Improving Municipal Solid Waste Management Strategies of Montréal (Canada) Using Life Cycle Assessment and Optimization of Technology Options

Abstract

Landfilling of organic waste is still the predominant waste management method in Canada. Data collection and analysis of the waste were done for the case study city of Montréal in Canada. A life cycle assessment was carried out for the current and proposed waste management system using the IWM-2 software. Using life cycle assessment results, a non-dominated sorting genetic algorithm was used to optimize the waste flows. The optimization showed that the current recovery ratio of organic waste of 23% in 2017 could be increased to 100% recovery of food waste. Also, recycling could be doubled, and landfilling halved. The objective functions were minimizing the total energy consumption and CO2eq emissions as well as the total cost in the waste management system. By using a three-objective optimization algorithm, the optimized waste flow for Montréal results in 2% of waste (14.7 kt) to anaerobic digestion (AD), 7% (66.3 kt) to compost, 32% (295 kt) to recycling, 1% (8.5 kt) to incineration, and 58% (543 kt) to landfill.

Biomass Waste for Energy Production

“…Dyjakon and Noszczyk [1] Waste-to-Energy Torrefaction Stępie ń et al [2] Waste-to-Energy Torrefaction Boer et al [3] Life-Cycle Analysis Biomass Waste Malmir et al [4] Life-Cycle Analysis Waste Management Dębowski et al [5] Waste-to-Energy Anaerobic Digestion Hoang et al [6] * Waste-to-Energy Biomass Waste Kozioł et al [7] Waste-to-Energy Combustion Calì et al [8] Waste-to-Energy Gasification Ferreira et al [9] Waste-to-Energy and Computational Models Gasification…”

“…Malmir et al [4] carried out a lifecycle assessment for the current and proposed waste management system in Montréal city. A genetic algorithm was used to optimize the waste flows.…”

Applications of Multi-Objective Optimization to Industrial Processes: A Literature Review

“…However, the Pareto fronts give the decision maker a tool to define the priorities and select the best scenario. There are other works that aim to improve the environmental aspect by designing optimal solid waste management (SWM) systems [10][11][12][13]. For example, Pourreza-Movahed et al [10] optimized an SWM system and compared it to recent technologies with enhanced systems that include gas recovery, finding that upgraded technologies provided better results in the economic and environmental aspect with respect to the current practice; however, they considered that the cost function reduced the environmental indicators by 18.2% (CO 2 equivalent emissions savings) and 6.2% (Energy consumption savings).…”

“…For example, Pourreza-Movahed et al [10] optimized an SWM system and compared it to recent technologies with enhanced systems that include gas recovery, finding that upgraded technologies provided better results in the economic and environmental aspect with respect to the current practice; however, they considered that the cost function reduced the environmental indicators by 18.2% (CO 2 equivalent emissions savings) and 6.2% (Energy consumption savings). Another work also studied the improvement of an SWM [12], finding that the current recovery ratio of organic waste could be increased, in Montreal, from 23% up to a 100%. These sort of systems are in the spotlight due to the increasing amount of residues generated in major cities around the world; therefore, their proper design and operation can contribute to the development of circular economies.…”

Sustainability Analysis of Anaerobic Digestion Systems for Decentralized Waste Management

“…The results revealed that the detrimental effects were mainly due to air emissions from the incinerators, whereas other impacts such as global warming potential and acidification were relatively low as a result of serving a small population (about 56,000 per capita). Other studies only discussed the optimization of the different SWM scenarios applied in small-scale settings, [7], [8].…”