English Abstract Anthropogenic activities have dramatically altered the
chemical composition of the atmosphere. The focus of this study is on the
composition of the troposphere, mainly associated with ozone which acts as a
greenhouse gas, is damaging to living organisms, and co-determines the
oxidative capacity of the atmosphere. A coupled tropospheric chemistry -
general circulation model (ECHAM) has been applied to the simulation of
tropospheric ozone distributions, using emissions of ozone precursors (NOx,
CO, higher hydrocarbons) as boundary conditions. The model has been
extended with detailed parameterizations for dry deposition of trace
species, for the lower stratospheric ozone concentration which is used as
boundary condition, and for the treatment of higher hydrocarbon species.
The model has been extensively evaluated by comparison with observed
long-term climatological data and with in-situ measurements from specific
measurement campaigns. A proper representation of all ozone sources and
sinks is prerequisite to an accurate estimate of the anthropogenic ozone
increase in the troposphere. The representativity of
stratosphere-troposphere exchange, which forms a major source for ozone in
the troposphere, and its contribution to tropospheric ozone levels has been
studied. Simulations have been performed using pre-industrial, present-day
and future emission scenarios as boundary conditions, and the radiative
forcing associated with the ozone increases has been estimated. The
annually averaged global tropospheric ozone contents from these simulations
are 190 Tg O3, 271 Tg O3, and 332 Tg O3 in 2025, corresponding to a global
annual net radiative forcing at the tropopause of 0.42 W m-2 between the
pre-industrial and the present-day simulations, and of 0.31 W m-2 between
the present and future simulations. A second focus of the study is the
simulation of the sulfur cycle. The model was part of a model
intercomparison exercise, that aimed to document the present status of
global sulfur cycle models and to identify major uncertainties in process
parameterizations.
