A New Aerosol Dry Deposition Model for Air Quality and Climate Modeling

Dry deposition of aerosols from the atmosphere is an important but poorly understood and inadequately modeled process in atmospheric systems for climate and air quality. Comparisons of currently used aerosol dry deposition models to a compendia of published field measurement studies in various landscapes show very poor agreement over a wide range of particle sizes. In this study, we develop and test a new aerosol dry deposition model that is a modification of the current model in the Community Multiscale Air Quality (CMAQ) model. The new model agrees much better with measured dry deposition velocities across particle sizes. The key innovation is the addition of a second inertial impaction term for microscale obstacles such as leaf hairs, microscale ridges, and needleleaf edge effects. The most significant effect of the new model is to increase the mass dry deposition of the accumulation mode aerosols in CMAQ. Accumulation mode mass dry deposition velocities increase by almost an order of magnitude in forested areas with lesser increases for shorter vegetation. Peak PM 2.5 concentrations are reduced in some forested areas by up to 40% in CMAQ simulations. Over the continuous United States, the new model reduced PM 2.5 by an average of 16% for July 2018 at the Air Quality System monitoring sites. For summer 2018 simulations, bias and error of PM 2.5 concentrations are significantly reduced, especially in forested areas. Plain Language Summary Aerosol dry deposition is an important sink for atmospheric particles that are a health hazard and a significant climate forcer. Uncertainties in modeling aerosol dry deposition hamper accurate predictions of air quality and climate. A new aerosol dry deposition model is developed that better agrees with observations of aerosol dry deposition velocity for a variety of vegetation such as forests, grasslands, and water surfaces. This improved aerosol dry deposition model when incorporated into air quality and climate models will improve the accuracy of model predictions. Key Points New aerosol deposition velocity model agrees better with observations than current models Impaction on microscale obstacles such as leaf hairs is key process New aerosol deposition velocity model increases dry deposition of PM 2.5 compared to the current Community Multiscale Air Quality model

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Publication Details

Journal
UNC Libraries
Published
2025-04-29
DOI
https://doi.org/10.17615/m4kx-zr22
Primary Topic
Vehicle emissions and performance
Type
article
Field-Weighted Citation Impact
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article

A New Aerosol Dry Deposition Model for Air Quality and Climate Modeling

Jeff Willison, Rick Saylor, Francis S. Binkowski, Jonathan Pleim et al.
UNC Libraries
Vehicle emissions and performance
article

A New Aerosol Dry Deposition Model for Air Quality and Climate Modeling

Jeff Willison, Rick Saylor, Francis S. Binkowski, Jonathan Pleim, Limei Ran
article en

Abstract

Dry deposition of aerosols from the atmosphere is an important but poorly understood and inadequately modeled process in atmospheric systems for climate and air quality. Comparisons of currently used aerosol dry deposition models to a compendia of published field measurement studies in various landscapes show very poor agreement over a wide range of particle sizes. In this study, we develop and test a new aerosol dry deposition model that is a modification of the current model in the Community Multiscale Air Quality (CMAQ) model. The new model agrees much better with measured dry deposition velocities across particle sizes. The key innovation is the addition of a second inertial impaction term for microscale obstacles such as leaf hairs, microscale ridges, and needleleaf edge effects. The most significant effect of the new model is to increase the mass dry deposition of the accumulation mode aerosols in CMAQ. Accumulation mode mass dry deposition velocities increase by almost an order of magnitude in forested areas with lesser increases for shorter vegetation. Peak PM 2.5 concentrations are reduced in some forested areas by up to 40% in CMAQ simulations. Over the continuous United States, the new model reduced PM 2.5 by an average of 16% for July 2018 at the Air Quality System monitoring sites. For summer 2018 simulations, bias and error of PM 2.5 concentrations are significantly reduced, especially in forested areas. Plain Language Summary Aerosol dry deposition is an important sink for atmospheric particles that are a health hazard and a significant climate forcer. Uncertainties in modeling aerosol dry deposition hamper accurate predictions of air quality and climate. A new aerosol dry deposition model is developed that better agrees with observations of aerosol dry deposition velocity for a variety of vegetation such as forests, grasslands, and water surfaces. This improved aerosol dry deposition model when incorporated into air quality and climate models will improve the accuracy of model predictions. Key Points New aerosol deposition velocity model agrees better with observations than current models Impaction on microscale obstacles such as leaf hairs is key process New aerosol deposition velocity model increases dry deposition of PM 2.5 compared to the current Community Multiscale Air Quality model

UNC Libraries
University of North Carolina at Chapel Hill (US)
Openalex Percentile: Top 71%
Vehicle emissions and performance
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