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CTT 2.0 Carbon Track and Trace presentation

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CTT 2.0 Carbon Track and Trace presentation

  1. 1. Text Text CTT 2.0 Carbon Track & Trace Dirk Ahlers, NTNU Ulan Bator, 06.04.2016
  2. 2. Carbon Track & Trace - CTT • Monitoring, Reporting, Understanding of city-level greenhouse gas emissions • Both emission inventories and real-time local measurements • Better accounting leads to better prioritization of mitigation projects • Part of larger SmartCities approaches
  3. 3. What is the basic problem? GHG emissions are not easy to track [GPC Standard]
  4. 4. Approach: Set up repeatable processes • Gap Analysis • What can be improved to implement the standard? • Workflow Process • How is the current workflow, where does data come from? • Requirements Definition • How can this be structured and put into a repeatable, automated process?
  5. 5. From inventories to workflows Workflow Analysis Requirements Gap Analysis Workflow System
  6. 6. From workflows to sensors Sensor Network Inventory Workflow Emissions Monitoring
  7. 7. 7 2016 activities •Deployment of sensor network in Trondheim and Vejle •Development of an analytics framework of GHC emissions •Work towards GPC-compliant inventories •Integration of emission data into city planning and decisions support •Development of a business plan, fundraising, and scaling out
  8. 8. 8
  9. 9. Ecosystem • CTT 2.0 consortium • NTNU, DTU • ICLEI-World, ICLEI-Europe, LSCE, South Pole Group, Virtual City Systems • Trondheim Municipality, Vejle Municipality, T:Lab, NumaScale, ICLEI-Europe, Sør-Trøndelag Fylkeskommune, Norwegian Institute for Air Research • Additional local projects, collaboration with DTU, H2020 proposals, Smart Sustainable Cities initiatives
  10. 10. Sensor/networks system [NASA, Wikipedia, tradlosetrondheim.no, CTT, NTNU]
  11. 11. Fundraising / self-sustainability • Inclusion of TTO (NTNU Technology Transfer Office), T:Lab, DTU Office for Innovation services • Business model: Provide cities with inventory methods to provide clear business cases for investments for mitigation strategies, coupled with sensor networks and IoT • Financial independence by the end of the project • Pursue contracts with municipalities and seek seed/startup capital • Additional multipliers from projects, innovation funds, city buy-ins
  12. 12. 12 Climathon 24-hour hackathon Trondheim 7-8 January 2016 The challenge: How can you use existing open datasets to calibrate and check official reported emissions from Statistics Norway (SSB)? Climathon winners: Team Polarbears: Atle Vesterkjær (Numascale), Jie Ren, Arne Jenssen, Pål Preede Revheim
  13. 13. 13 Seeing the effect of local political measures “Nordre avlastningsvei” opened in May 2010 [a shortcut road that leads motorists around the city center] LNG busses 2010 The air quality measurements in the city center shows a clear improvement after May 2010 In order to measure the effect of local actions you need local sensors Open datasets: Climathon winners: Team Polarbears: Atle Vesterkjær (Numascale), Jie Ren, Arne Jenssen, Pål Preede Revheim
  14. 14. 14 Initial result: Trondheim emitted ~14% less from private transport than the national average in 2009 Potential for further development: Data from more checkpoints e.g. toll posts and parking (with information on the vehicle). Data for public transport (busses) Verification of traffic emission Traffic at 4 checkpoints in Trondheim Composition of the car fleet Travel habit survey Survey of travels of ~ 6000 persons in the Trondheim-region Open datasets Population demographics of Trondheim Average emissions of different types of cars Climathon winners: Team Polarbears: Atle Vesterkjær (Numascale), Jie Ren, Arne Jenssen, Pål Preede Revheim
  15. 15. 15 The satellite data is applicable as a reference for: - Comparing Trondheim with non-inhabited regions to isolate man-made emissions - Comparing with other cities to see relative changes in trends - Used Together with ground sensors for - Calibration ACOS Satellite data For the Trondheim climathon Team Polarbears made a python program that read all the netCDF files from the satellite and extracted the CO2 data for coordinates close to Trondheim High accuracy (± 1 ppm) Low spatial resolution (~ 1e2 km) Low temporal resolution (weekly orbit overlap) There is a seasonal variation due to change in levels of photosynthesis, weather/cloud coverage and energy usage patterns. 2013 Trondheim area 2008 Climathon winners: Team Polarbears: Atle Vesterkjær (Numascale), Jie Ren, Arne Jenssen, Pål Preede Revheim
  16. 16. 16 • Open datasets can reveal patterns in emissions. • It is important to use local data to see effects of local actions. • A lot of useful data is collected but not always available/used (e.g. toll road statistics). • To get the most out of the existing open datasets, we need to invest in ground sensors. This will enable detailed monitoring of city-level emissions. • Good data is a foundation for better decision making. Conclusion
  17. 17. climate-kic.org dirk.ahlers@idi.ntnu.no http://carbontrackandtrace.com/ http://smartsustainablecities.org/ https://www.ntnu.edu/smartcities/

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