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Record W4239826177 · doi:10.32920/ryerson.14664546

A comparative analysis of environmental and economic costs of PV solar imports and manufacturing for Ontario

2021· preprint· en· W4239826177 on OpenAlexaffabout
Elizabeth Bich Ngoc Nguyen

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicPhotovoltaic Systems and Sustainability
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsPhotovoltaic systemSupply chainRenewable energyActivity-based costingGreenhouse gasChinaLife-cycle assessmentBusinessEnvironmental economicsEnvironmental impact assessmentManufacturingNatural resource economicsProduction (economics)EconomicsEngineering

Abstract

fetched live from OpenAlex

This research focuses on the environmental impacts related to the manufacturing of solar photovoltaic (PV) technology. The life cycle assessment (LCA) method was used to assess the environmental impacts for a CS6XVP module. The current supply chain, based in China, was compared to a hypothetical Ontario based supply chain to determine environmental and economic costs. LCA results showed that the manufacturing of modules in Ontario reduced primary energy demands by 22% and GHG emission by 88%. Moreover, the carbon difference between supply chains equated to $5.84 per module. This leads to the conclusion that there are clear environmental benefits to manufacturing PV technology in Ontario; however, the economic benefits of carbon costing are not significant enough to encourage a complete shift in the current supply chain. It is suggested that a change in carbon policy could help to support the development of PV manufacturing and other renewable energy technologies in Ontario.

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 score0.084
Threshold uncertainty score0.231

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.232
Teacher spread0.221 · 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
Published2021
Admission routes2
Has abstractyes

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