Urban Renewal: Opportunity for Green Innovation in the Face of Climate Change, A Case Study of Toronto Community Housing
Notice bibliographique
Résumé
Cities around the world have established ambitious targets to reduce greenhouse gas emissions in order to limit the global average temperature increase to within 1.5°C of pre-industrial levels by 2050. The effects of climate change are felt globally but urban environments are enormous contributors to emissions. With the majority of the globe’s population residing in cities, they are the most vulnerable to the effects of climate change, which can be catastrophic. Urban renewal, the natural replacement and restoration of buildings, presents an opportunity to interject and guide development to a more sustainable trajectory, in a way that considers the benefits of ecological processes in cities. This major paper argues for the adoption of stronger green building standards in Toronto, beginning from the City’s own building stock of Toronto Community Housing (TCHC), in order to demonstrate leadership and protect the people who are most vulnerable to the negative effects of climate change. The paper does this by exploring the current green building best practices used in North America and how they demonstrate, or are limited in, supporting sustainable development. Consideration is given to whether building high-efficiency buildings is the best option for sustainable development by weighing different factors. Despite best practice weaknesses, ultimately, it is the benefits that are extracted from these practices that are important, rather than any form of certification. Green building development is explored by looking at a case study of TCHC, to understand how the City, as a public entity, can lead the way in green development. This research finds that TCHC is tenaciously using sustainability as a motivator for resident wellbeing, financial sustainability, and reduction in greenhouse gas emissions. However, the case study also reveals limitations to further development of TCHC’s green buildings and emission reductions. This paper identifies those limitations and formulates recommendations to facilitate further reducing emissions. The city’s overall greenhouse gas emission reductions have come to a halt, and this is a sign that additional measures need to be taken to continue to reduce emissions. Improving green building standards for renovations, investing in data collection, and addressing user behaviour through education are the recommendations given in this paper to take the next steps to further reducing building-related emissions. These recommendations will allow TCHC and its tenants to lead efforts to reduce the city’s greenhouse gas emissions. The recommendations focus on maximizing the benefits from green technologies. As a city, Toronto must consider the majority of the current building stock, which will continue to exist into 2050, as well as new buildings which will exist for much longer, in its efforts to further reduce greenhouse gas emissions.
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Prédiction machine sur la base complète
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Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,019 | 0,007 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,002 | 0,005 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».