Global methane budget and trend, 2010–2017: complementarity of inverse analyses using in situ (GLOBALVIEWplus CH 4 ObsPack) and satellite (GOSAT) observations
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Erschienen in
-
Global methane budget and trend, 2010–2017: complementarity of inverse analyses using in situ (GLOBALVIEWplus CH 4 ObsPack) and satellite (GOSAT) observations ; year:2020 ; pages:1-39
Atmospheric chemistry and physics / Discussions. Discussions ; (2020), 1-39
- Urheber
-
Lu, Xiao
Jacob, Daniel J.
Zhang, Yuzhong
Maasakkers, Joannes D.
Sulprizio, Melissa P.
Shen, Lu
Qu, Zhen
Scarpelli, Tia R.
Nesser, Hannah
Yantosca, Robert M.
Sheng, Jianxiong
Andrews, Arlyn
Parker, Robert J.
Boech, Hartmut
Bloom, A. Anthony
Ma, Shuang
- DOI
-
10.5194/acp-2020-775
- URN
-
urn:nbn:de:101:1-2020100105520725817568
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
14.08.2025, 11:03 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Lu, Xiao
- Jacob, Daniel J.
- Zhang, Yuzhong
- Maasakkers, Joannes D.
- Sulprizio, Melissa P.
- Shen, Lu
- Qu, Zhen
- Scarpelli, Tia R.
- Nesser, Hannah
- Yantosca, Robert M.
- Sheng, Jianxiong
- Andrews, Arlyn
- Parker, Robert J.
- Boech, Hartmut
- Bloom, A. Anthony
- Ma, Shuang
Ähnliche Objekte (12)
2013–2019 increases of surface ozone pollution in China: anthropogenic and meteorological influences
Increases in surface ozone pollution in China from 2013 to 2019: anthropogenic and meteorological influences
Global methane budget and trend, 2010–2017: complementarity of inverse analyses using in situ (GLOBALVIEWplus CH<sub>4</sub> ObsPack) and satellite (GOSAT) observations
Systematic bias in evaluating chemical transport models with maximum daily 8-hour average (MDA8) surface ozone for air quality applications
Systematic bias in evaluating chemical transport models with maximum daily 8 h average (MDA8) surface ozone for air quality applications: a case study with GEOS-Chem v9.02
Discrete choice data with unobserved heterogeneity: A conditional binary quantile model
2010–2015 North American methane emissions, sectoral contributions, and trends: a high-resolution inversion of GOSAT observations of atmospheric methane
2010–2015 North American methane emissions, sectoral contributions, and trends: a high-resolution inversion of GOSAT satellite observations of atmospheric methane
Global distribution of methane emissions: a comparative inverse analysis of observations from the TROPOMI and GOSAT satellite instruments
Global distribution of methane emissions: a comparative inverse analysis of observations from the TROPOMI and GOSAT satellite instruments
Attribution of the accelerating increase in atmospheric methane during 2010–2018 by inverse analysis of GOSAT observations
Attribution of the accelerating increase in atmospheric methane during 2010–2018 by inverse analysis of GOSAT observations
2013–2019 increases of surface ozone pollution in China: anthropogenic and meteorological influences
Increases in surface ozone pollution in China from 2013 to 2019: anthropogenic and meteorological influences
Global methane budget and trend, 2010–2017: complementarity of inverse analyses using in situ (GLOBALVIEWplus CH<sub>4</sub> ObsPack) and satellite (GOSAT) observations
Systematic bias in evaluating chemical transport models with maximum daily 8-hour average (MDA8) surface ozone for air quality applications
Systematic bias in evaluating chemical transport models with maximum daily 8 h average (MDA8) surface ozone for air quality applications: a case study with GEOS-Chem v9.02
Discrete choice data with unobserved heterogeneity: A conditional binary quantile model
2010–2015 North American methane emissions, sectoral contributions, and trends: a high-resolution inversion of GOSAT observations of atmospheric methane
2010–2015 North American methane emissions, sectoral contributions, and trends: a high-resolution inversion of GOSAT satellite observations of atmospheric methane
Global distribution of methane emissions: a comparative inverse analysis of observations from the TROPOMI and GOSAT satellite instruments
Global distribution of methane emissions: a comparative inverse analysis of observations from the TROPOMI and GOSAT satellite instruments
Attribution of the accelerating increase in atmospheric methane during 2010–2018 by inverse analysis of GOSAT observations
Attribution of the accelerating increase in atmospheric methane during 2010–2018 by inverse analysis of GOSAT observations
2013–2019 increases of surface ozone pollution in China: anthropogenic and meteorological influences
Increases in surface ozone pollution in China from 2013 to 2019: anthropogenic and meteorological influences
Global methane budget and trend, 2010–2017: complementarity of inverse analyses using in situ (GLOBALVIEWplus CH<sub>4</sub> ObsPack) and satellite (GOSAT) observations
Systematic bias in evaluating chemical transport models with maximum daily 8-hour average (MDA8) surface ozone for air quality applications
Systematic bias in evaluating chemical transport models with maximum daily 8 h average (MDA8) surface ozone for air quality applications: a case study with GEOS-Chem v9.02
Discrete choice data with unobserved heterogeneity: A conditional binary quantile model
2010–2015 North American methane emissions, sectoral contributions, and trends: a high-resolution inversion of GOSAT observations of atmospheric methane
2010–2015 North American methane emissions, sectoral contributions, and trends: a high-resolution inversion of GOSAT satellite observations of atmospheric methane
Global distribution of methane emissions: a comparative inverse analysis of observations from the TROPOMI and GOSAT satellite instruments
Global distribution of methane emissions: a comparative inverse analysis of observations from the TROPOMI and GOSAT satellite instruments
Attribution of the accelerating increase in atmospheric methane during 2010–2018 by inverse analysis of GOSAT observations