When the spaceborne ultraviolet hyperspectral atmospheric composition spectrometer is in orbit, it obtains radiation and spectral information through the light path of the earth light observation as well as the light path of the sunlight observation, so it is necessary to be calibrated in the laboratory before launching. As the irradiance calibration coefficient will be used for obtaining the solar reference spectrum during the on-orbit observation, the calibration accuracy directly affects the instrument′s on-orbit detection and inversion accuracy, and determines the reliability of remote sensing information. The direct diverging light is used in the irradiance calibration method, and a two-dimensional calibration platform is build to carry out a series of tests at different angles and distances on the calibration light path. By using the least squares method to linearly fit the experimental values at three distances, the irradiance calibration coefficient is obtained, and then the influence of the angle and the other factors is corrected. The calibration results show that the combined uncertainty is 3.42%, which meets the requirements of radiation calibration, indicating the feasibility ofthe method.

The environmental trace gases monitoring instrument (EMI) launched on the Gaofen-5 satellite on May 9, 2018 is a high-resolution imaging spectrometer in the UV-visible band. In order to investigate its on-orbit spectral performance, the wavelength peak searching method was first adopted, namely, the solar Fraunhofer line was used as the characteristic peak to quickly obtain the spectral range of the load, then the spectral curve value of the load space dimension was obtained by using the spectrum-matchingmethod, and finally the spectral fitting method was used to obtain the change of spectral resolution. By comparing with the standard Fraunhofer, the peak searching method can find the characteristic peak and obtain the standard wavelength of the peak andthe corresponding pixel, and then the corresponding relationship between pixel and wavelength can be obtained by second order polynomial fitting. The Pearson correlation coefficient method is used as the criterion for spectral-matching method, that is, the maximum correlation coefficient between two spectral is used as the condition for the optimal matching result, and then the offset value between the measured spectral and the standard spectral is obtained. The calibration result satisfies the requirement that the calibration precision is higher than 0.05nm. The spectral fitting method can analyze the change of spectral resolution by solving and fitting the measured spectrum with the high-resolution solar reference spectrum. The analysis results of the all-day 15-track data on January 7, 2019 show that the change of spectral resolution is consistent within a day, and the single row standard deviation is less than 0.01. Therefore, it is of great significance to analyze the performance decay of the instrument in the case of long-term operation or interference.

Using GF-5/EMI tropospheric NO2 columns product developed by University of Science and Technology of China, combined with the emission inventory, surface precipitation and temperature data, the spatio-temporal variations of tropospheric NO2 thatis in the North China Plain (NCP) from January to August 2019 are studied. The results show that NO2 pollution is concentrated in Henan, Hebei and Tianjin, especially in Jiaozuo, Henan (1.670×1016 molecules·cm－2) and Shijiazhuang, Hebei (1.426×1016 molecules·cm－2). The weekly changes generally show “reverse-weekend effect”, but the trend in some agricultural cities is opposite. The monthly change decreases continuously from January (1.635×1016 molecules·cm－2) to the lowest level in August (1.839×1015 molecules·cm－2). The correlation coefficient with monthly precipitation and temperature are －0.8622 (p = 0.0059 < 0.01) and －0.9162 (p = 0.0014 < 0.01), respectively, and with anthropogenic monthly emissions is 0.9778 (p = 2.69×10－5< 0.01). The industrial cities in NCP, represented by Tianjin, are seriously polluted, which need to be paid more attention to on the prevention and control of air pollution in the future.

As one of the most dynamic urban economic circles in China, the Pearl River Delta has witnessed rapid economic development in recent years. At the same time, the prevention and control of local air pollution has attracted wide attention. Among the many means of air pollution monitoring, satellite remote sensing method has the advantages of wide observation range, ability for observation of many kinds of pollutants, sustainable observation, low cost and so on. EMI (Environmental trace gases monitoring instrument) is the first Chinese spaceborne atmosphere monitoring spectrometer, which loaded on GF-5 satellite launched on May 9, 2018. It has been widely used in monitoring spatial distribution and temporal change of atmospheric pollutants regional and global areas, and is of great significance for the control of air pollution as well as the research and development of Chinese satellite hyper-spectral remote sensing inversion algorithm. Based on EMI remote sensing data and satellite remote sensing products from University of Science and Technology of China, the spatial and temporal variation characteristics of tropospheric NO2 column concentration over Pearl River Delta region from January to August 2019 are analyzed in this work. The results show that: (1) From January to August 2019, the concentration of tropospheric NO2 column over Pearl River Delta region presents a concave pattern as a whole, showing a decreasing trend from January to June, and an increasing trend from July to August. (2) Themain NO2 pollution sources over Pearl River Delta are concentrated in the central part of FoShan city and the coastal areas along the Pearl River estuary. From January to August, the center of NO2 source gradually moved from central Foshan to Shenzhen and the Hong Kong. (3) There is a positive correlation between the concentration distribution of tropospheric NO2 column over Pearl River Delta region and the economic status, industrial structure, the number of permanent residents and the number of motor vehicles. Among them, the city’s overall economic status and the proportion of the secondary industry have a great influence on the concentration of tropospheric NO2 column. Therefore, attention should be paid to the development of local economy and the optimization of industrial structure in the prevention and control of air pollution.

