Radiological Risk Assessment of Radionuclides Releases From Nuclear Research Reactors Through Different Plume Rise Models

O.S. Ahmed

Objectives The purpose of this paper is to study the effect of the plume exposure models on the cancer risk at areas around a nuclear research reactor using different Fortran Programs Material and Methods Using models such as the Gaussian Plume Model to assess the distribution of radionuclide spread during research nuclear reactor normal/accident atmospheric dispersion equation are widely used, where radionuclide concentration with different shapes of plume rise, which computation of plume rise is one of the basic aspects for a correct estimation of the transport and dispersion of airborne pollutants and for the evaluation of ground level concentration Results The results indicated that the maximum concentration of Iodine-135 happens at a distance of 165 m, according to the majority of simulations. The greatest dose and danger are often found in the Carson and Moses method. The Gaussian model’s results are more consistent with the observed values. The impact of wind Unstable breezes can enhance ground concentration and dispersion in specific locations. Conclusion Show that the near-source area is the primary source of public exposure after airborne radioactive leaks. Moreover, the observed variation in plume rise models is a reflection of the model-related uncertainty that UNSCEAR identified as a major determinant of radiological risk assessments. The IAEA recommends that safety assessments be made more robust by identifying systematic differences in predicted dose and risk among commonly used dispersion models. This study also supports informed decision-making for radiation protection, siting analysis, and emergency planning zones.

Bounding atmospheric dispersion factors for nuclear facility siting without site meteorological data

Adam Stein

Atmospheric dispersion factors (χ/Q) are typically used in accident dose analysis for nuclear regulatory compliance. Regulatory guidance supplies two routes: an onsite record of a year or more, or qualified offsite data from representative nearby stations. At many proposed advanced reactor sites, the second is unavailable because no representative station exists: remote siting, sparse networks, complex terrain, or coastal exposure. A third route needs no site meteorology: a dispersion factor demonstrated conservative rather than representative, but has never been supplied with a bound or an acceptance basis. This paper provides both. ARCON96 was characterized by full-factorial parameterization and one-factor sensitivity over the admissible design region, in 3,386 code executions using constant-condition meteorology that removes weather as an input. Common intuitive bounds are non-conservative: a low-wind file understates the bound by up to 2.8 times near the source, and a near-field file is non-conservative by up to 40 percent at 1,200 m. The highest values occur at a moderate wind rather than the lightest: χ/Q is non-monotonic in wind speed, and the worst case switches regime with distance. The presented per-distance envelope bounds two real records at every distance and interval evaluated, by factors of 1.07 to 2.68. The results provide dispersion factors for an envelope at the exclusion area boundary and low population zone distances when considered with the building-area stated applicability conditions.

Atmospheric Dispersion of Radioactive Materials Modeled by Stochastic Differential Equations

Rodrigo C. Curzio · Vinicius C. Machado · Jakler Nichele · E. Andrade

This research utilized stochastic differential equations to investigate the dispersion of radiological agents in the atmosphere. The modeling involved a stochastic component in the advective term of the advection-diffusion equation. The solution was obtained using the Euler-Maruyama and finite difference methods to ensure numerical stability and accuracy. The results aligned well with the hypothetical scenario of an environmental release of radioactive material from a nuclear reactor accident. The simulations illustrated how random atmospheric fluctuations and varying wind speeds impact the spread of radionuclides. The study emphasizes the importance of incorporating stochastic elements into predictive models to accurately capture the complex dynamics of radiological dispersion.In this context, the current study aimed to develop better methodological tools to enhance our understanding of the physical processes behind the atmospheric dispersion of radiological contaminants. Although the proposed model relies on simplifying assumptions, the approach based on stochastic differential equations offers a theoretical framework that can serve as a foundation for creating more comprehensive models in the future. These future models will focus on analyzing disruptive events related to the uncontrolled release of radioactive material into the atmosphere or the environment.

Validation and reliability analysis of CFD-based atmospheric dispersion modeling against wind tunnel experiments at a nuclear power plant site with irregular buildings and complex terrain

Xinpeng Li · Yinglu Cao · Zhaoyang Wang · Li Yang · Sheng Fang

Rapid prediction of atmospheric radionuclide concentration at an AP1000 nuclear power plant with complex terrain using a neural network optimized by a quantum virus optimization algorithm

Xinpeng Li · Hao Zhou · Yun Liu · Jiayue Song · Li Yang · Sheng Fang

Atmospheric Dispersion and Deposition of Radioactive Contaminants from a Hypothetical Nuclear Event at Dimona: A Multi-Physics Lagrangian Puff Simulation and Machine-Learning Surrogate Study

Ali Bavarchee

Radiological site evaluation of the proposed Gosong Beach nuclear power plant site in Indonesia

Ambar Winansi · June Mellawati · Wahyu Retno Prihatiningsih · Mohamad Nur Yahya · Deddy Irawan Permana Putra · Y Priasetyono · et al.

