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This paper benchmarks six generative deep learning models for nowcasting aerosol particle size distributions from PM2.5 and meteorological data, finding that physics-guided flow matching performs best, with a reduced general dynamic equation constraint lowering CRPS by 5.5–11.5% at the training site.