• Energy Research
• 2021-2025close
• Restricted close
• Open Source close
• NL close
• AT close

Rising temperatures, increasingly frequent extreme weather events and sea level rise are playing a growing role in shaping displacement, rural-urban migration, circular movements but also voluntary and forced immobilities. The debate on climate mobilities – the interplay between climate change and human mobility – is currently moving centre stage in migration studies. Migration theory, on the other hand, does not necessarily reflect sufficiently on the role of the environment in mobility patterns. Including an understanding of the complex nature of climate mobilities avoids assuming climate change related mobility as new or exceptional per se, and offers understanding of the plural, multi-causal, and political ways in which climate change and human im/mobilities intersect.

The potential of renewable energy should be fully exploited in the transportation sector to achieve a cleaner production. Therefore, this paper proposes an on-grid hybrid hydrogen refueling and battery swapping station powered by wind energy. This novel concept can promote the development of low-carbon emission vehicles including hydrogen-based vehicle and battery electric vehicle. During the daily operation of the station, the multiple uncertainties may lead to a higher operational cost. To address this problem, a hybrid stochastic/distributionally robust optimization method is proposed to handle different uncertainties for the energy management problem. The first type of uncertainties can be depicted by a certain distribution, i.e. electricity price and wind power, which is processed by a stochastic optimization method. The second type of uncertainties is associated with human behaviors and is difficult to find its probability distribution, i.e. the hydrogen demand of hydrogen-based vehicles, so the second type is processed by a distributionally robust optimization method. The overall objective is to minimize the total operational cost of the station, which also considers the battery swapping station overstock punishment. Because a reasonable battery swapping scheduling can reduce the waiting time of users and operational cost of the station. The results indicate that the proposed method can effectively address the conservatism of solutions as its total operational cost is 4.4% lower than that of the hybrid stochastic/robust optimization method under a high confidence level.

AbstractNitrous oxide (N2O) is a potent greenhouse gas and causes stratospheric ozone depletion. While the emissions of N2O from soil are widely recognized, recent research has shown that terrestrial plants may also emit N2O from their leaves under controlled laboratory conditions. However, it is unclear whether foliar N2O emissions are universal across varying plant taxa, what the global significance of foliar N2O emissions is, and how the foliage produces N2O in situ. Here we investigated the abilities of 25 common plant taxa, including trees, shrubs and herbs, to emit N2O under in situ conditions. Using 15N isotopic labeling, we demonstrated that the foliage‐emitted N2O was predominantly derived from nitrate. Moreover, by selectively injecting biocide in conjunction with the isolating and back‐inoculating of endophytes, we demonstrated that the foliar N2O emissions were driven by endophytic bacteria. The seasonal N2O emission rates ranged from 3.2 to 9.2 ng N2O–N g−1 dried foliage h−1. Extrapolating these emission rates to global foliar biomass and plant N uptake, we estimated global foliar N2O emission to be 1.21 and 1.01 Tg N2O–N year−1, respectively. These estimates account for 6%–7% of the current global annual N2O emission of 17 Tg N2O–N year−1, indicating that in situ foliar N2O emission is a universal process for terrestrial plants and contributes significantly to the global N2O inventory. This finding highlights the importance of measuring foliar N2O emissions in future studies to enable the accurate assigning of mechanisms and the development of effective mitigation.

This chapter presents current knowledge, methods, and applications of nutritional energetics in an aquaculture setting. All organisms ingest and metabolize macronutrients that supply dietary energy and the nutrients have different fates. The different aspects of energy flow from feed to fish or shrimp are similar to those known in land animals or birds, but the aquatic mode of life imposes challenges and confers advantages both at the cellular level and at the whole organism level. Energy gain and losses are governed by the efficiency with which the macronutrients are utilized. The application of net energy system as prevailing in monogastric land animal nutrition is also valid for aquatic organisms. The large number of species reared by aquaculture is a real challenge, but many of the basic principles are valid across species. There is a need for precisely quantifying the partition of dietary digestible energy for somatic growth, reproduction, and other physiological changes due to environmental factors.

