By combining long monitoring data (> halftime of Cesium 137 after the Chernobyl Accident in 1986, 13 years after the Fukushima Accident in 2011, and other events), we can improve our knowledgebase on the environmental behavior of radioactive materials and its environmental/biological impact. This should lead to improved monitoring systems in the future including emergency response systems, acute sampling/measurement methodology, and remediation schemes for any future nuclear accidents.
The following specific topics have traditionally been discussed:
(a) Atmospheric Science (emissions, transport, deposition, pollution);
(b) Hydrology (transport in surface and ground water system, soil-water interactions);
(c) Oceanology (transport, bio-system interaction);
(d) Soil System (transport, chemical interaction, transfer to organic system);
(e) Forestry;
(f) Natural Hazards (warning systems, health risk assessments, geophysical variability);
(g) Measurement Techniques (instrumentation, multipoint data measurements);
(h) Ecosystems (migration/decay of radionuclides).
The session consists of updated observations, new theoretical developments including simulations, and improved methods or tools which could improve observation and prediction capabilities during eventual future nuclear emergencies. New evaluations of existing tools, past nuclear contamination events and other data sets also welcome.
Understanding the transport of 137Cs released during the Fukushima accident remains challenging, as existing source terms fail to adequately capture the critical emissions leading to the high-deposition zone. For the problem, this study presents an objective inverse reconstruction method that uses total deposition and atmospheric concentration data. The deposition data is used to extract the a-priori emissions by novel identifying the critical temporal formation process of these depositions in high-deposition areas, with the help of the WRF-Chem model, and deriving the corresponding emissions. This deposition-based prior was then fused with the concentration data within an inversion framework, compensating the spatiotemporal information of incomplete data and ensuring the continuity feature of the emissions.
The reconstructed source term reveals two prominent emission peaks on March 15, 2011, occurring between 10:00-11:00 and 14:00-15:00. These peaks align with in-situ pressure measurements and accident analysis, suggesting that they were caused by pressure drops in the primary containment vessels of Units 3 and 2, respectively. This finding provides an explanation for the observation of spherical 137Cs particles, likely formed through the condensation of vaporized or liquefied substances. The reconstructed source term also independently validates the widely adopted reverse estimation results by JAEA.
Simulations based on the reconstructed source term show significantly better agreement with various observational data than simulations using other source terms. The two-peak emission pattern accounts for the high-deposition areas, supporting the accuracy of the reconstruction. Furthermore, the proposed method outperforms traditional direct fusion approaches that combine deposition and atmospheric concentration data, which often fail to provide satisfactory results due to insufficient temporal information in deposition observations.
This new method offers a powerful tool for multi-observation fusion, providing a more accurate extraction of temporal information from total depositions. It represents a significant advancement in source term reconstruction, especially for complex nuclear accidents. The approach has broader implications for understanding the transport of short-lived radionuclides, with potential applications in iodine emission reconstruction, thyroid dose evaluation, and improving future environmental assessments in nuclear accident scenarios.
How to cite: Fang, S., Dong, X., Xu, Y., and Hu, H.: Uncovering the Key 137Cs Emission Sources Contributing to High-Deposition Zones After the Fukushima Accident, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20921, https://doi.org/10.5194/egusphere-egu25-20921, 2025.
Thirteen years have passed since the accident at the Fukushima Daiichi Nuclear Power Plant, but the levels of Cs-137 and H-3 near the power plant have not returned to the levels they were at before the accident. In addition, the levels of Cs-137 and H-3 near the power plant continue to be higher than in other areas of the sea. This suggests a persistent leakage from the power plant or the surrounding sea area. However, the mechanism of the leakage is unknown. As the estimated rate of leakage outside the port is higher than the estimated rate of leakage inside the port, it is also possible that the leakage is not via the port.
The ratio of radioactive material concentration does not change in seawater over a short period of time, so it is useful for estimating the source of leakage. Here, we focused on the ratio of H-3 and Cs-137 and analyzed the data.
After 2016, the concentration of Cs-137 near the power plant has hardly decreased.
The concentration of Cs-137 and H-3 is high in the port area and low outside the port area. However, the H-3/Cs-137 ratio is small in the port area and large outside the port area. This suggests that the concentration of Cs-137 and H-3 in the port area does not necessarily affect the concentration outside the port area, and there is a possibility that there is another source.
The H-3/Cs-137 ratio fluctuates greatly over time. This may be due to the presence of multiple sources with different H-3/Cs-137 ratios, or it may be a sampling issue due to large fluctuations in concentration over time and space.
We have now started analyzing the H-3/Cs-137 ratio in nearby river water and groundwater and will discuss the relationship between these at the time of the presentation.
How to cite: Godse, N. S., Tsumune, D., Kato, H., and Onda, Y.: Understanding H-3/Cs-137 Behavior to Track Dispersion Sources in Fukushima’s Marine Environment, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14589, https://doi.org/10.5194/egusphere-egu25-14589, 2025.
