CO sources and transport processes driving African upper tropospheric pollution:
quantification from the SOFT‐IO coupling model
CO sources and transport processes driving African upper tropospheric pollution:
quantification from the SOFT‐IO coupling model
Alain Fontaine1,2, Bastien Sauvage1, Sabine Eckhardt3, Hervé Pétetin1, Antoine Auby1 ,Damien Boulanger2 and Valerie Thouret1
1 Laboratoire d’Aérologie, Université Paul Sabatier, CNRS, Toulouse, France2 Observatoire Midi‐Pyrénées, UMS 831 SEDOO, CNRS, Toulouse, France3 NILU – Norway Institute for Air Research, Kjeller, Norway
Context of the studyContext of the study
Tropics are a key region in atmospheric pollution and climate issues‐ less in situ observations than in mid‐latitudes‐most of the rapid changes in anthropogenic emissions comes from South America, Africa and South‐East Asia with more growing mega cities‐most of the natural emissions (biomass burning, lightning) are in the Tropics every seasons‐ half of the global tropospheric O3 increase comes from the Tropics (Zangh et al. Nature Geos. accepted)
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Tropospheric O3 increase seen by satellite (TOAR, Cooper et al.)
IAGOS‐MOZAIC observationsIAGOS‐MOZAIC observationsIAGOS‐MOZAIC observations of O3, CO and Relative Humidity : Air Namibia aircraft daily flights between Frankfurt/London and Windhoek (December 2005‐October 2013) Give a description of the seasonal distribution variations of O3, CO and RH in the tropical African upper troposphere (9‐12km)
SOFT‐IO coupling modelAssign the sources & regions driving the meridional CO distributions Investigate the inter annual variability and trends of tropical CO
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UT/LS CO observations along MOZAIC aircraft
Methodology: quantifying the source/receptor link for the IAGOS database: SOFT‐IO
Methodology: quantifying the source/receptor link for the IAGOS database: SOFT‐IO
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IAGOS Aircraft
Operational analyses 1° resolution 60-137 levels
Residence time of plume dispersionMeteorological data
CO Emission inventories Anthropogenic: MACCITY, EDGARBiomass burning: GFAS, GFEDdistributed by the ECCAD database(http://eccad.pole‐aeris.fr)
IAGOS DatabaseAircraft measurementsAdd‐value products
Clusters
Regional CO contributionsCO sources contribution
IAGOS user interface
Coupling tool(SOFT-IO)
injection
resid
zEmissionTonContributi
SOFT‐IO diagram (Sauvage et al., GMD to be submitted)
Dynamical context: transport of pollutionDynamical context: transport of pollution
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Main circulation patterns
UT/LS trace gaz distributions (2005‐2013)UT/LS trace gaz distributions (2005‐2013)
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DJF
JJA
MAM
SON
O3 & CO (p
pb) / RH (%
)
ITCZ: RH & CO max, O3 negative min and gradients toward pole: negative RH & CO, positive O3
ITCZ
ITCZ ITCZ
ITCZ
LSLS
LSLS
UT/LS CO seasonal origins: sourcesUT/LS CO seasonal origins: sources
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DJF MAM
Observations vs total contributions
JJA SON
UT/LS CO seasonal origins: regionsUT/LS CO seasonal origins: regions
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DJF MAM
Observations vs fire regional contributions
JJA SON
UT/LS CO seasonal origins: regionsUT/LS CO seasonal origins: regions
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DJF MAM
Observations vs anthropic regional contributions
SONJJA
CO (ppb) time series (monthly means)CO (ppb) time series (monthly means)
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Observed CO Total CO contribution
Fire CO contribution Anthropogenic CO contribution
Further investigationsFurther investigationsInvestigate adjacent meridional CO gradients (South America, Atlantic, Indian Ocean regions with no IAGOSmeasurements) with satellite observations (IASI, MOPITT) to:
• Quantify CO import/export from Africa in the Tropics
• Investigate CO trends in the Tropics
Use CTM to better understand O3 positive meridional gradients (JJA & SON) and the role of other sources (South America, South‐East Asia, lightnings) in the ozone UT distributions.
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CO comparisons: IAGOS vs satellite (IASI) & CTM (GEOS‐Chem)
ConclusionsConclusions
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For the first time daily observations of O3, CO & RH allow to give a detailed description of the seasonal distributions over the African tropical upper troposphere
Negative CO & RH meridional gradients are observed south and north of the ITCZ winds divergence zone, while O3 displays positive gradients except in MAM
First estimation on the origin of the CO distributions are realizes thanks to SOFT‐IO modeling:
• African tropical UT CO is mostly related to the transport process scheme described in Sauvage et al. (2007): African emissions (anthropogenic and fires) are mostly influencing UT CO gradients through Hadley cells circulation
• Anthropogenic emissions drive tropical CO with 60 to 70% influence, except in DJF where fires are dominant (55% influence), considering mean values (Q2)
• Biomass burning are in majority emitted regionally (N. Africa in DJF & MAM, S. Africa in JJA & SON), except in SON with some fires influence from South America
• Tropical UT CO mixing ratios highest values (>Q3) are driven by biomass burning emissions while anthropogenic emissions drive subtropical CO highest valueswith Hadley cells transport of African emissions sustained with emission from Asia through easterly circulation (TEJ & AMA)