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URN: urn:nbn:de:swb:90-702410
DOI: 10.5194/acp-17-5751-2017
Zitationen: 7
Web of Science
Zitationen: 7

Satellite-derived methane hotspot emission estimates using a fast data-driven method

Buchwitz, M.; Schneising, O.; Reuter, M.; Heymann, J.; Krautwurst, S.; Bovensmann, H.; Burrows, J. P.; Boesch, H.; Parker, R. J.; Somkuti, P.; Detmers, R. G.; Hasekamp, O. P.; Aben, I.; Butz, A.; Frankenberg, C.; Turner, A. J.

Methane is an important atmospheric greenhouse gas and an adequate understanding of its emission sources is needed for climate change assessments, predictions, and the development and verification of emission mitigation strategies. Satellite retrievals of near-surface-sensitive column-averaged dry-air mole fractions of atmospheric methane, i.e. XCH₄, can be used to quantify methane emissions. Maps of time-averaged satellite-derived XCH₄ show regionally elevated methane over several methane source regions. In order to obtain methane emissions of these source regions we use a simple and fast data-driven method to estimate annual methane emissions and corresponding 1σ uncertainties directly from maps of annually averaged satellite XCH₄. From theoretical considerations we expect that our method tends to underestimate emissions. When applying our method to high-resolution atmospheric methane simulations, we typically find agreement within the uncertainty range of our method (often 100 %) but also find that our method tends to underestimate emissions by typically about 40 %. To what extent these findings are model dependent needs to be as ... mehr

Zugehörige Institution(en) am KIT Young Investigator Network (YIN)
Publikationstyp Zeitschriftenaufsatz
Jahr 2017
Sprache Englisch
Identifikator ISSN: 1680-7316, 1680-7324
KITopen ID: 1000070241
Erschienen in Atmospheric chemistry and physics
Band 17
Heft 9
Seiten 5751-5774
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