Raindrop spectrum is a critical parameter for describing the microphysical characteristics of precipitation, so its accurate measurement plays a pivotal role in enhancing radar-based quantitative precipitation estimation, investigating microphysical properties of precipitation, and understanding the evolution process of precipitation. To achieve synchronous measurement of raindrop size and terminal velocity, we propose an optical raindrop measurement method based on machine vision principles, design a system with a dual telecentric lens configuration, a telecentric light source, and a linear array camera as the core, and constuct a prototype of an optical raindrop spectrometer in this paper. The data processing and analysis system of the spectrometer, is based on the Microsoft Foundation Classes (MFC) framework, and a real-time automated raindrop measurement software is developed utilizing the camera software development kit (SDK) in conjunction with Halcon software. The Canny algorithm is employed for sub-pixel edge detection of the acquired images, interpolation algorithms are applied to restore raindrop contours, and finally based on the restored raindrop images, the size and terminal velocity of raindrops are computed, thus achieving automated measurement of raindrops. Calibration tests are conducted using steel spheres and water droplets, with calibration of the instrument's measurement range being performed using a standard gauge block. The calibration results show that the raindrop spectrometer has a measurement error of less than 21 μm and a velocity inversion error below 4.5% for steel sphere diameters between 0.6 and 5.0 mm, and the standard deviation for droplet measurements is 26 μm, indicating that the instrument can concurrently measure particle size and terminal velocity, and has good accuracy and consistency in measuring moving particles.

NO2 slant column density is retrieved using eight discrete wavelengths (DW) combined with differential optical absorption spectroscopy (DOAS) technique, and the difference between DW-DOAS and the traditional DOAS technique using continuous wavelengths is compared and discussed. The feasibility of DW-DOAS is validated using the ground-based data and the satellite-based data from environmental trace gases monitoring instrument (EMI) in the study. The results show that compared with the traditional DOAS, the average errors of the two data retrieved using DW-DOAS are both less than 7%, and the correlations are above 0.9, proving that the DW-DOAS retrieve method has certain application value in retrieving trace gas column density. In addition, it is also shown that the DW-DOAS algorithm can quickly and efficiently retrieve the NO2 slant column density only using a small amount of spectral information. This work not only provides a basis for further research on subsequent algorithms, but also indicates that based on DW-DOAS algorithm, simpler and more efficient instruments can be designed for monitoring NO2 with high spatial and temporal resolution.

Recent studies have shown that the photolysis of particulate nitrate may be one of the important sources of daytime atmospheric nitrous acid (HONO). However, the existing laboratory studies have reported a wide range of measured photolysis frequency of nitrate, spanning 1 to 2 orders of magnitude, which significantly affects the accurate assessment of the contribution of nitrate photolysis to daytime HONO formation. A common practice to determine the photolysis rates of nitrates is to use a flow tube reactor, where artificial light-source are commonly used to simulate solar radiation, so how to accurately obtain the radiation intensity of light sources is a critical step for this kind of experiments and may induce a significant uncertainty in measuring photolysis rates of nitrates. In this study, nitrogen dioxide (NO2) actinometry was used to determine the radiation intensity inside a flow tube. The principle is that NO2 will be photolyzed into NO and swiftly form ozone (O3) at the present of oxygen (O2). At the same time, O3 reacts with NO rapidly to form NO2. Eventually, a dynamic equilibrium will be reached. Therefore, the actinic flux and photolysis rates of NO2J(NO2) can be deduced from the measured concentrations of NOx and O3, and then the photolysis frequency of nitrate J(HNO3) can be obtained by using the empirical formula. Different from the traditional nitrate solution actinometry, which uses nitrate actinometry to measure the absorbed radiation, the method proposed in this work avoids the bias of light absorption caused by water since no aqueous solution is present. Meanwhile, the NO2 actinometry does not depend on the physical configuration of the flow tube in this method and thus can provide more accurate measurement results. When a xenon light source (500 W) was set directly above the flow tube (i.e., zenith angle θ = 0°) and the gas passage time was 61.7 s under 1 standard atmospheric pressure and at 25 ℃, the J(NO2) measured by the NO2 photolysis method was 6.78 × 10-3 s-1, and J(HNO3) = 3.40 × 10-7 s-1 was finally obtained by using the empirical formula of previous studies.

