The last 30 years have seen fossil fuel consumption grow by a factor of four. The use of fossil fuels is an important source of environmental change since its combustion results in emissions of different pollutants (carbon dioxide, sulfur dioxide, nitrogen oxide, volatile organic compounds, particulate matter etc.) into the atmosphere. Optimal emission control strategies must therefore be worked out as soon as possible but emission transformations in the atmosphere are extremely complex to understand and hence to forecast. Such complexity arises from the fact that many factors play an important role in these transformations (atmospheric dynamics, complex chemistry, solar radiation, etc.). Since numerical air quality models are able to account for all these factors, they constitute the only reasonable approach to understand and control air pollution.

Since several years, the modeling group of the "Laboratory for Air and Soil Pollution" (LPAS) at the EPFL focuses its work on the improvement, the validation and the use of Eulerian air quality models.

• Model improvement and model development: The group contributed to improve the speed and the precision of several numerical techniques (transport algorithms, chemical mechanisms, massive parallelisation) used in different existing models (see Models applied in the group). New models are also developed for specific simulations: 1) a mesoscale wind model adapted for alpine complex terrain and urban areas, and 2) a pollutant transport model designed to study the coupling between different gas phase chemical mechanism, the aerosol formation and the solar radiation (see Project development ).

• Model validation and model application: The models are regularly validated on various sites using the measurements obtained during different intensive campaigns (see Model studies). After the validation step the models are applied to predict the impact of abatement strategies, to study the effect of different mechanisms (gas phase chemical mechanisms, aerosol formation mechanisms) on the photo-oxidant formation or to estimate the model uncertainties.