Physics-Constrained Machine Learning for Scenario-Based Prediction of Far-Distance Radionuclide Attenuation at the Lufeng Nuclear Power Plant

Temidayo Alex‐Oke · Olusola Bamisile · Dongsheng Cai · Osamong Gideon Akou · A. Ayodeji · Qi Huang

Environmental radiological surveillance in the Baltic Sea: offshore wind farms as platforms for early-warning detection systems

Krzysztof Pająk · Barbara Wiaderek · Dorota Gajda · Artur Czapski · Marzena Walkowiak

The Baltic Sea is an environmentally sensitive semi-enclosed marine basin characterized by intensive maritime activity, expanding offshore infrastructure, and the presence of nuclear-related facilities. These conditions increase the importance of environmental radiological surveillance capable of supporting the early detection of transboundary contamination events. This study assesses the potential application of offshore wind farm infrastructure as a platform for autonomous radiation monitoring within an expanded regional surveillance network.The study combined a review of regional radiological hazards, assessment of existing monitoring infrastructure, analysis of environmental radiation data from the European Radiological Data Exchange Platform (EURDEP), and analysis of representative meteorological conditions from 2023-2024 using European Centre for Medium-Range Weather Forecasts (ECMWF) data.The results indicate that radiological monitoring in the Baltic region is concentrated predominantly in terrestrial and coastal areas, leaving offshore regions with limited surveillance coverage. Representative atmospheric conditions indicate that airborne contaminants originating near the Gulf of Finland could potentially reach the southern Baltic coast within approximately 24 h under favourable wind conditions. Assessment of offshore infrastructure suggests that offshore wind farms could serve as platforms for autonomous radiation monitoring because they provide existing power supply, communication infrastructure, distributed offshore locations, and maintenance accessibility. Integration of offshore monitoring with terrestrial surveillance networks could improve spatial coverage and strengthen regional early-warning capability.The proposed framework provides a basis for future atmospheric dispersion modelling and optimization of offshore radiological monitoring networks.

Applying IAEA Simplified Atmospheric Dispersion Model as a training tool for Technical Support Organization Capacity Building Courses

Ahmed O S · Aly A I M

In addition to its scientific and technical research duties, the Nuclear and Radiological Safety Research Center (NRSRC) is currently working hard to strengthen its role to become a technical support organization on the both national and international levels, in cooperation with the IAEA, in the fields of nuclear and radiation facilities as well other different energy sources. The Siting and Environmental department belonging to NRSRC, is interested to develop training programs suitable for new students and trainees to use airborne dispersion codes for both nuclear and radiation facilities and non-nuclear sources. This helps them understand how to deal with these issues and calculate, estimate, and assess the risks resulting from these facilities. Based on this principle, SCREEN 3 model-originally developed by the U.S. Environmental Protection Agency- for atmospheric dispersion industrial applications - was used to evaluate the atmospheric dispersion parameters, taking into account different scenarios in terms of (emission rate, stack height and inside diameter, stack exit velocity and exit temperature, ambient air temperature, receptor height and atmospheric stability) which are the necessary data to calculate the worst concentration of the released pollutants at the receptor points, taking into account the topography of the site surrounding the facility. The results showed that stable conditions (F) shifted peaks to larger distances (1737–7880 m) with lower concentrations, whereas unstable conditions (A) produced peak concentrations close to the source (500–1041 m).

