Detection of locally elevated methane concentrations by analyzing Sentinel-5 Precursor satellite data
Steffen Vanselow, Institute of Environmental Physics (IUP), University of Bremen FB1, Bremen, Germany, vanselow@iup.physik.uni-bremen.de (Presenter)
Oliver Schneising, Institute of Environmental Physics (IUP), University of Bremen FB1, Bremen, Germany, schneising@iup.physik.uni-bremen.de
Michael Buchwitz, Institute of Environmental Physics (IUP), University of Bremen FB1, Bremen, Germany, buchwitz@uni-bremen.de
Heinrich Bovensmann, Institute of Environmental Physics (IUP), University of Bremen FB1, Bremen, Germany, heinrich.bovensmann@iup.physik.uni-bremen.de
John P. Burrows, Institute of Environmental Physics (IUP), University of Bremen FB1, Bremen, Germany, burrows@iup.physik.uni-bremen.de
Methane (CH4) is an important anthropogenic greenhouse gas and its rising concentration in the atmosphere contributes significantly to global warming. Satellite measurements of the column-averaged dry-air mole fraction of atmospheric methane, denoted as XCH4, can be used to detect and quantify the emissions of methane.
In addition, sufficiently accurate long-term satellite measurements provide information on emission trends and other characteristics of the sources. This is important, for example, to improve emission inventories and to verify policy actions taken to mitigate climate change.
The Sentinel-5 Precursor (S5P) satellite with the TROPOspheric Monitoring Instrument (TROPOMI) onboard was launched in October 2017 into a sun-synchronous orbit with an equator crossing time of 13:30. TROPOMI measures reflected solar radiation in different wavelength bands to generate various data products and combines daily global coverage with high spatial resolution. TROPOMI's observations in the shortwave infrared (SWIR) spectral range yield methane with a horizontal resolution of typically 7 × 7 km2.
The WFM-DOAS retrieval method, developed at the University of Bremen, retrieves XCH4 with an accuracy of about 1%. We use a 2-year data set (2018/2019) generated with this retrieval algorithm to detect locally enhanced methane concentrations originating from emission sources. Our detection algorithm identifies temporally stable local enhancements relative to the surroundings by utilising different filter criteria, such as a certain threshold that the local methane anomalies must exceed. To investigate the detected sources of methane, these are compared to methane emission inventories for fossil fuel exploitation.
In this presentation, the algorithm and initial results concerning the detection of local methane enhancements by spatially localized methane sources (e.g. coal mining areas, oil and gas fields) are presented.
Poster: Poster_Vanselow__13_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