Objective
Addressing emissions from transport is becoming increasingly important due to its increasing contribution to total greenhouse gas emissions and the link to high levels of toxic pollutants in places with a high concentration of transport activity. The contribution of freight transport to these issues is already significant, and will become more so due to continued globalisation of supply chains and further global economic growth.
Efforts to address these issues are already underway. Transport companies have for a long time focused on their own activities because it is good business sense.
More recently, collaborative green freight programs have been developed. Several well-established industry-led green freight programs (Green Freight Europe, Lean & Green, ECO Stars etc.) developed to meet differing needs – operational data sharing to support benchmarking & reporting, efficiency improvement, reduction of toxic emissions in urban areas etc.
Public authorities are also taking a greater interest because of targets to reduce transport CO2 emissions and improve air quality. They are investigating a wide range of mechanisms, from incentives to access restrictions, and from vehicle-level certification of emissions to legislation requiring reporting.
There is much activity ongoing in this area; however, much of it takes place in isolation. This creates problems – for example, confusion over the role of different programs, disagreement over the most effective mechanisms that can be used to calculate and report emissions, where support is most needed to encourage certain behaviours, or ignorance of practical measures under development.
The overall goal of LEARN is to establish co-ordinated networks of industry, government and civil society stakeholders and build on existing initiatives to drive consistent and transparent emissions measurement and reporting across the global logistics supply chain.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- social sciencessocial geographytransportfreight transport
- engineering and technologyenvironmental engineeringair pollution engineering
- natural sciencesearth and related environmental sciencesenvironmental sciencespollution
- natural sciencescomputer and information sciencesdata sciencedata exchange
- social sciencespolitical sciencespolitical policiescivil society
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Programme(s)
Topic(s)
Call for proposal
(opens in new window) H2020-MG-2016-2017
See other projects for this callSub call
H2020-MG-2016-SingleStage-RTD-MOVE
Funding Scheme
CSA - Coordination and support actionCoordinator
1017 EM AMSTERDAM
Netherlands