Identification Tools of Microplastics from Surface Water Integrating Digital Image Processing and Statistical...

Area of Science:

• Environmental Science
• Analytical Chemistry
• Materials Science

Background:

• Microplastic (MP) pollution is a significant environmental concern in aquatic ecosystems.
• Accurate identification and characterization of MPs are essential for effective monitoring and mitigation.

Purpose of the Study:

• To demonstrate the potential of digital image analysis for identifying and characterizing microplastic particles in surface waters.
• To evaluate the 2D and 3D morphology of microplastics using advanced image processing techniques.

Main Methods:

• Microscopic analysis followed by digital image analysis of microplastic particles isolated from the Vistula River.
• Determination of 2D and 3D shape descriptors using image processing procedures.
• Multivariate analysis, including Principal Component Analysis (PCA), to interpret relationships between MP morphology, type, and color.

Main Results:

• Digital image analysis successfully characterized microplastic morphology, with PCA explaining approximately 90% of the variation.
• Strong correlations were found between 2D and 3D shape descriptors for granules, flakes, and films.
• A relationship between 2D shape and particle color was observed for granules, flakes, and films, but not for multicoloured scraps.

Conclusions:

• Digital image analysis is a valuable tool for microplastic identification and characterization in surface waters.
• Understanding microplastic morphology and its relationship with particle type and color is key for targeted monitoring and reduction efforts.
• The findings support the optimization of future monitoring strategies for aquatic plastic pollution, particularly for secondary microplastics.