Size-resolved eddy covariance measurements of fine particle vertical fluxes

Damay, P.; Maro, D.; Coppalle, A.; Lamaud, Éric; Connan, O.; Hébert, D.; Talbaut, M.; Irvine, Mark

doi:10.1016/j.jaerosci.2009.09.010

Cited by 24 publications

(17 citation statements)

References 18 publications

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“…Dry deposition velocities have been analysed selecting downward fluxes for the different datasets to separate emission (upward fluxes often associated with local sources) from deposition processes [47,48]. In general, under turbulence conditions, especially during daytime, dry deposition is controlled by the settling velocity, aerodynamic resistance, turbulent diffusion of the particles (Brownian motion), and their impaction and interception [26].…”

Section: Resultsmentioning

confidence: 99%

Correlation of Dry Deposition Velocity and Friction Velocity over Different Surfaces for PM2.5 and Particle Number Concentrations

Donateo

Contini

2014

Advances in Meteorology

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Dry deposition of particles is an important way of aerosol removal from the atmosphere and a key process in surface-atmosphere exchanges. The deposition velocities, Vd, are often parameterised in air quality and climate modelling as function of the friction velocity,u*, atmospheric stability, and particle size (if size-segregated information is available). In this work, a study of the correlation between Vd andu*over different surfaces is presented for both PM2.5 and particle number fluxes. Results indicate an almost linear increase of Vd withu*with slopes similar for PM2.5 fluxes and particle number fluxes over the different surfaces analysed. This means that the ratios Vd/u*tend to collapse over similar values even if Vd andu*are significantly different becauseu*take into account most of the surface effects. There is a limited difference between stable cases and unstable/neutral cases with slightly lower deposition velocities in stable cases for fixed values ofu*. The average value of Vd/u*is 0.010 ± 0.0017 (median 0.0062 ± 0.0015) (considering all stabilities) and 0.0097 ± 0.002 (median 0.005 ± 0.001) for stable cases. This could be the base for an empirical parameterisation of deposition velocities in air quality models.

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Section: Resultsmentioning

confidence: 99%

Correlation of Dry Deposition Velocity and Friction Velocity over Different Surfaces for PM2.5 and Particle Number Concentrations

Donateo

Contini

2014

Advances in Meteorology

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“…The technique can provide modest to high resolution (ratio of peak to FWHM >10, with much larger values possible), that is capable of resolving monodisperse and polydisperse distributions, with the simultaneous ability to quantify the extent of asphericity in non-spherical particle and droplets. While our focus in this study was on size and shape distribution functions, the ability to extract multidimensional distribution functions can be extended to examine velocity/flux distributions (Damay et al, 2009) turbulent deposition and dispersion of aerosols (Nicholson, 1988) which we hope to target in future studies.…”

Section: Discussionmentioning

confidence: 99%

Automated droplet size distribution measurements using digital inline holography

Kumar

Hogan

et al. 2019

Journal of Aerosol Science

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Droplet generation through spray breakup is an unsteady and non-linear process which produces a relatively dense, highly polydisperse aerosol containing non-spherical droplets with sizes spanning several orders of magnitude. Such variability in size and shape can lead to significant sources of error for conventional measurements based on laser scattering. Although direct imaging of droplets can potentially overcome these limitations, imaging suffers from a shallow depth of field as well as occlusions, which prevents the complete spray from being analyzed. In comparison, digital inline holography (DIH), a low cost coherent imaging technique, can enable high resolution imaging of the sample over an extended depth of field, typically several orders of magnitude larger than traditional imaging. In this study, we showcase an automated DIH imaging system for characterizing monodisperse and polydisperse aerosol droplet size and shape distributions in the 20 m -3 mm diameter range, over a large sample volume. The high accuracy of the technique is demonstrated by measurements of monodisperse droplets generated by a vibrating orifice droplet generator, achieving a resolution of ~14.2. Measurements of a polydisperse spray from a flat fan nozzle serve to establish the versatility of DIH in extracting a two-dimensional size-eccentricity distribution function, which indicates a strong semilogarithmic scaling between the two parameters that decays as the droplet migrates away from the nozzle. Due to its low cost and compact setup as well as high density of data obtained, DIH can serve as a promising approach for future aerosol characterization.

