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Titel |
Upper troposphere and stratosphere distribution of hydrocarbon species in ACE-FTS measurements and GEOS-Chem simulations |
VerfasserIn |
Ja-Ho Koo, Kaley A. Walker, Dylan B. A. Jones, Ashley Jones, Patrick E. Sheese, Chris D. Boone, Peter F. Bernath, Gloria L. Manney |
Konferenz |
EGU General Assembly 2016
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Medientyp |
Artikel
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Sprache |
en
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Digitales Dokument |
PDF |
Erschienen |
In: GRA - Volume 18 (2016) |
Datensatznummer |
250128912
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Publikation (Nr.) |
EGU/EGU2016-8952.pdf |
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Zusammenfassung |
Measurements of carbon-containing species, referred to herein as “hydrocarbons”, are
important components needed for describing and understanding the influence of natural
and anthropogenic emissions on atmospheric chemistry. Analysis of the global
pattern of hydrocarbons contributes to our understanding of the influence of regional
and seasonal variation in air pollution and natural fire events. The Atmospheric
Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) has monitored
trace gases in the upper troposphere and stratosphere based on solar occultation
measurements for more than ten years. In this study, we investigate the global pattern
of seven “hydrocarbon” species (CO, C2H6, C2H2, HCN, H2CO, CH3OH, and
HCOOH) and OCS using the ACE-FTS version 3.5 dataset from 2004 to 2013. All
hydrocarbons show strong seasonal variation and regional differences, but the detailed
pattern differs according to the speciation of the hydrocarbons. For example, in the
Northern Hemisphere, CO, C2H6, and C2H2 show the highest mixing ratios in winter,
but high CH3OH and HCOOH appear in summer. In the Southern hemisphere,
H2CO, HCN, and HCOOH show high mixing ratios in springtime. These patterns
indicate the impact of different emission sources including fuel combustion, wildfire
emission, and chemical production. By calculating correlations with CO, these results
can provide useful information to characterize each hydrocarbon emission. The
ACE-FTS measurements have also been compared with GEOS-Chem output to
examine the model performance and spatiotemporal patterns in the simulations. |
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