Recycling-oriented characterization of plastic frames and printed circuit boards from mobile phones by electronic and chemical imaging

This study characterizes the composition of plastic frames and printed circuit boards from end-of-life mobile phones. This knowledge may help define an optimal processing strategy for using these items as potential raw materials. Correct handling of such a waste is essential for its further “sustainable” recovery, especially to maximize the extraction of base, rare and precious metals, minimizing the environmental impact of the entire process chain. A combination of electronic and chemical imaging techniques was thus examined, applied and critically evaluated in order to optimize the processing, through the identification and the topological assessment of the materials of interest and their quantitative distribution. To reach this goal, end-of-life mobile phone derived wastes have been systematically characterized adopting both “traditional” (e.g. scanning electronic microscopy combined with microanalysis and Raman spectroscopy) and innovative (e.g. hyperspectral imaging in short wave infrared field) techniques, with reference to frames and printed circuit boards. Results showed as the combination of both the approaches (i.e. traditional and classical) could dramatically improve recycling strategies set up, as well as final products recovery.     

Imaging spectroscopy based strategies for ceramic glass contaminants removal in glass recycling

The presence of ceramic glass contaminants in glass recycling plants reduces production quality and increases production costs. The problem of ceramic glass inspection is related to the fact that its detectable physical and pictorial properties are quite similar to those of glass. As a consequence, at the sorting plant scale, ceramic glass looks like normal glass and is detectable only by specialized personnel. In this paper an innovative approach for ceramic glass recognition, based on imaging spectroscopy, is proposed and investigated. In order to define suitable inspection strategies for the separation between useful (glass) and polluting (ceramic glass) materials, reference samples of glass and ceramic glass presenting different colors, thicknesses, shapes and manufacturing processes have been selected. Reflectance spectra have been obtained using two equipment covering the visible and near infrared wavelength ranges (400-1000 and 1000-1700 nm). Results showed as recognition of glass and ceramic glass is possible using selected wavelength ratios, in both visible and near infrared fields.     

A new approach for the modelling of chestnut wood photo-degradation monitored by different spectroscopic techniques

The aim of this work is to study the colour and chemical modifications of the surfaces in chestnut wood samples as a consequence of irradiating in a controlled environment. The changes were investigated by a new analytical approach by combining traditional techniques such as reflectance spectrophotometry in the visible range and Fourier transform infrared spectroscopy with new hyperspectral imaging, in order to obtain forecast models to describe the phenomenon. The statistical elaboration of the experimental data allowed to validate the measurements and to obtain models enabling to relate the investigated parameters; the elaboration of the hyperspectral images by chemometric methods allowed for studying the changes in the reflectance spectra. A result of great importance is the possibility to correlate the oxidation of wood chemical components with the colour change in a totally non-invasive modality. This result is particularly relevant in the field of cultural heritage and in general in the control processes of wooden materials.     

Spectral cullet classification in the mid-infrared field for ceramic glass contaminants detection.

The presence of glass-like contaminants inside waste glass products, usually resulting from both industrial and differentiated urban waste collection, has greatly increased in recent years, due to the introduction to the market of a large amount of goods manufactured from ceramic glass. The presence of contaminants in the glass recycling streams reduces product quality and increases production costs. The detection of ceramic glass detection is an unresolved problem, as such material looks like normal glass and can only be detected by trained personnel. In this study an innovative approach to ceramic glass recognition, based on the spectral signature in the mid-infrared (MIR) field, was proposed and investigated. The study specifically addressed the spectral characterization of glass and ceramic glass fragments collected in a real recycling plant from two different production lines: coloured container glass and white container glass. To define suitable inspection strategies to separate the useful (glass) from the polluting (ceramic glass) materials at the recycling plants, fragments presenting different colour, thickness, size, shape and manufacturing were selected. Both dirty and clean cullet was considered. The analyses, carried out in the MIR spectral field (2280-4480 nm), show that ceramic glass and glass fragments can be recognized according to their different spectral signature. In particular, by selecting a specific wavelength ratio the two classes of materials can be rapidly recognized, suggesting the possibility of developing an integrated hardware and software sorting system for 'on-line' ceramic glass separation.     

Classification and distribution of freshwater microplastics along the Italian Po river by hyperspectral imaging

Environmental Science and Pollution Research - In this work, freshwater microplastic samples collected from four different stations along the Italian Po river were characterized in terms of...     

