Quantifying and modeling ecosystem services provided by urban greening in cities of the Southern Alps, N Italy

Population growth in urban areas is a world-wide phenomenon. According to a recent United Nations report, over half of the world now lives in cities. Numerous health and environmental issues arise from this unprecedented urbanization. Recent studies have demonstrated the effectiveness of urban green spaces and the role they play in improving both the aesthetics and the quality of life of its residents. In particular, urban green spaces provide ecosystem services such as: urban air quality improvement by removing pollutants that can cause serious health problems, carbon storage, carbon sequestration and climate regulation through shading and evapotranspiration. Furthermore, epidemiological studies with controlled age, sex, marital and socio-economic status, have provided evidence of a positive relationship between green space and the life expectancy of senior citizens. However, there is little information on the role of public green spaces in mid-sized cities in northern Italy. To address this need, a study was conducted to assess the ecosystem services of urban green spaces in the city of Bolzano, South Tyrol, Italy. In particular, we quantified the cooling effect of urban trees and the hourly amount of pollution removed by the urban forest. The information was gathered using field data collected through local hourly air pollution readings, tree inventory and simulation models. During the study we quantified pollution removal for ozone, nitrogen dioxide, carbon monoxide and particulate matter (<10 microns). We estimated the above ground carbon stored and annually sequestered by the urban forest. Results have been compared to transportation CO2 emissions to determine the CO2 offset potential of urban streetscapes. Furthermore, we assessed commonly used methods for estimating carbon stored and sequestered by urban trees in the city of Bolzano. We also quantified ecosystem disservices such as hourly urban forest volatile organic compound emissions.

Origin and variability of PM10 and atmospheric radiotracers at the WMO-GAW station of Mt. Cimone (1998-2011) and in the central Po Valley

Particulate matter is one of the main atmospheric pollutants, with a great chemical-environmental relevance. Improving knowledge of the sources of particulate matter and of their apportionment is needed to handle and fulfill the legislation regarding this pollutant, to support further development of air policy as well as air pollution management. Various instruments have been used to understand the sources of particulate matter and atmospheric radiotracers at the site of Mt. Cimone (44.18° N, 10.7° E, 2165 m asl), hosting a global WMO-GAW station. Thanks to its characteristics, this location is suitable investigate the regional and long-range transport of polluted air masses on the background Southern-Europe free-troposphere. In particular, PM10 data sampled at the station in the period 1998-2011 were analyzed in the framework of the main meteorological and territorial features. A receptor model based on back trajectories was applied to study the source regions of particulate matter. Simultaneous measurements of atmospheric radionuclides Pb-210 and Be-7 acquired together with PM10 have also been analysed to acquire a better understanding of vertical and horizontal transports able to affect atmospheric composition. Seasonal variations of atmospheric radiotracers have been studied both analysing the long-term time series acquired at the measurement site as well as by means of a state-of-the-art global 3-D chemistry and transport model. Advection patterns characterizing the circulation at the site have been identified by means of clusters of back-trajectories. Finally, the results of a source apportionment study of particulate matter carried on in a midsize town of the Po Valley (actually recognised as one of the most polluted European regions) are reported. An approach exploiting different techniques, and in particular different kinds of models, successfully achieved a characterization of the processes/sources of particulate matter at the two sites, and of atmospheric radiotracers at the site of Mt. Cimone.

Influence of climate changes on cross allergies: possible involvement of pollen transglutaminase

