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Record W6996198908

Refrigerators given cold shoulder : strategies to improve sustainable refrigerator management in Manitoba

2008· dissertation· en· W6996198908 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2008
Typedissertation
Languageen
FieldComputer Science
TopicDiverse Research and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsHazardous wasteRefrigerator carGovernment (linguistics)SustainabilityManagement systemSustainable developmentSustainable managementBest practice
DOInot available

Abstract

fetched live from OpenAlex

Refrigerators contain significant amounts of ozone-depleting substances (ODS), which must be recovered prior to disposal to prevent ozone depletion and climate change. Currently, municipal governments are burdened with appliance management - utilizing practices that encourage recovery of highly valuable resources but neglect recycling less valuable and safely disposing of hazardous components. More progressive strategies have emerged, however, incorporating product lifecycle analysis through end-of-life (EOL) manufacturer involvement and technologies that minimize pollution and increase component recovery. This thesis examined EOL refrigerator management in Manitoba to recommend best practices and sustainable frameworks for management. Objectives included: 1) identifing critical issues in EOL refrigerator management and current waste management policy; 2) identifying gaps in Manitoba's refrigerator management policies, practice and procedure; 3) determining best management frameworks for sustainable management; and 4) recommending feasible management structures for implementation in Manitoba. To achieve these objectives, a number of activities were conducted including a literature review, site tours (Manitoba, UK), consultations with Manitoba Stakeholders, roundtable discussions and distribution of a refrigerator management survey and electronic questionnaires. Manitoba's management system is unsustainable. The largest concern is that most of the ODS in refrigerators is allowed to be released, as regulations requiring its capture are limited to the cooling circuit only and not CFCs in the insulating foam. The insulating foam typically contains two-thirds of the CFCs in refrigerators. Municipalities in Manitoba do not consider safe disposal of these foams, which results in the release of CFCs during the recyling process. Another unsustainable factor is that plastics and other components are not recycled but sent to landfill. Lack of waste management legislation for refrigerators has created over 200 individual municipal management strategies - each with their own criteria for disposal. Residents and municipalities lack proper education and pay as you throw disposal fees has resulted in improper disposals. Appliance resale of old inefficient refrigerators, which are twice the energy consumers of Energy Star models, result in large energy bills to the consumer of several hundred dollars per year. Operating one 20 year-old refrigerator has the carbon dioxide equivalent of running two automobiles for one year. A study tour of refrigerator recycling facilities in the UK and a survey of North American appliance recycling programs provided examples of best management practices (BMPs) form regulatory and voluntary perspectives. Regulations on refrigerator disposal were found to be most effective, as the scope encompasses all units for recycling; targets and standards can be set; most advanced treatment technologies can be utilized; and producers can help with waste management and redesign of sustainable products. To be proactive, refrigerators with high ozone depleting or global warming potential should be discouraged from use and sale and replaced by hydrocarbon technolgy, possibly through eco-rebate incentives. The most effective strategy for Manitoba would be to regulate EOL management through extended producer responsibility (EPR), replacing municipal management approaches with a single strategy, managed and financed by industry producers. Eventually, Manitoba's product stewardship framework must begin to include the principles of EPR for greater...

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)0.002
metaresearch head score (Gemma)0.002
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 score0.289
Threshold uncertainty score0.581

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0030.002
Scholarly communication0.0040.002
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.015
GPT teacher head0.240
Teacher spread0.225 · 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

Citations2
Published2008
Admission routes1
Has abstractyes

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