A new method to assess the climate effect of mitigation strategies for road traffic

Emissions of road traffic crucially influence Earth's climate. The vehicle fleet emits not only carbon dioxide (CO2), but also nitrogen oxides (NOx), volatile organic compounds (VOC) and carbon monoxide (CO). The latter species lead to a production of ozone (O3) and a reduction of methane (CH4) in the troposphere. As the demand of mobility is expected to further increase in future, a reduction of the climate effect from road traffic emissions is indispensable. Therefore, it is essential to assess the climate impact of emission changes caused by technological trends and mitigation strategies for road traffic. Hereby, it is not only important to determine the impact but also the contribution of road traffic emissions on climate. Several studies have already quantified the impact of road traffic emissions on climate. But climate simulations with complex chemistry climate models are still computational expensive hampering the assessment of many road traffic emission scenarios. Consequently, an efficient method for quantifying the climate impact and contribution of mitigation options is required. Within the scope of this thesis, I developed a unique chemistry-climate response model called TransClim (Modelling the effect of surface Transportation on Climate) which assesses the impact and the contribution of road traffic emission scenarios on O3 and CH4 concentration as well as their corresponding radiative forcings. I tested various algorithms to find an efficient approach. The following approach was chosen: Road traffic emissions are split into seven emission regions. Climate simulations are performed with the global chemistry climate model EMAC by varying the road traffic emissions of NOx, VOC and CO in each emission region individually. These simulations deliver the input data for a look-up table (LUT) for each emission region. To determine, for example, the O3 concentration of a particular emission scenario, the difference of O3 to a reference simulation is computed by interpolating within each LUT. These O3 changes of each emission region are added to the reference O3 to obtain the new O3 concentration. Comparing the results delivered by TransClim with simulations of the complex global chemistry climate model EMAC reveals very low deviations (0.02-6 %). Thus, TransClim reproduces the results calculated by EMAC very well. To determine not only the impact but also the contribution of road traffic emissions to O3, OH and CH4 in TransClim, a so-called tagging method is applied. It attributes the concentrations of O3 to emission sources such as road traffic. This tagging method also determines the contribution of the short-lived species OH and HO2. However, the former version had certain shortcomings which I improved. It now applies not only to the troposphere but also to the stratosphere. Moreover, the sum over all contributions equals the total concentration. Additionally, I introduced a new tagging method which determines the contribution of road traffic emissions to CH4. Within the scope of this thesis, TransClim enabled to assess the climate effect of two scientific questions. First, the effect of three prospective mitigation options of German road traffic is quantified with TransClim. The future emission scenario including the strictest environmental regulations and emission controls leads to the strongest decrease of O3 and CH4 radiative forcing. Second, two scenarios have been constructed describing the cases that European vehicles use fuel blends containing a low and a high proportion of biofuels. Simulations with TransClim reveal that fuels with a low content of biofuels mainly reduce CH4 while fuels with a high content of biofuels reduce tropospheric O3. Summing up, TransClim offers a new method to quickly assess the climate impact and the contribution of mitigation strategies for road traffic in a sufficiently accurate manner. As TransClim simulates about 6000 times faster than a complex chemistry climate model, it enables to quantify the effect of many emission scenarios in different regions.