The Greenhouse gases Monitoring Instrument on GaoFen-5 satellite-II (GMI-II) uses spatial heterodyne spectroscopy (SHS) for quantitative monitoring of atmospheric greenhouse gases (GHG). Unlike the traditional SHS, the interferometer component of the GMI-II was designed with zero optical path difference offset, effectively improving spectral resolution while maintaining the same detector specifications. The secondary imaging system with non-isometric scaling of spatial and spectral dimensions was designed to decrease the integration time of a frame image or improve the spectral signal-to-noise ratio (SNR) under the same integration time. This paper introduces the design, manufacture, adjustment methods, and test results of the main performance indexes of the GMI-II that indicate that the spectral resolution of the O₂ A-band detection channel is better than 0.6 cm⁻¹ and other channels are better than 0.27 cm⁻¹. Under the typical radiance of other carbon monitors’ on-orbit statistics, the spectral SNR of the GMI-II is more than 300. These test results demonstrate that the GMI-II can be well adapted to quantitative remote sensing monitoring of atmospheric GHG.

The wafer eccentricity deviation caused by misalignment between the center of the wafer and rotary table will lead to edge image distortion and quality degradation of the defect signals during automated inspection. However, wafer end jump and edge topography change will bring great challenges to the accurate measurement of micrometer deviations. A new wafer eccentricity deviation measurement method based on line-scanning chromatic confocal sensors (LSCCSs) is proposed. Firstly, the LSCCS with Z-axis submicron resolution used in the experiment acquires the 3D profile height of the wafer edge as the turntable rotates, and the edge distance is calculated at each rotation angle. Secondly, a robust Fourier-LAR fitting method is used to fit edge distance serial to reduce sensitivity to outliers. Finally, the wafer eccentricity deviation that is equal to the wafer center coordinate can be calculated using the wafer eccentricity deviation model. In the simulated experiment, the results show that the eccentricity deviation measurement accuracy was insensitivity to noise and reached the micron level. Additionally, the measurement uncertainty of eccentricity deviation coordinate $\left(X_w,Y_w\right)$ was (0.53 µm, 1.4 µm) in the actual data of the 12-inch wafers.

The Greenhouse Gas Monitoring Instrument (GMI), carried by Gaofen 5 (GF5-01), and the Hyperspectral Observation Satellite (GF5-02) were successfully launched on 9 May 2018, and September 7, 2021, respectively, and are the only passive greenhouse gas payloads in China that can regularly obtain effective detection data in-orbit at this stage. Before launch, the research team carried out much laboratory calibration work and designed an on-board calibration system based on solar radiation sources which guarantees the quantitative accuracy of the payload data to the greatest extent. In order to more effectively meet the high frequency calibration requirements over the whole life cycle of the payload, the research team carried out research using the on-track site calibration method based on digital calibration field network technology, and the obtained calibration coefficient effectively complements the laboratory and on-board calibration results. The working principle of the GMI is quite different from that of a traditional imaging payload. Spatial heterodyne spectroscopy (SHS) is used to detect the absorption spectrum of greenhouse gases, has a large field of view and is non-imaging and hyperspectral. The existing fixed-site alternative calibration methods cannot fully meet the requirements of calibration tasks. In this paper, we propose a set of global digital calibration radiation field screening criteria that can meet the characteristics of the GMI and design a method to calculate the site calibration coefficients of non-absorption spectral channels according to the characteristics of hyperspectral data. Based on the historical observation data of the GMI, the initial calibration calculation of the payload launch was carried out, and the calibration results of four spectral channels of the GMI were obtained: The calibration coefficient range of the O₂ channel is 1.05–1.15, the mean value is 1.10 and the standard deviation is 2.72%; the calibration coefficient of the CO₂-1 channel is 1.05–1.13, the mean value is 1.09 and the standard deviation is 2.64%; the calibration coefficient of the CH₄ channel is 1.08–1.10, the mean value is 1.11 and the standard deviation is 2.73%; the calibration coefficient of the CO₂-2 channel is 1.09–1.14, the mean value is 1.12 and the standard deviation is 2.93%. The above results show that the radiation performance of each channel of the GMI shows no significant attenuation during this period, that the site calibration coefficient has no significant fluctuation and that the in-orbit operation state is stable.

