Analisi modellistica delle caratteristiche idrologiche del tratto di mare costiero antistante Capo Altano (Sardegna sud-occidentale) finalizzato ad investigare i potenziali impatti di un impianto di maricoltura (Tonnare Sulcitane)

Il lavoro si propone di investigare i potenziali impatti derivanti dall’attività di maricoltura prevista nel tratto di mare antistante Capo Altano, Sardegna sud-occidentale, attraverso un’analisi correntometrica. Lo studio è finalizzato ad una stima dell’areale maggiormente soggetto all’accumulo di sostanza organica prodotta dagli impianti di produzione. Al fine di riprodurre la circolazione delle acque e del moto ondoso nell’area di indagine e di effettuare delle simulazioni in grado di stabilire quale siano le aree interessate al deposito di sostanza organica prodotta dall’attività di maricoltura, sono state implementati diverse classi di modelli numerici ed effettuati alcuni esperimenti in laboratorio. In particolare, sono stati sviluppati un modello numerico idrodinamico, agli elementi finiti, in grado di riprodurre il campo di moto bidimensionale; un modello ondametrico, agli elementi finiti, al fine di riprodurre lo stato del mare; nonché un modello numerico in grado di simulare il trasporto di sostanze disperse nella colonna d’acqua ad opera dei venti, correnti e moto ondoso finalizzato ad individuare l’estensione delle aree potenzialmente impattabili dai detriti organici prodotti. Tali strumenti numerici sono stati applicati all’area di interesse in modalità accoppiata al fine di simulare ed analizzare le dinamiche di interesse sia nell’arco di un intero anno solare sia per definiti scenari meteomarini di riferimento. Lo studio ha permesso di simulare la dinamica di trasporto e deposizione dei fecal pellets prodotti e dei mangimi utilizzati nell’ambito dell’attività prevista di maricoltura. Infine è stato possibile valutare l’estensione massima raggiunta dalla sostanza organica rilasciata dagli impianti di acquicoltura prima della deposizione sul fondale, in relazione a determinati scenari meteo-marini, ed individuare l’areale soggetto ad un potenziale impatto sulle comunità bentoniche

Studio sull’impatto ambientale delle attività di maricoltura nel Golfo di Oristano

L’obiettivo del presente lavoro è stato di simulare la dispersione e il tempo di residenza delle sostanze organiche immesse nell’ambiente a seguito delle attività di acquacoltura all’interno del Golfo di Oristano (Sardegna, Italia). A questo scopo è stato implementato un modello numerico di circolazione, con moduli di dispersione e diffusione euleriana e lagrangiana. Il modello ha evidenziato il ruolo fondamentale della direzione e dell’intensità del vento sulla dispersione dei rifiuti organici. A parità d’intensità, la direzione del vento influenza in maniera decisiva la distanza alla quale i rifiuti organici vengono trasportati e depositati. In tutti gli scenari di vento, il mangime non consumato, indipendentemente dalla sua dimensione, si deposita in un’area direttamente sotto le gabbie ma con una distribuzione spaziale che dipende dalle correnti indotte. In tutti i casi, la materia organica disciolta si diluisce ed è trasportata al di fuori del golfo. Con i venti da Maestrale i rifiuti organici sono spinti verso, l’interno del golfo per poi uscirne in forma disciolta da sud. Negli scenari di Libeccio e Scirocco i rifiuti organici disciolti tendono a diluirsi ed essere trasportati al di fuori del golfo dalla parte nord. In tutti gli scenari, la capacità di ricambio delle acque interne al golfo risulta elevata, con la maggior parte delle sostanze organiche disciolte presenti in concentrazioni molto basse dopo dieci ore dalla loro produzione. Dal punto di vista del ricambio d’acqua e conseguentemente per la dispersone di agenti inquinanti, quasi tutti i 13 siti simulati, ad esclusione dei due in prossimità dei capi, hanno tempi di residenza idonei per il posizionamento delle gabbie. Sono comunque da preferire le regioni più a sud perché i tempi di transito sono più bassi creando un impatto minore. Infine considerando che il golfo è ricoperto quasi interamente da Posidonia, i siti meno impattanti sono quelli che si trovano su un fondale fangoso e in prossimità del fiume Tirso (Sito 3 e 4). L’utilizzo di modelli numerici ha permesso di portare a termine studi a priori (tempi di transito, zone di deposizione, dispersioni inquinanti) per la pianificazione della disposizione ottimale delle gabbie, avente come conseguenza una più proficua produzione (maggiore redditività) e un minore impatto ambientale. Si può infine affermare che nonostante l’assenza di studi antecedenti al presente, le gabbie all’interno del Golfo di Oristano siano state posizionate correttamente, in una regione ottimale per produzione e impatto ambientale

