LAPSE:2023.13251
Published Article
LAPSE:2023.13251
Energy Transition Pathways for Deep Decarbonization of the Greater Montreal Region: An Energy Optimization Framework
Sajad Aliakbari Sani, Azadeh Maroufmashat, Frédéric Babonneau, Olivier Bahn, Erick Delage, Alain Haurie, Normand Mousseau, Kathleen Vaillancourt
March 1, 2023
Abstract
More than half of the world’s population live in cities, and by 2050, it is expected that this proportion will reach almost 68%. These densely populated cities consume more than 75% of the world’s primary energy and are responsible for the emission of around 70% of anthropogenic carbon. Providing sustainable energy for the growing demand in cities requires multifaceted planning approach. In this study, we modeled the energy system of the Greater Montreal region to evaluate the impact of different environmental mitigation policies on the energy system of this region over a long-term period (2020−2050). In doing so, we have used the open-source optimization-based model called the Energy−Technology−Environment Model (ETEM). The ETEM is a long-term bottom−up energy model that provides insight into the best options for cities to procure energy, and satisfies useful demands while reducing carbon dioxide (CO2) emissions. Results show that, under a deep decarbonization scenario, the transportation, commercial, and residential sectors will contribute to emission reduction by 6.9, 1.6, and 1 million ton CO2-eq in 2050, respectively, compared with their 2020 levels. This is mainly achieved by (i) replacing fossil fuel cars with electric-based vehicles in private and public transportation sectors; (ii) replacing fossil fuel furnaces with electric heat pumps to satisfy heating demand in buildings; and (iii) improving the efficiency of buildings by isolating walls and roofs.
Keywords
bottom–up energy model, cities, deep decarbonization, energy policy, ETEM
Suggested Citation
Aliakbari Sani S, Maroufmashat A, Babonneau F, Bahn O, Delage E, Haurie A, Mousseau N, Vaillancourt K. Energy Transition Pathways for Deep Decarbonization of the Greater Montreal Region: An Energy Optimization Framework. (2023). LAPSE:2023.13251
Author Affiliations
Aliakbari Sani S: GERAD (Group for Research in Decision Analysis) and Department of Decision Sciences, HEC Montréal, Montréal, QC H3T 2A7, Canada [ORCID]
Maroufmashat A: GERAD (Group for Research in Decision Analysis) and Department of Decision Sciences, HEC Montréal, Montréal, QC H3T 2A7, Canada
Babonneau F: Department of Operations Management-Supply Chain-Information Systems, KEDGE Business School, 680 Cr de la Libération, 33405 Talence, France; ORDECSYS, 4 Place de l’Etrier, CH-1224 Chêne-Bougeries, Switzerland [ORCID]
Bahn O: GERAD (Group for Research in Decision Analysis) and Department of Decision Sciences, HEC Montréal, Montréal, QC H3T 2A7, Canada [ORCID]
Delage E: GERAD (Group for Research in Decision Analysis) and Department of Decision Sciences, HEC Montréal, Montréal, QC H3T 2A7, Canada
Haurie A: GERAD (Group for Research in Decision Analysis) and Department of Decision Sciences, HEC Montréal, Montréal, QC H3T 2A7, Canada; ORDECSYS, 4 Place de l’Etrier, CH-1224 Chêne-Bougeries, Switzerland; Geneva School of Economics and Management, Universit
Mousseau N: Département de Physique, Faculté des Arts et des Sciences, Université de Montréal, Montréal, QC H3T 1J4, Canada
Vaillancourt K: ESMIA Consultants, Blainville, QC J7B 6B4, Canada
Journal Name
Energies
Volume
15
Issue
10
First Page
3760
Year
2022
Publication Date
2022-05-20
ISSN
1996-1073
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Original Submission
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PII: en15103760, Publication Type: Journal Article
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LAPSE:2023.13251
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https://doi.org/10.3390/en15103760
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