3 resultados para high-use area

em AMS Tesi di Laurea - Alm@DL - Università di Bologna


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The hydrogenation of biomass-derived molecules is a key reaction in upgrading these compounds into chemicals and fuels. The use of catalytic transfer hydrogenation, employing alcohols as hydrogen sources, offers an alternative approach to this process, avoiding the use of H2 under high pressure and precious metal catalysts. In this work, the gas-phase conversion of biomass-derived furfural into furfuryl alcohol and 2-methylfuran was studied, using methanol as the H-transfer agent and CaO-based catalysts. The results obtained with this catalyst were compared with those obtained by using MgO, which due to its basic properties and to its high surface area, at present appears to be among the best basic catalysts used for the conversion of biomass-derived molecules. Pure CaO, despite having a very low surface area, compared to MgO catalyst (5 m2/g vs. 172 m2/g), was shown to reduce furfural into its corresponding unsaturated alcohol at 350°C, thus allowing selective H-transfer from methanol to the substrate. These results highlight the potential application of the H-transfer reaction over CaO based catalysts as an efficient process for the selective reduction of biomass-derived molecules.

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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.

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The Great Barrier Reef hosts the only known reliable aggregation of dwarf minke whale (Balaenoptera acutorostrata subspecies) in Australian waters. While this short seasonal aggregation is quite predictable, the distribution and movements of the whales during the rest of their annual cycle are poorly understood. In particular, feeding and resting areas on their southward migration which are likely to be important have not been described. Using satellite telemetry data, I modelled the habitat use of seven whales during their southward migration through waters surrounding Tasmania. The whales were tagged with LIMPET satellite tags in the GBR in July 2013 (2 individuals) and 2014 (5 individuals). The study area around Tasmania was divided into 10km² cells and the time spent by each individual in each cell was calculated and averaged based on the number of animals using the cell. Two areas of high residency time were highlighted: south-western Bass Strait and Storm Bay (SE Tasmania). Remotely sensed ocean data were extracted for each cell and averaged temporally during the entire period of residency. Using Generalised Additive Models I explored the influence of key environmental characteristics. Nine predictors (bathymetry, distance from coast, distance from shore, gradient of sea surface temperature, sea surface height (absolute and variance), gradient of current speed, wind speed and chlorophyll-a concentration) were retained in the final model which explained 68% of the total variance. Regions of higher time-spent values were characterised by shallow waters, proximity to the coast (but not to the shelf break), high winds and sea surface height but low gradient of sea surface temperature. Given that the two high residency areas corresponded with regions where other marine predators also forage in Bass Strait and Storm Bay, I suggest the whales were probably feeding, rather than resting in these areas.