Detecting and classifying defects on unpatterned wafers is a key part of wafer front-end inspection. Defect inspection schemes vary depending on the type and location of the defects. In this paper, the structure of the prototype is designed to meet the requirements of wafer surface and edge defect inspection. This prototype has four inspection channels: scattering, reflection, phase, and contour, with two working conditions: surface and edge inspection. The key structure of the prototype was simulated using Ansys. The simulation results show that the maximum deformation of the optical detection subsystem is 19.5 μm and the fundamental frequency of the prototype is 96.9 Hz; thus, these results meet the requirements of optical performance stability and structural design. The experimental results show that the prototype meets the requirements of the inspection sensitivity better than 200 nm equivalent PSL spherical defects.

Satellite remote sensing is currently the best monitoring means to obtain global carbon source and sink data. The United States, Japan, China and other countries are vigorously developing spaceborne detection technology. However, the important factors that restrict the application of greenhouse gas satellite remote sensing technology include the limited accuracy of data products. How to improve the retrieval level of greenhouse gas payloads is a problem that needs to be solved urgently. One effective way to improve data quality is to carry out satellite ground synchronous authenticity verification and system error correction. This paper mainly aims at the shortcomings of the existing TCCON and the portable verification equipment EM27/SUN, and develops a High-Resolution Fourier Transform Spectrometer (HRFTS) based on dynamic collimation technology. Through the gas absorption method and the band scanning method of the hyperspectral monochromatic light source, the instrument’s absorption spectrum measurement capability and the Instrument Line Shape (ILS) are demonstrated. The instrument’s spectral resolution is consistent with the on-orbit greenhouse gas satellite load, reaching 0.26 cm⁻¹. For the interference data obtained by the spectrometer, spectral restoration processing, data quality control and inversion algorithm optimization were carried out to solve the problems of baseline correction, spectral fine registration, and environmental parameter profile reconstruction, and cross comparison experiments with EM27/SUN were carried out simultaneously. Finally, for the gases monitoring instrument (GMI) of the GF5-02 satellite launched on 7 September 2021, the first satellite ground synchronization verification experiment with high space-time matching was carried out. The results showed that the CO₂ column concentration deviation of the satellite ground synchronization inversion was about 1.5 ppm, and the CH₄ column concentration deviation was about 11.3 ppb, which verified the on-orbit detection accuracy of the GMI, and laid a foundation for the subsequent satellite inversion algorithm optimization and systematic error correction.

Coal-fired power plants, as major anthropogenic CO₂ emission sources, constitute one of the largest contributors to global greenhouse gas emissions. Accurately calculating the dispersion process of CO₂ emissions from these point sources is crucial, as it will aid in quantifying CO₂ emissions using remote sensing measurements. Employing the Lagrangian Particle Dispersion Theory Model (LPDTM), our study involves modeling CO₂ diffusion from point sources. Firstly, we incorporated high-resolution DEM (Digital Elevation Model) and artificial building elements obtained through the Adaptive Deep Learning Location Matching Method, which is involved in CO₂ simulation. The accuracy of the results was verified using meteorological stations and aircraft measurements. Additionally, we quantitatively analyzed the influence of terrain and artificial building characteristics on high spatial resolution atmospheric CO₂ diffusion simulations, revealing the significance of surface characteristics in dispersion modeling. To validate the accuracy of the LPDTM in high-resolution CO₂ diffusion simulation, a comparative experiment was conducted at a power plant in Yangzhou, Jiangsu Province, China. The simulated result was compared with observation from aerial flights, yielding the R² (Correlation Coefficient) of 0.76, the RMSE (Root Mean Square Error) of 0.267 ppm, and the MAE (Mean Absolute Error) of 0.2315 ppm for the comparison of 73 pixels where the plume intersected with flight trajectories. The findings demonstrate a high level of consistency between the modeled CO₂ point source plume morphology and concentration quantification and the actual observed outcomes. This study carried out a quantitative assessment of the influence of surface features on high-resolution atmospheric CO₂ point source diffusion simulations, resulting in an enhanced accuracy of the simulated CO₂ concentration field. It offers essential technological and theoretical foundations for the accurate quantification of anthropogenic CO₂ emissions using top-down approaches.