Sie haben Javascript deaktiviert. Zur vollständigen Darstellung und Nutzung der Seite sollten Sie Javascript aktivieren.
Marlin Arnz

Marlin Arnz

Data

  • RLS-year 2019

CV from Marlin Arnz

Marlin Arnz

From 2012 to 2018 Marlin studied Industrial Engineering and Management at the TU Berlin, where he focused on the energy system transition and corresponding modelling techniques. In addition, he was involved in university politics and worked in student assistant jobs, mostly as a programmer. Marlin wrote his master thesis at the German Aerospace Centre, where he developed a mode choice model for the multidimensional evaluation of an innovative rail freight transport concept. Now he is a PhD student at the Workgroup for Infrastructure Policy at the TU Berlin and part of the graduate school EnergieSystemWende.

Short description of the doctoral thesis:

Energy demand of the renewable, integrated transport sector

The climate crisis requires a reinvention of energy systems worldwide. While 46 % of the electricity in Germany already comes from renewable sources (status 2019), 94 % of final energy consumption in the transport sector still relies on fossil fuels (status 2018). Thereof, road transport accounts for the largest share.
German aspirations to climate change mitigation include the transport sector transformation ("Verkehrswende") which consists of efficiency measures to improve the current system (e.g. electrified drive trains) as well as consistency and sufficiency measures affecting mobility behaviour (e.g. shifting traffic to energy-efficient modes, reducing transport demand). Both, the technical and the behavioural dimension are expected to have an evenly important mitigation potential.

Modelling traditionally supports such complex system analysis. Yet, the renewable energy demand of transport, commonly derived from energy system modelling with exogenous representation of transport or transport modelling with subsequent calculation of energy demand, is highly uncertain. This PhD project integrates both modelling strategies in order to generate realistic decarbonisation pathways for transport, which will then translate into both political implications and sensitivities of the renewable transport energy demand.