In this work, we propose a new protocol for producing model microplastics from an industrial polymer and compare it to a conventional method, cryomilling. Polypropylene industrial pellets were chosen due to their widespread production and frequent presence in the environment, making them a notable source of microplastics. Both protocols start with aging under Ultra-Violet light of the pellets but differ in the subsequent mechanical stress applied-strong vs. soft-to break down the photodegraded pellets into microplastics. All generated particles were fully characterized in terms of size, shape, oxidation rate, and stability in aqueous media. Microplastics produced via cryomilling exhibited significant size and oxidation heterogeneity and tended to aggregate in water. Although the new protocol involving soft mechanical stress required a longer preparation time, it simulated more accurately the environmental degradation of raw plastic. This method successfully produced oxidized microplastics with a controlled size distribution centered around 50 µm which remained stable in water without stabilizers.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.ecoenv.2024.116769 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Lanternfish as bioindicator of microplastics in the deep sea: A spatiotemporal analysis using museum specimens.
J Hazard Mater
January 2025
Universidade Federal do Rio de Janeiro (UFRJ), Instituto de Biodiversidade e Sustentabilidade (NUPEM), Av. São José do Barreto, 764, Macaé, RJ 27965-045, Brazil.
We investigated MP ingestion in lanternfishes (Myctophidae), one of the most abundant vertebrates in the world, using archived specimens from museum collections from 1999 to 2017. Microplastics were detected in 55 % of the 1167 specimens analysed (0.95 ± 1.
View Article and Find Full Text PDFChanges in population fitness and gene co-expression networks reveal the boosted impact of toxic cyanobacteria on Daphnia magna through microplastic exposure.
J Hazard Mater
January 2025
Jiangsu Key Laboratory for Biodiversity and Biotechnology, School of Biological Sciences, Nanjing Normal University, 1 Wenyuan Road, Nanjing 210023, China. Electronic address:
The concomitant prevalence of toxic cyanobacteria blooms and plastic pollution in aquatic ecosystems is emerging as a pressing global water pollution dilemma. While toxic cyanobacteria and microplastics (MPs) can each independently exert significant impacts on aquatic biota, the magnitude and trajectory of the combined interactions remains rudimentary. In this study, we evaluated how MPs influences cyanobacterial stress on keystone grazer Daphnia, focusing on population, individual, biochemical and toxicogenomic signatures.
View Article and Find Full Text PDFMicrocontaminants and microplastics in water from the textile sector: a review and a database of physicochemical properties, use in the textile process, and ecotoxicity data for detected chemicals.
Environ Sci Process Impacts
January 2025
Environmental Modelling Group, Department of Science and High Technology (DiSAT), University of Insubria, Como, 22100, Italy.
Microcontaminants (MCs) and microplastics (MPs) originating from the textile sector are today receiving a great deal of attention due to potential environmental concerns. Environmental pressures and impacts related to the textile system include not only the use of resources (, water) but also the release of a wide variety of pollutants. This review's main objective is to highlight the presence of textile MCs and MPs in water, in their full path from textile factories (from raw materials to the final product) to wastewater treatment plants (WWTPs), and finally to the receiving surface waters.
View Article and Find Full Text PDFIntegrating C-H Information to Improve Machine Learning Classification Models for Microplastic Identification from Raman Spectra.
Anal Chem
January 2025
Department of Chemistry, University of Waterloo, 200 University Avenue W., Waterloo, Ontario N2L 3G1, Canada.
Research has shown microplastic particles to be pervasive pollutants in the natural environment, but labor-intensive sample preparation, data acquisition, and analysis protocols continue to be necessary to navigate their diverse chemistry. Machine learning (ML) classification models have shown promise for identifying microplastics from their Raman spectra, but all attempts to date have focused on the lower energy "fingerprint" region of the spectrum. We explore strategies to improve ML classification models based on the -nearest-neighbor algorithm by including other regions of the Raman spectra.
View Article and Find Full Text PDFMicroplastic ingestion by an aquatic ciliate: Functional response, modulation, and reduced population growth.
Sci Total Environ
January 2025
Department of Life Sciences, Whitelands College, Roehampton University, London SW15 4JD, United Kingdom; Networks Unit, IMT School for Advanced Studies Lucca, Italy.
Microplastic particles are ubiquitous in aquatic environments and are considered a major threat to the large range of heterotrophic organisms that involuntarily consume them. However, there is current uncertainty around the mechanisms underpinning microplastic uptake by aquatic consumers and the consequences for both the fate of the microplastics and the growth potential of consumer populations. We performed a feeding experiment, exposing a model freshwater ciliate, Tetrahymena pyriformis, to six different microplastic concentrations and measured microplastic uptake and population growth over the course of several generations.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!