Reviewing the Impact of 2D-COS on Analyzing Microplastic Impact on the Environment

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A recent review article highlighted how two-dimensional correlation spectroscopy (2D-COS) is advancing microplastics research and uncovering their aging processes and interactions with environmental substances.

A research collaboration of scientists from the Chinese Academy of Sciences, University of Chinese Academy of Sciences, and North Minzu University examined the application of two-dimensional correlation spectroscopy (2D-COS) and how it is being used to better understand the impact of microplastics (MPs) on the environment. This review article, which was published in the Journal of Environmental Sciences, highlights the potential of 2D-COS to advance research on MPs’ aging mechanisms, interactions with natural organic matter (NOM), and the development of effective mitigation strategies (1).

Close-up of micro plastic particles in a person's hand. The concept for water pollution and global warming. Macro shot on a bunch of microplastics that cannot be recycled. | Image Credit: © SIV Stock Studio - stock.adobe.com

Close-up of micro plastic particles in a person's hand. The concept for water pollution and global warming. Macro shot on a bunch of microplastics that cannot be recycled. | Image Credit: © SIV Stock Studio - stock.adobe.com

The 2D-COS technique has been growing in popularity and is being applied in various industries. It is designed to improve on the limitations generally seen from traditional one-dimensional (1D) spectroscopic methods (1). The 2D-COS analytical technique enhances the interpretation of the spectral data to allow researchers to understand the relationships between spectral features better when overlapping peaks or subtle variations are present (2,3). This is important for analyzing MPs because of their minuscule size. When used effectively, 2D-COS can reveal more information in the spectral data of MPs than traditional techniques. 2D-COS has been used to learn about the behavior of MPs under different environmental conditions, when interacting with other substances; and when temperature and chemical interactions influence MPs (1).

Dongbin Wei of the Chinese Academy of Sciences and his team highlighted the recent work done in analyzing MPs using 2D-COS. Their review was structured to address specific applications where 2D-COS was being used, including detecting the effects of aging processes on MPs and determining how natural organic matter (NOM) and other pollutants interact with MPs (1). Their article shows how 2D-COS can help scientists learn more about how MPs are impacting the environment ecologically.

Using Web of Science (WoS), the researchers collected 67 papers where 2D-COS was applied in MP analysis. Out of those 67, 51.9% focused on aging processes, whereas 42.6% of papers were dedicated to the interaction of MPs on the environment (1). Using those papers, the researchers determined how 2D-COS was being used by researchers. They concluded that 2D-COS was useful in determining the relationship between aging time and spectral adulteration (1). For the papers that focused on measuring MP’s ecological impact, the researchers noticed that 2D-COS was used to evaluate the major interactions and functional group response order (1). Most studies were focused on learning more about the interaction mechanisms between coexisting substances and MPs, with the idea being that knowing this would help clarify the risk MPs have on the environment (1).

Wei and his team did make note that in all these studies, there were some general, underlying challenges in applying 2D-COS to analyzing MPs for environmental analysis. As an example, 2D-COS currently is not capable of establishing causal relationships between environmental perturbations and observed spectral changes (1). Therefore, it can identify correlations, but it cannot dive too deeply into them, which prevents scientists from independently attributing any changes to one variable, such as temperature or chemical interactions (1).

Additionally, the researchers note that subtle spectral variations can be amplified by 2D-COS. The problem with this is that it requires researchers to be more diligent in interpreting signals to avoid inaccuracies (1). As Dongbin Wei and colleagues note, synergizing 2D-COS with other advanced detection methods could address these current limitations, enhancing the reliability and scope of MPs research (1).

Therefore, this review article helps explain, on a general level, how 2D-COS is being applied in environmental analysis. Where the use of 2D-COS is progressing is not completely clear, but the authors believe that the next step in this research will be for researchers to try and alleviate some of the existing limitations of the technique described previously. 2D-COS is expected to be combined with other detection technologies, so that researchers can achieve more accurate assessments of MPs’ aging processes and interactions with the environmental (1). This integrated approach may not only advance our understanding of MPs' ecological behaviors, but it may also contribute to the formulation of targeted MP mitigation strategies.

References

  1. Peng, S.; Wang, F.; Wei, D.; et al. Application of FTIR Two-dimensional Correlation Spectroscopy (2D-COS) Analysis in Characterizing Environmental Behaviors of Microplastics: A Systematic Review. J. Environ. Sci. 2025, 147, 200–216. DOI: 10.1016/j.jes.2023.10.004
  2. Wetzel, W. An Inside Look at the Fundamentals and Principles of Two-Dimensional Correlation Spectroscopy. Spectroscopy. Available at: https://www.spectroscopyonline.com/view/an-inside-look-at-the-fundamentals-and-principles-of-two-dimensional-correlation-spectroscopy (accessed 2025-01-16).
  3. NIST, Advanced Spectral Analysis: Two-Dimensional Correlation Spectroscopy (2DCOS). NIST.gov. Available at: https://www.nist.gov/programs-projects/advanced-spectral-analysis-two-dimensional-correlation-spectroscopy-2dcos#:~:text=The%202DCOS%20method%20compares%20spectral,correlations%20between%20two%20spectral%20components (accessed 2025-01-13).
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