Interpreting Temporal Changes of Atmospheric CO2 Over Fire Affected Regions Based on GOSAT Observations

被引:8
|
作者
Shi, Yusheng [1 ,2 ]
Matsunaga, Tsuneo [1 ,2 ]
Noda, Hibiki [1 ,2 ]
机构
[1] Natl Inst Environm Studies, Ctr Global Environm Res, Tsukuba, Ibaraki 3058506, Japan
[2] Natl Inst Environm Studies, Satellite Observat Ctr, GOSAT 2 Project, Tsukuba, Ibaraki 3058506, Japan
关键词
Carbon dioxide (CO2) concentration; fire CO2 emissions; greenhouse gases observing satellite (GOSAT); temporal variation; HIGH-RESOLUTION; SOUTHEAST-ASIA; EMISSIONS; DEFORESTATION; SATELLITE;
D O I
10.1109/LGRS.2016.2627056
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
The carbon dioxide (CO2) emissions released from biomass burning significantly affect the temporal variations of atmospheric CO2 concentrations. Based on a long-term (July 2009-June 2015) retrieved data sets by the greenhouse gases observing satellite (GOSAT), the seasonal cycle and interannual variations of column-averaged volume mixing ratios of atmospheric carbon dioxide (XCO2) in four fire affected continental regions were analyzed. The results showed that Northern Africa (NA) had the largest seasonal variations after removing its regional trend of XCO2 with peak-to-peak amplitude of 6.2 ppm within the year, higher than central South America (CSA) (2.4 ppm), Southern Africa (SA) (3.8 ppm), and Australia (1.7 ppm). The detrended regional XCO2 (Delta XCO2) was found to be positively correlated with the fire CO2 emissions during the fire activity period but with different seasonal variabilities. NA recorded the largest change of seasonal variations of Delta XCO2 with a total of 12.8 ppm during fire seasons, higher than CSA, SA, and Australia with 5.4, 6.7, and 2.2 ppm, respectively. During the fire episode, the positive Delta XCO2 was noticed during June-November in CSA, December to next June in NA, and May-November in SA. The Pearson correlation coefficients between the variations of Delta XCO2 and fire CO2 emissions achieved the best correlations in SA (R = 0.77 and p < 0.05). This letter revealed that fire CO2 emissions and GOSAT XCO2 presented consistent seasonal variations.
引用
收藏
页码:77 / 81
页数:5
相关论文
共 50 条
  • [41] The characteristic of atmospheric CO2 and CO concentrations based on aircraft observation over Tangshan
    Yang, Qiang
    Ma, Qian-Li
    Yao, Bo
    Yang, Yang
    Dong, Xiao-Bo
    Wang, Wu-Yi
    Lü, Feng
    Mai, Rong
    Zhongguo Huanjing Kexue/China Environmental Science, 2020, 40 (04): : 1460 - 1467
  • [42] Spatial and Temporal Variability in Atmospheric CO2 Measurements
    de Vries, Donald F. H.
    Bernardo, Cirilo H.
    10TH INTERNATIONAL CONFERENCE ON GREENHOUSE GAS CONTROL TECHNOLOGIES, 2011, 4 : 5573 - 5578
  • [43] Effects of atmospheric light scattering on spectroscopic observations of greenhouse gases from space. Part 2: Algorithm intercomparison in the GOSAT data processing for CO2 retrievals over TCCON sites
    Oshchepkov, Sergey
    Bril, Andrey
    Yokota, Tatsuya
    Wennberg, Paul O.
    Deutscher, Nicholas M.
    Wunch, Debra
    Toon, Geoffrey C.
    Yoshida, Yukio
    O'Dell, Christopher W.
    Crisp, David
    Miller, Charles E.
    Frankenberg, Christian
    Butz, Andre
    Aben, Ilse
    Guerlet, Sandrine
    Hasekamp, Otto
    Boesch, Hartmut
    Cogan, Austin
    Parker, Robert
    Griffith, David
    Macatangay, Ronald
    Notholt, Justus
    Sussmann, Ralf
    Rettinger, Markus
    Sherlock, Vanessa
    Robinson, John
    Kyro, Esko
    Heikkinen, Pauli
    Feist, Dietrich G.
    Morino, Isamu
    Kadygrov, Nikolay
    Belikov, Dmitry
    Maksyutov, Shamil
    Matsunaga, Tsuneo
    Uchino, Osamu
    Watanabe, Hiroshi
    JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2013, 118 (03) : 1493 - 1512
  • [44] Assessment of Anthropogenic Methane Emissions over Large Regions Based on GOSAT Observations and High Resolution Transport Modeling
    Janardanan, Rajesh
    Maksyutov, Shamil
    Ito, Akihiko
    Yukio, Yoshida
    Matsunaga, Tsuneo
    REMOTE SENSING, 2017, 9 (09):
  • [45] Inverse Modeling of CO2 Fluxes Using GOSAT Data and Multi-Year Ground-Based Observations
    Saeki, T.
    Maksyutov, S.
    Saito, M.
    Valsala, V.
    Oda, T.
    Andres, R. J.
    Belikov, D.
    Tans, P.
    Dlugokencky, E.
    Yoshida, Y.
    Morino, I.
    Uchino, O.
    Yokota, T.
    SOLA, 2013, 9 : 45 - 50
  • [46] Erratum to: An improved constraint method in optimal estimation of CO2 from GOSAT SWIR observations
    MingMin Zou
    LiangFu Chen
    ShenShen Li
    Meng Fan
    JinHua Tao
    Ying Zhang
    Science China Earth Sciences, 2017, 60 : 2228 - 2228
  • [47] Erratum to: An improved constraint method in optimal estimation of CO2 from GOSAT SWIR observations
    ZOU MingMin
    CHEN LiangFu
    LI ShenShen
    FAN Meng
    TAO JinHua
    ZHANG Ying
    ScienceChina(EarthSciences), 2017, 60 (12) : 2228 - 2228
  • [48] On the impact of transport model errors for the estimation of CO2 surface fluxes from GOSAT observations
    Chevallier, Frederic
    Feng, Liang
    Boesch, Hartmut
    Palmer, Paul I.
    Rayner, Peter J.
    GEOPHYSICAL RESEARCH LETTERS, 2010, 37
  • [49] Temporal variations of atmospheric CO2 and CO at Ahmedabad in western India
    Chandra, Naveen
    Lal, Shyam
    Venkataramani, S.
    Patra, Prabir K.
    Sheel, Varun
    ATMOSPHERIC CHEMISTRY AND PHYSICS, 2016, 16 (10) : 6153 - 6173
  • [50] Temporal and spatial distribution of tropospheric CO2 over China based on satellite observations during 2003-2010
    Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center, China Meteorological Administration , Beijing 100081, China
    不详
    Int. Symp. Remote Sens. Environ. - GEOSS Era: Towards Oper. Environ. Monit.,