This thesis aims at evaluating, in two separate studies, strategies for physiological noise and head motion correction in resting state brain FC-fMRI. In particular, as a general marker of noise correction performance we use the test-retest reproducibility of the DMN. The guiding hypothesis is that methods that improve reproducibility should reflect more efficient corrections and thus be preferable in longitudinal studies. The physiological denoising study evaluated longitudinal changes in a 3T harmonized multisite fMRI study of healthy elderly participants from the PharmaCog Consortium (Jovicich et al., 2016). Retrospective physiological noise correction (rPNC) methods were here implemented to investigate their influence on several DMN reliability measures within and between 13 MRI sites. Each site involved five different healthy elderly participants who were scanned twice at least a week apart (5 participants per site). fMRI data analysis was performed once without rPNC and then with WM/CSF regression, with physiological estimation by temporal ICA (PESTICA) (Beall & Lowe, 2007) and FMRIB's ICA-based Xnoiseifier (FSL-FIX) (Griffanti et al., 2014; Salimi-Khorshidi et al., 2014). These methods differ for their data-based computational approach to identify physiological noise fluctuations and need to be applied at different stages of data preprocessing. As a working hypothesis, physiological denoising was in general expected to improve DMN reliability. The head motion study evaluated longitudinal changes in the DMN connectivity from a 4T single-site study of 24 healthy young volunteers who were scanned twice within a week. Within each scanning session, RS-fMRI scans were acquired once using interleaved and then sequential slice-order acquisition methods. Furthermore, brain volumes were corrected for motion using once rigid-body volumetric and then slice-wise methods. The effects of these choices were then evaluated computing multiple DMN reliability measures and investigating single regions within the DMN to assess the existence of inter-regional effects associated with head-motion. In this case, we expected to find slice-order acquisition effects in reliability estimates under standard volumetric motion correction and no slice-order acquisition effect under 2D slice-based motion correction. Both studies used ICA to characterize the DMN using group-ICA and dual regression procedures (Beckmann et al., 2009). This methodology proved successful at defining consistent DMN connectivity metrics in longitudinal and clinical RS-fMRI studies (Zuo & Xing, 2014). Automatic DMN selection procedures and other quality assurance analyses were made to supervise ICA performance. Both studies considered several test-retest (TRT) reliability estimates (Vilagut, 2014) for some DMN connectivity measurements: absolute percent error between the sessions, intraclass correlation coefficients (ICC) between sessions and multiple sites, the Jaccard index to evaluate the degree of voxel-wise spatial pattern actiavtion overlap between sessions.

Grasslands are one of the most important ecosystems on Earth, covering approximately one-third of the Earth’s surface. Grassland biodiversity is important as many services provided by such ecosystems are crucial for the human economy and well-being. Given the importance of grasslands ecosystems, in recent years research has been carried out on the potential to monitor them with novel remote sensing techniques. Improved detectors technology and novel sensors providing fine-scale hyperspectral imagery have been enabling new methods to monitor plant traits (PTs) and biodiversity. The aims of the work were to study different approaches to monitor key grassland PTs such as Leaf Area Index (LAI) and biodiversity-related traits. The thesis consists of 3 parts: 1) Evaluating the performance of remote sensing methods to estimate LAI in grassland ecosystems, 2) Estimating plant biodiversity by using the optical diversity approach in grassland ecosystems, and 3) Investigating the relationship between PTs variability with alpha and beta diversity for the applicability of the optical diversity approach in a subalpine grassland of the Italian Alps To evaluate the performance of remote sensing methods to estimate LAI, temporal and spatial observations of hyperspectral reflectance and LAI were analyzed at a grassland site in Monte Bondone, Italy (IT-MBo). In 2018, ground temporal observations of hyperspectral reflectance and LAI were carried out at a grassland site in Neustift, Austria (AT-NEU). To estimate biodiversity, in 2018 and 2019 a floristics survey was conducted to determine species composition and hyperspectral data were acquired at two grassland sites: IT-MBo and University of Padova’s Experimental Farm, Legnaro, Padua, Italy (IT-PD) respectively. Furthermore, in 2018, biochemistry analysis of the biomass samples collected from the grassland site IT-MBo was carried out to determine the foliar biochemical PTs variability. The results of the thesis demonstrated that the grassland spectral response across different spectral regions (Visible: VIS, red-edge: RE, Near-infrared: NIR) showed to be both site-specific and scale-dependent. In the first part of the thesis, the performance of spectral vegetation indices (SVIs) based on visible, red-edge (RE), and NIR bands alongside SVIs solely based or NIR-shoulder bands (wavelengths 750 - 900 nm) was evaluated. A strong correlation (R2 > 0.8) was observed between grassland LAI and both RE and NIR-shoulder SVIs on a temporal basis, but not on a spatial basis. Using the PROSAIL Radiative Transfer Model (RTM), it was demonstrated that grassland structural heterogeneity strongly affects the ability to retrieve LAI, with high uncertainties due to structural and biochemical PTs co-variation. In the second part, the applicability of the spectral variability hypothesis (SVH) was questioned and highlighted the challenges to use high-resolution hyperspectral images to estimate biodiversity in complex grassland ecosystems. It was reported that the relationship