浏览全部资源
扫码关注微信
纸质出版日期： 2022-12-07 ，
扫 描 看 全 文
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
Bai W G, Zhang X Y and Zhang P. 2010. Temporal and spatial distribution of tropospheric CO2 over China based on satellite observation. Chinese Science Bulletin, 55(30): 3612-3618
白文广, 张兴赢, 张鹏. 2010. 卫星遥感监测中国地区对流层二氧化碳时空变化特征分析. 科学通报, 55(30): 2953-2960 [DOI: 10.1360/csb2010-55-30-2953http://dx.doi.org/10.1360/csb2010-55-30-2953]
Barkley M P, Monks P S, Hewitt A J, Machida T, Desai A, Vinnichenko N, Nakazawa T, Arshinov M Y, Fedoseev N and Watai T. 2007. Assessing the near surface sensitivity of SCIAMACHY atmospheric CO2 retrieved using (FSI) WFM-DOAS. Atmospheric Chemistry and Physics, 7(13): 3597-3619 [DOI: 10.5194/acp-7-3597-2007http://dx.doi.org/10.5194/acp-7-3597-2007]
Bu R, Lei L P, Guo L J, Liu D and Zeng Z C. 2015. Temporal and spatial potential applications of satellite remote sensing of atmospheric CO2 concentration monitoring. Journal of Remote Sensing, 19(1): 34-45
布然, 雷莉萍, 郭丽洁, 刘达, 曾招城. 2015. 大气CO2浓度时空变化卫星遥感监测的应用潜力分析. 遥感学报, 19(1): 34-45 [DOI: 10.11834/jrs.20154031http://dx.doi.org/10.11834/jrs.20154031]
Buchwitz M, de Beek R, Noël S, Burrows J P, Bovensmann H, Bremer H, Bergamaschi P, Körner S and Heimann M. 2005. Carbon monoxide, methane and carbon dioxide columns retrieved from SCIAMACHY by WFM-DOAS: year 2003 initial data set. Atmospheric Chemistry and Physics, 5(12): 3313-3329 [DOI: 10.5194/acp-5-3313-2005http://dx.doi.org/10.5194/acp-5-3313-2005]
Buchwitz M, Reuter M, Bovensmann H, Pillai D, Heymann J, Schneising O, Rozanov V, Krings T, Burrows J P, Boesch H, Gerbig C, Meijer Y and Löscher A. 2013. Carbon Monitoring Satellite (CarbonSat): assessment of scattering related atmospheric CO2 and CH4 retrieval errors and first results on implications for inferring city CO2 emissions. Atmospheric Measurement Techniques Discussions, 6: 4769-4850 [DOI: 10.5194/amtd-6-4769-2013http://dx.doi.org/10.5194/amtd-6-4769-2013]
Cogan A J, Boesch H, Parker R J, Feng L, Palmer P I, Blavier J F L, Deutscher N M, Macatangay R, Notholt J, Roehl C, Warneke T and Wunch D. 2012. Atmospheric carbon dioxide retrieved from the Greenhouse gases Observing SATellite (GOSAT): comparison with ground-based TCCON observations and GEOS-Chem model calculations. Journal of Geophysical Research: Atmospheres, 117(D21): D21301 [DOI: 10.1029/2012JD018087http://dx.doi.org/10.1029/2012JD018087]
Dai L J, Cui W H and Jiang Y B. 2012. Temporal and spatial distribution of tropospheric carbon dioxide from 2003 to 2010 in China. Ecology and Environmental Sciences, 21(7): 1266-1270
戴丽君, 崔伟宏, Jiang Y B. 2012. 2003-2010年中国对流层CO2时空分布研究. 生态环境学报, 21(7): 1266-1270 [DOI: 10.16258/j.cnki.1674-5906(2012)07-1266-05http://dx.doi.org/10.16258/j.cnki.1674-5906(2012)07-1266-05]
Deng A J, Guo H B, Hu J, Jiang C Z, Liu P G and Jing H F. 2020. Temporal and distribution characteristic of CO2 concentration over China based on GOSAT satellite data. Journal of Remote Sensing, 24(3): 319-325
