Microplastics are small particles of disposed plastic that usually are 5 mm or smaller. Recently, there has been an increased focus to monitor and mitigate plastic waste in the environment. However, colorless fragments of plastic have gone mostly unnoticed, and most current detection methods cannot pick up these bits of plastic.
Researchers from Tongji University in Shanghai and the Shanghai Institute of Pollution Control and Ecological Security explored a new method for detecting plastic pollution in the environment.
The novel method, which uses near-infrared hyperspectral imaging (NIR-HSI) and advanced machine learning (ML) models, was designed to detect colorless fragments of microplastics, which have been overlooked by other detection methods. The findings of this study were in the Journal of Environmental Sciences.
The ability to detect both colored and colorless plastics with high precision is a major advancement in plastic pollution research. Traditional microplastic identification methods often rely on tedious extraction and purification steps, limiting their scalability (1). By eliminating these bottlenecks, this new technique paves the way for large-scale environmental monitoring programs, enabling faster and more comprehensive assessments of plastic contamination.
With plastic pollution continuing to threaten marine and terrestrial ecosystems, such technological advancements will play a crucial role in shaping future environmental policies and sustainability initiatives. This research marks a critical step toward more efficient, large-scale monitoring of plastic waste, providing a promising solution for tackling one of the world’s most persistent environmental challenges.
Source: Spectroscopy, Feb 5, 2025. https://www.spectroscopyonline.com/view/detection-of-colorless-microplastics-in-the-environment-using-nir-spectroscopy-and-machine-learning
China Environment News 