Global daily CO2 emissions from 1970 to 2024

As extreme temperature events become increasingly frequent, there is a growing need for daily CO<sub>2</sub> emissions data to quantify their impacts. However, such data are available only from 2019 onward. To address this gap, we compiled over two million near-real-time observations of electricity generation, traffic activity, natural gas consumption or heating degree days (HDD), and industrial output since 2019, and used these high-frequency data to construct a daily CO<sub>2</sub> emissions dataset for 2019-2024. We then applied machine-learning models and degree-day methods to disaggregate non-residential and residential monthly CO<sub>2</sub> emissions for 1970-2018 to a daily basis. The historical dataset was then merged with the 2019-2024 dataset to produce a global daily CO<sub>2</sub> emissions dataset spanning 1970 to 2024 for 14 countries and regions, covering four sectors: power, industry, residential, and transport (including ground transport and aviation). The resulting long-term dataset will enable robust analyses of extreme-temperature impacts on emissions and enhance the accuracy of chemical transport model inversions of carbon fluxes.

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Publication Details

Journal
Scientific Data
Published
2026-02-24
DOI
https://doi.org/10.1038/s41597-026-06621-9
Primary Topic
Atmospheric and Environmental Gas Dynamics
Type
article
Field-Weighted Citation Impact
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article

Global daily CO2 emissions from 1970 to 2024

Taochun Sun, Piyu Ke, Glen P. Peters, Duo Cui et al.
Scientific Data
Atmospheric and Environmental Gas Dynamics
article

Global daily CO2 emissions from 1970 to 2024

Taochun Sun, Piyu Ke, Glen P. Peters, Duo Cui, Li Tao, Chenxi Lu, Hao Ye, Zihan Qiu, Lixing Wang, Zhu Deng, Glen P. Peters, Xiaoting Huang, Philippe Ciais, Matthew W. Jones, Robert B. Jackson, Zhu Liu, Yufei Zhao, Steven J. Davis, Pierre Friedlingstein
article en

Abstract

As extreme temperature events become increasingly frequent, there is a growing need for daily CO<sub>2</sub> emissions data to quantify their impacts. However, such data are available only from 2019 onward. To address this gap, we compiled over two million near-real-time observations of electricity generation, traffic activity, natural gas consumption or heating degree days (HDD), and industrial output since 2019, and used these high-frequency data to construct a daily CO<sub>2</sub> emissions dataset for 2019-2024. We then applied machine-learning models and degree-day methods to disaggregate non-residential and residential monthly CO<sub>2</sub> emissions for 1970-2018 to a daily basis. The historical dataset was then merged with the 2019-2024 dataset to produce a global daily CO<sub>2</sub> emissions dataset spanning 1970 to 2024 for 14 countries and regions, covering four sectors: power, industry, residential, and transport (including ground transport and aviation). The resulting long-term dataset will enable robust analyses of extreme-temperature impacts on emissions and enhance the accuracy of chemical transport model inversions of carbon fluxes.

Scientific Data
University of East Anglia (GB), Centre National de la Recherche Scientifique (FR), Université de Versailles Saint-Quentin-en-Yvelines (FR), University of Exeter (GB), Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR), Université Paris-Saclay (FR), Norwich Research Park (GB), Mercator Research Institute on Global Commons and Climate Change (DE), Education University of Hong Kong (HK), CICERO Center for International Climate Research (NO), Laboratoire des Sciences du Climat et de l'Environnement (FR), CEA Paris-Saclay (FR), Tyndall Centre (GB), China Agricultural University (CN), Zhejiang University (CN), University of Hong Kong (HK), Stanford University (US), Tsinghua University (CN)
Openalex Percentile: Top 53%
Atmospheric and Environmental Gas Dynamics
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