With the continuous advancement of atmospheric environmental governance, particulate matter pollution has significantly decreased, but at the same time, ozone pollution has become increasingly severe. Therefore, constructing a long-term ground-level ozone dataset for China is essential for understanding the distribution and transmission of ground-level ozone and promoting the coordinated control of fine particulate matter and ozone. In this study, by combining the advantages of two machine learning algorithms, extreme random tree and extreme gradient boosting, we use ozone monitoring data, remote sensing products, and atmospheric reanalysis data to construct a daily maximum eight-hour average ozone (MDA8 O3) concentration estimation model for China's surface. The model accuracy is validated from sample, space, and time perspectives, and its spatiotemporal applicability is verified at annual, quarterly, historical, and regional scales. And at last, a China-wide ozone data product covering the period of 2001 to 2020 is derived. The results show that: (1) the ozone estimation model, which combines the advantages of the two algorithms, exhibits excellent accuracy, with R2 ranging from 0.89 to 0.95 and root mean square error (RMSE) ranging from 10.73 to 15.56 μg/m3; (2) The multiple spatiotemporal verifications indicate that the model constructed in this study can be applied to large-scale, long-term ozone estimation work in the China region; (3) The ozone data product constructed in this study can well reflect the spatiotemporal differentiation of ground-level ozone at the monthly and annual scales, and display the spatiotemporal changes of ozone concentration intuitively.

In March 2021, there were three large-scale sand-dust pollutions in northern China. In order to accurately understand the transmission process of these three sand-dust pollutions, the vertical detection results of the Mie scattering aerosol lidars distributed in the Beijing-Tianjin-Hebei region in this period were analyzed and studied. The vertical detection results show that the transmission sequences of the three sand-dust pollutions processes in March 2021 were almost the same: Zhangjiakou, Beijing, Langfang (Baoding), Tianjin, Qinhuangdao, sequentially. During this period, the pollution weather in the Beijing-Tianjin-Hebei region was affected by northwest and north winds, resulting in sand-dust pollutions in this region. Among them, Zhangjiakou and Beijing in this area were seriously affected by the three pollution events. During the two more serious sand-dust pollutions from March 14 to 18 and from March 27 to 31, pollution was transmitted from northwest to southeast in Beijing, Langfang and Tianjin, and the concentration of pollutants in the three cities decreased in turn. Overall, during the three sand-dust pollutions in March 2021, the impact on various cities gradually weakened as they transported from northwest to southeast. Based on the air mass movement trajectory and the retrieve mapping, a scientific analysis was made on the pollution processes of the three sand-dust events in the Beijing-Tianjin-Hebei region, which provides a case and reference for the prevention and control of sand-dust pollution in the future.

Studying the spatial distributions and complex optical properties of marine aerosol particles is of great significance for understanding atmospheric environment over ocean and global climate change issues. In this study, the observation data of directional polarimetric camera (DPC) onboard Gaofen-5(02) satellite and the components module of the generalized retrieval of atmosphere and surface properties (GRASP) algorithm are used to study various aerosol optical properties and their spatial distributions over ocean, and furthermore, the observation data from aerosol robotic network (AERONET) sites are used to preliminarily verify the results from DPC/GRASP. The verification results show that the retrieved various aerosol properties over ocean from DPC/GRASP have a good performance. Specifically, the correlation coefficients between the aerosol optical depth (AOD), Angstrom exponent (AExp), fine-mode AOD (FAOD), coarse-mode AOD (CAOD), and single scattering albedo (SSA) retrieved from DPC/GRASP and AERONET observation results are 0.961, 0.848, 0.837, 0.914, and 0.750, respectively. There is a positive bias of AOD (0.034) and it indicates that the DPC/GRASP slightly overestimates the concentration of aerosols over ocean, which is mainly due to fine-mode particle. In the perspective of AOD global spatial distribution, the results of DPC/GRASP have a good consistency with the products from the Moderate Resolution Imaging Spectroradiometer (MODIS), indicating that DPC can correctly describe the spatial distribution of aerosols over ocean. This study demonstrates the good performance of DPC for monitoring various marine aerosol properties, which will provide valuable experience and research basis for the development of atmospheric hardware instruments and aerosol inversion algorithms in the future.

