scholarly journals A New Mechanism of Droplet Size Distribution Broadening during Diffusional Growth

2013 ◽  
Vol 70 (7) ◽  
pp. 2051-2071 ◽  
Author(s):  
Alexei Korolev ◽  
Mark Pinsky ◽  
Alex Khain
Keyword(s):  
Size Distribution ◽  
Droplet Size ◽  
Initial Conditions ◽  
Droplet Size Distribution ◽  
Cloud Base ◽  
Diffusional Growth ◽  
Cloud Droplets ◽  
Droplet Concentration ◽  
Droplet Sizes ◽  
Precipitation Formation

Abstract A new mechanism has been developed for size distribution broadening toward large droplet sizes. This mechanism may explain the rapid formation of large cloud droplets, which may subsequently trigger precipitation formation through the collision–coalescence process. The essence of the new mechanism consists of a sequence of mixing events between ascending and descending parcels. When adiabatically ascending and descending parcels having the same initial conditions at the cloud base arrive at the same level, they will have different droplet sizes and temperatures, as well as different supersaturations. Isobaric mixing between such parcels followed by further ascents and descents enables the enhanced growth of large droplets. The numerical simulation of this process suggests that the formation of large 30–40-μm droplets may occur within 20–30 min inside a shallow adiabatic stratiform layer. The dependencies of the rate of the droplet size distribution broadening on the intensity of the vertical fluctuations, their spatial amplitude, rate of mixing, droplet concentration, and other parameters are considered here. The effectiveness of this mechanism in different types of clouds is discussed.

scholarly journals Aerosol indirect effect from turbulence-induced broadening of cloud-droplet size distributions

2016 ◽  
Vol 113 (50) ◽  
pp. 14243-14248 ◽  
Author(s):  
Kamal Kant Chandrakar ◽  
Will Cantrell ◽  
Kelken Chang ◽  
David Ciochetto ◽  
Dennis Niedermeier ◽  
...  
Keyword(s):  
Size Distribution ◽  
Droplet Size ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Aerosol Concentration ◽  
Droplet Radius ◽  
Droplet Growth ◽  
Moist Convection ◽  
Concentration Changes ◽  
Precipitation Formation

The influence of aerosol concentration on the cloud-droplet size distribution is investigated in a laboratory chamber that enables turbulent cloud formation through moist convection. The experiments allow steady-state microphysics to be achieved, with aerosol input balanced by cloud-droplet growth and fallout. As aerosol concentration is increased, the cloud-droplet mean diameter decreases, as expected, but the width of the size distribution also decreases sharply. The aerosol input allows for cloud generation in the limiting regimes of fast microphysics (τc<τt) for high aerosol concentration, and slow microphysics (τc>τt) for low aerosol concentration; here, τc is the phase-relaxation time and τt is the turbulence-correlation time. The increase in the width of the droplet size distribution for the low aerosol limit is consistent with larger variability of supersaturation due to the slow microphysical response. A stochastic differential equation for supersaturation predicts that the standard deviation of the squared droplet radius should increase linearly with a system time scale defined as τs−1=τc−1+τt−1, and the measurements are in excellent agreement with this finding. The result underscores the importance of droplet size dispersion for aerosol indirect effects: increasing aerosol concentration changes the albedo and suppresses precipitation formation not only through reduction of the mean droplet diameter but also by narrowing of the droplet size distribution due to reduced supersaturation fluctuations. Supersaturation fluctuations in the low aerosol/slow microphysics limit are likely of leading importance for precipitation formation.

scholarly journals A Comprehensive Approach from Interfacial to Bulk Properties of Legume Protein-Stabilized Emulsions

Fluids ◽  
2019 ◽  
Vol 4 (2) ◽  
pp. 65 ◽  
Author(s):  
Manuel Félix ◽  
Alberto Romero ◽  
Cecilio Carrera-Sanchez ◽  
Antonio Guerrero
Keyword(s):  
Rheological Properties ◽  
Size Distribution ◽  
Droplet Size ◽  
Electrostatic Interactions ◽  
Ph Value ◽  
Droplet Size Distribution ◽  
Interfacial Properties ◽  
Industrial Applications ◽  
Droplet Sizes ◽  
Legume Protein

