Subventions et des contributions :

Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2022-2023)

Life cycle assessment (LCA) is increasingly required to support private-sector supply-chain requirements, comply with regulatory disclosure and content requirements, and obtain third-party sustainability certifications. While LCA has been a tool for reducing environmental impact, it is increasingly becoming a prerequisite for market access. My research program is focused on expanding the scope of LCA, integrating LCA data and methods, and democratizing LCA. This research proposal will support the goals of my research program by developing a framework and computational structure for modular, integrated hybrid LCA.

Hybrid LCA models use process-level data to provide a detailed analysis of some components of a system and input-output (IO) data, generally industry average data, to fill gaps where detailed data is not available. Integrated hybrid LCA models, which computationally integrate process- and IO-based data, have been developed and presented for a number of specific case studies. It's not clear if the modeling components were computationally integrated in these studies. None of these models have been operationalized for general use. My colleagues and I recently developed and operationalized an integrated hybrid LCA model for general use. It allows a user to input their own detailed process-based data as available, use process-data for activities included in the model, and rely on industry average data when detailed data is not available. As we incorporate more processes, economies, and impact assessments methods into the model, it will become increasingly more complex. This is especially true for life cycle inventory data or life cycle impact assessment methods that don't follow the traditional LCA mold. In addition, the ability to integrate an organization’s environmental (or other) data into an integrated hybrid LCA model would expand its usefulness and accuracy. Emerging impact assessment methods and organizational data are often structured differently than process- or IO-based LCA data. Scalable and flexible approaches for integrated hybrid LCA are needed. The proposed research will develop a framework and computational structure that treats process-level, IO-based, impact assessment, and other relevant data as modules to be incorporated into a modular integrated hybrid LCA model. To test the approach, a process-based dataset, an industry-specific dataset, and a novel impact assessment method will be developed using Canadian data and incorporated into the modular integrated hybrid LCA model. The process-based dataset will focus on energy and transportation in Canada; the industry-specific dataset will focus on the Canadian aerospace and aviation industry; and the novel impact assessment method will focus on impacts to occupational health and safety. The resulting methods will be disseminated in a format that can be used by Canadian industry and policy-makers.