A large-scale forest fire occurred in Australia in 2019-2020, which burned more than 8 million hectares of eucalyptus forest in six months. In this work, the variation of NO2 during the Australian fire was studied by the environmental trace gases monitoring instrument (EMI). It was found that in November 2019, the NO2 concentration and distribution in southeastern Australia showed a significant increase compared with the same period in previous years. In addition, aiming at the fires in Australia′s two major national parks, the correlation between the frequency distribution of NO2 relative concentration and the degree as well as frequency of fires was studied. It was found that the frequency distribution of NO2 relative concentration in the two places also increased significantly in November 2019, indicating that forest fire is the main reason for the increase of NO2 concentration in these regions. At the same time, this work also proves the feasibility of EMI in monitoring major pollution events.

The slant column density (SCD) of ozone detected by Chinese first space-borne environmental trace gases monitoring instrument (EMI) was retrieved by using differential optical absorption spectroscopy (DOAS) method. Then the lookup table of atmospheric quality factor (AMF) was built based on SCIATRAN radiative transfer model, and the vertical column density of ozone (VCD, namely total ozone column) was finally obtained. A comparative analysis of the total ozone column from EMI, OMI and TROPOMI in the Antarctica on November 2, 2018 shows that EMI, OMI and TROPOMI all observed the high ozone values area in mid and high latitude of Antarctica (30° S～70° S) and the low ozone values area in inland Antarctica (75° S～90c S), and the correlation coefficients (R2) between EMI and OMI, TROPOMI are 0.977 and 0.958 respectively. Furthermore, the total ozone columns of EMI was compared with that of ground-based ZSL-DOAS at Great Wall station (62.22 S, 58.96 W) from October 25 to November 25, 2018, and the correlation coefficient (R2) is 0.926.

As cloud parameters are important input parameters for retrieval of trace gases, it is of great significance for their accurate acquisition. Based on environmental trace gas monitoring instrument (EMI) observation on March 2019, the effective cloud fraction is retrieved by using the absorption feature of O4 at 477 nm. To verify the accuracy of EMI cloud algorithm, the retrieval cloud fraction of EMI is compared with TROPOMI cloud products, and the correlation analysis of EMI and TROPOMI cloud fraction on March 2, 6, 9 and 10, 2019 is carried out, and the cloud fraction correlation coefficient (R) is 0.752, 0.712, 0.764, and 0.762 respectively, indicating that the two results have good correlation. Furthermore, the cloud fractions of three different regions of desert, ocean, and land are selected to study the distribution characteristics of cloud fraction in different underlying surface. It is found that the cloud fractions of EMI and TROPOMI in the three regions are consistent, and the cloud fraction over the ocean is relatively low, the cloud fraction over the land is relatively high, and the cloud fraction over the desert changes frequently.

Carbon dioxide (CO2) is one of the most important greenhouse gases in the atmosphere. Accurate understanding its content and variation in the atmosphere can provide support for climate change prediction and environmental decision-making. In order to meet the requirement of climate research, the retrieval precision of column-averaged dry-air mole fraction of CO2 (XCO2) observed by satellite should be better than 1%. The greenhouse gases monitoring instrument (GMI) onboard GF-5 used for atmospheric CO2 and CH4 observation adopts a novel spatial heterodyne spectroscopy technology, which can supply hyperspectral resolution. Considering that satellite observations with hyperspectral resolution are easily effected by atmosphere, groundsurface and instrument, a retrieval method special for GMI data is designed in this work. In the method, through the analysis of spectrum information, the information spectrum for atmospheric CO2 retrieval and the reference spectrum for removal of slow frequency interference are constructed firstly, then the measurement vector and simulation vector are rebuilt based on the constructed spectra, and at last atmospheric XCO2 is retrieved by using the optimization estimation method. As the method has the ability of slow frequency interference removal, it makes retrieval of GMI spectrum possible. By using the proposed retrieval method, the GMI observations between August 2018 and March 2019 are retrieved, and the ground-based carbon dioxide measurements from twelve stations of Total Carbon Column Observing Network are used to validate the retrieval results. The validation results show that the algorithm is able to retrieve the GMI observations stably, and the retrieval precision of atmospheric CO2 is high as 0.67%, which is better than the basic requirement of 1%.

