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Record W4389733369 · doi:10.1039/d3en00559c

The elemental fingerprint as a potential tool for tracking the fate of real-life model nanoplastics generated from plastic consumer products in environmental systems

2023· article· en· W4389733369 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEnvironmental Science Nano · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsUniversité Laval
FundersOffice of Research and DevelopmentU.S. Environmental Protection AgencyNational Science Foundation
KeywordsMetalloidPolyethyleneMicroplasticsPolypropyleneCarbon blackEnvironmental chemistryPolystyreneMaterials sciencePlastic pollutionPolymerMetalChemistryComposite materialMetallurgy

Abstract

fetched live from OpenAlex

Metals and metalloids are widely used in producing plastic materials as fillers and pigments, which can be used to track the environmental fate of real-life nanoplastics in environmental and biological systems. Therefore, this study investigated the metal and metalloids concentrations and fingerprint in real-life model nanoplastics generated from new plastic products (NPP) and from environmentally aged ocean plastic fragments (NPO) using single particle-inductively coupled plasma-mass spectrometry (SP-ICP-TOF-MS) and transmission electron microscopy coupled with energy dispersive X-ray spectroscopy (TEM-EDX). The new plastic products include polypropylene straws (PPS), polyethylene terephthalate bottles (PETEB), white low-density polyethylene bags (LDPEB), and polystyrene foam shipping material (PSF). All real-life model nanoplastics contained metal and metalloids, including Si, Al, Sr, Ti, Fe, Ba, Cu, Pb, Zn, Cd, and Cr, and were depleted in rare earth elements. Nanoplastics generated from the white LDPEB were rich in Ti-bearing particles, whereas those generated from PSF were rich in Cr, Ti, and Pb. The Ti/Fe in the LDPEB nanoplastics and the Cr/Fe in the PSF nanoplastics were higher than the corresponding ratios in natural soil nanoparticles (NNPs). The Si/Al ratio in the PSF nanoplastics was higher than in the NNPs, possibly due to silica-based fillers. The elemental ratio of Si/Al, Fe/Cr, and Fe/Ni in the nanoplastics derived from ocean plastic fragments was intermediate between the nanoplastics derived from real-life plastic products and NNPs, indicating a combined contribution from pigments and fillers used in plastics and from natural sources. This study provides a method to track real-life nanoplastics in controlled laboratory studies based on nanoplastic elemental fingerprints. It expands the realm of nanoplastics that can be followed based on their metallic signatures to all kinds of nanoplastics. Additionally, this study illustrates the importance of nanoplastics as a source of metals and metal-containing nanoparticles in the environment.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.733
Threshold uncertainty score0.867

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.013
GPT teacher head0.211
Teacher spread0.198 · 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