A regression-based approach to the CO2 airborne fraction

Mikkel Bennedsen; Eric Hillebrand; Siem Jan Koopman

doi:10.1038/s41467-024-52728-1

A regression-based approach to the CO₂ airborne fraction

Mikkel Bennedsen^*, Eric Hillebrand, Siem Jan Koopman

^*Corresponding author for this work

Department of Economics and Business Economics

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review

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Abstract

The global fraction of anthropogenically emitted carbon dioxide (CO₂) that stays in the atmosphere, the CO₂ airborne fraction, has been fluctuating around a constant value over the period 1959 to 2022. The consensus estimate of the airborne fraction is around 44%. In this study, we show that the conventional estimator of the airborne fraction, based on a ratio of changes in atmospheric CO₂ concentrations and CO₂ emissions, suffers from a number of statistical deficiencies. We propose an alternative regression-based estimator of the airborne fraction that does not suffer from these deficiencies. Our empirical analysis leads to an estimate of the airborne fraction over 1959–2022 of 47.0% (± 1.1%; 1σ), implying a higher, and better constrained, estimate than the current consensus. Using climate model output, we show that a regression-based approach provides sensible estimates of the airborne fraction, also in future scenarios where emissions are at or near zero.

Original language	English
Article number	8507
Journal	Nature Communications
Volume	15
Issue	1
Number of pages	9
ISSN	2041-1723
DOIs	https://doi.org/10.1038/s41467-024-52728-1
Publication status	Published - Dec 2024

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abstract = "The global fraction of anthropogenically emitted carbon dioxide (CO2) that stays in the atmosphere, the CO2 airborne fraction, has been fluctuating around a constant value over the period 1959 to 2022. The consensus estimate of the airborne fraction is around 44%. In this study, we show that the conventional estimator of the airborne fraction, based on a ratio of changes in atmospheric CO2 concentrations and CO2 emissions, suffers from a number of statistical deficiencies. We propose an alternative regression-based estimator of the airborne fraction that does not suffer from these deficiencies. Our empirical analysis leads to an estimate of the airborne fraction over 1959–2022 of 47.0% (± 1.1%; 1σ), implying a higher, and better constrained, estimate than the current consensus. Using climate model output, we show that a regression-based approach provides sensible estimates of the airborne fraction, also in future scenarios where emissions are at or near zero.",

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A regression-based approach to the CO₂ airborne fraction

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