15 citations as recorded by crossref.

1. Inverse modeling of 137Cs during Chernobyl 2020 wildfires without the first guess O. Tichý et al. https://doi.org/10.1016/j.apr.2025.102419
2. 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
3. A method for radionuclide emission optimization using four-dimensional variational assimilation framework X. Yang et al. https://doi.org/10.1016/j.aeaoa.2026.100516
4. Sources and fate of atmospheric microplastics revealed from inverse and dispersion modelling: From global emissions to deposition N. Evangeliou et al. https://doi.org/10.1016/j.jhazmat.2022.128585
5. Source term inversion method for nuclear accidents based on Harris Hawks Optimization X. Miao et al. https://doi.org/10.1016/j.anucene.2025.112090
6. Decreasing trends of ammonia emissions over Europe seen from remote sensing and inverse modelling O. Tichý et al. https://doi.org/10.5194/acp-23-15235-2023
7. Multi-scenario validation of the robust inversion method with biased plume range and values X. Dong et al. https://doi.org/10.1016/j.jenvrad.2023.107363
8. Bayesian inversion of HFC-134a emissions in southern China from a new AGAGE site: Results from an observing system simulation experiment J. Li et al. https://doi.org/10.1016/j.atmosenv.2024.120715
9. Estimating volcanic ash emissions using retrieved satellite ash columns and inverse ash transport modeling using VolcanicAshInversion v1.2.1, within the operational eEMEP (emergency European Monitoring and Evaluation Programme) volcanic plume forecasting system (version rv4_17) A. Brodtkorb et al. https://doi.org/10.5194/gmd-17-1957-2024
10. 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
11. Source term determination with elastic plume bias correction O. Tichý et al. https://doi.org/10.1016/j.jhazmat.2021.127776
12. 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
13. Unchanged PM2.5 levels over Europe during COVID-19 were buffered by ammonia N. Evangeliou et al. https://doi.org/10.5194/ar-3-155-2025
14. Real-time measurement of radionuclide concentrations and its impact on inverse modeling of 106Ru release in the fall of 2017 O. Tichý et al. https://doi.org/10.5194/amt-14-803-2021
15. Method of Source Identification Following an Accidental Release at an Unknown Location Using a Lagrangian Atmospheric Dispersion Model S. Andronopoulos & I. Kovalets https://doi.org/10.3390/atmos12101305