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Using the online-coupled Global/Regional Assimilation and Prediction System coupled with the Chinese Unified Atmospheric Chemistry Environment (GRAPES_CUACE) model, numerical experiments are conducted to compare the impacts of three planetary boundary layer (PBL) schemes—Medium Range Forecast (MRF), Yonsei University (YSU), and Mellor-Yamada-Janjic (MYJ)—on PM 2.5 simulations and their responses to aerosol-radiation feedback (ARF), under different terrain and weather conditions. The baseline experiments without ARF with all three PBL schemes can reproduce the spatial and temporal distribution characteristics of surface PM 2.5 on the whole and show that the model can capture the PM 2.5 variation better in unstable conditions (clean days) than in stable conditions (pollution days). The three PBL schemes show differences in the simulations of meteorological factors, e.g., the MRF scheme produces the best 10-m wind speed, the MYJ scheme produces the best 2-m temperature, and the YSU scheme produces the lowest PBL height (PBLH) and vertical diffusivity. Consequently, there is no significant difference among the three PBL schemes in surface PM 2.5 simulations due to the combined action of the surface and the PBL structure. However, all the baseline experiments massively underestimate PM 2.5 during severe pollution days. The online computing of ARF in the three PBL schemes can substantially improve the underestimation of PM 2.5 by reducing sensible heat fluxes, 2-m temperature, friction velocity, and the PBL height. More importantly, the response intensity of three PBL schemes to ARF is very different. For PM 2.5 simulations, MYJ has the weakest response, whereas MRF and YSU have similar responses. During the heavy pollution days with more intense aerosol-radiation effect, the increase of PM 2.5 induced by ARF in MRF and YSU is about twice that in MYJ, making the PM 2.5 simulated by MRF and YSU more consistent with the observations. This result shows the ARF dependence on the PBL processes and suggests the importance of PBL-ARF interaction to the PM 2.5 numerical prediction during haze episodes. • The variation of PM 2.5 is affected by the interaction between land surface and atmospheric boundary layer. • Aerosol-radiation feedback substantially improves the underestimation of PM 2.5 during heavy haze pollution. • Aerosol-radiation feedback strongly depends on the boundary layer processes. [ABSTRACT FROM AUTHOR]