CTT 2.0 Carbon Track and Trace presentation

Text
Text
CTT 2.0
Carbon Track & Trace
Dirk Ahlers, NTNU
Ulan Bator, 06.04.2016
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
What is the basic problem? GHG
emissions are not easy to track
[GPC Standard]
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?
From inventories to workflows
Workflow Analysis
Requirements
Gap Analysis
Workflow System
From workflows to sensors
Sensor Network
Inventory
Workflow
Emissions Monitoring
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
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
Sensor/networks system
[NASA, Wikipedia, tradlosetrondheim.no, CTT, NTNU]
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
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
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
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
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
• 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
climate-kic.org
dirk.ahlers@idi.ntnu.no
http://carbontrackandtrace.com/
http://smartsustainablecities.org/
https://www.ntnu.edu/smartcities/
1 of 17

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CTT 2.0 Carbon Track and Trace presentation

  • 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
  • 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 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
  • 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