Data preprocessing & evaluation used in the microplastics identification process: A critical review & practical guide

Abstract Characterising microplastics based on spectroscopic measurements is one key step of many studies that analyse the fate of microplastics in the environment. Over the years, many potential sources of error were identified, which can be seen by the implementation of anti-contamination protocols, measuring laboratory blanks or using less aggressive chemicals for sample purification. However, the identification process itself in the meaning of a traceable and transparent documentation is hard to find in many research studies. Unfortunately, this can make it difficult to estimate if the presented results are representative and reproducible, as the evaluation process during microplastics identification depends dramatically on the performed data treatment. To increase the awareness of this often neglected topic, this article reviews suitable data preprocessing and evaluation methods for microplastics identification based on spectroscopic measurements and will recommend a practical workflow or check list that can easily be used for further research studies.

• Publication year

  2019

• Venue

  Trends in Analytical Chemistry (TrAC)

• Publication date

  2019-02-01

• Fields of study

  Materials Science, Computer Science, Environmental Science

• Identifiers
  DOI 10.1016/J.TRAC.2018.12.004
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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