Modeling microplastic with polyethylene (PE) spherical particles: a differential scanning calorimetry approach for...

Area of Science:

• Environmental Science
• Analytical Chemistry
• Materials Science

Background:

• Microplastic detection and quantification are crucial for understanding environmental pollution.
• Thermal analysis offers alternative methods for microplastic quantification.
• Difference scanning calorimetry (DSC) signal can be influenced by microplastic particle size.

Purpose of the Study:

• To investigate the effect of microplastic particle size on DSC signals.
• To evaluate DSC's capability for quantitative microplastic analysis, including mixtures.
• To assess interferences and applicability in real environmental samples.

Main Methods:

• Utilized spherical polyethylene (PE) particles of varying sizes (75-710 μm) as a model.
• Studied the impact of particle size and mixtures on DSC melting curves.
• Analyzed real microplastics isolated from wastewater samples.

Main Results:

• DSC signal (melting temperature and peak shape) is significantly affected by particle size, even in mixtures.
• Appropriate sample preparation enables identification and quantification of different microplastic sizes.
• Inorganic materials alter melting temperature, while organic interferences can be removed.
• Identified polypropylene (PP), high-density polyethylene (HDPE), and low-density polyethylene (LDPE) in wastewater.

Conclusions:

• DSC is a viable technique for microplastic analysis, capable of detecting and quantifying particles of different sizes within a single sample.
• This method allows for estimation of microplastic particle numbers in environmental matrices.
• The study demonstrates DSC's applicability for microplastics in real-world environmental samples.