Aerosol dry deposition is an important sink for particulate matter and a source of uncertainty in air quality modeling. Using the Weather Research and Forecasting model coupled with CUACE (WRF-CUACE), we quantified how three aerosol dry deposition schemes and satellite-based leaf area index (LAI) information affected PM2. 5 dry removal and near-surface PM2. 5 over central and eastern China in January 2022. The schemes were abbreviated as Z01, E20, and PZ10, respectively. A fourth simulation (PZ10MLAI) used PZ10 but replaced the baseline LAI dataset with a Moderate Resolution Imaging Spectroradiometer (MODIS) constrained LAI field. Hourly PM2. 5 was evaluated with the China National Environmental Monitoring Center network. The schemes produced pronounced, size-dependent differences in deposition velocities, with a pronounced spread in the 0 to 2. 5 µm average and more than one order of magnitude spread in the accumulation mode diagnostic, leading to distinct regional mean PM2. 5 dry deposition fluxes. The mean PM2. 5 flux increased by 5. 9% in E20 relative to Z01 and decreased by 54. 4% in PZ10. The MODIS LAI adjustment changed the PZ10 mean flux by 0. 42%. The flux contrasts yielded coherent PM2. 5 responses, with E20 reducing near-surface concentrations by about 10 to 30% and PZ10 increasing them by about 20 to 60%, reaching about 80 to 100% in parts of southern China. Domain mean correlations ranged from 0. 61 to 0. 65 and PZ10-based simulations exhibited near-zero mean bias. Although MODIS LAI effects were modest for this winter month, local PM2. 5 differences commonly remained within about 4% and approached 6 to 10%, indicating that satellite LAI constraints can be important for multi-year and decadal applications.
Zhang et al. (Sun,) studied this question.