The correlation between interfacial properties and emulsion microstructure is a topic of special interest that has many industrial applications. This study deals with the comparison between the rheological properties of oil-water interfaces with adsorbed proteins from legumes (chickpea or faba bean) and the properties of the emulsions using them as the only emulsifier, both at microscopic (droplet size distribution) and macroscopic level (linear viscoelasticity). Two different pH values (2.5 and 7.5) were studied as a function of storage time. Interfaces were characterized by means of dilatational and interfacial shear rheology measurements. Subsequently, the microstructure of the final emulsions obtained was evaluated thorough droplet size distribution (DSD), light scattering and rheological measurements. Results obtained evidenced that pH value has a strong influence on interfacial properties and emulsion microstructure. The best interfacial results were obtained for the lower pH value using chickpea protein, which also corresponded to smaller droplet sizes, higher viscoelastic moduli, and higher emulsion stability. Thus, results put forward the relevance of the interfacial tension values, the adsorption kinetics, the viscoelastic properties of the interfacial film, and the electrostatic interactions among droplets, which depend on pH and the type of protein, on the microstructure, rheological properties, and stability of legume protein-stabilized emulsions.

scholarly journals Quantifying the aerosol effect on droplet size distribution at cloud top

2019 ◽  
Vol 19 (11) ◽  
pp. 7839-7857
Author(s):  
Lianet Hernández Pardo ◽  
Luiz Augusto Toledo Machado ◽  
Micael Amore Cecchini ◽  
Madeleine Sánchez Gácita
Keyword(s):  
Size Distribution ◽  
Droplet Size ◽  
Initial Conditions ◽  
Cloud Condensation Nuclei ◽  
Droplet Size Distribution ◽  
Number Concentration ◽  
Population Characteristics ◽  
Aerosol Size Distribution ◽  
Effective Diameter ◽  
Distribution Sensitivity

Abstract. This work uses the number concentration-effective diameter phase-space to test cloud sensitivity to variations in the aerosol population characteristics, such as the aerosol size distribution, number concentration and hygroscopicity. It is based on the information from the top of a cloud simulated by a bin-microphysics single-column model, for initial conditions typical of the Amazon, using different assumptions regarding the entrainment and the aerosol size distribution. It is shown that the cloud-top evolution can be very sensitive to aerosol properties, but the relative importance of each parameter is variable. The sensitivity to each aerosol characteristic varies as a function of the parameter tested and is conditioned by the base values of the other parameters, showing a specific dependence for each configuration of the model. When both the entrainment and the bin treatment of the aerosol are allowed, the largest influence on the droplet size distribution sensitivity was obtained for the median radius of the aerosols and not for the total number concentration of aerosols. Our results reinforce that the cloud condensation nuclei activity can not be predicted solely on the basis of the w∕Na supersaturation-based regimes.

scholarly journals Influence of Microphysical Variability on Stochastic Condensation in a Turbulent Laboratory Cloud

2018 ◽  
Vol 75 (1) ◽  
pp. 189-201 ◽  
Author(s):  
N. Desai ◽  
K. K. Chandrakar ◽  
K. Chang ◽  
W. Cantrell ◽  
R. A. Shaw
Keyword(s):  
Relaxation Time ◽  
Size Distribution ◽  
Droplet Size ◽  
Droplet Size Distribution ◽  
Number Concentration ◽  
Droplet Growth ◽  
Diffusional Growth ◽  
Phase Relaxation ◽  
Distribution Width ◽  
Phase Relaxation Time

Diffusional growth of droplets by stochastic condensation and a resulting broadening of the size distribution has been considered as a mechanism for bridging the cloud droplet growth gap between condensation and collision–coalescence. Recent studies have shown that supersaturation fluctuations can lead to a broadening of the droplet size distribution at the condensational stage of droplet growth. However, most studies using stochastic models assume the phase relaxation time of a cloud parcel to be constant. In this paper, two questions are asked: how variability in droplet number concentration and radius influence the phase relaxation time and what effect it has on the droplet size distributions. To answer these questions, steady-state cloud conditions are created in the laboratory and digital inline holography is used to directly observe the variations in local number concentration and droplet size distribution and, thereby, the integral radius. Stochastic equations are also extended to account for fluctuations in integral radius and obtain new terms that are compared with the laboratory observations. It is found that the variability in integral radius is primarily driven by variations in the droplet number concentration and not the droplet radius. This variability does not contribute significantly to the mean droplet growth rate but does contribute significantly to the rate of increase of the size distribution width.

