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Record W6908747313 · doi:10.34726/hss.2019.62904

Qualitative analysis of reducing packaging consumption through reusable systems for takeaway containers

2019· article· en· W6908747313 on OpenAlexaboutno aff

Bibliographic record

VenuereposiTUm (TU Wien) · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Waste Reduction and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsWork (physics)Quality (philosophy)LimitingProcess (computing)Filter (signal processing)

Abstract

fetched live from OpenAlex

This thesis is a qualitative review of reusable takeaway systems and how they may decrease packaging consumption and so negative environmental effects. First, the thesis introduces plastic, the main material used for both disposable and reusable food packaging. Its benefits and disadvantages, as well as its economic implications are explained. The thesis finds plastic to be a complex set of materials and delves into further details on different types of plastic. The thesis also determines that plastic still has heavy environmental impacts and a high potential for environmental improvement, especially through recycling, and new technologies using alternative feedstocks. Thus, while plastic is a necessary and practical material, action is needed for improved lifecycle management. This has been recognised by governments who have taken legislative action, which is examined by this thesis with a focus on the EU. Because of plastics examined features, this thesis establishes that it is also a practical material for reusable takeaway containers. Hence the thesis examines LCAs, which compare disposable with reusable plastic containers as well as other materials, aluminium, bagasse, and glass. Various LCAs indicate that PP is a sustainable choice for a reusable container system under certain conditions, if the container is reused at least 40 times. The use of local manufacturers, commercial dishwashers and short distribution paths are important factors, too. Overall, findings confirm that indeed a reusable plastic container system is preferable to disposable containers. Finally, the thesis gives an overview of systems and provides case studies of their application. All examined types of systems, where containers are washed on-site or elsewhere, seem viable from an economic, environmental and social perspective. Surprisingly this thesis observes that deposit fees of up to EUR/CHF 10 had no significant negative effect on the system. System success rather depends on how the rate of loss and efficiency is managed through clear definition of the systems area, accountability and distribution mechanisms, incentives, marketing and pricing. It also depends on expected container lifetime (durability) as well as how and where these are produced, washed, monitored, and discarded. Short reuse times are essential, too. The thesis finds that the main cause for longer reuse times are consumers who keep the container instead of returning it. Keeping and washing the container at home is not optimal from an environmental perspective, also as returned containers may have to be rewashed because of sanitation regulations, wasting valuable resources. Outdated and complicated sanitation regulations are one example of a barrier where local government action could substantially help change the situation. Local governments are central to help modify consumer behaviour and decrease waste and litter. This can be achieved through zero waste strategies or charges on disposable container waste, as examples in Canada and Australia have shown and European ones soon will. The EU has led by example extending producer responsibilities but local governments must follow suit, focussing on public waste. Also, regulations on using recycled granulate for food containers must be adjusted to allow closed loop recycling. Overall, societal trends will continue pushing for convenience but also increased environmental awareness. The author believes it is only a matter of time before the takeaway industry mainstreams reusable systems. Vienna has strong potential for a reusable system, especially if it is grown through clusters and the right communities are targeted.

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)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.005
Scholarly communication0.0040.004
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.045
GPT teacher head0.332
Teacher spread0.288 · 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 designQualitative
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
Published2019
Admission routes1
Has abstractyes

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