Quantitative visualization of a radioactive plume using gamma-ray imaging spectrometry: estimation of initial release condition by machine learning and feasibility of real-time analysis in emergency monitoring applications

Haruyasu Nagai · Daiki Satoh · T. Tanimori · Atsushi Takada

A novel monitoring method for the quantitative visualization of 3D distribution of a radioactive plume accidentally released from a nuclear facility was proposed, and the feasibility of its analysis method was demonstrated in our previous study by means of a preliminary test using hypothetical data. The method combines gamma-ray imaging spectroscopy with an Electron Tracking Compton Camera (ETCC) and real-time high-resolution atmospheric dispersion simulation driven by wind observations. The 3D plume distribution is reconstructed inversely from the direct gamma-ray images by several ETCCs deployed around the target area. This reconstruction employs a regularized optimization in which the air‑concentration field predicted by the dispersion simulation serves as prior information. We also prototyped a method to identify a release point, which is required as input conditions for the atmospheric dispersion calculation, solely from gamma-ray images of the ETCC immediately after the release. A method based on machine learning was employed in test analyses targeting the Fukushima Daiichi Nuclear Power Station. The results show good performance in identifying the release point when using theoretical gamma-ray image data. In practical aspect, the scope of application and accuracy of the method was evaluated using hypothetical gamma-ray image data under realistic assumptions. Moreover, the feasibility of real-time analysis was confirmed by implementing an analysis workflow designed based on the 10-minute interval data acquisition.

Assessment of radiological consequences from a hypothetical nuclear reactor accident at a proposed site in Sierra Leone

Milford Hanciles · S.A. Birikorang · Kwame Gyamfi

Abstract This study presents a hypothetical radiological impact assessment of a proposed nuclear research reactor site as part of an Environmental Impact Assessment (EIA) to support regulatory review. The study evaluates the potential radiological consequences of a postulated Loss of Coolant Accident (LOCA), where failure of the cooling system may lead to fuel overheating, core damage, and the release of radioactive materials into the environment. The HotSpot 3.2.1 atmospheric dispersion and health physics code was used to simulate the spread of radionuclides and estimate their impact. The analysis focuses on the Total Effective Dose (TED) to on-site workers and the surrounding public, as well as on ground deposition of selected radionuclides, such as 137 Cs, 90 Sr, and 85 Kr, due to their radiological importance and relatively long half-lives. The results show that 90 Sr contributes the highest TED of 3.32E−08 Sv, while the combined source term from the damaged core produces a TED of 4.92E−06 Sv at 0.21 km from the release point. In terms of environmental impact, 137 Cs records the highest ground deposition of 3.00E−03 kBq/m 2 at 0.20 km, with a peak total deposition of 2.00E+02 kBq/m 2 for the overall source term at the same distance. The dispersion pattern indicates that radionuclides are mainly transported in the northwest direction. All estimated dose and deposition values are below the regulatory limits set by the International Atomic Energy Agency General Safety Requirements (GSR) Part 3. These findings suggest that, even under conservative accident conditions, the proposed reactor site meets international radiological safety standards and is unlikely to pose significant risks to public health or the environment.

Multi-model ensemble analysis of JRODOS atmospheric dispersion models for nuclear emergency planning

Ramy-Badr Ahmed · Thomas Schichtel · Dmytro Trybushnyi · W. Raskob · Sadeeb S. Ottenburger

Implementation of a GPU-Accelerated Lagrangian Particle Dispersion Model for Atmospheric Transport of Radioactive Nuclides

Qingyun Li · Tao He · Mingye Li · Junfang Zhang · Bing Lian · Liye Liu · et al.

Large-scale atmospheric dispersion model for emergency response to nuclear accidents requires high computational efficiency and numerical reliability. A GPU-oriented Lagrangian particle dispersion model was developed within FLEXPART framework to address these demands. Core transport processes—including advection, turbulent diffusion, convective mixing, and dry/wet deposition—were restructured for GPU parallel execution. Further incorporation of fast arithmetic operators and multi-level parallelization strategies substantially improved overall computational performance while preserving physical accuracy. Additional MPI-based parallel meteorological data decoupling and preprocessing tool has been developed, which alleviates data-handling bottlenecks. Meanwhile, multi-GPU execution and a load-balancing strategy enable efficient scaling in heterogeneous computing environments. Using the first release of European Tracer Experiment (ETEX-I) as a benchmark, the GPU program’s accuracy and acceleration were rigorously evaluated. Results show that, while maintaining nearly comparable accuracy (with relative errors on the order of 10−2), the program achieves an overall speedup of approximately 40.45 on a single-GPU platform, which can be further increased to about 52.05 in high-performance application scenarios where meteorological background fields are reusable. Moreover, multi-GPU experiments reveal favorable parallel scalability across configurations ranging from one to four GPUs, and confirm that the proposed load-balancing strategy effectively enhances computational efficiency in heterogeneous GPU environments.

