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Communicating Confidence in the Reliability of Micro- and Nanoplastic Identification in Human Health Studies
Kevin V. Thomas
,
Susanne Belz,
Andy M. Booth
,
Martin Clift
,
Richard K. Cross
,
Grace Davies
,
Hubert Dirven,
Sarah Dunlop
,
Alessio Gomiero
,
Shaowei Guo
,
Dorte Herzke,
Albert A. Koelmans
,
Ian S. Mudway,
Elvis D. Okoffo
,
Cassandra Rauert
,
Saer Samanipour
,
Christos Symeonides,
Douglas I. Walker,
Tingting Wang,
Stephanie L. Wright
,
Jun-Li Xu
,
Leon P. Barron
Environment & Health
Swansea University Author:
Martin Clift
-
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© 2026 The Authors. This publication is licensed under CC-BY-NC-ND 4.0 .
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DOI (Published version): 10.1021/envhealth.5c00671
Abstract
Accurately quantifying and characterizing human internal exposure to micro- and nanoplastics are critical for assessing potential health risks. However, the detection of these particles in human tissues, fluids, cell systems, and relevant models remains a major analytical challenge. There is an urge...
| Published in: | Environment & Health |
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| ISSN: | 2833-8278 2833-8278 |
| Published: |
American Chemical Society (ACS)
2026
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| Online Access: |
Check full text
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa71348 |
| Abstract: |
Accurately quantifying and characterizing human internal exposure to micro- and nanoplastics are critical for assessing potential health risks. However, the detection of these particles in human tissues, fluids, cell systems, and relevant models remains a major analytical challenge. There is an urgent need for robust, selective, sensitive, and high-throughput methods capable of generating reliable quantitative data. Equally essential is the transparent reporting of methodological limitations and uncertainties, supported by rigorous data collection and standardized practices. These challenges are compounded by the ubiquity of plastic particles, and therefore the risk of sample contamination and their diverse properties (e.g., size, shape, composition), all adding to the complexity of identifying and quantifying them in biological matrices. To address these issues, we propose a framework that integrates orthogonal analytical techniques to enhance the data reliability. Commonly used analytical techniques for the analysis of micro- and nanoplastics are assigned a category based on their specificity when identifying plastic particles. The framework proposes minimum data requirements from orthogonal techniques for the identification of plastic particles at various confidence levels. Clear communication of analytical confidence is vital, and we present a structured approach to support this. We emphasize the importance of scientific integrity, rigorous study design, and transparent reporting in health research. Finally, we call for the universal adoption of harmonized confidence criteria for reporting the presence of plastics in humans, an essential step toward informed decision-making. |
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| Keywords: |
microplastics, nanoplastics, human exposure, analytical methods, biological matrices, quantification, detection |
| College: |
Faculty of Medicine, Health and Life Sciences |
| Funders: |
This work was supported by Minderoo Foundation. A.M.B. was supported by the Plastic Trace project, funded by the European Partnership on Metrology, cofinanced by the European Union’s
Horizon Europe Research and Innovation Programme and by the Participating States (Grant Agreement No. 21GRD07). EO is supported by the Australian Research Council (IC220100035). H.D. received support from the European Union’s Horizon 2020 research and innovation programme
under Grant Agreement No. 964766 (POLYRISK). I.S.M. and S.W. received partial support through the MRC Centre for Environment and Health (MR/S019669/1), and the NIHR Health Protection Research Units in Environmental Exposures and Health, and Chemical and Radiation Threats and Hazards, a
partnership between the U.K. Health Security Agency and Imperial College London (https://eeh.hpru.nihr.ac.uk/). Support was also provided by the Norwegian Research Council
project PlastPoll21. |

