Discrimination of Microplastics and Phytoplankton Using Impedance Cytometry

Area of Science:

• Marine biology
• Environmental science
• Microparticle analysis

Background:

• Microplastics and phytoplankton coexist as suspended microparticles in marine environments.
• Effective monitoring of plankton communities and microplastic pollution requires high-throughput, deployable identification technologies.
• Existing methods struggle with specificity, throughput, deployability, and analyzing particles below 10 μm.

Purpose of the Study:

• To develop and present a novel impedance cytometer for discriminating and counting microplastics and phytoplankton.
• To address the need for in situ analysis of small microparticles (1.5-10 μm) in marine environments.
• To create a sensitive, rugged, and mass-producible technology for marine deployment.

Main Methods:

• Utilized impedance cytometry with microfluidic chips and integrated microelectrodes to measure individual particle impedance.
• Employed dual-frequency impedance measurements (1 MHz for size, 500 MHz for internal composition) for particle characterization.
• Applied a simple machine learning algorithm for classifying microplastic particles within a mixture.

Main Results:

• Successfully discriminated and counted microplastic particles in the 1.5-10 μm size range from a mixture with phytoplankton.
• Demonstrated the ability to differentiate particles based on size and internal electrical properties.
• Validated the potential for in situ marine application due to the chip's sensitivity and ruggedness.

Conclusions:

• The developed impedance cytometer shows significant promise for real-time, in situ monitoring of microplastics and phytoplankton in marine ecosystems.
• The technology is suitable for analyzing the abundant, yet often overlooked, smallest size fractions of microparticles.
• The mass-producible nature of the microfluidic chip supports widespread adoption for environmental monitoring.