Spatial and temporal distribution of XCO2 and XCH4 in China
based on satellite remote sensing

Abstract

Abstract: The large amount of greenhouse gases, mainly CO2 and CH4, 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 CO2 and CH4. In this paper, we verify the accuracy of XCO2 and XCH4, the remote sensing products of atmospheric CO2 and CH4 column concentrations from GOSAT and OCO-2 satellites, and analyze the spatial and temporal distributions and trends of XCO2 and XCH4 in China. The main conclusions are as follows. (1) Among XCO2 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 XCH4 products (up to 0.78). (2) In the years of study, XCO2 concentration increases year by year, for example, the annual average OCO-2 XCO2 concentration in China increases from 396.92 × 10−6 in 2014 to 414.72 × 10−6 in 2021. The high values of CO2 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, XCO2 has the temporal characteristics of high in winter and spring and low in summer and autumn. (3) The concentration of XCH4 also increases year by year. Unlike XCO2, the high concentration of XCH4 is distributed in central areas of China such as eastern Sichuan, western Chongqing, central Shaanxi and Shanxi where natural gas and coal mining are concentrated, and the northern China where industry is concentrated. And the seasonal concentration of XCH4 is high in summer and autumn and low in spring and winter. (4) In 2020, the XCO2 high value area shifts. Compared with 2020, the CO2 growth rate of 2021 increases a little, but the increase is still reduced compared with that before 2019.

Key words: satellite remote sensing, XCO2, XCH4, spatial and temporal distribution, inversion accuracy

CLC Number:

P407.4

JIA Yizhen, TAO Minghui∗, DING Sijia, LIU Hangyu, ZENG Mingyu, CHEN Liangfu. Spatial and temporal distribution of XCO2 and XCH4 in China based on satellite remote sensing[J]. Journal of Atmospheric and Environmental Optics, 2022, 17(6): 679-692.

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Spatial and temporal distribution of XCO2 and XCH4 in China based on satellite remote sensing

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