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Record W7133020436

Performance of Green Roof Integrated Solar Photovoltaics in Toronto

2018· dissertation· W7133020436 on OpenAlexaboutno aff
Dalia El Helow

Bibliographic record

VenueTSpace · 2018
Typedissertation
Language
FieldEnvironmental Science
TopicUrban Heat Island Mitigation
Canadian institutionsnot available
Fundersnot available
KeywordsGreen roofPhotovoltaicsBuilding-integrated photovoltaicsPhotovoltaic systemRenewable energyUrban heat islandRoofElectricity generation
DOInot available

Abstract

fetched live from OpenAlex

Green (vegetated) roofs and solar photovoltaics are among a range of solutions intended to meet environmental sustainability targets and transition to low-carbon communities. In urban environments, they are means to integrate onsite stormwater management and renewable energy. Research shows that the evaporative cooling from green roofs helps to keep photovoltaics near best operational temperature, while proving that vegetation can survive under variable shade and precipitation conditions. This study evaluated photovoltaic surface temperature and power output at two heights (2 and 4 ft.) from two high-performance roof surface types, green and high-albedo (white) roof membrane, at the University of Toronto’s GRIT Lab. Photovoltaic surface temperature and power output showed dependence on height and surface type. Higher separation (4 ft.) allowed for increased biomass, improved cooling effects, and an increase in power output. This short-term study showed a successful integration of both technologies, and hence a viable option for green building practices. الأسطح الخضراء (النباتية) والضوئية الشمسية هي من بين مجموعة من الحلول التي تهدف إلى تحقيق أهداف الاستدامة البيئية والانتقال إلى المجتمعات منخفضة الكربون. في البيئات الحضرية، هي وسيلة لدمج إدارة مياه الأمطار وتوليد الطاقة المتجددة في الموقع. تبين البحوث أن التبريد التبخيري من الأسطح الخضراء يساعد على إبقاء الخلايا الكهروضوئية بالقرب من أفضل درجة حرارة تشغيلية، مع إثبات أن الغطاء النباتي يمكن أن يبقى على قيد الحياة تحت ظلال وأمطار متغيرة. قيمت هذه الدراسة درجة حرارة الاسطح الكهروضوئية وإنتاج الطاقة على ارتفاعين (2 و 4 قدم) من نوعين من الاسطح، السطح الأخضر و السطح الغشائى عالي الإنعكاس (الأبيض) في مختبر جريت بجامعة تورونتو. أظهرت درجة حرارة الاسطح وإنتاج الطاقة الاعتماد على الارتفاع ونوع السطح. يسمح الفصل ألاعلى (4 قدم) بين الوحدات الضوئية والسطح النباتي بزيادة الكتلة الحيوية، وتحسين آثار التبريد، وزيادة في انتاج الطاقة. وأظهرت هذه الدراسة قصيرة الأجل اندماجا ناجحا بين الخلايا الكهروضوئية الشمسية وأنظمة الأسطح الخضراء، وبالتالي خيارا صالحا لممارسات البناء الأخضر.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.622
Threshold uncertainty score0.753

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.277
Teacher spread0.266 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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