| 1. |
- Li, Longxiang, et al.
(author)
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A spatiotemporal ensemble model to predict gross beta particulate radioactivity across the contiguous United States
- 2021
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In: Environment International. - : Elsevier BV. - 0160-4120. ; 156
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Journal article (peer-reviewed)abstract
- Particulate radioactivity, a characteristic of particulate matter, is primarily determined by the abundance of radionuclides that are bound to airborne particulates. Exposure to high levels of particulate radioactivity has been associated with negative health outcomes. However, there are currently no spatially and temporally resolved particulate radioactivity data for exposure assessment purposes. We estimated the monthly distributions of gross beta particulate radioactivity across the contiguous United States from 2001 to 2017 with a spatial resolution of 32 km, via a multi-stage ensemble-based model. Particulate radioactivity was measured at 129 RadNet monitors across the contiguous U.S. In stage one, we built 264 base learning models using six methods, then selected nine base models that provide different predictions. In stage two, we used a non-negative geographically and temporally weighted regression method to aggregate the selected base learner predictions based on their local performance. The results of block cross-validation analysis suggested that the non-negative geographically and temporally weighted regression ensemble learning model outperformed all base learning model with the smallest rooted mean square error (0.094 mBq/m3). Our model provided an accurate estimation of particulate radioactivity, thus can be used in future health studies.
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| 2. |
- Zhou, Yixiao, et al.
(author)
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The relationship between photometric and spectroscopic oscillation amplitudes from 3D stellar atmosphere simulations
- 2021
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In: Monthly notices of the Royal Astronomical Society. - : Oxford University Press. - 0035-8711 .- 1365-2966. ; 503:1, s. 13-27
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Journal article (peer-reviewed)abstract
- We establish a quantitative relationship between photometric and spectroscopic detections of solar-like oscillations using ab initio, 3D, hydrodynamical numerical simulations of stellar atmospheres. We present a theoretical derivation as a proof of concept for our method. We perform realistic spectral line formation calculations to quantify the ratio between luminosity and radial velocity amplitude for two case studies: the Sun and the red giant ϵ Tau. Luminosity amplitudes are computed based on the bolometric flux predicted by 3D simulations with granulation background modelled the same way as asteroseismic observations. Radial velocity amplitudes are determined from the wavelength shift of synthesized spectral lines with methods closely resembling those used in Birmingham Solar Oscillations Network (BiSON) and Stellar Oscillations Network Group (SONG) observations. Consequently, the theoretical luminosity to radial velocity amplitude ratios are directly comparable with corresponding observations. For the Sun, we predict theoretical ratios of 21.0 and 23.7 ppm [m s−1]−1 from BiSON and SONG, respectively, in good agreement with observations 19.1 and 21.6 ppm [m s−1]−1. For ϵ Tau, we predict K2 and SONG ratios of 48.4 ppm [m s−1]−1, again in good agreement with observations 42.2 ppm [m s−1]−1, and much improved over the result from conventional empirical scaling relations that give 23.2 ppm [m s−1]−1. This study thus opens the path towards a quantitative understanding of solar-like oscillations, via detailed modelling of 3D stellar atmospheres.
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