Executive Summary

While circularity is often assumed to be climate-smart, which is defined as reducing greenhouse gas (GHG) emissions relative to the emissions associated with the production of virgin materials, the goals of closing material flows and reducing net GHG emissions relative to virgin materials are not always aligned. Inappropriately designed circular pathways could unintentionally counteract efforts to catalyze the climate transition. This report investigates the conditions that make circularity climate-smart by examining multiple circular pathways for seven discarded material streams (DMSs) across three key Canadian sectors.

The research conducted for this report identified structural similarities across circular pathways that are climate-smart, with the goal of providing evidence-based guidelines to support the development of an effective circular economy. The following seven DMSs from three key sectors were assessed:

• Textile sector: Cotton and polyester fibres.
• Construction sector: Wood, concrete, and plastic.
• Agrifood sector: Wet spent grain and fruit and vegetable residue.

For each DMS, various circular pathways were analyzed, including reuse, recycling, repurposing materials to other sectors, downcycling to lower quality applications, and energy recovery. A life cycle assessment (LCA) approach was used to evaluate the net GHG emissions avoided when a circular pathway substituted equivalent virgin production. Primary and secondary data were collected through field interviews, reviews of academic and industry literature, and the ecoinvent database. Using openLCA software and Microsoft Excel, the study modelled diverse circular pathways focusing on their operational structures, defined as a combination of geographical scaling in the form of transportation distances and technological configuration in the form of energy intensity. The LCA approach focused primarily on the quantification of GHG emissions. Given the uncertainties in the data, sensitivity analyses were performed in the form of best and worst cases to capture the variability in GHG emissions for each operational structure. A regression analysis was also performed to explore the underlying potential relationship between carbon budget, defined as the GHG emissions associated with the production of specific virgin resources substituted by a given circular pathway, and the maximum transportation and energy intensity thresholds that characterize the circular pathway.

Key findings highlight that circularity, when designed and implemented effectively, can lead to significant GHG savings. For example, in the textile sector, all circular pathways generate net GHG savings relative to substituted virgin materials, but there are significant differences across pathways: reusing saves approximately 154 to 260% more GHG emissions than chemical recycling; chemical recycling saves 94 to 620% more GHG emissions than mechanical; and mechanical recycling saves 104 to 630% more GHG emissions than downcycling. However, the GHG savings were not as consistent and pronounced in the agrifood and construction sectors, with only some circular pathways being climate-smart. The research also identified operational thresholds for achieving a minimum of 20% net GHG emissions reduction, aligning with Canada’s 2030 climate targets. The regression analysis revealed a linear relationship between carbon budgets and maximum thresholds of transportation and energy consumption for circular pathways, finding that one standard deviation increase in carbon budget (i.e., an increase of 3910 kg CO2e/t of virgin material) allows the energy consumption of a climate-smart circular pathway to expand by 65 686 MJ (i.e., 0.677 times the standard deviation of the energy consumption data distribution in the sample, which is about 97 025 MJ), and allows the transportation of a climate-smart circular pathway to expand by 53 288 t·km (i.e., 0.670 times the standard deviation of transportation data in the sample, which is about 79 535 t·km). While total carbon budget is an important determining factor for maximum geographical scale, GHG intensities of energy and transportation are equally important. The circular pathways in the agrifood sector use light commercial vehicles for collecting DMSs, which are GHG inefficient; and concrete recycling uses portable diesel-based electricity generators, resulting in high GHG intensity energy to run machines. These factors further explain why climate-smart circular pathways in the agrifood and construction sectors must operate within lower maximum thresholds of total energy consumption and transportation.

As diverse organizations work collaboratively to develop circular pathways, they should be mindful of design conditions that make circular pathways more likely to be climate-smart. This report concludes with several recommendations for consideration when designing circular climate-smart pathways.