Characterizing regional-scale temporal evolution of air dose rates after the Fukushima Daiichi Nuclear Power Plant accident

Wainwright, Haruko M.; Seki, Akiyuki; Mikami, Satoshi; Saito, Kimiaki

doi:10.1016/j.jenvrad.2018.04.006

Title: Characterizing regional-scale temporal evolution of air dose rates after the Fukushima Daiichi Nuclear Power Plant accident

Abstract

In this paper, 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. 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. We apply this method to the datasets from three years: 2014 to 2016. The temporal changes among the three integrated maps enables us to characterize the spatiotemporal dynamics of radiation air dose rates. The data-driven ecological decay model is then coupled with the integrated map to predict future dose rates. Results show that the air dose rates are decreasing consistently across the region. While slower in the forested region, the decrease is particularly significant in the town area. The decontamination has contributed to significant reduction of air dose rates. By 2026, the air dose rates will continue to decrease, andmore »« less

Authors:

Wainwright, Haruko M. ^[1];

^[2]; Mikami, Satoshi ^[3]; Saito, Kimiaki ^[4]

Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Japan Atomic Energy Agency, Ibaraki (Japan)
Japan Atomic Energy Agency, Fukushima (Japan)
Japan Atomic Energy Agency, Tokyo (Japan)

Publication Date:: 2018-04-24

Research Org.:: Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

Sponsoring Org.:: USDOE Office of Science (SC)

OSTI Identifier:: 1460346

Alternate Identifier(s):: OSTI ID: 1548446

Grant/Contract Number:: AC02-05CH11231; AWD00000626

Resource Type:: Accepted Manuscript

Journal Name:: Journal of Environmental Radioactivity

Additional Journal Information:: Journal Volume: 189; Journal Issue: C; Related Information: © 2018 Elsevier Ltd; Journal ID: ISSN 0265-931X

Publisher:: Elsevier

Country of Publication:: United States

Language:: English

Subject:: 61 RADIATION PROTECTION AND DOSIMETRY; 54 ENVIRONMENTAL SCIENCES

Citation Formats


                    Wainwright, Haruko M., Seki, Akiyuki, Mikami, Satoshi, and Saito, Kimiaki. Characterizing regional-scale temporal evolution of air dose rates after the Fukushima Daiichi Nuclear Power Plant accident.  United States: N. p., 2018. 
Web.  doi:10.1016/j.jenvrad.2018.04.006.

Copy to clipboard


                    Wainwright, Haruko M., Seki, Akiyuki, Mikami, Satoshi, & Saito, Kimiaki. Characterizing regional-scale temporal evolution of air dose rates after the Fukushima Daiichi Nuclear Power Plant accident.  United States.  https://doi.org/10.1016/j.jenvrad.2018.04.006

Copy to clipboard


                    Wainwright, Haruko M., Seki, Akiyuki, Mikami, Satoshi, and Saito, Kimiaki. Tue .  
"Characterizing regional-scale temporal evolution of air dose rates after the Fukushima Daiichi Nuclear Power Plant accident".  United States.  https://doi.org/10.1016/j.jenvrad.2018.04.006.  https://www.osti.gov/servlets/purl/1460346.

Copy to clipboard


                    
@article{osti_1460346,

  title        = {Characterizing regional-scale temporal evolution of air dose rates after the Fukushima Daiichi Nuclear Power Plant accident},

  author       = {Wainwright, Haruko M. and Seki, Akiyuki and Mikami, Satoshi and Saito, Kimiaki},

  abstractNote = {In this paper, 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. 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. We apply this method to the datasets from three years: 2014 to 2016. The temporal changes among the three integrated maps enables us to characterize the spatiotemporal dynamics of radiation air dose rates. The data-driven ecological decay model is then coupled with the integrated map to predict future dose rates. Results show that the air dose rates are decreasing consistently across the region. While slower in the forested region, the decrease is particularly significant in the town area. The decontamination has contributed to significant reduction of air dose rates. By 2026, the air dose rates will continue to decrease, and the area above 3.8 μSv/h will be almost fully contained within the non-residential forested zone.},

  doi          = {10.1016/j.jenvrad.2018.04.006},

  journal      = {Journal of Environmental Radioactivity},

  number       = C,

  volume       = 189,

  place        = {United States},

  year         = {2018},

  month        = {4}

}

Copy to clipboard

Journal Article:

