Carbon Track and Trace (CTT)
The Carbon Track and Trace (CTT) project is intended to provide cities with real-time greenhouse gas (GHG) measurement capability. Traditional methods of building and maintaining municipal GHG emission inventories are expensive, time-consuming, and are of questionable utility for mitigation decision and planning support processes. CTT couples low-cost, open source Internet of Things sensors to a Big Data analytics platform that provides cities and regions with a unique capacity to directly measure the impacts of their policy and planning decisions and to develop a semi-autonomous system for building, maintaining, and reporting their annual GHG emissions.
CTT is a joint project of the NTNU departments of Architecture and Design (AB) and Computer Science (IDI) and part of NTNU Smart Sustainable Cities.
CTT is funded by LoCaL, the Low Carbon City Lab flagship of Climate-KIC.
A Measurement-Driven Approach to Understand Urban Greenhouse Gas Emissions in Nordic Cities. Dirk Ahlers, Patrick Driscoll, Frank Alexander Kraemer, Fredrik Anthonisen, John Krogstie. Norwegian Informatics Conference 2016.
Understanding challenges in municipal greenhouse gas emissions inventories. Dirk Ahlers, Patrick Driscoll. IEEE ICE ITMC 2016.
CTT 2.0 Carbon Track and Trace, NILUs know-how and experience from previous research activities. Sundseth, K., Castell, N., Marsteen, L., Dauge, F.R., Ødegård, R., Driscoll, P., Anthonisen, F., Vesterkjær, A. NILU report, 34/2016. Kjeller: NILU.
Supporting Municipal Greenhouse Gas (GHG) Emission Inventories Using Business Process Modeling: A Case Study of Trondheim Municipality. Dirk Ahlers, John Krogstie, Patrick Driscoll, Hans-Einar Lundli, Simon-James Loveland, Carsten Rothballer, Annemie Wyckmans. Business Process Management Workshops 2016, Revised Papers. (Workshop on Sustainability-Aware Business Process Management @ BPM2016), LNBIP vol.281, Springer, 2017.
Deliverables and Reports
CTT Phase 2
This document is the high-level description of the project results and technical achievements. The main result consists of a prototype GHG measurement and reporting system showcasing the components from sensors and measurement devices through Internet of Things sensor networks, gateways, cloud storage, data collection, processing, and visualization for stakeholders and towards decision support. It additionally explores different sensor setups and processing systems, integration into emission inventories, and gap analyses as a roadmap from manual to automatic data gathering and emission monitoring and inventories.
The technical architecture describes the overall CTT concept, the coordination and cooperation of its components, deployment and installation in the field, data flows, components, and analysis and visualization systems.
This report discusses requirements, hardware, components, and initial air quality analyses of an analysis prototype.
This report provides an overview of the data flow from the sensors through the cloud and to databases to provide real-time data from the IoT sensors to different user groups including decision makers and the public. Collection of data from other sources is discussed and a flexible visualization tool is presented.
This study provides a data quality assessment based on cities’ reported GPC Inventories, investigating the existing data quality and availability of transport-related emissions in cities that currently used the GPC reporting methodology.
Data on GHG emissions has become the cornerstone for implementation of mitigation projects. This report discusses the potential of real-time sensor-based data to be integrated into GHG inventories and how the integration could be pivotal for monitoring policy impact.
This report develops insight into the processes within municipalities to estimate effort and quality of existing emission inventories and systems. It gives better insight into pressure points for cities and ways that CTT can support cities aiming at understanding and reducing their emissions. This study helps close the cost-benefit information gap, comparing activity-based data with automated, sensor-based emission inventories, both in a short- and long-term perspective. The study helps to understand present perceptions and future expectations for the scale of benefits and co-benefits when applying activity- or sensor-based systems to specific energy sectors.
Visualization prototype of a 3D city model of Vejle with access to live data from installed sensors.
CTT Phase 1
Some key topics discussed in this gap analysis include calculation vs. measurement, system boundaries count, data quality and reliability, the statistics data problem, multiple data sources and multiple reporting platforms.
The workflow analysis presented here analyses the data collection and processing for municipal GHC emission inventories and highlights issues of complexity, data sourcing, data quality, and automation.