Atmospheric aerosol is an important influence factor of climate change and remote sensing quantification, so it is of great significance to study aerosol optical properties. Based on the measurements of directional polarimetric camera (DPC) onboard GF-5 satellite over China, the retrieval of aerosol optical depth (AOD) is carried out. Based on the vector radiative transfer model 6sv, a look-up table of aerosol optical properties is constructed. Then the contribution of land surface is calculated by Ross Li surface BRDF model and semi empirical NB model. Finally, AOD is retrieved by using multi angle information of intensity and polarization and look-up table method. It is found that the retrieval results of DPC aerosol optical depth are in good agreement with the observation results of AERONET ground stations in China, the linear fitting degree is good and the correlation coefficient is greater than 0.8, which verifies the reliability of the algorithm.And it is believed that the development of the algorithm provides technical support for DPC to effectively monitor the spatial and temporal distribution of aerosols.

Clouds are important in ocean remote sensing detection, and cloud detection accuracy is significant to the inversion of cloud microphysical characteristics over ocean and the observation of ocean waterbody. By using the on-orbit imaging data of the atmospheric aerosol multi-angle polarization detector (directional polarimetric camera, DPC) onboard GF-5, a detection method for cloud cover over the ocean based on multi-angle polarization radiation information is proposed. Firstly, the sunlight angle discrimination method is used to distinguish the ocean glint area and the non-glint area. Then the multi-angle polarization information is used to detect cloud in the ocean glint area, and on the other hand,the methods of reflectance threshold, the visible-near infrared reflectance ratio and the polarization information inspection are used to detect cloud in the non-glint aeras. Taking the Indian Ocean and the Atlantic Ocean as experiment aeras, cloud detection over the ocean was carried out based on DPC data, then the results were compared with MODIS (Moderate-Resolution Imaging Spectroradiometer) cloud mask data, and the consistency reaches 91.39% and 94.73% respectively. In addition, the data of FrenchPOLDER3 (polarization and directionality of the earth′s reflectances) is also used to verify the effectiveness of the proposed algorithm in this work, and the consistency between the cloud detection results and the official POLDER3 cloud detection productsreaches 90.40%. It is believed that the multi-angle polarization radiation threshold cloud detection algorithm proposed in this work can provide effective cloud detection data for satellite observation of cloud characteristics over the ocean and ocean water observation.

Cloud top pressure can be used to estimate cloud height, which is important for meteorological observation and cloud characteristics research. Based on 763 nm and 765 nm bands (in oxygen A-band) of the Directional Polarimetric Camera (DPC) onboard GF-5 satellite, a cloud top pressure retrieval method is studied. First, the calculation formula of atmospheric pressure is obtained by using radiative transfer simulation and polynomial fitting, and the fitting error of the formula is analyzed and corrected. Then, the influence of aerosol, atmosphere profile and other factors on the cloud top retrieval is analyzed, and the stability test and principle verification of the retrieval method are further carried out by using clear-sky surface. The stability test results show that the oxygen A-band retrieval method is stable and can be applied to different weather conditions and view angles, and the principle verification results show that the DPC retrieved pressure is in good correlation with the DEM estimated pressure, with the average deviation of surface pressure of 47.6 hPa. Finally, the retrieved DPC cloud top pressure is compared with the MODIS cloud top pressure product (MYD06), and it is shown that cloud top pressure observation results of the two satellitesare in good agreement.

GF-4 is the first high spatial-resolution geostationary satellite of China. Surface reflectance products are of great value for evaluating ecological environment and reducing disasters. GF-4 atmospheric correction algorithm estimates surface reflectance, iteratively calculates the minimum residual error of observed and calculated apprent reflectance to get aerosol optical depth, and constructs a 6SV look-up table to obtain the surface reflectance results. Based on the accuracy verification of GF-4 surfacereflectance products, considering the high-efficiency requirements of data analysis and product production, the computationally complex steps are designed based on the graphics processing unit (GPU) to optimize the performance of threads and registers. The results show that the GPU-accelerated atmospheric correction algorithm has great advantages in performance and energy consumption. Compared with sequential execution, a scene of GF-4 PMS image data with 10240×10240 pixels has an overall speedup of 57.3, while the overall energy consumption is only 15.5% of sequential execution.