Toward the Systematic Identification of Microplastics in the Environment: Evaluation of a New Independent Software Tool (siMPle) for Spectroscopic Analysis

Primpke, Sebastian; Cross, Richard; Mintenig, Svenja M.; Simon, Márta; Vianello, Alvise; Gerdts, Gunnar; Vollertsen, Jes

doi:10.1177/0003702820917760

Cited by 156 publications

(121 citation statements)

References 36 publications

(108 reference statements)

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“…Free image analysis software (e.g., MPhunter/siMPle) [122,123] and computer vision-based systems (e.g., SMACC) [118,120] can be used, respectively, on the one hand for the systematic chemical identification of MPs, and on the other hand, for the automatic counting and classification of MPs in the environment, reducing the data calculation time and the human bias during manual data analysis.…”

Section: Quantification and Identificationmentioning

confidence: 99%

A Practical Overview of Methodologies for Sampling and Analysis of Microplastics in Riverine Environments

et al. 2020

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Microplastics have recently been stated as being remarkable contaminants of all environmental matrices. The lack of consistent and standardised methods and protocols used to evaluate and quantify microplastics present in riverine systems made a comparison among different studies a critical issue. Based on literature research and the practical expertise of the authors, this work presents a complete collection and analysis of procedures concerning the monitoring of microplastics in riverine environments, focusing on their sampling and analytical protocols to identify, quantify, and characterise them. Further details regarding the advantages and disadvantages of each analytical technique described, such as general recommendations and suggestions, are provided to give practical support for analytical procedures. In particular, microplastics studies consist firstly of their sampling from the aquatic compartment (aqueous and solid phase). Based on the goal of the research, specific devices can be used to collect particles from different matrices. It follows their quantification after extraction from the environmental matrix, adopting different protocols to isolate microplastics from a large amount of organic matter present in a riverine system. In the end, additional qualitative analyses (e.g., RAMAN and FTIR spectroscopy, GC-MS) are required to identify the chemical composition of particles for a better image regarding the abundance of polymer types, their origin, or other information related to manufacturing processes.

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Section: Quantification and Identificationmentioning

confidence: 99%

A Practical Overview of Methodologies for Sampling and Analysis of Microplastics in Riverine Environments

et al. 2020

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“…A few open access tools developed specifically for plastic that are available now are Open Specy 71 and siMPle. 72 In publications using spectral data analyses, smoothing, baseline correction, data transformation, and background subtraction processing steps should be discussed. In this review, very few of the papers that used spectroscopy mentioned any of these topics, much less discussed them in the level of detail required to support reproducibility.…”

Section: Opportunities For Spectra Data Processing Developmentmentioning

confidence: 99%

Critical Review of Processing and Classification Techniques for Images and Spectra in Microplastic Research

et al. 2020

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“…To calculate the mass, the ratio (R D ) between minor and major dimension of all determined MP of one sample (Holdorf1708) was calculated. A median value of 0.7 ± 0.3 was achieved, which was used for all further calculations as well as the individual densities ρ polymer of the siMPle database [34].…”

Section: Mass Estimationmentioning

confidence: 99%

“…One of the most applied or amended approaches [ 3 ] is currently based on the automated analysis pipeline (AAP) [ 23 ] using vector-normalized spectra and a specialized database [ 33 ]. This approach has the advantage to exclude human bias nearly completely and to operate via free of charge accessible tools based on Python scripts and the software siMPle [ 34 ].…”

Section: Introductionmentioning

confidence: 99%

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Comparison of pyrolysis gas chromatography/mass spectrometry and hyperspectral FTIR imaging spectroscopy for the analysis of microplastics

et al. 2020

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Analysis of microplastics (MP) in environmental samples is an emerging field, which is performed with various methods and instruments based either on spectroscopy or thermoanalytical methods. In general, both approaches result in two different types of data sets that are either mass or particle number related. Depending on detection limits of the respective method and instrumentation the derived polymer composition trends may vary. In this study, we compare the results of hyperspectral Fourier-transform infrared (FTIR) imaging analysis and pyrolysis gas chromatography-mass spectrometry (Py-GC/MS) analysis performed on a set of environmental samples that differ in complexity and degree of microplastic contamination. The measurements were conducted consecutively, and on exactly the same sample. First, the samples were investigated with FTIR using aluminum oxide filters; subsequently, these were crushed, transferred to glass fiber filters, in pyrolysis cups, and measured via Py-GC/MS. After a general data harmonization step, the trends in MP contamination were thoroughly investigated with regard to the respective sample set and the derived polymer compositions. While the overall trends in MP contamination were very similar, differences were observed in the polymer compositions. Furthermore, polymer masses were empirically calculated from FTIR data and compared with the Py-GC/MS results. Here, a most plausible shape-related overestimation of the calculated polymer masses was observed in samples with larger particles and increased particle numbers. Taking into account the different measurement principles of both methods, all results were examined and discussed, and future needs for harmonization of intermethodological results were identified and highlighted.

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Toward the Systematic Identification of Microplastics in the Environment: Evaluation of a New Independent Software Tool (siMPle) for Spectroscopic Analysis

Cited by 156 publications

References 36 publications

A Practical Overview of Methodologies for Sampling and Analysis of Microplastics in Riverine Environments

A Practical Overview of Methodologies for Sampling and Analysis of Microplastics in Riverine Environments

Critical Review of Processing and Classification Techniques for Images and Spectra in Microplastic Research

Comparison of pyrolysis gas chromatography/mass spectrometry and hyperspectral FTIR imaging spectroscopy for the analysis of microplastics

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