Power Plant accident, decision support systems (DSS) for supporting response of the decision makers in emergencies have been developed and refined. Data available from real accidents are used to validate these systems, thus demonstrating their real capabilities and finally to improve them. This article presents the findings of the simulation exercises using JRODOS DSS performed in Spain after the first days of the accident in the Fukushima Daiichi Nuclear Power Plant. The investigation was carried out in two phases. The first phase is considered the early phase of the accident when few details of the real emissions are known (operational modeling). The second phase demonstrates how real measurements could be used (reconstructive modeling) to improve model predictions. Only major releases to the atmosphere, occurring during the first two weeks, were taken into account. Validation of the model was performed by direct comparison of the modeled results with real measurements.