17 citations as recorded by crossref.

1. Spatial-temporal source term estimation using deep neural network prior and its application to Chernobyl wildfires A. Brožová et al. https://doi.org/10.1016/j.jhazmat.2025.137510
2. Efficient Bayesian source reconstruction and uncertainty quantification of atmospheric radionuclide releases by replacing release rate sampling with Maximum-A-Posteriori estimation of time-varying release rates Y. Xu et al. https://doi.org/10.1016/j.jhazmat.2025.138171
3. Bayesian reconstruction of atmospheric radionuclide releases from sparse observations using nonuniform continuous priors for both spatial location and temporal release Y. Xu & S. Fang https://doi.org/10.1016/j.jhazmat.2026.141898
4. Impact of background representation on Bayesian radioxenon source estimation using IMS measurements O. Tichý et al. https://doi.org/10.1016/j.jenvrad.2026.108139
5. A baseline for source localisation using the inverse modelling tool FREAR P. De Meutter et al. https://doi.org/10.1016/j.jenvrad.2024.107372
6. Sensitivity of Bayesian source reconstruction to likelihood functions: analyses based on ETEX field experiments Y. Zhao et al. https://doi.org/10.1016/j.pnucene.2025.105909
7. NeuPlume: generative inversion of atmospheric point-source emissions from sparse observations L. Wang & X. Ma https://doi.org/10.5194/acp-26-14185-2026
8. Uncertainty and source term reconstruction with environmental air samples I. Hoffman et al. https://doi.org/10.1016/j.jenvrad.2022.106836
9. Robust source reconstruction of atmospheric radionuclides from observations of different sparsity with spatial preselection and non-smooth constraints Y. Xu et al. https://doi.org/10.1016/j.jhazmat.2024.136919
10. Quantification of uncertainties in the assessment of an atmospheric release source applied to the autumn 2017 106Ru event J. Dumont Le Brazidec et al. https://doi.org/10.5194/acp-21-13247-2021
11. SAUNA Q - Array: The realization of a new concept in radioxenon detection A. Ringbom et al. https://doi.org/10.1016/j.jenvrad.2023.107136
12. Comparison of source-location algorithms for atmospheric samplers P. Eslinger et al. https://doi.org/10.1016/j.jenvrad.2024.107384
13. Source term estimation using noble gas and aerosol samples P. Eslinger & B. Milbrath https://doi.org/10.1016/j.jenvrad.2024.107544
14. Intuitively tuned elastic bias correction of atmospheric inversion using Gaussian process prior: Application to accidental radioactive emissions A. Brožová et al. https://doi.org/10.1016/j.jhazmat.2026.141523
15. Source reconstruction for atmospheric radionuclide leakage: Recent advances in decoding information from atmospheric transport physics Y. Xu et al. https://doi.org/10.1016/j.jhazmat.2025.139534
16. A spatiotemporally separated framework for reconstructing the sources of atmospheric radionuclide releases Y. Xu et al. https://doi.org/10.5194/gmd-17-4961-2024
17. Source term determination with elastic plume bias correction O. Tichý et al. https://doi.org/10.1016/j.jhazmat.2021.127776