Journal cover Journal topic
Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 5.668 IF 5.668
  • IF 5-year value: 6.201 IF 5-year
    6.201
  • CiteScore value: 6.13 CiteScore
    6.13
  • SNIP value: 1.633 SNIP 1.633
  • IPP value: 5.91 IPP 5.91
  • SJR value: 2.938 SJR 2.938
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 174 Scimago H
    index 174
  • h5-index value: 87 h5-index 87
Discussion papers
https://doi.org/10.5194/acp-2019-643
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-2019-643
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 06 Jan 2020

Submitted as: research article | 06 Jan 2020

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Chemistry and Physics (ACP).

Evaluating China's fossil-fuel CO2 emissions from a comprehensive dataset of nine inventories

Pengfei Han1, Ning Zeng2, Tom Oda3, Xiaohui Lin4, Monica Crippa5, Dabo Guan6,7, Greet Janssens-Maenhout5, Xiaolin Ma8, Zhu Liu6,9, Yuli Shan10, Shu Tao11, Haikun Wang8, Rong Wang11,12, Lin Wu4, Xiao Yun11, Qiang Zhang13, Fang Zhao14, and Bo Zheng15 Pengfei Han et al.
  • 1State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
  • 2Department of Atmospheric and Oceanic Science, and Earth System Science Interdisciplinary Center, University of Maryland, College Park, Maryland, USA
  • 3Goddard Earth Sciences Research and Technology, Universities Space Research Association, Columbia, MD, USA
  • 4State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
  • 5European Commission, Joint Research Centre (JRC), Directorate for Energy, Transport and Climate, Air and Climate Unit, Ispra (VA), Italy
  • 6Department of Earth System Science, Tsinghua University, Beijing, China
  • 7Water Security Research Centre, School of International Development, University of East Anglia, Norwich, UK
  • 8State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, China
  • 9Tyndall Centre for Climate Change Research, School of International Development, University of East Anglia, Norwich, UK
  • 10Energy and Sustainability Research Institute Groningen, University of Groningen, Groningen 9747 AG, the Netherlands
  • 11Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, China
  • 12Department of Environmental Science and Engineering, Fudan University, Shanghai, China
  • 13Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, China
  • 14Key Laboratory of Geographic Information Science (Ministry of Education), School of Geographic Sciences, East China Normal University, Shanghai, China
  • 15Laboratoire des Sciences du Climat et de l’Environnement, CEA-CNRS-UVSQ, UMR8212,Gif-sur-Yvette, France

Abstract. China's fossil-fuel CO2 emissions (FFCO2) account for 28 % of the global total FFCO2 in 2016. An accurate estimate of China’s FFCO2 is a prerequisite for global and regional carbon budget analyses and monitoring of carbon emission reduction efforts. However, large uncertainties and discrepancies exist in China’s FFCO2 estimations due to lack of detailed traceable emission factors and multiple statistical data sources. Here, we evaluated China's FFCO2 emissions from 9 published global and regional emission datasets. These datasets show that the total emission increased from 3.4 (3.0–3.7) in 2000 to 9.8 (9.2–10.4) Gt CO2 yr−1 in 2016. The variations in their estimates were due largely to the different emission factors (0.491–0.746 for coal) and activity data. The large-scale patterns of gridded emissions showed a reasonable agreement with high emissions concentrated in major city clusters, and the standard deviation mostly ranged 10–40 % at provincial level. However, patterns beyond the provincial scale vary greatly with the top 5 % of grid-level account for 50–90 % of total emissions for these datasets. Our findings highlight the significance of using locally-measured EF for the Chinese coals. To reduce the uncertainty, we call on the enhancement of physical CO2 measurements and use them for datasets validation, key input data sharing (e.g. point sources) and finer resolution validations at various levels.

Pengfei Han et al.
Interactive discussion
Status: open (until 02 Mar 2020)
Status: open (until 02 Mar 2020)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
[Subscribe to comment alert] Printer-friendly Version - Printer-friendly version Supplement - Supplement
Pengfei Han et al.
Pengfei Han et al.
Viewed  
Total article views: 203 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
155 46 2 203 15 3 2
  • HTML: 155
  • PDF: 46
  • XML: 2
  • Total: 203
  • Supplement: 15
  • BibTeX: 3
  • EndNote: 2
Views and downloads (calculated since 06 Jan 2020)
Cumulative views and downloads (calculated since 06 Jan 2020)
Viewed (geographical distribution)  
Total article views: 151 (including HTML, PDF, and XML) Thereof 151 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Cited  
Saved  
No saved metrics found.
Discussed  
No discussed metrics found.
Latest update: 24 Jan 2020
Publications Copernicus
Download
Short summary
An accurate estimation of China’s fossil-fuel CO2 emissions (FFCO2) is significant for quantification of carbon budget and emissions reductions towards the Paris Agreement goals. Here we assessed 9 global and regional inventories. Our findings highlight the significance of using locally-measured coal emission factors. We call on the enhancement of physical measurements for validation and provide comprehensive information for inventory, monitoring, modeling, assimilation and reducing emissions.
An accurate estimation of China’s fossil-fuel CO2 emissions (FFCO2) is significant for...
Citation