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|Title:||Comparing Optimized CO Emission Estimates Using MOPITT or NOAA Surface Network Observations|
|Authors:||HOOGHIEMSTRA P.b.; KROL M; BERGAMASCHI Peter; DE LAAT J.; VAN DERWERF G. R.; NOVELLI P.c.; DEETER M. N.; ABEN I.; RÖCKMANN Thomas|
|Citation:||JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES vol. 117 no. D06309 p. 1-23|
|Publisher:||AMER GEOPHYSICAL UNION|
|Type:||Articles in periodicals and books|
|Abstract:||This paper compares two global inversions to estimate carbon monoxide (CO) emissions for 2004. Either surface flask observations from the National Oceanic and Atmospheric Administration Earth System Research Laboratory (NOAA/ESRL) Global Monitoring Division (GMD) or CO total columns from the Measurement of Pollution in the Troposphere (MOPITT) instrument are assimilated in a 4D-Var framework. Inferred emission estimates from the two inversions are consistent over the Northern Hemisphere (NH). For example, both inversions yield anthropogenic CO emissions about a factor 2 higher then the EDGARv4.1 inventory for Europe and Asia. In the Southern Hemisphere (SH) three important findings are reported. First, due to their different vertical sensitivity, the stations-only inversion increases SH biomass burning emissions by 108 Tg CO/yr more than the MOPITT-only inversion. Conversely, the MOPITT-only inversion results in SH natural emissions (mainly CO from oxidation of NMVOCs) that are 185 Tg CO/yr higher compared to the stations-only inversion. Second, MOPITT-only derived biomass burning emissions are reduced with respect to the prior which is in contrast to previous (inverse) modeling studies. Finally, MOPITT derived total emissions are significantly higher for South America and Africa compared to the stations only inversion. This is likely due to a positive bias in the MOPITT V4 product. This bias is also apparent from validation with surface stations, ground truth FTIR columns and total column measurements from SCIAMACHY. Our results show that a combined inversion is promising on the NH. However, implementation of a satellite bias correction scheme is essential to combine both datasets on the SH.|
|JRC Institute:||Sustainable Resources|
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