Assimilation of Meteosat Second Generation (MSG) satellite data in a regional numerical weather prediction model using a one-dimensional variational approach

The quality of temperature and humidity retrievals from the infrared SEVIRI sensors on the geostationary Meteosat Second Generation (MSG) satellites is assessed by means of a one dimensional variational algorithm. The study is performed with the aim of improving the spatial and temporal resolution of available observations to feed analysis systems designed for high resolution regional scale numerical weather prediction (NWP) models. The non-hydrostatic forecast model COSMO (COnsortium for Small scale MOdelling) in the ARPA-SIM operational configuration is used to provide background fields. Only clear sky observations over sea are processed. An optimised 1D–VAR set-up comprising of the two water vapour and the three window channels is selected. It maximises the reduction of errors in the model backgrounds while ensuring ease of operational implementation through accurate bias correction procedures and correct radiative transfer simulations. The 1D–VAR retrieval quality is firstly quantified in relative terms employing statistics to estimate the reduction in the background model errors. Additionally the absolute retrieval accuracy is assessed comparing the analysis with independent radiosonde and satellite observations. The inclusion of satellite data brings a substantial reduction in the warm and dry biases present in the forecast model. Moreover it is shown that the retrieval profiles generated by the 1D–VAR are well correlated with the radiosonde measurements. Subsequently the 1D–VAR technique is applied to two three–dimensional case–studies: a false alarm case–study occurred in Friuli–Venezia–Giulia on the 8th of July 2004 and a heavy precipitation case occurred in Emilia–Romagna region between 9th and 12th of April 2005. The impact of satellite data for these two events is evaluated in terms of increments in the integrated water vapour and saturation water vapour over the column, in the 2 meters temperature and specific humidity and in the surface temperature. To improve the 1D–VAR technique a method to calculate flow–dependent model error covariance matrices is also assessed. The approach employs members from an ensemble forecast system generated by perturbing physical parameterisation schemes inside the model. The improved set–up applied to the case of 8th of July 2004 shows a substantial neutral impact.

Seemingly unrelated linear regression for contaminated data based on Gaussian mixtures

In this thesis, new classes of models for multivariate linear regression defined by finite mixtures of seemingly unrelated contaminated normal regression models and seemingly unrelated contaminated normal cluster-weighted models are illustrated. The main difference between such families is that the covariates are treated as fixed in the former class of models and as random in the latter. Thus, in cluster-weighted models the assignment of the data points to the unknown groups of observations depends also by the covariates. These classes provide an extension to mixture-based regression analysis for modelling multivariate and correlated responses in the presence of mild outliers that allows to specify a different vector of regressors for the prediction of each response. Expectation-conditional maximisation algorithms for the calculation of the maximum likelihood estimate of the model parameters have been derived. As the number of free parameters incresases quadratically with the number of responses and the covariates, analyses based on the proposed models can become unfeasible in practical applications. These problems have been overcome by introducing constraints on the elements of the covariance matrices according to an approach based on the eigen-decomposition of the covariance matrices. The performances of the new models have been studied by simulations and using real datasets in comparison with other models. In order to gain additional flexibility, mixtures of seemingly unrelated contaminated normal regressions models have also been specified so as to allow mixing proportions to be expressed as functions of concomitant covariates. An illustration of the new models with concomitant variables and a study on housing tension in the municipalities of the Emilia-Romagna region based on different types of multivariate linear regression models have been performed.

The coupling between electron transfer and Protein/Solvent Dynamics in Photosynthetic Reaction Centers: Spectroscopic Studies in Amorphous Matrices

We investigated at the molecular level protein/solvent interactions and their relevance in protein function through the use of amorphous matrices at room temperature. As a model protein, we used the bacterial photosynthetic reaction center (RC) of Rhodobacter sphaeroides, a pigment protein complex which catalyzes the light-induced charge separation initiating the conversion of solar into chemical energy. The thermal fluctuations of the RC and its dielectric conformational relaxation following photoexcitation have been probed by analyzing the recombination kinetics of the primary charge-separated (P+QA-) state, using time resolved optical and EPR spectroscopies. We have shown that the RC dynamics coupled to this electron transfer process can be progressively inhibited at room temperature by decreasing the water content of RC films or of RC-trehalose glassy matrices. Extensive dehydration of the amorphous matrices inhibits RC relaxation and interconversion among conformational substates to an extent comparable to that attained at cryogenic temperatures in water-glycerol samples. An isopiestic method has been developed to finely tune the hydration level of the system. We have combined FTIR spectral analysis of the combination and association bands of residual water with differential light-minus-dark FTIR and high-field EPR spectroscopy to gain information on thermodynamics of water sorption, and on structure/dynamics of the residual water molecules, of protein residues and of RC cofactors. The following main conclusions were reached: (i) the RC dynamics is slaved to that of the hydration shell; (ii) in dehydrated trehalose glasses inhibition of protein dynamics is most likely mediated by residual water molecules simultaneously bound to protein residues and sugar molecules at the protein-matrix interface; (iii) the local environment of cofactors is not involved in the conformational dynamics which stabilizes the P+QA-; (iv) this conformational relaxation appears to be rather delocalized over several aminoacidic residues as well as water molecules weakly hydrogen-bonded to the RC.

