Spatio-temporal Variation Characteristics of CO2 Concentration in China Based on OCO-2 Satellite Data
The issue of climate warming caused by the increase of atmospheric CO2 is a hot issue for scholars,but there have been more uncertainties in the monitoring of CO2.In this paper,we analyze the spatial and temporal distribution and variation characteristics of CO2 concentration in China based on methods such as kriging interpolation and standard deviation ellipsoid using the CO2 column concentration mixing ratio data(XCO2)observed by OCO-2 satellite from 2015-2022.The results show that:1)the accuracy of the XCO2 dataset based on OCO-2 satellite data is high,and the root-mean-square errors is only 1.75 ppm and 1.58 ppm with correlation coefficients is 0.91 and 0.96 respectively,when compared with the observations from ground monitoring stations(Waliguan and Lulin stations).2)Interannually,the XCO2 in China increases from 399.52 ppm in 2010 to 417.64 ppm in 2022,with an average annual growth rate of 2.56 ppm/a,which is higher than the average growth rate of global CO2 concentration in the past 10 years(2.06 ppm/a),but the growth rate of XCO2 shows a decreasing trend after 2019.Seasonally,XCO2 has obvious seasonal variation characteristics,with the highest XCO2 in spring and the lowest in summer.3)XCO2 shows the spatial distribution characteristics of high in the east,low in the west and northeast.The areas with high values of XCO2 are urban clusters such as Beijing-Tianjin-Hebei and Yangtze River Delta.The growth rate of XCO2 in Northeast China and Southwest China is faster than that in economically developed areas such as East China and South China.
remote sensing data inversionOCO-2XCO2spatial-temporal analysis
NETL
NSTL
万方数据