邓安健, 郭海波, 胡洁, 姜成桢, 刘培更, 荆海峰. 2020. GOSAT卫星数据监测中国大陆上空CO2浓度时空变化特征. 遥感学报, 24(3): 319-325 [DOI: 10.11834/jrs.20208324http://dx.doi.org/10.11834/jrs.20208324]
Dettinger M D and Ghil M. 1998. Seasonal and interannual variations of atmospheric CO2 and climate. Tellus B, 50(1): 1-24 [DOI: 10.1034/j.1600-0889.1998.00001.xhttp://dx.doi.org/10.1034/j.1600-0889.1998.00001.x]
Gregg J S, Andres R J and Marland G. 2008. China: emissions pattern of the world leader in CO2 emissions from fossil fuel consumption and cement production. Geophysical Research Letters, 35(8): L08806 [DOI: 10.1029/2007GL032887http://dx.doi.org/10.1029/2007GL032887]
Guerlet S, Butz A, Schepers D, Basu S, Hasekamp O P, Kuze A, Yokota T, Blavier J F, Deutscher N M, Griffith D W T, Hase F, Kyro E, Morino I, Sherlock V, Sussmann R, Galli A and Aben I. 2013. Impact of aerosol and thin cirrus on retrieving and validating XCO2 from GOSAT shortwave infrared measurements. Journal of Geophysical Research: Atmospheres, 118(10): 4887-4905 [DOI: 10.1002/jgrd.50332http://dx.doi.org/10.1002/jgrd.50332]
Guo M, Wang X, Li J, Wang H. 2013. Examining the relationships between land cover and greenhouse gas concentrations using remote-sensing data in East Asia. International Journal of Remote Sensing, 34 (12): 4281-4303 [DOI: 10.1080/01431161.2013.775535http://dx.doi.org/10.1080/01431161.2013.775535]
Houghton R A. 2002. Magnitude, distribution and causes of terrestrial carbon sinks and some implications for policy. Climate Policy, 2(1): 71-88 [DOI: 10.1016/S1469-3062(02)00012-8http://dx.doi.org/10.1016/S1469-3062(02)00012-8]
IPCC. 2013. Climate Change 2013: The Physical Science Basis. Cambridge (eds Thomas. F. Stocher et al). United Kingdom and New York: Cambridge University Press
Kuze A, Suto H, Nakajima M and Hamazaki T. 2009. Thermal and near infrared sensor for carbon observation Fourier-transform spectrometer on the Greenhouse Gases Observing Satellite for greenhouse gases monitoring. Applied Optics, 48(35): 6716-6733 [DOI: 10.1364/AO.48.006716http://dx.doi.org/10.1364/AO.48.006716]
Le Quéré C, Raupach M R, Canadell J G, Marland G, Bopp L, Ciais P, Conway T J, Doney S C, Feely R A, Foster P, Friedlingstein P, Gurney K, Houghton R A, House J I, Huntingford C, Levy P E, Lomas M R, Majkut J, Metzl N, Ometto J P, Peters G P, Prentice I C, Randerson J T, Running S W, Sarmiento J L, Schuster U, Sitch S, Takahashi T, Viovy N, van der Werf G R and Woodward F I. 2009. Trends in the sources and sinks of carbon dioxide. Nature Geoscience, 2(12): 831-836 [DOI: 10.1038/ngeo689http://dx.doi.org/10.1038/ngeo689]
Liu L X, Zhou L X, Zhang X C, Wen M, Zhang F, Yao B, Fang S X. 2009. The characteristics of atmospheric CO2 concentration variation of four national background stations in China. Science in China Series D: Earth Sciences, 52(11): 1857-1863
