Journals >Journal of Atmospheric and Environmental Optics
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2022
Volume: 17 Issue 6
9 Article(s)
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Advances in atmospheric observation techniques for greenhouse gases by satellite remote sensing
Xiaoyu YANG, Zhongting WANG, Guang PAN, Wei XIONG, Wei ZHOU, Lianhua ZHANG, Zhaojun WANG, Tenglong JIANG, Jianjun LIU, Yazhen DAI, Pengfei MA, Qing LI, and Shaohua ZHAO
In response to climate change, the information of global, regional and urban carbon concentration, as well as carbon source and sink is essential for achieving dual carbon goals, actively participating in international negotiations, and providing policymakers with reliable and up-to-date support. The “top-down” approacIn response to climate change, the information of global, regional and urban carbon concentration, as well as carbon source and sink is essential for achieving dual carbon goals, actively participating in international negotiations, and providing policymakers with reliable and up-to-date support. The “top-down” approach to carbon source-sink accounting, which uses satellite observations as the base flux calculation technology, has become an internationally recognized method for supporting and validating greenhouse gas emissions inventories. This paper systematically introduces the principle, category and development of the satellite detection payloads for greenhouse gases, the atmospheric remote sensing estimation methods for CO 2 , CH 4 , and N 2 O concentrations and emission fluxes, as well as the influencing factors of detection deficiency and errors. And the urgent demand for improving the detection capability of satellites for greenhouse gas, the insufficient accuracy of concentration inversion and emission estimation, the lack of remote sensing research on other greenhouse gases such as N 2 O and fluoride, and the weak verification capability of ground-based remote sensing are analyzed in depth. Finally, the future development trends of greenhouse gas satellite remote sensing technology in China are summarized, which are mainly focusing on the development and application of active and passive, high temporal and spatial resolution satellites, high-precision emission estimation (especially for cities, small areas and point source scales), and remote sensing assessment of fluoride, in order to promote the understanding of carbon cycle, and improve the ability to sense and respond to climate change..
Journal of Atmospheric and Environmental Optics
- Publication Date: Jan. 01, 1900
- Vol. 17, Issue 6, 581 (2022)
Research on spectral feature cloud detection method of directional polarimetric camera on Chinese satellite
Mengyu HOU, Zhengqiang LI, Yisong XIE, Rui QIAO, Yanqing XIE, Lili QIE, and Zheng SHI
Cloud detection is a crucial process of satellite remote sensing because of its significant impacts on the monitoring and quantitative retrieval of various atmospheric and surface parameters, and its accuracy also affects the retrieval of cloud microphysical properties. In this study, an improved cloud detection algoriCloud detection is a crucial process of satellite remote sensing because of its significant impacts on the monitoring and quantitative retrieval of various atmospheric and surface parameters, and its accuracy also affects the retrieval of cloud microphysical properties. In this study, an improved cloud detection algorithm based on spectral information is established for the directional polarimetric camera (DPC) onboard Gaofen-5 satellite. Based on thedifferences between cloud pixels and clear pixels in the visible spectrum, the absorption characteristics of oxygen A-band, the polarized reflectance of blue band, and the polarized rainbow feature, the algorithm establishes a comprehensive cloud detection method over land and ocean area, and further proposes a multi-angle fusion strategy for the final determination of cloud detection. The recognition of high thin clouds and low thin clouds is improved by adding apparent pressure detection and polarization rainbow detection over land, respectively, and in other hand, the combination of apparent pressure and degree of linear polarization is used to improve the detection of cloud pixels in the sun-glint area over ocean. Examples of global cloud detection results of DPC have shown the effectiveness of this method, and the results of typical areas have also shown good consistency with MODIS cloud products. This research can be expected to provide a methodological basis for the cloud detection on the multi-angle and polarimetric sensor onboard the recently launched Gaofen-5(02) satellite..
Journal of Atmospheric and Environmental Optics
- Publication Date: Jan. 01, 1900
- Vol. 17, Issue 6, 598 (2022)
Comparison and historical trend analysis of satellite remote sensing datasets of near-surface PM 2.5 mass concentration in China
Liuxin DAI, Ying ZHANG, Zhengqiang LI, and Sijia LOU
With the increasing attention to air pollution, monitoring atmospheric particulate mass concentration has become a hot research field. In this paper, the scientific data sets of near-surface PM 2.5 mass concentration generated by two popular algorithms (model simulation and machine learning) are compared, quantitativelWith the increasing attention to air pollution, monitoring atmospheric particulate mass concentration has become a hot research field. In this paper, the scientific data sets of near-surface PM 2.5 mass concentration generated by two popular algorithms (model simulation and machine learning) are compared, quantitatively evaluated the uncertainty of the two data sets by using urban annual average PM 2.5 monitoring data, and the spatial rationality of the two data sets through spatial autocorrelation analysis. Meanwhile, the spatial-temporal evolution trend of PM 2.5 in major pollution areas (Beijing, Tianjin, Hebei, Henan, Shanxi and Shandong) from 2000 to 2018 was also studied by using standard deviation ellipse analysis. The results show that the data set (CHAP) based on machine learning algorithm has high precision and is suitable for regional air quality research, and the data set (vanDonkelaarA) generated by the model simulation algorithm has a reasonable spatial distribution and is more suitable for large-scale and long-term pollution trend analysis. According to the analysis of standard deviation ellipse, the center of standard deviation ellipse in the study area moved to the northeast from 2000 to 2018. Before 2013, the distribution range and annual mean value of PM 2.5 showed an overall trend of increase, and then decreased significantly. It is shown that the main factor contributing to the decrease in PM 2.5 concentration is the implementation of effective control measures. The result provides a reference for the selection of fine particulate matter pollution research data sets in China, and also provides scientific support for the prevention and control of atmospheric fine particulate matter pollution..
