Study On The Spatiotemporal Variation Characteristics Of Atmospheric CO₂ Concentration And Anthropogenic Carbon Emissions In China Using Multi-source Satellite Remote Sensin

Accurately assess the spatiotemporal changes of atmospheric CO₂ concentration and anthropogenic CO₂ emission,is critical to mitigate greenhouse gas emissions contributing to climate change.Satellite remote sensing of greenhouse gases is one of the effective means for monitoring global and regional atmospheric CO₂ concentrations and anthropogenic CO₂emissions.However,the GOSAT and OCO-2 satellites used in the current study suffer from inconsistency in spatiotemporal scales and a large number of data gaps.How to use multi-source satellite remote sensing data to conduct research on anthropogenic CO₂ emissions needs to be discussed further.In this study,we first used the in-situ observations from atmospheric background station to evaluate the performance of the continuous XCO₂ dataset（Mapping-XCO₂）in China;Evaluated the validity of XCO₂ anomaly method for separating anthropogenic CO₂ emissions based on anthropogenic emission inventory data（EDGAR、ODIAC）;Explored the synergistic emission relationship between anthropogenic CO₂ emissions and atmospheric pollutant data（NO₂,CO）by comparing the spatial distribution of XCO₂ anomalies with XNO₂and XCO.Our results can provide scientific reference for satellite monitoring and evaluation of the spatiotemporal changes of atmospheric CO₂ concentration and anthropogenic CO₂emissions.The main research contents and conclusions of this paper are as follows:（1）Our results showed that Mapping-XCO₂ had a high consistency with in-situ observations from atmospheric background stations,indicating the potential of Mapping-XCO₂to apply for regional analysis.The XCO₂ anomalies in the non-growing season were well consistent with anthropogenic CO₂ emissions collected from EDGAR and ODIAC,with a correlation coefficient of 0.71 and 0.67 at provincial-level,respectively（P<0.01）.The XCO₂anomaly is in good agreement with the spatial distribution of the atmospheric pollutants NO₂and XCO,and the correlation between XCO₂ anomalies and XNO₂（r=0.79,P<0.01）is higher than that of XCO（r=0.61,P<0.01）at the provincial administrative level,and the XCO₂anomalies to XNO₂ and XCO ratio shows that the emission ratio of low combustion emission efficiency areas is twice as high as that of high combustion emission efficiency areas.（2）From 2010 to 2020,the annual average XCO₂ in China is 400.4 ppm,with a high value in the East and a low value in the West.The annual increase rate of XCO₂ is 2.47 ppm.Influenced by the absorption of natural ecosystems,the monthly average XCO₂ changes in China show a"peak"and then a"trough",and the correlation coefficient between XCO₂ and SIF and GPP is -0.63 and-0.6,respectively（P<0.01）.The XCO₂ anomaly in the non-growing season can portray the spatial and temporal variation of anthropogenic CO₂ emissions,and the increase rate of anthropogenic CO₂ emissions in Beijing-Tianjin-Hebei,Yangtze River Delta and Pearl River Delta was 0.12 ppm/a,0.08/a ppm and 0.08/a ppm respectively.（3）The impact of Satellite monitoring of COVID-19 control on the changes of XCO₂ anomaly,XNO₂ and XCO varied in different regions.XCO₂ anomalies during the COVID-19 were 2 ppm and 1 ppm in Beijing-Tianjin-Hebei and Yangtze River Delta,respectively.Compared with the same period of the COVID-19,XCO₂ anomalies decreased by about 0.5ppm in Yangtze River Delta and increased by about 1.5 ppm in Beijing-Tianjin-Hebei.XNO₂decreased significantly in Yangtze River Delta and Beijing-Tianjin-Hebei,with a decrease rate of 60%and 35%,respectively,and the change of XCO was not significant.The temporal changes of XCO₂ anomaly,XNO₂ and XCO during the epidemic period indicate that the pollution carbon emissions affected by the control of the epidemic show a first decrease and then an increase.During the COVID-19,the anthropogenic emission transport in the southwest direction of Beijing-Tianjin-Hebei（35%of trajectories）was higher than that in the year-on-year period of the COVID-19（12%）,while the Yangtze River Delta is less affected by long-range transport during the COVID-19.