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Online identification and characterization of suspended aerosols can provide a scientific basis for understanding aerosol transformations, quantitatively evaluating the impacts on air quality, public health, and the source apportionment of different atmospheric particulate matters. In this study, we confirm the validity of our developed high-throughput multi-angle polarized scattering vector detection of aerosols and multidimensional polarization scattering index systems. By observation of the mean values, variance, and Wilk’s Lambda of multidimensional polarization indices for different aerosol types, the polarization index shows unique characterization abilities for aerosol properties, and the optimal combination of polarization indices can always be found for a specific aerosol category with a high resolution and discrimination. Clearly, the multidimensional polarization indices of individual aerosols are more suitable for online and real-time aerosol identification and even help to explain the in situ microphysical characteristics of aerosols or evaluate the dynamic evolution of aerosols.

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.

The use of Raman and high-spectral lidars enables measurements of a stratospheric aerosol extinction profile independent of backscatter, and a multi-wavelength (MW) lidar can obtain additional information that can aid in retrieving the microphysical characteristics of the sampled aerosol. The inversion method for retrieving aerosol particle size distributions and microphysical particle parameters from MW lidar data was studied. An inversion algorithm for retrieving aerosol particle size distributions based on the regularization method was established. Based on the inversion of regularization, the inversion method was optimized by choosing the base function closest to the aerosol distribution. The logarithmic normal distribution function was selected over the triangle function as the base function for the inversion. The averaging procedure was carried out for three main types of aerosol. The 1% averaging result near the minimum of the discrepancy gave the best estimate of the particle parameters. The accuracy and stabilization of the optimized algorithm for microphysical parameters were tested by scores of aerosol size distributions. The systematic effects and random errors impacting the inversion were also considered, and the algorithm was tested by the data, showing 10% systematic error and 15% random error. At the same time, the reliability of the proposed algorithm was also verified by using the aerosol particle size distribution data of the aircraft. The inversion results showed that the algorithm was reliable in retrieving the aerosol particle size distributions at vertical heights using lidar data.

A Mie scattering radar system with a white light-emitting diode (LED) light source is proposed for the multi-wavelength detection of atmospheric aerosols. By splitting the continuous spectrum, the multi-wavelength echo signals are extracted to achieve multi-wavelength real-time detection of atmospheric aerosols. The white LED spectrum characteristics are analyzed, and four detection wavelengths are set at 450, 525, 600, and 661 nm. The composition and detection principles of a white LED light source radar system are expounded, the design of each system part is described in detail, and the system parameters and data inversion algorithm are presented. We built a white LED light source radar system and conducted preliminary observation experiments. The results show that radar can achieve multi-wavelength real-time detection of atmospheric aerosols within a 300 m height, which can provide effective data for further study of aerosol particle distribution and lay a foundation for further studies of aerosol characteristics at special wavelengths.

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.

In order to investigate the aerosol variability over the southwest region of Slovenia, an ultraviolet scanning elastic backscatter LiDAR was utilized to make the vertical scan for atmospheric probing. With the assumption of horizontal atmospheric homogeneity, aerosol optical variables were retrieved from the horizontal pixel data points of two-dimensional range-height-indicator (RHI) diagrams by using a multiangle retrieval method, in which optical depth is defined as the slope of the resulting linear function when height is kept constant. To make the data retrieval feasible and precise, a series of key procedures complemented the data processing, including construction of the RHI diagram, correction of Rayleigh scattering, assessment of horizontal atmospheric homogeneity and retrieval of aerosol optical variables. The measurement example demonstrated the feasibility of the ultraviolet scanning elastic backscatter LiDAR in the applications of the retrieval of aerosol extinction and determination of the atmospheric boundary layer height. Three months’ data combined with the modeling of air flow trajectories using Hybrid Single Particle Lagrangian Integrated Trajectory Model were analyzed to investigate aerosol variability. The average value of aerosol extinction with the presence of land-based air masses from the European continent was found to be two-times larger than that influenced by marine aerosols from the Mediterranean or Adriatic Sea.