Impact of cloud base turbulence on CCN activation: Single size CCN

2021 ◽  
Keyword(s):  
Droplet Size ◽  
Initial Conditions ◽  
Cloud Condensation Nuclei ◽  
Droplet Size Distribution ◽  
Spectral Width ◽  
Cloud Base ◽  
Computational Domain ◽  
Critical Supersaturation ◽  
The Impact ◽  
Single Size

Abstract This paper examines the impact of cloud-base turbulence on activation of cloud condensation nuclei (CCN). Following our previous studies, we contrast activation within a non-turbulent adiabatic parcel and an adiabatic parcel filled with turbulence. The latter is simulated by applying a forced implicit large eddy simulation within a triply periodic computational domain of 643 m3. We consider two monodisperse CCN. Small CCN have a dry radius of 0.01 micron and a corresponding activation (critical) radius and critical supersaturation of 0.6 micron and 1.3%, respectively. Large CCN have a dry radius of 0.2 micron and feature activation radius of 5.4 micron and critical supersaturation 0.15 %. CCN are assumed in 200 cm−3 concentration in all cases. Mean cloud base updraft velocities of 0.33, 1, and 3 m s−1 are considered. In the non-turbulent parcel, all CCN are activated and lead to a monodisperse droplet size distribution above the cloud base, with practically the same droplet size in all simulations. In contrast, turbulence can lead to activation of only a fraction of all CCN with a non-zero spectral width above the cloud base, of the order of 1 micron, especially in the case of small CCN and weak mean cloud base ascent. We compare our results to studies of the turbulent single-size CCN activation in the Pi chamber. Sensitivity simulations that apply a smaller turbulence intensity, smaller computational domain, and modified initial conditions document the impact of specific modeling assumptions. The simulations call for a more realistic high-resolution modeling of turbulent cloud base activation.

Cloud water composition in relation to the droplet size distribution and cloud base altitude

2000 ◽  
Vol 31 ◽  
pp. 301-302
Author(s):  
W. Wieprecht ◽  
D. Moeller ◽  
K. Acker ◽  
R. Auel ◽  
D. Kalass
Keyword(s):  
Size Distribution ◽  
Droplet Size ◽  
Droplet Size Distribution ◽  
Cloud Water ◽  
Cloud Base ◽  
Water Composition

Turbulence Effects of Collision Efficiency and Broadening of Droplet Size Distribution in Cumulus Clouds

2018 ◽  
Vol 75 (1) ◽  
pp. 203-217 ◽  
Author(s):  
Sisi Chen ◽  
M. K. Yau ◽  
Peter Bartello
Keyword(s):  
Size Distribution ◽  
Droplet Size ◽  
Droplet Size Distribution ◽  
Droplet Growth ◽  
Small Scale ◽  
Cumulus Clouds ◽  
Collision Efficiency ◽  
Cloud Droplets ◽  
R Ratio ◽  
Condensational Growth

This paper aims to investigate and quantify the turbulence effect on droplet collision efficiency and explore the broadening mechanism of the droplet size distribution (DSD) in cumulus clouds. The sophisticated model employed in this study individually traces droplet motions affected by gravity, droplet disturbance flows, and turbulence in a Lagrangian frame. Direct numerical simulation (DNS) techniques are implemented to resolve the small-scale turbulence. Collision statistics for cloud droplets of radii between 5 and 25 μm at five different turbulence dissipation rates (20–500 cm2 s−3) are computed and compared with pure-gravity cases. The results show that the turbulence enhancement of collision efficiency highly depends on the r ratio (defined as the radius ratio of collected and collector droplets r/ R) but is less sensitive to the size of the collector droplet investigated in this study. Particularly, the enhancement is strongest among comparable-sized collisions, indicating that turbulence can significantly broaden the narrow DSD resulting from condensational growth. Finally, DNS experiments of droplet growth by collision–coalescence in turbulence are performed for the first time in the literature to further illustrate this hypothesis and to monitor the appearance of drizzle in the early rain-formation stage. By comparing the resulting DSDs at different turbulence intensities, it is found that broadening is most pronounced when turbulence is strongest and similar-sized collisions account for 21%–24% of total collisions in turbulent cases compared with only 9% in the gravitational case.