Allergies are a complex of symptoms derived from altered IgE-mediated reactions of the immune system towards substances known as allergens. Allergic sensibilization can be of food or respiratory origin and, in particular, apple and hazelnut allergens have been identified in pollens or fruits. Allergic cross-reactivity can occur in a patient reacting to similar allergens from different origins, justifying the research in both systems as in Europe a greater number of people suffers from apple fruit allergy, but little evidence exists about pollen. Apple fruit allergies are due to four different classes of allergens (Mal d 1, 2, 3, 4), whose allergenicity is related both to genotype and tissue specificity; therefore I have investigated their presence also in pollen at different time of germination to clarify the apple pollen allergenic potential. I have observed that the same four classes of allergens found in fruit are expressed at different levels also in pollen, and their presence might support that the apple pollen can be considered allergenic as the fruit, deducing that apple allergy could also be indirectly caused by sensitization to pollen. Climate changes resulting from increases in temperature and air pollution influence pollen allergenicity, responsible for the dramatic raise in respiratory allergies (hay fever, bronchial asthma, conjunctivitis). Although the link between climate change and pollen allergenicity is proven, the underlying mechanism is little understood. Transglutaminases (TGases), a class of enzymes able to post-translationally modify proteins, are activated under stress and involved in some inflammatory responses, enhancing the activity of pro-inflammatory phospholipase A2, suggesting a role in allergies. Recently, a calcium-dependent TGase activity has been identified in the pollen cell wall, raising the possibility that pollen TGase may have a role in the modification of pollen allergens reported above, thus stabilizing them against proteases. This enzyme can be involved also in the transamidation of proteins present in the human mucosa interacting with surface pollen or, finally, the enzyme itself can represent an allergen, as suggested by studies on celiac desease. I have hypothesized that this pollen enzyme can be affected by climate changes and be involved in exhacerbating allergy response. The data presented in this thesis represent a scientific basis for future development of studies devoted to verify the hypothesis set out here. First, I have demonstrated the presence of an extracellular TGase on the surface of the grain observed either at the apical or the proximal parts of the pollen-tube by laser confocal microscopy (Iorio et al., 2008), that plays an essential role in apple pollen-tube growth, as suggested by the arrest of tube elongation by TGase inhibitors, such as EGTA or R281. Its involvement in pollen tube growth is mainly confirmed by the data of activity and gene expression, because TGase showed a peak between 15 min and 30 min of germination, when this process is well established, and an optimal pH around 6.5, which is close to that recorded for the germination medium. Moreover, data show that pollen TGase can be a glycoprotein as the glycosylation profile is linked both with the activation of the enzyme and with its localization at the pollen cell wall during germination, because from the data presented seems that the active form of TGase involved in pollen tube growth and pollen-stylar interaction is more exposed and more weakly bound to the cell wall. Interestingly, TGase interacts with fibronectin (FN), a putative SAMs or psECM component, inducing possibly intracellular signal transduction during the interaction between pollen-stylar occuring in the germination process, since a protein immunorecognised by anti-FN antibody is also present in pollen, in particular at the level of pollen grain cell wall in a punctuate pattern, but also along the shank of the pollen tube wall, in a similar pattern that recalls the signal obtained with the antibody anti TGase. FN represents a good substrate for the enzyme activity, better than DMC usually used as standard substrate for animal TGase. Thus, this pollen enzyme, necessary for its germination, is exposed on the pollen surface and consequently can easily interact with mucosal proteins, as it has been found germinated pollen in studies conducted on human mucus (Forlani, personal communication). I have obtained data that TGase activity increases in a very remarkable way when pollen is exposed to stressful conditions, such as climate changes and environmental pollution. I have used two different species of pollen, an aero allergenic (hazelnut, Corylus avellana) pollen, whose allergenicity is well documented, and an enthomophylus (apple, Malus domestica) pollen, which is not yet well characterized, to compare data on their mechanism of action in response to stressors. The two pollens have been exposed to climate changes (different temperatures, relative humidity (rH), acid rain at pH 5.6 and copper pollution (3.10 µg/l)) and showed an increase in pollen surface TGase activity that is not accompanied to an induced expression of TGase immunoreactive protein with AtPNG1p. Probably, climate change induce an alteration or damage to pollen cell wall that carries the pollen grains to release their content in the medium including TGase enzyme, that can be free to carry out its function as confirmed by the immunolocalisation and by the in situ TGase activity assay data; morphological examination indicated pollen damage, viability significantly reduced and in acid rain conditions an early germination of apple pollen, thus possibly enhancing the TGase exposure on pollen surface. Several pollen proteins were post-translationally modified, as well as mammalian sPLA2 especially with Corylus pollen, which results in its activation, potentially altering pollen allergenicity and inflammation. Pollen TGase activity mimicked the behaviour of gpl TGase and AtPNG1p in the stimulation of sPLA2, even if the regulatory mechanism seems different to gpl TGase, because pollen TGase favours an intermolecular cross-linking between various molecules of sPLA2, giving rise to high-molecular protein networks normally more stable. In general, pollens exhibited a significant endogenous phospholipase activity and it has been observed differences according to the allergenic (Corylus) or not-well characterized allergenic (Malus) attitude of the pollen. However, even if with a different intensity level in activation, pollen enzyme share the ability to activate the sPLA2, thus suggesting an important regulatory role for the activation of a key enzyme of the inflammatory response, among which my interest was addressed to pollen allergy. In conclusion, from all the data presented, mainly presence of allergens, presence of an extracellular TGase, increasing in its activity following exposure to environmental pollution and PLA2 activation, I can conclude that also Malus pollen can behave as potentially allergenic. The mechanisms described here that could affect the allergenicity of pollen, maybe could be the same occurring in fruit, paving the way for future studies in the identification of hyper- and hypo- allergenic cultivars, in preventing environmental stressor effects and, possibly, in the production of transgenic plants.

