Authors: Andreas Geiges (Climate Analytics), Steffen Fürst (Zuse Institute Berlin, Global Climate Forum), Gesine Steudle (Zuse Institute Berlin, Global Climate Forum), Sarah Wolf (Freie Universität Berlin, Global Climate Forum), Carlo Jaeger (Global Climate Forum, Arizona State University, Beijing Normal University)

Description: This data set contains output from the Mobility Transition Model (MoTMo), an agent-based model of private mobility demand in Germany. Time series over 180 steps (representing the years 2005-2035 in bi-monthly resolution) provide the numbers of agents choosing each one of five mobility types (combustion car, electric vehicle, public transport, car sharing, and non-motorized) and the resulting greenhouse gas emissions. The values are further categorized into eleven household types and 16 regions (the Federal states). Each time series corresponds to one out of over 500 scenarios that arise from combinations of ten options that can be switched on or off in the model, three policy measures, three investment strategies, and four external evolutions, where max. two options per category can be chosen.

Background: see the following paper.

Original Purpose: Originally, the scenarios were produced for use in the Decision Theatre – a communication format for scientists and stakeholders where participants discuss sustainable mobility supported by interaction with the model to explore potential futures.

Questions: Given the structure of combinations of options underlying the 500+ scenarios, find out what can be said about the effects of single options and their combinations (e.g. per Bundesland or per household type).

Contact: Sarah Wolf (, Steffen Fürst (

Download: here

License: 4.0 International


Explanatory slides from the Opening Day: here


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