Classification-constrained retrieval of PM 2.5 vertical profiles from fluorescence-raman-mie polarization lidar

Abstract. The vertical distribution of PM2.5 during urban haze events is jointly affected by aerosol composition, boundary-layer structure, and regional transport. Empirical PM2.5 retrievals based on lidar-derived extinction coefficients can be biased by the optical contribution of coarse-mode mineral particles. This study used fluorescence–Raman–Mie polarization lidar observations in Beijing to identify anthropogenic pollution aerosols (APA), desert dust (DD), and mineral dust (MD) using the particle depolarization ratio (PDR) and fluorescence capacity (Gf). The classification results were incorporated into the construction and application of an empirical extinction–PM2.5 relationship. For mixed-aerosol samples, the APA component fraction and its associated extinction contribution were estimated before retrieving the vertical PM2.5 distribution. To quantify the effect of classification constraints, three linear models were developed: a model without aerosol-type constraints, a PDR-only screening model, and a model constrained by combined PDR–Gf classification. Near-surface, date-separated validation using 411 hourly samples from 69 observation dates showed that the combined-classification model achieved an RMSE of 17.32 µg m−3, an MAE of 13.54 µg m−3, and a Bias of 3.30 µg m−3. Compared with the model without aerosol-type constraints, the RMSE, MAE, and Bias decreased by 38.2 %, 45.0 %, and approximately 83.0 %, respectively. Uncertainty analysis showed that classification end-member and aerosol-type-dependent lidar-ratio perturbations affected the quantitative PM2.5 estimates under mixed-aerosol conditions, whereas the residual scatter and parameter stability of the empirical extinction–PM2.5 relationship were the dominant sources of prediction uncertainty. For a mixed-to-pollution aerosol evolution episode in Beijing in November 2024, the classification-constrained PM2.5 vertical structure was physically consistent with temperature stratification, wind fields, and backward trajectories. Seasonal testing showed no stable and consistent improvement from season-specific fitting. The proposed method provides classification-constrained estimates of the PM2.5 vertical structure under APA-dominated conditions in Beijing. Model parameters should be recalibrated using local observations when applied to regions, seasons, or aerosol conditions with substantially different composition.