A regression-based approach to the CO₂ airborne fraction

Area of Science:

• Earth and Environmental Sciences
• Atmospheric Science
• Climate Science

Background:

• The airborne fraction (AF) quantifies the proportion of anthropogenic carbon dioxide (CO2) emissions remaining in the atmosphere.
• Previous estimates of the CO2 airborne fraction have been around 44% globally.
• The conventional method for estimating the AF has known statistical limitations.

Purpose of the Study:

• To address statistical deficiencies in the conventional airborne fraction estimator.
• To develop and apply a more robust, regression-based method for estimating the CO2 airborne fraction.
• To provide an updated and better-constrained estimate of the global CO2 airborne fraction.

Main Methods:

• A novel regression-based estimator was developed to calculate the airborne fraction.
• Empirical analysis was conducted using data from 1959 to 2022.
• Climate model outputs were utilized to validate the regression-based approach in future emission scenarios.

Main Results:

• The study estimates the global CO2 airborne fraction from 1959-2022 to be 47.0% (±1.1%).
• This estimate is higher and more precisely constrained than the current consensus value.
• The regression-based method demonstrated reliable AF estimates, even for future scenarios with near-zero emissions.

Conclusions:

• The conventional airborne fraction estimator has significant statistical drawbacks.
• A regression-based approach offers a more accurate and reliable method for estimating the CO2 airborne fraction.
• The updated airborne fraction estimate has implications for climate modeling and carbon budget assessments.