Spatio-temporal pattern and changes of XCH4 in China from GOSAT observations during 2009-2020

Liping Lei,  Key Lab of Digital Earth, Chinese Academy of Sciences,  leilp@aircas.ac.cn
Luman Li,  Key Lab of Digital Earth, Chinese Academy of Sciences,  liluman19@mails.ucas.ac.cn
Hao Song,  China University of Geosciences (Beijing),  3001200117@cugb.edu.cn (Presenter)
Mengya Sheng,  Key Lab of Digital Earth, Chinese Academy of Sciences,  shengmy@aircas.ac.cn
Shaoqing Zhang,  Key Lab of Digital Earth, Chinese Academy of Sciences,  zhangsq@aircas.ac.cn

This study detected the spatial and timely variation and pattern of XCH4 in China using the mapping XCH4 dataset derived from GOSAT observations from 2009 to 2020 based on spatio-temporal geostatistical approach. We investigated the correlation between the mapping data and surface emission inventory. We find the geographical distribution of high XCH4 values correspond well with strong emissions as indicated in the inventory map. Over the five?year period, the two datasets show a significant high correlation coefficient, indicating the dominant role of surface emissions in determining the distribution of XCH4 concentration in this region and suggesting a promising statistical way of constraining surface CH4 sources and sinks, which is simple and easy to implement using satellite observations over a long term period.

Poster: Poster_Lei_0_53_25.pdf 

Presentation Type: Poster

Session: 3.2c Observations to quantify hot spots and local/urban emissions

Session Date: Wednesday (6/16) 9:45 AM