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Road traffic emits not only carbon dioxide (CO 2 ), but also other pollutants such as nitrogen oxides (NO x ), volatile organic compounds (VOC) and carbon monoxide (CO). These chemical species influence the atmospheric chemistry and produce ozone (O 3 ) in the troposphere. Ozone acts as a greenhouse gas and thus contributes to anthropogenic global warming. Technological trends and political decisions can help to reduce the O 3 effect of road traffic emissions on climate. In order to assess the O 3 response of such mitigation options on climate, we developed a chemistry-climate response model called TransClim (Modelling the effect of surface Trans portation on Clim ate). It considers road traffic emissions of NO x , VOC and CO and determines the O 3 change and its corresponding stratospheric-adjusted radiative forcing. Using a tagging method, TransClim is further able to quantify the contribution of road traffic emissions to the O 3 concentration. The response model bases on lookup-tables which are generated by a set of emission variation simulations performed with the global chemistry climate model EMAC (ECHAM5 v5.3.02, MESSy v2.53.0). Evaluating TransClim against independent EMAC simulations reveals very low deviations of all considered species (0.01–7 %). Hence, TransClim is able to reproduce the results of an EMAC simulation very well. Moreover, TransClim is about 6000 times faster in computing the climate effect of an emission scenario than the complex chemistry-climate model. This makes TransClim a suitable tool to efficiently assess the climate effect of a broad range of mitigation options for road traffic or to analyse uncertainty ranges by employing Monte-Carlo simulations.

E-government portals at the local level are a vital part of the modernization of public administration. However, there are few research articles that focus on the informational success factors of these portal websites. As the foundation of more advanced service levels, informational offers still constitute the majority of e-government content. In this article, a model of e-government usage with a focus on informational offers is empirically tested. The four dimensions information attractiveness, information usefulness, information awareness, and ease of navigation are used as relevant criteria for user-based informational performance perception. Using structural equation modelling a moderating effect of local community interest can be shown. Citizens with low interest in their community show a higher dependency on information attractiveness, information usefulness, information awareness, and ease of navigation to predict the usage intention. Corresponding implications for future research and practitioners are derived.