In this work, the application of Short-Wave Infrared (SWIR: 1000–2500 nm) spectroscopy was evaluated to identify plastic waste containing brominated flame retardants (BFRs) using two different technologies: a portable spectroradiometer, providing spectra of single spots, and a hyperspectral imaging (HSI) platform, acquiring spectral images. X-ray Fluorescence (XRF) analysis was preliminarily performed on plastic scraps to analyze their bromine content. Chemometric methods were then applied to identify brominated plastics and polymer types. Principal Component Analysis (PCA) was carried out to explore collected data and define the best preprocessing strategies, followed by Partial Least Squares—Discriminant Analysis (PLS-DA), used as a classification method. Plastic fragments were classified into “High Br content” (Br > 2000 mg/kg) and “Low Br content” (Br < 2000 mg/kg). The identified polymers were acrylonitrile butadiene styrene (ABS) and polystyrene (PS). Correct recognition of 89–90%, independently from the applied technique, was achieved for brominated plastics, whereas a correct recognition ranging from 81 to 89% for polymer type was reached. The study demonstrated as a systematic utilization of both the approaches at the industrial level and/or at laboratory scale for quality control can be envisaged especially considering their ease of use and the short detection response.

In this study, the possibility of applying the hyperspectral imaging (HSI) technique in the Short-Wave InfraRed (SWIR) spectral range to characterize polymeric parts coming from Waste from Electric and Electronic Equipment (WEEE) is explored. Different case studies are presented referring to the identification of (i) plastic flakes inside a mixed waste stream coming from a recycling plant of monitors and flat screens, (ii) different polymers inside a mixed plastic waste stream coming from End-Of-Life (EOL) electronic device housings and trims, (iii) contaminants (i.e., metals) in a mix of shredded plastic particles coming from a recycling line of electrical cables, and (iv) brominated plastics in mixed streams constituted by small appliances (i.e., cathode-ray tube televisions and monitors). The application of chemometric techniques to hyperspectral data demonstrated the potentiality of this approach for systematic utilization for material characterization, quality control and sorting purposes. The experimental findings highlight the feasibility of employing this method due to its user-friendly nature and quick detection response. To increase and optimize WEEE valorization avoiding disposal in landfills or incineration, recycling-oriented characterization and/or quality control of the processed products are fundamental to identify and quantify substances to be recovered.

Waste management is a crucial global issue that affects both society and the environment

This paper reported a study based on the application of SWIR (shortwave infrared) spectroscopy to assess the presence of brominated flame retardants (BFRs) in plastic scraps coming from an e-waste stream composed by CRT (i.e., cathode-ray tube) monitors and televisions. An X-ray fluorescence (XRF) analysis was performed on plastic scraps to determine the presence and content of bromine (Br). The presence in plastic waste-flow streams, fed to or resulting from a recycling process, of individuals characterized by high concentrations of Br does not allow their use as secondary raw materials, imposing the need for an ad hoc separation processes. Chemometric methods were adopted for setting up models able to discriminate Br content. In more detail, principal component analysis (PCA) was used as an exploratory tool, while partial least squares (PLS) and locally weighted regression based on PLS regressions (LWRPLS) were used as multivariate regression models to test the ability of the spectra to predict Br content. The LWRPLS, showing an R_p² of about 0.9, demonstrates the ability of this algorithm to establish a good correlation between the spectral signatures of plastic scraps and their Br content.