The suspended particle in the environment is an indispensable component of the atmospheric system. Because of the uncertainty in time and space, it is difficult to identify and characterize the suspension system accurately in real time. Researchers in related fields focus on obtaining the online index system of the interaction between suspended particles and light technically, simulating the process and mechanism of the interaction between suspended particles and light theoretically, and then identifying and distinguishing the microphysical properties of suspended particles qualitatively and quantitatively by light scattering detection. The polarization scattering analysis in optical measurement can not only detect the original particle scattering process but also expand the information dimension of experimental data by polarization vector analysis, providing the possibility for the fine identification of different particle classes and attribute differences.

The light intensity distribution on the scattered sphere will change when the size, refractive index, structure, and other factors of suspended particles change. Based on the number of particles, the light scattering method can be divided into group suspended particle and single suspended particle detection.

1) Group suspended particle detection technology. In the field of atmospheric climate prediction, the measurement of group suspended particles has broad application value. Han et al. designed an aerodynamic particle size spectrometer (APS) probe for measuring aerosol size distribution and an integral turbidimeter for measuring the total light scattering coefficient (Fig. 1) to measure the scattering coefficient, particle size, and complex refractive index of aerosol suspended particles, respectively.

In the field of aerosol identification, LiDAR technology is widely used in aerosol monitoring and identification since it can provide longitudinal profile aerosol distribution information. Costabile et al. proposed a scheme to classify aerosol populations based on the spectral optical properties of suspended particles. Groß et al. proposed an aerosol identification scheme based on high spectral resolution lidar (HSRL) (Fig. 2) to analyze the two-dimensional graph of the lidar coefficient and linear polarization parameter to determine the aerosol type. However, such methods can only identify a limited number of aerosols and are limited to the analysis of two-component mixtures.

2) Single suspended particle detection technology. Kaye et al. designed a suspended particle detection instrument based on spatial light scattering [Fig. 3(a)], which qualitatively analyzed the types of particles through angular scattered light and fluorescence intensity, effectively avoiding false positive detection of bioaerosols. Ding et al. designed an instrument that can measure multi-angle scattered light [Fig. 3(a)], enabling measurement and signal acquisition of 250 to 500 suspended particles per minute at three scattering angles (0°, 120°, and 240°), and the experimental results proved its feasibility in identifying spherical and irregular particles. In addition, Renard et al. designed a continuous particle monitor based on small-angle scattered light, enabling real-time monitoring of the concentration of suspended particles in the environment. By integrating active microfluidic and optical fluid technology into a single PDMS chip, Parks et al. demonstrated the feasibility of microfluidic chips for manipulating and detecting individual fluorescent particles.

3) Polarized light suspended particle measurement technology. The particle information extraction after the introduction of polarization analysis reduces the high dependence on the scattering space angle and adds a new information dimension based on the polarization vector. At this time, the information of incident light and scattered light is transformed from a single light intensity dimension representation to a four-dimensional Stokes vector representation to realize a more detailed study of the physical properties of particles. It provides a guarantee for the identification of particle size, shape, structure, and more complex physical properties of suspended particles. Chen et al. designed an instrument based on single-angle polarization scattering measurement (Fig. 5), and the results showed that ball, ellipsoid, and fiber bundle samples had different mean and variance of polarization indices at 85° scattering angle, which proved the feasibility of the experimental device to identify particle morphology. Li et al. designed a device for measuring the polarization scattering of suspended particles (Fig. 6), realizing real-time high-throughput measurement of suspended particles in the air.

4) Theoretical calculation of the scattering process of suspended particles. To solve the propagation process of polarized light in group particles, solving the scattering characteristics of single particles is the basis of solving the radiative transfer equation of group particles. There are many simulation methods for the single particle scattering process (Table 1), including the separation of variables method (SVM), finite difference time domain method (FDTD), Mie theory, and discrete dipole analysis (DDA).

5) Optical information extraction of suspended particles. Suspended particles usually have a wide size distribution, complex composition and morphology, and a variety of complex microphysical characteristics. In the interaction between light and particles, the change in polarization state contains a wealth of information about the microphysical properties of particles. Therefore, some studies on the refinement of composite properties of suspended particles and quantitative extraction mostly use polarization scattering measurement signals. For example, a polarized optical particle counter determines the particle size by scattering signals, extracts morphological features from the polarized signals, and then qualitatively characterizes the type of particles. Liao et al. used the obtained polarization-measurement signals to retrieve the refractive index of the aerosol complex.

The data obtained from the measurement of suspended particles are often complex temporal pulse signals, so it is very important to develop suitable data analysis algorithms. At present, the analysis methods of suspended particle detection data mainly include multi-dimensional polarization spectrum (Fig. 8), neural network (Figs. 9-11), and attribute inversion algorithm.

Suspended particles are an important part of the earth's atmospheric environment, which affects the climate environment and various activities of human society. Although the source of pollutant suspended particles only accounts for about 10% of the total aerosol, its impact on people's health cannot be ignored. The double uncertainty in time and space greatly improves the difficulty in real-time monitoring, accurate identification, and reliable prediction of suspended particles. Therefore, it is very important to introduce new detection and analysis techniques. The scattering polarization measurement method in the optical detection method can not only detect the scattering behavior of particles but also expand the dimension of measurement information by relying on the polarization property, which provides more possibilities for particle detection and identification.

In this paper, advances in detection technology, calculation theory, and information extraction of suspended particles are reviewed. The two measurement methods of group particle and single particle are summarized respectively, especially the polarization scattering correlation technique. On the theoretical methods of suspended particle optical processes, several modeling methods of single particle scattering processes are introduced. Finally, the analysis and application of suspended particle detection data are summarized from three aspects: multi-polarization spectrum, neural network, and attribute inversion. These studies show the important application value of scattering polarization measurement in the field of aerosol measurement and also provide an important basis for the follow-up of researchers in more complex aerosol measurement solutions.