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Record W6963770385 · doi:10.25439/rmt.27597018

Identification of trace organic chemicals attached to plastic fragments collected in Melbourne, Port Philip Bay, Victoria

2022· dissertation· en· W6963770385 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueRMIT Research Repository (RMIT University Library) · 2022
Typedissertation
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsnot available
Fundersnot available
KeywordsMicroplasticsDebrisPlastic pollutionMarine debrisContaminationPollutionBiodegradationAquatic ecosystemPlastic waste

Abstract

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The increase in plastic pollution from plastic debris in the aquatic environment has caused increasing concern worldwide over the past decade. According to available statistics, the global production of plastics reached 359 million tonnes in 2018. Extensive use of plastics with high chemical stability and resistance has seen a concomitant increase in their release into the environment due to poor waste management practices. Most of the plastic in the marine environment comes from the land, although around 20% is due to marine activities such as shipping and fishing. Plastic litter breaks down over time following exposure to solar radiation, oxidation processes and physical processes that convert large plastic debris into smaller particles. According to their sizes, they can be meso-plastics (5-40 mm), microplastics (1-5000 µm) and nano plastics (NPs) (1-1000 nm). Microplastics (MPs) are classified as either primary or secondary MPs. Primary MPs enter the environment without change, i.e., fugitive particles such as plastic resin pellets used in microplastic production or consumer products such as microbeads in cosmetics. Secondary MPs are the result of the degradation of larger plastics. When plastic particles become smaller, and nano particles form, their physical and chemical properties, such as the ratio of surface area to size, strength, conductivity, reactivity, and biological response, change dramatically. In addition, sorption of organic chemicals and metals, weathering, UV, and biodegradation are factors that affect the composition of microplastics. There is limited information on MPs in Australian aquatic environments, and to date, no studies have explored chemical concentrations on MP debris in Victoria. Consequently, the project sought to identify and quantify organic chemical pollutants attached to the plastic fragments. The plastic samples were obtained by the Port Philip Ecocentre from Stony Creek, the Yarra and Maribyrnong rivers, and from 6 beaches along the eastern coastline of Port Phillip Bay, including Brighton, Rickett’s Point, Canadian Bay, Seaford, Frankston, and Mount Martha. To achieve the results, a comprehensive analytical multi-residue method using gas chromatography-mass spectroscopy with automated identification and quantification system database (AIQS-DB) was employed to identify and quantify chemicals presented in extracted liquid from plastic samples. The different types of plastic polymer in the debris were identified by FT-IR, then the pollution profiles of these types of plastics were detected by GC-MS spectrometry database (AIQS-DB). Microplastic samples were collected from Stony Creek after an industrial fire in nearby West Footscray. The purpose was to estimate the pollutant loads on plastic debris in the runoff flow path and if there was any possibility that this plastic debris accumulated fire-related chemicals. The result showed that samples close to the fire contained more fire-related than the two other sites. To obtain an insight into pollution profile for organic chemicals present on plastic debris on trawl samples collected from Maribyrnong and Yarra rivers, MPs were extracted from trawls made on 6th September 2018. The data demonstrated that fragments had a higher abundance in the collected samples, and polypropylene and polyethylene were the predominant polymers. Forty-six and forty-two chemicals were detected in trawl samples in Yarra and Maribyrnong River samples, respectively. The other objective of this research was to discuss regarding associated chemicals of plastic litter in 6 beaches on the eastern coastline of Port Phillip Bay. These plastic debris is divided into two groups pellets and plastic fragments. Polyethylene and polypropylene were the common types of plastics in beached samples. Analysis data showed seventy-eight and sixty chemicals in resin pellet beached samples, while seventy-seven and sixty-three of various chemicals were identified in extracts of fragments collected in Port Phillip Bay in 2019 and 2020, respectively. The toxicity of plastic particles depends not only on the size of particles, their concentration, and the period of exposure of any organism to them, but also on the sorption of contaminants by plastics or their additives and their combinations. These particles can be ingested by organisms and block their ingestion system, or they can release their chemicals either the ones sorbed on them or their additives. Ecotoxicological studies have shown some adverse effects of microplastics on some organisms. Although some sort of estimation in terms of polymer hazards considered for collected samples of beaches and rivers, the accurate risk assessment of microplastics could not be performed in this study because of lack of data and uncertainty in the measurements and sampling. However, this estimation categorised Yarra River and some beaches including Brighton and Ricketts Point samples as highly polluted environment in terms of their polymer risk index of samples. This study adds to the existing information on the distribution of contaminants in Melbourne’s aquatic environment. It may help determine the role of plastic debris in transferring trace organic chemicals to marine organisms. It may be useful for policy makers who want to take adequate measures to reduce MP related pollution.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.595
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.010
GPT teacher head0.246
Teacher spread0.236 · 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