Journal of Atmospheric and Environmental Optics
- Publication Date: Jan. 01, 1900
- Vol. 17, Issue 6, 613 (2022)
An optimized retrieval algorithm of aerosol layer height from hyperspectral satellites using O 2 -A band
Jian XU, Lanlan RAO, Adrian DOICU, Letu HUSI, and Kai QIN
To address the retrieval errors in passive satellite remote sensing of aerosol parameters due to the uncertainty of aerosol models, a novel aerosol layer height retrieval algorithm based on Bayesian theory is introduced and applied to the TROPOspheric Monitoring Instrument (TROPOMI) of the Sentinel-5 Precursor (SentineTo address the retrieval errors in passive satellite remote sensing of aerosol parameters due to the uncertainty of aerosol models, a novel aerosol layer height retrieval algorithm based on Bayesian theory is introduced and applied to the TROPOspheric Monitoring Instrument (TROPOMI) of the Sentinel-5 Precursor (Sentinel-5P) satellite in this work. The algorithm determines the aerosol model that meets the current observation data conditions based on the model evidence (conditional probability density of aerosol models) of different candidate aerosol models, and obtains the estimated maximum and estimated mean values as the results by two model selection schemes, respectively. Taking a real wildfire event observed by TROPOMI as an example, the retrieval results show a good spatial agreement with the official products. The underestimation found in previous algorithms is significantly improved, which proves that the algorithm can efficiently select a suitable aerosol model in the lack of a prior knowledge, and will offer a new solution for future operational data processing of aerosol layer height inversion from hyperspectral satellites..
Journal of Atmospheric and Environmental Optics
- Publication Date: Jan. 01, 1900
- Vol. 17, Issue 6, 630 (2022)
Accuracy verification of OMI global ozone products based on Pandora observations
Ke WANG, Zhengqiang LI, Kaitao LI, Hua XU, Mengyu HOU, and Bolin WANG
As an important trace gas in the atmosphere, ozone is one of the important components that affect the movement of the atmosphere in the troposphere and stratosphere. The high-precision detection of ozone is of great significance to the environment and climate, and OMI sensor is currently one of the main remote sensing As an important trace gas in the atmosphere, ozone is one of the important components that affect the movement of the atmosphere in the troposphere and stratosphere. The high-precision detection of ozone is of great significance to the environment and climate, and OMI sensor is currently one of the main remote sensing sensors capable of detecting global ozone levels. In this paper, the accuracy of OMI satellite data products is verified by using the data of 44 ozone observation stations around the world of the ground-based Pandora observation network. The results show that there is a good linear correlation between OMI ozone products and Pandora ground measurement results, with the correlation coefficient reaching 0.946. However, there are regional differences in the accuracy results. In the southern hemisphere, the correlation coefficient is 0.894. While in the northern hemisphere low latitudes, the correlation coefficient is 0.931, in the middle latitudes, the correlation coefficient is 0.951, and in the high latitudes, the correlation coefficient reaches 0.957. In addition, the verification accuracy is also related to the total ozone column. When the total ozone column is less than 220 Du (corresponding to the ozone hole condition), OMI satellite product is overestimated by about 13%. Above 400 Du, OMI ′ s ozone product is lower than Pandora ′ s ground-based measurement. And as the total ozone column increases, the underestimation becomes more serious. When the total ozone column reaches 500 Du, OMI ′ s ozone product is underestimated by about 4%..
Journal of Atmospheric and Environmental Optics
- Publication Date: Jan. 01, 1900
- Vol. 17, Issue 6, 640 (2022)
Remote sensing emission inventory of field-level open biomass burning NO x of China
Yonglin SHEN, Changmin JIANG, Zemin XIAO, Ling YAO, and Kai QIN
Aiming at different land cover types, especially the spatial distribution of crops, an emission factor (EF) weighting strategy, which considers the prior probability of the elaborate crop distributionwithin the fire pixels, was proposed, and then under the assumption of Gaussian distribution of diurnal cycle of fire raAiming at different land cover types, especially the spatial distribution of crops, an emission factor (EF) weighting strategy, which considers the prior probability of the elaborate crop distributionwithin the fire pixels, was proposed, and then under the assumption of Gaussian distribution of diurnal cycle of fire radiative power (FRP), the emission inventory of nitrogen oxide (NO x ) from biomass combustion on field-level of China was constructed. To validate the assumption of Gaussian distribution of diurnal cycle of FRP, comparison between the established emission inventory and the Himawari-8 satellite observations was conducted, and the Pearson correlation coefficient between the two results reaches 0.65. Meanwhile, in order to evaluate the emission inventory, comparisons with the global fire emission database (GFED), in-situ observations at three environmental monitoring stations in Hubei Province and ozone monitoring instrument (OMI) product were also conducted. It is shown that the correlation coefficients between the emission inventories established in this study and the two in-situ observations are 0.56 and 0.65, respectively, and in other hand, the emission inventory agrees well with GFED database and OMI observations in general with higher spatiotemporal resolution..