The world has experienced three major nuclear accidents (Chernobyl, Three Mile Island, and Fukushima). We have accumulated a vast amount of data from those accidents as well as from less severe nuclear accidents and incidents tracked in the nuclear industry. It is time for us to develop an open knowledge base that gathers and shares nuclear accident-related data and enables users to utilize those data to prevent future nuclear accidents and implement effective remediation measures when an accident occurs. However, nuclear-related data have peculiar challenges when it comes to understanding and organizing the data because of the behavior of radioisotopes. Having examined the nuclear accident literature, we identified four data axes that are important to organize nuclear accident data systemically. Those axes are: (1) historical time flow vs. nuclear decay (logarithmic radioactive decay), (2) temporal extent affected by radioactive decay vs. spatial extent affected by environmental processes, (3) contamination vs. non-contamination (background) comparison for which a comparison method is decided upon (1) and (2), and (4) radioactivity vs. dose (health risk inflicted on organisms) as a result of exposure to radioactivity. These four axes need to be considered in every step related to nuclear accidents.
For example, when a nuclear accident occurs, the first step is to assess the level of radioactive contamination in the nearby environment. Distinguishing the accident-derived radioactivity from the background radioactivity [axis 3] is crucial to implementing evacuation and remediation procedures and assessing health risks [axis 4]. However, comparing accident-driven radioactivity against the background activity is not straightforward. Identifying a proper background location and collecting a sample involves spatial and temporal considerations [axis 1, 2], such as sampling distance, direction, depth, sampling timing, sampling frequency, etc. So far, a data organization scheme for nuclear accidents has not been established despite the vast amount of accident/incident data accumulated and the possible severe implications of nuclear accidents to society.
We propose ontology as a tool that addresses the peculiar nature of nuclear data and systematically organizes the knowledge we have acquired on nuclear accidents. Ontology originated as a metaphysical study in the field of philosophy to study the properties and relations of all involved entities. With the help of ontology, we provide formal definitions of the entities within the nuclear accident knowledge domain and connect those entities with logical rules. In this study, as the first step of nuclear accident ontology building, we present an ontology-based conceptual model on background comparison for environmental radioactivity utilizing a well-established Basic Formal Ontology (BFO) for upper-level ontology and several ontology models that have been developed in the sub-fields of the nuclear and energy industries. The rule-based entity structure based on ontology will contribute to building a comprehensive knowledge base for nuclear accidents. Our aim is to build a knowledge base adaptable to machine learning that will shorten the time needed for nuclear accident data search and provide insights into the best practices to minimize the adverse effects on humans and the environment from nuclear accidents.
How to cite: Yasumiishi, M. and Bittner, T.: Developing Ontology-Based Nuclear Accident Knowledge Base Part 1: Spatiotemporal Considerations in Background Comparison, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5199, https://doi.org/10.5194/egusphere-egu25-5199, 2025.
The 2011 Fukushima Daiichi Nuclear Power Plant (FDNPP) accident released significant amounts of radioactive Cesium-137 (137Cs). Both dissolved and suspended forms of 137Cs contribute to river runoff. Although the Ministry of the Environment has monitored 137Cs in Fukushima river-bottom sediments since 2011, identifying long-term trends is challenging. Existing adsorption/desorption models focus on ideal lab conditions and lack real-world field data. This study uses long-term monitoring data to examine changes in 137Cs concentration in river sediments. Sediment samples were collected every four months, while river water and suspended sediment were sampled quarterly. The model simulates adsorption/desorption reactions between river water and sediments, incorporating fast and slow reaction sites. By adjusting reaction rates, measured and modeled 137Cs concentrations were optimized. Results show 137Cs concentrations in particle-size-corrected sediments aligned with suspended forms within a year. An increase in 137Cs concentration at 45 sites was observed, a phenomenon not seen in dissolved or suspended forms. The distribution coefficient (Kd) of river bottom sediments fluctuated significantly in the first three years. Slow adsorption dominated 137Cs accumulation within six months, while its effect on suspended concentrations was negligible. These findings highlight that slow adsorption/desorption processes are critical for the long-term behavior of 137Cs in river-bottom sediments.
How to cite: Onda, Y., Wada, N., Igarashi, Y., and Smith, J.: Field-Based Modeling of Cesium-137 Adsorption/Desorption Reactions in Fukushima River bottom Sediment, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14888, https://doi.org/10.5194/egusphere-egu25-14888, 2025.
The Fukushima Daiichi Nuclear Power Plant accident, triggered by the Great East Japan Earthquake on March 11, 2011, caused large-scale radioactive contamination across terrestrial areas. Among the released radionuclides, Cesium-137 remains a significant source of radiation due to its long half-life, resulting in persistently high ambient dose rates in contaminated forests. To reduce these dose rates, forest thinning is being implemented as a radiation countermeasure. However, its effectiveness and the specific mechanisms through which thinning influences dose rates remain unclear. This study focuses on the relationship between forest thinning, throughfall, soil moisture, and ambient dose rates. Previous research has shown that rainfall temporarily reduces dose rates by increasing soil moisture, which attenuates gamma radiation from Cesium-137 in the soil. Building on these findings, we investigated the impact of thinning on rainfall reaching the forest floor and its subsequent effect on dose rates. Field studies were conducted at two sites, Iitoi and Fuyuzumi, located approximately 40 km northwest of the FDNPP. Thinning was implemented from October to December 2022, and monitoring devices were installed in April 2024. Results show that thinning increases throughfall and soil moisture, reducing dose rates over time. Soil moisture in thinned plots rose from 33.1% to 35.0%, while control plots decreased from 28.6% to 25.5%. Correspondingly, ambient dose rates dropped from 0.9 μSv/h to 0.75 μSv/h in thinned plots, compared to 0.85 μSv/h in control plots. Based on these observations, we developed a long-term predictive model to estimate ambient dose rates from rainfall and soil moisture data, providing a generalized framework for assessing the long-term impact of forest management on radiation levels in contaminated areas.
