Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11765/12945
Quantification of CH4 emissions from waste disposal sites near the city of Madrid using ground- and space-based observations of COCCON, TROPOMI and IASI [Discussion paper]
Title: Quantification of CH4 emissions from waste disposal sites near the city of Madrid using ground- and space-based observations of COCCON, TROPOMI and IASI [Discussion paper]
Authors: Tu, QiansiHase, FrankSchneider, Matthias RESEARCHERID García Rodríguez, Omaira Elena ORCID RESEARCHERID Autor AEMETBlumenstock, ThomasBorsdorff, TobiasFrey, MatthiasKhosrawi, FarahnazLorente, AlbaAlberti, CarlosBustos Seguela, Juan José deAutor AEMETButz, AndréCarreño Corbella, VirgilioAutor AEMETCuevas Agulló, Emilio ORCID RESEARCHERID SCOPUSID Autor AEMETCurcoll, RogerDiekmann, ChristopherDubravica, DarkoErtl, BenjaminEstruch, CarmeLeón-Luis, Sergio FabiánAutor AEMETMarreño, CarlosMorguí, J. A.Ramos López, RamónAutor AEMETScharun, ChristianSchneider, C.Sepúlveda Hernández, EliezerAutor AEMETToledano, CarlosTorres, Carlos ORCID RESEARCHERID Autor AEMET
Keywords: Carbon Column Observing Network; Tropospheric Monitoring Instrument; Infrared Atmospheric Sounding Interferometer; Greenhouse gases emissions; Remote sensing; Methane
Issue Date: 2021
Publisher: European Geosciences Union
Citation: Atmospheric Chemistry and Physics Discussions. 2021
Publisher version: https://doi.org/10.5194/acp-2021-437
Abstract: We use different methane ground- and space-based remote sensing data sets for investigating the emission strength of three waste disposal sites close to Madrid. We present a method that uses wind-assigned anomalies for deriving emission strengths from satellite data and estimating their uncertainty to 9–14 %. The emission strengths estimated from the remote sensing data sets are significantly larger than the values published in the official register.
Sponsorship : ESA support through the COCCON-PROCEEDS and COCCON-PROCEEDS II projects. In addition, this research was funded by the Ministerio de Economía y Competitividad from Spain through the INMENSE project (CGL2016-80688-P). This research has largely benefit from funds of the Deutsche Forschungsgemeinschaft (provided for the two projects MOTIV and TEDDY with IDs/290612604 and 416767181, respectively).
URI: http://hdl.handle.net/20.500.11765/12945
ISSN: 1867-8610
Appears in Collections:Artículos científicos 2019-2022


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