Advertisement

Specific patterns of XCO2 observed by GOSAT during 2009–2016 and assessed with model simulations over China

  • Nian Bie
  • Liping LeiEmail author
  • Zhonghua He
  • Zhaocheng Zeng
  • Liangyun Liu
  • Bing Zhang
  • Bofeng Cai
Research Paper

Abstract

Spatiotemporal patterns of column-averaged dry air mole fraction of CO2 (XCO2) have not been well characterized on a regional scale due to limitations in data availability and precision. This paper addresses these issues by examining such patterns in China using the long-term mapping XCO2 dataset (2009–2016) derived from the Greenhouse gases Observing SATellite (GOSAT). XCO2 simulations are also constructed using the high-resolution nested-grid GEOS-Chem model. The following results are found: Firstly, the correlation coefficient between the anthropogenic emissions and XCO2 spatial distribution is nearly zero in summer but up to 0.32 in autumn. Secondly, on average, XCO2 increases by 2.08 ppm every year from 2010 to 2015, with a sharp increase of 2.6 ppm in 2013. Lastly, in the analysis of three typical regions, the GOSAT XCO2 time series is in better agreement with the GEOS-Chem simulation of XCO2 in the Taklimakan Desert region (the least difference with bias 0.65±0.78 ppm), compared with the northern urban agglomeration region (−1.3±1.2 ppm) and the northeastern forest region (−1.4±1.4 ppm). The results are likely attributable to uncertainty in both the satellite-retrieved XCO2 data and the model simulation data.

Keywords

GEOS-Chem GOSAT OCO-2 Specific pattern XCO2 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Notes

Acknowledgements

ACOS v7.3 were produced by the ACOS/OCO-2 project at the Jet Propulsion Laboratory, California Institute of Technology, and obtained from the JPL website co2.jpl.nasa.gov. We are grateful for NASA, ACOS/OCO-2 project, NIES GOSAT Project and geos-chem team. This research was supported by the National Key Research and Development Program of China (Grant No. 2016YFA0600303) and the Key Deployment Projects of the Chinese Academy of Sciences (Grant No. ZDRW-ZS-2019-1-3).