How to cite: Uehara, Y., Onda, Y., Takahashi, J., Nakanishi, M., Zhang, Y., and Takamura, S.: Elucidation and modeling of the effects of forest management on air dose rates, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14919, https://doi.org/10.5194/egusphere-egu25-14919, 2025.
The environmental and health effects of the transport and diffusion of pollutants released into the atmosphere and ocean due to a nuclear accident must be evaluated rapidly and accurately to ensure the safety of the surrounding population and ecosystem. Since the Fukushima accident in 2011, a web-based nuclear emergency support system named Radiological Accident Preparedness System in Korea (RAPS-K) has been developed to predict the dispersion of radioactive materials released into the environment and estimate dose assessment for humans. The system is composed of atmospheric dispersion, marine dispersion, and dose assessment models, along with a graphic user interface module. It can evaluate the dispersion patterns of radionuclides in the air and ocean, and the short-term and long-term radiological effects of a nuclear accident on humans. The atmospheric dispersion, marine dispersion, and dose assessment models have already been validated by model-to-model comparisons and measurements from the Chernobyl and Fukushima accidents. Especially, atmospheric dispersion model is connected with numerical weather forecast data produced by Korea Meteorological Administration (KMA) in real-time and the air conentrations are rapidly calculated in the system. Atmospheric dispersion model named LADAS(Lagrangian Atmospheric Dose Assessment System) was applied to evaluate the behavior of radioactive material released into the air for the hypothetical nuclear accident. RAPS-K is now operating through a web Graphic User Interface (GUI) on Linux OS. The developed system covers the Northeast Asian and worldwide regions in the event of a nuclear accident.
How to cite: Suh, K.-S., Park, K., Min, B.-I., Kim, S., Choi, Y., Kim, J., Kim, M.-C., KIm, H., and Kim, K.-O.: Atmospheric Dispersion Model for a Nuclear Accident using RAPS-K, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1280, https://doi.org/10.5194/egusphere-egu25-1280, 2025.
In this study, the FLEXPART atmospheric transport model was used to simulate the atmospheric transport of Cs-137 following the Fukushima NPP accident in March 2011, using the source term estimation described in [1]. The simulation results were compared with airborne concentration measurements conducted in Japan and globally. It was shown that FLEXPART results as compared to Fukushima are highly sensitive to assumptions regarding size distribution of the radioactivity in the source. Based on our study, 'conventional' assumptions regarding the mean aerodynamic diameter (MAD) of particles, which are typically reported in the range of 0.2 to 0.7 μm in various studies, yielded reasonable agreement between simulated and observed concentrations within Japan. However, at greater distances from the source (e.g., across Eurasia), our results showed that the calculated concentrations were significantly overestimated. As discussed in our study, the size distribution of particles in the plume evolves over time. Therefore, measurements of AMAD conducted in Europe [2], which report a similar range of AMAD values, may not be representative enough to determine the initial AMAD at the source. To address this, we curve-fitted the observed size distribution of emitted particles measured in Japan shortly after the accident, as presented in [3]. This approach resulted in the following estimates for the size distribution: AMAD ≈ 2.5 μm and geometric standard deviation (GSD) ≈ 1.8. Simulations conducted with these updated size distribution parameters showed significant improvement in the agreement between calculated and observed airborne concentrations, as compared to using conventional assumptions.
References
- 1. Terada H, Nagai H., Tsuduki K., et al. (2020) Refinement of source term and atmospheric dispersion simulations of radionuclides during the Fukushima Daiichi Nuclear Power Station accident, Journal of Environmental Radioactivity, Volume 213,106104, https://doi.org/10.1016/j.jenvrad.2019.106104
- 2. Masson O., Ringer W., Malá H., et al. (2013) Size Distributions of Airborne Radionuclides from the Fukushima Nuclear Accident at Several Places in Europe. Environmental Science & Technology 47 (19), 10995-11003 DOI: 10.1021/es401973c
- 3. Miyamoto Y., Yasuda K., Magara M., (2014) Size distribution of radioactive particles collected at Tokai, Japan 6 days after the nuclear accident, Journal of Environmental Radioactivity (132) 1-7, https://doi.org/10.1016/j.jenvrad.2014.01.010
How to cite: Kim, K. O., Kovalets, I., and Park, C.-W.: Evaluation of the parameters of size distribution of emitted aerosols for simulation of radionuclides atmospheric transport following Fukushima accident using FLEXPART model, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2670, https://doi.org/10.5194/egusphere-egu25-2670, 2025.
Since the mid-20th century, exposure to radioactive materials has occurred through various sources, such as nuclear tests, nuclear safety incidents, and releases from reprocessing plants. These materials have undergone global fallout and deposition through ocean-atmosphere circulation. This study aims to calculate the global spatial distribution of radioactive fallout on the Earth's surface based on observational data (fallout database), assuming wet deposition processes, and to evaluate temporal changes. The results will be utilized in a global climate model (GCM), Geophysical Fluid Dynamics Laboratory Earth System Model Version 4 (GFDL-ESM4), to better understand the patterns of deposition. Through this approach, we aim to estimate the extent of radioactive diffusion into the atmosphere and ocean and the subsequent accumulation in biological resources. Furthermore, this study investigates to assess how early 21st-century climate change may influence the global spatial variations of radioactive fallout and deposition.