Die anhaltenden globalen Umweltprobleme haben die Bedeutung des Übergangs zu einer nachhaltigeren und grüneren Wirtschaft hervorgehoben. Um einen solchen Übergang zu erleichtern, ist es entscheidend, Fachleute mit den richtigen grünen Kompetenzen auszustatten. Fähigkeiten, die Einstellung und das Wissen bilden zusammen grüne Kompetenzen, welche in ihrer Gesamtheit erforderlich sind, um eine nachhaltigere Gesellschaft zu fördern und aufzubauen. In aktueller Literatur wird deutlich, dass die Identifizierung von Fähigkeiten aufgrund der sich ständig weiterentwickelnden Qualifikationsanforderungen schwierig ist. In dieser Hinsicht haben Bildungsanbieter Schwierigkeiten, ihre Programme und Schulungen so anzupassen, dass sie die notwendigen Fähigkeiten fördern. Die vorliegende Arbeit soll Antworten darauf geben und ist durch eine kohärente Methodik und Zielsetzungen wie folgt strukturiert: das Verständnis der "grünen" Terminologie und ihrer Relevanz, die Rolle der Hochschulbildung bei der Förderung grüner Fähigkeiten, Identifizierung geeigneter generischer Fähigkeiten, Evaluierung der wichtigsten generischen grünen Fähigkeiten und Analyse der Curricula ausgewählter Bachelor- und Masterstudiengänge des Management Departments der FH JOANNEUM, um das Vorhandensein generischer grüner Fähigkeiten zu bestimmen. Zu diesem Zweck erfolgt eine systematische Literaturrecherche, die Erstellung einer Liste relevanter Publikationen und die Durchführung einer quantitativen Häufigkeitsanalyse, um eine Hierarchie der Fähigkeiten zu ermitteln. Der zweite Teil der Forschung zielt darauf ab, das Vorhandensein und das Ausmaß von generischen grünen Fähigkeiten in den Lehrplänen der Hochschulstudiengänge, die am Management Department der FH JOANNEUM angeboten werden, zu analysieren. Die Arbeit leistet einen Beitrag zum Verständnis der Bedeutung grüner Fähigkeiten in der Hochschulbildung und der Rolle, die regionale Bildungsanbieter bei der Förderung des grünen Wandels spielen können. Die Arbeit schließt mit einer Diskussion über die Grenzen und Implikationen für zukünftige Forschung. Ongoing global environmental concerns and issues have emphasized the importance of transitioning towards a more sustainable and green economy. To facilitate such a transition, it is crucial to equip professionals with the right set of green skills. Skills, attitudes and knowledge form green competences that are collectively needed to promote and build a more sustainable society. Recent literature highlights that the identification of necessary skills can be challenging due to the constant evolvement of skill requirements. In this respect, education providers are struggling to adapt their programmes and training to foster necessary skills. The thesis aims to provide answers in this regard and is structured around a coherent methodology and objectives: understanding the "green" terminology and its relevance, identifying the role of higher education in fostering green skills, identifying an appropriate generic skill framework, evaluating the most important generic green skills, and analysing the curricula of selected bachelor's, master's, and master course programmes of the Management Department of FH JOANNEUM to determine the presence of generic green skills. For this purpose, the thesis employs a systematic literature review, generating a list of relevant publications and a quantitative frequency analysis to evaluate a hierarchy of generic green skills. The second part of the study aims to analyse the presence and extent of generic green skills in the curricula of higher education programmes offered at the Management Department of FH JOANNEUM. The thesis contributes to understanding the importance of green skills in higher education and the role that regional education providers can play in promoting green change by including green skills in the curricula. The thesis concludes with a discussion of the limitations and implications for future research.