Based on CALIPSO satellite data and ERA5 reanalysis data, the correlation between the optical properties of tropospheric aerosols and relative humidity in the marine areas within the longitude range of 108° E–124° E and the latitude range of 18° N–41° N (i.e. China's offshore waters) from 2007 to 2016 is analyzed. The results show that during the study period, the 532 nm total backscattering coefficient and the 532 nm extinction coefficient of aerosols in the sea area increases with the increase of relative humidity, while the depolarization ratio of aerosols decreases with the increase of relative humidity. This may be due to the change of the hygroscopicity and overall morphology of aerosol particles caused by the increase of relative humidity. At the same time, the values of various aerosol optical properties are the lowest in summer as a whole, while the values in spring, autumn and winter will change alternately with the increase of relative humidity, which may be related to the different proportions of various types of aerosols in different seasons. In the other hand, the values of aerosol optical properties in 2014–2016 were significantly lower than those in the previous seven years, which may be the result of the strong implementation of China's environmental protection policies. After further dividing the offshore waters of China, it is found that from 2007 to 2016, the proportion of marine derived aerosols increases in order of the Bohai and Yellow Seas, the East China Sea and the South China Sea, and the overall value of each optical property of aerosols decreases in order of the Bohai and Yellow Seas, the East China Sea and the South China Sea. Further analysis on the division of altitude layers in the sea area shows that, within the range of 0–7 km, the higher the altitude, the smaller the proportion of marine source aerosols and the larger the proportion of land source aerosols, and at the same time, the overall value of aerosol depolarization ratio continues to increase.

Hyperspectral image can obtain fine spectral information of ground objects, and is a data source for fine identification of ground objects and high-precision inversion of parameters. However, due to its own characteristics, hyperspectral sensors often have low resolution and long coverage periods, which limits their application and promotion. In order to improve the timeliness of hyperspectral images, researchers have carried out a lot of research on hyperspectral image simulation. However, most of the existing methods are based on the ideal spectrum library, which is quite different from the actual scene spectra. A hyperspectral image simulation method is constructed based on a scene spectral library, and a spectral matching algorithm is proposed based on normalized difference vegetation index (NDVI), which greatly improves the speed and accuracy of simulation. The method was tested in the southwest of Dezhou City, Shandong Province, China, and the GF-1 WFV multispectral data were used as the template images to simulate the GF-5 AHSI load data, and at last, the simulation results was compared with the traditional simulation methods. The comparison results show that the simulation results of this method are good, with an average R2 of 0.69 for 283 effective bands, which is 0.16 higher than that of the traditional simulation method based on category retrieval. However, the simulation effect of each band is different, among which the best simulation effect is at band 71, where R2 reaches 0.81, which is 0.18 more than the simulation method based on category matching retrieval. In terms of operation efficiency, the simulation time of the new method is greatly shortened and the simulation speed is increased by 75%.

The spaceborne high-precision solar irradiance spectrometer is one of the important instruments for observing and studying the solar irradiance, and the precision of its wavelength scanning mechanism largely determines the accuracy of the spectral measurement results. In order to achieve the required positioning accuracy of the grating, a servo drive system with a voice coil motor as the core is designed. According to the required functions of the system, a drive controller structure scheme of digital signal processing (DSP) and field programmable gate array (FPGA) is designed, then the functions of the system are divided, and the hardware circuits and software programs are designed according to the required functions. The hardware circuits mainly include a motor drive circuit, a high-precision current acquisition circuit, and a position feedback acquisition circuit. The software programs consist of two parts: DSP and FPGA. DSP mainly includes system initialization, external memory interface (EMIF) communication, and three-loop proportional-integral-derivative (PID) calculation. FPGA is mainly used to cooperate with the three-loop PID algorithm of DSP. Its functions mainly include motor driver, analog/digital (A/D) sampling control, coding sampling, and data exchange with DSP. Finally, through simulation verification, experimental test and practical application, the effectiveness of the drive system is verified, the three-loop PID control of the voice coil motor is realized, and at the same time, it is also shown that the actual motor positioning accuracy can meet the design requirements of the drive grating.