[A-CG35] Global Carbon Cycle Observation and Analysis

[ACG35-08] Verifying global fugitive fossil fuel CH₄ emission trends using atmospheric CH₄ and δ¹³C-CH₄ observations

*Naveen Chandra¹, Prabir Patra^1,2,7, Ryo Fujita³, Lena Höglund Isaksson⁴, Taku Umezawa⁵, Daisuke Goto⁶, Shinji Morimoto⁷ (1.RIGC, JAMSTEC, Kanazawa, Yokohama, Japan, 2.CeRES, Chiba University, Chiba, Japan, 3.Meteorological Research Institute, Tsukuba, Japan, 4.International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria, 5.National Institute for Environmental Studies, Tsukuba, Japan, 6.National Institute for Polar Research, Tachikawa, Tokyo, Japan, 7.CAOS, Tohoku University, Sendai, Japan)

Keywords:Methane, Stable carbon isotope ratio of CH4 , Fugitive fossil fuel CH4 emission , ACTM

Reducing methane (CH₄) emissions is now a top priority for climate action because of its short lifetime and high global warming potential. Emissions from fossil fuel exploitation sectors (oil-gas extraction, coal mining, geological), accounting for 33% of global anthropogenic CH₄ emissions, are the most attractive and cost-effective mitigation option. However, the estimated CH₄emissions and trends of the fossil-fuel sector are largely uncertain across the existing inventories (e.g., EDGAR, GAINSv4, FAO estimates, etc.) and source/sink inversions of atmospheric CH₄. The atmospheric CH₄ data alone do not provide source-type information and hence cannot constrain magnitudes of specific sectors. Stable carbon isotope ratio of CH₄ (δ¹³C-CH₄) in the atmosphere is controlled by relative contributions from different source types with distinctive isotope signatures, and could help to probe sectoral emissions with the help of the atmospheric chemistry-transport model (ACTM).

We have simulated the global history (1985-2020) of CH₄ and δ¹³C-CH₄ using MIROC4-ACTM and compared with the measurement results at networks of monitoring stations (e.g., INSTAAR, TU/NIPR, MPI, etc.). The base simulations (based on anthropogenic CH₄ emissions from the EDGARv6 database) could not reproduce the observed atmospheric CH₄ and δ¹³C-CH₄(Fig. 1). The discrepancy between the observed and modelled CH₄ and δ¹³C-CH₄ suggest incomplete knowledge of emissions used for baseline simulations. Different sensitivity experiments are performed by revising fugitive fossil fuel emissions (from different inventories and literature) and spatially resolved distributions of δ¹³C-CH₄ source signatures to reproduce the measurements. The emission scenario (sONG-Coal_geol19) is then prepared by using GAINSv4 inventory for Oil and Gas, coal mining and scaled natural geological sectors, which reproduces the trend and meridional gradients in the observed CH₄ and δ¹³C-CH₄ (Fig. 1), but does not compare well with the absolute δ¹³C-CH₄ values. Spatially resolved δ¹³C-CH₄ source signatures in place of globally invariant source signature helps to reduce the mismatch between observed and simulated δ¹³C-CH₄ from ~1 ‰ to less than 0.1 ‰ (magenta line lower panel of Fig. 1). The most likely emission scenario, which can reconstruct the latitudinal gradient and trends in atmospheric CH₄ and δ¹³C-CH₄ simultaneously suggests a decreasing-to-constant emissions from fossil fuel exploitations 1985-2020, contrary to an increasing trend in EDGARv6 inventory. This study suggests that the increase in atmospheric CH₄ after 2006 is primarily due to microbial sources, mainly the agricultural and waste management sector. The detail will be presented in the meeting.

Figure 1. Comparison of modelled CH₄ and δ¹³C-CH₄ with observations (black circle) made by Tohoku University (TU) and National Institute of Polar Research (NIPR) at two northern and southern surface baseline stations, Ny-Alesund, Svalbard and Syowa, Antarctica.