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“…Most studies having measured particle flux from this technique focused on the quantification of the flux itself and not on its analogy with momentum or heat fluxes. These studies were mainly performed over urban areas (Deventer, El‐Madany, et al, ; Dorsey et al, ; Ma˙rtensson et al, ), vegetated surfaces (Damay et al, ; Deventer, Held, et al, ), and much less over desert areas (Fratini et al, ; Porch & Gillette, ). The only studies comparing particle and heat turbulent transports either observed similarity between both scalars (Fratini et al, ; Ma˙rtensson et al, ) or assumed similarity to correct their particle flux from the heat flux due to the slow response time of their particle counter (Damay et al, ; Deventer, Held, et al, ).…”

Section: Introductionmentioning

confidence: 99%

“…These studies were mainly performed over urban areas (Deventer, El‐Madany, et al, ; Dorsey et al, ; Ma˙rtensson et al, ), vegetated surfaces (Damay et al, ; Deventer, Held, et al, ), and much less over desert areas (Fratini et al, ; Porch & Gillette, ). The only studies comparing particle and heat turbulent transports either observed similarity between both scalars (Fratini et al, ; Ma˙rtensson et al, ) or assumed similarity to correct their particle flux from the heat flux due to the slow response time of their particle counter (Damay et al, ; Deventer, Held, et al, ). Hence, in these studies particles are usually considered as passive scalars with the same source/sink distributions as heat.…”

Section: Introductionmentioning

confidence: 99%

Dissimilarity Between Dust, Heat, and Momentum Turbulent Transports During Aeolian Soil Erosion

et al. 2019

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Measuring accurately size‐resolved dust flux near the surface is crucial for better quantifying dust losses by semiarid soils. Dust fluxes have been usually estimated from the flux‐gradient approach, assuming similarity between dust and momentum turbulent transport. This similarity has, however, never been verified. Here we investigate the similarity between dust (0.3 to 6.0 μm in diameter), momentum, and heat fluxes during aeolian erosion events. These three fluxes were measured by the Eddy Covariance technique during the WIND‐O‐V (WIND erOsion in presence of sparse Vegetation's) 2017 field experiment over an isolated erodible bare plot in South Tunisia. Our measurements confirm the prevalence of ejection and sweep motions in transporting dust as for heat and momentum. However, our measurements also reveal a different partition of the dust flux between ejection and sweep motions and between eddy time scales compared to that of momentum and heat fluxes. This dissimilarity results from the intermittency of the dust emission compared to the more continuous emission (absorption) of heat (momentum) at the surface. Unlike heat emission and momentum absorption, dust release is conditioned by the wind intensity to initiate sandblasting. Consequently, ejection motions do not carry dust as often as heat and low momentum from the surface. This dissimilarity diminishes with increasing wind intensity as saltation patterns, and thus dust emission through sandblasting, become spatially more frequent. Overall, these findings may have implications on the evaluation of dust flux from techniques based on similarity with momentum or heat turbulent transport.

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Size-resolved eddy covariance measurements of fine particle vertical fluxes

Cited by 24 publications

References 18 publications

Correlation of Dry Deposition Velocity and Friction Velocity over Different Surfaces for PM2.5 and Particle Number Concentrations

Correlation of Dry Deposition Velocity and Friction Velocity over Different Surfaces for PM2.5 and Particle Number Concentrations

Automated droplet size distribution measurements using digital inline holography

Dissimilarity Between Dust, Heat, and Momentum Turbulent Transports During Aeolian Soil Erosion

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