Urban air quality: new high-resolution modeling approaches and forecasting tools for citizens

Air pollution is one of the greatest health risks in the world. At the same time, the strong correlation with climate change, as well as with Urban Heat Island and Heat Waves, make more intense the effects of all these phenomena. A good air quality and high levels of thermal comfort are the big goals to be reached in urban areas in coming years. Air quality forecast help decision makers to improve air quality and public health strategies, mitigating the occurrence of acute air pollution episodes. Air quality forecasting approaches combine an ensemble of models to provide forecasts from global to regional air pollution and downscaling for selected countries and regions. The development of models dedicated to urban air quality issues requires a good set of data regarding the urban morphology and building material characteristics. Only few examples of air quality forecast system at urban scale exist in the literature and often they are limited to selected cities. This thesis develops by setting up a methodology for the development of a forecasting tool. The forecasting tool can be adapted to all cities and uses a new parametrization for vegetated areas. The parametrization method, based on aerodynamic parameters, produce the urban spatially varying roughness. At the core of the forecasting tool there is a dispersion model (urban scale) used in forecasting mode, and the meteorological and background concentration forecasts provided by two regional numerical weather forecasting models. The tool produces the 1-day spatial forecast of NO2, PM10, O3 concentration, the air temperature, the air humidity and BLQ-Air index values. The tool is automatized to run every day, the maps produced are displayed on the e-Globus platform, updated every day. The results obtained indicate that the forecasting output were in good agreement with the observed measurements.

High-resolution stratigraphy of Central and Southern Adriatic Quaternary deposits of sub-Milankovian climate change on Mediterranean circulation

