0
Article Tier 2 Detection Methods Marine & Wildlife Policy & Risk Sign in to save

Plastic waste monitoring and recycling by hyperspectral imaging technology

2019 5 citations

AI summary Read the abstract

This paper presented hyperspectral imaging (HSI) technology coupled with chemometric analysis as a tool for identifying and characterizing microplastics in marine environments, and for monitoring and sorting plastic waste — supporting both pollution monitoring and circular economy recycling goals.

Environmentally sound management of plastic waste is a fundamental achievement in order to move towards circular economy and sustainable patterns of consumption and production. In this work, different emerging applications for plastic waste monitoring and recycling based on hyperspectral imaging (HSI) technology, coupled with chemometric logics, are presented and discussed. Marine microplastics, one of the main environmental concerns, can be recognized and characterized by HSI, providing at the same time information related to the particle morphological and morphometrical attributes. Furthermore, some critical issues in plastic recycling can be solved by HSI, as separation of polyolefins, identification of black polymers and recognition of biopolymers in conventional plastic recycled streams.

More Papers Like This

Article Tier 2

A comprehensive and fast microplastics identification based on near-infrared hyperspectral imaging (HSI-NIR) and chemometrics

AI summary Read the abstract

Researchers developed a near-infrared hyperspectral imaging method combined with chemometric analysis for rapid, high-throughput identification of microplastic types in mixed samples, achieving high classification accuracy and offering a faster alternative to FTIR and Raman methods for routine monitoring.

Article Tier 2

Hyperspectral imaging based approach for monitoring of microplastics from marine environment

AI summary Read the abstract

Researchers explored using hyperspectral imaging sensors to detect and identify different types of microplastics collected from various sea areas, combining spectral analysis with morphological characterization of particle shape and size. The approach shows potential as an automated monitoring tool for marine microplastic surveillance.

Article Tier 2

Microplastics characterization by hyperspectral imaging in the SWIR range

AI summary Read the abstract

Researchers developed a hyperspectral imaging methodology operating in the short-wave infrared range (1000-2500 nm) combined with chemometric classification to rapidly identify polymer types in microplastic samples collected from marine environments. The non-destructive approach enabled polymer characterisation across samples from multiple geographical regions without requiring chemical pre-treatment.

Article Tier 2

Hyperspectral imaging systems (HSI) and chemometric methods for the rapid and direct detection of microplastics

AI summary Read the abstract

Researchers evaluated hyperspectral imaging (HSI) systems combined with chemometric analysis methods as a rapid, direct detection approach for microplastics on filters, avoiding the time-consuming visual pre-sorting and sample purification steps required by conventional spectroscopic methods. The study demonstrated that HSI can identify and map microplastic particles across diverse sample matrices faster and with reduced contamination risk compared to traditional FTIR and Raman approaches.

Article Tier 2

An effective strategy for the monitoring of microplastics in complex aquatic matrices: Exploiting the potential of near infrared hyperspectral imaging (NIR-HSI)

AI summary Read the abstract

Researchers developed a near infrared hyperspectral imaging (NIR-HSI) method for rapid monitoring of microplastics in complex marine matrices, demonstrating effective detection and polymer identification that overcomes the time and cost limitations of conventional spectroscopic analysis approaches.

Research digests by email

When a large batch of papers lands in the Atlas, we read through it and send a short write-up of what stood out.

Email me about

Share this paper