The pig industry needs strategies to solve problems such as poor rearing environment, diseases, odours, and high energy loads. In this study, an air recirculated ventilation system (ARVS) was developed with optimally designed modules and an operating algorithm. Validation experiments conducted in winter and reported here but experiments carried out during the summer and during changes in season and reported in Kim et al. (2023). Environmental data (air temperature, relative humidity, carbon dioxide, ammonia, and ventilation rate) were automatically collected during winter and livestock disease and stress of piglets were evaluated by sampling. In winter the ARVS reused internal heat energy to satisfy the pig thermal demand. Each module of ARVS modules was designed and integrated based on the previous researches. Environmental factors were monitored in real time, and then ARVS was automatically controlled using developed algorithm. The ventilation rate of the ARVS was about 3 times more than that of the conventional ventilation system (CVS). Air temperature, relative humidity, and ammonia gas inside the ARVS piglet room were optimally maintained. Also, by reusing about 73% of internal energy, it was possible to reduce heating costs. The average concentrations of ammonia and odour measured at the outlet were 2.1 ppm and 251 OU. Piglets of the ARVS weighed 1.6 kg more than those of the CVS. The disease detection rate was <1% with beneficial bacteria increased and harmful bacteria decreased.

Die vorliegende Arbeit befasst sich mit der Anwendung von Lastverschiebungsstrategien in IT-Umgebungen. Dabei liegt der Fokus auf der Nutzung von maschinellem Lernen zur Steigerung der Energieeffizienz und der damit verbundenen Reduktion von Kosten. Angesichts der steigenden Nachfrage nach IT-Dienstleistungen und der zunehmenden Nutzung erneuerbarer Energien im Stromnetz wird ein effizientes Ressourcenmanagement immer wichtiger. Durch eine umfassende Analyse der Infrastruktur eines global agierenden IT- Unternehmens, wird die Wirksamkeit von zeitbasierter und standortbasierter Lastverschiebung analysiert und bewertet. Das Ziel dabei ist es, Energiekosten zu minimieren, ohne die Leistungsfähigkeit und Ausfallsicherheit des Systems zu beeinträchtigen. Um einen Einblick in das Thema ”LoadShifting“ zu gewinnen, wird ein umfassender Überblick über das Thema Energiemanagement bei Servern und die damit verbundenen Herausforderungen gegeben. Zusätzlich werden Techniken wie Virtualisierung, der Einsatz von Containern und Methoden des maschinellen Lernens behandelt, um die Effizienz von Lastverschiebungsstrategien zu verbessern. Darüber hinaus wird der Einfluss externer Faktoren wie die Variabilität der Energiepreise und die Verfügbarkeit erneuerbarer Energiequellen auf die Effizienz von Lastverschiebungsstrategien untersucht. Anschließend wird die Methodik zur Analyse der Infrastruktur des Unternehmens und der Erstellung der Laststatistiken beschrieben. In dieser wird ein detaillierter Plan zur Datenerhebung, die verwendeten Methoden zur Auswertung der Messwerte und der Vergleich von verschiedenen Cloud Dienstleistern erläutert. Die Analyse der IT-Infrastruktur des Unternehmens zeigt dabei eine signifikante Unterauslastung der Serverressourcen auf und verdeutlicht das Optimierungspotenzial durch eine dynamische Ressourcenzuweisung. Durch die Simulation einer optimierten Serverauslastung zeigt die Arbeit ein Reduktionspotenzial der Infrastrukturkosten von 57,14% bei gleichbleibender Performance. Des Weiteren werden alternative Cloud-Anbieter, wie die Azure Cloud von Microsoft und die Private Cloud von Hetzner analysiert und deren Einsparungspotenzial berechnet. Die Cloud der Firma Hetzner hat sich dabei als die kosteneffektivste Lösung erwiesen und führt im Vergleich zur aktuellen Infrastruktur des Unternehmens zu einer Kostenreduktion von 69,43%. Die Arbeit untersucht außerdem die mögliche Integration von Algorithmen für maschinelles Lernen für die prädiktiven Lastverwaltung und deren Trainingsmethoden. Die Ergebnisse deuten darauf hin, dass durch die Implementierung fortgeschrittener Algorithmen und durch die Anpassung flexibler Lastverschiebungsstrategien erhebliche Verbesserungen bei der Energieeffizienz, den Betriebskosten und der Gesamtsystemleistung zu finden sind. Diese Forschung trägt zur laufenden Diskussion über nachhaltige IT-Praktiken bei und liefert Erkenntnisse über das Potenzial von Lastverschiebung und maschinellem Lernen zur Optimierung von IT-Infrastrukturen. This thesis focuses on the application of load shifting strategies in IT environments, with an emphasis on the use of machine learning to increase energy efficiency and reduce associated costs. Given the growing demand for IT services and the increasing use of renewable energy in the power grid, efficient resource management is becoming increasingly important. Through a comprehensive analysis of the infrastructure of a globally operating IT company, the effectiveness of time-based and location-based load shifting is analyzed and evaluated. The goal is to minimize energy costs without compromising the system’s performance and reliability. To gain insight into the topic of load shifting, a comprehensive overview of server energy management and associated challenges is provided. In addition, techniques such as virtualization, the use of containers, and methods of machine learning are discussed to improve the efficiency of load shifting strategies. Furthermore, the thesis explores the impact of external factors such as the variability of energy prices and the availability of renewable energy sources on the efficiency of load shifting strategies. The methodology for analyzing the company’s infrastructure and creating load statistics is then described. This includes a detailed plan for data collection, the methods used to evaluate the measurements, and a comparison of various cloud service providers. The analysis of the company’s IT infrastructure shows a significant underutilization of server resources and highlights the optimization potential through dynamic resource allocation. By simulating optimized server utilization, the thesis demonstrates a potential reduction in infrastructure costs of 57.14% while maintaining the same level of performance. Furthermore, alternative cloud providers such as Microsoft’s Azure Cloud and Hetzner’s Private Cloud are analyzed, and their cost-saving potential is calculated. Hetzner’s cloud proved to be the most cost-effective solution, leading to a cost reduction of 69.43% compared to the company’s current infrastructure. The thesis also examines the potential integration of machine learning algorithms for predictive load management and their training methods. The results suggest that significant improvements in energy efficiency, operating costs, and overall system performance can be found through the implementation of advanced algorithms and the adaptation of flexible load shifting strategies. This research contributes to the ongoing discussion on sustainable IT practices and provides insights into the potential of load shifting and machine learning to optimize IT infrastructures.

