This PDF file contains the front matter associated with SPIE Proceedings Volume 13504, including the Title Page, Copyright information, Table of Contents, and Conference Committee information.

This study examines the polarization retention of linearly polarized light during forward transmission through concentric spherical microparticles. By using silica-encapsulated water and oil-encapsulated water-encapsulated silica as examples, the study explores the effects of wavelength, particle size, refractive index variations, different distributions, and double/triple-layered spheres on polarization retention in forward transmission. The research identifies polarization-preserving channels at specific wavelengths. Polarization retention characteristics vary with particle size. For silica-encapsulated water spheres with radii of 1μm, 2μm, 5μm, 10μm, and 20μm, distinct intervals exhibit rapid declines in polarization retention. In contrast, silica-encapsulated water spheres with radii of 0.2μm and 0.5μm show no intervals of rapid polarization retention decline. Each silica-encapsulated water sphere exhibits a unique depolarization interval under varying refractive index conditions. As the forward transmission angle increases under different distributions, superior polarization retention characteristics shift from monodisperse to normal and log-normal distributions. For double-layered and triple-layered concentric spherical microparticles, both silicaencapsulated water and oil-encapsulated water-encapsulated silica exhibit distinct depolarization intervals.

Atmospheric aerosol affects electromagnetic radiation transmission through scattering and absorption, which has great influence on optical satellite remote sensing, environmental monitoring, climate forcing and aerosol-cloud interaction. In2021, based on the data collected in the Yellow Sea and the South China Sea near the coast, we developed the coast aerosol model (CAM) to predict the aerosols size distribution under coastal environments. This work makes a comprehensive model evaluation for the CAM with the atmospheric aerosol observation results at the South China Sea coastal station (Maoming) in November 2023. The comparison results show that the CAM can effectively describe the characteristics of aerosol (number concentration, particle size distribution and extinction coefficient) in this area. During the observation period, the average error of prediction results of aerosol concentration is around 20.6%, indicating that the CAM is promising in prediction coastal aerosol microphysical and optical properties.

Atmospheric lidar is one of the important tools for environmental monitoring. However, the conventional backscattering lidar has a blind detection zone, which limits the effective monitoring of aerosol concentrations near the ground. A lidar system based on the Scheimpflug imaging condition captures the echo signals and obtains the spatial and temporal evolution of aerosols in the underlying atmosphere by optical imaging principles and geometric calculations. The system uses a simple continuous diode laser and an industrial camera for signal transmission and reception, which is stable and cost-effective. In this paper, from the basic principle of Scheimpflug imaging lidar, the detection capability of Scheimpflug imaging lidar system for near-range aerosols under single-channel and dual-channel conditions is explored through numerical simulation; and a prototype Scheimpflug imaging lidar is developed for single-channel and dual-channel pollution source detection experiments. By comparing the results of single-channel and dual-channel aerosol detection experiments, the advantages and feasibility of dual-channel and multi-channel Scheimpflug imaging lidar systems for high-precision detection in short detection blind zones are verified.

Optical tweezers have been widely used in the study of the physical and chemical properties of individual aerosol particles. However, the traditional method of using optical tweezers can only measure one particle at a time, which limits the efficiency and throughput of the measurement. Although the method of using a spatial light modulator (SLM) to simultaneously generate multiple optical traps has been developed, which adds significant complexity to the overall optical setup including the need for precise alignment of the SLM, integration with the trapping laser, and the implementation of algorithms to generate the desired multi-trap patterns. This research proposes a method for the simultaneous measurement of multiple aerosol particles based on optical tweezers. The method uses multiple combinations of polarization beam splitters and half-wave plates to generate multiple optical traps, which can capture and manipulate multiple aerosol particles simultaneously. The proposed method has the advantages of improved trapping efficiency, faster temporal control and reduced aberrations, which provides a new tool for the study of multiple aerosol particles properties and behavior.

