Images based on RGB pixel values were used to measure the extinction coefficient of aerosols suspended in an atmospheric state. The pixel values of the object-image depend on the target-object reflection ratio, reflection direction, object type, distances, illumination intensity, atmospheric particle extinction coefficient, and scattering angle between the sun and the optical axes of the camera, among others. Therefore, the imaged intensity cannot directly provide information on the aerosol concentration or aerosol extinction coefficient. This study proposes simple methods to solve this problem, which yield reasonable extinction coefficients at the three effective RGB wavelengths. Aerosol size information was analogized using the RGB Ångström exponent measured at the three wavelengths for clean, dusty, rainy, Asian dust storm, and foggy days. Additionally, long-term measurements over four months showed reasonable values compared with existing PM_2.5 measurements and the proposed method yields useful results.

Two important parameters of liquid clouds are the cloud effective size (CES) and liquid water content (LWC). To measure these parameters, we have used two multiple scattering depolarization effects: (1) the slope of the degree of linear polarization (SLDLP) at the cloud base, and (2) the saturated degree of linear polarization (SADLP) at infinite altitude. We used Monte Carlo simulation to validate this method, with the assumption that the water cloud droplet size follows a Gamma distribution. From our calculation, we find that although the SADLP varies with both extinction coefficient (or LWC) and the CES, the SLDLP varies only with the extinction coefficient. After extracting the extinction coefficient using the SLDLP, we can easily obtain the CES using the SADLP. As a result, we found that the CES and the LWC can be extracted from the experimental parameters of SLDLP and SADLP, which can be easily measured using a single wavelength depolarization LIDAR.

Rapid industrialization has intensified air pollution, particularly in areas where industrial and residential zones overlap. This study analyzed emissions from the Yeosu Industrial Complex, South Korea, a major source of volatile organic compounds (VOCs), methane (CH₄), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and particulate matter (PM). Advanced remote and in situ optical techniques—solar occultation flux (SOF), sky differential optical absorption spectroscopy (SkyDOAS), mobile extraction Fourier transform infrared spectrometry (MeFTIR), sniffer 4D, and LiDAR—were employed to assess spatial pollutant distribution across five zones. Zones A and B exhibited the highest emissions (8,622,468 kg/year and 21,826,416 kg/year), largely due to petrochemical and rubber manufacturing activities. Pollutants, particularly alkanes, NO₂, and SO₂, were highest during southeasterly winds, which transported emissions to nearby residential areas, increasing health risks. A comparison with the Clean Air Policy Support System (CAPSS) inventory highlighted underestimations of VOC emissions in national records. Discrepancies in PM₁₀ measurements by Sniffer 4D (2–6 µg/m³) and LiDAR (14–15 µg/m³) in zone A emphasized the importance of integrating measurement methods to improve emission accuracy. This study demonstrates the potential of combining mobile and remote sensing techniques to enhance emission inventories and provides critical insights for targeted air quality management in industrial-residential interfaces.

Methods and means of remote control of the ecological state of the atmosphere are constantly improving. Lidar sensing allows obtaining up-to-date information about natural and technogenic sources of atmospheric pollution. There is a wide range of problems in ecological control, where the deployment of an inexpensive mobile lidar network is required. For this purpose, it is suggested to use Q-switch and MOPA fiber lasers in lidars. Q-switch fiber lasers have a simpler design and are more practical to use. However, pulses from Q-switch lasers have long full-pulse durations. In the present work, a lidar signal inversion method (LSIM) is proposed for solving this problem. Verification and outdoor experimentation of the LSIM was carried out with the reference signal method (RSM). The advantage of the proposed RSM is the minimum number of controllable parameters necessary for LSIM verification and approbation. As a result, the accuracy of the obtained results increased. Thus, the possibility of application of the Q-switch fiber lasers for lidar sensing is shown both theoretically and experimentally.

Scattered light polarization serves as an indicator and a characteristic of various processes in the atmosphere. The polarization measurements of all scattering matrix elements provide an adequate description of the optical and morphological parameters and orientation of particles in clouds. In this article, we consider the problem of the calibration of matrix polarization lidar (MPL) parameters. Calibration by air is an effective alternative to the technique for correcting optical element parameters and among the calibration parameters of the MPL optical path are the relative transmission coefficient of a two-channel receiver, the angular positions of the transmission axes of the optical elements of the transmitter and receiver units, including the polarizers and wave plates, and the retardance of wave plates. For the first time, the method of calibration by air was partially implemented in the MPL to study Asian dust in the atmosphere. We considered the calibration problem more generally and this was due to the need to calibrate different MPL modifications from stationary to mobile ones. The calibration equations have been derived in terms of instrumental vectors, and the method of their solution by the generalized least squares method has been proposed. The method has been verified on a numerical MPL model and validated using MPL measurements in Daejeon, Republic of Korea.