Environmental Engineering Reference
In-Depth Information
2.21 Influence of Biogenic Emission Estimates
on Ozone and PM10
1
1,2
Andreas Kerschbaumer and Peter J.H. Builtjes
1
Institut für Meteorologie, FU-Berlin, Germany
2
TNO, Utrecht, The Netherlands
Abstract
In this study we report results of REM_Calgrid (RCG) runs with two
different tree inventories over Europe. Both inventories are based on Corine-
Landcover information, the first comprising only 3 surrogate forest types and the
second specifying 126 individual tree species. Biogenic VOC and NO emissions
were estimated and the model was tested for a summer 10 days period in 2005.
Biggest differences in biogenic emissions were found in Northern Europe, Spain
and the Alps. A significant improvement was achieved in Ozone simulations
when biogenic emissions were derived from the comprehensive forest database.
Also, secondary organic aerosol (SOA) production rate is enhanced especially
in Scandinavia, Northern Russia and the Alps, giving more realistic SOA-
contributions to the total PM10 concentrations.
Keywords
SOA, RCG, aerosols, tree inventories, biogenic emissions
1. Introduction
Ozone and atmospheric aerosols (PM10) are known to have adverse health effects.
While the formation of ozone and of secondary inorganic aerosols (SIA) is well
understood, and thus modelled with satisfactory accuracy, there is still a lack of
knowledge about secondary organic aerosols (SOA). Even the relative importance
of secondary organic compounds in the total PM10 mass is not clear. It is
generally accepted that biogenic emissions play an important role not only in the
formation of ozone but also of SOA. The estimate of biogenic VOC including
terpenes and isoprenes, and NOx, is still a challenging task and depends deeply on
the availability of an accurate description of the land. Furthermore, geographical
position, light availability and physiological situation of the plants may change
enormously these factors. The Chemistry Transport Model REM_Calgrid (RCG)
has been used to analyse the influence of different land-use-databases with
differing quantities of information on O3 and SOA. The first database comprises
13 different land-use-classes, the second one is a detailed forest inventory with