Pyrolysis-Gas Chromatography-Mass Spectometry and Chemometric Analysis for the Characterization of Complex Matrices

The present PhD thesis was focused on the development and application of chemical methodology (Py-GC-MS) and data-processing method by multivariate data analysis (chemometrics). The chromatographic and mass spectrometric data obtained with this technique are particularly suitable to be interpreted by chemometric methods such as PCA (Principal Component Analysis) as regards data exploration and SIMCA (Soft Independent Models of Class Analogy) for the classification. As a first approach, some issues related to the field of cultural heritage were discussed with a particular attention to the differentiation of binders used in pictorial field. A marker of egg tempera the phosphoric acid esterified, a pyrolysis product of lecithin, was determined using HMDS (hexamethyldisilazane) rather than the TMAH (tetramethylammonium hydroxide) as a derivatizing reagent. The validity of analytical pyrolysis as tool to characterize and classify different types of bacteria was verified. The FAMEs chromatographic profiles represent an important tool for the bacterial identification. Because of the complexity of the chromatograms, it was possible to characterize the bacteria only according to their genus, while the differentiation at the species level has been achieved by means of chemometric analysis. To perform this study, normalized areas peaks relevant to fatty acids were taken into account. Chemometric methods were applied to experimental datasets. The obtained results demonstrate the effectiveness of analytical pyrolysis and chemometric analysis for the rapid characterization of bacterial species. Application to a samples of bacterial (Pseudomonas Mendocina), fungal (Pleorotus ostreatus) and mixed- biofilms was also performed. A comparison with the chromatographic profiles established the possibility to: • Differentiate the bacterial and fungal biofilms according to the (FAMEs) profile. • Characterize the fungal biofilm by means the typical pattern of pyrolytic fragments derived from saccharides present in the cell wall. • Individuate the markers of bacterial and fungal biofilm in the same mixed-biofilm sample.

Perfluoroalkylated substances in food matrices: development of mass spectrometry based analytical methods and preliminary monitoring

Perfluoroalkylated substances are a group of chemicals that have been largely employed during the last 60 years in several applications, widely spreading and accumulating in the environment due to their extreme resistance to degradation. As a consequence, they have been found also in various types of food as well as in drinking water, proving that they can easily reach humans through the diet. The available information concerning their adverse effects on health has recently increased the interest towards these contaminants and highlighted the importance of investigating all the potential sources of human exposure, among which diet was proved to be the most relevant. This need has been underlined by the European Union through Recommendation 2010/161/EU: in this document, Member States were called to monitor their presence of in food, producing accurate estimations of human exposure. The purpose of the research presented in this thesis, which is the result of a partnership between an Italian and a French laboratory, was to develop reliable tools for the analysis of these pollutants in food, to be used for generating data on potentially contaminated matrices. An efficient method based on liquid chromatography-mass spectrometry for the detection of 16 different perfluorinated compounds in milk has been validated in accordance with current European regulation guidelines (2002/657/EC) and is currently under evaluation for ISO 17025 accreditation. The proposed technique was applied to cow, powder and human breast milk samples from Italy and France to produce a preliminary monitoring on the presence of these contaminants. In accordance with the above mentioned European Recommendation, this project led also to the development of a promising technique for the quantification of some precursors of these substances in fish. This method showed extremely satisfying performances in terms of linearity and limits of detection, and will be useful for future surveys.

