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Wainwright, H. M.*; Seki, Akiyuki; Mikami, Satoshi; Saito, Kimiaki
Journal of Environmental Radioactivity, 189, p.213 - 220, 2018/09
Times Cited Count：4 Percentile：14.1(Environmental Sciences)In this study, we quantify the temporal changes of air dose rates in the regional scale around the Fukushima Daiichi 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. 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.
Wainwright, H. M.*; Seki, Akiyuki; Chen, J.*; Saito, Kimiaki
Journal of Environmental Radioactivity, 167, p.62 - 69, 2017/02
Times Cited Count：13 Percentile：40.97(Environmental Sciences)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 demonstrate our approach using three types of datasets collected at the same time over Fukushima City in Japan: (1) coarse-resolution airborne surveys covering the entire area, (2) car surveys along major roads, and (3) walk surveys in multiple neighborhoods. Results show that the method can successfully integrate three types of datasets and create an integrated map (including the confidence intervals) of air dose rates over the domain in high resolution. Moreover, this study provides us with various insights into the characteristics of each data set, as well as radiocaesium distribution. In particular, the urban areas show high heterogeneity in the contaminant distribution due to human activities as well as large discrepancy among different surveys due to such heterogeneity.
