Geoscientific Model Development Discussions
www.geosci-model-dev-discuss.net
1991-9611
1991-962X
3
3
2010
10.5194/gmdd-3-949-2010
http://www.geosci-model-dev-discuss.net/3/949/2010/
http://www.geosci-model-dev-discuss.net/3/949/2010/gmdd-3-949-2010.html
http://www.geosci-model-dev-discuss.net/3/949/2010/gmdd-3-949-2010.pdf
949
1007
2010-07-07
SMOKE for Europe – adaptation, modification and evaluation of a comprehensive emission model for Europe
J. Bieser
johannes.bieser@gkss.de
A. Aulinger
V. Matthias
M. Quante
P. Builtjes
GKSS Research Center, Institute for Coastal Research, Max-Planckstr. 1, 21502 Geeshacht, Germany
Leuphana University Lüneburg, Institute of Ecology and Environmental Chemistry, Scharnhorststraße 1, 21335 Lüneburg, Germany
Institut fur Meteorologie, Freie Universität Berlin, Carl-Heinrich-Becker Weg 6-10, 12165 Berlin, Germany
TNO Built Environment and Geosciences, Air Quality and Climate Team, Princetonlaan 6, Utrecht, The Netherlands
The US EPA regional emission model SMOKE was adopted and modified to create
temporally and spatially distributed emission for Europe and surrounding
countries based on official reports and public domain data only. The aim is
to develop a flexible model capable of creating consistent high resolution
emission data for long-term runs of Chemical Transport Models (CTM). This
modified version of SMOKE, called SMOKE for EUROPE (SMOKE-EU) was
successfully used to create hourly gridded emissions for the timespan
1970–2010.
<br><br>
In this paper the SMOKE-EU model and the underlying European datasets are
introduced. Emission data created by SMOKE-EU for the year 2000 are evaluated
by comparison to data of three different state of the art emission models.
Differences of SMOKE-EU to those models were in the same range as the
differences amongst them. Further, concentrations of criteria pollutants
calculated by the CTM CMAQ using the four different emission datasets were
compared against EMEP measurements with hourly and daily resolution. Using
SMOKE-EU emissions O<sub>3</sub>, NO<sub>2</sub> and SO<sub>4</sub> could be modelled most reliably.
The amount of simulated concentrations within a factor of 2 (F2) of the
observations for these species are: O<sub>3</sub> (F2=0.79 <i>N</i>=329 197), NO<sub>2</sub>
(F2=0.55 <i>N</i>=11 465), and SO<sub>4</sub> (F2=0.62 <i>N</i>=17 536). The lowest values
were found for NH<sub>4</sub> (F2=0.34 <i>N</i>=7400) and NO<sub>3</sub> (F2=0.25 <i>N</i>=6184).
NH<sub>4</sub> concentrations were generally overestimated, leading to a fractional
bias (FB) averaged over 22 measurement stations of (FB=0.83±0.41) while
better agreements with observations were found for SO<sub>4</sub>
(FB=0.06±0.38, 51 stations) and NO<sub>3</sub> (FB=0.13±0.75, 18
stations).
<br><br>
CMAQ simulations using the three other emission datasets were similar to
those modelled using SMOKE-EU emissions. Highest differences where found for
NH<sub>4</sub> while O<sub>3</sub> concentrations were almost identical. The results of this
comparison confirm that it is adequate to use emissions created by SMOKE-EU
as input for CTMs.
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