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KnowItAll Microplastic Classification

Mo, 18.3.2024
| Original article from: LabRulez
Comparison of microplastic IR spectra to parent polymers available in KnowItAll IR Spectral Library exhibit similar characteristics and can be used for unknown microplastic identification.
<ul>
<li><strong>photo:</strong> Wiley: KnowItAll Microplastic Classification</li>
</ul>
  • photo: Wiley: KnowItAll Microplastic Classification

Authors: Michelle D’Souza, Ph. D., Graeme Whitley, Natalie Clines, Keith Kunitsky, Gabrielle Bethancourt-Hughes, Zille Huma (Wiley Science Solutions)

Microplastics are everywhere [1-3]. Studies have found that they have profound impacts on lives across species. Environmental sample classification/identification has received a lot of attention lately. One popular method is to apply IR/Raman spectroscopy technologies [2,4,5]. These technologies have proven records of effectiveness in analyzing polymers, which are parents of microplastics. However, it is not easy to collect samples to make reliable reference spectral databases for unknown comparison. Spectrum analysis organizations are under pressure to provide a quick, easy and low-cost tool to meet this challenge.

Visual comparison of typical microplastic IR spectra [4,5] to those of parent polymers available in KnowItAll IR Spectral Library [ 6,7] lead us to believe that microplastic IR spectra exhibit similar characteristics. Therefore, “classification spectra” have been derived by using patented Overlap Density Heat Map (ODHM) technology. Our study suggests that these classification spectra can be used for unknown microplastic classification. Combined with the massive KnowItAll IR databases offered by Wiley, one can identify microplastics.

Wiley: KnowItAll Microplastic Classification - Introduction

Research has also shown that Raman spectrum of microplastics can be compared to that of the parent polymers [2]. We suggest using the KnowItAll Raman Spectral Library [6,7], the largest collection, for microplastic identification.

Method

IR

The IR Microplastic Classifications spectral database was created using patented ODHM technology.
Currently, it has these classes and is extendable:

  • Polyethylene (IR and ATR-IR)
  • Polyacrylate (IR)
  • Polyamide (IR and ATR-IR)
  • Polycarbonate (IR and ATR-IR)
  • Polypropylene (IR and ATR-IR)
  • Polystyrene (IR and ATR-IR)
  • Polyvinylchloride (IR and ATR-IR)
  • Chlorinated Polyvinylchloride (IR)
  • Polyester (IR)

Microplastic testing datasets (IR and Raman) have been obtained from open sources, such as the US EPA [8], the University of Southampton [9] and OpenSpecy [10], to evaluate the IR Microplastics Classifications database. Class separations and classifications have been studied. The effect of classification spectra used in combination with real plastic database spectra has also been researched.

Raman

We examined various classes of plastic Raman spectra and concluded that it is difficult to build classification spectra for each plastic class. Since the Wiley Raman spectrum collection is relatively small and inexpensive, one can identify microplastics [8] using the existing Raman data collection.

Results and Discussion

IR microplastic classification and class separation

A correlation algorithm was used to compare spectra of microplastics from the three test datasets against the IR Microplastic Classifications database. Carbon dioxide and water vapor peaks existing in sample spectra were excluded from the spectral comparison. Matches were judged by good peak alignment as well as Hit Quality Index (HQI) values. Below are the results of those studies.

US EPA Dataset

IR: 89 spectra and 11 types
Raman: 60 records

There are replicated IR samples per microplastic class; we chose one example to report. We observed good HQI values and peak alignments among hits (Table 1). We also observed good separations and poor peak alignments in the second hit class. (https://catalog.data.gov/dataset/isotope-ratio-massspectrometry- irms-and-spectroscopic-techniques-for-microplastic-charact)

Table 1 - EPA dataset to test microplastic classification spectra
Wiley: KnowItAll Microplastic Classification: Table 1 - EPA dataset to test microplastic classification spectra

U. of Southampton

IR - 2,675 spectra

None of the sample spectra were labeled for a particular class. For replicate samplings, we chose one of the replicate spectra for testing. The results are listed in Table 2.

Table 2 - Southampton samples to test microplastic classification spectra
Wiley: KnowItAll Microplastic Classification: Table 2 - Southampton samples to test microplastic classification spectra

Open Specy

IR/ATR-IR - 636 spectra

Most of the spectra in this database are ATR-IR. Many sample spectra resemble each other. For these cases, we selected one spectrum per for test purposes. As displayed in Table 3, the spectra were classified effectively.

Table 3 - OpenSpecy samples to test microplastic classification spectra
Wiley: KnowItAll Microplastic Classification: Table 3 - OpenSpecy samples to test microplastic classification spectra

Examples of using the Spectroscopy Edition for unknown microplastic classification and identification:

Due to the urgent need for microplastic analysis, we are including the microplastic classification spectral database with the KnowItAll Spectroscopy Edition so users can make immediate impact in this important area of research critical to our environment.

