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一种基于回归的一氧化碳空气传播分数方法。

A regression-based approach to the CO airborne fraction.

作者信息

Bennedsen Mikkel, Hillebrand Eric, Koopman Siem Jan

机构信息

Department of Economics and Business Economics, Aarhus University, Aarhus V, Denmark.

Center for Research in Energy: Economics and Markets (CoRE), Aarhus University, Aarhus V, Denmark.

出版信息

Nat Commun. 2024 Oct 1;15(1):8507. doi: 10.1038/s41467-024-52728-1.

Abstract

The global fraction of anthropogenically emitted carbon dioxide (CO) that stays in the atmosphere, the CO 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 CO concentrations and CO 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.

摘要

1959年至2022年期间,人为排放的二氧化碳(CO)滞留在大气中的全球占比,即CO的空气传播分数,一直在一个恒定值附近波动。空气传播分数的共识估计约为44%。在本研究中,我们表明,基于大气CO浓度变化与CO排放之比的传统空气传播分数估计器存在一些统计缺陷。我们提出了一种基于回归的空气传播分数替代估计器,该估计器不存在这些缺陷。我们的实证分析得出,1959 - 2022年期间空气传播分数的估计值为47.0%(±1.1%;1σ),这意味着比当前的共识估计值更高且约束更好。利用气候模型输出结果,我们表明,基于回归的方法在排放为零或接近零的未来情景中,也能提供合理的空气传播分数估计值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d997/11445245/58e7e2435c5d/41467_2024_52728_Fig1_HTML.jpg

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