The influence of varying atmospheric CO<sub>2</sub> on global warming potentials and carbon emission impulse response functions

Abstract Impulse response functions (IRF), the response in a climate parameter to an emission pulse of CO 2 , are used to characterize Earth system response timescales and to calculate Global Warming Potentials (GWPs). GWPs are widely used to compare emissions of different greenhouse gases and to compute CO 2 equivalent emissions as reported by governments to the United Nations Framework Convention on Climate Change (UNFCCC). The GWP of any gas x is the absolute GWP of gas x Absolute and relative Global Warming Potential (AGWP x ) divided by AGWP of CO 2 . Ideally, AGWP <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msub> <mml:mrow/> <mml:mrow> <mml:mi>C</mml:mi> <mml:msub> <mml:mi>O</mml:mi> <mml:mn>2</mml:mn> </mml:msub> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> and GWP x would be independent of atmospheric CO 2 and climate. However, AGWP <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msub> <mml:mrow/> <mml:mrow> <mml:mi>C</mml:mi> <mml:msub> <mml:mi>O</mml:mi> <mml:mn>2</mml:mn> </mml:msub> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> , and, in turn, GWP x change under rising atmospheric CO 2 and global warming, affecting the emission reporting under the UNFCCC. Here, we apply perturbed parameter ensemble simulations, constrained in a Bayesian approach by observational data, to investigate how AGWP <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msub> <mml:mrow/> <mml:mrow> <mml:mi>C</mml:mi> <mml:msub> <mml:mi>O</mml:mi> <mml:mn>2</mml:mn> </mml:msub> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> and IRF vary under different atmospheric background CO 2 levels (CO <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msub> <mml:mrow/> <mml:mrow> <mml:mn>2</mml:mn> <mml:mo>,</mml:mo> <mml:mi>b</mml:mi> <mml:mi>g</mml:mi> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> ). We provide analytical formulations to compute AGWP <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msub> <mml:mrow/> <mml:mrow> <mml:mi>C</mml:mi> <mml:msub> <mml:mi>O</mml:mi> <mml:mn>2</mml:mn> </mml:msub> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> and IRF for CO 2 , ocean and land carbon uptake, global mean surface air temperature, steric sea level, and ocean heat content, and to adjust these metrics to different CO <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msub> <mml:mrow/> <mml:mrow> <mml:mn>2</mml:mn> <mml:mo>,</mml:mo> <mml:mi>b</mml:mi> <mml:mi>g</mml:mi> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> . AGWP <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msub> <mml:mrow/> <mml:mrow> <mml:mi>C</mml:mi> <mml:msub> <mml:mi>O</mml:mi> <mml:mn>2</mml:mn> </mml:msub> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> , given by the time-integrated response in CO 2 at year 100 multiplied by its radiative efficiency, is 101.8(±13.5) 10 −15 yr W m −2 kg-CO <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msubsup> <mml:mrow/> <mml:mn>2</mml:mn> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>1</mml:mn> </mml:mrow> </mml:msubsup> </mml:mrow> </mml:math> for CO <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msub> <mml:mrow/> <mml:mrow> <mml:mn>2</mml:mn> <mml:mo>,</mml:mo> <mml:mi>b</mml:mi> <mml:mi>g</mml:mi> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> = 425 ppm and decreases by 7% for CO <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msub> <mml:mrow/> <mml:mrow> <mml:mn>2</mml:mn> <mml:mo>,</mml:mo> <mml:mi>b</mml:mi> <mml:mi>g</mml:mi> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> = 500 ppm. The decrease is driven by a decrease in the radiative efficiency of CO 2 , partly canceled by a concomitant increase of IRF <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msub> <mml:mrow/> <mml:mrow> <mml:mi>C</mml:mi> <mml:msub> <mml:mi>O</mml:mi> <mml:mn>2</mml:mn> </mml:msub> </mml:mrow>

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Publication Details

Journal
Environmental Research Letters
Published
2025-05-07
DOI
https://doi.org/10.1088/1748-9326/add54b
Citations
1
Primary Topic
Atmospheric and Environmental Gas Dynamics
Type
article
Field-Weighted Citation Impact
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article

The influence of varying atmospheric CO2 on global warming potentials and carbon emission impulse response functions

