Airborne gamma-ray emitters from Fukushima detected in New York State

Kitto, Michael E.; Menia, Traci A.; Haines, Douglas K.; Beach, S.E.; Bradt, Clayton J.; Fielman, Eileen M.; Syed, Umme-Farzana; Semkow, Thomas M.; Bari, Abdul; Khan, Abdul Jabbar

doi:10.1007/s10967-012-2043-0

Cited by 9 publications

(4 citation statements)

References 6 publications

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“…1b and Supplementary Movie S2 ). Vertical mixing was still provided by frontal convection and precipitation attached to the jet stream, thus Fukushima-derived radioiodine was detected early on the surface following the jet stream pathway in New York State (18 March) 15 , Iceland and Norway (19–20 March) 16 , Sweden, Finland and Western Russia (21–22 March) 17 18 ( Supplementary Figures S2 and S3 ). Over Asia, the jet stream formed meridional waves resulting in a slower and more heterogeneous transport of radioiodine over Asia with arrival to South Korea on 28 March 19 , Taiwan on 29 March 20 and China only on 31 March 21 .…”

Section: Resultsmentioning

confidence: 99%

Predictability of the dispersion of Fukushima-derived radionuclides and their homogenization in the atmosphere

Mészáros

Leelőssy

Kovács

et al. 2016

Sci Rep

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Long-range simulation of the dispersion of air pollutants in the atmosphere is one of the most challenging tasks in geosciences. Application of precise and fast numerical models in risk management and decision support can save human lives and can diminish consequences of an accidental release. Disaster at Fukushima Daiichi nuclear power plant has been the most serious event in the nuclear technology and industry in the recent years. We present and discuss the results of the numerical simulations on dispersion of Fukushima-derived particulate 131I and 137Cs using a global scale Lagrangian particle model. We compare concentrations and arrival times, using two emission scenarios, with the measured data obtained from 182 monitoring stations located all over the Northern Hemisphere. We also investigate the homogenization of isotopes in the atmosphere. Peak concentrations were predicted with typical accuracy of one order of magnitude showing a general underestimation in the case of 131I but not for 137Cs. Tropical and Arctic plumes, as well as the early detections in American and European midlatitudes were generally well predicted, however, the later regional-scale mixing could not be captured by the model. Our investigation highlights the importance of the parameterization of free atmospheric turbulence.

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Section: Resultsmentioning

confidence: 99%

Predictability of the dispersion of Fukushima-derived radionuclides and their homogenization in the atmosphere

Mészáros

Leelőssy

Kovács

et al. 2016

Sci Rep

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“…A vertikális keveredési folyamatok által okozott, a terjedési modell által nem kimutatható mezoskálájú térbeli változékonyság mértékét finom térbeli felbontású megfigyelések alapján lehet becsülni. A mindössze 55 000 km 2 területű New York államban fekvő hat mérőhely nyolc napos időintervallumban, március 18. és 25. között észlelte először a fukushimai radioaktivitást, a csúcskoncentrációk pedig 0,44-1,19 mBq/m 3 között változtak (Kitto et al, 2012). Felismerve ezt a bizonytalanságot, hasonló helyzetekben a felszínen mérhető érkezési idők előrejelzésében jelentős hozzáadott értéket adhatna, ha a terjedési modell által a magasban helyesen szimulált csóvából történő lekeveredést szinoptikus szempontok alapján, emberi beavatkozással jeleznénk előre.…”

Section: Szélesség Szerinti Eloszlásunclassified

Szennyezőanyagok légköri koncentrációját előrejelző modellrendszer fejlesztése és alkalmazása

Leelőssy¹

2017

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Atmospheric dispersion models have become important tools for air pollution meteorology for the last decades. Based on meteorological data, these models can simulate the transmission of pollutants released from accidental or normal industrial processes, traffic and households, as well as deflation and evaporation. The scale of the dispersion process can range from local air pollution events to globally detectable nuclear accidents. Simulation of atmospheric dispersion on different scales requires different modeling approaches.The aim of this research is to develop an atmospheric dispersion model applicable on a wide range of scales. A regional-to-global scale Lagrangian particle dispersion model and a local scale plume model have been developed, which can be used with data from several numerical weather prediction systems.The main application of the Lagrangian model was the simulation of the global dispersion of radionuclides released from the Fukushima Nuclear Power Plant. Measurement data from several sites in the Northern Hemisphere provided a resource to validate model results and to reconstruct the dispersion process in each region.The developed dispersion models have been applied for recent cases in Hungary that reached large public interest. Our plume model was used to simulate the long-term spatial distribution of deflated industrial dust from the Budapest Chemical Works site for a period of thirteen years. Radioiodine release from the Institute of Isotopes in Budapest was simulated with our Lagrangian model to reveal model uncertainties in a complex weather situation with low-level inversion and wind shear.Our Gaussian and Lagrangian models can simulate the dispersion of passive tracers or toxic substances with a simple chemical mechanism. Development of the model allows the flexible adaptation for special needs of users and its integration into complex decision support software. Development and testing provided valuable experience for future applications to select and set up the best possible modeling tool for atmospheric dispersion problems.

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“…Hot particles travel significant distances with the plume [17] [18]. Gas-phase and aerosol 131 I from Fukushima were observed as far as New York State [19].…”

Section: Introductionmentioning

confidence: 99%

Monte Carlo Simulation Study of Hot-Particle Detection in Voluminous Samples by Gamma Spectrometry

Chu¹,

Burn²,

Bradt³

et al. 2021

JAMP

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In this work, we addressed the inhomogeneity problem in gamma spectrometry caused by hot particles, which are dispersed into environment from large nuclear reactor accidents such as at Chernobyl and Fukushima. Using Monte Carlo simulation, we have determined the response of a gamma spectrometer to individual and grouped hot particles randomly distributed in a soil matrix of 1-L and 0.6-L sample containers. By exploring the fact that the peak-to-total ratio of efficiencies in gamma spectrometry is an empirical parameter, we derived and verified a power-law relationship between the peak efficiency and peak-to-total ratio. This enabled creation of a novel calibration model which was demonstrated to reduce the bias range and bias standard deviation, caused by measuring hot particles, by several times, as compared with the homogeneous calibration. The new model is independent of the number, location, and distribution of hot particles in the samples. In this work, we demonstrated successful performance of the model for a single-peak 137 Cs radionuclide. An extension to multi-peak radionuclide was also derived.

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Airborne gamma-ray emitters from Fukushima detected in New York State

Cited by 9 publications

References 6 publications

Predictability of the dispersion of Fukushima-derived radionuclides and their homogenization in the atmosphere

Predictability of the dispersion of Fukushima-derived radionuclides and their homogenization in the atmosphere

Szennyezőanyagok légköri koncentrációját előrejelző modellrendszer fejlesztése és alkalmazása

Monte Carlo Simulation Study of Hot-Particle Detection in Voluminous Samples by Gamma Spectrometry

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