References

  1. Bie N, Lei L, He Z, Liu M. 2016. An analysis of atmospheric CO2 concentration around the takelamagan desert with five products retrieved from satellite observations. Beijing: International Geoscience and Remote Sensing Symposium. 4087–4089Google Scholar
  2. Bie N, Lei L, Zeng Z C, Cai B, Yang S, He Z, Wu C, Nassar R. 2018. Regional uncertainty of GOSAT XCO2 retrievals in China: Quantification and attribution. Atmos Meas Tech, 11: 1251–1272CrossRefGoogle Scholar
  3. Bovensmann H, Buchwitz M, Burrows J P, Reuter M, Krings T, Gerilowski K, Schneising O, Heymann J, Tretner A, Erzinger J. 2010. A remote sensing technique for global monitoring of power plant CO2 emissions from space and related applications. Atmos Meas Tech, 3: 781–811CrossRefGoogle Scholar
  4. Buchwitz M, Reuter M, Schneising O, Boesch H, Guerlet S, Dils B, Aben I, Armante R, Bergamaschi P, Blumenstock T, Bovensmann H, Brunner D, Buchmann B, Burrows J P, Butz A, Chédin A, Chevallier F, Crevoisier C D, Deutscher N M, Frankenberg C, Hase F, Hasekamp O P, Heymann J, Kaminski T, Laeng A, Lichtenberg G, De Mazière M, Noël S, Notholt J, Orphal J, Popp C, Parker R, Scholze M, Sussmann R, Stiller G P, Warneke T, Zehner C, Bril A, Crisp D, Griffith D W T, Kuze A, O’Dell C, Oshchepkov S, Sherlock V, Suto H, Wennberg P, Wunch D, Yokota T, Yoshida Y. 2015. The greenhouse gas climate change initiative (GHG-CCI): Comparison and quality assessment of near-surface-sensitive satellite-derived CO2 and CH4 global data sets. Remote Sens Environ, 162: 344–362CrossRefGoogle Scholar
  5. Cai B, Zhang L. 2014. Urban CO2 emissions in China: Spatial boundary and performance comparison. Energy Policy, 66: 557–567CrossRefGoogle Scholar
  6. 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, 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. J Geophys Res, 117: D21301CrossRefGoogle Scholar
  7. Connor B J, Boesch H, Toon G, Sen B, Miller C, Crisp D. 2008. Orbiting carbon observatory: Inverse method and prospective error analysis. J Geophys Res, 113: D05305CrossRefGoogle Scholar
  8. Crisp D, Fisher B M, O’Dell C, Frankenberg C, Basilio R, Bösch H, Brown L R, Castano R, Connor B, Deutscher N M, Eldering A, Griffith D, Gunson M, Kuze A, Mandrake L, McDuffie J, Messerschmidt J, Miller C E, Morino I, Natraj V, Notholt J, O’Brien D M, Oyafuso F, Polonsky I, Robinson J, Salawitch R, Sherlock V, Smyth M, Suto H, Taylor T E, Thompson D R, Wennberg P O, Wunch D, Yung Y L. 2012. The ACOS CO2 retrieval algorithm—Part II: Global XCO2 data characterization. Atmos Meas Tech, 5: 687–707CrossRefGoogle Scholar
  9. Guo L, Lei L, Zeng Z, Zou P, Liu D, Zhang B. 2015. Evaluation of spatio-temporal variogram models for mapping XCO2 using satellite observations: A case study in China. IEEE J-STARS, 8: 376–385Google Scholar
  10. He Z, Zeng Z C, Lei L, Bie N, Yang S. 2017. A data-driven assessment of biosphere-atmosphere interaction impact on seasonal cycle patterns of XCO2 using GOSAT and MODIS observations. Remote Sens, 9: 251CrossRefGoogle Scholar
  11. Ingmann P, Veihelmann B, Langen J, Lamarre D, Stark H, Courrèges-Lacoste G B. 2012. Requirements for the GMES atmosphere service and ESA’s implementation concept: Sentinels-4/-5 and -5p. Remote Sens Environ, 120: 58–69CrossRefGoogle Scholar
  12. Janardanan R, Maksyutov S, Oda T, Saito M, Kaiser J W, Ganshin A, Stohl A, Matsunaga T, Yoshida Y, Yokota T. 2016. Comparing GOSAT observations of localized CO2 enhancements by large emitters with inventory-based estimates. Geophys Res Lett, 43: 3486–3493CrossRefGoogle Scholar
  13. Keeling C D, Bacastow R B, Bainbridge A E, Ekdahl Jr C A, Guenther P R, Waterman L S, Chin J F S. 1976. Atmospheric carbon dioxide variations at Mauna Loa Observatory, Hawaii. Tellus, 28: 538–551Google Scholar
