Nowadays, the detection of microplastics (MPs) is an emerging critical issue in environmental and analytical science. Thus far, there is no standardized method for the identification and quantification of MPs (Nguyen et al., 2019). One method can be the visual identification without further chemical identification, which has a high potential of false counts. Therefore, chemical identification is indispensable to monitor. To determine the mass of plastic within the sample, mass spectrometry could be combined with pyrolysis gas chromatography or thermal extraction desorption gas chromatography. Both methods allow the chemical identification of the polymer types as well as the determination of mass of MPs in the sample; nonetheless, through these processes, the sample is destroyed and particle sizes and numbers cannot be calculated. In addition, these methods are time - and reagent-consuming analytical procedures because they require concentration or separation steps that present also a limiting factor in terms of sample load. Currently, Fourier Transform Infrared Spectroscopy (FTIR) is widely recognized as a reliable tool for nondestructive analysis and it is a rapidly expanding research area. In particular, Fourier transform infrared photoacoustic spectroscopy (FTIR-PAS) has been applied in many fields, such as soil physical and chemical properties analysis (Xing et al., 2016), identification of plant diseases (Andrade et al., 2008), gas monitoring (Wang and Wang, 2016), and food safety (Yang and Irudayaraj, 2001). However, the scope of FTIR-PAS to identify MPs nature remains unexplored. To set up a general spectral database, different plastic samples from different suppliers were measured with a FTIR Perkin-Elmer Spectrum GX2000 spectrometer (running under Spectrum 5.0 software) with a MTEC 300 detector (MTEC, Ames, IA). Samples were placed in the photoacoustic cup for direct determination in the infrared photoacoustic spectrum. Before the determination was made, helium was purged for 5 min (at a slow flow rate of 5 cm 3 sec -1 to prevent fine particles spreading) to reduce the infrared absorption interference from carbon dioxide and water in the air. All spectra were collected in the wavenumber range of 4000 to 400 cm -1 at 4 cm -1 resolution. Each sample was scanned 256 times in succession: the final spectra was the merging version resulting from all these scans. All spectra were made compatible so they contain the same number of wavenumber datapoints in the considered spectral range (x axis). Spectra with a low signal-to-noise ratio were excluded afterwards. An initial charcoal blank spectrum was run to test the spectrometer performance and as a reference for calculating the sample spectra in photoacoustic units. At the end of the analysis, sample spectra were processed using The Unscrambler 10.4 software to detect differences, if present, among different type of polymers. After the collection of all database spectra, it was possible to distinguish among samples and all materials could be well separated by cluster analysis. The statistical hierarchical cluster analysis well separated spectra of different polymers. A dendrogram was obtained when normalized spectra from the FTIR-PAS database were subjected to a hierarchical cluster analysis. A number was assigned to each spectra and a library with database entries was created. From the results of the analysis, FTIR-PAS has proven to be a versatile, bias-free tool to succeed at the prefixed task. It could overcome the disadvantage of time-costing (measurements take only about 20-30 min/sample totally; as a comparison, the fastest thermal degradation methods take approximately 2-3 h per sample) and rapidly assess chemical composition of microplastics without any chemical pretreatment. Due to differences in their chemical structure and composition, polymers exposed to Fourier transform infrared photoacoustic radiation displayed characteristic absorption patterns which allow the distinction. In this work, through statistical analysis and clustering of spectra, the basis for an adaptable reference database for the analysis of MPs has be provided. Moreover, the database can be expanded with new spectra in the future, by allowing the implementation. Finally, as FTIR-PAS has been successfully used for the identification of many components of complex matrices, such as bulk sediment samples using calibration databases between spectra of the sediment and known values of the detrital component, in the next future similar models for the detection of microplastics in food could be established. Bibliography Yang H, Irudaraj J. 2001. Characterization of Beef and Pork using Fourier-Transform Infrared Photoacoustic Spectroscopy. LWT Food Sci Technol 34(6): 402-409. Andrade L, Freitas P, Mantovani B, Figueiredo M, Lima R, Lima S, Rangel M, Mussury R. 2008. Detection of soybean rust contamination in soy leaves by FTIR photoacoustic spectroscopy. Eur Phys J Spec Top 153,539-541. Wang J, Wang H. 2016. Ammonia, carbon dioxide and water vapor detection based on tunable fiber laser photoacoustic spectroscopy. Optik 127(2): 942-945. Xing Z, Du C, Tian K, Ma F, Shen Y, Zhou J. 2016. Application of FTIR-PAS and Raman spectroscopies for the determination of organic matter in farmland soils. Talanta. 158:262-269. Nguyen B, Claveau-Mallet D, Hernandez LM, Xu EG, Farner JM, Tufenkji N. 2019. Separation and Analysis of Microplastics and Nanoplastics in Complex Environmental Samples. Acc Chem Res. 52(4):858-866.