Analysis of the radiological impact on the Gulf region from an unexpected incident at the Bushehr nuclear power plant

Akbar Abbasi · Mayeen Uddin Khandaker · Fatemeh Mirekhtiary

Atmospheric dispersion and dose assessment of key radionuclides from a hypothetical VVER-1000 accident

Kambiz Kangarlou · Bahman Jalali Kondori · M T Holisaz · Armin Mosayebi · Behshad Valizadeh · Seyed Pezhman Shirmardi · et al.

Abstract In this study, the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model was utilized to simulate the atmospheric dispersion of major radionuclides including elements of Iodine ( 131 I, 132 I, 133 I, 134 I, 135 I), Cesium ( 134 Cs, 137 Cs), Strontium-90 ( 90 Sr), and Plutonium-239( 239 Pu) following a hypothetical accident at the VVER-1000 reactor (28.82°N, 50.88°E). Meteorological datasets from February, April, August, and October 2023 were incorporated into the model, and the corresponding inhalation and external radiation doses were evaluated using standard dose conversion factors. The simulation results demonstrated that both dispersion behavior and dose magnitude are highly influenced by meteorological parameters and the inherent physical–chemical characteristics of each radionuclide. Among the analyzed elements, 134 Cs exhibited the widest dispersion range, over a 24 h exposure period, the maximum inhalation dose (9.24 Sv) from 134 Cs and the maximum external dose from 131 I (1.28 Sv) were recorded in February. Furthermore, the maximum external dose from 134 Cs (0.22 Sv) was observed in August, and the maximum external dose from 133 I (0.04 Sv) was recorded in April. Incorporating seasonal variability and radionuclide-specific behavior into radiological impact assessments is significant. The results provide a robust scientific foundation for enhancing nuclear safety strategies, developing effective early warning systems, and optimizing emergency response and evacuation planning around nuclear power facilities.

An Integrated Tool Set for Spent Nuclear Fuel Pool Sabotage Assessment: Coupling DEPO-Based Physical Protection Effectiveness with WSPEEDI Consequence Modeling

Hamza El-Asaad

This study presents an integrated methodological framework that couples a physical protection system (PPS) performance assessment with atmospheric dispersion consequence modeling for a hypothetical sabotage scenario involving a spent nuclear fuel pool. The framework has two objectives: (1) to estimate the probability of adversary success using the design and evaluation process outline (DEPO) methodology and (2) to quantify off-site external dose consequences using the worldwide version of the system for prediction of environmental emergency dose information (WSPEEDI). Two U.S. nuclear power plants (South Texas Project and Comanche Peak) are examined as comparative case studies. A one-year meteorological and dispersion database (8760 simulations per site) is used to characterize the variability in the plume transport and deposition and to identify high-consequence scenarios.The results indicate that plausible variations in the PPS response parameters yield adversary success probabilities on the order of 10−1, while meteorological variability produces order-of-magnitude differences in the 4-day integrated external dose, as illustrated by the selected high-consequence realizations. These findings demonstrate that integrating protection effectiveness with consequence modeling provides a structured basis for comparative risk-informed assessments of spent fuel pool security vulnerabilities.

Particulate dispersion characteristics in the atmospheric boundary layer: Unraveling the effects of wind velocity profile and thermal stability

Deyi Chen · Baojie Nie · D Z Wang

Artificial Intelligence for the Determination of Factors Affecting Atmospheric Dispersion of Radionuclides, the Potential Concentration of Pollutants Downwind of a Source, to Study the Risk for Any Nuclear Facility

O.S. Ahmed · Hekmat Elbegawy · Khaled A Salman

Objectives The study’s primary goal is to use artificial intelligence programs to determine the factors influencing radionuclide atmospheric dispersion and the potential concentration of a pollutant downwind of a source.. Material and Methods These programs can provide information about atmospheric dispersion and determine the potential concentration of a pollutant downwind of a source, which is typically used to study risk analysis, emergency planning, and comprehension of the pertinent atmospheric dispersion in the study of radiological impact on man and his environment. Results The analysis demonstrated that the results of the artificial intelligence program’s atmospheric stability class correspond with the Pasquill-Guifford scheme and that the concentration of pollutants in the atmosphere is directly related to air quality, Our results for this work are shown with application. Conclusion As demonstrated by the application of artificial intelligence software tools, the concentration of pollutants decreases as the distance above ground increases at constant parameters like emission rate and height above ground. Finally, from the author’s point of view, recommended this work is used as training.