  14. Keller C A, Long M S, Yantosca R M, Da Silva A M, Pawson S, Jacob D J. 2014. HEMCO v1.0: A versatile, ESMF-compliant component for calculating emissions in atmospheric models. Geosci Model Dev, 7: 1409–1417CrossRefGoogle Scholar
  15. Keppel-Aleks G, Wennberg P O, O’Dell C W, Wunch D. 2013. Towards constraints on fossil fuel emissions from total column carbon dioxide. Atmos Chem Phys, 13: 4349–4357CrossRefGoogle Scholar
  16. Kulawik S, Wunch D, O’Dell C, Frankenberg C, Reuter M, Oda T, Chevallier F, Sherlock V, Buchwitz M, Osterman G, Miller C E, Wennberg P O, Griffith D, Morino I, Dubey M K, Deutscher N M, Notholt J, Hase F, Warneke T, Sussmann R, Robinson J, Strong K, Schneider M, De Mazière M, Shiomi K, Feist D G, Iraci L T, Wolf J. 2016. Consistent evaluation of ACOS-GOSAT, BESD-SCIAMACHY, CarbonTracker, and MACC through comparisons to TCCON. Atmos Meas Tech, 9: 683–709CrossRefGoogle Scholar
  17. Le Quéré C, Moriarty R, Andrew R M, Peters G P, Ciais P, Friedlingstein P, Jones S D, Sitch S, Tans P, Arneth A, Boden T A, Bopp L, Bozec Y, Canadell J G, Chini L P, Chevallier F, Cosca C E, Harris I, Hoppema M, Houghton R A, House J I, Jain A K, Johannessen T, Kato E, Keeling R F, Kitidis V, Goldewijk K K, Koven C, Landa C S, Landschützer P, Lenton A, Lima I D, Marland G, Mathis J T, Metzl N, Nojiri Y, Olsen A, Ono T, Peng S, Peters W, Pfeil B, Poulter B, Raupach M R, Regnier P, Rödenbeck C, Saito S, Salisbury J E, Schuster U, Schwinger J, Séférian R, Segschneider J, Steinhoff T, Stocker B D, Sutton A J, Takahashi T, Tilbrook B, van der Werf G R, Viovy N, Wang Y P, Wanninkhof R, Wiltshire A, Zeng N. 2015. Global carbon budget 2014. Earth Syst Sci Data, 7: 47–85CrossRefGoogle Scholar
  18. 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, Woodward F I. 2009. Trends in the sources and sinks of carbon dioxide. Nat Geosci, 2: 831–836CrossRefGoogle Scholar
  19. Lei L P, Guan X H, Zeng Z C, Zhang B, Ru F, Bu R. 2014. A comparison of atmospheric CO2 concentration GOSAT-based observations and model simulations. Sci China Earth Sci, 57: 1393–1402CrossRefGoogle Scholar
  20. Lindqvist H, O’Dell C W, Basu S, Boesch H, Chevallier F, Deutscher N, Feng L, Fisher B, Hase F, Inoue M, Kivi R, Morino I, Palmer P I, Parker R, Schneider M, Sussmann R, Yoshida Y. 2015. Does GOSAT capture the true seasonal cycle of carbon dioxide? Atmos Chem Phys, 15: 13023–13040CrossRefGoogle Scholar
  21. Liu D, Lei L, Guo L, Zeng Z C. 2015. A cluster of CO2 change characteristics with GOSAT observations for viewing the spatial pattern of CO2 emission and absorption. Atmosphere, 6: 1695–1713CrossRefGoogle Scholar
  22. Nassar R, Jones D B A, Suntharalingam P, Chen J M, Andres R J, Wecht K J, Yantosca R M, Kulawik S S, Bowman K W, Worden J R, Machida T, Matsueda H. 2010. Modeling global atmospheric CO2 with improved emission inventories and CO2 production from the oxidation of other carbon species. Geosci Model Dev, 3: 689–716CrossRefGoogle Scholar
  23. O’Dell C W, Connor B, Bösch H, O’Brien D, Frankenberg C, Castano R, Christi M, Eldering D, Fisher B, Gunson M, McDuffie J, Miller C E, Natraj V, Oyafuso F, Polonsky I, Smyth M, Taylor T, Toon G C, Wennberg P O, Wunch D. 2012. The ACOS CO2 retrieval algorithm—Part 1: Description and validation against synthetic observations. Atmos Meas Tech, 5: 99–121CrossRefGoogle Scholar
  24. Rawlins M A, McGuire A D, Kimball J S, Dass P, Lawrence D, Burke E, Chen X, Delire C, Koven C, MacDougall A, Peng S, Rinke A, Saito K, Zhang W, Alkama R, Bohn T J, Ciais P, Decharme B, Gouttevin I, Hajima T, Ji D, Krinner G, Lettenmaier D P, Miller P, Moore J C, Smith B, Sueyoshi T. 2015. Assessment of model estimates of land-atmosphere CO2 exchange across Northern Eurasia. Biogeosciences, 12: 4385–4405CrossRefGoogle Scholar
