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Evaluation of an Advanced Aerosol Dry Deposition Model
Citation:
Cheng, B., Kiran Alapaty, Q. Shu, AND S. Arunachalam. Evaluation of an Advanced Aerosol Dry Deposition Model. 103rd American Meteorological Society annual meeting 2023, denver, CO, January 08 - 12, 2023.
Impact/Purpose:
This work advances the turbulence strength representation improving dry deposition of particles thereby improving PM2.5 concentrations that can aid to better estimation of human health impacts.
Description:
Magnitude of atmospheric turbulence, a key driver of several processes that contribute to aerosol (i.e., particle) deposition, is typically underrepresented in current models. Various formulations have been developed to model particle dry deposition; all these formulations mostly rely on friction velocity and some use additional ad hoc factors to represent enhanced impacts of turbulence. However, none were formally linked with the three-dimensional (3-D) turbulence. Here, we propose a set of 3-D turbulence-dependent resistance formulations for particle dry deposition simulation and intercompare the performance of the new resistance formulations with that obtained from using the existing formulations and measured dry deposition velocity. Turbulence parameters such as turbulence velocity scale, turbulence factor, intensity of turbulence, effective sedimentation velocity, and effective Stokes number are newly introduced into two different particle deposition schemes to improve turbulence representation. For an assumed particle size distribution, the newly proposed schemes predict stronger diurnal variation of particle dry deposition velocity and are comparable to corresponding measurements while existing formulations indicate large underpredictions. We also find that the incorporation of new turbulence parameters either introduced or added stronger diurnal variability to sedimentation velocity and collection efficiencies values, resulting in higher deposition values during daytime and nighttime predicted by the new schemes when compared to existing schemes. The findings from this research may help improve the capability of dry deposition schemes and help foster the development of a community dry deposition modeling system for use in regional and global models. Disclaimer: The views expressed in this article are those of the authors and do not necessarily represent the views or policies of US EPA.