This volume is a collection of the work done in a three years-lasting PhD, focused in the analysis of Central and Southern Adriatic marine sediments, deriving from the collection of a borehole and many cores, achieved thanks to the good seismic-stratigraphic knowledge of the study area. The work was made out within European projects EC-EURODELTA (coordinated by Fabio Trincardi, ISMAR-CNR), EC-EUROSTRATAFORM (coordinated by Phil P. E. Weaver, NOC, UK), and PROMESS1 (coordinated by Serge Bernè, IFREMER, France). The analysed sedimentary successions presented highly expanded stratigraphic intervals, particularly for the last 400 kyr, 60 kyr and 6 kyr BP. These three different time-intervals resulted in a tri-partition of the PhD thesis. The study consisted of the analysis of planktic and benthic foraminifers’ assemblages (more than 560 samples analysed), as well as in preparing the material for oxygen and carbon stable isotope analyses, and interpreting and discussing the obtained dataset. The chronologic framework of the last 400 kyr was achieved for borehole PRAD1-2 (within the work-package WP6 of PROMESS1 project), collected in 186.5 m water depth. The proposed chronology derives from a multi-disciplinary approach, consisting of the integration of numerous and independent proxies, some of which analysed by other specialists within the project. The final framework based on: micropaleontology (calcareous nannofossils and foraminifers’ bioevents), climatic cyclicity (foraminifers’ assemblages), geochemistry (oxygen stable isotope, made out on planktic and benthic records), paleomagnetism, radiometric ages (14C AMS), teprhochronology, identification of sapropel-equivalent levels (Se). It’s worth to note the good consistency between the oxygen stable isotope curve obtained for borehole PRAD1-2 and other deeper Mediterranean records. The studied proxies allowed the recognition of all the isotopic intervals from MIS10 to MIS1 in PRAD1-2 record, and the base of the borehole has been ascribed to the early MIS11. Glacial and interglacial intervals identified in the Central Adriatic record have been analysed in detail for the paleo-environmental reconstruction, as well. For instance, glacial stages MIS6, MIS8 and MIS10 present peculiar foraminifers’ assemblages, composed by benthic species typical of polar regions and no longer living in the Central Adriatic nowadays. Moreover, a deepening trend in the paleo-bathymetry during glacial intervals was observed, from MIS10 (inner-shelf environment) to MIS4 (mid-shelf environment).Ten sapropel-equivalent levels have been recognised in PRAD1-2 Central Adriatic record. They showed different planktic foraminifers’ assemblages, which allowed the first distinction of events occurred during warm-climate (Se5, Se7), cold-climate (Se4, Se6 and Se8) and temperate-intermediate-climate (Se1, Se3, Se9, Se’, Se10) conditions, consistently with literature. Cold-climate sapropel equivalents are characterised by the absence of an oligotrophic phase, whereas warm-temeprate-climate sapropel equivalents present both the oligotrophic and the eutrophic phases (except for Se1). Sea floor conditions vary, according to benthic foraminifers’ assemblages, from relatively well oxygenated (Se1, Se3), to dysoxic (Se9, Se’, Se10), to highly dysoxic (Se4, Se6, Se8) to events during which benthic foraminifers are absent (Se5, Se7). These two latter levels are also characterised by the lamination of the sediment, feature never observed in literature in such shallow records. The enhanced stratification of the water column during the events Se8, Se7, Se6, Se5, Se4, and the concurring strong dilution of shallow water, pointed out by the isotope record, lead to the hypothesis of a period of intense precipitation in the Central Adriatic region, possibly due to a northward shift of the African Monsoon. Finally, the expression of Central Adriatic PRAD1-2 Se5 equivalent was compared with the same event, as registered in other Eastern Mediterranean areas. The sequence of substantially the same planktic foraminifers’ bioevents has been consistently recognised, indicating a similar evolution of the water column all over the Eastern Mediterranean; yet, the synchronism of these events cannot be demonstrated. A high resolution analysis of late Holocene (last 6000 years BP) climate change was carried out for the Adriatic area, through the recognition of planktic and benthic foraminifers’ bioevents. In particular, peaks of planktic Globigerinoides sacculifer (four during the last 5500 years BP in the most expanded core) have been interpreted, based on the ecological requirements of this species, as warm-climate, arid intervals, correspondent to periods of relative climatic optimum, such as, for instance, the Medieval Warm Period, the Roman Age, the Late Bronze Age and the Copper Age. Consequently, the minima in the abundance of this biomarker could correspond to relatively cooler and more rainy periods. These conclusions are in good agreement with the isotopic and the pollen data. The Last Occurrence (LO) of G. sacculifer has been dated in this work at an average age of 550 years BP, and it is the best bioevent approximating the base of the Little Ice Age in the Adriatic. Recent literature reports the same bioevent in the Levantine Basin, showing a rather consistent age. Therefore, the LO of G. sacculifer has the potential to be extended to all the Eastern Mediterranean. Within the Little Ice Age, benthic foraminifer V. complanata shows two distinct peaks in the shallower Adriatic cores analysed, collected hundred kilometres apart, inside the mud belt environment. Based on the ecological requirements of this species, these two peaks have been interpreted as the more intense (cold and rainy) oscillations inside the LIA. The chronologic framework of the analysed cores is robust, being based on several range-finding 14C AMS ages, on estimates of the secular variation of the magnetic field, on geochemical estimates of the activity depth of 210Pb short-lived radionuclide (for the core-top ages), and is in good agreement with tephrochronologic, pollen and foraminiferal data. The intra-holocenic climate oscillations find out in the Adriatic have been compared with those pointed out in literature from other records of the Northern Hemisphere, and the chronologic constraint seems quite good. Finally, the sedimentary successions analysed allowed the review and the update of the foraminifers’ ecobiostratigraphy available from literature for the Adriatic region, thanks to the achievement of 16 ecobiozones for the last 60 kyr BP. Some bioevents are restricted to the Central Adriatic (for instance the LO of benthic Hyalinea balthica , approximating the MIS3/MIS2 boundary), others occur all over the Adriatic basin (for instance the LO of planktic Globorotalia inflata during MIS3, individuating Dansgaard-Oeschger cycle 8 (Denekamp)).