Dual-mode wake-up nodes for IoT monitoring applications: Measurements and algorithms

Internet of Things (IoTs)-based monitoring applications usually involve large-scale deployments of battery-enabled sensor nodes providing measurements at regular intervals. In order to guarantee the service continuity over time, the energy-efficiency of the networked system should be maximized. In this paper, we address such issue via a combination of novel hardware/software solutions including new classes of Wake-up radio IoT Nodes (WuNs) and novel data- and hardware-driven network management algorithms. Three main contributions are provided. First, we present the design and prototype implementation of WuN nodes able to support two different energy-saving modes; such modes can be configured via software, and hence dynamically tuned. Second, we show by experimental measurements that the optimal policy strictly depends on the application requirements. Third, we move from the node design to the network design, and we devise proper orchestration algorithms which select both the optimal set of WuN to wake-up and the proper energy-saving mode for each WuN, so that the application lifetime is maximized, while the redundancy of correlated measurements is minimized. The proposed solutions are extensively evaluated via OMNeT++ simulations under different IoT scenarios and requirements of the monitoring applications

Marine and Coastal Hazard Assessment for Three Coastal Oil Rigs

A forecasting and hazard assessment system for oil dispersion from Italian oil rigs was set up within the framework of a national research project. The system is based on 3D hydrodynamic, mesoscale resolving models providing forcing fields for a Lagrangian module of oil dispersion and slick evolution (oil transport and transformation). The tool provides,daily, the outputs of numerical simulations of possible oil spills from extraction platform sites. In this work we present the results for the 3 platforms closest to the Italian coast. Aside the operational usage, the numerical outputs are also stored and adopted to compute statistics of the slick distributions in the coastal and marine areas of interest. The hazard was assessed by means of two different indices (Hazard Index and Occurrence Index) based on the operational system outputs, for the estimation of the hazard at sea (marine hazard or aerial hazard). As short forecasts (2 days long) often do not allow the oil to reach the coast, an extra set of long-period simulations has been performed in order to compute a third Hazard Index (Coastal Hazard Index) suitable to estimate the hazard along the shorelines. The adopted methodology allowed, as a whole, to assess both coastal and marine oil spill hazard due to oil spill extraction activities. The indices constitute a basic informative layer on which the environmental risk could be also evaluated, once opportunely combined with coastal vulnerability and sensitivity layers

From Heterogeneous Sensor Networks to Integrated Software Services: Design and Implementation of a Semantic Architecture for the Internet of Things at ARCES@UNIBO

The Internet of Things (IoTs) is growing fast both in terms of number of devices connected and of complexity of deployments and applications. Several research studies an- alyzing the economical impact of the IoT worldwide identify the interoperability as one of the main boosting factor for its growth, thanks to the possibility to unlock novel commercial opportunities derived from the integration of heterogeneous systems which are currently not interconnected. However, at present, interoperability constitutes a relevant practical issue on any IoT deployments that is composed of sensor platforms mapped on different wireless technologies, network protocols or data formats. The paper addresses such issue, and investigates how to achieve effective data interoperability and data reuse on complex IoT deployments, where multiple users/applications need to consume sensor data produced by heterogeneous sensor networks. We propose a generic three-tier IoT architecture, which decouples the sensor data producers from the sensor data consumers, thanks to the intermediation of a semantic broker which is in charge of translating the sensor data into a shared ontology, and of providing publish-subscribe facilities to the producers/consumers. Then, we describe the real-world implementation of such architecture devised at the Advanced Research Center on Electronic System (ARCES) of the University of Bologna. The actual system collects the data produced by three different sensor networks, integrates them through a SPARQL Event Processing Architecture (SEPA), and supports two front- end applications for the data access, i.e. a web dashboard and an Amazon Alexa voice service