between biodiversity (Shannon, Richness, Simpson, and Evenness) and optical diversity metrics (Coefficient of variation (CV) and Standard deviation (SD)) is not consistent across plant communities. The results of the second part suggested that biodiversity in terms of species richness could be estimated by optical diversity metrics with an R2 = 0.4 at the IT-PD site where the grassland plots were artificially established and are showing a lower structure and complexity from the natural grassland plant communities. On the other hand, in the natural ecosystems at IT-MBo, it was more difficult to estimate biodiversity indices, probably due to structural and biochemical PTs co-variation. The effects of canopy non-vegetative elements (flowers and dead material), shadow pixels, and overexposed pixels on the relationship between optical diversity metrics and biodiversity indices were highlighted. In the third part, we examined the relationship between PTs variability (at both local and community scales, measured by standard deviation and by the Euclidean distances of the biochemical and biophysical PTs respectively) and taxonomic diversity (both α-diversity and β-diversity, measured by Shannon’s index and by Jaccard dissimilarity index of the species, families, and functional groups percent cover respectively) in Monte Bondone, Trentino province, Italy. The results of the study showed that the PTs variability metrics at alpha scale were not correlated with α-diversity. However, the results at the community scale (β-diversity) showed that some of the investigated biochemical and biophysical PTs variations metrics were associated with β-diversity. The SVH approach was also tested to estimate β-diversity and we found that spectral diversity calculated by spectral angular mapper (SAM) showed to be a better proxy of biodiversity in the same ecosystem where the spectral diversity failed to estimate alpha diversity, this leading to the conclusion that the link between functional and species diversity may be an indicator of the applicability of optical sampling methods to estimate biodiversity. The findings of the thesis highlighted that grassland structural heterogeneity strongly affects the ability to retrieve both LAI and biodiversity, with high uncertainties due to structural and biochemical PTs co-variation at complex grassland ecosystems. In this context, the uncertainties of satellite-based products (e.g., LAI) in monitoring grassland canopies characterized by either spatially or temporally varying structure need to be carefully taken into account. The results of the study highlighted that the poor performance of optical diversity proxies in estimating biodiversity in structurally heterogeneous grasslands might be due to the complex relationships between functional diversity and biodiversity, rather than the impossibility to detect functional diversity with spectral proxies.

The present work regards the development of a methodology for the study of atmospheric particulate matter (PM) which is alternative to instrumental measurements. The methodology developed exploits the surfaces already present in the field as samplers of PM. In particular, conifer needles and building facades are employed to investigate different temporal ranges: conifer needles potentially retain particles circulating in the atmosphere from the recent past up to now, while building facades could retain particles from an older period up to know. The field of application of the approach developed are the situations in which a wide territory must be monitored, eventually including remote locations, or information on past pollution scenario must be reconstructed in the absence of monitoring stations. For instance, the evaluation of the improved efficiency of off-gas abatement systems of industrial plants is a typical case of application. These pollution sources affect large areas and might have been active before regulation on air quality required constant monitoring of their emissions. Typically in such a case the methodology could assist in evaluating how large was in the past and it is nowadays the area of impact of the plant. In general, such an approach could be valuable whenever relying on instrumental measurements is cost and time consuming in terms of installing a large network of monitoring stations to study the dispersion of pollutants from a single or few sources. To have a detailed description of the spatial distribution of pollutant particles, they are studied individually with subsequent higher magnification. Where no traces of a source are detected by scanning electron microscopy coupled with energy dispersive x-ray spectroscopy (SEM-EDXS), the samples are analyzed with the higher resolution of transmission electron microscopy coupled with energy dispersive x-ray spectroscopy (TEM-EDXS) and selected area electron diffraction (SAED) in order to make sure that no smaller particles, able to travel farther from their source, are present at a certain site. All data provided by electron microscopy analysis of particles collected by conifer needles are placed in the context of elemental concentrations measured by inductively coupled plasma atomic emission spectroscopy (ICP-AES), which is a bulk analytical technique. The same is not possible for the data on single particles present on building facades given the inorganic matrix of the substrate, especially in the case of metal oxide paints, which does not allow the bulk measurement. Both the preparation of the samples for bulk analytical techniques and single particle analysis by electron microscopy were optimized. For method development and evaluation, the analytical protocol was applied to estimate spatial and temporal trends of accumulation of inorganic pollutants that can be related with changes in the emissions of atmospheric pollutants by an electric arc furnace (EAF) steelmaking plant located in a test site. The benefits of combining the single particle and bulk analytical techniques emerged especially for the discrimination of the emissions from different sources.

