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While the effects of climate change unfold and become more visible, infrastructures - especially those related to the distribution of water and energy - are the most exposed to the deep changes expected in the next years. Water is fundamental for people, and for infrastructures like energy, waste, and food production. Water sustainability is therefore a fundamental aspect to be addressed by an efficient use of the resources and by mainteining high quality standards. Hence, water industry and water infrastructure need a deep transformation; in this paper we present a framework based on complex systems and management science as a possible pathway to reshape and optimize the performance of the water infrastructure to cope with the complexity of todays' challenges. To this aim, we propose the framework Acque 2.0 (Water 2.0), where we point out how the increase of the infrastructural resilience and of the overall quality of service can be attained by integrating models, algorithms and numerical methods like network simulations and big data analytics for the predictive maintenance of water networks. We discuss how Complexity Science is the natural glue allowing technical, management and social issues to be integrated in the holistic vision of the "water system" needed play to provide measures for an integrated sustainability reporting that involves utilities, regulators, policy makers, and citizens.

In this contribution, we discuss the implementation of a novel microelectromechanical-systems (MEMS)-based energy harvester (EH) concept within the technology platform available at the ISAS Institute (TU Vienna, Austria). The device, already presented by the authors, exploits the piezoelectric effect to convert environmental vibrations energy into electricity, and presents multiple resonant modes in the frequency range of interest (i.e. below 10 kHz). The experimental characterisation of a sputter deposited aluminium nitride piezoelectric thin-film layer is reported, leading to the extraction of material properties parameters. Such values are then incorporated in the finite element method model of the EH, implemented in Ansys Workbench (TM), in order to get reasonable estimates of the converted power levels achievable by the proposed device solution. Multiphysics simulations indicate that extracted power values in the range of several mu W can be addressed by the EH-MEMS concept when subjected to mechanical vibrations up to 10 kHz, operating in closed-loop conditions (i.e. piezoelectric generator connected to a 100 k Omega resistive load). This represents an encouraging result, opening up the floor to exploitations of the proposed EH-MEMS device in the field of wireless sensor networks and zero-power sensing nodes.

The biomimetic CCS strategy is based on the enhancement of CO2 absorption rate into aqueous solutions by the enzyme carbonic anhydrase (CA). Immobilized CA on fine dispersed solids promotes the heterogeneous biocatalysis close to the gas-liquid interface and the enhancement of CO2 absorption rate. In this work a theoretical model of a slurry absorption unit for the biomimetic CO2 capture in K2CO3 solutions was developed and solved using the commercial software package Comsol Multiphysics®. The staged bubble column (SBC) configuration was selected to capture CO2 in aqueous slurry containing immobilized CA under counter-current gas-liquid flow. The theoretical framework included: the 'tanks-in-series' model to describe the unit; the two films theory to describe the absorption rate at the gas-liquid interface; the pseudo-homogeneous approach and a reversible Michaelis and Menten kinetics to model CO2 conversion by the slurry biocatalyst. The simulations provided the CO2 capture rate and the CO2 concentration profiles in the liquid boundary layer. Simulation results showed that the CO2 capture rate poorly increased when dissolved CA was used within the solubility limit (≈100 mg/L). Remarkably, about three fold enhancement of the CO2 absorption rate with respect to pure alkaline solvent when absorption in the presence of CA immobilized on fine particles was simulated.

Silicon has long been established as the material of choice for the microelectronics industry. This is not yet true in photonics, where the limited degrees of freedom in material design combined with the indirect bandgap are a major constraint. Recent developments, especially those enabled by nanoscale engineering of the electronic and photonic properties, are starting to change the picture, and some silicon nanostructures now approach or even exceed the performance of equivalent direct-bandgap materials. Focusing on two application areas, namely communications and photovoltaics, we review recent progress in silicon nanocrystals, nanowires and photonic crystals as key examples of functional nanostructures. We assess the state of the art in each field and highlight the challenges that need to be overcome to make silicon a truly high-performing photonic material.

Adaptation to climate change is a major challenge facing the agricultural sector worldwide. Olive (Olea europaea L.) is a global, high value crop currently cultivated in 28 countries worldwide. Global data to assess the vulnerability of the crop to climate variability are scarce, and in some notable cases, such the United Nations Food and Agriculture Organization database (FAO, 2006), qualitative assessments rather than quantitative indicators are provided. The aim of this study is to demonstrate a new approach to help overcome these constraints toward a globally applicable method to assess the adaptability of olive cultivars. The adaptability of 11 cultivars, widely used in 11 countries worldwide, was studied using a new generic approach based on the evaluation of soil hydrological regime against cultivar-specific hydrological requirements. The approach requires local data, notably on soil hydrological properties, but it is easily transferable to other countries and regions. We applied an agrohydrological model in 60 soil units to determine hydrological indicators both in a reference (1961-1990) and a future (2021-2050) climate case. We compared indicators with cultivar-specific requirements to achieve the target yield; requirements were established using experimental yield response curves. We estimated the probability of adaptation, i.e., the probability that a given cultivar attains the target yield, and we used it to evaluate the cultivar potential distribution in the study area. At the locations where soil hydrological conditions were favorable, the probabilities of adaptation of the cultivars were high in both climate cases. The results show that the area with suitable conditions for the target yield (area of adaptability) decreased under future climate for all the cultivars, with higher reduction for Frantoio and Maiatica and smaller reduction for Itrana, Nocellara, Ascolana, and Kalamata. These cultivars are currently grown in Argentina, United States (US), Australia, France, Greece, and Italy. Our results indicate also that these cultivars require higher available soil water to attain the target yield, i.e., we may expect similar vulnerability in other parts of the world. Based on these findings, we provide some specific recommendations for enrichment of global databases and for further developments of our approach, to increase its potential for global application.