刘立新, 周凌晞, 张晓春, 温民, 张芳, 姚波, 方双喜. 2009. 我国4个国家级本底站大气CO2浓度变化特征. 中国科学(D辑: 地球科学), 39(2): 222-228 [DOI: 10.1007/s11430-009-0143-7http://dx.doi.org/10.1007/s11430-009-0143-7]
Liu R X, Zhang X Y, Liu J and Liu Y G. 2015. A spatial-temporal distribution characteristics study on the atmospheric carbon dioxide observed by GOSAT satellite remote sensing. Journal of Tropical Meteorology, 21(4): 408-416 [DOI: 10.16555/j.1006-8775.2015.04.009http://dx.doi.org/10.16555/j.1006-8775.2015.04.009]
Mousavi S M, Falahatkar S and Farajzadeh M. 2017. Assessment of seasonal variations of carbon dioxide concentration in Iran using GOSAT data. Natural Resources Forum, 41(2): 83-91 [DOI: 10.1111/1477-8947.12121http://dx.doi.org/10.1111/1477-8947.12121]
Patra P K, Crisp D, Kaiser J W, Wunch D, Saeki T, Ichii K, Sekiya T, Wennberg P O, Feist D G, Pollard D F, Griffith D W T, Velazco V A, De Maziere M, Sha M K, Roehl C, Chatterjee A and Ishijima K. 2017. The Orbiting Carbon Observatory (OCO-2) tracks 2-3 peta-gram increase in carbon release to the atmosphere during the 2014—2016 El Niño. Scientific Reports, 7(1): 13567 [DOI: 10.1038/s41598-017-13459-0http://dx.doi.org/10.1038/s41598-017-13459-0]
Piao S L, Zhang X P, Chen A P, Liu Q, Lian X, Wang X H, Peng S S and Wu X C. 2019. The impacts of climate extremes on the terrestrial carbon cycle: a review. Science China: Earth Sciences, 62(10): 1551-1563
朴世龙, 张新平, 陈安平, 刘强, 连旭, 王旭辉, 彭书时, 吴秀臣. 2019. 极端气候事件对陆地生态系统碳循环的影响. 中国科学: 地球科学, 49(9): 1321-1334 [DOI: 10.1007/s11430-018-9363-5http://dx.doi.org/10.1007/s11430-018-9363-5]
Reichstein M, Bahn M, Ciais P, Frank D, Mahecha M D, Seneviratne S I, Zscheischler J, Beer C, Buchmann N, Frank D C, Papale D, Rammig A, Smith P, Thonicke K, van der Velde M, Vicca S, Walz A and Wattenbach M. 2013. Climate extremes and the carbon cycle. Nature, 500(7462): 287-295 [DOI: 10.1038/nature12350http://dx.doi.org/10.1038/nature12350]
Reuter M, Bovensmann H, Buchwitz M, Burrows J P, Connor B J, Deutscher N M, Griffith D W T, Heymann J, Keppel-Aleks G, Messerschmidt J, Notholt J, Petri C, Robinson J, Schneising O, Sherlock V, Velazco V, Warneke T, Wennberg P O and Wunch D. 2011. Retrieval of atmospheric CO2 with enhanced accuracy and precision from SCIAMACHY: validation with FTS measurements and comparison with model results. Journal of Geophysical Research: Atmospheres, 116(D4): D04301 [DOI: 10.1029/2010JD015047http://dx.doi.org/10.1029/2010JD015047]
Wang K, Jiang H, Zhang X Y and Zhou G M. 2011. Analysis of spatial and temporal variations of carbon dioxide over China using SCIAMACHY satellite observations during 2003—2005. International Journal of Remote Sensing, 32(3): 815-832 [DOI: 10.1080/01431161.2010.517805http://dx.doi.org/10.1080/01431161.2010.517805]
