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Carbon Monitor, a near-real-time daily dataset of global CO 2 emission from fossil fuel and cement production.

Authors :
Liu Z
Ciais P
Deng Z
Davis SJ
Zheng B
Wang Y
Cui D
Zhu B
Dou X
Ke P
Sun T
Guo R
Zhong H
Boucher O
Bréon FM
Lu C
Guo R
Xue J
Boucher E
Tanaka K
Chevallier F
Source :
Scientific data [Sci Data] 2020 Nov 09; Vol. 7 (1), pp. 392. Date of Electronic Publication: 2020 Nov 09.
Publication Year :
2020

Abstract

We constructed a near-real-time daily CO <subscript>2</subscript> emission dataset, the Carbon Monitor, to monitor the variations in CO <subscript>2</subscript> emissions from fossil fuel combustion and cement production since January 1, 2019, at the national level, with near-global coverage on a daily basis and the potential to be frequently updated. Daily CO <subscript>2</subscript> emissions are estimated from a diverse range of activity data, including the hourly to daily electrical power generation data of 31 countries, monthly production data and production indices of industry processes of 62 countries/regions, and daily mobility data and mobility indices for the ground transportation of 416 cities worldwide. Individual flight location data and monthly data were utilized for aviation and maritime transportation sector estimates. In addition, monthly fuel consumption data corrected for the daily air temperature of 206 countries were used to estimate the emissions from commercial and residential buildings. This Carbon Monitor dataset manifests the dynamic nature of CO <subscript>2</subscript> emissions through daily, weekly and seasonal variations as influenced by workdays and holidays, as well as by the unfolding impacts of the COVID-19 pandemic. The Carbon Monitor near-real-time CO <subscript>2</subscript> emission dataset shows a 8.8% decline in CO <subscript>2</subscript> emissions globally from January 1 <superscript>st</superscript> to June 30 <superscript>th</superscript> in 2020 when compared with the same period in 2019 and detects a regrowth of CO <subscript>2</subscript> emissions by late April, which is mainly attributed to the recovery of economic activities in China and a partial easing of lockdowns in other countries. This daily updated CO <subscript>2</subscript> emission dataset could offer a range of opportunities for related scientific research and policy making.

Details

Language :
English
ISSN :
2052-4463
Volume :
7
Issue :
1
Database :
MEDLINE
Journal :
Scientific data
Publication Type :
Academic Journal
Accession number :
33168822
Full Text :
https://doi.org/10.1038/s41597-020-00708-7