Articles | Volume 20, issue 19
https://doi.org/10.5194/acp-20-11371-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-20-11371-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
06 Oct 2020
Research article |
| 06 Oct 2020
| 06 Oct 2020
Evaluating China's fossil-fuel CO2 emissions from a comprehensive dataset of nine inventories
State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
Department of Atmospheric and Oceanic Science, and Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA
Tom Oda
Goddard Earth Sciences Research and Technology, Universities Space Research Association, Columbia, MD, USA
Xiaohui Lin
State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
Monica Crippa
European Commission, Joint Research Centre (JRC), Directorate for Energy, Transport and Climate, Air and Climate Unit, Ispra (VA), Italy
Dabo Guan
Department of Earth System Science, Tsinghua University, Beijing, China
Water Security Research Centre, School of International Development, University of East Anglia, Norwich, UK
Greet Janssens-Maenhout
European Commission, Joint Research Centre (JRC), Directorate for Energy, Transport and Climate, Air and Climate Unit, Ispra (VA), Italy
Xiaolin Ma
State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, China
Department of Earth System Science, Tsinghua University, Beijing, China
Tyndall Centre for Climate Change Research, School of International Development, University of East Anglia, Norwich, UK
Yuli Shan
Energy and Sustainability Research Institute Groningen, University of Groningen, Groningen 9747 AG, the Netherlands
Shu Tao
Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, China
Haikun Wang
State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, China
Rong Wang
Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, China
Department of Environmental Science and Engineering, Fudan University, Shanghai, China
Lin Wu
State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
Xiao Yun
Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, China
Qiang Zhang
Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, China
Fang Zhao
Key Laboratory of Geographic Information Science (Ministry of Education), School of Geographic Sciences, East China Normal University, Shanghai, China
Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, UMR8212, Gif-sur-Yvette, France
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39 citations as recorded by crossref.
- Evaluating Anthropogenic CO2 Bottom-Up Emission Inventories Using Satellite Observations from GOSAT and OCO-2 S. Zhang et al. 10.3390/rs14195024
- Atmospheric methane isotopes identify inventory knowledge gaps in the Surat Basin, Australia, coal seam gas and agricultural regions B. Kelly et al. 10.5194/acp-22-15527-2022
- A Novel Approach for Predicting Anthropogenic CO2 Emissions Using Machine Learning Based on Clustering of the CO2 Concentration Z. Ji et al. 10.3390/atmos15030323
- China’s Fossil Fuel CO2 Emissions Estimated Using Surface Observations of Coemitted NO2 S. Feng et al. 10.1021/acs.est.3c07756
- Assumptions about prior fossil fuel inventories impact our ability to estimate posterior net CO2 fluxes that are needed for verifying national inventories T. Oda et al. 10.1088/1748-9326/ad059b
- Detection of Chinese Spring Festival in Beijing using in-situ CO2 observations and atmospheric inversion Z. Liu et al. 10.1016/j.atmosenv.2024.120446
- Daily Emission Patterns of Coal-Fired Power Plants in China Based on Multisource Data Fusion N. Wu et al. 10.1021/acsenvironau.2c00014
- Predictability of fossil fuel CO2 from air quality emissions K. Miyazaki & K. Bowman 10.1038/s41467-023-37264-8
- Regional impacts of COVID-19 on carbon dioxide detected worldwide from space B. Weir et al. 10.1126/sciadv.abf9415
- Impact of Prior Terrestrial Carbon Fluxes on Simulations of Atmospheric CO2 Concentrations Y. Fu et al. 10.1029/2021JD034794
- Anthropogenic carbon dioxide origin tracing study in Anmyeon-do, South Korea: Based on STILT-footprint and emissions data J. Kim et al. 10.1016/j.scitotenv.2023.164677
- CDIAC-FF: global and national CO<sub>2</sub> emissions from fossil fuel combustion and cement manufacture: 1751–2017 D. Gilfillan & G. Marland 10.5194/essd-13-1667-2021
- Mapping the spatial-temporal changes in energy consumption-related carbon emissions in the Beijing-Tianjin-Hebei region via nighttime light data X. Zhang et al. 10.1016/j.scs.2023.104476