Modeling Subsurface Dispersant Applications for Response Planning and Preparation

2014 ◽  
Vol 2014 (1) ◽  
pp. 933-948 ◽  
Author(s):  
Deborah Crowley ◽  
Daniel Mendelsohn ◽  
Nicole Whittier Mulanaphy ◽  
Zhengkai Li ◽  
Malcolm Spaulding
Keyword(s):  
Interfacial Tension ◽  
Water Column ◽  
Size Distribution ◽  
Droplet Size ◽  
Droplet Size Distribution ◽  
Relative Volume ◽  
Modeling Tools ◽  
Droplet Sizes ◽  
Oil Water ◽  
The Relationship

ABSTRACT The increase in oil and gas development activity at increasing water depths has highlighted the need for modeling tools to evaluate the unique aspects of accidental deepwater releases, one aspect being the need to assess the impact of subsurface dispersant application to a deepwater blowout. In response to this need, the effect of subsurface dispersant application has been implemented within RPS ASA's blowout model OILMAPDeep. OILMAPDeep was developed to simulate deepwater blowout releases; it predicts the evolution and characteristics of the subsurface plume and estimates the oil droplet size distribution associated with the release. The droplet size distribution dictates the vertical transport of oil within the water column, and impacts the relative volume anticipated to either surface or remain trapped in the water column. Droplet sizes are primarily a function of the energy of the release and the oil-water interfacial tension. The energy of the release is characterized by a reference velocity, typically the exit velocity, and the oil-water interfacial tension as a function of the oil properties. Dispersants mixed with oil reduce the oil-water interfacial tension, which in turn reduces the droplet sizes associated with treated releases serving to delay or eliminate surfacing oil. The present model implementation takes advantage of recent studies that have quantitatively assessed the relationship between the dispersant to oil ratio and surface tension. Here we present a background of the OILMAPDeep module, the governing physical processes of droplet formation, and the relationship between dispersant-to-oil ratio (DOR) and droplet size formation as characterized in the model. A description of the model implementation including model inputs and outputs are provided. Furthermore a set of scenarios are presented that demonstrate the model's capabilities for planning and preparing response activities in the event of a potential oil well blowout. This paper shows how the implementation of subsurface dispersant application within OILMAPDeep provides an effective means of evaluating potential response activities associated with subsurface dispersant application to a deepwater blowout. This includes evaluating the effect of subsurface dispersant application on droplet size distribution, and the ultimate impact on the timing, location and the relative volume of surfacing oil.

scholarly journals Chemical composition and droplet size distribution of cloud at the summit of Mount Tai, China

2017 ◽  
Author(s):  
Jiarong Li ◽  
Xinfeng Wang ◽  
Jianmin Chen ◽  
Chao Zhu ◽  
Weijun Li ◽  
...  
Keyword(s):  
Chemical Composition ◽  
Size Distribution ◽  
Droplet Size ◽  
Atmospheric Aerosols ◽  
Ph Value ◽  
Inorganic Ions ◽  
Droplet Size Distribution ◽  
Dilution Effect ◽  
Water Soluble ◽  
Cloud Droplets

Abstract. Chemical composition of 39 cloud samples and droplet size distribution in 24 cloud events were investigated at the summit of Mt. Tai from July to October 2014. Inorganic ions, organic acids, metals, HCHO, H2O2, sulfur(IV), organic carbon, element carbon as well as pH and electrical conductivity were analyzed. The acidity of the cloud water significantly decreased from a reported value of pH 3.86 in 2007–2008 (Guo et al., 2012) to pH 5.87 in the present study. The concentrations of nitrate and ammonium were both increased since 2007–2008, but the overcompensation of ammonium led to the increase of the mean pH value. The microphysical properties showed that cloud droplets were smaller than 26.0 μm and the most were in the range of 6.0–9.0 μm. The maximum droplet number concentration (Nd) was associated with droplet sizes of 7.0 μm. Cloud droplets exhibited a strong interaction with atmospheric aerosols. High PM2.5 level resulted in higher concentrations of water soluble ions and smaller sizes with more numbers of cloud droplets, and further gave rise to relatively high acidity. High degrees of relative humidity facilitated the formation of large cloud droplets and led to high liquid water contents under low PM2.5 level. The cloud droplets to wet deposition acted as an important sink of soluble material in the atmosphere and the dilution effect of the water content should be considered when estimating concentrations of soluble components in the cloud phase.

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