Montréal: Towards a post-industrial reinvention

Moser, Sarah; Fauveaud, Gabriel; Cutts, Adam

doi:10.1016/j.cities.2018.09.013

Cited by 21 publications

(9 citation statements)

References 17 publications

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“…Overreliance on the chemical industry also exacerbates the "resource curse" phenomenon [19], which has caused many cities to face difficulties in their economic transitions as well as economic recessions due to excessive dependence on resources [20]. erefore, many economically developed cities have begun to switch out of the chemical industry and develop non-/low-polluting industries, which scholars call the post-oil industry era [6,21,22]. Many resource-based cities and CICs, such as Pittsburgh (USA), Kitakyushu (Japan), Ruhr (German), and Lorraine (France), have already successfully achieved sustainable development under different policies [20].…”

Section: Introductionmentioning

confidence: 99%

Exploring the Classification and Restructuring of Chemical Industrial Cities in China: The Perspectives of Sectoral and Spatial Differences

et al. 2021

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As an economic pillar, major resource consumer, and polluter of cities, the chemical industry determines many cities’ transformation, prosperity, and decay. It is thus a major concern for achieving the UN Sustainable Development Goals. In China, which is at the stage of accelerated industrialization that is varied across regions, the chemical industry has gradually retreated from developed cities, such as Beijing and Shanghai, in the eastern region, and has become the inevitable choice for industrialization of less-developed cities, such as Xi’an, Chengdu, and Chongqing, in the western region. This study took the perspectives of chemical industrial sectors and their spatial differences to understand the changing patterns of the chemical industry and its dominant cities. It identified chemical industrial cities (CICs), examined their spatial-temporal patterns with respect to their industry scale and structure, and accounted for factors influencing the spatial evolution from coastal areas to inland regions. The results show that large CICs were mainly located in coastal port regions with balanced industrial sectors, while small CICs were mainly distributed in inland areas with abundant oil and coal resources and a single dominant industrial sector. The location factors of ports, markets, and technology play important roles in the eastern region, while resource conditions and foreign direct investment promote the chemical industry’s development in the central, western, and northeastern cities. These findings improve the understanding of CICs’ spatial transformation and shed light on the policy-making of chemical industrial development in China and other developing countries.

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Section: Introductionmentioning

confidence: 99%

Exploring the Classification and Restructuring of Chemical Industrial Cities in China: The Perspectives of Sectoral and Spatial Differences

et al. 2021

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“…In 2022, Montreal's vacancy rate fell to 2.3% ( Press, 2023 ), due in part to a return of international students and a slower transition to homeownership linked to a strong increase in house prices during the pandemic ( Rental Market Report, 2023 ). More recently, gentrification has been in part driven by the relocation of international organizations to Montréal through incentivization of international investments, and a strong governmental support of the tech and start-up ecosystem ( Moser et al, 2019 ), among other reasons.…”

Section: Methodsmentioning

confidence: 99%

Gentrification, perceptions of neighborhood change, and mental health in Montréal, Québec

Youngbloom¹,

Thierry²,

Fuller³

et al. 2023

SSM - Population Health

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“…The area encompassing these building complexes' typology covers approximately five million square feet. Over the years, however, the industrial building stock has been transformed for various purposes [38].…”

Section: Case Study Informationmentioning

confidence: 99%

Supporting Decision Making for Building Decarbonization: Developing Surrogate Models for Multi-Criteria Building Retrofitting Analysis

Saad,

Menon,

Eicker

2023

Energies

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Decarbonizing buildings is crucial in addressing pressing climate change issues. Buildings significantly contribute to global greenhouse gas emissions, and reducing their carbon footprint is essential to achieving sustainable and low-carbon cities. Retrofitting buildings to become more energy efficient constitutes a solution. However, building energy retrofits are complex processes that require a significant number of simulations to investigate the possible options, which limits comprehensive investigations that become infeasible to carry out. Surrogate models can be vital in addressing computational inefficiencies by emulating physics-based models and predicting building performance. However, there is a limited focus on investigating feature engineering and selection methods and their effect on the model’s performance and optimization. Feature selection methods are considered effective with interpretable models such as multi-variate linear regression (MVLR) and multiple adaptive regression splines (MARS) for achieving stable prediction stability. This study proposes a modelling framework to create, optimize, and improve the performance of surrogate predictive models for energy consumption, carbon emissions, and the associated cost of building energy retrofit processes. The investigated feature selection methods are wrapper and embedded methods such as backward-stepwise feature selection (BSFS), recursive feature elimination (RFE), and Elastic Net embedded regularization in order to provide insights into the model’s behavior and optimize the model’s performance. The most accurate surrogate models developed achieved a mean absolute percentage error (MAPE) of 0.2–1.8% compared to the used test data. In addition, when calculated for a million samples, all developed surrogate models reduced the computational time by one-thousand-fold compared to physics-based models. The study’s findings pave the way towards low-computational accurate models that can comprehensively predict building performance in near real-time, ultimately leading to identifying decarbonization measures at scale.

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Montréal: Towards a post-industrial reinvention

Cited by 21 publications

References 17 publications

Exploring the Classification and Restructuring of Chemical Industrial Cities in China: The Perspectives of Sectoral and Spatial Differences

Exploring the Classification and Restructuring of Chemical Industrial Cities in China: The Perspectives of Sectoral and Spatial Differences

Gentrification, perceptions of neighborhood change, and mental health in Montréal, Québec

Supporting Decision Making for Building Decarbonization: Developing Surrogate Models for Multi-Criteria Building Retrofitting Analysis

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