For modelling air quality, accurate emission data is crucial. These emission data is estimated based on socioeconomic numbers. Therefore multiple emission inventories, with individual advantages exist and deciding which inventory is the most suitable for a study is a difficult task. Including new emission inventories into a chemistry transport model (CTM) such as Tracer Model 5 in its massive parallel version (TM5-MP) can be significantly simplified by the use of an emission preprocessor. This emission preprocessor harmonizes the file format, as well as the unit and gridding of emission data to the users needs. In this work, the emission preprocessor High-Elective Resolution Modelling Emission System version 3 for global and regional models (HERMESv3gr) is adapted to be used with a modified version of the CTM TM5-MP. Besides the simplified introduction of new emission inventories, the use of HERMESv3gr enables more advantages, such as the adaptation of country specific modification factors to the original emission data to create emission datasets suitable to answer different research questions. This capacity was explored further, by investigating the influence of electric vehicles on global atmospheric composition. Emissions from 2013 were modified based on real-world statistics to create two scenarios: a world with only combustion cars being used and a world were subsequently electric vehicles are introduced. The comparison of the two modelling results showed that, with the adoption of electric vehicles, carbon monoxide is decreasing, while nitrogen oxides, ozone, particulate matter, and sulfur dioxide were increasing up to the year 2030. For a future scenario in 2050, were the electric scenario is defined with 100% adoption of electric cars, also ozone shows a decreasing trend. The study showed how complex the atmospheric consequences of switching to electric cars can be and emphasizes the importance of a clean energy sector.
S. W. Seemann (Thu,) studied this question.