Wang S P, Zhang X Y, Wang W H and Fang L. 2015. Global and China-based regional near-surface distributions of CO2 concentrations based on GOSAT L4B data. Science and Technology Review, 33(17): 63-68
王舒鹏, 张兴赢, 王维和, 方莉. 2015. 基于GOSAT L4B数据的全球和中国区域近地面CO2含量变化分析. 科技导报, 33(17): 63-68 [DOI: 10.3981/j.issn.1000-7857.2015.17.006http://dx.doi.org/10.3981/j.issn.1000-7857.2015.17.006]
Weatherhead E C, Reinsel G C, Tiao G C, Meng X L, Choi D, Cheang W K, Keller T, DeLuisi J, Wuebbles D J, Kerr J B, Miller A J, Oltmans S J and Frederick J E. 1998. Factors affecting the detection of trends: statistical considerations and applications to environmental data. Journal of Geophysical Research: Atmospheres, 103(D14): 17149-17161 [DOI: 0.1029/98JD00995http://dx.doi.org/0.1029/98JD00995]
Xia L J, Liu L X, Li B Z and Zhou L X. 2018. Spatial and temporal distribution characteristics of atmospheric CO2 in Central China. China Environmental Science, 38(8): 2811-2819
夏玲君, 刘立新, 李柏贞, 周凌晞. 2018. 我国中部地区大气CO2柱浓度时空分布. 中国环境科学, 38(8): 2811-2819 [DOI: 10.3969/j.issn.1000-6923.2018.08.003http://dx.doi.org/10.3969/j.issn.1000-6923.2018.08.003]
Yang D X, Liu Y, Cai Z N, Deng J B, Wang J and Chen X. 2015. An advanced carbon dioxide retrieval algorithm for satellite measurements and its application to GOSAT observations. Science Bulletin, 60(23): 2063-2066 [DOI: 10.1007/s11434-015-0953-2http://dx.doi.org/10.1007/s11434-015-0953-2]
Yoshida Y, Kikuchi N, Morino I, Uchino O, Oshchepkov S, Bril A, Saeki T, Schutgens N, Toon G C, Wunch D, Roehl C M, Wennberg P O, Griffith D W T, Deutscher N M, Warneke T, Notholt J, Robinson J, Sherlock V, Connor B, Rettinger M, Sussmann R, Ahonen P, Heikkinen P, Kyrö E and Yokota T. 2013. Improvement of the retrieval algorithm for GOSAT SWIR XCO2 and XCH4 and their validation using TCCON data. Atmospheric Measurement Techniques Discussions, 6: 949-988 [DOI: 10.5194/amtd-6-949-2013http://dx.doi.org/10.5194/amtd-6-949-2013]
Zhang X Y, Zhang P, Fang Z Y, Qiu H, Li X J and Zhang Y. 2007. The progress in trace gas remote sensing study based on the satellite monitoring. Meteorological Monthly, 33(7): 3-14
张兴赢, 张鹏, 方宗义, 邱红, 李晓静, 张艳. 2007. 应用卫星遥感技术监测大气痕量气体的研究进展. 气象, 33(7): 3-14 [DOI: 10.3969/j.issn.1000-0526.2007.07.001http://dx.doi.org/10.3969/j.issn.1000-0526.2007.07.001]
Zhang Y J, Niu Z, Wang L and Chang C Y. 2008. Study on tropospheric NO2 change trend in cities using OMI satellite data. Geography and Geo-information Science, 24(3): 96-99
张彦军, 牛铮, 王力, 常超一. 2008. 基于OMI卫星数据的城市对流层NO2变化趋势研究. 地理与地理信息科学, 24(3): 96-99
Zhao M W, Li C C, Zhang X Y, Wang C, Jiang L, Sun J L. 2017. Study on the Spatial-Temporal Change Characteristics of Global CO2 Concentration Based on SCIAMACHY Retrievals. Climate Change Research, 13(2): 95-102
赵明伟, 李晨晨, 张兴赢, 王春, 江岭, 孙京禄. 2017. 基于SCIAMACHY反演数据的全球 CO2浓度时空变化特征研究. 气候变化研究进展, 13(2): 95-102 [DOI: 10.12006/j.issn.1673-1719.2016.152http://dx.doi.org/10.12006/j.issn.1673-1719.2016.152]
相关作者
相关机构
京公网安备11010802024621