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A regression-based approach to the CO₂ airborne fraction

Environmental Studies and Forestry

A regression-based approach to the CO₂ airborne fraction

M. Bennedsen, E. Hillebrand, et al.

This groundbreaking study by Mikkel Bennedsen, Eric Hillebrand, and Siem Jan Koopman uncovers key flaws in the traditional methods for calculating the airborne fraction of CO₂ emissions. With a novel regression-based approach, they present a more precise estimate of 47.0% for the years 1959 to 2022, offering a significant shift in our understanding of CO₂ emissions' impact on climate change.... show more
Abstract
The fraction of anthropogenic CO₂ emissions that remains in the atmosphere—the airborne fraction (AF)—has fluctuated around a near-constant value since 1959, with a consensus estimate near 44%. This study shows that the conventional AF estimator, based on the ratio of yearly atmospheric CO₂ increases to emissions, has statistical deficiencies, including problematic behavior under trends and when emissions approach zero. The authors propose a regression-based estimator that avoids these issues. Using 1959–2022 data, they estimate the AF at 47.0% (±1.1%; 1σ), higher and more tightly constrained than the consensus. Using climate model output, they further show that the regression-based method yields sensible AF estimates in future scenarios, including when emissions are near or at zero.
Publisher
Nature Communications
Published On
Oct 01, 2024
Authors
Mikkel Bennedsen, Eric Hillebrand, Siem Jan Koopman
Tags
airborne fraction
CO₂ emissions
regression-based estimator
climate change
statistical analysis
global warming
emission metrics
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