Particle size distribution retrieval from multiwavelength lidar signals for droplet aerosol

Pre-filter analysis for retrieval of microphysical particle parameters: a quality-assurance method applied to 3 backscatter (β) +2 extinction (α) optical data taken with HSRL/Raman lidar

We analyze the solution space of 3β+2α optical data inferred from lidar measurements, i.e., backscatter coefficients at three wavelengths and extinction coefficients at two wavelengths. These optical data are governed by microphysical parameters that can be expressed in terms of particle size distribution, effective radius, and complex refractive index (CRI). In our analysis, we consider two scenarios of the solution space. First, it can be expressed in terms of monomodal particle size distributions represented either by fine modes or by coarse modes. Secondly, the particle size distributions contain a fine mode as well as a coarse mode. Consideration of both scenarios and different values of the effective radius and CRI allows us to find synthetic 3β+2α optical data and corresponding intensive parameters (IPs) such as lidar ratios, backscatter- and extinction-related Ångström exponents at the available measurement wavelengths. Based on interdependencies between synthetic IPs and various microphysical properties, the qualitative and quantitative criteria for the optical data quality-assurance tool are developed. We derive the conditions of smoothness, closeness, convergence, and stability of the solution space for the quantitative criteria to test the quality of the 3β+2α optical data. Our novel methodology, to the best of our knowledge, can be used not only for particles of spherical shape, but also for cases in which particles are irregularly shaped. Another strength of our methodology is that it also works for the case of a size-dependent and wavelength-dependent CRI. We show the potential of this methodology for a measurement case from the ORACLES campaign. Data were taken with NASA Langley's airborne HSRL-2 instrument on September 24, 2016.

Study of Mixed Pollution of Haze and Dust in Jinan Based on LiDAR

From 26 March to 30 March 2021, a severe mixed haze and dust pollution process occurred in Jinan, China. Ground light detection and ranging (LiDAR) and satellite radar were used to observe and analyze the mixed pollution. In this study, a variety of data, including the pollutant concentration, meteorological factors, radiosonde data, and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite data, as well as back-trajectory analysis, were employed to analyze the causes of the mixed pollution. The results show that, at the beginning of this weather process, fine particulate matter such as PM2.5 was the main source of pollution, and the low air mass transporting the main pollution originated from nearby cities and polluted industrial areas. After 28 March, due to the influence of a high-altitude Mongolian air mass, the concentration of coarse particulate matter such as PM10 increased significantly. The surface temperature, humidity, and wind speed also affected the accumulation of pollutants, which affected the timely diffusion of the pollution. In this study, ground LiDAR and satellite-based radar were used to detect the pollution. On the basis of a comprehensive analysis of the various meteorological factors, the formation and influence of the pollution were investigated from various perspectives. The extinction coefficient reflected the PM2.5 concentration, verifying the effectiveness of LiDAR in pollution concentration detection. The variation in the boundary layer height also had an important effect on pollution dissipation.

Improved algorithm of aerosol particle size distribution based on remote sensing data

The optical parameters (extinction or backscatter coefficients) of multi-wavelength beams can be used for the retrieval of the aerosol particle size distribution (APSD). An improved algorithm for APSD and aerosol microphysical parameters (AMPs) is studied and discussed by using only multi-wavelength extinction coefficients data. The regularized algorithm and prior value are combined for the retrieval of APSD and AMPs. The regularization algorithm, based on minimum discrepancy principle and averaging procedure, is used for the retrieval of fine-mode APSD and an averaging procedure that can achieve stable outputs is proposed. The 1% averaging result near the minimum of the discrepancy is selected and verified. Based on the inversion results of fine mode from the regularization algorithm, the lognormal distribution with a prior value (model radius) is applied to reconstruct the coarse mode of APSDs through fitting the data. The comprehensive application of the regularization algorithm and averaging process improves the stability of the inversion in the fine mode, and the use of the prior value broadens the inversion radius range of APSD. The complex refractive index need not be assumed for this method. The inversion error for different types of aerosols is analyzed and studied. The reliability of the algorithm is tested and verified by many typical APSDs and the measured APSDs by particle size spectrometer in different pollution days. The algorithm sensitivity analysis is also provided and discussed. The algorithm can obtain reliable inversion of APSD and AMPs with large radius range.

Precise size distribution measurement of aerosol particles and fog droplets in the open atmosphere

A precise measurement for the aerosol particle size distribution and fog droplet size distribution simultaneously in the open atmosphere is proposed. The extinction coefficient and small-angle forward scattering measurement are integrated into the detection for particle size distribution in the open atmosphere, and can achieve the fine detection of the particles in the atmosphere with radius between 0.1 to 30 μm. The key technology including optimal scattering angle in small-angle forward scattering measurement and optimal wavelengths selection are discussed and solved in detail. The fourteen different particle size distributions including aerosol size distributions and fog droplet size distributions are used for the determination of optimal forward scattering angle and wavelengths. The optimal forward scattering angle is calculated to be 1.1°. Seven wavelengths for extinction coefficients and five wavelengths for forward scattering coefficients are chosen for the retrieval of particle size distribution in the measurement. The regularization inversion of optical parameters for the retrieval of particle size distribution is described. The aerosol particle size distributions measured by particle spectrometer and actual fog particle size distributions are used for the method test and the reconstructions of particle size distributions. The inversion results show that the method can achieve the precise measurements of aerosol particle size distribution and fog droplet size distribution. The error influence on the inversion results of distributions is discussed. Based on the sensitivity analysis of inversion results, the feasibility of measurement in the real atmosphere is analyzed and discussed, and the scheme of detection system is provided.

Digital micro-mirror device-based detector for particle-sizing instruments via Fraunhofer diffraction

In this paper, a digital micro-mirror device (DMD)-based detector is proposed for the detection of light intensity in particle-sizing instruments using Fraunhofer diffraction. The detector consists of only one photodiode, which eliminates the distortions caused by the nonuniformity of the detector arrays used in traditional instruments. The center of the diffraction pattern was accurately located to distribute the optimized arc-shaped mirror arrays for the intensity detection. Both simulated and experimental results showed that the proposed detector was superior to the classical one as it was less sensitive to noise than the detector arrays used in traditional systems.

Attenuation of an electromagnetic wave by charged dust particles in a sandstorm

We calculate the light scattering properties of the partially charged dust particles with the Mie theory for electromagnetic waves with different frequencies, and the attenuation coefficients of an electromagnetic wave propagating in a sandstorm are also calculated. The results show that the electric charges distributed on the sand surface have a significant effect on the attenuation of the electromagnetic wave, especially for a frequency lower than 40 GHz, and attenuation coefficients increase with the magnitude of charges carried by the dust particles (expressed by the charge-to-mass ratio in this paper). For the higher frequency electromagnetic wave, such as visible light, the effect of charges carried by sand particles on its attenuation is very little, which can be ignored.

Integral inversion to Fraunhofer diffraction for particle sizing

A new solution to the inversion of Fraunhofer diffraction for particle sizing was introduced. Compared with the well-known Chin-Shifrin inversion, it is an inversion of the form of integral transform and less sensitive to noise. Simulation results with noise-contaminated data were obtained and showed that the new inversion is better than the Chin-Shifrin inversion. Especially when the particle diameter was small, the new inversion still performed well, whereas the Chin-Shifrin inversion did not converge.