Journal
TRAC-TRENDS IN ANALYTICAL CHEMISTRY
Volume 166, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.trac.2023.117158
Keywords
Microplastics; Nanoplastics; Sample preparation; Imaging analysis; Algorithm; Hyperspectral matrix
Categories
Ask authors/readers for more resources
Microplastics and nanoplastics, as emerging contaminants, present analytical challenges due to their small size, diverse composition, and complex environmental background. Research on nanoplastics lags behind that on microplastics due to the smaller size and weaker signal, making analysis more challenging. This review discusses recent advancements in the analysis of microplastics and nanoplastics, including sampling, sample preparation, testing, and data analysis. The unique properties of these contaminants complicate the sampling and sample preparation processes, which are rarely reported but crucial for subsequent analysis. Various techniques for morphological and chemical characterizations are compared, highlighting their advantages and disadvantages. Non-imaging analysis may introduce bias, and imaging analysis using micro-IR and micro-Raman spectroscopy shows promise in overcoming this bias. However, these techniques have limitations in terms of time consumption and resolution. Algorithms of chemometrics and artificial intelligence can be utilized to decode hyperspectral data and reconstruct images. Overall, this review addresses the challenges and advances in the analysis of microplastics and nanoplastics and suggests future research directions.
As emerging contaminants, microplastics and nanoplastics pose analytical challenges to the scientific community due to the small size, diverse composition and complex environmental background. The research on nanoplastics is far behind that on microplastics because the shrink size and the weak signal lead to more challenging analysis. Herein we review the recent advancements on their analysis including sampling, sample preparation, test and aftermath data analysis. We begin by clarifying the unique properties of microplastics and nanoplastics that complicate the sampling and the sample preparation processes, which have been rarely reported but should be emphasised for the subsequent analysis. For the analysis, there are various techniques for morphological and chemical characterisations, including microscope, element analysis, mass spectroscopy and molecular spectroscopy. They are compared herein to highlight their advantages and disadvantages. Because the microplastics and nanoplastics can have their own sub-structures, there might be bias if the non-imaging analysis is conducted, such as using a single spectrum analysis (point analysis) conducted at a selective position that is only a partial surface area of the whole structure (surface and bulk). Imaging analysis via micro-IR and micro-Raman spec-troscopy particularly Raman imaging shows some advantages to overcome this bias. However, Raman imaging is a time-consuming process with a diffraction-limited resolution problem that is also discussed herein. Moreover, it is difficult to convert the scanning hyperspectral matrix to image. To address this, algorithms of chemometrics and artificial intelligent (AI) can be utilised to decode the hyperspectral matrix that acts as a big data, and re-construct the image towards deconvolution. The current analysis techniques should be either improved or combined for the emerging contaminants' analysis. Overall, this review summarises the analysis challenges and advances, and also suggests the future research directions. & COPY; 2023 Elsevier B.V. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available