How to cite: Seung-Hwon, H. and Hyung-Gyu, L.: Study of fallout distribution based on the wet deposition of major radiochemical species and application on the global climate model, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2690, https://doi.org/10.5194/egusphere-egu25-2690, 2025.
Tritium is a radioactive substance released into the environment through air and water systems during nuclear facility operation, potentially affecting ecosystems. Understanding its concentration variations is essential. This study analyzed tritium concentrations measured in air (unit: Bq/m³) and rainwater (unit: Bq/L) from 2011 to 2022 to evaluate the reliability of sampling methods for atmospheric and precipitation samples. A multi-faceted analysis was conducted using variables such as precipitation, release rates, and seasonal factors. The results showed that increased precipitation led to decreased tritium concentrations in rainwater at all locations, with significant dilution effects observed in northern and western monitoring points (approximately -0.0309 Bq/L and -0.0301 Bq/L per 1mm precipitation increase, respectively). Tritium concentrations in the air also tended to decrease with increasing precipitation, although the magnitude of variation was smaller compared to rainwater. A statistically significant correlation between increased precipitation and decreased air tritium concentrations was observed at the eastern monitoring point (P < 0.01). Comparing tritium concentrations across seasons under similar precipitation conditions revealed no significant differences in most cases; however, slightly higher concentrations were found in winter. This may be related to specific factors such as temperature conditions or emission patterns during winter. This study quantitatively confirmed the environmental behavior of tritium and its dilution effect by precipitation, providing crucial baseline data for the long-term management of radioactive substances around nuclear facilities and contributing to the evaluation of sampling methods' reliability.
How to cite: Yun, J., Lee, J., and Lim, J.-M.: Analysis of the Impact of Precipitation on Tritium Concentrations Based on Nuclear Facility Operation Data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7764, https://doi.org/10.5194/egusphere-egu25-7764, 2025.
We recently developed a marine environment exposure dose assessment model to evaluate the radiological doses to the public following marine radiological accidents. The following six exposure pathways were considered: external exposure through beach activity, swimming, and boating and internal exposure through inhalation via sea spray, ingestion of seawater during swimming and ingestion of seafood. A model for estimating radionuclide concentration in marine organisms in the present dose assessment model was developed based on the equilibrium model, taking into account realistic aspects related to food intake and data availability related to model input variables. However, when the equilibrium model was applied in the early phase of an accident in which the radionuclide concentration changes significantly, there is a possibility that the evaluation result of nuclide concentration in marine organisms could be overestimated, so a dynamic marine foodchain model was added to the equilibrium model-based marine dose assessment module so that it can be selectively applied according to the purpose of the assessment. When applying the dynamic model, the limitations of the model to the uncertainty about the input variables and assessment results due to the lack of available data must be considered. The dynamic model considered three groups of seafood (fish, invertebrate, seaweed), as in the equilibrium model. The model contains compartments for water, sediment, and marine organism groups. The radioactivity transfer for compartments is dynamically modeled by a first-order differential equation using rate constant. Radioactive decay is considered in all compartments. To the next step, it is planning to develop a module that can evaluate the public exposure doses by linking the dose assessment model with the marine dispersion model, and apply it to the case study for calculating the public exposure following hypothetical marine radiological accidents.
How to cite: Kim, S., Suh, K.-S., Keum, D.-K., Min, B.-I., Choi, Y., Kim, J., Kim, M., Kim, H.-J., and Park, K.: Improvement of a model for estimating radionuclide concentration in marine organisms in a marine environment exposure dose assessment model, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2649, https://doi.org/10.5194/egusphere-egu25-2649, 2025.
According to the World Nuclear Association, the capacity of nuclear power plants around the world is growing steadily. In detail, about 60 reactors are under construction among which 29 reactors are to be launched by 2025 with 19 reactors located on the coast. This increases the risk of radioactive contamination of ocean waters in the case of potential nuclear accidents. Rapid growth of NPPs amount around the world requires the development of the global model that can simulate the release of radioactive materials from any NPP and assess its impact on the adjacent local/regional seas and global ocean. The compartment model POSEIDON with the new global system of boxes could be such a model which simulates transport of a wide range of radionuclides in the marine environment including marine food chains and calculates doses to humans from seafood consumption. Also, the model operates with both atmospheric and direct releases of radionuclides to the marine environment.
A new global system of boxes for the POSEIDON-GM (Global Model) has been developed which consists of 437 boxes of variable sizes. Most ocean boxes have 4 vertical layers in the water column: first surface layer with a depth of 30 m, second layer between 30 and 200 m depth, third layer between 200 and 1000 m depth, and fourth layer below 1000 m. Boxes with an average depth of less than 1000 m have fewer vertical layers depending on their depth. Water fluxes between boxes were calculated from the Global Ocean Physical Multi-Year product by Copernicus Marine Environment Monitoring Service, which contains monthly mean circulation data averaged for 1993-2016.
