A New Divergence Method to Quantify Methane Emissions Using Observations of Sentinel‐5P TROPOMI. Issue 18 (25th September 2021)

• Record Type: Journal Article
• Authors: Liu, Mengyao; van der A, Ronald; van Weele, Michiel; Eskes, Henk; Lu, Xiao; Veefkind, Pepijn; de Laat, Jos; Kong, Hao; Wang, Jingxu; Sun, Jiyunting; Ding, Jieying; Zhao, Yuanhong; Weng, Hongjian
• Is Part Of: Geophysical research letters. Volume 48:Issue 18(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-09-25
• Subjects: methane emissions -- divergence -- TROPOMI -- Texas; Geophysics -- Periodicals; Planets -- Periodicals; Lunar geology -- Periodicals; 550
• DOI: 10.1029/2021GL094151
• Languages: English
• ISSNs: 0094-8276

Abstract

Abstract: We present a new divergence method to estimated methane (CH4 ) emissions from satellite observed mean mixing ratio of methane (XCH4 ) by deriving the regional enhancement of XCH4 in the Planetary Boundary Layer (PBL). The applicability is proven by comparing the estimated emissions with its known emission inventory from a 3‐month GEOS‐Chem simulation. When applied to TROPOspheric Monitoring Instrument observations, sources from well‐known oil/gas production areas, livestock farms and wetlands in Texas become clearly visible in the emission maps. The calculated yearly averaged total CH4 emission over the Permian Basin is 3.06 (2.82, 3.78) Tg a −1 for 2019, which is consistent with previous studies and double that of EDGAR v4.3.2 for 2012. Sensitivity tests on PBL heights, on the derived regional background and on wind speeds suggest our divergence method is quite robust. It is also a fast and simple method to estimate the CH4 emissions globally. Plain Language Summary: Methane (CH4 ) is an important greenhouse gas in the atmosphere and plays a crucial role in the global climate change. It kept increasing over the last decades. About 70% of CH4 comes from human activities like oil/gas productions or livestock farms. The recently launched TROPOspheric Monitoring Instrument provides an opportunity to estimate the emissions of CH4 on a regional scale. This work presents a new method to fastly derive CH4 emissions at a fairly high spatial resolution without a priori knowledge of sources. Key Points: A new divergence method is developed to estimate methane emissions based on satellite observations, requiring no a priori emissions The applicability of this method in identifying and quantifying sources is proven by a GEOS‐Chem simulation with known emission inventory The estimated emissions over Texas (United States) based on TROPOspheric Monitoring Instrument observations are evaluated and are found to be robust