AbstractBACKGROUNDOfficial stable isotope databases, based on the analysis of (D/H)I ethanol, (D/H)II ethanol, δ13Cethanol and δ18Owater of wine, are an indispensable tool for establishing the limits beyond which the mislabeling or the addition of sugar and/or water in wine production can be detected. The present study investigates, for the first time, whether the use of hybrid varieties instead of European Vitis vinifera for wine production can have an impact on the stable isotope ratios.RESULTSThe analyses were performed by isotope ratio mass spectrometry and site‐specific natural isotope fractionation by nuclear magnetic resonance, in accordance with the official methods of the International Organization of Grapes and Wine. The comparison shows the tendency of some stable isotope ratios of hybrid varieties, in particular (D/H)I, to deviate from the regional averages of the V. vinifera samples. Notably, Baron, Monarch and Regent showed significantly different values at one of the two sampling sites. Particularly high δ13C values characterize Helios compared to other hybrid varieties.CONCLUSIONFor the first time, and from an isotopic point of view, the present study investigates the wine obtained from hybrid varieties, showing that further attention should be paid to their interpretation, on the basis of the database established according to the European Regulation 2018/273. © 2022 Society of Chemical Industry.

Abstract Climate change and rapid adaption of invasive pathogens pose a constant pressure on the fruit industry to develop improved varieties. Aiming to accelerate the development of better-adapted cultivars, new breeding techniques have emerged as a promising alternative to meet the demand of a growing global population. Accelerated breeding, cisgenesis, and CRISPR/Cas genome editing hold significant potential for crop trait improvement and have proven to be useful in several plant species. This review focuses on the successful application of these technologies in fruit trees to confer pathogen resistance and tolerance to abiotic stress and improve quality traits. In addition, we review the optimization and diversification of CRISPR/Cas genome editing tools applied to fruit trees, such as multiplexing, CRISPR/Cas-mediated base editing and site-specific recombination systems. Advances in protoplast regeneration and delivery techniques, including the use of nanoparticles and viral-derived replicons, are described for the obtention of exogenous DNA-free fruit tree species. The regulatory landscape and broader social acceptability for cisgenesis and CRISPR/Cas genome editing are also discussed. Altogether, this review provides an overview of the versatility of applications for fruit crop improvement, as well as current challenges that deserve attention for further optimization and potential implementation of new breeding techniques.