10 citations as recorded by crossref.

1. J-GAIN v1.1: a flexible tool to incorporate aerosol formation rates obtained by molecular models into large-scale models D. Yazgi & T. Olenius https://doi.org/10.5194/gmd-16-5237-2023
2. Reduced effective radiative forcing from cloud–aerosol interactions (ERFaci) with improved treatment of early aerosol growth in an Earth system model S. Blichner et al. https://doi.org/10.5194/acp-21-17243-2021
3. Influence of emission size distribution and nucleation on number concentrations over Greater Paris K. Sartelet et al. https://doi.org/10.5194/acp-22-8579-2022
4. Treatment of Key Aerosol and Cloud Processes in Earth System Models – Recommendations from the FORCeS Project I. Riipinen et al. https://doi.org/10.16993/tellusb.1883
5. Time-dependent characteristics and parameter sensitivity of aerosol evolution under multiple dynamic processes M. Sun et al. https://doi.org/10.1016/j.ces.2026.123449
6. Research on Audit Simulation of Accounting Computerization Based on Internet Complex Discrete Dynamic Modeling Technology Z. Chen et al. https://doi.org/10.1155/2022/5854105
7. Constraining global transport of perfluoroalkyl acids on sea spray aerosol using field measurements B. Sha et al. https://doi.org/10.1126/sciadv.adl1026
8. Global fields of daily accumulation-mode particle number concentrations using in situ observations, reanalysis data, and machine learning A. Ovaska et al. https://doi.org/10.5194/ar-3-589-2025
9. Modellering av biogeokjemiske prosesser i den norske klimamodellen NorESM T. Berntsen https://doi.org/10.18261/issn.1504-3118-2021-05-06
10. Atmospheric nanoparticle growth D. Stolzenburg et al. https://doi.org/10.1103/RevModPhys.95.045002