Aiming at the detection of water vapor mixing ratio, particle linear depolarization ratio, extinction coefficient and cloud information, the Water vapor, Cloud and Aerosol Lidar (WVCAL) was developed by the lidar group at Ocean University of China. The Lidar consists of transmitting subsystem, receiving subsystem, data acquisition and controlling subsystem and auxiliary subsystem. These parts were presented and described in this paper. For the measurement of various physical properties, three channels including Raman channel, polarization channel and infrared channel are integrated in this Lidar system. In this paper, the integration and working principle of these channels is introduced in details. Finally, a measurement example which was operated in coastal area-Qingdao, Shandong province, during 2014 is provided.

In order to improve accuracy of aerosol measurements, a novel method using twin scanning lidars is presented; this method is able to overcome the incomplete overlap range of vertical lidar as well as provide 2D spatial distributions. The scanning lidar setups in the opposite directions are employed as remote sensing tools. Aerosol measurements are performed with cross scanning from the ground to the height of interest. Aerosol optical properties are retrieved using numerical approximation, in which differences between the measured values and the constructed values of the logarithmic range-square-corrected lidar data in the cross-scanning region are minimized. In the data retrieval, we utilize a matrix formulation, in which a Cartesian 2D range-height-indicator diagram is constructed. To verify this method, scanning measurements by ultraviolet Mie scanning lidar performed at different time intervals were taken as the cross-scanning measurements from the twin scanning lidars. With the retrieved spatial distributions of aerosol optical properties, such as aerosol backscatter, aerosol extinction, and lidar ratio, the regional aerosol studies showed that aerosol loading was relatively small and in the presence of multiple layers, which may be influenced by airflow from long-range transportation and cause a large impact on the local environment. To conclude, the presented method using twin scanning lidars is feasible for aerosol measurement in the application of horizontally atmospheric inhomogeneity.

Aiming at the detection of atmospheric water vapor mixing ratio, depolarization ratio, backscatter coefficient, extinction coefficient and cloud information, the Water vapor, Cloud and Aerosol Lidar (WACAL) is developed by the lidar group at Ocean University of China. The lidar consists of transmitter, receiver, data acquisition and auxiliary system. For the measurement of various atmospheric physical properties, three channels including Raman channel, polarization channel and infrared channel are integrated in WACAL. The integration and working principle of these channels are introduced in details. The optical setup, the housekeeping of the system and the data retrieval routines are also presented. After the completion of the construction of the lidar, the WACAL system was installed in Ocean University of China (36.165°N, 120.5°E), Qingdao for the measurement of atmosphere during 2013 and 2014. The measurement principles and some case studies corresponding to various atmospheric physical properties are provided. Finally, the result of one continuous measurement example operated on 13 June 2014 is presented. The WACAL can measure the aerosol and cloud optical properties as well as the water vapor mixing ratio. It is useful for studying the direct and indirect effects of the aerosol on the climate change.

Telescopes in polarization lidar often modify the input polarization of the return signal, such that the telescope may significantly impact the depolarization estimates of aerosol and introduce error to the polarization lidar measurements. The error cannot be corrected by a traditional calibration constant. We present a method to correct the polarization effect of the telescope. We analyze the polarization effect of a telescope on the basis of the Mueller formalism, and introduce an algorithm for correcting the depolarization parameter of aerosol. A Newton telescope and a Cassegrain telescope are often chosen as the receiver in lidar. Their polarization models are established, and the Mueller matrices are calculated. The components of these matrices are dependent on wavelength, incident angle of the incoming light, and surface properties. The polarization impact of the telescope in lidar can be calibrated by a parameter, and the effects of different telescopes are discussed. The polarization crosstalk induced by the Newton telescope is obvious. The depolarization parameters change greatly with coating and wavelength, and they are calculated and presented. Whereas the crosstalk of a Cassegrain telescope is much smaller, the error can reach the level of 10−3 and can be negligible. The method presented in this paper could also be upgraded by taking into account all of the optical devices instead of only the telescope.