Free Publicly Available Full Text

Accepted Manuscript (Publisher)

Accepted Manuscript (DOE)

Publisher's Version of Record

https://doi.org/10.1016/j.jenvrad.2018.04.006

Other availability

Search WorldCat to find libraries that may hold this journal

Citation Metrics:

Cited by: 3 works

Citation information provided by
Web of Science

Figures / Tables:

Fig. 1: (a) Evacuation designated area and (b) land cover types (blue= urban, green= cropland and yellow= forest). In (a), the red region is the evacuation designated area as of April 2017. The green region is where the restriction order was lifted in April 2017.

All figures and tables (8 total)

Save / Share:

Export Metadata

Save to My Library

Figures / Tables found in this record:

Figures/Tables have been extracted from DOE-funded journal article accepted manuscripts.

Similar Records in DOE PAGES and OSTI.GOV collections:

Characterizing regional-scale temporal evolution of air dose rates after the Fukushima Daiichi Nuclear Power Plant accident

Journal Article Wainwright, Haruko M. ; Seki, Akiyuki ; Mikami, Satoshi ; ... - Journal of Environmental Radioactivity

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. 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.more »« less
Cited by 3
https://doi.org/10.1016/j.jenvrad.2018.09.006

Full Text Available
A multiscale Bayesian data integration approach for mapping air dose rates around the Fukushima Daiichi Nuclear Power Plant

Journal Article Wainwright, Haruko M. ; Seki, Akiyuki ; Chen, Jinsong ; ... - Journal of Environmental Radioactivity

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. The Bayesian method allows us to quantify the uncertainty in the estimates, and to provide the confidence intervals thatmore »« less
Cited by 11
https://doi.org/10.1016/j.jenvrad.2016.11.033

Full Text Available
Optimizing long-term monitoring of radiation air-dose rates after the Fukushima Daiichi Nuclear Power Plant

Journal Article Sun, Dajie ; Wainwright, Haruko M. ; Oroza, Carlos A. ; ... - Journal of Environmental Radioactivity

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 processesmore »« less
https://doi.org/10.1016/j.jenvrad.2020.106281

Full Text Available
A Multiscale Bayesian Data Integration Approach for Mapping Air Dose Rates around the Fukushima Daiichi Nuclear Power Plant - 17166

Conference Wainwright, Haruko ; Chen, Jinsong ; Seki, Akiyuki ; ...

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 geo-statistics to represent spatial heterogeneous structures, and also on Bayesian hierarchical models to integrate multiscale, multi-type datasets in a consistent manner. The Bayesian method allows us to quantify the uncertainty in the estimates, and to provide the confidence intervals thatmore »« less
Integrating Multiscale Datasets for Monitoring Air Dose Rates in Fukushima - 18437

Conference Wainwright, Haruko ; Seki, Akiyuki ; Mikami, Satoshi ; ...

Six years has passed since the radionuclide release occurred at the Fukushima Daiichi NPP. Measurements and monitoring of air dose rates (i.e., ambient dose equivalent rates) in the region around the Fukushima Daiichi NPP have been performed continuously since the accident. Such mapping efforts are essential to protect the public, to guide decontamination efforts, and to plan the return of evacuated residents. An extensive monitoring program has enabled to develop a data-driven environmental decay model for describing and predicting the decay of radiation air dose rates in the environment. However, it has been difficult to quantify the heterogeneity of environmentalmore »« less

Similar Records