Characterization and modeling of the barrier properties in nanostructured systems

The object of the present study is the process of gas transport in nano-sized materials, i.e. systems having structural elements of the order of nanometers. The aim of this work is to advance the understanding of the gas transport mechanism in such materials, for which traditional models are not often suitable, by providing a correct interpretation of the relationship between diffusive phenomena and structural features. This result would allow the development new materials with permeation properties tailored on the specific application, especially in packaging systems. The methods used to achieve this goal were a detailed experimental characterization and different simulation methods. The experimental campaign regarded the determination of oxygen permeability and diffusivity in different sets of organic-inorganic hybrid coatings prepared via sol-gel technique. The polymeric samples coated with these hybrid layers experienced a remarkable enhancement of the barrier properties, which was explained by the strong interconnection at the nano-scale between the organic moiety and silica domains. An analogous characterization was performed on microfibrillated cellulose films, which presented remarkable barrier effect toward oxygen when it is dry, while in the presence of water the performance significantly drops. The very low value of water diffusivity at low activities is also an interesting characteristic which deals with its structural properties. Two different approaches of simulation were then considered: the diffusion of oxygen through polymer-layered silicates was modeled on a continuum scale with a CFD software, while the properties of n-alkanthiolate self assembled monolayers on gold were analyzed from a molecular point of view by means of a molecular dynamics algorithm. Modeling transport properties in layered nanocomposites, resulting from the ordered dispersion of impermeable flakes in a 2-D matrix, allowed the calculation of the enhancement of barrier effect in relation with platelets structural parameters leading to derive a new expression. On this basis, randomly distributed systems were simulated and the results were analyzed to evaluate the different contributions to the overall effect. The study of more realistic three-dimensional geometries revealed a prefect correspondence with the 2-D approximation. A completely different approach was applied to simulate the effect of temperature on the oxygen transport through self assembled monolayers; the structural information obtained from equilibrium MD simulations showed that raising the temperature, makes the monolayer less ordered and consequently less crystalline. This disorder produces a decrease in the barrier free energy and it lowers the overall resistance to oxygen diffusion, making the monolayer more permeable to small molecules.

3D probability tomography: theoretical developments and applications to high-resolution geophysical prospecting

The theory of the 3D multipole probability tomography method (3D GPT) to image source poles, dipoles, quadrupoles and octopoles, of a geophysical vector or scalar field dataset is developed. A geophysical dataset is assumed to be the response of an aggregation of poles, dipoles, quadrupoles and octopoles. These physical sources are used to reconstruct without a priori assumptions the most probable position and shape of the true geophysical buried sources, by determining the location of their centres and critical points of their boundaries, as corners, wedges and vertices. This theory, then, is adapted to the geoelectrical, gravity and self potential methods. A few synthetic examples using simple geometries and three field examples are discussed in order to demonstrate the notably enhanced resolution power of the new approach. At first, the application to a field example related to a dipole–dipole geoelectrical survey carried out in the archaeological park of Pompei is presented. The survey was finalised to recognize remains of the ancient Roman urban network including roads, squares and buildings, which were buried under the thick pyroclastic cover fallen during the 79 AD Vesuvius eruption. The revealed anomaly structures are ascribed to wellpreserved remnants of some aligned walls of Roman edifices, buried and partially destroyed by the 79 AD Vesuvius pyroclastic fall. Then, a field example related to a gravity survey carried out in the volcanic area of Mount Etna (Sicily, Italy) is presented, aimed at imaging as accurately as possible the differential mass density structure within the first few km of depth inside the volcanic apparatus. An assemblage of vertical prismatic blocks appears to be the most probable gravity model of the Etna apparatus within the first 5 km of depth below sea level. Finally, an experimental SP dataset collected in the Mt. Somma-Vesuvius volcanic district (Naples, Italy) is elaborated in order to define location and shape of the sources of two SP anomalies of opposite sign detected in the northwestern sector of the surveyed area. The modelled sources are interpreted as the polarization state induced by an intense hydrothermal convective flow mechanism within the volcanic apparatus, from the free surface down to about 3 km of depth b.s.l..

