Rapid detection of colored and colorless macroand micro-plastics in complex environment via near-infrared spectroscopy and machine learning  

作　　者：Hui-Huang Zou Pin-Jing He Wei Peng Dong-Ying Lan Hao-Yang Xian Fan Lü Hua Zhang 

机构地区：[1]Institute of Waste Treatment&Reclamation,College of Environmental Science and Engineering,Tongji University,Shanghai 200092,China [2]Shanghai Institute of Pollution Control and Ecological Security,Shanghai 200092,China

出　　处：《Journal of Environmental Sciences》2025年第1期512-522,共11页环境科学学报(英文版)

基　　金：supported by the National Natural Science Foundation of China(No.22276139);the Shanghai’s Municipal State-owned Assets Supervision and Administration Commission(No.2022028).

摘　　要：To better understand the migration behavior of plastic fragments in the environment,development of rapid non-destructive methods for in-situ identification and characterization of plastic fragments is necessary.However,most of the studies had focused only on colored plastic fragments,ignoring colorless plastic fragments and the effects of different environmental media(backgrounds),thus underestimating their abundance.To address this issue,the present study used near-infrared spectroscopy to compare the identification of colored and colorless plastic fragments based on partial least squares-discriminant analysis(PLS-DA),extreme gradient boost,support vector machine and random forest classifier.The effects of polymer color,type,thickness,and background on the plastic fragments classification were evaluated.PLS-DA presented the best and most stable outcome,with higher robustness and lower misclassification rate.All models frequently misinterpreted colorless plastic fragments and its background when the fragment thickness was less than 0.1mm.A two-stage modeling method,which first distinguishes the plastic types and then identifies colorless plastic fragments that had been misclassified as background,was proposed.The method presented an accuracy higher than 99%in different backgrounds.In summary,this study developed a novel method for rapid and synchronous identification of colored and colorless plastic fragments under complex environmental backgrounds.

关 键 词：Colorless microplastics Near-infrared hyperspectral imaging Plastic identification Partial least squares discriminant analysis Machine learning 

分 类 号：X832[环境科学与工程—环境工程]