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. 2024 Oct 29;121(44):e2411212121.
doi: 10.1073/pnas.2411212121. Epub 2024 Oct 21.

Rapid shift in methane carbon isotopes suggests microbial emissions drove record high atmospheric methane growth in 2020-2022

Sylvia Englund Michel  1   2 , Xin Lan  3   4 , John Miller  4 , Pieter Tans  1 , J Reid Clark  1 , Hinrich Schaefer  5 , Peter Sperlich  5 , Gordon Brailsford  5 , Shinji Morimoto  6 , Heiko Moossen  7 , Jianghanyang Li  1   2
Affiliations

Rapid shift in methane carbon isotopes suggests microbial emissions drove record high atmospheric methane growth in 2020-2022

Sylvia Englund Michel et al. Proc Natl Acad Sci U S A. .

Abstract

The growth rate of the atmospheric abundance of methane (CH4) reached a record high of 15.4 ppb yr-1 between 2020 and 2022, but the mechanisms driving the accelerated CH4 growth have so far been unclear. In this work, we use measurements of the 13C:12C ratio of CH4 (expressed as δ13CCH4) from NOAA's Global Greenhouse Gas Reference Network and a box model to investigate potential drivers for the rapid CH4 growth. These measurements show that the record-high CH4 growth in 2020-2022 was accompanied by a sharp decline in δ13CCH4, indicating that the increase in CH4 abundance was mainly driven by increased emissions from microbial sources such as wetlands, waste, and agriculture. We use our box model to reject increasing fossil fuel emissions or decreasing hydroxyl radical sink as the dominant driver for increasing global methane abundance.

Keywords: greenhouse gases; methane; stable isotopes.

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Conflict of interest statement

Competing interests statement:The authors declare no competing interest.

Figures

Fig. 1.
Fig. 1.
(A) Trend of globally averaged CH4 abundance (in gray) and δ13CCH4 (purple) from the NOAA/GML GGGRN. Mean growth rates of CH4 mole fraction and δ13CCH4 are shown for the following time periods: 1983–1998, 1999–2006, 2008–2014, 2014–2020, and 2020–2022. (B) Colocated δ13CCH4 measurements at Alert (Canada), Svalbard (Norway), and Antarctica by INSTAAR, NIWA, TU/NIPR, and MPI. Each dataset is fitted with a trend in the same color.
Fig. 2.
Fig. 2.
(A) Modeled response of CH4 mole fraction and δ13CCH4 due to different CH4 growth drivers. (B) Emissions and CH4 lifetime relative to OH for each scenario.
See this image and copyright information in PMC

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