Size-dependent aerosol deposition velocities during BEARPEX'07

Vong, Richard J.; Vong, I. J.; Vickers, Dean; Covert, David S.

doi:10.5194/acpd-10-4649-2010

Cited by 7 publications

(12 citation statements)

References 23 publications

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“…In fact, the data suggest that there may be a minimum somewhere in the 0.1-0.2 mm range, with a sharp rise in V d between 0.2 and 0.3 mm, rather than the gradual decrease that is predicted by most of the V d (D p ) algorithms. This is consistent across many of the measurement data sets (Gallagher et al, 1997;Gronholm et al, 2007;Vong et al, 2010;Gordon et al, 2011;Mammarella et al, 2011), but not all (e.g. Buzorius et al, 2000).…”

Section: Models Of Atmospheric Particle Depositionsupporting

confidence: 65%

“…This phenomenon was noted as far back as the 1980's (Hicks et al, 1982; and is observed routinely with more modern instruments and technologies (e.g. Vong et al, 2010;Gordon et al, 2011) and has been examined theoretically by Pryor et al (2008b). However, since in-canopy physical and chemical processes are largely ignored by current air quality and atmospheric chemistry models , there are no mechanisms included in these models that can produce upward particle fluxes.…”

Section: Conclusion Implications and Recommendationsmentioning

confidence: 99%

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The particle dry deposition component of total deposition from air quality models: right, wrong or uncertain?

Saylor

Baker

Lee

et al. 2019

Tellus B: Chemical and Physical Meteorology

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2019) The particle dry deposition component of total deposition from air quality models: right, wrong or uncertain?, Tellus B: Chemical and Physical Meteorology, 71:1, 1550324, ABSTRACT Dry deposition is an important loss process for atmospheric particles and can be a significant part of total deposition estimates calculated for critical loads analyses. However, algorithms used in large-scale air quality and atmospheric chemistry models to predict particle deposition velocity as a function of particle size are highly uncertain. Many of these algorithms, although derived from a common heritage, predict vastly different particle deposition velocities for a given particle diameter even under identical environmental conditions for major land use classes. Even more problematic, for vegetated landscapes (forests, in particular) the algorithms do not agree very well with available measurements. In this work, we perform a sensitivity study to estimate how significant the uncertainties in particle deposition algorithms may be in an air quality model's predictions of ground-level fine particle concentrations, particle deposition and overall total deposition of nitrogen and sulfur. Our results suggest that fine particle concentration predictions at the surface may vary by 5-15% depending on the choice of particle deposition velocity algorithm, while particle dry deposition is affected to a much greater extent with differences among algorithms >200%. Moreover, if accumulation mode particle dry deposition measurements over forests are correct, then dry particle deposition and total elemental deposition to these landscapes may be much larger than is typically simulated by current air quality and atmospheric chemistry models, calling into question commonly available estimates of total deposition and their use in critical loads analyses. Since accurate predictions of atmospheric particle concentrations and deposition are critically important for future air quality, weather and climate models and management of pollutant deposition to sensitive ecosystems, an investment in new dry deposition measurements in conjunction with integrated modelling efforts seems not only justified but vitally necessary to advance and improve the treatment of particle dry deposition processes in atmospheric models.

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Section: Models Of Atmospheric Particle Depositionsupporting

confidence: 65%

Section: Conclusion Implications and Recommendationsmentioning

confidence: 99%

The particle dry deposition component of total deposition from air quality models: right, wrong or uncertain?

Saylor

Baker

Lee

et al. 2019

Tellus B: Chemical and Physical Meteorology

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“…On the one hand, Gallagher et al [2002] indicate that differences among areas dominated by different vegetation species can be ordered by the roughness length, z 0 . On the other hand, Vong et al [2010] find that leaf area index (LAI) is a dominant factor. These two surface features are obviously related, with the former being dependent on the wind profile above the surface and the latter by the canopy itself.…”

Section: 1002/2015jd024742mentioning

confidence: 99%

Dry deposition of particles to canopies—A look back and the road forward

Hicks¹,

Saylor

Baker

2016

JGR Atmospheres

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The so‐called accumulation‐size range of airborne particles is the center of a continuing disagreement about the formulation of dry deposition. Some contemporary meteorological and air quality models use theoretical developments based on early wind tunnel and other controlled experiments, while other models consider the bulk properties of the underlying surface and the ability of atmospheric turbulence to deliver particles to it. This dichotomy arose when the first micrometeorological measurements of particle deposition velocities became available, yielding numbers exceeding the highest expectations of the then‐current models based on assumptions about inertial impaction and interception. The model predictions had previously been shown to be in accord with theoretical treatments of filtration. A common reaction was to distrust the field experimental results, but the experimental findings were supported by subsequent studies. The difference between model predictions and field measurements appears greatest for densely vegetated canopies. Ongoing research is investigating factors that could give rise to the discrepancy, e.g., turbulence intermittency, leaf orientation, leaf morphology, leaf flutter, electrical charges, and a number of phoretic effects. In the meantime, many investigators are faced with a decision as to whether to make use of parameterized field results or theoretical descriptions of behaviors that are not yet well examined. Here the history of the ongoing disagreement is reviewed, and some possible resolutions are presented.

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“…The influence of particle size on deposition can then only be inferred. Faster samplers have been developed in the last decade and measurements of direct size-resolved particle number flux are being gathered in temperate coniferous forests (Gallagher et al, 1997;Vong et al, 2010;Deventer et al, 2015) and only rarely in tem-perate broadleaf forest (Pryor et al, 2009, on particles smaller than 100 nm) or mixed forest (Gordon et al, 2011).…”

Section: Introductionmentioning

confidence: 99%