Baltic Transport Outlook 2030

Time schedule:
June 2010 to December 2011

Applicant: Trafikverket (Swedish Transport Administration) and European Commission
Report: Main Task 2: Drivers of transport demand and supply

Project consortium:
Main Partners:
Tetraplan AS, Denmark
Progtrans AG, Switzerland
Christian-Albrecht-University, Germany
Hamburg Port Consulting, Germany
Centre for Maritime Studies, Finland

Rapidis ApS (DK),
DTU Transport (DK),
Gdansk University (PL).

Consortium leader: Tetraplan AS, Copenhagen, Denmark

General project objectives
The overall aim of the project is to achieve better prerequisites for national long term infrastructure planning in the Baltic Sea region to make the region more accessible and competitive. The Baltic Transport Outlook will contribute to:

  • A common view of the region’s development concerning transport flows and economic growth
  • A joint awareness of future challenges and potentials
  • Better knowledge exchange of national and regional transport systems.

The core of the project is a study with the following elements:

  • Describing current transport flows, infrastructure status, bottlenecks of both infrastructural and administrative character and the use of the transport system in the Baltic Sea region as well as into and from the Baltic Sea.
  • Including all modes of transport: road, rail, maritime, civil aviation and pipelines, for both goods and passengers.
    Making forecasts/scenarios for 2016 and year 2030.
    Recommending measures for managers of the Baltic Transport system – short term and long term.
  • Ensuring that the results, based on high quality data, could be adapted in different countries' national transport strategies.
  • Achieving synergies within the framework of the Northern Dimension and other relevant EU projects.

Contribution of the Institute for Regional Research (IfR), University of Kiel

Project Leader at the Institute: Dr. Artem Korzhenevych

The IfR participates in the development of growth scenarios for the Baltic Sea Region and applies the trade prediction model to produce transport forecasts in Task 2 (Drivers of transport demand and supply).