Journal of Atmospheric and Environmental Optics
- Publication Date: Jan. 01, 1900
- Vol. 17, Issue 6, 655 (2022)
High-resolution XCH4 anomaly detection method using GF-5 AHSI payload
Keyi YANG, Ge HAN, Huiqin MAO, Yanni DONG, Xin MA, Siwei LI, and Wei GONG
Coal mining is the most important methane emission source, yet a key reason for the low accuracy of its emission inventories is the lack of capability to accurately identify and locate this type of emission source. In recent years, cutting-edge research has shown that it is possible to use satellite hyperspectral data Coal mining is the most important methane emission source, yet a key reason for the low accuracy of its emission inventories is the lack of capability to accurately identify and locate this type of emission source. In recent years, cutting-edge research has shown that it is possible to use satellite hyperspectral data to invert high-resolution methane anomalies and thus help to identify emission sources. However, this algorithm will fail completely inareas with complex surface types. To address this problem, the paper proposes the L1 reweighted iterative shrinkage thresholding algorithm (ISTA) matched filter algorithm for the first time. Experiments in Shanxi region using GF-5 advanced hyperspectral imager (AHSI) data show that the performance of the modified method is significantly better than that of the other existing methods. In the experiments, this method identifies 23 strong methane point sources, all of which are located in the methane high value area of TROPOMI, and the high-resolution remote sensing images also show the presence of typical coal mining facilities at these point sources. This method has laid a technical foundation for the worldwide implementation of methane point source identification using GF-5 AHSI data..
Journal of Atmospheric and Environmental Optics
- Publication Date: Jan. 01, 1900
- Vol. 17, Issue 6, 670 (2022)
Spatial and temporal distribution of XCO 2 and XCH 4 in China based on satellite remote sensing
Yizhen JIA, Minghui TAO, Sijia DING, Hangyu LIU, Mingyu ZENG, and Liangfu CHEN
The large amount of greenhouse gases, mainly CO 2 and CH 4 , emitted by human activities is a major contributor to global warming. Due to the scarcity of ground-based observation sites, satellite remote sensing provides a new technical means to monitor the spatial and temporal distribution and trends of CO 2 and CH 4 .The large amount of greenhouse gases, mainly CO 2 and CH 4 , emitted by human activities is a major contributor to global warming. Due to the scarcity of ground-based observation sites, satellite remote sensing provides a new technical means to monitor the spatial and temporal distribution and trends of CO 2 and CH 4 . In this paper, we verify the accuracy of XCO 2 and XCH 4 , the remote sensing products of atmospheric CO 2 and CH 4 column concentrations from GOSAT and OCO-2 satellites, and analyze the spatial and temporal distributions and trends of XCO 2 and XCH 4 in China. The main conclusions are as follows. (1) Among XCO 2 remote sensing products, OCO-2_ACOS has the highest correlation with ground observation (up to 0.93); while GOSAT_OCPR has the highest correlation with XCH 4 products (up to 0.78). (2) In the years of study, XCO 2 concentration increases year by year, for example, the annual average OCO-2 XCO 2 concentration in China increases from 396.92 × 10 －6 in 2014 to 414.72 × 10 －6 in 2021. The high values of CO 2 concentration are mainly distributed in urban and industrial concentrated East China, and the high values in the Taklamakan Desert in Northwest China are related to the influence of aerosol scattering. And in the other hand, influenced by the seasonality of anthropogenic and natural sources, XCO 2 has the temporal characteristics of high in winter and spring and low in summer and autumn. (3) The concentration of XCH 4 also increases year by year. Unlike XCO 2 , the high concentration of XCH 4 is distributed in central areas of China such as eastern Sichuan, western Chongqing, centralShaanxi and Shanxi where natural gas and coal mining are concentrated, and the northern China where industry is concentrated. And the seasonal concentration of XCH 4 is high in summer and autumn and low in spring and winter. (4) In 2020, the XCO 2 high value area shifts. Compared with 2020, the CO 2 growth rate of 2021 increases a little, but the increase is still reduced compared with that before 2019..
Journal of Atmospheric and Environmental Optics
- Publication Date: Jan. 01, 1900
- Vol. 17, Issue 6, 679 (2022)
[in Chinese]
Journal of Atmospheric and Environmental Optics
- Publication Date: Jan. 01, 1900
- Vol. 17, Issue 6, 1 (2022)
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