China's carbon reduction and emission reduction under the ‘double carbon’ target requires high-precision atmospheric CO₂ inversion data. High-precision atmospheric CO2 satellite observation is the basis for accurate positioning of emission sources. Aiming at the problem that the inversion algorithm is difficult to converge in the existing inversion methods, a statistical method integrating multi-source information is explored to obtain accurate prior profiles. It provides relatively accurate initial values for subsequent high-precision CO₂ inversion algorithms in order to improve the accuracy of CO₂ inversion. The statistical inversion method establishes a regression relationship model between satellite spectrum and atmospheric CO₂ concentration, and the inversion accuracy is affected by the representativeness of the sample and the regression analysis method. According to the difference of regional characteristics, the CO₂ profile samples are counted, and the sensitivity of environmental parameters is analyzed to construct a representative sample set. It is verified that the profile obtained by inversion is very close to the real profile, which verifies the feasibility of the method.

Anthropogenic emissions of greenhouse gases (GHGs), particularly carbon dioxide (CO2) and methane (CH4), constitute the primary drivers of global warming. Controlling anthropogenic emissions is crucial in mitigating global warming. Satellite remote sensing technology is considered the most viable and effective technological support for carbon monitoring. Global-scale, long-term carbon monitoring enhances understanding of human activities' impact on carbon cycles and climate change, while high spatiotemporal resolution carbon monitoring in key regions aims to provide data support in reducing anthropogenic emissions. Passive optical remote sensing is considered the primary technological means for satellite-based carbon monitoring. The satellite-borne passive remote sensing detection technologies successfully validated in orbit include Michelson interferometric spectroscopy, grating spectroscopy, Fabry-Pérot technology, and spatial heterodyne interferometric spectroscopy. This article reviews recent advancements in optical solutions for remote sensing payloads. It thoroughly analyzes the optical performance metrics of these payloads, comparing the strengths and weaknesses of different detection technologies through optical scheme analyses. Furthermore, specific metrics and development trends for passive payloads used in high spatiotemporal resolution remote sensing of key areas have been discussed. Finally, considering the technical requirements for China's next-generation carbon satellite. A novel static interferometric imaging technique is proposed, which combines spatial heterodyne interferometric spectral technology with azimuthal arc vector orthogonal direction heterogeneous optical field modulation. This innovative technology retains the advantages of traditional spatial heterodyne interferometry with high optical throughput and spectral resolution, while introducing new modulation techniques for enhanced spatial resolution. It is anticipated to advance global environmental protection and mitigating climate change.

Due to the complex sources of aerosols in coastal regions in China. The Optical Properties of Aerosols and Clouds(OPAC) isn’t been able to cover the microphysical and optical properties of coastal mixed aerosols. This research employs an external mixing method to mix the maritime clean aerosols with other aerosol types in different proportions by volume. Four mixed aerosol environments were defined, which are clean marine-average continent environment (SS-CV), clean marine-polluted continent environment (SS-CP), clean marine-urban environment (SS-UR), and clean marine-desert environment (SS-DESERT). Simulation experiments were conducted on the aerosol optical parameters(including extinction coefficient (EXT) and LiDAR ratio (SA)) of these four environments at 550 nm and 1000nmwavelengths, in order to analyze the variation of aerosol optical parameters with relative humidity (RH) and component number density in different mixed environments. The results indicate that EXT of aerosols in the four mixed environments increased with RH in both wavelengths, and EXT of aerosols increased linearly with the number density of components. The variation of SA is influenced by multiple factors such as wavelengths, relative humidity, and Multi factor effects of relative humidity and component number density. For the SS-CV, SS-CP, and SS-UR mixtures, water soluble and accumulation mode sea salts have a greater influence on SA and EXT, while for the SS-DESERT mixture, accumulation mode mineral and mode sea salts particles have a more substantial effect. This study enhances the understanding and prediction of optical property changes in complex aerosol environments near marine regions.