Parallel modeling of the electric field distribution in the brain

The term "Brain Imaging" identi�es a set of techniques to analyze the structure and/or functional behavior of the brain in normal and/or pathological situations. These techniques are largely used in the study of brain activity. In addition to clinical usage, analysis of brain activity is gaining popularity in others recent �fields, i.e. Brain Computer Interfaces (BCI) and the study of cognitive processes. In this context, usage of classical solutions (e.g. f MRI, PET-CT) could be unfeasible, due to their low temporal resolution, high cost and limited portability. For these reasons alternative low cost techniques are object of research, typically based on simple recording hardware and on intensive data elaboration process. Typical examples are ElectroEncephaloGraphy (EEG) and Electrical Impedance Tomography (EIT), where electric potential at the patient's scalp is recorded by high impedance electrodes. In EEG potentials are directly generated from neuronal activity, while in EIT by the injection of small currents at the scalp. To retrieve meaningful insights on brain activity from measurements, EIT and EEG relies on detailed knowledge of the underlying electrical properties of the body. This is obtained from numerical models of the electric �field distribution therein. The inhomogeneous and anisotropic electric properties of human tissues make accurate modeling and simulation very challenging, leading to a tradeo�ff between physical accuracy and technical feasibility, which currently severely limits the capabilities of these techniques. Moreover elaboration of data recorded requires usage of regularization techniques computationally intensive, which influences the application with heavy temporal constraints (such as BCI). This work focuses on the parallel implementation of a work-flow for EEG and EIT data processing. The resulting software is accelerated using multi-core GPUs, in order to provide solution in reasonable times and address requirements of real-time BCI systems, without over-simplifying the complexity and accuracy of the head models.

CFD modeling of two-phase boiling flows in the slug flow regime with an interface capturing technique

The objective of this thesis was to improve the commercial CFD software Ansys Fluent to obtain a tool able to perform accurate simulations of flow boiling in the slug flow regime. The achievement of a reliable numerical framework allows a better understanding of the bubble and flow dynamics induced by the evaporation and makes possible the prediction of the wall heat transfer trends. In order to save computational time, the flow is modeled with an axisymmetrical formulation. Vapor and liquid phases are treated as incompressible and in laminar flow. By means of a single fluid approach, the flow equations are written as for a single phase flow, but discontinuities at the interface and interfacial effects need to be accounted for and discretized properly. Ansys Fluent provides a Volume Of Fluid technique to advect the interface and to map the discontinuous fluid properties throughout the flow domain. The interfacial effects are dominant in the boiling slug flow and the accuracy of their estimation is fundamental for the reliability of the solver. Self-implemented functions, developed ad-hoc, are introduced within the numerical code to compute the surface tension force and the rates of mass and energy exchange at the interface related to the evaporation. Several validation benchmarks assess the better performances of the improved software. Various adiabatic configurations are simulated in order to test the capability of the numerical framework in modeling actual flows and the comparison with experimental results is very positive. The simulation of a single evaporating bubble underlines the dominant effect on the global heat transfer rate of the local transient heat convection in the liquid after the bubble transit. The simulation of multiple evaporating bubbles flowing in sequence shows that their mutual influence can strongly enhance the heat transfer coefficient, up to twice the single phase flow value.

In defence of modeling simultaneity for a correct approximation of cultural aspects: implications for food consumers studies with latent variables

Dealing with latent constructs (loaded by reflective and congeneric measures) cross-culturally compared means studying how these unobserved variables vary, and/or covary each other, after controlling for possibly disturbing cultural forces. This yields to the so-called ‘measurement invariance’ matter that refers to the extent to which data collected by the same multi-item measurement instrument (i.e., self-reported questionnaire of items underlying common latent constructs) are comparable across different cultural environments. As a matter of fact, it would be unthinkable exploring latent variables heterogeneity (e.g., latent means; latent levels of deviations from the means (i.e., latent variances), latent levels of shared variation from the respective means (i.e., latent covariances), levels of magnitude of structural path coefficients with regard to causal relations among latent variables) across different populations without controlling for cultural bias in the underlying measures. Furthermore, it would be unrealistic to assess this latter correction without using a framework that is able to take into account all these potential cultural biases across populations simultaneously. Since the real world ‘acts’ in a simultaneous way as well. As a consequence, I, as researcher, may want to control for cultural forces hypothesizing they are all acting at the same time throughout groups of comparison and therefore examining if they are inflating or suppressing my new estimations with hierarchical nested constraints on the original estimated parameters. Multi Sample Structural Equation Modeling-based Confirmatory Factor Analysis (MS-SEM-based CFA) still represents a dominant and flexible statistical framework to work out this potential cultural bias in a simultaneous way. With this dissertation I wanted to make an attempt to introduce new viewpoints on measurement invariance handled under covariance-based SEM framework by means of a consumer behavior modeling application on functional food choices.