Fortunat Joos, Aurich Jeltsch‐Thömmes, Markus Adloff, Qing Sun
1 citations
Environmental Research Letters
Atmospheric and Environmental Gas Dynamics
1.11
article

The influence of varying atmospheric CO2 on global warming potentials and carbon emission impulse response functions

Fortunat Joos, Aurich Jeltsch‐Thömmes, Markus Adloff, Qing Sun
article en
1 citations

Abstract

Abstract Impulse response functions (IRF), the response in a climate parameter to an emission pulse of CO 2 , are used to characterize Earth system response timescales and to calculate Global Warming Potentials (GWPs). GWPs are widely used to compare emissions of different greenhouse gases and to compute CO 2 equivalent emissions as reported by governments to the United Nations Framework Convention on Climate Change (UNFCCC). The GWP of any gas x is the absolute GWP of gas x Absolute and relative Global Warming Potential (AGWP x ) divided by AGWP of CO 2 . Ideally, AGWP <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msub> <mml:mrow/> <mml:mrow> <mml:mi>C</mml:mi> <mml:msub> <mml:mi>O</mml:mi> <mml:mn>2</mml:mn> </mml:msub> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> and GWP x would be independent of atmospheric CO 2 and climate. However, AGWP <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msub> <mml:mrow/> <mml:mrow> <mml:mi>C</mml:mi> <mml:msub> <mml:mi>O</mml:mi> <mml:mn>2</mml:mn> </mml:msub> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> , and, in turn, GWP x change under rising atmospheric CO 2 and global warming, affecting the emission reporting under the UNFCCC. Here, we apply perturbed parameter ensemble simulations, constrained in a Bayesian approach by observational data, to investigate how AGWP <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msub> <mml:mrow/> <mml:mrow> <mml:mi>C</mml:mi> <mml:msub> <mml:mi>O</mml:mi> <mml:mn>2</mml:mn> </mml:msub> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> and IRF vary under different atmospheric background CO 2 levels (CO <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msub> <mml:mrow/> <mml:mrow> <mml:mn>2</mml:mn> <mml:mo>,</mml:mo> <mml:mi>b</mml:mi> <mml:mi>g</mml:mi> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> ). We provide analytical formulations to compute AGWP <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msub> <mml:mrow/> <mml:mrow> <mml:mi>C</mml:mi> <mml:msub> <mml:mi>O</mml:mi> <mml:mn>2</mml:mn> </mml:msub> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> and IRF for CO 2 , ocean and land carbon uptake, global mean surface air temperature, steric sea level, and ocean heat content, and to adjust these metrics to different CO <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msub> <mml:mrow/> <mml:mrow> <mml:mn>2</mml:mn> <mml:mo>,</mml:mo> <mml:mi>b</mml:mi> <mml:mi>g</mml:mi> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> . AGWP <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msub> <mml:mrow/> <mml:mrow> <mml:mi>C</mml:mi> <mml:msub> <mml:mi>O</mml:mi> <mml:mn>2</mml:mn> </mml:msub> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> , given by the time-integrated response in CO 2 at year 100 multiplied by its radiative efficiency, is 101.8(±13.5) 10 −15 yr W m −2 kg-CO <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msubsup> <mml:mrow/> <mml:mn>2</mml:mn> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>1</mml:mn> </mml:mrow> </mml:msubsup> </mml:mrow> </mml:math> for CO <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msub> <mml:mrow/> <mml:mrow> <mml:mn>2</mml:mn> <mml:mo>,</mml:mo> <mml:mi>b</mml:mi> <mml:mi>g</mml:mi> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> = 425 ppm and decreases by 7% for CO <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msub> <mml:mrow/> <mml:mrow> <mml:mn>2</mml:mn> <mml:mo>,</mml:mo> <mml:mi>b</mml:mi> <mml:mi>g</mml:mi> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> = 500 ppm. The decrease is driven by a decrease in the radiative efficiency of CO 2 , partly canceled by a concomitant increase of IRF <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msub> <mml:mrow/> <mml:mrow> <mml:mi>C</mml:mi> <mml:msub> <mml:mi>O</mml:mi> <mml:mn>2</mml:mn> </mml:msub> </mml:mrow>

Environmental Research LettersVol. 20(6)
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
Openalex Percentile: Top 25%
Atmospheric and Environmental Gas Dynamics
1.11
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