Overview of the CTT 2.0 Carbon Track and Trace project

1. Text
Text
CTT 2.0
Carbon Track & Trace
Dirk Ahlers, NTNU
Ulan Bator, 06.04.2016

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. What is the basic problem? GHG
emissions are not easy to track
[GPC Standard]

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. From inventories to workflows
Workflow Analysis
Requirements
Gap Analysis
Workflow System

6. From workflows to sensors
Sensor Network
Inventory
Workflow
Emissions Monitoring

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

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. Sensor/networks system
[NASA, Wikipedia, tradlosetrondheim.no, CTT, NTNU]

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
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

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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

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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
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

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• 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. climate-kic.org
dirk.ahlers@idi.ntnu.no
http://carbontrackandtrace.com/
http://smartsustainablecities.org/
https://www.ntnu.edu/smartcities/