Analysis and mathematical modeling of wave-structure interaction

The aim of this thesis, included within the THESEUS project, is the development of a mathematical model 2DV two-phase, based on the existing code IH-2VOF developed by the University of Cantabria, able to represent together the overtopping phenomenon and the sediment transport. Several numerical simulations were carried out in order to analyze the flow characteristics on a dike crest. The results show that the seaward/landward slope does not affect the evolution of the flow depth and velocity over the dike crest whereas the most important parameter is the relative submergence. Wave heights decrease and flow velocities increase while waves travel over the crest. In particular, by increasing the submergence, the wave height decay and the increase of the velocity are less marked. Besides, an appropriate curve able to fit the variation of the wave height/velocity over the dike crest were found. Both for the wave height and for the wave velocity different fitting coefficients were determined on the basis of the submergence and of the significant wave height. An equation describing the trend of the dimensionless coefficient c_h for the wave height was derived. These conclusions could be taken into consideration for the design criteria and the upgrade of the structures. In the second part of the thesis, new equations for the representation of the sediment transport in the IH-2VOF model were introduced in order to represent beach erosion while waves run-up and overtop the sea banks during storms. The new model allows to calculate sediment fluxes in the water column together with the sediment concentration. Moreover it is possible to model the bed profile evolution. Different tests were performed under low-intensity regular waves with an homogeneous layer of sand on the bottom of a channel in order to analyze the erosion-deposition patterns and verify the model results.

Kinematics of local and high-z galaxies through 3D modeling of emission-line datacubes

The kinematics is a fundamental tool to infer the dynamical structure of galaxies and to understand their formation and evolution. Spectroscopic observations of gas emission lines are often used to derive rotation curves and velocity dispersions. It is however difficult to disentangle these two quantities in low spatial-resolution data because of beam smearing. In this thesis, we present 3D-Barolo, a new software to derive the gas kinematics of disk galaxies from emission-line data-cubes. The code builds tilted-ring models in the 3D observational space and compares them with the actual data-cubes. 3D-Barolo works with data at a wide range of spatial resolutions without being affected by instrumental biases. We use 3D-Barolo to derive rotation curves and velocity dispersions of several galaxies in both the local and the high-redshift Universe. We run our code on HI observations of nearby galaxies and we compare our results with 2D traditional approaches. We show that a 3D approach to the derivation of the gas kinematics has to be preferred to a 2D approach whenever a galaxy is resolved with less than about 20 elements across the disk. We moreover analyze a sample of galaxies at z~1, observed in the H-alpha line with the KMOS/VLT spectrograph. Our 3D modeling reveals that the kinematics of these high-z systems is comparable to that of local disk galaxies, with steeply-rising rotation curves followed by a flat part and H-alpha velocity dispersions of 15-40 km/s over the whole disks. This evidence suggests that disk galaxies were already fully settled about 7-8 billion years ago. In summary, 3D-Barolo is a powerful and robust tool to separate physical and instrumental effects and to derive a reliable kinematics. The analysis of large samples of galaxies at different redshifts with 3D-Barolo will provide new insights on how galaxies assemble and evolve throughout cosmic time.

Trees: radiocarbon and dendrochronology - together for the Resolution project

The year 14,226 BP marks an important border in the actual radiocarbon (14C) calibration curve: the high resolution and precision characterising the first part (0 – 14,226 BP) of the curve are due to the potential represented by tree-ring datasets, which directly provide the atmospheric 14C content at the time of tree-rings formation with high resolution. They systematically decrease going back in time, where only a few floating tree-ring chronologies alternate to other low-resolution records. The lack of resolution in the dating procedure before 14,226 years BP leads to significant issues in the interpretation and untangling of tricky facts of our past, in the field of Human Evolution. Research on sub-fossil trees and the construction of new Glacial tree-ring chronologies can significantly improve the radiocarbon dating in terms of temporal resolution and precision until 55,000 years BP to clear puzzles in the Human Evolution history. In this thesis, the dendrochronological study, the radiocarbon dating and the extrapolation of environmental and climate information from sub-fossil trees found on the Portugal foreshore, remnants of a Glacial lagoonal forest, are presented. The careful sampling, the dendrochronological measurements and cross-dating, the application of the most suitable cellulose extraction protocol and the most advanced technologies of the MICADAS system at ETH-Zurich, led to the construction of a new 220-years long tree-ring site chronology and to high resolution, highly reliable and with a tight error range radiocarbon ages. At the moment, it results impossible to absolutely date this radiocarbon sequence by the comparison of Δ14C of the trees and 10 Be fluctuations from the ice-cores. For this reason, tree growth analysis, comparisons with a living pine stand and forest-fires history reconstruction have made it possible to hypothesize site and climate characteristics useful to constrain the positioning in time of the obtained radiocarbon sequence.

