A study of particle size distributions

Yu, Aibing; Standish, N.

doi:10.1016/0032-5910(90)80073-8

Cited by 103 publications

(37 citation statements)

References 20 publications

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“…The use of this distribution has also been inspired by (Cugerone and De Michele, 2015;D'Adderio et al, 2016); and (Cugerone and De Michele, 2017), where the authors have recently demonstrated the accuracy of this probability function in modelling the number size distribution of drops at the ground, a particular case of PNSD. Furthermore, the outcomes of this study are in accordance with the works of (Yu and Standish, 1990) and (Liu and Liu, 1994), in which JSB was firstly proposed for this aim. In order to statistically prove the adequacy of this distribution, we use the skewnesskurtosis moment ratio diagram (S-K plane), the locus of the couples skewness (β 3 ) and kurtosis (β 4 ) as a diagnostic tool (Vargo et al, 2010).…”

Section: Introductionsupporting

confidence: 83%

On the functional form of particle number size distributions: influence of particle source and meteorological variables

et al. 2018

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Abstract. Particle number size distributions (PNSDs) have been collected periodically in the urban area of Milan, Italy, during 2011 and 2012 in winter and summer months. Moreover, comparable PNSD measurements were carried out in the rural mountain site of Oga-San Colombano (2250 m a.s.l.), Italy, during February 2005 and August 2011. The aerosol data have been measured through the use of optical particle counters in the size range 0.3-25 µm, with a time resolution of 1 min. The comparison of the PNSDs collected in the two sites has been done in terms of total number concentration, showing higher numbers in Milan (often exceeding 10 3 cm −3 in winter season) compared to Oga-San Colombano (not greater than 2×10 2 cm −3 ), as expected. The skewness-kurtosis plane has been used in order to provide a synoptic view, and select the best distribution family describing the empirical PNSD pattern. The four-parameter Johnson system-bounded distribution (called Johnson SB or JSB) has been tested for this aim, due to its great flexibility and ability to assume different shapes. The PNSD pattern has been found to be generally invariant under site and season changes. Nevertheless, several PNSDs belonging to the Milan winter season (generally more than 30 %) clearly deviate from the standard empirical pattern. The seasonal increase in the concentration of primary aerosols due to combustion processes in winter and the influence of weather variables throughout the year, such as precipitation and wind speed, could be considered plausible explanations of PNSD dynamics.

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Section: Introductionsupporting

confidence: 83%

On the functional form of particle number size distributions: influence of particle source and meteorological variables

et al. 2018

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“…The simulated ACF data were generated using PSDs by numbers described by Johnson's S B function [17]:…”

Section: Simulation Of Mdls Datamentioning

confidence: 99%

Effect of scattering angle error on particle size determination by multiangle dynamic light scattering

et al. 2015

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Dynamic light scattering (DLS) is a popular method of particle size measurement. Multiangle dynamic light scattering (MDLS) collects DLS data at multiple angles and analyzes the data simultaneously to improve the particle size measurement. Using data from several scattering angles admits the possibility of introducing noise caused by scattering angle error in the measurement, which may have an impact on the performance of the MDLS technique. We investigate the effect of scattering angle noise on recovered particle size distributions (PSDs) using simulated and measured MDLS data and various levels of angular noise. Our results show that, for unimodal PSDs, those with small particle sizes are more strongly affected by the noise than are medium and large particle size systems. For bimodal PSDs, those containing small-sized particles are also more affected by the noise than the systems of larger particles. Furthermore, broad PSDs are more vulnerable to angular noise than narrow PSDs.

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“…Johnson's S B function [32] was used to simulate PSDs, and it could be expressed as follows: In Eq. (16), m and s are distribution parameters, t is the normalized particle size.…”

Section: Numerical Simulation Resultsmentioning

confidence: 99%

The reconstruction of particle size distributions from dynamic light scattering data using particle swarm optimization techniques with different objective functions

Zhu

Shen

Wang

et al. 2011

Optics & Laser Technology

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A study of particle size distributions

Cited by 103 publications

References 20 publications

On the functional form of particle number size distributions: influence of particle source and meteorological variables

On the functional form of particle number size distributions: influence of particle source and meteorological variables

Effect of scattering angle error on particle size determination by multiangle dynamic light scattering

The reconstruction of particle size distributions from dynamic light scattering data using particle swarm optimization techniques with different objective functions

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