Study on Temporal and Spatial Distribution Characteristics and Influencing Factors of XCO2 Concentration in China
Based on GOSAT satellite remote sensing XCO2 data,the study analyzes the spatio-temporal dynamics characteristics of XCO2 in China from 2011 to 2020,and adopts pearson correlation coefficient and geographically and temporally weighted regression model to explore the influence mechanism of natural and human activities on the distribution of XCO2 in China.The results indicate that:(1)High XCO2 exhibits a spatial pattern of"southeast high-northwest low",with localized high-concentration aggregation phenomena.Except in the deserts in western Xinjiang and Tibet,the low XCO2 decreases from high to low latitude,with an over 6 g/mL concentration gap between the eastern and central-western regions.(2)The average annual change range of XCO2 from 2011 to 2020 is over 5.5%.The monthly average XCO2 shows seasonal variations during the year,with the highest rate of concentration change occurring during the spring-summer transition period.Additionally,a rapid decrease in XCO2 relative to the annual mean is observed every summer.(3)The correlation between XCO2 and influencing factors ranks as follows:carbon emissions from fossil fuel combustion,vegetation,precipitation and temperature.Over time,the positive impact of carbon emissions from fossil fuel combustion on the spatial distribution of XCO2 gradually diminishes,while the influence of temperature intensifies both in intensity and spatial range.
XCO2time series analysisgeographically and temporally weighted regression modelinfluencing factors
NETL
NSTL
万方数据
