Spatial distribution of soil radon as a tool to recognize active faulting on an active volcano: the example of Mt. Etna (Italy)

This study concerns measurements of radon and thoron emissions from soil carried out in 2004 on the eastern flank of Mt. Etna, in a zone characterized by the presence of numerous seismogenic and aseismic faults. The statistical treatment of the geochemical data allowed recognizing anomaly thresholds for both parameters and producing distribution maps that highlighted a significant spatial correlation between soil gas anomalies and tectonic lineaments. The seismic activity occurring in and around the study area during 2004 was analyzed, producing maps of hypocentral depth and released seismic energy. Both radon and thoron anomalies were located in areas affected by relatively deep (5-10 km depth) seismic activity, while less evident correlation was found between soil gas anomalies and the released seismic energy. This study confirms that mapping the distribution of radon and thoron in soil gas can reveal hidden faults buried by recent soil cover or faults that are not clearly visible at the surface. The correlation between soil gas data and earthquakes depth and intensity can give some hints on the source of gas and/or on fault dynamics.     

Concentrations of PCDD/PCDF in soil close to a secondary aluminum smelter

Polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDDs/Fs) were analyzed in samples of the emissions from a secondary aluminum smelter (ALS) and soil samples around the plant. The purpose was to estimate the impact of the emissions on the surrounding environment.PCDD/F soil concentrations were higher in the proximity of the plant, exceeding the limit adopted in Italy in soils for green areas and residential uses and the upper limit of several reference concentrations. The most contaminated sites were less than 500 m from the plant and the dioxin concentration with the distance from the ALS.Principal component analysis (PCA) showed that emissions from the ALS were the source of PCDD/F contamination in the soils closest to the plant. Multivariate data analyses such as PCA are therefore useful to identify sources of emission causing contamination.     

New eco-friendly proposal for the crystallization of beet raw juice

In the past years we evaluated different strategies with the aim of eliminating completely from the beet sugar factory, the traditional calco-carbonic purification process taking into account the well-known problems related to the utilization of lime and the production of carbonation sludge.To complete the picture of the possible solutions to be adopted for the elimination of the traditional purification process, we tested and evaluated in laboratory and in pilot plants a new eco-friendly proposal.The results obtained, as well as the proposed flow-sheet and some economic evaluations, are presented and discussed.     

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.     

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.