Annual depositions of 137Cs and 90Sr in each box of the POSEIDON-GM due to the global fallout have been calculated using data of deposition density from UNSCEAR for the 1945-1987 period with extrapolation for the 1988-2020 period. The transport of 137Cs and 90Sr entered the World Ocean due to global fallout has been simulated by POSEIDON-GM. Calculated concentrations of both radionuclides in water have been compared with measurement data from the MARIS database for the Southern Hemisphere, where the global fallout was the dominant source of radioactive contamination.
The next stage of the POSEIDON-GM development will include consideration of other sources of radioactive contamination, such as local sources from nuclear weapon tests, releases from nuclear reprocessing plants, sources due to Fukushima and Chornobyl nuclear accidents, etc. The model results will be compared with measurement data for concentrations of radionuclides in water and from different trophic levels of marine organisms from around the World Ocean.
How to cite: Jung, . T., Bezhenar, R., Maderich, V., Bezhenar, Y., and Kim, H.: Development of the POSEIDON-GM–box-based radioactivity transport model for the global ocean: preliminary results of Cs-137 and Sr-90 distributions due to global fallout, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2671, https://doi.org/10.5194/egusphere-egu25-2671, 2025.
13 years after the Fukushima nuclear accident, the coastal area in front of the Fukushima Dai-ichi Nuclear Power Plant remains contaminated. First, it relates to the bottom sediments, which were contaminated with Cs-137 during the accidental and post-accidental releases. Additional contamination of bottom sediments could be caused by river runoff of Cs-bearing microparticles, which were formed in the initial phase of the accident, dispersed in the atmosphere, and fell into the watershed of nearby rivers. Cesium may be preserved in such particles for a long time due to its insoluble characteristics. River runoff carries suspended particles along with Cs-bearing microparticles to the coastal areas of the ocean, especially during heavy rains.
In the study, we applied the Lagrangian particle tracking model Parcels to identify places of potential deposition of such Cs-bearing microparticles in the Fukushima coastal area. As input data we used
- 3D circulation data from the detailed ROMS-based ocean circulation model customized to the Fukushima coast for the period 2013-2016;
- Estimates of released Cs-bearing microparticles from rivers during heavy rains in selected period;
- Estimates of microparticles’ sizes define the vertical velocity of their falling in the water column.
Lagrangian particles simulated the transport of Cs-bearing microparticles, which were released from the Abakuma River mouth, by the coastal currents taking into account Stokes settling velocity. Maximums in the distribution of such particles on the bottom identified areas with possible accumulation of Cs-bearing microparticles in the coastal area after heavy rains. Distributions for different particles’ sizes obtained in simulations were analyzed.
How to cite: Bezhenar, R., Takata, H., Tsumune, D., Maderich, V., and Tateda, Y.: Sedimentation areas along the Fukushima coast for Cs-bearing microparticles from the Lagrangian particle tracking, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8294, https://doi.org/10.5194/egusphere-egu25-8294, 2025.
As part of the decommissioning work at the Fukushima Daiichi Nuclear Power Plant, the discharge of ALPS-treated water began in August 2023. ALPS-treated water contains not only H-3, but also other nuclides, albeit at extremely low concentrations. ALPS-treated water is treated so that the total of the concentration ratios of the 30 target nuclides is less than 1, and then diluted so that the H-3 concentration is less than 1500 Bq/L before being discharged. Prior to discharge, a radiation impact assessment was carried out by TEPCO. This assessment used a marine dispersion model that had been verified using observation results for Cs-137 that had leaked out as a result of the Fukushima Daiichi Nuclear Power Plant accident.
The ocean dispersion model was a 1 km x 1 km ROMS model with a variable mesh that was refined to 200 m x 200 m in the vicinity. It was driven by meteorological reanalysis data from the Japan Meteorological Agency, and data assimilation was performed using JCOPE2M ocean reanalysis data to reproduce the Kuroshio and mesoscale eddies.
In this assessment, a H-3 concentration of 0.1 Bq/L was used as the background concentration from atmospheric nuclear testing. However, a concentration of 1 Bq/L of H-3 was observed even before the release, and this is thought to be due to the influence of the supply from the power plant site or surrounding areas, or from rivers. After taking into account the influence of these background concentrations, the results of the model simulations were verified against the results of the monitoring of H-3 concentrations. Because the rate of release of the ALPS processed water was small, the range of influence of the monitoring of H-3 concentrations was limited, but the verification results were consistent. It is necessary to determine the average distribution by continuing to monitor in the future.
How to cite: Tsumune, D., Tsubono, T., Misumi, K., Okamura, T., Abe, H., Kato, H., and Onda, Y.: Simulation of the impact assessment of the discharge of ALPS treated water into the ocean, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14834, https://doi.org/10.5194/egusphere-egu25-14834, 2025.
Anthropogenic radionuclides were released into the world's oceans as a result of large-scale weapons testing in the late 1950s and early 1960s. These anthropogenic radionuclides have long lifetimes and are still present in the oceans today. The behavior of long-lived radionuclides is useful for seawater circulation in the global ocean.
