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Record W4403227557 · doi:10.1016/j.jenvman.2024.122731

The degradation of polylactic acid face mask components in different environments

2024· article· en· W4403227557 on OpenAlexafffund
Linxiang Lyu, Monisha Bagchi, Kelvin Tsun Wai Ng, Nektaria Markoglou, Rumpa Chowdhury, Chunjiang An, Zhikun Chen, Xiaohan Yang

Bibliographic record

VenueJournal of Environmental Management · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsInnovation, Science and Economic Development CanadaConcordia University
FundersNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsPolylactic acidDegradation (telecommunications)Face (sociological concept)Environmental scienceComputer scienceMaterials scienceTelecommunicationsComposite material

Abstract

fetched live from OpenAlex

The disposal of fossil fuel-based plastics poses a huge environmental challenge, leading to increased interest in biodegradable alternatives such as polylactic acid (PLA). This study focuses on the environmental impact and degradation of PLA face mask components under various conditions (UV (Ultraviolet) radiation, DI water, landfill leachate of various ages, seawater, and enzyme). Under UV exposure, notable changes in physicochemical properties were observed in the PLA masks, including increased oxidation over time. Degradation rates varied across environments, with old landfill leachate and enzyme degradation having a notable impact, especially on meltblown layers. Furthermore, it was found that seawater conditions hampered the degradation of PLA masks, likely due to the inhibitory effect of high salt concentrations. The pathways of chemical group changes during degradation were elucidated using 2D-COS (Two-Dimensional Correlation Spectroscopy) maps. The investigation into the release of microparticles and oligomers further revealed the degradation mechanism. Moreover, PLA masks were found to release fewer microparticles when degraded in studied environments when compared to traditional polypropylene masks. Furthermore, correlation analysis highlighted the influence of factors such as carbonyl index and contact angle on degradation rates, underscoring the complex interplay between environmental conditions and PLA degradation. This comprehensive investigation advances the understanding of PLA degradation pathways, which are crucial for mitigating plastic pollution and promoting the development of sustainable products. • UV exposure caused notable changes and increased oxidation of PLA mask components. • PLA mask components exhibited different degradation rates across varying environmental contexts. • The mechanisms during aging and degradation were analyzed based on 2D-COS maps. • Fewer microparticles were released by PLA mask components compared to polypropylene masks. • Seawater conditions impeded the degradation of PLA masks due to the high salt concentration.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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

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 head0.009
GPT teacher head0.193
Teacher spread0.184 · 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 designBench or experimental
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

Citations14
Published2024
Admission routes2
Has abstractyes

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