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TOSCA. Rail freight...
TOSCA. Rail freight transport : Techno-economic analysis of energy and greenhouse gas reductions
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- Andersson, Evert (författare)
- KTH,Spårfordon,Järnvägsgruppen, JVG
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- Berg, Mats (författare)
- KTH,Spårfordon,Järnvägsgruppen, JVG
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- Nelldal, Bo-Lennart (författare)
- KTH,Trafik och logistik,Järnvägsgruppen, JVG
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visa fler...
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- Fröidh, Oskar (författare)
- KTH,Trafik och logistik,Järnvägsgruppen, JVG
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visa färre...
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(creator_code:org_t)
- 2011
- Engelska 38 s.
- Relaterad länk:
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http://www.toscaproj...
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https://urn.kb.se/re...
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Abstract
Ämnesord
Stäng
- In Stage 1 of the EU/FP7-funded project TOSCA (Technology Opportunities and Strategies toward Climate-friendly trAnsport) the techno-economical feasibility of different technolo-gies and means to reduce greenhouse gas (GHG) emissions is being analysed for different modes of transport. This is made over the long-term perspective until 2050, with 2009 as the reference year. This is the report on the rail freight transport market, applicable to the European Union (EU-27).The analysis presented in this report estimates that a number of efficient technologies and means are available, individually and in combination, to significantly reduce energy use and the resulting GHG emissions on the rail freight market until 2050. The analysis has considered the following technologies and means:– heavy freight trains (high payload capacity per metre of train as well as longer trains)– eco-driving, including traffic flow management– energy recovery– high-efficiency machinery in locomotives and electric supply– low air drag– incremental improvements, in particular reduced tare mass of wagons.Despite anticipated higher train speeds in most future train operations the above-mentioned technologies and means have, according to the analysis, the potential to reduce the average energy use per net-tonne-km (tkm) of payload by 40–50 % until 2050. As a consequence also the direct and indirect GHG emissions will be reduced. Energy use and GHG emissions are measured per net-tonne-km, assuming representative load factors in different operations.
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