In this study, we focus on the spatiotemporal variations in the 137Cs and 90Sr activity concentrations in the surface seawater and vertical distributions. Most of data were included into the database, Historical Artificial radioactivity database in Marine environment, Global integrated version 2021 (Inomata and Aoyama, 2023). The ratio of 137Cs to 90Sr from large-scale nuclear tests was reported by Harley et al. (1965) to be 1.45. These ratios were in agreement with the average value of the ratio found in open ocean seawater (1.43±0.70) (Bowen et al., 1974). However, the ratios analysed in the present study did not always consistent with the reported values. This may be due to the different behaviour of 90Sr and 137Cs, e.g. 137Cs is mainly present in the dissolved form, whereas 90Sr is incorporated into particles in seawater. Furthermore, the 90Sr/137Cs ratio may be closely related to seawater circulation. However, as data on 90Sr are very scarce compared to 137Cs, detailed analysis of long-term variations in the 137Cs/90Sr ratio is limited to the North Pacific Ocean and its marginal sea.
The results showed that the 137Cs/90Sr ratio varied in the northern North Pacific and adjacent waters (northern North Pacific Ocean (NNPO), western North Pacific Ocean (WNPO), Sea of Japan (SOJ), Sea of Okhotsk (OKH) and East China Sea (ECS)). The apparent half-life (Tap) of 90Sr in ECS were longer than those in other area. Considering that a longer Tap indicates a larger inflow into the area and a shorter Tap indicates a lower inflow, it can be assumed that the OKH has sources of 137Cs and 90Sr. At some SOJ stations, the ratio of 90Sr/137Cs was large at depths greater than 2000 m. Furthermore, inventories of 137Cs and 90Sr have increased since 1990 at the SOJ stations. The increase in inventories may be attributed to the dumping of radioactive material.
How to cite: Inomata, Y., Tsumune, D., and Hirose, K.: Long term variations of 137Cs and 90Sr distribution in the Sea of Japan , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16740, https://doi.org/10.5194/egusphere-egu25-16740, 2025.
When radiation exposure occurs, evaluating the radiation dose is necessary to assess the risk and implement appropriate protective measures. Typically, radiation workers use personal dosimeters, which conservatively calculate the effective dose based on measured values. However, in scenarios involving potential high radiation exposure, emergency response tasks, or accidental exposure, precise dose evaluation is crucial. Conventional methods estimate human dose from dosimeter readings by applying dosimeter-to-human dose conversion factors under the assumption of a parallel radiation field, but this can introduce significant errors when the radiation field is inhomogeneous.
In this study, Deep Neural Networks (DNN) was applied to rapidly estimate absorbed doses to humans and dose conversion factors in inhomogeneous radiation fields. It was assumed that the radiation field can be described by the location and energy distribution of point sources, and the basic exposure scenario was set to external exposure by a standing adult male from a point source. Through GEANT4-based Monte Carlo simulations, absorbed doses to radiation-sensitive organs and whole-body were calculated, and conversion factors between chest-worn dosimeters and organ doses were determined.
Due to significant skewness in dose data, statistical techniques that transform the data to approximate a normal distribution, such as log transformation and Box-Cox transformation, to facilitate more effective training. The transformed dataset was divided into training, validation, and test sets. Optimization of model hyperparameters was performed using training and validation data and optimized model was trained. The model's predictive performance was verified by evaluating its relative error rate in predicting test data compared to ground truth values. The prediction results demonstrated an acceptable relative error rate, factoring in the uncertainty inherent in simulation-derived data. The results of this study are expected to provide a foundation for easily and quickly assessing the predicted risk to the human body when radiation exposure occurs in an unexpected inhomogeneous source distribution situation. This will help to quickly determine follow-up measures.
How to cite: Choi, Y., Kim, H., Kim, M. C., Kim, S., Min, B.-I., Kim, J., Suh, K.-S., and Lee, J.: Deep Neural Network for risk assessment via organ dose estimation in inhomogeneous radiation fields, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2406, https://doi.org/10.5194/egusphere-egu25-2406, 2025.
The 3H and 36Cl radionuclides, released during the Fukushima nuclear accident in 2011, contaminated forested environments. However, the opportunity to periodically observe these radionuclides was lost due to the catastrophic conditions caused by the earthquake and tsunami associated with the accident. The concentrations of these released nuclides in precipitation and their fates are critical when considering the effects of internal exposure. Given that 3H and 36Cl are reliable hydrological tracers, records of their continuous depositional flux within unsaturated soil layers could provide valuable insights into the contamination levels during the initial years after the accident. Such records are indispensable for understanding the extent of contamination. Using a borehole drilled in 2014 at Koriyama, 60 km from the accident site, we reconstructed the deposition record of atmospheric 3H and 36Cl following the accident. The contributions of 3H and 36Cl from the accident were determined to be 1.4 × 1013 and 2.0 × 1012 atoms m−2, respectively, at this site. Unlike approaches based on radionuclide migration analysis, the 3H and 36Cl concentrations in precipitation during the approximately six weeks following the accident were accurately recovered (607 Bq/L and 4.74 × 1010 atoms/L, respectively) by analyzing the depositional flux in the unsaturated soil column from depths of 0 m to 4.25 m. Both the 3H and 36Cl concentration profiles were reassessed at the site in 2016. By that time, both soluble radionuclides had mostly been flushed out of the unsaturated soil zone due to rainfall over the 5.6 years since the accident. Although 3H concentrations in the unsaturated soil water and shallow groundwater had returned to less than 6 tritium units (TU), the 36Cl concentration had not yet returned to the natural cosmogenic background deposition level. In contrast, 129I was primarily found in the litter layer and the soil near the ground surface.
