Evidence map›Paper›PMID 40164936›Full record

ArticleAnalytical and bioanalytical chemistry2025

Pyrolysis-GC/MS differentiates polyesters and detects additives for improved monitoring of textile labeling accuracy and plastic pollution.

Josh Forakis, Jennifer Lynch

Abstract read
In one paragraph

Article in Analytical and bioanalytical chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Josh ForakisCenter for Marine Debris Research, Hawaii Pacific University, 41-202 Kalanianaole Hwy #9, Waimanalo, HI, 96744, USA. jforakis@hpu.edu.
Jennifer LynchCenter for Marine Debris Research, Hawaii Pacific University, 41-202 Kalanianaole Hwy #9, Waimanalo, HI, 96744, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Polyesters comprise the greatest proportion of textile fibers and are found in various everyday goods; hence, polyester fibers are a significant source of microplastic pollution and textile waste. The specific chemical composition of commercial polyester fibers is often proprietary and mostly assumed to be poly(ethylene terephthalate) (PET). Polyester is a class of polymers that include poly(butylene terephthalate) (PBT), poly(cyclohexylenedimethylene terephthalate) (PCT), and poly(ethylene naphthalate) (PEN), as well as biodegradable polymers. Our study aims to clarify whether household polyester products are primarily PET, are labeled accurately, or contain phthalate additives by applying double-shot pyrolysis-gas chromatography/mass spectroscopy (Py-GC/MS). We analyzed four scientific-grade polyester reference standards, 52 manufacturer-grade polyester fibers or pellets, and 229 samples from 193 consumer polyester products. From the pyrograms, samples were predominantly identified as PET (87.4%, 95% CI [93.5-81.3%]), but five samples were identified as a different polyester, nine as non-polyester polymers, and 23 as a blend of PET with another polymer. From the thermal desorption chromatograms, diethyl phthalate was the most frequently detected phthalate, found in 23.3% (95% CI [17.3-29.3%]) of the consumer products, including children's toys. Double-shot py-GC/MS advantageously results in these empirical data that (1) counter the assumption that products labeled polyester are always PET, (2) emphasize the importance of creating spectral libraries with well-characterized materials for accurate polymer identification of unknown plastic particles, and (3) demonstrate that phthalates are common additives in household products.

Indexed as

MicrofibersPolyestersPolymer identificationPy-GC/MS

Identifiers

PMID40164936
PMCPMC12103379

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.