Bayesian space-time data fusion for real-time forecasting and map uncertainty

Environmental computer models are deterministic models devoted to predict several environmental phenomena such as air pollution or meteorological events. Numerical model output is given in terms of averages over grid cells, usually at high spatial and temporal resolution. However, these outputs are often biased with unknown calibration and not equipped with any information about the associated uncertainty. Conversely, data collected at monitoring stations is more accurate since they essentially provide the true levels. Due the leading role played by numerical models, it now important to compare model output with observations. Statistical methods developed to combine numerical model output and station data are usually referred to as data fusion. In this work, we first combine ozone monitoring data with ozone predictions from the Eta-CMAQ air quality model in order to forecast real-time current 8-hour average ozone level defined as the average of the previous four hours, current hour, and predictions for the next three hours. We propose a Bayesian downscaler model based on first differences with a flexible coefficient structure and an efficient computational strategy to fit model parameters. Model validation for the eastern United States shows consequential improvement of our fully inferential approach compared with the current real-time forecasting system. Furthermore, we consider the introduction of temperature data from a weather forecast model into the downscaler, showing improved real-time ozone predictions. Finally, we introduce a hierarchical model to obtain spatially varying uncertainty associated with numerical model output. We show how we can learn about such uncertainty through suitable stochastic data fusion modeling using some external validation data. We illustrate our Bayesian model by providing the uncertainty map associated with a temperature output over the northeastern United States.

Novel investigation methods in Computational Social Dynamics and Complex Systems

In this thesis the evolution of the techno-social systems analysis methods will be reported, through the explanation of the various research experience directly faced. The first case presented is a research based on data mining of a dataset of words association named Human Brain Cloud: validation will be faced and, also through a non-trivial modeling, a better understanding of language properties will be presented. Then, a real complex system experiment will be introduced: the WideNoise experiment in the context of the EveryAware european project. The project and the experiment course will be illustrated and data analysis will be displayed. Then the Experimental Tribe platform for social computation will be introduced . It has been conceived to help researchers in the implementation of web experiments, and aims also to catalyze the cumulative growth of experimental methodologies and the standardization of tools cited above. In the last part, three other research experience which already took place on the Experimental Tribe platform will be discussed in detail, from the design of the experiment to the analysis of the results and, eventually, to the modeling of the systems involved. The experiments are: CityRace, about the measurement of human traffic-facing strategies; laPENSOcosì, aiming to unveil the political opinion structure; AirProbe, implemented again in the EveryAware project framework, which consisted in monitoring air quality opinion shift of a community informed about local air pollution. At the end, the evolution of the technosocial systems investigation methods shall emerge together with the opportunities and the threats offered by this new scientific path.