A Decarbonization Framework for Existing Building Portfolios

加拿大到2050年实现净零碳排放目标的道路必须包括改造加拿大的建筑存量。我们的研究旨在达到以下目标：-首先，我们将扩展现有的知识库，这些知识库通常侧重于单个建筑物的翻新（一个具体案例和耗时的过程），并将其应用于大型建筑物组合。这需要超越建筑科学和建筑的研究；该项目将在加拿大的大型建筑组合中结合数据驱动分析和机器学习技术。-在气候变化的影响下，现在表现良好的建筑在未来将处于次优状态。该项目将考虑不同的气候变化情景，以优化改造措施，从而随着时间的推移产生稳健的性能。-由于投资回收期可能很长且充满不确定性，碳市场的波动往往会阻碍建筑业主投资于改造措施的意愿。该项目将应用随机风险分析来制定政策建议，以继续激励业主参与改造措施，同时使长期融资负担得起和可持续。该项目将通过聘请工程和金融背景的专家，为大型建筑组合开发一个多学科的脱碳框架。项目成果支持决策，并优先考虑加拿大大部分建筑存量的改造措施。

Canada's pathway to a net-zero carbon target by 2050 must include revamping Canada's building stock. Our study aims to achieve the followings:- First, we will extend the existing knowledge base that typically focuses on retrofitting individual buildings (a case-specific and time-consuming process) and apply it to large portfolios of buildings. This requires research that goes beyond building science and construction; this project will incorporate data-driven analysis and machine-learning techniques over large portfolios of buildings in Canada.- Buildings that perform well now will operate at sub-optimal conditions in the future under climate change. This project will consider different climate change scenarios to optimize retrofitting measures to yield robust performance over time.- Volatility in the carbon market tends to discourage the willingness of building owners to invest in retrofitting measures, as payback period can be long and full of uncertainty. This project will apply stochastic risk analyses to devise policy recommendations that will continue incentivizing building owners to engage in retrofitting measures while making long-term financing affordable and sustainable.This project will develop a multidisciplinary decarbonization framework, by engaging experts from both engineering and finance backgrounds, for large portfolios of buildings. The project outcome supports decision-making and prioritizes retrofitting measures on a significant portion of building stock in Canada.