Publications by authors named "Akiyuki Seki"

In this paper, we have developed a methodology to estimate the spatiotemporal distribution of radiation air dose rates around the Fukushima Daiichi Nuclear Power Plant (FDNPP). In our exploratory data analysis, we found that (1) the temporal evolution of dose rates is composed of a log-linear decay trend and fluctuations of air dose rates that are spatially correlated among adjacent monitoring posts; and (2) the slope of the log-linear environmental decay trend can be represented as a function of the apparent initial dose rates, coordinate position, land-use type, and soil type. From these observations, we first estimated the log-linear decay trend at each location based on these predictors, using the random forest method.

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An enormous amount of environmental monitoring data has been acquired by various organisations for the evaluation and implementation of countermeasures to mitigate the effects of the accident at the Fukushima Daiichi Nuclear Power Plant. However, it is difficult to collate, compare, and analyse this data because it was published in different formats at different sites according to the respective objectives of the publishing organisations. Moreover, these organisations have been accumulating data in large volumes for over nine years after the accident.

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Radiation air dose rates near the Fukushima Daiichi Nuclear Power Plant (FDNPP) have been steadily decreasing over the past eight years since the release of radioactive elements in March 2011. Currently, the radiation monitoring program is expected to transition to long-term monitoring after most of the remediation activities are completed. The main long-term monitoring objectives are to (1) confirm the continuing reduction of contaminant and hazard levels, (2) provide assurance for the public, (3) accumulate the basic datasets for scientific knowledge and future preparation, and (4) detect changes or anomalies in contaminant mobility (if they occur), or any unexpected processes or events.

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We summarized temporal changes in air dose rates and radionuclide deposition densities over five years in the 80 km zone based on large-scale environmental monitoring data obtained continuously after the Fukushima Nuclear Power Plant (NPP) accident, including those already reported in the present and previous special issues. After the accident, multiple radionuclides deposited on the ground were detected over a wide area; radiocesium was found to be predominantly important from the viewpoint of long-term exposure. The relatively short physical half-life of Cs (2.

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In this study, we quantify the temporal changes of air dose rates in the regional scale around the Fukushima Dai-ichi Nuclear Power Plant in Japan, and predict the spatial distribution of air dose rates in the future. We first apply the Bayesian geostatistical method developed by Wainwright et al. (2017) to integrate multiscale datasets including ground-based walk and car surveys, and airborne surveys, all of which have different scales, resolutions, spatial coverage, and accuracy.

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Article Synopsis
  • This study analyzes changes in air dose rates around the Fukushima Dai-ichi Nuclear Power Plant from 2014 to 2016 and predicts future dose rates using a Bayesian geostatistical method.
  • It integrates various datasets from walk, car, and airborne surveys to represent spatial variability in radiation exposure accurately.
  • Findings indicate a consistent decrease in air dose rates, particularly in town areas due to cleanup efforts, with predictions showing significant reductions by 2026, especially in residential regions.
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This paper presents a multiscale data integration method to estimate the spatial distribution of air dose rates in the regional scale around the Fukushima Daiichi Nuclear Power Plant. We integrate various types of datasets, such as ground-based walk and car surveys, and airborne surveys, all of which have different scales, resolutions, spatial coverage, and accuracy. This method is based on geostatistics to represent spatial heterogeneous structures, and also on Bayesian hierarchical models to integrate multiscale, multi-type datasets in a consistent manner.

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Soil deposition density maps of gamma-ray emitting radioactive nuclides from the Fukushima Dai-ichi Nuclear Power Plant (NPP) accident were constructed on the basis of results from large-scale soil sampling. In total 10,915 soil samples were collected at 2168 locations. Gamma rays emitted from the samples were measured by Ge detectors and analyzed using a reliable unified method.

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