- City-level carbon emissions accounting and differentiation integrated nighttime light and city attributes Y. Zhou et al. 10.1016/j.resconrec.2022.106337
- Foreign direct investment, financial development, energy consumption, and air quality: A way for carbon neutrality in China Z. Tan et al. 10.1016/j.jenvman.2021.113572
- Aprotic phosphonium‐based ionic liquid as electrolyte for high CO2electroreduction to oxalate C. Jiang et al. 10.1002/aic.17859
- Revisiting the quantification of power plant CO2 emissions in the United States and China from satellite: A comparative study using three top-down approaches C. He et al. 10.1016/j.rse.2024.114192
- Assessment to China's Recent Emission Pattern Shifts Y. Guan et al. 10.1029/2021EF002241
- Estimation of Anthropogenic CH4 and CO2 Emissions in Taiyuan‐Jinzhong Region: One of the World's Largest Emission Hotspots C. Hu et al. 10.1029/2022JD037915
- Weaker regional carbon uptake albeit with stronger seasonal amplitude in northern mid-latitudes estimated by higher resolution GEOS-Chem model Z. Liu et al. 10.1016/j.scitotenv.2023.169477
- Proactive visual prediction auditing the green eco-safety through backcasting approach booster by grey recruitment priority conceptual framework A. Abed et al. 10.1016/j.heliyon.2022.e11729
- Extension of Japan’s Prefectural Emission Accounting and Enrichment of Socioeconomic Data from 1990 to 2020 Z. Chen et al. 10.1038/s41597-024-03316-x
- Anthropogenic CO2 emission reduction during the COVID-19 pandemic in Nanchang City, China C. Hu et al. 10.1016/j.envpol.2022.119767
- Cross-Inventory Uncertainty Analysis of Fossil Fuel CO2 Emissions for Prefecture-Level Cities in Shandong Province M. Tao et al. 10.3390/atmos13091474
- Characteristics of STILT footprints driven by KIM model simulated meteorological fields: implication for developing near real-time footprints S. Kenea et al. 10.1007/s44273-023-00016-7
- Quantifying the Impact of COVID‐19 Pandemic on the Spatiotemporal Changes of CO2 Concentrations in the Yangtze River Delta, China Y. Wang et al. 10.1029/2023JD038512
- An integrated view of correlated emissions of greenhouse gases and air pollutants in China X. Lin et al. 10.1186/s13021-023-00229-x
- Estimation of Atmospheric Fossil Fuel CO2 Traced by Δ14C: Current Status and Outlook M. Yu et al. 10.3390/atmos13122131
- The spatiotemporal evolution and impact mechanism of energy consumption carbon emissions in China from 2010 to 2020 by integrating multisource remote sensing data M. Wang et al. 10.1016/j.jenvman.2023.119054
- Spatial and Temporal Variations of Atmospheric CH4 in Monsoon Asia Detected by Satellite Observations of GOSAT and TROPOMI H. Song et al. 10.3390/rs15133389
- Mitigating geolocation errors in nighttime light satellite data and global CO2 emission gridded data V. Kinakh et al. 10.23939/mmc2021.02.304
- Green growth, sustainability, and decoupling carbon emissions from industrial activities in emerging economies: A focus on Zambia's energy sector C. Makondo 10.1016/j.exis.2023.101271
- Anthropogenic CO <sub>2</sub> Emission Reduction During the COVID-19 Pandemic: Evidence from Three Years of Urban Atmospheric Observations in Eastern China C. Hu et al. 10.2139/ssrn.3978864
- Challenges to achieve carbon neutrality of China by 2060: status and perspectives B. Chen et al. 10.1016/j.scib.2022.08.025
- Optimal design of surface CO2 observation network to constrain China’s land carbon sink Y. Wang et al. 10.1016/j.scib.2023.07.010
- Trade-off between vegetation CO2 sequestration and fossil fuel-related CO2 emissions: A case study of the Guangdong–Hong Kong–Macao Greater Bay Area of China Z. Luo et al. 10.1016/j.scs.2021.103195
- Assessing uncertainties and discrepancies in agricultural greenhouse gas emissions estimation in China: A comprehensive review H. Li et al. 10.1016/j.eiar.2024.107498
- Contributions of China's terrestrial ecosystem carbon uptakes to offsetting CO2 emissions under different scenarios over 2001–2060 M. Xu et al. 10.1016/j.gloplacha.2024.104485
- Land Zoning Management to Achieve Carbon Neutrality: A Case Study of the Beijing–Tianjin–Hebei Urban Agglomeration, China G. Liu & F. Zhang 10.3390/land11040551
Latest update: 29 Jun 2024
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...
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