Dust storms pose a serious threat to air quality and public health through large‐scale, long‐distance transport. In early April 2018, two severe dust storm events occurred in the Taklimakan and Gobi Deserts in northwestern China. The advected air‐masses containing dust traveled eastward over long distances reaching the western Yangtze River Delta region (WYRDR) with local PM₁₀ peak concentrations of 190 and 410 μg/m³ on April 6 and April 11, 2018, respectively. Satellite remote sensing and ground‐based lidar observations showed that the first dust event was transported to WYRDR at an altitude of <5 km, while the second transport height was at an altitude of <3 km. The first one was accompanied with the dry‐cold air mass in the northwest moving eastward and southward. By comparison, in the second event, the dust aerosols were mixed with anthropogenic aerosols from southwestern China. Meanwhile, as southerly warm‐humid air flows prevailed at near‐surface layer over the WYRDR in the second event, the associated higher relative humidity potentially induced hygroscopic growth of polluted dust aerosols, resulting in explosive growth of PM₁₀. In addition, the average depolarization ratio of aerosols over WYRDR on April 6 was 0.3, while on April 11 it was 0.2, indicating that the previous pollution event featured more obvious nonspherical characteristics of aerosols. Our findings provide scientific evidence that transboundary dust events and resultant local PM₁₀ pollution are closely related to various transport trajectories of dust aerosols as well as the local vertical wind profiles and surface humidity conditions.

A metal–insulator–metal (MIM) waveguide consisting of a circular split-ring resonance cavity (CSRRC) and a double symmetric rectangular stub waveguide (DSRSW) is designed, which can excite quadruple Fano resonances. The finite element method (FEM) is used to investigate influences of geometric parameters on the transmission characteristics of the structure. The results show that Fano resonances are excited by the interference between the DSRSW and the CSRRC. Among them, the resonance wavelengths of the Fano resonances are tuned by the narrow-band discrete state excited by the CSRRC, and the resonance line transmittance and profiles are tuned by the wide-band continuous state excited by the DSRSW. The sensitivity (S) can be up to 1328.8 nm/RIU, and the figure of merit (FOM) can be up to 4.80 × 10⁴. Based on these advantages, the structure has potential applications in sensing in the sub-wavelength range.

The mechanism of aerosol pollution transport remains highly elusive owing to the myriad of influential factors. In this study, ground station data, satellite data, ground-based LiDAR remote sensing data, sounding data, ERA5 reanalysis and a backward trajectory model were combined to investigate the formation process and optical properties of winter aerosol pollution in Beijing and surrounding areas. The analysis of ground station data shows that compared to 2019 and 2021, the pandemic lockdown policy resulted in a decrease in the total number of pollution days and a decrease in the average concentration of particulate matter in the Beijing area in 2020. The terrain characteristics of the Beijing-Tianjin-Hebei (BTH) made it prone to northeast and southwest winds. The highest incidence of aerosol pollution in Beijing occurs in February and March during the spring and winter seasons. Analysis of a typical heavy aerosol pollution process in the Beijing area from 28 February to 5 March 2019 shows that dust and fine particulate matter contributed to the primary pollution; surface air temperature inversion and an average wind speed of less than 3 m/s were conducive to the continuous accumulation of pollutants, which was accompanied by the oxidation reaction of NO₂ and O₃, forming photochemical pollution. The heavy aerosol pollution was transmitted and diffused towards the southeast, gradually eliminating the pollution. Our results provide relevant research support for the prevention and control of aerosol pollution.

LiDAR and CALIPSO satellites are effective tools for detecting air pollution, and by employing PM_2.5 observation data, ground-based LiDAR measurements, CALIPSO satellite data, meteorological data, and back-trajectory analysis, we analyzed the process of pollution (moderate pollution, heavy pollution, excellent weather, and dust transmission weather) in Hefei, China from 24 to 27 January 2019 and analyzed the meteorological conditions and pollutants causing heavy pollution. Observation data from the ground station showed that the concentrations of PM₁₀ and PM_2.5 increased significantly on 25 January; the maximum value of PM₁₀ was 175 µg/m³, and the maximum value of PM_2.5 was 170 µg/m³. In this study, aerosol transboundary transport was observed using a combination of ground-based LiDAR and CALIPSO satellite observations. This method showed that aerosols were distributed at a height of 3–4 km over Hefei at 12:00 on 26 January, and it was found that the aerosols came from the desert region in northwest China. Moreover, we determined its transport pathway based on the backward trajectory, and the transportation of pollutants from the surrounding important industrial cities in central and eastern China led to severe pollution after aggregating and mixing with local aerosols in Hefei in the winter. Therefore, the method proposed in this paper can effectively monitor the optical properties and transportation process of aerosols, help to explore the causes of pollution under complex conditions, and improve environmental quality.

A method to calibrate the overlap factor of Lidar is proposed, named unmanned aerial vehicle correction (UAVC), which uses unmanned aerial vehicles (UAVs) to detect the vertical distribution of particle concentrations. The conversion relationship between the particulate matter concentration and the aerosol extinction coefficient is inverted by the high-altitude coincidence of the vertical detection profiles of the UAV and Lidar. Using this conversion relationship, the Lidar signal without the influence of the overlap factor can be inverted. Then, the overlap factor profile is obtained by comparing the signal with the original Lidar signal. A 355 nm Raman-Mie Lidar and UAV were used to measure overlap factors under different weather conditions. After comparison with the Raman method, it is found that the overlap factors calculated by the two methods are in good agreement. The changing trend of the extinction coefficient at each height is relatively consistent, after comparing the inversion result of the corrected Lidar signal with the ground data. The results show that after the continuously measured Lidar signal is corrected by the overlap factor measured by this method, low-altitude aerosol information can be effectively obtained.