Figure 1. IR - EPS.0_Microplastic
Wiley: KnowItAll Microplastic Classification: Figure 1. IR - EPS.0_Microplastic

Figure 2. IR - Clear Blue Water Bottle_Microplastic
Wiley: KnowItAll Microplastic Classification: Figure 2. IR - Clear Blue Water Bottle_Microplastic

In this case, the sample spectrum best matches that of a commercial polymer product. However, one cannot easily identify the polymer. The classification spectrum match is the 6th hit, classifying the unknown parent as polyester.

Figure 3a. IR - Brown Lid_Microplastic
Wiley: KnowItAll Microplastic Classification: Figure 3a. IR - Brown Lid_Microplastic

Figure 3b. IR - Detail of 3a - Brown Lid_Microplastic
Wiley: KnowItAll Microplastic Classification: Figure 3b. IR - Detail of 3a - Brown Lid_Microplastic

Again, identification of an unknown to a commercial name means very little. The microplastic spectrum classifies this example’s parent compound as polyethylene.

Figure 4. Raman - HDPE Bead_Microplastic
Wiley: KnowItAll Microplastic Classification: Figure 4. Raman - HDPE Bead_Microplastic

Raman microplastic samples can be identified by the Wiley Raman spectral database matching economically and accurately.

Figure 5a. Raman - PS Clear_Microplastic
Wiley: KnowItAll Microplastic Classification: Figure 5a. Raman - PS Clear_Microplastic

Figure 5b. Raman - bad baseline
Wiley: KnowItAll Microplastic Classification: Figure 5b. Raman - bad baseline

The original microplastic sample has a bad baseline (Figure 5b), but this is not a problem for KnowItAll’s Optimized Correction (Figure 5a).

Conclusion

We found that IR/ATR-IR microplastic classification, using classification spectra, is an effective method for classifying unknown microplastic IR samples. Search results provide enough separation in HQI values among classes for the practitioner to have confidence in the classification. The “IR microplastic classification database” returns results instantly.

The microplastic classification database is available in the 2021 maintenance release for the KnowItAll Spectroscopy Edition, and is available as a new feature to all current subscribers. This ensures that all users can address microplastic contamination in an efficient and effective manner. Practitioners who need to perform more comprehensive microplastic identifications should consider adding a subscription to the more inclusive IR and Raman collections.

Resources

[1] National Oceanic and Atmospheric Administration. What are microplastics? (accessed 9 September 2021).

[2] Sh.R. Pozdnyakov, E.V. Ivanova, A.V. Guzeva, E.P. Shalunova, K.D. Martinson, D.A. Tikhonova. (2020). Studying the concentration of microplastic particles in water, bottom sediments and subsoils in the coastal area of the Neva Bay, the Gulf of Finland. Water Resources 47(4): 599–607.

[3] S. Selvam, A. Manisha, S. Venkatramanan, S.Y. Chung, C.R. Paramasivam, C. Singaraja. (2020). Microplastic presence in commercial marine sea salts: A baseline study along Tuticorin Coastal salt pan stations, Gulf of Mannar, South India. Marine Pollution Bulletin 150: 110675.

[4] M.G.J. Löder and G. Gerdts (2015). Methodology Used for the Detection and Identification of Microplastics— A Critical Appraisal. In: Bergmann M., Gutow L., Klages M. (eds) Marine Anthropogenic Litter. Springer, Cham.

[5] S. Tagg, J.P. Harrison, Y. Ju-Nam, M. Sapp, E.L. Bradley, C.J. Sinclair, J.J. Ojeda. (2017). Fenton’s reagent for the rapid and efficient isolation of microplastics from wastewater. Chem. Commun. 53: 372-375.

[6] KnowItAll Software (version 2021). John Wiley & Sons, Inc. Hoboken, NJ (2021). [Computer Software]

[7] KnowItAll IR & Raman Spectral Libraries. John Wiley & Sons, Inc. Hoboken, NJ (2021). [Computer Software]

[8] Isotope ratio mass spectrometry (IRMS) and spectroscopic techniques for microplastic characterization. (2021) U.S. EPA Office of Research and Development (ORD). https://catalog.data.gov/dataset/isotope-ratio-mass-spectrometry-irms-and-spectroscopic-techniques-for-microplasticcharact [Dataset]

[9] Stead, Jessica, Laura (2021) Data: FTIR spectra for particles in subsampled water samples from Southampton Water and analysed for microplastic content. University of Southampton doi:10.5258/SOTON/D1892 [Dataset]

[10] Cowger W, Steinmetz Z, Gray A, Munno K, Lynch J, Hapich H, Primpke S, De Frond H, Rochman C, Herodotou O (2021). “Microplastic Spectral Classification Needs an Open Source Community: Open Specy to the Rescue!” Analytical Chemistry, 93(21), 7543–7548. [Dataset]

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