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Technical and economic developments in battery and fast-charging technologies could soon make fuel cell electric vehicles, which run on hydrogen, superfluous in road transport

Wireless Sensor Networks (WSN) are a key component of the Internet of Things (IoT) revolution. WSN nodes are in general battery-powered, thereby and efficient usage of their energy budget is of paramount importance to avoid performance degradation in IoT applications. To this end, this chapter proposes techniques to manage the WSN nodes’ power consumption. The aim of the first technique is to minimize the transmitted power for a given quality of service requirement at the receiver side. To this end, a power control is considered at each WSN node as well as the use of multiple distributed access points at the receiver side. The second technique to reduce the WSN energy consumption is energy harvesting (EH). Namely, the use of artificial light EH is considered to extend the WSN lifetime. Thus, an experimental setup based on a photovoltaic cell, a boost converter and a commercial WSN node is presented. It is shown that under certain settings it is possible to extend the WSN node’s lifetime without bound, when the transmission time period is above a certain threshold.

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Plants are sessile organisms that suffer from a multitude of challenges such as abiotic stress or the interactions with competitors, antagonists and symbionts, which influence their performance as well as their eco-physiological and biochemical responses in complex ways. In particular, the combination of different stressors and their impact on plant biomass production and the plant's ability to metabolically adjust to these challenges are less well understood. To study the effects of mineral nitrogen (N) availability, interspecific competition and the association with arbuscular mycorrhizal fungi (AMF) on biomass production, biomass allocation patterns (root/shoot ratio, specific leaf area) and metabolic responses, we chose the model organism Plantago lanceolata L. (Plantaginaceae). Plants were grown in a full factorial experiment. Biomass production and its allocation patterns were assessed at harvest, and the influence of the different treatments and their interactions on the plant metabolome were analysed using a metabolic fingerprinting approach with ultra-high performance liquid chromatography coupled with time-of-flight-mass spectrometry. Limited supply of mineral N caused the most pronounced changes with respect to plant biomass and biomass allocation patterns, and altered the concentrations of more than one third of the polar plant metabolome. Competition also impaired plant biomass production, yet affected the plant metabolome to a much lesser extent than limited mineral N supply. The interaction of competition and limited mineral N supply often caused additive changes on several traits. The association with AMF did not enhance biomass production, but altered biomass allocation patterns such as the root/shoot ratio and the specific leaf area. Interestingly, we did not find significant changes in the plant metabolome caused by AMF. A targeted analysis revealed that only limited mineral N supply reduced the concentrations of one of the main target defence compounds of P. lanceolata, the iridoid glycoside catalpol. In general, the interaction of competition and limited mineral N supply led to additive changes, while the association with AMF in any case alleviated the observed stress responses. Our results show that the joint analysis of biomass/allocation patterns and metabolic traits allows a more comprehensive interpretation of plant responses to different biotic and abiotic challenges; specifically, when multiple stresses interact.

SUSTAGRI4.0 will bring digital and marketing skills to small-scale farmers and agribusiness owners towards a sustainable and community-driven future. SUSTAGRI4.0 core aim is to promote a more sustainable agriculture and support sustainable agriculture businesses in their transition to Agriculture 4.0. This report, comprised from three clusters, the highlighting results of the study, focusing on the professional skills of the future European farming community build on the cornerstones of sustainability, digitalization, and entrepreneurship: Best practices at consortium level; digital survey; focus groups. The country analysis is based on critical research of relevant open sources, including, inter alia, data from national and regional/municipal organizations, law enforcement practice, formal education curriculum, scientific publications and NGOs reports. These desk studies have been of high importance for us, balancing academic findings, correcting views and seriously expanding our understanding of youth issues and related processes of digitalization. Moreover, they have served as a pool for ideas, inspiration and practical models for partner organizations [Cluster I]. Digital Survey recap the desk and case studies, providing valuable insights from our target groups – both from youth and stakeholders and enriching us with clarifying first-hand knowledge for preparing the next steps of our project [Cluster II]. Development of focus groups: Research on local producers & sustainable agricultural business owners and VET. After finishing the research phase (national level) has been completed, a number of best practices has been identified and described in order to compare official data and statistics with real implementation of abovementioned tools [Cluster III]

Abstract In a one-day ahead energy market, power plant owners have to provide a generation schedule in advance. A scheduling strategy for concentrating solar power plants with thermal energy storage is studied in this paper. The strategy is based on a mixed-integer linear programming model which approximates the plant operation. The main novelty of the method is the inclusion in the optimization model of a penalty term for generation variation (cycling) with different intensities depending on the power block situation, i.e., normal operation, startup or shutdown. This distinction increases the search space for schedules with reduced cycling and high energy sale profits. Cycling reduction leads to higher lifetimes of the power block elements, lower maintenance costs, and easier plant operability. A simulation case study, based on a 50 MW plant participating in the Spanish market, is included. The main conclusion of this study is that an important reduction of the generation cycling can be achieved without reducing profits. Other advantages of the method are also shown. By means of historical data, it is possible to estimate the lowest level of generation cycling which maintains profits. Moreover, lower generation deviations are obtained, facilitating the tasks of the electric system operator.

Global crises such as climate change and the COVID-19 pandemic do not affect cities uniformly. These crises converge in urban areas and often interact through their primary and secondary impacts with the vulnerability of urban populations. This paper investigates urban development dynamics and socio-environmental vulnerability in a megalopolis in the Global South, São Paulo (Brasil). Our goal is to assess the connections between urbanisation and risk exposure, a gap in vulnerability research when considering climate and health hazards. We implement an innovative mixed methods research design using thematic, hot spots, and survival analysis techniques. Two focus groups at the central and peripheral regions of the city provide qualitative data, while open data sets and COVID-19 case microdata (n= 1,948,601) support the quantitative methods. We find a complex system of relationships between urbanisation and risk exposure. Socioeconomic vulnerability characteristics of the population do not explain exposure entirely but significantly contribute to risk-prone location choices. Additionally, social vulnerability factors such as low income and social segregation are highly concentrated in São Paulo, coinciding with substantial COVID-19 fatality rates during 25 months of the pandemic. Finally, qualitative analysis helps us overcome the limitations of quantitative methods on the intraurban scale, indicating contrasting experiences of resilience and resistance during the health crisis. While the low-income group faced mental health and food security issues, the upper-middle-income sample took advantage of opportunities arising during the pandemic to improve work and well-being. We argue that these results demonstrate potential synergies for climate adaptation and health policies in combating socio-environmental vulnerability at the community scale. Environmental justice is thus paramount for global development agendas such as the Sustainable Development Goals, Sendai Framework, and the Paris Agreement.

This article presents an optimization model to allocate the energy produced by a PV-coupled battery system in an energy community using the compensation mechanism available to self-consumption renewable systems up to 100 kW in Spain. The considered community incorporates public buildings, an EV charging station, and a group of households in situation of energy poverty. The evaluated scenarios considered three strategies to fairly distribute the energy among the group of vulnerable households, while minimizing costs for all members' involved. The scenarios also incorporate the use of sharing coefficients with different temporalities (annual, monthly, hourly). Our results indicate that providing vulnerable households with the same energy volume annually, but with the flexibility to allocate it differently throughout the year is the most efficient. We also found that using temporarily variable coefficients – monthly, hourly – instead of fixed annual coefficients maximizes the energy community's benefits. These results highlight the importance of the regulation introduced by the end of 2021 in Spain, which allowed the use of sharing coefficients up to an hourly level.