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Context. Theoretical calculations have shown that when solar prominences move away from the surface of the Sun, their radiative output is affected via the Doppler dimming or brightening effects. Aims. In this paper we ask whether observational signatures of the changes in the radiative output of eruptive prominences can be found in EUV (extreme ultraviolet) observations of the first resonance line of ionised helium at 304 {AA}. We also investigate whether these observations can be used to perform a diagnostic of the plasma of the eruptive prominence. Methods. We first look for suitable events in the SDO/AIA database. The variation of intensity of arbitrarily selected features in the 304 channel is studied as a function of velocity in the plane of the sky. These results are then compared with new non-LTE radiative transfer calculations of the intensity of the He II 304 resonance line. Results. We find that observations of intensities in various parts of the four eruptive prominences studied here are sometimes consistent with the Doppler dimming effect on the He II 304 {AA} line. However, in some cases, one observes an increase in intensity in the 304 channel with velocity, in contradiction to what is expected from the Doppler dimming effect alone. The use of the non-LTE models allows us to explain the different behaviour of the intensity by changes in the plasma parameters inside the prominence, in particular the column mass of the plasma and its temperature. Conclusions. The non-LTE models used here are more realistic than what was used in previous calculations. They are able to reproduce qualitatively the range of observations from SDO/AIA analysed in this study. Thanks to non-LTE modelling, we can infer the plasma parameters in eruptive prominences from SDO/AIA observations at 304 {AA}.
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We report on a statistical study of prominence eruptions (PEs) using a catalog of these events routinely imaged by the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO) in the 304 r{A} pass band. Using an algorithm deve
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