Buildings are responsible for nearly 40% of global greenhouse gas emissions. The mass adoption of deep energy retrofits (DERs) represent a key opportunity to reduce this figure. DERs involve overcladding candidate buildings with prefabricated insulated panels and replacing their mechanical systems with efficient alternatives. Altogether, this contributes to energy savings of 50-80%.

To make a meaningful difference in the fight against climate change, DERs must be deployed on a large scale following the success of a few carefully chosen pilot projects. To save time and expense in selecting the first of these buildings, Reconstruct is developing a suite of tools that can quickly pick them out of a provided building stock.

The tool suite assesses the technical feasibility of a pilot project and its potential emissions savings (both operational and embodied) and estimates the costs of a retrofit according to the inputted interests of multiple stakeholders. It operates off a universal database which stores building information to maximize the interoperability of its component parts. In the future, machine learning and Google Maps API could be combined to automate this data collection process and fill in commonly encountered data gaps. When completed, this tool suite will support pre-retrofit decision-making to facilitate wider deep energy retrofit adoption in Quebec and across Canada.