The gigatonne gap in China’s carbon dioxide inventories

Journal name:
Nature Climate Change
Year published:
Published online
Corrected online

Reliable national statistics are fundamental for climate change science as well as for global negotiations about future emission targets and the allocation of responsibilities. China, the world’s top CO2 emitter1, 2, has frequently been questioned about its data transparency and accuracy of energy and emission statistics 3, 4, 5, 6, 7. China implemented a top-down statistical system where energy statistics are compiled under the aegis of the National Bureau of Statistics (NBS) at the central government level, which oversees and coordinates the corresponding statistical departments at provincial and county levels8. The NBS publishes annually both national and provincial energy statistics. We compile the CO2 emission inventories for China and its 30 provinces for the period 1997–2010. However, CO2 emissions calculated on the basis of the two publicly available official energy data sets differ by 1.4 gigatonnes for 2010. The figure is equivalent to Japan’s annual CO2 emissions, the world’s fourth largest emitter, with 5% of the global total. Differences in reported coal consumption in coal washing and manufacturing are the main contributors to the discrepancy in official energy statistics. This paper presents an initial step to share and validate data and discuss methodologies in full transparency towards better energy and emission data for China.

At a glance


  1. The sources of China/'s CO2 emissions by fuel type during 1997-2010.
    Figure 1: The sources of China’s CO2 emissions by fuel type during 1997–2010.

    The area chart (left) illustrates the increase of CO2 emissions calculated from the national energy statistics since 1997 broken down by different fuel type. Other fuels include, for example, coke oven gas, other gas, other coking products, LPG, refinery gas and other petroleum products. The dashed line represents the aggregated CO2 emissions calculated from the provincial energy statistics 1997–2010. The column chart (right) presents the 1.4Gt emission gap in 2010 between national and provincial statistics and the pattern of different fuel types in contributing to the emission gap. For data sources, see refs 9, 24.

  2. Comparison of China/'s emission and energy statistics.
    Figure 2: Comparison of China’s emission and energy statistics.

    For data sources, see Supplementary Section S4. The starting point of all bars is ‘0’. National total and provincial summation CO2 emissions are estimated by the authors (see Methods). We select raw coal, crude oil and natural gas to illustrate the differences in China’s energy statistics. Each energy type includes the final energy consumption and energy for transformation. There are different representations of the total CO2 emissions from international statistical sources, but their emission accounting approaches are different (the full data set and explanations of data sources are available at Supplementary Section S4). The pie charts and associated percentages on the right side of the figure explain the energy consumption sectors contributing to the discrepancy in raw coal consumption between provincial and national statistics in 2010. The total gap of 747Mt was mainly caused by energy transformation and loss (56%) and final consumption sectors (44%).

  3. Comparison of industrial outputs in physical units between China/'s national and provincial statistics in 2010.
    Figure 3: Comparison of industrial outputs in physical units between China’s national and provincial statistics in 2010.

    A positive percentage shows how much larger the provincial statistics are compared with the national statistics. Data set and data source explanation is available in Supplementary Table S2.1.

Change history

Corrected online 14 June 2012
In the version of this Letter originally published online, the affiliation for Dabo Guan, Zhu Liu and Yong Geng was incorrect. This has been corrected in all versions of the Letter.


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Author information


  1. Key Laboratory of Pollution Ecology and Environmental Engineering, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China

    • Dabo Guan,
    • Zhu Liu &
    • Yong Geng
  2. School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, UK

    • Dabo Guan
  3. St Edmund’s College, University of Cambridge, Cambridge, CB3 0BN, UK

    • Dabo Guan
  4. Graduate University of Chinese Academy of Sciences, Beijing, 100049, China

    • Zhu Liu
  5. Department of Land Economy, University of Cambridge, Cambridge, CB3 9EP, UK

    • Sören Lindner
  6. Department of Geographical Sciences, University of Maryland, College Park, Maryland 20742, USA

    • Klaus Hubacek


D.G. and Z.L. designed the research; Z.L., S.L. and D.G. compiled the data; D.G. and Z.L. performed initial analysis; all authors contributed to the results’ interpretations and writing.

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The authors declare no competing financial interests.

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