  25. Reuter M, Buchwitz M, Hilker M, Heymann J, Schneising O, Pillai D, Bovensmann H, Burrows J P, Bösch H, Parker R, Butz A, Hasekamp O, O’Dell C W, Yoshida Y, Gerbig C, Nehrkorn T, Deutscher N M, Warneke T, Notholt J, Hase F, Kivi R, Sussmann R, Machida T, Matsueda H, Sawa Y. 2014. Satellite-inferred European carbon sink larger than expected. Atmos Chem Phys, 14: 13739–13753CrossRefGoogle Scholar
  26. Thoning K W, Tans P P, Komhyr W D. 1989. Atmospheric carbon dioxide at Mauna Loa Observatory: 2. Analysis of the NOAA GMCC data, 1974–1985. J Geophys Res, 94: 8549–8565CrossRefGoogle Scholar
  27. Wang J, Cai B, Zhang L, Cao D, Liu L, Zhou Y, Zhang Z, Xue W. 2014. High resolution carbon dioxide emission gridded data for China derived from point sources. Environ Sci Technol, 48: 7085–7093CrossRefGoogle Scholar
  28. Wang W, Tian Y, Liu C, Sun Y, Liu W, Xie P, Liu J, Xu J, Morino I, Velazco V A, Griffith D W T, Notholt J, Warneke T. 2017. Investigating the performance of a greenhouse gas observatory in Hefei, China. Atmos Meas Tech, 10: 2627–2643CrossRefGoogle Scholar
  29. Wang X, Zhang X, Zhang L, Gao L, Tian L. 2015. Interpreting seasonal changes of low-tropospheric CO2 over China based on SCIAMACHY observations during 2003–2011. Atmos Environ, 103: 180–187CrossRefGoogle Scholar
  30. Wunch D, Wennberg P O, Messerschmidt J, Parazoo N C, Toon G C, Deutscher N M, Keppel-Aleks G, Roehl C M, Randerson J T, Warneke T, Notholt J. 2013. The covariation of Northern Hemisphere summertime CO2 with surface temperature in boreal regions. Atmos Chem Phys, 13: 9447–9459CrossRefGoogle Scholar
  31. Wunch D, Wennberg P O, Toon G C, Connor B J, Fisher B, Osterman G B, Frankenberg C, Mandrake L, O’Dell C, Ahonen P, Biraud S C, Castano R, Cressie N, Crisp D, Deutscher N M, Eldering A, Fisher M L, Griffith D W T, Gunson M, Heikkinen P, Keppel-Aleks G, Kyrö E, Lindenmaier R, Macatangay R, Mendonca J, Messerschmidt J, Miller C E, Morino I, Notholt J, Oyafuso F A, Rettinger M, Robinson J, Roehl C M, Salawitch R J, Sherlock V, Strong K, Sussmann R, Tanaka T, Thompson D R, Uchino O, Warneke T, Wofsy S C. 2011. A method for evaluating bias in global measurements of CO2 total columns from space. Atmos Chem Phys, 11: 12317–12337CrossRefGoogle Scholar
  32. Zeng Z, Lei L, Hou S, Ru F, Guan X, Zhang B. 2014. A Regional Gap-Filling Method Based on Spatiotemporal Variogram Model of CO2 Columns. IEEE Trans Geosci Remote Sens, 52: 3594–3603CrossRefGoogle Scholar
  33. Zeng Z C, Lei L, Strong K, Jones D B A, Guo L, Liu M, Deng F, Deutscher N M, Dubey M K, Griffith D W T, Hase F, Henderson B, Kivi R, Lindenmaier R, Morino I, Notholt J, Ohyama H, Petri C, Sussmann R, Velazco V A, Wennberg P O, Lin H. 2017. Global land mapping of satellite-observed CO2 total columns using spatio-temporal geostatistics. Int J Digital Earth, 10: 426–456CrossRefGoogle Scholar

Copyright information

© Science China Press and Springer-Verlag GmbH Germany, part of Springer Nature 2020

Authors and Affiliations

  • Nian Bie
    • 1
    • 2
  • Liping Lei
    • 1
    Email author
  • Zhonghua He
    • 1
    • 2
  • Zhaocheng Zeng
    • 3
  • Liangyun Liu
    • 1
  • Bing Zhang
    • 1
  • Bofeng Cai
    • 4
  1. 1.Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital EarthChinese Academy of SciencesBeijingChina
  2. 2.University of Chinese Academy of SciencesBeijingChina
  3. 3.Division of Geological and Planetary SciencesCalifornia Institute of TechnologyPasadenaUSA
  4. 4.The Center for Climate Change and Environmental PolicyChinese Academy for Environmental Planning, Ministry of Environmental ProtectionBeijingChina

Personalised recommendations