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Simulated and experimental data were used to investigate the particle size distribution (PSD) recovery from a flowing aerosol via dynamic light scattering (DLS). It is found that, for a unimodal PSD, increasing the flow velocity leads to an increase in the error of the peak position, a decrease in the peak height and a broadening of the PSD. This is exacerbated for larger aerosol particles. For a bimodal PSD, the separation of the two peaks decreases and results in a single-peak PSD as the velocity increases. The effect of velocity on the measurement is similar to adding signal noise, which increases with the velocity. This effect is related to the measured aerosol particle size. The larger the particles, the lower the signal-to-noise ratio. By comparing DLS measurement results for flowing and non-flowing aerosol samples, it is possible to determine the maximum flow rate at which measurements can be usefully made. [ABSTRACT FROM AUTHOR]

Dynamic light scattering (DLS) is a popular method of particle size measurement, but at ultra-low particle concentrations, the occurrence of number concentration fluctuations limits the use of the technique. Number fluctuations add a non-Gaussian term to the scattered light intensity autocorrelation function (ACF). This leads to an inaccurate particle size distribution (PSD) being recovered if the normal DLS analysis model is used. We propose two methods for inverting the DLS data and recovering the PSDs when number fluctuations are apparent. One is to directly establish the relationship between the non-Gaussian ACF and the PSD by the kernel function reconstruction (KFR) method while including the non-Gaussian term to recover the PSD. The other is to remove the effect of the non-Gaussian term in the ACF by the baseline reset (BR) method. By including the number fluctuation term, the ideal recovered PSD can be obtained from the simulated data, but this will not happen in the experimental measurement data. This is because the measured intensity ACF contains more noise than the simulated ACF at ultra-low concentration. In particular, the baseline noise at the tail of long delay time of ACF overwhelms the number fluctuation term, making it difficult to recover reliable PSD data. Resetting the baseline can effectively remove the digital fluctuation term in ACF, which is also a feasible method to improve PSD recovery under ultra-low concentration. However, increasing noise at ultra-low concentrations can lead to errors in determining an effective baseline. This greatly reduces the accuracy of inversion results. Results from simulated and measured ACF data show that, for both methods, noise on the ACF limits reliable PSD recovery. [ABSTRACT FROM AUTHOR]

• The velocity of flow aerosol is obtained based on cumulants of the intensity autocorrelation function (ACF). • The flow velocity acquisition based on cumulants of ACF is used for both unimodal and bimodal distribution of aerosols. • In the inversion of dynamic light scattering for flow aerosol measurement, the noise widens the distribution, shifts the peak value, and increases the peak height ratio. In the dynamic light scattering (DLS) measurement for a flowing aerosol, an anemometer, is needed to measure the flow velocity to invert the aerosol particle size. In this work, a cumulative analysis method has been used to obtain the aerosol velocity through the light intensity autocorrelation function (ACF) based on the relation between the particle velocity and the second cumulant of the electric field ACF of flowing aerosol particles. Additionally, the particle size distribution (PSD) has been inversed by the regularization method, which enables the online measurement of flowing aerosol to be realized. The simulation results at different noise levels show that the accurate velocity and PSD for flowing aerosols can be obtained by the proposed method at low noise levels and high noise levels. It has been observed that higher noise causes the PSD broadening and the peak offset. For aerosol particles with a bimodal distribution, the increase of noise leads to the increase of peak height ratio and peak of small particles in bimodal distribution disappears, leaving only unimodal distribution. Furthermore, the increase of noise has no significant effect on the calculated velocity value both for unimodal and bimodal aerosol distributions. The experimental results of DLS measurements on unimodal and bimodal aerosols verified the above statements. [ABSTRACT FROM AUTHOR]