Day 4

Detailed paper information

Back to list

Paper title Methane emissions in the Eastern Mediterranean and Middle East as seen from space
Authors
  1. Xin Lin Laboratoire des Sciences du Climat et de l'Environnement (LSCE) Speaker
  2. Philippe Ciais Laboratoire des Sciences du Climat et de l'Environnement (LSCE)
  3. Frédéric Chevallier Laboratoire des Sciences du Climat et de l'Environnement (LSCE)
  4. Marielle Saunois Université Paris-Saclay, CNRS CEA UVSQ, Laboratoire des Sciences du Climat et de l’Environnement (LSCE)
  5. Zitely Tzompa Sosa Laboratoire des Sciences du Climat et de l'Environnement (LSCE)
  6. Jos Lelieveld The Cyprus Institute
  7. Jean Sciare The Cyprus Institute
Form of presentation Poster
Topics
  • A1. Atmosphere
    • A1.04 Greenhouse Gases
Abstract text Anthropogenic greenhouse gas (GHG) emissions in the Eastern Mediterranean and Middle East (EMME) have increased fivefold over the last five decades. Emission rates in this region were ~3.4 GtCO2eq/yr during the 2010s, accounting for ~7% of the global anthropogenic GHG emissions. Among various GHGs emitted, methane (CH4) is of particular interest, given its stronger global warming potential relative to CO2 and the role of EMME as a key oil and gas producing region. Bottom-up inventories have reported that the anthropogenic CH4 emissions in EMME were ~22.0 Tg/yr in the 2010s, of which ~70% were contributed by oil and gas sectors. As inventory-based estimates often suffer from uncertainties in emission factors and activity statistics, independent budget estimation based on atmospheric observations, preferably at regional or national scales, are required to verify inventories and evaluate effectiveness of climate mitigation measures. Meanwhile, the availability of satellite CH4 observations in the recent decade (notably GOSAT XCH4 and TROPOMI XCH4) provides new opportunities to constrain CH4 emissions in this region previously underrepresented by ground-based observational networks. Here, we present a study of CH4 inverse modeling over EMME, using a Bayesian variational inversion system PYVAR-LMDz-SACS developed by LSCE, France with satellite XCH4 observations. The inversion system takes advantage of the dense XCH4 observations from space and the zooming capability of the atmospheric transport model LMDz to resolve CH4 emissions in EMME at a spatial resolution of ~50km. Instead of the default model settings for global CH4 inversions, we adapt the definition of error structure in the inversion system wherever necessary to address issues with ultra-emitters (which are common in the study region) at the high spatial resolution. The inversion results are evaluated against independent observations within and outside the study region from various platforms, and compared with emission inventories and other global or regional inversion products. With these datasets and modeling tools, we aim to assess the variations in CH4 emissions in EMME at the scales where decision-making and climate actions take place.