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@ARTICLE{ToengesSchuller:49906,
author = {Toenges-Schuller, N. and Stein, O. and Rohrer, F. and
Wahner, A. and Richter, A. and Burrows, J. P. and Beirle, S.
and Wagner, T. and Platt, U. and Elvidge, J. M.},
title = {{G}lobal distribution pattern of anthropogenic nitrogen
oxide emissions: {C}orrelation analysis of satellite
measurements and model calculations},
journal = {Journal of Geophysical Research},
volume = {111},
issn = {0148-0227},
address = {Washington, DC},
publisher = {Union},
reportid = {PreJuSER-49906},
pages = {D05312},
year = {2006},
note = {Record converted from VDB: 12.11.2012},
abstract = {[1] Nitrogen oxides play a key role in tropospheric
chemistry; to study the distribution patterns of the
corresponding anthropogenic emissions ( fossil, industrial,
waste), we use three independent data sources: GOME
measurements of the tropospheric NO2 column density fields,
the EDGAR 3 emission inventory as an estimation of the
anthropogenic NOx emissions and nighttime images of
worldwide human settlements seen by the DMSP OLS satellite
instrument as a proxy for these emission patterns. The
uncertainties are not known precisely for any of the fields.
Using the MOZART-2 CTM, tropospheric column density fields
are calculated from the emission estimates, and
transformations are developed to turn the GOME columns into
anthropogenic emission fields. Assuming the errors of the
three data sources ( GOME, EDGAR, lights) to be independent,
we are able to determine ranges for the pattern errors of
the column density fields and values for the pattern errors
of the source fields by a correlation analysis that connects
relative error (co) variances and correlation coefficients.
That method was developed for this investigation but can
generally be used to calculate relative error variances of
data sets, if the errors of at least three of them can be
assumed to be independent. We estimate the pattern error of
the EDGAR 3 anthropogenic NOx emission field as ( 27 +/-
$5)\%,$ which can be reduced by combining all fields to ( 15
+/- $3)\%.$ By determining outliers, we identify locations
with high uncertainty that need further examination.},
keywords = {J (WoSType)},
cin = {ICG-II / JARA-ENERGY},
ddc = {550},
cid = {I:(DE-Juel1)VDB48 / $I:(DE-82)080011_20140620$},
pnm = {Atmosphäre und Klima},
pid = {G:(DE-Juel1)FUEK406},
shelfmark = {Meteorology $\&$ Atmospheric Sciences},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000236270600001},
doi = {10.1029/2005JD006068},
url = {https://juser.fz-juelich.de/record/49906},
}