Abstract
The radioactive materials are generally concentrated downwind of their origins when the prevailing winds blow continuously in one direction. If this principle determined the pattern of dispersion in all cases, dispersion directions could be estimated by wind patterns. However, this hypothesis has not been sufficiently verified because of the complexity of dispersion processes and weather systems. Here, we show that dispersion directions, which are divided into four ranges, can be estimated by wind patterns using a machine learning approach. The five-year average hit rates of the directions of dispersion estimated using near-surface winds exceed 0.85 in all months. The dispersion directions can be estimated up to 33 hours in advance using forecast winds. In particular, high hit rates exceeding 0.95 are achieved in January and March, when large-scale weather systems dominate. These results indicate that the dispersion directions are determined by the wind patterns that correspond to large-scale weather systems and diurnal circulation patterns in most cases. Our findings also provide more reliable information on dispersion patterns with reduced uncertainties, given that reasonable skill is achieved at a sufficient lead time for evacuation.
Highlights
High contamination densities of 137Cs exceeding 1480 kBqm−2 were observed from 150 to 250 km northeast of the Chernobyl nuclear power plant after the accident in April 19861–6
Lower winds had strong effects on the dispersion of radioactive materials released during the Fukushima Daiichi nuclear power plant accident in March 20119,10
We evaluate the dispersion directions estimated by the support vector machine (SVM) approach using the forecast wind fields provided by the Japan Meteorological Agency (JMA) to obtain the lead time, which is necessary to prepare for evacuation
Summary
High contamination densities of 137Cs exceeding 1480 kBqm−2 were observed from 150 to 250 km northeast of the Chernobyl nuclear power plant after the accident in April 19861–6. In the Fukushima Daiichi nuclear power plant (FDNPP) accident in March 2011, predictions of the dispersion of radioactive materials made using atmospheric models were not used to inform evacuations[11,12,13]. The characteristics of dispersion patterns, such as direction and range, which are influenced by the winds that accompany weather systems, can be estimated in such experiments, the amounts of nuclear materials deposited cannot be estimated because they depend strongly on the emission conditions. Despite the committee’s advice, the Japanese government has decided not to use model predictions to determine whether people should evacuate in the future because such model predictions have limited accuracy[14,15] This decision may increase the risk of radiation exposure in cases in which limited information is available. The identification of regular patterns or generalizations of complex phenomena could be an effective approach in both reducing uncertainties and clearly explaining the reliability of predictions to laypeople
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