Spatial and temporal prediction of radiation dose rates near Fukushima Daiichi Nuclear Power Plant
Name
1-s2.0-S0265931X22001370-main.pdf
Description
Published version
Size
4.83 MB
Format
Adobe PDF
Checksum (MD5)
dc3a369e316e91bb8090a9e28342851d
Author(s)
Sun, Dajie
Wainwright, Haruko
Suresh, Ishita
Seki, Akiyuki
Takemiya, Hiroshi
Saito, Kimiaki
Date Issued
October 2022
Journal
Journal of Environmental Radioactivity
Publisher
Elsevier BV
Citation
Sun, Dajie, Wainwright, Haruko, Suresh, Ishita, Seki, Akiyuki, Takemiya, Hiroshi et al. 2022. "Spatial and temporal prediction of radiation dose rates near Fukushima Daiichi Nuclear Power Plant." Journal of Environmental Radioactivity, 251-252.
Version
Final published version
Abstract
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. We then developed a modified Kalman filter coupled with a Gaussian process model to estimate the dose-rate time series at a given location and time. We applied this method to the Fukushima evacuation zone (as of March 2017), which included 17 monitoring post locations (with monitoring datasets collected between 2014 and 2018) and generated a time series of dose-rate maps. Our results show that this approach allows us to produce accurate spatial and temporal predictions of radiation dose-rate maps using limited spatiotemporal measurements.
MIT Department
Massachusetts Institute of Technology. Department of Nuclear Science and Engineering
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1016/j.jenvrad.2022.106946
