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 Doppler lidar mounted on a rotary platform has been developed for measuring wind fields in the upper troposphere and stratosphere. The rotating platform was used to support a large system for the detection of wind velocities of sight (VOS) in four directions. The principle, structure, and parameters of the lidar system are introduced. The Fabry-Perot interferometer (FPI), the core component of the wind measurement system, was designed after comprehensively considering the measurement uncertainty and the influence of Mie scattering. Its dual-edge channel bandwidth is 1.05 GHz with 3.48 GHz spacing. In operation, the FPI channels are locked to the laser frequency with a stability of 14.8 MHz. Compared with the local radiosonde, it was found that the deviation in wind speed below 28 km was generally less than 10 m/s, and the deviation in wind direction below 19 km was less than 10 degrees. The 42-day profile comparison between lidar in Hefei and radiosondes in Anqing and Fuyang was analyzed. The statistical results show that the wind speed and wind direction deviations between lidar and radiosondes below 20 km were approximately 10 m/s and 20 degrees, respectively, which are comparable to the regional differences in the wind field. However, as altitudes exceed 20 km, the deviations increased rapidly with height. The experiments indicate that the Doppler lidar could measure wind fields from 7 km to 30 km, with better detection accuracy below 20 km.

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.

Atmospheric transmittance, turbulence, and wind play a crucial role in the field of laser atmospheric transmission. In response to the demand for comprehensive detection of atmospheric optical parameters, a LiDAR system for comprehensive measurement of atmospheric transmittance, turbulence, and wind (ACW-LiDAR) has been developed through integrated optical and mechanical design. The remote sensing measurement of atmospheric transmittance, turbulence, and wind simultaneously and along a common path has been realized by the ACW-LiDAR. By proposing a limb scanning algorithm, the problem of preference for atmospheric transmittance estimation has been overcome, and the problem of inconvenient turbulence measurement at near-surface has been effectively solved. It is also possible to obtain wind information on the laser transmission route. The experimental results based on the ACW-LiDAR system indicate that the detection distance of atmospheric transmittance is greater than 10 km @ 1064 nm. The detection distance of turbulence is greater than 10 km @ 532 nm. The detection distance of wind is greater than 4 km @ 1550 nm. The comparison between the ACW-LiDAR system and the ground meteorological automatic observation system shows that the variation trend in extinction coefficient, turbulence, and radial wind velocity is consistent, with a correlation better than 0.69, verifying the accuracy of the developed ACW-LiDAR system. The analysis of comprehensive scanning detection indicates that the three key atmospheric parameters mentioned above are interrelated and mutually influencing. So the measurement of the same time and common path of atmospheric transmittance, turbulence, and wind is of great significance. These can provide a theoretical and experimental basis for long-term observation and accumulation of atmospheric parameters, as well as the correction of atmospheric parameters.