New analytical LC-mass spectrometry methodologies for the quali-quantitative determination of natural substances and drugs in complex matrices

This thesis reports an integrated analytical and physicochemical approach for the study of natural substances and new drugs based on mass spectrometry techniques combined with liquid chromatography. In particular, Chapter 1 concerns the study of Berberine a natural substance with pharmacological activity for the treatment of hepatobiliary and intestinal diseases. The first part focused on the relationships between physicochemical properties, pharmacokinetics and metabolism of Berberine and its metabolites. For this purpose a sensitive HPLC-ES-MS/MS method have been developed, validated and used to determine these compounds during their physicochemical properties studies and plasma levels of berberine and its metabolites including berberrubine(M1), demethylenberberine(M3), and jatrorrhizine(M4) in humans. Data show that M1, could have an efficient intestinal absorption by passive diffusion due to a keto-enol tautomerism confirmed by NMR studies and its higher plasma concentration. In the second part of Chapter 1, a comparison between M1 and BBR in vivo biodistribution in rat has been studied. In Chapter 2 a new HPLC-ES-MS/MS method for the simultaneous determination and quantification of glucosinolates, as glucoraphanin, glucoerucin and sinigrin, and isothiocyanates, as sulforaphane and erucin, has developed and validated. This method has been used for the analysis of functional foods enriched with vegetable extracts. Chapter 3 focused on a physicochemical study of the interaction between the bile acid sequestrants used in the treatment of hypercholesterolemia including colesevelam and cholestyramine with obeticolic acid (OCA), potent agonist of nuclear receptor farnesoid X (FXR). In particular, a new experimental model for the determination of equilibrium binding isotherm was developed. Chapter 4 focused on methodological aspects of new hard ionization coupled with liquid chromatography (Direct-EI-UHPLC-MS) not yet commercially available and potentially useful for qualitative analysis and for “transparent” molecules to soft ionization techniques. This method was applied to the analysis of several steroid derivatives.

Essays in Macroecometrics: methodological aspects and empirical applications

In the first chapter, I develop a panel no-cointegration test which extends Pesaran, Shin and Smith (2001)'s bounds test to the panel framework by considering the individual regressions in a Seemingly Unrelated Regression (SUR) system. This allows to take into account unobserved common factors that contemporaneously affect all the units of the panel and provides, at the same time, unit-specific test statistics. Moreover, the approach is particularly suited when the number of individuals of the panel is small relatively to the number of time series observations. I develop the algorithm to implement the test and I use Monte Carlo simulation to analyze the properties of the test. The small sample properties of the test are remarkable, compared to its single equation counterpart. I illustrate the use of the test through a test of Purchasing Power Parity in a panel of EU15 countries. In the second chapter of my PhD thesis, I verify the Expectation Hypothesis of the Term Structure in the repurchasing agreements (repo) market with a new testing approach. I consider an "inexact" formulation of the EHTS, which models a time-varying component in the risk premia and I treat the interest rates as a non-stationary cointegrated system. The effect of the heteroskedasticity is controlled by means of testing procedures (bootstrap and heteroskedasticity correction) which are robust to variance and covariance shifts over time. I fi#nd that the long-run implications of EHTS are verified. A rolling window analysis clarifies that the EHTS is only rejected in periods of turbulence of #financial markets. The third chapter introduces the Stata command "bootrank" which implements the bootstrap likelihood ratio rank test algorithm developed by Cavaliere et al. (2012). The command is illustrated through an empirical application on the term structure of interest rates in the US.

Original analytical methods for the determination of psychoactive compounds in complex matrices

This thesis work aims to develop original analytical methods for the determination of drugs with a potential for abuse, for the analysis of substances used in the pharmacological treatment of drug addiction in biological samples and for the monitoring of potentially toxic compounds added to street drugs. In fact reliable analytical techniques can play an important role in this setting. They can be employed to reveal drug intake, allowing the identification of drug users and to assess drug blood levels, assisting physicians in the management of the treatment. Pharmacological therapy needs to be carefully monitored indeed in order to optimize the dose scheduling according to the specific needs of the patient and to discourage improper use of the medication. In particular, different methods have been developed for the detection of gamma-hydroxybutiric acid (GHB), prescribed for the treatment of alcohol addiction, of glucocorticoids, one of the most abused pharmaceutical class to enhance sport performance and of adulterants, pharmacologically active compounds added to illicit drugs for recreational purposes. All the presented methods are based on capillary electrophoresis (CE) and high performance liquid chromatography (HPLC) coupled to various detectors (diode array detector, mass spectrometer). Biological samples pre-treatment was carried out using different extraction techniques, liquid-liquid extraction (LLE) and solid phase extraction (SPE). Different matrices have been considered: human plasma, dried blood spots, human urine, simulated street drugs. These developed analytical methods are individually described and discussed in this thesis work.