Life Cycle Assessment of Municipal Solid Waste Management in the Region of Waterloo, Canada

Abstract

Waste generation is an unavoidable consequence of human activities. Recent studies have highlighted Canada as the second-largest waste generator per capita, with the Region of Waterloo, Ontario, exemplifying a dynamic urban region characterized by rapid economic and population growth. This project performs a consequential LCA of three different municipal solid waste management (MSWM) scenarios in the Region of Waterloo. Scenario 1 models a business-as-usual MSWM system where: organic waste is composted, recyclables are recycled, and residuals are disposed off in a landfill where electricity is generated because of landfill gas production and collection. Scenario 2 considers an incinerator for residual waste treatment, and an anaerobic digestion for organic waste, while the recycling process remains the same as in Scenario 1. Scenario 3 models the province's Extended Producer Responsibility (EPR) recovery targets for recyclables, maintaining the same treatment pathways for organic waste and residuals as in Scenario 1. The functional unit (FU) is set to the management of 1 ton of residential MSW in the Region of Waterloo in 2021. Data is collected from the Region’s database, LCA software and databases such as EASETECH and Ecoinvent 3.9.1, publicly available reports on waste composition in 2021, and literature. The waste-specific LCA software EASETECH is used; IPCC 2021 is selected for the Global Warming Potential (GWP100), and Traci 2.1 is selected for the following environmental impact categories: particulate matter formation (PM2.5), photochemical ozone formation, and eutrophication. Sensitivity analysis is conducted to further explore the influence of changes in assumptions made to assess the scenarios. Results indicate that Scenario 2 contributes to the least favorable results considering the GWP100, PM2.5, and eutrophication. Scenario 3 achieves the most significant offsets in GWP and photochemical ozone formation impact categories, with savings of 134% and 95%, respectively, in comparison to Scenario 1. When the GWP20 is selected instead of the GWP100, Scenario 1 becomes the least favorable scenario for MSWM, whereby the result increases from -35 kg CO2 eq per FU with a GWP100 to 119 kg CO2 eq per FU with a GWP20. Policymakers can prioritize the GWP20 results due to the immediate impacts of gases with shorter lifetimes, such as methane. The need for more rigorous research with better data quality is highlighted for further understanding of sustainability implications of MSWM in a Canadian context.