17:15 〜 18:45
[MIS01-P12] Top-down estimates of oil and gas sector methane emissions in Russia based on surface and satellite observations
キーワード：methane emissions, GOSAT, inverse model, oil and gas
Methane emissions from the oil and gas sector tended to increase in recent decades due to growing production in several regions. Emission reduction in the sector is an attractive approach as it requires a minor fraction of total production costs. At the same time, fugitive emissions by the oil and gas sector are difficult to estimate due to the sporadic distribution of leaks. Large variation of the methane emission estimates between recent releases of the national inventory report for the Russian oil and gas sector is due to the use of different emission factors from the 1996 and 2006 IPCC inventory guidelines. Similarly, top-down emission estimates with global inverse models and bottom-up estimates by global inventories also showed significant spread. We estimate methane emissions using a high-resolution inverse model NIES-TM-FLEXPART-VAR (NTFVAR) based on GOSAT and surface observations for the period 2010-2020 and compare to other estimates. The model uses as input anthropogenic emissions from EDGAR v.6 and GAINS, wetland emissions, biomass burning emissions from GFED and GFAS, soil and chemical sinks, and oceanic, geological, and termite sources. The optimized emission categories in addition to oil and gas, are agriculture, waste, biomass burning, coal, and wetlands. In comparison to other global inverse models, our model gives higher oil and gas sector emissions (still in the range of bottom-up estimates). At the same time, the estimated emissions from coal production are closer to the national inventory, while other top-down models give higher estimates. To reduce the spread of emission estimates at high latitudes, we can consider using improving simulated methane concentrations driven by wetland emissions in summer and anthropogenic emissions in winter.