Global Atmospheric δ13CH4 and CH4 Trends for 2000–2020 from the Atmospheric Transport Model TM5 Using CH4 from Carbon Tracker Europe–CH4 Inversions

Vilma Mannisenaho*, Aki Tsuruta, Leif Backman, Sander Houweling, Arjo Segers, Maarten Krol, Marielle Saunois, Benjamin Poulter, Zhen Zhang, Xin Lan, Edward J. Dlugokencky, Sylvia Michel, James W.C. White, Tuula Aalto

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

This study investigates atmospheric (Formula presented.) CH (Formula presented.) trends, as produced by a global atmospheric transport model using CH (Formula presented.) inversions from CarbonTracker-Europe CH (Formula presented.) for 2000–2020, and compares them to observations. The CH (Formula presented.) inversions include the grouping of the emissions both by (Formula presented.) CH (Formula presented.) isotopic signatures and process type to investigate the effect, and to estimate the CH (Formula presented.) magnitudes and model CH (Formula presented.) and (Formula presented.) CH (Formula presented.) trends. In addition to inversion results, simulations of the global atmospheric transport model were performed with modified emissions. The estimated global CH (Formula presented.) trends for oil and gas were found to increase more than coal compared to the priors from 2000–2006 to 2007–2020. Estimated trends for coal emissions at 30 (Formula presented.) N–60 (Formula presented.) N are less than 50% of those from priors. Estimated global CH (Formula presented.) rice emissions trends are opposite to priors, with the largest contribution from the EQ to 60 (Formula presented.) N. The results of this study indicate that optimizing wetland emissions separately produces better agreement with the observed (Formula presented.) CH (Formula presented.) trend than optimizing all biogenic emissions simultaneously. This study recommends optimizing separately biogenic emissions with similar isotopic signature to wetland emissions. In addition, this study suggests that fossil-based emissions were overestimated by 9% after 2012 and biogenic emissions are underestimated by 8% in the inversion using EDGAR v6.0 as priors.

Original languageEnglish
Article number1121
JournalAtmosphere
Volume14
Issue number7
DOIs
Publication statusPublished - Jul 2023

Keywords

  • atmospheric modelling
  • isotopes
  • methane

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