NEOTROPICAL XENARTHRANS: a data set of occurrence of xenarthran species in the Neotropics

Xenarthrans – anteaters, sloths, and armadillos – have essential functions for ecosystem maintenance, such as insect control and nutrient cycling, playing key roles as ecosystem engineers. Because of habitat loss and fragmentation, hunting pressure, and conflicts with 24 domestic dogs, these species have been threatened locally, regionally, or even across their full distribution ranges. The Neotropics harbor 21 species of armadillos, ten anteaters, and six sloths. Our dataset includes the families Chlamyphoridae (13), Dasypodidae (7), Myrmecophagidae (3), Bradypodidae (4), and Megalonychidae (2). We have no occurrence data on Dasypus pilosus (Dasypodidae). Regarding Cyclopedidae, until recently, only one species was recognized, but new genetic studies have revealed that the group is represented by seven species. In this data-paper, we compiled a total of 42,528 records of 31 species, represented by occurrence and quantitative data, totaling 24,847 unique georeferenced records. The geographic range is from the south of the USA, Mexico, and Caribbean countries at the northern portion of the Neotropics, to its austral distribution in Argentina, Paraguay, Chile, and Uruguay. Regarding anteaters, Myrmecophaga tridactyla has the most records (n=5,941), and Cyclopes sp. has the fewest (n=240). The armadillo species with the most data is Dasypus novemcinctus (n=11,588), and the least recorded for Calyptophractus retusus (n=33). With regards to sloth species, Bradypus variegatus has the most records (n=962), and Bradypus pygmaeus has the fewest (n=12). Our main objective with Neotropical Xenarthrans is to make occurrence and quantitative data available to facilitate more ecological research, particularly if we integrate the xenarthran data with other datasets of Neotropical Series which will become available very soon (i.e. Neotropical Carnivores, Neotropical Invasive Mammals, and Neotropical Hunters and Dogs). Therefore, studies on trophic cascades, hunting pressure, habitat loss, fragmentation effects, species invasion, and climate change effects will be possible with the Neotropical Xenarthrans dataset

ATLANTIC-CAMTRAPS: a dataset of medium and large terrestrial mammal communities in the Atlantic Forest of South America

Our understanding of mammal ecology has always been hindered by the difficulties of observing species in closed tropical forests. Camera trapping has become a major advance for monitoring terrestrial mammals in biodiversity rich ecosystems. Here we compiled one of the largest datasets of inventories of terrestrial mammal communities for the Neotropical region based on camera trapping studies. The dataset comprises 170 surveys of medium to large terrestrial mammals using camera traps conducted in 144 areas by 74 studies, covering six vegetation types of tropical and subtropical Atlantic Forest of South America (Brazil and Argentina), and present data on species composition and richness. The complete dataset comprises 53,438 independent records of 83 species of mammals, includes 10 species of marsupials, 15 rodents, 20 carnivores, eight ungulates and six armadillos. Species richness averaged 13 species (±6.07 SD) per site. Only six species occurred in more than 50% of the sites: the domestic dog Canis familiaris, crab-eating fox Cerdocyon thous, tayra Eira barbara, south American coati Nasua nasua, crab-eating raccoon Procyon cancrivorus and the nine-banded armadillo Dasypus novemcinctus. The information contained in this dataset can be used to understand macroecological patterns of biodiversity, community, and population structure, but also to evaluate the ecological consequences of fragmentation, defaunation, and trophic interactions. © 2017 by the Ecological Society of Americ