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Record W2773648684

Two Degrees Celsius, Assessing the Potential of Urban Commercial Buildings in Canada to Reach the 2°C Climate Change Target

2017· dissertation· en· W2773648684 on OpenAlexaboutno aff
Christopher Black

Bibliographic record

VenueUWSpace (University of Waterloo) · 2017
Typedissertation
Languageen
FieldEnvironmental Science
TopicEnvironmental Impact and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsDegree CelsiusClimate changeArchitectural engineeringGeographyEngineeringEnvironmental scienceMeteorologyGeologyPhysics
DOInot available

Abstract

fetched live from OpenAlex

To avoid the catastrophic effects of climate change, scientific consensus and international convention have determined that the mean rise in global temperatures must be limited to between 1.5°C and 2.0°C. The Intergovernmental Panel on Climate Change suggests the building sector possesses the most immediate mitigation potential and has proven technological and design capability at hand. To meet this goal, a 55% reduction is required compared to a proposed Business-As-Usual Scenario forecast in emissions between 2005 and 2050. For Canadian commercial buildings, this is equivalent to emissions dropping from 88.4 MtCO₂e to 39.8 MtCO₂e/yr. \n \nBetween 2005 and 2050, the floor area of commercial building is expected to double from 654.2 million m² to 1,139.5 million m² while the emissions are to be halved. The proposed model suggests that, by 2050, new and substantially renovated buildings should emit 15.3 kgCO₂e/m² /yr to achieve this. When combined with existing buildings, the blended emissions cap is expected to be 34.9 kgCO₂e/m²/yr. Given that in 2013 new, renovated, and existing buildings in Canada was 46.67 kgCO₂e/m²/yr, this ambitious target implies a significant transformation of commercial buildings. \n \nWhen consistently applied to every building, the 15.3 kgCO₂e/m²/yr rate suggests an evolving approach to design. This is especially true for urban sites where passive design and renewable energy opportunities are limited. Although there are a number of built projects that meet the criteria, they remain the exception rather than the norm and deploy a maximum of energy efficient technologies and design strategies. A full range of innovative passive and active building technologies is leveraged, and many examples are most often not situated in a dense urban environment. \n \nUsing an emission rate per square metre reflects a "bottom-up" approach to transforming Canadian commercial buildings. Rather than relying on sweeping policy intervention or mandating particular technologies, this metric can be used to bring the various drivers of emissions together for a particular building, thus allowing the most applicable technologies and strategies to be selected on a case-by-case basis. The thesis will demonstrate that a suite of measures focused on the combination of energy conservation and fuel choice can not only achieve this target on urban projects with limited passive means but suggest that the adoption of further passive and active technologies could push performance even further. \n \nTo investigate the implications of the emission cap in this context, a demonstration project is proposed and sited in three different locations on a prototypical urban block. Located on a north-facing end-block, a mid-block, and a south-facing end-block site, each is designed to both current code requirements and the 2°C scenario emission limit. The selection of an urban context bridges the gap between the ideal conditions of rural or campus buildings, where few obstructions to leveraging passive design and implementing extensive on-site renewable energy systems exist, and urban buildings with tight sites and limited passive opportunities. With the world now predominantly urban, these sites are expected to represent the norm. Pablo Picasso saw constraints as sources of inspiration and invention rather than limitations to creativity. Similarly, rather than being a limitation to design, this thesis will show that it has the opportunity to become a foundational design driver motivating invention and innovation within the field’s practical and conceptual foundations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.336

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.226
Teacher spread0.215 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2017
Admission routes1
Has abstractyes

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