Recycling-oriented characterization of polyolefin packaging waste

Packaging waste is one of the main sources of secondary polyolefins. It is essential to characterize polyolefins derived from this waste stream in such way, that not only mechanical sorting methods can effectively separate, but also that on-line sensor systems can quantitatively assess their distribution. The characterization methodology is hierarchical, relating all properties of waste particles in any phase of the processing ultimately to the input End-Of-Life products. The present paper documents a pre-concentrate obtained by hand picking of mixed Romanian household waste. Investigations have been addressed to identify the composition of this polyolefin waste stream, to study the polyolefin density distribution, to distinguish the polymer manufacturing methods (i.e. injection molding and blow molding) by flake physical properties and finally to perform all the required characterization and identification by hyperspectral imaging. On the basis of these analyses, polyolefins from packaging wastes can be recycled by density separation and their rheological properties and wall thickness indicate the molding procedures. Hyperspectral imaging based procedures have been also applied to set up quality control actions for recycled products.     

Monitoring of abandoned quarries by remote sensing and in situ surveying

In Italy quarrying causes relevant environmental damages and alterations to the land and the ecosystems. Despite the present Italian legislation requiring the restoration of the sites after exploitation, most of the quarries, both the abandoned and the still operational ones, are not restored.The objective of this work is to indicate a monitoring methodology in order to survey the present state of the quarry sites and their evolution in time, which are the basic data needed to implement an adequate land reclamation project.Such methodology has been applied to several abandoned limestone quarries in the Latina province (close to Rome), characterised by a typical Mediterranean vegetation, but it can be applied to any other kind of litology and vegetation.The land monitoring has been realised both by using remote sensing techniques, supported by a Geographic Information System of the studied area, and by in situ surveying. The in situ surveying was able to assess the capability of the remote sensing model to describe the state of each site.     

Non-parametric analysis of infrared spectra for recognition of glass and glass ceramic fragments in recycling plants

Glass ceramic detection in glass recycling plants represents a still unsolved problem, as glass ceramic material looks like normal glass and is usually detected only by specialized personnel. The presence of glass-like contaminants inside waste glass products, resulting from both industrial and differentiated urban waste collection, increases process production costs and reduces final product quality. In this paper an innovative approach for glass ceramic recognition, based on the non-parametric analysis of infrared spectra, is proposed and investigated. The work was specifically addressed to the spectral classification of glass and glass ceramic fragments collected in an actual recycling plant from three different production lines: flat glass, colored container-glass and white container-glass. The analyses, carried out in the near and mid-infrared (NIR-MIR) spectral field (1280-4480 nm), show that glass ceramic and glass fragments can be recognized by applying a wavelet transform, with a small classification error. Moreover, a method for selecting only a small subset of relevant wavelength ratios is suggested, allowing the conduct of a fast recognition of the two classes of materials. The results show how the proposed approach can be utilized to develop a classification engine to be integrated inside a hardware and software sorting architecture for fast "on-line" ceramic glass recognition and separation.     

Characterization of post-consumer polyolefin wastes by hyperspectral imaging for quality control in recycling processes

In this paper new analytical inspection strategies, based on hyperspectral imaging (HSI) in the VIS–NIR and NIR wavelength ranges (400–1000 and 1000–1700 nm, respectively), have been investigated and set up in order to define quality control logics that could be applied at industrial plant level for polyolefins recycling. The research was developed inside the European FP7 Project W2Plastics “Magnetic Sorting and Ultrasound Sensor Technologies for Production of High Purity Secondary Polyolefins from Waste”. The main aim of the project is the separation of pure polyethylene and polypropylene adopting an innovative process, the magnetic density separation (MDS). Spectra of plastic particles and contaminants resulting from post-consumer complex wastes and of virgin polyolefins have been acquired by HSI and by Raman spectroscopy. The classification results obtained applying principal component analysis (PCA) on HSI data have been compared with those obtained by Raman spectroscopy, in order to validate the proposed innovative methodology. Results showed that HSI sensing techniques allow to identify both polyolefins and contaminants. Results also demonstrated that HSI has a great potentiality as a tool for quality control of feed (identification of contaminants in the plastic waste) and of the two different pure polypropylene and polyethylene flow streams resulting from the MDS-based recycling process.