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

Author

Listed:
  • Tahereh Malmir

    (Canada Excellence Research Chair Next Generation Cities, Gina Cody School of Engineering and Computer Science, Concordia University, Montréal, QC H3G 1M8, Canada)

  • Saeed Ranjbar

    (Canada Excellence Research Chair Next Generation Cities, Gina Cody School of Engineering and Computer Science, Concordia University, Montréal, QC H3G 1M8, Canada)

  • Ursula Eicker

    (Canada Excellence Research Chair Next Generation Cities, Gina Cody School of Engineering and Computer Science, Concordia University, Montréal, QC H3G 1M8, Canada)

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 CO 2eq 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.

Suggested Citation

  • Tahereh Malmir & Saeed Ranjbar & Ursula Eicker, 2020. "Improving Municipal Solid Waste Management Strategies of Montréal (Canada) Using Life Cycle Assessment and Optimization of Technology Options," Energies, MDPI, vol. 13(21), pages 1-15, October.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:21:p:5701-:d:438063
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    References listed on IDEAS

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    3. Wang, Yanfeng & Shen, Yongpeng & Zhang, Xuncai & Cui, Guangzhao & Sun, Junwei, 2018. "An Improved Non-dominated Sorting Genetic Algorithm-II (INSGA-II) applied to the design of DNA codewords," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 151(C), pages 131-139.
    4. Sooriyaarachchi, Thilanka M. & Tsai, I-Tsung & El Khatib, Sameh & Farid, Amro M. & Mezher, Toufic, 2015. "Job creation potentials and skill requirements in, PV, CSP, wind, water-to-energy and energy efficiency value chains," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 653-668.
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    Cited by:

    1. Venkata Ravi Sankar Cheela & Michele John & Wahidul K. Biswas & Brajesh Dubey, 2021. "Environmental Impact Evaluation of Current Municipal Solid Waste Treatments in India Using Life Cycle Assessment," Energies, MDPI, vol. 14(11), pages 1-23, May.
    2. Patel, Sanjay K.S. & Das, Devashish & Kim, Sun Chang & Cho, Byung-Kwan & Kalia, Vipin Chandra & Lee, Jung-Kul, 2021. "Integrating strategies for sustainable conversion of waste biomass into dark-fermentative hydrogen and value-added products," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).

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