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. 2021 Nov 2;3(1):100182.
doi: 10.1016/j.xinn.2021.100182. eCollection 2022 Jan 25.

Near-real-time global gridded daily CO2 emissions

Xinyu Dou  1 , Yilong Wang  2 , Philippe Ciais  3 , Frédéric Chevallier  3 , Steven J Davis  4 , Monica Crippa  5 , Greet Janssens-Maenhout  5 , Diego Guizzardi  5 , Efisio Solazzo  5 , Feifan Yan  6 , Da Huo  1 , Bo Zheng  7 , Biqing Zhu  1 , Duo Cui  1 , Piyu Ke  1 , Taochun Sun  1 , Hengqi Wang  1 , Qiang Zhang  1 , Pierre Gentine  8 , Zhu Deng  1 , Zhu Liu  1
Affiliations

Near-real-time global gridded daily CO2 emissions

Xinyu Dou et al. Innovation (Camb). .

Abstract

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° by 0.1° 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. We show 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.

Keywords: 2020; daily; global change; gridded CO2 emission; near real time.

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Conflict of interest statement

The authors declare no competing interests.

Figures

None
Graphical abstract
Figure 1
Figure 1
The fossil fuel and cement CO2 emissions distributions of GRACED in 2020 The value is given in the unit of kilograms of carbon per day per cell
Figure 2
Figure 2
Map of weekend minus weekday emissions in 2020
Figure 3
Figure 3
Difference in daily average CO2 emissions between 2020 and 2019 (2020 minus 2019)
Figure 4
Figure 4
The day of the year with the biggest change in 2020 compared with 2019 (A and B) The day of the year with (A) the maximum reduction, and (B) the maximum rebound of each grid in 2020 compared with 2019.
Figure 5
Figure 5
Sector share of CO2 emissions and its difference between 2020 and 2019 (A–G) Sector share of CO2 emissions in 2020 (A–G). (H–N) Difference in sector share of CO2 emissions between 2020 and 2019 (2020 minus 2019) (H–N).
Figure 6
Figure 6
The framework of top-down spatially gridding methodology
See this image and copyright information in PMC

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