Scaling up methodology CO 2 emissions: Stage 1

1. Scaling up methodology CO2 emissions: Stage 1 Dick Mans, Ecorys Eline Jonkers, TNO IoannisGiannelos, Ecorys DorinPalanciuc, TeamNet

2. Amitran Objectives • Amitran aims to: • Develop a CO2 assessment methodology for ICT measures that includes multimodal passenger and freight transport and that takes into account the whole chain of effects from user behaviour to CO2 production • Design open interfaces for models and simulation tools implementing the project’s methodology • Establish a generic scaling up methodology and a publicly available database with statistics to translate local effects to the European level • Validate the proposed methodology and its implementation by using data available from other projects and studies • Produce an online checklist and a handbook that can be used as a reference for future projects

3. Scaling up methodology • From local level to higher level (such as country or EU-27) • Previous steps in methodology deliver results at local scale (e.g. city) • Policy and business decisions are taken based on expected effects at a more global level • Two methods for scaling up: • Direct method using statistical information • Modelling, using macroscopic multimodal traffic model

4. Scaling up Outlook • General outline of scaling up methodology has been developed • Next step is collection of links to data for scaling up at EU and national level • Further development and implementation of KB • Validation of the method with selected use cases

5. Scaling up methodology CO2 emissions: Stage 2 Dick Mans, Ecorys Eline Jonkers, TNO IoannisGiannelos, Ecorys DorinPalanciuc, TeamNet

6. ICT applications in traffic and transport in EU Introduction of Amitran Scaling up methodology Limitations and ITS systems Scaling up Knowledge Base Scaling up Outlook

7. Amitran Consortium, facts & figures • Amitran: • Assessment Methodologies for ICT in Multimodal • Transport from User Behaviour to CO2 reduction • Budget: 2.6 M€ • Funding: 1.9 M€ • Co-funded by the 7th Framework Programme, • Duration: 30 months • Dates: November 2011 – April 2014 • Coordinator: TNO • Contact: Gerdien Klunder (TNO), • gerdien.klunder@tno.nl • Website: www.amitran.eu ECORYS TNO DLR TEAMNET PTV ERTICO TECNALIA

8. Amitran Objectives • Amitran aims to: • Develop a CO2 assessment methodology for ICT measures that includes multimodal passenger and freight transport and that takes into account the whole chain of effects from user behaviour to CO2 production • Design open interfaces for models and simulation tools implementing the project’s methodology • Establish a generic scaling up methodology and a publicly available database with statistics to translate local effects to the European level • Validate the proposed methodology and its implementation by using data available from other projects and studies • Produce an online checklist and a handbook that can be used as a reference for future projects

9. Amitran approach • Amitran will develop and deliver a standardised methodology dedicated to the evaluation of CO2 impacts of ITS • Based on modelling (with real-world data as input) • Generic interfaces between model types • Broad scope: road traffic, rail, shipping, multi-modal, freight • Scaling-up to EU level (knowledgebase with links to traffic statistics) • Validation with stakeholders/FP7 projects and use-cases • Delivering online handbook

10. Scaling up in Amitran Framework • From local level to higher level • Policy and business decisions are taken based on expected effects at a more global level

11. Scaling up methodology • From local level to higher level (such as country or EU-27) • Previous steps in methodology deliver results at local scale (e.g. city) • Policy and business decisions are taken based on expected effects at a more global level • Two methods for scaling up: • Direct method using statistical information • Modelling, using macroscopic multimodal traffic model

12. Two scaling up methods Macro level Micro level Flow model Scaling up using modelling: if macro model is available at large scale! Emissions model CO2 emissions Large scale CO2 emissions Small scale Scaling up using statistics

13. Scaling up using statistics • Starting point: impacts on CO2 emissions at a local level as distinguished for different situations (such as traffic state, vehicle type, etc.) • For the same situations, data on the large scale level are needed • CO2 effects on a small scale are then scaled up using statistics on kilometres driven (for the relevant modes) under the specific situations

14. (Simple) example • When all vehicles are equipped, there is • no effect on 2.3% (3/133) of the total kilometres driven • a reduction of 5% on 37.6% (50/133) of the total kilometres driven • a reduction of 1% on 60% (80/133) of the total kilometres driven • The weighted average is then a 2.5% reduction of CO2 • emissions on the country level • (0% x 0.023 + 5% x 0.376 + 1% x 0.6).

15. Scaling up using macroscopic model • Is the model at the required level (country/EU), then direct effect of the system can be calculated by running the macroscopic model. • Optionally, the economic effect can be calculated with an appropriate model. A second run with the macroscopic model is performed to account for second order effects. • This method is most appropriate in case the effects of ITS that mainly affect macroscopic mechanisms in the network, such as mode or route change

16. Scaling up limitations • Scaling up possible if results on small scale are valid in other regions as well. • Network and type of system are very relevant • Motorways and rural roads usually possible • Urban environment can be more difficult

17. Scaling up for different ITS systems (1) • Navigation and travel information. If there is knowledge on the level and amount of travel options, the scaling up process can be made more reliable. • Traffic management and control: Depending on how specific the implementation of the system is and the network characteristics, the effects of the system can be used for scaling up. • Demand and access management: Scaling up to EU level is likely not to be reliable for these types of systems. However scaling up within a country could be done.

18. Scaling up for different ITS systems (2) • Driver behaviour and eco-driving systems: When local results are available, scaling up is possible and pretty straightforward. • Logistics and fleet management: A reliable sample size for different classes of companies should be obtained. Then for the larger scale also the amount of companies in a certain class should be known. • Safety and emergency systems: scaling up is in most cases possible and pretty straightforward.

19. Amitran Scaling up Knowledge base (1) The knowledge base is structured as follows: • General information about scaling up • Detailed information about scaling up for specific user cases – the set of specific use-cases shall be updated and extended as the methodology is being employed in real-life usage cases • Examples of scaling up – for different transport modes, for passenger and freight transport, and for scaling up to different levels. • Links to data needed for scaling up – at European and national level.

20. Amitran Scaling up Knowledge base (2) • A wiki framework is used to host the KB • The wiki can be browsed freely • Only authorised users are allowed to contribute • Content of KB is structured in articles, and cross references will be used

21. Scaling up Outlook • General outline of scaling up methodology has been developed • Next step is collection of links to data for scaling up at EU and national level • Further development and implementation of KB • Validation of the method with selected use cases