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Developing strategies for efficient, reliable and timely elimination of greenhouse gas (GHG) emissions and eventual reduction of GHGs in the atmosphere requires extensive data, analysis and modeling. Models must be tuned and validated by comparison with real-world experiences. Our efforts in this area are aligned with the focus of the Boltzmann Institute on GHG emissions associated with buildings in Canada, beginning with Ontario and more specifically the Greater Toronto and Hamilton Area (GTHA).

Significant progress has been made on collection of needed data and development of code to use the data in analyses and modeling. This includes searches and review of published literature for relevant international data, analysis and modeling tools and results covering diverse aspects of building energy efficiency improvements and decarbonization of the energy supply.

Scientific and technical data at the international level and especially from European countries tends to be broadly accessible and of high quality. Many publications provide excellent detail on various building decarbonization and district energy initiatives, programs and research efforts. There are numerous software systems / frameworks freely available to perform analysis and modeling for building energy use, but most of these are too focused on details of individual buildings and components rather than facilitating analysis and modeling of large communities with a great diversity of buildings.

Several Canadian sources provide relevant and high quality data. Code has been developed to automatically acquire and do preliminary processing of the following:

  • historical and current hourly temperature, dew point and other data at weather stations across Canada
  • geographic units, attributes and coordinates with population and residence counts at all levels of aggregation from the 2021 Canadian census
  • comprehensive energy usage data tables from Natural Resources Canada (NRCan), with ample historical data but far less geographic granularity than we would hope to have
  • historical and current hourly electricity data from the Independent Electricity System Operator (IESO).

Efforts are underway to obtain good data on the costs of residential building retrofit measures, electric power system upgrades and expansion, and implementation and operational costs of district energy systems for residential communities. District energy systems include a variety of heat (and cold) sources and thermal energy storage systems, for which information is also being collected.

Much more data is still needed to support the desired level of analysis and modeling. The needed data is often held by public or private sector entities who need to be persuaded of the importance and benefits of sharing it. This work will continue indefinitely.

Amongst other information, obtaining the following remains a priority:

  • details of energy supply and consumption at as granular level as possible, including hourly rates and future projections. Ideally this will include data from local electricity distribution companies and fossil fuel suppliers to give greater detail than is available from the IESO.
  • inventory of buildings – purpose / occupancy, geometry, construction type, age, energy and water usage, solar exposure, etc.
  • details of GHG emissions (embodied carbon) associated with the extraction of materials, shipping, manufacturing, etc. of products used in the construction or retrofitting of buildings and their associated systems (HVAC, etc.).

More strategic analysis is being undertaken to evaluate the long-term viability of various potential GHG reduction pathways. This often involves order of magnitude calculations of implementation times, resource requirements, energy flows, costs, risks and long-term consequences and can help to validate innovative ideas or avoid dead ends. 

Results of all the work described above will be published or otherwise made accessible in due course.