Viticulture is a worldwide agricultural sector with a relevant economic importance, especially in regions where the climate and environmental conditions meet requirements for the production of high quality wines. The impact of climate change combined with the increased frequency of extreme events predicted for the next future has already shown its potential detrimental effects on viticulture suitability, but few studies currently explored the effect of long-term climate change and extreme events by considering the inter-varietal variability of grapevine. In this study, the combined effect of mean climate change and extreme events (frost events at bud break and suboptimal temperatures for fruit-set) under future scenarios (RCP 4.5 and 8.5 for two time slices 2036-2065 and 2066-2095, respectively) was evaluated considering four grapevine varieties with very early, early, middle-early and late phenological cycles. The UniChill model calibrated for these varieties was applied in Europe to assess phenological dynamics (budbreak and flowering) using the outputs of a statistical downscaling procedure. Frost impact around budbreak stage as well as the impact of suboptimal temperature around flowering was estimated under present and future scenarios. The results showed a general earlier occurrence of budbreak and flowering stages with a particular relevance on northeastern Europe. The effect of warmer temperatures had a greater effect on late compared to very early and early varieties in western regions. The frequency of frost events at budbreak (T-min < 0 degrees C) showed wide variability across Europe, with a strong decrease in western regions (e.g. Spain and UK) and an increase in central Europe (e.g. Germany) for future scenarios. The decrease in the frequency of frost events was especially evident for very early and early varieties. The impact of suboptimal temperatures at flowering evidenced a significant variability across a latitudinal gradient while this effect did not show significant results when comparing cultivars and scenarios. The results of these studies highlighted that in a warmer climate frost events rather than stress at flowering will reshape the distribution of grapevine varieties in Europe.

The aim of the present study was to develop a kinetic model for a recently proposed unique and novel metabolic process called capnophilic (CO2-requiring) lactic fermentation (CLF) pathway in Thermotoga neapolitana. The model was based on Monod kinetics and the mathematical expressions were developed to enable the simulation of biomass growth, substrate consumption and product formation. The calibrated kinetic parameters such as maximum specific uptake rate (k), semi-saturation constant (kS), biomass yield coefficient (Y) and endogenous decay rate (kd) were 1.30 h(-1), 1.42 g/L, 0.1195 and 0.0205 h(-1), respectively. A high correlation (>0.98) was obtained between the experimental data and model predictions for both model validation and cross validation processes. An increase of the lactate production in the range of 40-80% was obtained through CLF pathway compared to the classic dark fermentation model. The proposed kinetic model is the first mechanistically based model for the CLF pathway. This model provides useful information to improve the knowledge about how acetate and CO2 are recycled back by Thermotoga neapolitana to produce lactate without compromising the overall hydrogen yield.

Climate Data Records of soil moisture are fundamental for improving our understanding of long-term dynamics in the coupled water, energy, and carbon cycles over land. To respond to this need, in 2012 the European Space Agency (ESA) released the first multi-decadal, global satellite-observed soil moisture (SM) dataset as part of its Climate Change Initiative (CCI) program. This product, named ESA CCI SM, combines various single-sensor active and passive microwave soil moisture products into three harmonised products: a merged ACTIVE, a merged PASSIVE, and a COMBINED active + passive microwave product. Compared to the first product release, the latest version of ESA CCI SM includes a large number of enhancements, incorporates various new satellite sensors, and extends its temporal coverage to the period 1978–2015. In this study, we first provide a comprehensive overview of the characteristics, evolution, and performance of the ESA CCI SM products. Based on original research and a review of existing literature we show that the product quality has steadily increased with each successive release and that the merged products generally outperform the single-sensor input products. Although ESA CCI SM generally agrees well with the spatial and temporal patterns estimated by land surface models and observed in-situ, we identify surface conditions (e.g., dense vegetation, organic soils) for which it still has large uncertainties. Second, capitalising on the results of > 100 research studies that made use of the ESA CCI SM data we provide a synopsis of how it has contributed to improved process understanding in the following Earth system domains: climate variability and change, land-atmosphere interactions, global biogeochemical cycles and ecology, hydrological and land surface modelling, drought applications, and meteorology. While in some disciplines the use of ESA CCI SM is already widespread (e.g. in the evaluation of model soil moisture states) in others (e.g. in numerical weather prediction or flood forecasting) it is still in its infancy. The latter is partly related to current shortcomings of the product, e.g., the lack of near-real-time availability and data gaps in time and space. This study discloses the discrepancies between current ESA CCI SM product characteristics and the preferred characteristics of long-term satellite soil moisture products as outlined by the Global Climate Observing System (GCOS), and provides important directions for future ESA CCI SM product improvements to bridge these gaps.