Hydrothermal carbonization (in acronym, HTC) is a thermochemical conversion process through which it is possible to directly transform wet organic substrates into a carbonaceous material, referred as hydrochar. Hydrochar has chemical and physical characteristics that make it similar to fossil peats and lignite. Depending on the process conditions, mostly temperature and residence time, this material can be enriched in its carbon content, modifying its structure and providing it interesting characteristics that make it possible to be used for several applications, such as for energy production, as a soil conditioner and improver, for carbon dioxide sorption and sequestration, and some others reported in literature. HTC is a different process, if compared to other common thermochemical processes, such as pyrolysis, torrefaction, gasification, etc., because it works in wet conditions (humidity content higher than 60%). As a matter of fact, biomass is transformed into hydrochar because of the properties of hot pressurized water, that acts both as a reactant and as a catalyst. The HTC process has been studied from many years, although at present not all the chemical reactions that occur during the process are completely known. Moreover, the application of this quite new process to different substrates can bring to different results. Even though HTC can be applied to any kind of organic material (of both animal and vegetable derivation), the possible uses of hydrochar can strongly be influenced by the characteristics of the feedstock. This, for example, can be due to legislative constraints. In Chapter 1, an overview of the existing literature is presented. To get insights on this process, a small bench scale batch reactor has been designed and built at the Department of Civil, Environmental and Mechanical engineering of the University of Trento, Italy. This reactor has been tested, prior to be used with real substrates. In Chapter 2 the reactor and the preliminary tests done are described. In this work, the HTC process applied to three different substrates have been studied: grape marc, the EWC 19.05.03 residue and the EWC 19.12.12 residue. In Chapter 3 the three raw substrates are described. Grape marc is produced by the winery industries or by distilleries. This feedstock is composed by woody seeds and holocellulosic skins and it presents an average humidity content of about 60%. At present, it is used for the production of animal food or it is landfilled. In this case, the application of HTC can be an interesting alternative to these end uses because, through this process, grape marc can be recovered, for example, for energy production. The hydrochar produced from this feedstock could be even used as a soil conditioner. In Chapter 4 several analyses on the hydrochar, on the process water and on the gaseous phase obtained during the carbonization tests are presented. The EWC 19.05.03 residue is a by-product of the composting treatment applied to the organic fraction of municipal solid waste (MSW). In collaboration with Contarina S.p.A., a company that collects and treats MSW in the province of Treviso, in the North-East of Italy, this by-product was carbonized and tested both as a soil conditioner and for energy production. Results of the analyses on the solid, liquid and gaseous phases produced by the HTC process are reported in Chapter 5. The EWC 19.12.12 residue is a by-product of the refuse derived fuel (RDF) production, from the residual fraction of the MSW. This substrate was provided by Contarina S.p.A. and preliminary tests on the exploitability of the hydrochar for energy production are reported in Chapter 6, together with analyses on both the liquid and gaseous phases. A rigorous energy balance has been proposed in Chapter 8, based on the experimental data obtained for grape seeds. In this chapter, all the hypotheses and the assumptions taken to evaluate the enthalpy of the HTC reaction at different process conditions (namely, three different temperatures and three residence times) are described. In Chapter 8 a kinetic model is proposed, based on a two-step reaction mechanism. The activation energy and pre-exponential factor of the various degradation reactions were determined by means of least square optimization versus the experimental data of grape marc. A thermo fluid model is even proposed in this chapter. The model integrates mass, momentum and heat equations within the reactor domain by means of the finite volumes method (f.v.m.) approach. Convective and radiative exchange between the reactor and the fluid within the reactor have been implemented in the f.v.m. model. Under two strong assumptions (mono-component and mono-phase fluid, which fulfils the reactor), it was possible to estimate the behaviour of an equivalent fluid (eq_fluid), in terms of thermal properties of the fluid (thermal capacity, thermal conductivity and thermal diffusivity). Moreover, a simplified dynamic analytic model is also presented – based on lumped capacitance method – in order to simulate the thermal behaviour of the system, using the actual temperature profile imposed by the reactor external heater. A resistance-capacitance network was used to describe the system. Finally, the Henry’s law has been applied to assess the amount of gas really produced during the HTC process. In Chapter 9, the main conclusions of this work are reported.