Improving the particle dry deposition scheme in the CMAQ photochemical modeling system. (15th November 2022)

• Record Type: Journal Article
• Authors: Shu, Qian; Murphy, Benjamin; Schwede, Donna; Henderson, Barron H.; Pye, Havala O.T.; Appel, K. Wyat; Khan, Tanvir R.; Perlinger, Judith A.
• Is Part Of: Atmospheric environment. Volume 289(2022)
• Publication Date: 2022-11-15
• Subjects: Air -- Pollution -- Periodicals; Air -- Pollution -- Meteorological aspects -- Periodicals; 551.51
• DOI: 10.1016/j.atmosenv.2022.119343
• Languages: English
• ISSNs: 1352-2310

Abstract

Abstract: Dry deposition of atmospheric aerosols in large-scale models is a critical, but highly uncertain, sink process with a strong dependence on particle size, meteorological conditions, and land surface properties. This study investigates the particle dry deposition scheme implemented in the standard Community Multiscale Air Quality (CMAQ) model v5.2.1, characterizes its underlying parameterized components with comparison to a similar scheme in a contemporary regional-scale model, and proposes two updated schemes that are then evaluated with available ambient particle deposition velocity (Vd ) measurements. Both updated schemes reduce the surprisingly strong dependence of deposition velocity on the aerosol mode width, with one scheme further introducing a dependence on vegetation coverage that is broadly consistent with variability in observations between vegetated and non-vegetated surfaces. Compared to the base scheme, the updated scheme with vegetation dependence increases Vd for submicron particles and decreases it for larger particles by an average of 37% and −66%, respectively. This scheme performs statistically better than the base scheme, reducing fractional biases by 56%–97% for vegetated land-use types and has roughly equivalent performance over water. The base and updated schemes are tested with three annual CMAQ (v5.2.1) simulations for the year 2011; predicted ambient aerosol concentrations are evaluated with routine monitoring network observations and predicted dry deposition fluxes are evaluated with data from the Clean Air Status and Trends Network (CASTNET). The updated scheme with vegetation dependence reduces negative fractional biases for PM10 by 41% and positive fractional biases for PM2.5 organic carbon by 15%. This scheme has been incorporated into the most recent publicly accessible versions of CMAQ (v5.3 and beyond) to replace the scheme used in previous versions of CMAQ (v4.5 through v5.2.1). Highlights: A 0-D box model is designed to characterize the parameterized components of particle dry deposition in CTMs. The source of the differences between CAMx and CMAQ particle dry deposition schemes is characterized in the box model. Incremental revisions to the particle dry deposition scheme are updated in CMAQ. The behaviors of updated schemes are characterized in the 0-D box model and full 3-D CMAQ. Key issues for current applications and future development of particle dry deposition are highlighted.