The characteristics of atmospheric optical turbulence are critical for the design and operation of modern groundbased optical telescopes. The effective implementation of Adaptive Optics (AO) systems in large telescopes, in particular, relies on a comprehensive understanding of the atmospheric turbulence parameters at the installation site. These key parameters include the atmospheric coherence time and the turbulence profile. The 2.5-m WideField and High-Resolution Telescope (WeHoT), planned for installation at Wuming Mountain Site in Daocheng, is designed for both day and night observations. A Ground Layer Adaptive Optics (GLAO) system will be an integral component of WeHoT. In the initial phase of measuring atmospheric turbulence parameters, the primary focus was on assessing the overall atmospheric turbulence intensity, with limited attention to detailed turbulence profile measurements. To address this gap, this study developed several devices capable of measuring atmospheric turbulence profiles and conducted field tests at Wuming Mountain Site. This paper details the hardware setup of these devices and presents preliminary test results.

Passive Fourier Transform Infrared (FT-IR) is a widely employed technique for the remote sensing of target vapors, including clouds, plumes and fugitive emissions. Prior to any qualitative or quantitative analysis of passive FT-IR data, it is essential to ensure that the instrument has been radiometrically calibrated. This process converts the instrument's detection signal spectrum into an equivalent radiation intensity spectrum. However, the measurement spectrum can be distorted due to inherent characteristics of the instrument or environmental variations during the measurement process. Furthermore, there has been a paucity of discourse and analysis concerning the verification of the measurement spectrum. In this paper, the instrument response matrix is employed for the purposes of spectral verification and radiometric calibration. The matrix is constituted of three columns: the spectral intensity maximum value and corresponding wavenumber, as well as the temperature. The initial and subsequent parameters are indicative of the spectra, and experimental data indicates that they are functions of the blackbody temperature. The instrument response matrix is a valuable tool for determining the range of the corresponding blackbody temperature and for assessing the adequacy of the measured intensity. The spectrum was measured at different temperatures within the range of 300K to 600K, and then the instrument response matrix was created through data processing. The following example illustrates the application of the instrument response matrix for the purposes of spectral validation and radiometric correction.

Coal is a key component of the global energy structure and plays a central role in various industrial and civil fields. The chemical and physical properties of coal determine the applicability of different types of coal. Therefore, precise coal classification and management are crucial for promoting resource efficiency and environmental sustainability. However, due to the high similarity in composition between different types of coal, traditional classification methods are challenging to apply. In light of this, this paper proposes a Laser-Induced Breakdown Spectroscopy (LIBS) method combined with Principal Component Analysis (PCA) and Radial Basis Function network (RBF) for the classification and identification of 12 types of coal samples. Firstly, the spectral data of the coal samples are collected after laser ablation, followed by preprocessing steps such as noise removal, background correction, and normalization. Then, PCA is used to reduce the dimensionality of the preprocessed spectral data, and RBF is employed to classify and train the reduced-dimensional data. The research results show that the PCA-RBF model can classify coal samples with an accuracy rate of 98.96%. The combination of LIBS with the PCA-RBF model achieves rapid and accurate classification of different varieties of coal samples, providing an accurate and efficient data processing method that helps to promote the optimal allocation of coal resources and the sustainable development of the economy and environment.

This paper reports on a non-modulated all-fiber LHR setup that utilizes a 1.316 μm narrow-linewidth DFB laser as the local oscillator. This device abandons the traditional method of using a chopper and a lock-in amplifier for modulation and demodulation. Instead, it employs multiple averaging techniques, reducing the complexity of the signal processing module in the LHR. This approach avoids the impact of low-pass filtering during demodulation on the instrument line shape function and measurement speed of the LHR, thereby enhancing spectral resolution and effectively improving the system's measurement speed. In May and June 2024, field measurements were conducted in the Changxing Island area of Dalian. The LHR signals of water vapor molecules in the 7597-7598 cm⁻¹ range were obtained with a spectral resolution of 0.003 cm⁻¹. The processed signals were then wavelength-calibrated and normalized, resulting in the relative transmittance spectrum of the entire atmospheric column for water vapor molecules. An optimal estimation method was used to establish a LHR retrieval algorithm. The retrieval ultimately yielded vertical profiles and column concentrations of water vapor molecules throughout the entire atmosphere. The research findings indicate that the non-modulated all-fiber approach can simplify the structure of the LHR, improve device performance, and has significant implications for the optimization and integration of LHR.