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Published： 07 December 2022 ，
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肖钟湧，陈颖锋，林晓凤，刘珊红，谢静晗，谢先全.2022.基于多源卫星遥感数据的中国2003年—2018年CO2时空变化研究.遥感学报，26（12）： 2486-2496
Xiao Z Y，Chen Y F，Lin X F，Liu S H，Xie J H and Xie X Q. 2022. The temporal and spatial variation of CO2 column concentration over China from 2003 to 2018 based on multi-source satellite remote sensing data. National Remote Sensing Bulletin， 26（12）：2486-2496
本研究利用大气制图扫描成像吸收仪SCIAMACHY （Scanning Imaging Absorption Spectrometer for Atmospheric Chartography）和傅里叶变换光谱仪FTS （Fourier Transformation Spectrometer）卫星遥感传感器反演的CO
2
产品，结合瓦里关地面站点观测的CO
2
浓度数据进行验证，并对遥感数据进行校正，最后分析了2003年—2018年中国CO
2
时空变化特征及其影响因素。结果表明，中国区域CO
2
柱浓度呈近12个月周期变化且持续上升的趋势。2003年CO
2
柱浓度年均值为374.4 ppm，2018年CO
2
柱浓度年均值为413.7 ppm，16年间增加了39.3 ppm，约为10.51%，年均增长率为0.59%。中国区域大气CO
2
柱浓度的月变化存在明显的时空差异，月变化呈现弦曲线变化，最小值和最大值分别出现在8和4月，2018年月平均大约分别为407.7 ppm和416.3 ppm。CO
2
柱浓度的高值区主要出现在东部的亚热带和温带地区，2018年年平均最大可达417.9 ppm；最低值是在内蒙古北部，2018年平均约为409.5 ppm。从省级行政单元来看，2018年平均CO
2
柱浓度最高和最低的省份是浙江省和青海省，分别约为417.8 ppm和412.1 ppm。中国2003年—2018年CO
2
柱浓度在整个区域出现较大的增长，但是增长率在空间上存在明显的异质性。在空间上，2018年比2003年增长的数值在31.0—45.4 ppm之间，增长的百分比范围在8.9%—12.2%之间，增长较大的区域在高值区，最大增长出现在辽宁和吉林的交界处，约为12.2%；增长较小的区域出现在中国中部，最低的增长约为8.9%。
This paper used CO
2
products inversed from Scanning Imaging Absorption spectrometer for Atmospheric CartograpHY (SCIAMACHY) and Greenhouse Gases Observing Satellite Fourier Transformation Spectrometer (GOSAT FTS)
and the linear regression analysis was used to validate the remote sensing data with CO
2
concentration data observed at the Waliguan station
then the remote sensing data were corrected. The superposition model of linear and sine function was further used to analyze the temporal trend and periodicity of regional mean CO
2
over China from 2003 to 2018
and the CO
2
was synthesized at different temporal scales to study the spatial distribution characteristics. Finally
the influencing factors on these temporal and spatial characteristics were analyzed. The results showed that SCIAMACHY and GOSAT CO
2
retrievals agree well in general with ground observation CO
2
but the satellite remote sensing has obvious systematic errors. The differences between GOSAT and WDCGG CO
2
were larger than those between SCIAMACHY and WDCGG CO
2
with an average deviation of -3.89 ppm and 1.00 ppm
respectively. The SCIAMACHY CO
2
was overestimated at smaller value and underestimated at the larger value. In terms of seasonal variation
the regional monthly mean value of CO
2
column concentration appeared a cyclical variation at 12 months and gradually increase with temporal processing. The annual regional average CO
2
column concentration in 2003 and 2018 were 374.4 ppm and 413.7 ppm
respectively. The CO
2
increased 39.3 ppm (about 10.51%) from 2003 to 2018
with the average annual growth rate of 0.59%. The monthly variation of CO
2
column concentration showed significant temporal and spatial differences characterizing by a sinusoidal fluctuation
with the minimum and maximum values appeared in August and April with 407.7 ppm and 416.3 ppm in 2018
respectively. The periodic characteristics of CO
2
column concentration are primarily affected by the vegetation growth cycle of terrestrial ecosystems
various chemical processes in the soil
and anthropogenic emissions. The multi-yearly average CO
2
column concentration values from 2003 to 2018 varied between 388 and 398 ppm
with the standard deviation ranged from 10 ppm to 15 ppm. Additionally
the high values of CO
2
column concentration mainly appeared in the subtropical and temperate regions in the eastern China. The annual average CO
2
column concentration in 2018 is up to 417.9 ppm. The lowest value was in northern Inner Mongolia of about 409.5 ppm in 2018. The CO
2
column concentration in the entire region of China showed increased significantly from 2003 to 2018
but the growth rate has obvious heterogeneity in space. The increase values from 2003 to 2018 were between 31.0 ppm and 45.4 ppm. Furthermore
the growth rate had obvious heterogeneity in space
which was in range of 8.9%—12.2% in space. There was an obvious shed line for the growth rate of CO
2
column concentration
which was from northeast to southwest
coinciding with the geographical dividing line of China (Mohe-Tengchong Line). The largest growth rate occurred at the junction of Liaoning and Jilin Province
with the value of 12.2%. The region with the smaller growth appeared in Central China
with the lowest growth rate of about 8.9%.
SCIAMACHYGOSATCO2柱浓度遥感变异系数
SCIAMACHYGOSATCO2 column concentrationremote sensingvariation coefficient
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