Data description paper
18 Sep 2019
Data description paper
| 18 Sep 2019
Global atmospheric carbon monoxide budget 2000–2017 inferred from multi-species atmospheric inversions
Bo Zheng et al.
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- A global land aerosol fine-mode fraction dataset (2001–2020) retrieved from MODIS using hybrid physical and deep learning approaches X. Yan et al. 10.5194/essd-14-1193-2022
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Latest update: 23 May 2022
Short summary
We use a multi-species atmospheric Bayesian inversion approach to attribute satellite-observed atmospheric carbon monoxide (CO) variations to its sources and sinks in order to achieve a full closure of the global CO budget during 2000–2017. We identify a declining trend in the global CO budget since 2000, driven by reduced anthropogenic emissions in the US, Europe, and China, as well as by reduced biomass burning emissions globally, especially in equatorial Africa.
We use a multi-species atmospheric Bayesian inversion approach to attribute satellite-observed...