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Spatial and Temporal Variations of Atmospheric CH 4 in Monsoon Asia Detected by Satellite Observations of GOSAT and TROPOMI.

Authors :
Song, Hao
Sheng, Mengya
Lei, Liping
Guo, Kaiyuan
Zhang, Shaoqing
Ji, Zhanghui
Source :
Remote Sensing. Jul2023, Vol. 15 Issue 13, p3389. 18p.
Publication Year :
2023

Abstract

Space-based measurements, such as the Greenhouse gases Observing SATellite (GOSAT) and the TROPOspheric Monitoring Instrument (TROPOMI) aboard the Sentinel-5 Precursor satellite, provide global observations of the column-averaged CH4 concentration (XCH4). Due to the irregular observations and data gaps in the retrievals, studies on the spatial and temporal variations of regional atmospheric CH4 concentrations are limited. In this paper, we mapped XCH4 data over monsoon Asia using GOSAT and TROPOMI observations from April 2009 to December 2021 and analyzed the spatial and temporal pattern of atmospheric CH4 variations and emissions. The results show that atmospheric CH4 concentrations over monsoon Asia have long-term increases with an annual growth rate of roughly 8.4 ppb. The spatial and temporal trends of XCH4 data are significantly correlated with anthropogenic CH4 emissions from the bottom-up emission inventory of EDGAR. The spatial pattern of gridded XCH4 temporal variations in China presents a basically consistent distribution with the Heihe–Tengchong Line, which is mainly related to the difference in anthropogenic emissions in the eastern and western areas. Using the mapping of XCH4 data from 2019 to 2021, this study further revealed the response of atmospheric CH4 concentrations to anthropogenic emissions in different urban agglomerations. For the urban agglomerations, the triangle of Central China (TCC), the Chengdu–Chongqing City Group (CCG), and the Yangtze River Delta (YRD) show higher CH4 concentrations and emissions than the Beijing–Tianjin–Hebei region and nearby areas (BTH). The results reveal the spatial and temporal distribution of CH4 concentrations and quantify the differences between urban agglomerations, which will support further studies on the drivers of methane emissions. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20724292
Volume :
15
Issue :
13
Database :
Academic Search Index
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
164922302
Full Text :
https://doi.org/10.3390/rs15133389