This study investigates particle dry deposition by characterizing critical parameters and land-use dependence in a 0-D box model as well as quantifying the resulting impact of dry deposition parameterizations on regional-scale 3-D model predictions. A publicly available box model configured with several land-use dependent dry deposition schemes is developed to evaluate predictions of several model approaches with available measurements. The 0-D box model results suggest that current dry deposition schemes in 3-D regional models underestimate particle dry deposition velocities, but this varies with size distribution properties and land-use categories. We propose two new schemes to improve dry deposition performance in air quality models and test them in the Community Multiscale Air Quality (CMAQ) model. The first scheme improves the previous CMAQ scheme by preserving the original dry deposition impaction calculation but turning off redundant integration across particle size for each aerosol mode. The second scheme adds a dependence on leaf area index (LAI) to better estimate uptake to vegetative surfaces while using a settling velocity that is integrated across particle size for the Stokes number calculation. CMAQ model performance was evaluated for a month in July 2011 for the conterminous U.S. based on available observations of ambient sulfate (SO42-) aerosol concentrations from multiple routine particulate matter monitoring networks. Incorporation of the first scheme has a larger impact on coarse particles than fine particles, systematically reducing monthly domain-wide average particle dry deposition velocities (〖 V〗_d) by approximately 96% and 35%, respectively, and increasing monthly average SO4 concentrations by 395% and 21%. After incorporating LAI into the boundary layer resistance (R_b), the second scheme creates more spatial diversity of V_d and changes SO4 concentrations (coarse = -76% to +336%; fine = -7% to +18%) with land-use categories. These improvements are incorporated into the current publicly available version of CMAQ (v5.3 and beyond).

This dataset is associated with the following publication: Shu, Q., B. Murphy, D. Schwede, B. Henderson, H. Pye, K.W. Appel, T. Khan, and J. Perlinger. Improving the particle dry deposition scheme in the CMAQ photochemical modeling system. ATMOSPHERIC ENVIRONMENT. Elsevier B.V., Amsterdam, NETHERLANDS, 289: 119343, (2022).