How to cite: Ohta, T., Fifield, K., Palcus, L., Tims, S., Pavetich, S., Matsuzaki, H., Tsumune, D., and Mahara, Y.: Record of the Fukushima nuclear accident in unsaturated soil water and the fate of nuclear contamination, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3386, https://doi.org/10.5194/egusphere-egu25-3386, 2025.
The Radiocaesium (¹³⁷Cs) released as a result of past and potential nuclear accidents is of great concern for agriculture because of the relatively long half-life and easy absorption by plants. A countermeasure is the use of potassium fertilizers, but the relationship between transferability from soil to crop and exchangeable potassium (Ex K) varies depending on the soil. Previous studies have suggested that exchangeable ¹³⁷Cs (Ex ¹³⁷Cs) and the solid/liquid distribution coefficient (Kd) can be important factors explaining the variability of the ¹³⁷Cs dynamic in soil. However, the methods to measure these soil parameters are not suitable for adequate emergency deployment and preparedness because they are expensive and time consuming.
Mid-infrared spectroscopy (MIRS) has been shown to predict soil parameters more quickly and cost-effectively. However, the prediction of Cs parameters (Ex ¹³⁷Cs, Kd) using MIRS has not yet been evaluated. This study aims to evaluate whether MIRS can predict Cs-related parameters such as Kd, Ex 137Cs/Total 137Cs, and other parameters that may influence on the behavior of 137Cs in the soil, such as total carbon (soil total C).
The 1,682 samples were collected in Fukushima Prefecture, Japan from 2013 to 2020, most of them are Andosols. Each soil property (soil total C, Ex 137Cs/Total 137Cs ) was obtained from the monitoring data of MAFF and NARO. As for Kd for 133Cs, 176 samples were measured at Hokkaido University using ICP-MS. Each sample was dried at 37°C for at least one night and then sieved to less than 0.2 mm before measurement. The spectra data was obtained with four replicates in each soil sample using MIRS. To date, a total of 1,419 samples have been analyzed and their properties predicted using partial least squares regression (PLSR).
The PLSR models provided a relatively high accuracy for the prediction of soil total C, where the R2 (coefficient of determination) was 0.9±0.01. However, low accuracy was observed in the prediction of Kd for 133Cs, where the R2 was 0.46±0.06, which was attributed to the low concentration of the data and the limited number of samples. On the other hand, the result of Ex 137Cs/Total 137Cs showed relatively higher value then Kd for 133Cs, where the R2 was 0.56±0.04. Variable importance on projection Ex 137Cs/ Total 137Cs suggests that wavelength range related to clay mineralogy, quartz, and organic matter are influential in the estimation of Ex 137Cs/Total 137Cs.
To further evaluate the potential for MIRS for rapid and affordable prediction of Radiocaesium risks, additional samples will be analyzed to improve the representativeness of the model and broaden the dataset, and more modeling techniques (Cubist, Support Vector Machine, etc) will be applied.
How to cite: Iwai, J., Dercon, G., Vlasimsky, M., Albinet, F., Maruyama, H., and Shinano, T.: Predicting soil Radiocaesium uptake and dynamics using Mid-Infrared Spectroscopy (MIRS), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10714, https://doi.org/10.5194/egusphere-egu25-10714, 2025.
Radioactive cesium-bearing microparticles (CsMPs) were insoluble glassy matrixes derived from Fukushima Daiichi Nuclear Power Plant accident. CsMPs have greater radioactive cesium (Cs) concentration per unit mass than other particles adsorbing Cs such as clay and organic particles (i.e., particulate Cs). In addition, the size of CsMPs was about a few µm. CsMPs may move around the environment as in the case of particulate Cs. Therefore, there is a concern for an internal exposure when CsMPs may enter the living organisms. Furthermore, previous studies have shown that CsMPs may attach to soil and crops, and locally increase Cs concentration of them. On the other hand, the difference of particulate Cs and CsMPs is Cs desorption from those particles. For particulate Cs, some Cs may electrically adsorb onto clay planar site and functional groups, therefore, their Cs may be exchanged with other cations, desorbed, and adsorbed by the crop through the roots. However, Cs in the CsMPs is included in in soluble grassy matrixes. In other words, it is considered that Cs in the CsMPs may be difficult for crops to absorb. Transfer factor (TF) is used to evaluate transfer of Cs from soils to crops. However, the conventional TF is a simple ratio of Cs concentrations between soils and crops. This suggests that conventional TF may not be able to accurately assess Cs transfer from soils to crops, since Cs in the soils contains a mixture of Cs with different crop availability. Since there are many contaminated forest areas in Fukushim, it is necessary to evaluate secondary contamination due to the inflow of Cs and CsMPs from these areas into farmland after decontamination.
In this study, we investigated the changes of Cs and CsMPs deposition in the paddy field in the first year of resumption of farming after the accident. Furthermore, we evaluate the contribution of CsMPs on particulate Cs to grasp the impact of CsMPs on TF of brown rice.
