Life cycle assessment (lca) of six separation methods of polyethylene and aluminum in tetra pak

In food and beverage industry, packaging plays a crucial role in protecting food and beverages and maintaining their organoleptic properties. Their disposal, unfortunately, is still difficult, mainly because there is a lack of economically viable systems for separating composite and multilayer materials. It is therefore necessary not only to increase research in this area, but also to set up pilot plants and implement these technologies on an industrial scale. LCA (Life Cycle Assessment) can fulfil these purposes. It allows an assessment of the potential environmental impacts associated with a product, service or process. The objective of this thesis work is to analyze the environmental performance of six separation methods, designed for separating the polymeric from the aluminum fraction in multilayered packaging. The first four methods utilize the chemical dissolution technique using Biodiesel, Cyclohexane, 2-Methyltetrahydrofuran (2-MeTHF) and Cyclopentyl-methyl-ether (CPME) as solvents. The last two applied the mechanical delamination technique with surfactant-activated water, using Ammonium laurate and Triethanolamine laurate as surfactants, respectively. For all six methods, the LCA methodology was applied and the corresponding models were built with the GaBi software version 10.6.2.9, specifically for LCA analyses. Unfortunately, due to a lack of data, it was not possible to obtain the results of the dissolution methods with the solvents 2-MeTHF and CPME; for the other methods, however, the individual environmental performances were calculated. Results revealed that the methods with the best environmental performance are method 2, for dissolution methods, and method 5, for delamination methods. This result is confirmed both by the analysis of normalized and weighted results and by the analysis of 'original' results. An hotspots analysis was also conducted.

The use of remote sensing imagery for monitoring recovery in the aftermath of a natural disaster: the Hurricane Katrina Case

Although Recovery is often defined as the less studied and documented phase of the Emergency Management Cycle, a wide literature is available for describing characteristics and sub-phases of this process. Previous works do not allow to gain an overall perspective because of a lack of systematic consistent monitoring of recovery utilizing advanced technologies such as remote sensing and GIS technologies. Taking into consideration the key role of Remote Sensing in Response and Damage Assessment, this thesis is aimed to verify the appropriateness of such advanced monitoring techniques to detect recovery advancements over time, with close attention to the main characteristics of the study event: Hurricane Katrina storm surge. Based on multi-source, multi-sensor and multi-temporal data, the post-Katrina recovery was analysed using both a qualitative and a quantitative approach. The first phase was dedicated to the investigation of the relation between urban types, damage and recovery state, referring to geographical and technological parameters. Damage and recovery scales were proposed to review critical observations on remarkable surge- induced effects on various typologies of structures, analyzed at a per-building level. This wide-ranging investigation allowed a new understanding of the distinctive features of the recovery process. A quantitative analysis was employed to develop methodological procedures suited to recognize and monitor distribution, timing and characteristics of recovery activities in the study area. Promising results, gained by applying supervised classification algorithms to detect localization and distribution of blue tarp, have proved that this methodology may help the analyst in the detection and monitoring of recovery activities in areas that have been affected by medium damage. The study found that Mahalanobis Distance was the classifier which provided the most accurate results, in localising blue roofs with 93.7% of blue roof classified correctly and a producer accuracy of 70%. It was seen to be the classifier least sensitive to spectral signature alteration. The application of the dissimilarity textural classification to satellite imagery has demonstrated the suitability of this technique for the detection of debris distribution and for the monitoring of demolition and reconstruction activities in the study area. Linking these geographically extensive techniques with expert per-building interpretation of advanced-technology ground surveys provides a multi-faceted view of the physical recovery process. Remote sensing and GIS technologies combined to advanced ground survey approach provides extremely valuable capability in Recovery activities monitoring and may constitute a technical basis to lead aid organization and local government in the Recovery management.