Lecture
From Detection to Decision: Assessing SP ICP‑MS for Comprehensive Microplastic Analysis in an Industrial Laboratory
- at -
- ICM Saal 5
- Type: Lecture
Lecture description
K. Vogel, Stade/DE, A. Wegener, Stade/DE, E. Idi, Münster/DE, M. Elinkmann, Graz/AT
Polymeric microplastics have become an emerging class of anthropogenic particles of global interest, driving the need for robust and scalable analytical methods (e.g., [1]). Due to the complex nature of microplastics (MP), a comprehensive characterization therefore relies on complementary analytical approaches. Established techniques such as Raman & Fourier transform infrared (FT-IR) spectroscopy and pyrolysis gas
chromatography-mass spectrometry (py-GC-MS) allow the identification of the polymeric backbone of the material and the nature of the compound but often require extensive sample preparation and are not ideally suited for rapid screening in routine industrial laboratories.
In the present work, single‑particle inductively coupled plasma-mass spectrometry (SP ICP‑MS) is evaluated as a complementary screening approach for polymeric microparticles in an industrial environment. Carbon detection was implemented on a triple‑quadrupole ICP‑MS using an oxygen mass‑shift method, enabling particle detection and size determination with minimal sample preparation. Polystyrene reference particles and self-made polyolefin‑based materials, including silicon‑tagged polymers, were investigated to assess sensitivity, robustness, and practical feasibility. In addition to carbon‑based particle detection, silicon analysis supported the assessment of tagged materials.
Single‑event data evaluation was performed using the open‑source tools spTool and spCal, which enable statistically robust processing of large SP ICP‑MS data sets and reliable determination of particle size and mass distributions [2–4].
The results demonstrate that SP ICP‑MS, combined with open‑source data evaluation tools, enables rapid particle screening and contamination control using instrumentation already available in many routine laboratories. Advantages and current limitations of the approach are discussed, highlighting its potential role in supporting microplastic analytics and reference material development in an industrial context.
Literature:
[1] P.-F. Fu and S. Yang, J. Polym. Sci. Part A: Polym. Chem., 2018, 56, 1308-1321.
[2] T. E. Lockwood et al., J. Anal. At. Spectrom., 2021, 36, 2536-2544.
[3] T. E. Lockwood et al., J. Anal. At. Spectrom., 2025, 40, 130-136.
[4] M. Elinkmann et al., J. Anal. At. Spectrom., 2023, 38, 2607-2618.
Polymeric microplastics have become an emerging class of anthropogenic particles of global interest, driving the need for robust and scalable analytical methods (e.g., [1]). Due to the complex nature of microplastics (MP), a comprehensive characterization therefore relies on complementary analytical approaches. Established techniques such as Raman & Fourier transform infrared (FT-IR) spectroscopy and pyrolysis gas
chromatography-mass spectrometry (py-GC-MS) allow the identification of the polymeric backbone of the material and the nature of the compound but often require extensive sample preparation and are not ideally suited for rapid screening in routine industrial laboratories.
In the present work, single‑particle inductively coupled plasma-mass spectrometry (SP ICP‑MS) is evaluated as a complementary screening approach for polymeric microparticles in an industrial environment. Carbon detection was implemented on a triple‑quadrupole ICP‑MS using an oxygen mass‑shift method, enabling particle detection and size determination with minimal sample preparation. Polystyrene reference particles and self-made polyolefin‑based materials, including silicon‑tagged polymers, were investigated to assess sensitivity, robustness, and practical feasibility. In addition to carbon‑based particle detection, silicon analysis supported the assessment of tagged materials.
Single‑event data evaluation was performed using the open‑source tools spTool and spCal, which enable statistically robust processing of large SP ICP‑MS data sets and reliable determination of particle size and mass distributions [2–4].
The results demonstrate that SP ICP‑MS, combined with open‑source data evaluation tools, enables rapid particle screening and contamination control using instrumentation already available in many routine laboratories. Advantages and current limitations of the approach are discussed, highlighting its potential role in supporting microplastic analytics and reference material development in an industrial context.
Literature:
[1] P.-F. Fu and S. Yang, J. Polym. Sci. Part A: Polym. Chem., 2018, 56, 1308-1321.
[2] T. E. Lockwood et al., J. Anal. At. Spectrom., 2021, 36, 2536-2544.
[3] T. E. Lockwood et al., J. Anal. At. Spectrom., 2025, 40, 130-136.
[4] M. Elinkmann et al., J. Anal. At. Spectrom., 2023, 38, 2607-2618.