As a result, the accumulation of Cs and CsMPs increased in the entire field of this study in the period from plowing to harvest. The deposition of Cs per unit area increased in the center and the four corners of the paddy field other than inlet and outlet. This may be due to the deposition of suspended matter in areas with relatively litte water movement. On the other hand, there was no clear trend for CsMPs deposition in the paddy filed. This is because CsMPs were only detected in some of the soil samples, and the amounts varied depending on the soil. The Cs concentration in brown rice was less than 100 Bq kg-1-FW in all samples. This indicated that safe rice could be produced on this study site after decontamination. Furthermore, there was no significant difference between TF values with and without the contribution of CsMPs to Cs concentration in the soil. This suggested that there was no problem to evaluate TF using conventional methods for the paddy filed in Fukushima Prefecture.
How to cite: Tatsuno, T., Nihei, N., and Yoshimura, K.: The impact of radioactive cesium-bearing microparticles on Cs transfer factor of brown rice on the paddy field in the first year of resumption of farming, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3130, https://doi.org/10.5194/egusphere-egu25-3130, 2025.
The Arctic Ocean and the North Pacific are the main reservoirs of anthropogenic radionuclides introduced in the past 80 years. The Lagrangian particle tracking approach was applied to the Arctic oceans to study the pathways of 137Cs contamination from point sources representing the locations of solid radioactive waste in the bays of the Novaya Zemlya archipelago and in the Kara Sea. The model includes radioactive decay and the interaction of dissolved radionuclides with suspended and bottom sediments. Lagrangian model uses accurate approach for simulating the absorption-desorption processes and novel algorithm for the bottom boundary conditions. As input for the model, the 3D hydrodynamic fields from NEMO model simulation with 10 km horizontal resolution and 121 vertical layers were used. 3D velocity fields along with vertical velocity and vertical turbulent mixing coefficient were used from NEMO simulation for 38 years from 1980 to 2018. Suspended sediment concentration fields were reconstructed using the 1D SEDTRANS05 sediment transport model in each grid node.
A set of potential scenarios of radioactive release were considered to analyse the most probable pathways of contamination. In each simulation, 1M of particles was used and individual trajectories were stored. The maps of visitation probability were built to show pathways of radioactivity contamination in the Arctic Ocean from the selected sources.
How to cite: Brovchenko, I., Maderich, V., Lambin, C., and Martazinova, V.: Lagrangian pathways of 137Cs released from multiple sources in the Arctic Ocean, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10014, https://doi.org/10.5194/egusphere-egu25-10014, 2025.
Large-scale nuclear accidents may contaminate large areas of land with long-lived radionuclides such as 137Cs. Rivers are important pathways for transporting these radionuclides from upstream to downstream. The 137Cs concentration released during the Chornobyl nuclear accident has been shown to decrease over time. Previous studies also have shown that the concentration of 137Cs in rivers is influenced by competing ions, hydrological processes, the amount of adsorption sites on suspended particles, and the land cover of the catchment. However, comparative studies between rivers are limited, and the factors that determine the variation in 137Cs concentrations in rivers remain unclear. In this study, we collected time-series measurements of 137Cs from nine major rivers across Europe, each from different regions and countries affected by varying environmental conditions. We also characterized the properties of each river’s catchment, including land cover, water chemistry, and hydrological characteristics. By linking the 137Cs concentration data with these catchment attributes, we aimed to identify the most significant factors influencing 137Cs transport. Our findings reveal a quantitative relationship between the transport of 137Cs and the catchment characteristics, highlighting key factors that control radionuclide behavior in rivers. These results can be used for long-term predictions of radionuclide transport in rivers, which is crucial for risk assessment and management in regions affected by nuclear accidents.
How to cite: Igarashi, Y., Onda, Y., and Smith, J.: Long-term trends in 137Cs concentrations in rivers across Europe originating from Chornobyl, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14889, https://doi.org/10.5194/egusphere-egu25-14889, 2025.
Posters virtual: Tue, 29 Apr, 14:00–15:45 | vPoster spot 4
EGU25-4077 | ECS | Posters virtual | VPS19
Multiscale model coupling for watershed-scale contaminant transport modeling from point sources in Savannah River SiteTue, 29 Apr, 14:00–15:45 (CEST) | vP4.4
Soil and groundwater contamination at some sites impacts downstream populations when contaminants migrate from groundwater to rivers. Predictive modeling is challenging since it is required to include detailed subsurface structure and groundwater flow models within the site, as well as watershed-scale models for large-scale transport. Now that climate change impacts are major concerns at many sites, it is important to have the capability to represent the water balance change and its impact on contaminant transport both at the site and watershed scale in a consistent manner. This study introduces a new simulation framework to couple a detailed 2D site/hillslope-scale groundwater model to the 3D watershed-scale model to describe contaminant transport from groundwater to river water within the catchment. Within the site, we estimate the contaminant discharges to the river from contaminant sources based on the Richards equation and advection-dispersion equation. The discharges are then applied as the boundary conditions to the watershed-scale model considering the width of the 2D site/hillslope-scale groundwater model and recharge rates for both models.
We demonstrate and validate our framework based on the tritium concentration datasets in surface water and groundwater collected at the Savannah River Site F-Area. Results show that the method can successfully reproduce the contaminant concentration time series in river water.
How to cite: Sakuma, K., Wainwright, H., Xu, Z., Lawrence, A., and Hazenberg, P.: Multiscale model coupling for watershed-scale contaminant transport modeling from point sources in Savannah River Site, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4077, https://doi.org/10.5194/egusphere-egu25-4077, 2025.