A rapid method for the identification and classification of microplastics based on Fourier transform infrared photoacoustic spectroscopy (FTIR-PAS)
Di Lonardo S;Bonetti A;D'Acqui LP
2021
Abstract
Nowadays, the detection of microplastics (MPs) is an emerging critical issue in environmental and analytical science. Thus far, there is no standardized method for the identification and quantification of MPs (Nguyen et al., 2019). One method can be the visual identification without further chemical identification, which has a high potential of false counts. Therefore, chemical identification is indispensable to monitor. To determine the mass of plastic within the sample, mass spectrometry could be combined with pyrolysis gas chromatography or thermal extraction desorption gas chromatography. Both methods allow the chemical identification of the polymer types as well as the determination of mass of MPs in the sample; nonetheless, through these processes, the sample is destroyed and particle sizes and numbers cannot be calculated. In addition, these methods are time - and reagent-consuming analytical procedures because they require concentration or separation steps that present also a limiting factor in terms of sample load. Currently, Fourier Transform Infrared Spectroscopy (FTIR) is widely recognized as a reliable tool for nondestructive analysis and it is a rapidly expanding research area. In particular, Fourier transform infrared photoacoustic spectroscopy (FTIR-PAS) has been applied in many fields, such as soil physical and chemical properties analysis (Xing et al., 2016), identification of plant diseases (Andrade et al., 2008), gas monitoring (Wang and Wang, 2016), and food safety (Yang and Irudayaraj, 2001). However, the scope of FTIR-PAS to identify MPs nature remains unexplored. To set up a general spectral database, different plastic samples from different suppliers were measured with a FTIR Perkin-Elmer Spectrum GX2000 spectrometer (running under Spectrum 5.0 software) with a MTEC 300 detector (MTEC, Ames, IA). Samples were placed in the photoacoustic cup for direct determination in the infrared photoacoustic spectrum. Before the determination was made, helium was purged for 5 min (at a slow flow rate of 5 cm 3 sec -1 to prevent fine particles spreading) to reduce the infrared absorption interference from carbon dioxide and water in the air. All spectra were collected in the wavenumber range of 4000 to 400 cm -1 at 4 cm -1 resolution. Each sample was scanned 256 times in succession: the final spectra was the merging version resulting from all these scans. All spectra were made compatible so they contain the same number of wavenumber datapoints in the considered spectral range (x axis). Spectra with a low signal-to-noise ratio were excluded afterwards. An initial charcoal blank spectrum was run to test the spectrometer performance and as a reference for calculating the sample spectra in photoacoustic units. At the end of the analysis, sample spectra were processed using The Unscrambler 10.4 software to detect differences, if present, among different type of polymers. After the collection of all database spectra, it was possible to distinguish among samples and all materials could be well separated by cluster analysis. The statistical hierarchical cluster analysis well separated spectra of different polymers. A dendrogram was obtained when normalized spectra from the FTIR-PAS database were subjected to a hierarchical cluster analysis. A number was assigned to each spectra and a library with database entries was created. From the results of the analysis, FTIR-PAS has proven to be a versatile, bias-free tool to succeed at the prefixed task. It could overcome the disadvantage of time-costing (measurements take only about 20-30 min/sample totally; as a comparison, the fastest thermal degradation methods take approximately 2-3 h per sample) and rapidly assess chemical composition of microplastics without any chemical pretreatment. Due to differences in their chemical structure and composition, polymers exposed to Fourier transform infrared photoacoustic radiation displayed characteristic absorption patterns which allow the distinction. In this work, through statistical analysis and clustering of spectra, the basis for an adaptable reference database for the analysis of MPs has be provided. Moreover, the database can be expanded with new spectra in the future, by allowing the implementation. Finally, as FTIR-PAS has been successfully used for the identification of many components of complex matrices, such as bulk sediment samples using calibration databases between spectra of the sediment and known values of the detrital component, in the next future similar models for the detection of microplastics in food could be established. Bibliography Yang H, Irudaraj J. 2001. Characterization of Beef and Pork using Fourier-Transform Infrared Photoacoustic Spectroscopy. LWT Food Sci Technol 34(6): 402-409. Andrade L, Freitas P, Mantovani B, Figueiredo M, Lima R, Lima S, Rangel M, Mussury R. 2008. Detection of soybean rust contamination in soy leaves by FTIR photoacoustic spectroscopy. Eur Phys J Spec Top 153,539-541. Wang J, Wang H. 2016. Ammonia, carbon dioxide and water vapor detection based on tunable fiber laser photoacoustic spectroscopy. Optik 127(2): 942-945. Xing Z, Du C, Tian K, Ma F, Shen Y, Zhou J. 2016. Application of FTIR-PAS and Raman spectroscopies for the determination of organic matter in farmland soils. Talanta. 158:262-269. Nguyen B, Claveau-Mallet D, Hernandez LM, Xu EG, Farner JM, Tufenkji N. 2019. Separation and Analysis of Microplastics and Nanoplastics in Complex Environmental Samples. Acc Chem Res. 52(4):858-866.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