Data assimilation for advanced cross-scale unstructured-grid ocean modeling.

The coastal ocean is a complex environment with extremely dynamic processes that require a high-resolution and cross-scale modeling approach in which all hydrodynamic fields and scales are considered integral parts of the overall system. In the last decade, unstructured-grid models have been used to advance in seamless modeling between scales. On the other hand, the data assimilation methodologies to improve the unstructured-grid models in the coastal seas have been developed only recently and need significant advancements. Here, we link the unstructured-grid ocean modeling to the variational data assimilation methods. In particular, we show results from the modeling system SANIFS based on SHYFEM fully-baroclinic unstructured-grid model interfaced with OceanVar, a state-of-art variational data assimilation scheme adopted for several systems based on a structured grid. OceanVar implements a 3DVar DA scheme. The combination of three linear operators models the background error covariance matrix. The vertical part is represented using multivariate EOFs for temperature, salinity, and sea level anomaly. The horizontal part is assumed to be Gaussian isotropic and is modeled using a first-order recursive filter algorithm designed for structured and regular grids. Here we introduced a novel recursive filter algorithm for unstructured grids. A local hydrostatic adjustment scheme models the rapidly evolving part of the background error covariance. We designed two data assimilation experiments using SANIFS implementation interfaced with OceanVar over the period 2017-2018, one with only temperature and salinity assimilation by Argo profiles and the second also including sea level anomaly. The results showed a successful implementation of the approach and the added value of the assimilation for the active tracer fields. While looking at the broad basin, no significant improvements are highlighted for the sea level, requiring future investigations. Furthermore, a Machine Learning methodology based on an LSTM network has been used to predict the model SST increments.

Data-driven multivariate flood hazard modeling

The present Dissertation shows how recent statistical analysis tools and open datasets can be exploited to improve modelling accuracy in two distinct yet interconnected domains of flood hazard (FH) assessment. In the first Part, unsupervised artificial neural networks are employed as regional models for sub-daily rainfall extremes. The models aim to learn a robust relation to estimate locally the parameters of Gumbel distributions of extreme rainfall depths for any sub-daily duration (1-24h). The predictions depend on twenty morphoclimatic descriptors. A large study area in north-central Italy is adopted, where 2238 annual maximum series are available. Validation is performed over an independent set of 100 gauges. Our results show that multivariate ANNs may remarkably improve the estimation of percentiles relative to the benchmark approach from the literature, where Gumbel parameters depend on mean annual precipitation. Finally, we show that the very nature of the proposed ANN models makes them suitable for interpolating predicted sub-daily rainfall quantiles across space and time-aggregation intervals. In the second Part, decision trees are used to combine a selected blend of input geomorphic descriptors for predicting FH. Relative to existing DEM-based approaches, this method is innovative, as it relies on the combination of three characteristics: (1) simple multivariate models, (2) a set of exclusively DEM-based descriptors as input, and (3) an existing FH map as reference information. First, the methods are applied to northern Italy, represented with the MERIT DEM (∼90m resolution), and second, to the whole of Italy, represented with the EU-DEM (25m resolution). The results show that multivariate approaches may (a) significantly enhance flood-prone areas delineation relative to a selected univariate one, (b) provide accurate predictions of expected inundation depths, (c) produce encouraging results in extrapolation, (d) complete the information of imperfect reference maps, and (e) conveniently convert binary maps into continuous representation of FH.