Options
2012
Report
Title
Bottom-up quantifications of selected measures to reduce GHG emissions of transport for the time horizons 2020 and 2050. Cost assessment of GHG mitigation measures of transport
Title Supplement
Deliverable D 3.1 (D3); Annex 1: Road Technology Measures; Annex 2.1: Road Mode - Universal Policy Measures; Annex 2.2: Road Mode - Urban Measures; Annex 3: Rail Transport Mode Measures; Annex 4: Shipping Mode Measures; Annex 6.1: Alternative Fuel Measures - Biofuels; Annex 6.2: Alternative Fuel Measures - Hydrogen
GHG-TransPoRD. Reducing Greenhouse-gas Emissions of Transport Beyond 2020: Linking R&D, Transport Policies and Reduction Targets
Grant Agreement Number: 233828. Contract No: TCS8-GA-2009-233828
Abstract
This report extends the analysis of single measures (i.e. technologies and policies) to reduce GHG emissions of transport by a cost assessment for each measure. Costs are assessed from different perspectives. In particular the user perspective and the society perspective have been applied for the analysis in GHG-TransPoRD. As a starting point an approach consisting of five levels of sophistication for cost assessments has been developed to provide a generic framework for the cost assessment. The most sophisticated levels were based on the learning curve concept. However, it turned out that these concepts were applicable for road technologies and biofuels only, while the empirical database for other modes was too limited. Thus depending on the measure abatement cost by measure have been assessed taking the different perspectives and applying different levels of sophistication. This limits the comparability of abatement cost across modes, though within each mode / area abatement cost of different measures should be comparable. Draft cost estimates have been presented and discussed with stakeholders at the 3rd workshop <http://www.ghg-transpord.eu/ghg-transpord/inhalte/events/workshop3.php> of GHG-TransPoRD. Additionally to the cost assessment a patent analysis is carried out on major technologies like fuel cells, hybrid and electric vehicles, lithium-ion batteries and biofuels. This analysis should support the assessment of future cost of such technologies. These cost trends or directly the learning curves will be implemented in the GHG-TransPoRD models for the scenario analysis in WP4. These trends constitute the main output of this deliverable.
Author(s)