Near-real-time global gridded daily CO2 emissions

被引:66
作者
Dou, Xinyu [1 ]
Wang, Yilong [2 ]
Ciais, Philippe [3 ]
Chevallier, Frederic [3 ]
Davis, Steven J. [4 ]
Crippa, Monica [5 ]
Janssens-Maenhout, Greet [5 ]
Guizzardi, Diego [5 ]
Solazzo, Efisio [5 ]
Yan, Feifan [6 ,7 ]
Huo, Da [1 ]
Zheng, Bo [8 ]
Zhu, Biqing [1 ]
Cui, Duo [1 ]
Ke, Piyu [1 ]
Sun, Taochun [1 ]
Wang, Hengqi [1 ]
Zhang, Qiang [1 ]
Gentine, Pierre [9 ]
Deng, Zhu [1 ]
Liu, Zhu [1 ]
机构
[1] Tsinghua Univ, Dept Earth Syst Sci, Beijing 100084, Peoples R China
[2] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China
[3] Univ Paris Saclay, Lab Sci Climat & Environm, LSCE IPSL, CEA CNRS UVSQ, Gif Sur Yvette, France
[4] Univ Calif Irvine, Dept Earth Syst Sci, Irvine, CA USA
[5] European Commiss, Joint Res Ctr JRC, Ispra, Italy
[6] Ocean Univ China, Key Lab Marine Environm & Ecol, Minist Educ, Qingdao 266100, Peoples R China
[7] Ocean Univ China, Frontiers Sci Ctr Deep Ocean Multispheres & Earth, Minist Educ, Qingdao 266100, Peoples R China
[8] Tsinghua Univ, Tsinghua Shenzhen Int Grad Sch, Inst Environm & Ecol, Shenzhen 518055, Peoples R China
[9] Columbia Univ, Dept Earth & Environm Engn, New York, NY USA
来源
INNOVATION | 2022年 / 3卷 / 01期
基金
中国国家自然科学基金; 北京市自然科学基金;
关键词
INVENTORY; TRANSPORT; INDUSTRY; DATABASE; CHINA;
D O I
10.1016/j.xinn.2021.100182
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Precise and high-resolution carbon dioxide (CO2) emission data is of great importance in achieving carbon neutrality around the world. Here we present for the first time the near-real-time Global Gridded Daily CO2 Emissions Dataset (GRACED) from fossil fuel and cement production with a global spatial resolution of 0.1 degrees by 0.1 degrees and a temporal resolution of 1 day. Gridded fossil emissions are computed for different sectors based on the daily national CO2 emissions from near-real-time dataset (Carbon Monitor), the spatial patterns of point source emission dataset Global Energy Infrastructure Emissions Database (GID), Emission Database for Global Atmospheric Research (EDGAR), and spatiotemporal patters of satellite nitrogen dioxide (NO2) retrievals. Our study on the global CO2 emissions responds to the growing and urgent need for high-quality, fine-grained, near-real-time CO2 emissions estimates to support global emissions monitoring across various spatial scales. Weshow the spatial patterns of emission changes for power, industry, residential consumption, ground transportation, domestic and international aviation, and international shipping sectors from January 1, 2019, to December 31, 2020. This gives thorough insights into the relative contributions from each sector. Furthermore, it provides the most up-to-date and fine-grained overview of where and when fossil CO2 emissions have decreased and rebounded in response to emergencies (e.g., coronavirus disease 2019 [COVID-19]) and other disturbances of human activities of any previously published dataset. As the world recovers from the pandemic and decarbonizes its energy systems, regular updates of this dataset will enable policymakers to more closely monitor the effectiveness of climate and energy policies and quickly adapt.
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页数:8
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