日本地球惑星科学連合2022年大会

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[E] 口頭発表

セッション記号 A (大気水圏科学) » A-CG 大気海洋・環境科学複合領域・一般

[A-CG38] 衛星による地球環境観測

2022年5月23日(月) 13:45 〜 15:15 104 (幕張メッセ国際会議場)

コンビーナ:沖 理子(宇宙航空研究開発機構)、コンビーナ:本多 嘉明(千葉大学環境リモートセンシング研究センター)、高薮 縁(東京大学 大気海洋研究所)、コンビーナ:松永 恒雄(国立環境研究所地球環境研究センター/衛星観測センター)、座長:松永 恒雄(国立環境研究所地球環境研究センター/衛星観測センター)

14:30 〜 14:45

[ACG38-16] Observations of atmospheric CH4 enhancements due to anthropogenic emissions by the GOSAT-2 satellite.

*Shamil Maksyutov1、Rajesh Janardanan1Yukio Yoshida1Tsuneo Matsunaga1 (1.National Institute for Environmental Studies)

キーワード: methane emission inventory, anthropogenic emission, GOSAT-2

We present early results of applying the observational data by the Greenhouse gases Observing SATellite-2 (GOSAT-2) to the detection of the local anthropogenic methane emissions signatures in the total column-averaged concentrations of atmospheric methane around the globe. We use the column-averaged methane observations data retrieved with NIES Level 2 algorithms v01.03 (with proxy algorithm) and v01.04 (with full physics algorithm). To relate the observations to the EDGAR anthropogenic methane emission inventory in various regions, we extract localized emission anomalies from column-averaged methane observations (XCH4) by GOSAT-2 satellite using high-resolution atmospheric transport model simulations made with FLEXPART model, that match the size of the satellite observation footprint. XCH4 enhancement due to anthropogenic emissions is estimated as the difference between polluted observations from surrounding cleaner observations after categorizing the observations with model simulations. To reduce the impact of the observation error we apply binning the observations over large region according to model-simulated enhancements. We found that the local enhancements observed by GOSAT-2 and retrieved with both algorithms scale linearly with inventory-based simulations of XCH4 for the globe, confirming good potential for using GOSAT-2 observations for quantification of the methane emissions.