4.7 Article

Influence of interaction on accuracy of quantification of mixed microplastics using Py-GC/MS

Journal

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jece.2022.108012

Keywords

Microplastics; Quantification; Co-pyrolysis; Interaction; Py-GC; MS

Funding

  1. National Natural Science Foundation of China [52076190]
  2. Key Research and Development Program of Zhejiang Province [2022C03082]
  3. Zhe-jiang University Ecological Civilization Plan

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Accurate identification and quantification of microplastics (MPs) is challenging yet crucial. This study used pyrolysis gas chromatography mass spectrometry (Py-GC/MS) to detect five common types of MPs and investigated the thermochemical interactions during co-pyrolysis of different plastics. The results showed that previous indicators for quantitative analysis may lead to high uncertainty, but new indicators were proposed in this study to improve accuracy. The maximum quantification uncertainties of PE, PP, and PS were successfully reduced.
Accurate identification and quantification are very challenging and extremely important in evaluating microplastic (MP) pollution. Although pyrolysis-based MP measurement methods have attracted intensive interest due to their great potential for rapid qualitative and quantitative analysis, the influence of thermochemical interactions during co-pyrolysis of different plastics has not been addressed. In the present study, five common MP materials, polyethylene (PE), polypropylene (PP), polystyrene (PS), polyvinyl chloride (PVC), and polymethyl methacrylate (PMMA), were detected using pyrolysis gas chromatography mass spectrometry (Py-GC/MS). The existence of interactions was confirmed by comparing the experimental results of individual and mixed pyrolysis. Upon the specific analysis of the impact on the quantitative calculation, we found that some indicators selected in previous studies may lead to high uncertainty, exceeding 100%. On this basis, new indicators with better reliability were proposed for the quantitative analysis of mixed MP samples, including 1- octadecene, pentane, and bibenzyl. Finally, the maximum quantification uncertainties of PE, PP, and PS were reduced from 91-25%, 130-32%, and 93-24%, respectively. The present study can provide a reference for improving the accuracy of quantitative analysis of mixed MPs.

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