Role of Land–Atmosphere Processes in the Pm Simulation of a River Valley City with Complex Topography

Realistic representation of land–atmosphere processes (LAPs) plays a significant role in meteorology and consequent air quality simulations. In this study, 15 series setups, different combinations of five planetary boundary layers (PBL) with compatible surface layer (SL) schemes, and three land surface models (LSMs) were designed in the WRF-Chem model to perform a sensitivity study assessing the influence of LAPs on simulations. Sensitivity tests were conducted over the river valley city at 1 km resolution under synoptically quiescent conditions on December 1–6, 2019. The results were evaluated via comparison with five meteorological and 29 air quality stations. Statistical indicators were used to understand the physical mechanisms of various LAPs which impact air pollution diffusion and to identify the preferred configuration. Our studies revealed that adequate representations of physical processes occurred in lower atmosphere play a more significant role in both meteorological and air quality predictions than those of moderate and upper atmosphere characteristics over complex topography under synoptically quiescent conditions. The simulations also seemed more sensitive to the LSMs than to PBL schemes. The NoahMP land surface model exhibited better performance than the RUC and SLAB models, likely because it effectively captured the daily variations in near-surface temperature and wind direction. LAPs had a significant effect on the air quality simulations. The differences in correlation coefficients and daily particulate matter (PM) concentrations between the model simulations in response to the LAP configurations were approximately double. The MYN_N configuration, namely the NoahMP land surface model coupled with the MYNN PBL scheme, improved the accuracy of the modeled PM concentration and constituted a reference for air quality prediction over complex topography under calm synoptic conditions.