The world is talking about the Industry 4.0 or the fourth industrial revolution, that is, the current trend of higher level of automation, digitalization and data exchange in manufacturing technologies. It includes cyber-physical systems, Internet of Things and cloud computing among other technological assets. With more than 5000 sensors, which generate up to 10 GB of data per second, modern aircraft engines are an exponent of what digitalization and the Internet of Aircraft Things could furnish, as part of the upcoming Industry 4.0 revolution, in the aviation industry. This new era has the potential to improve air transport key performance areas. Particularly, in an industry where safety levels are so high and the margins for improvement are extremely tight, this upcoming era might imply a shift in safety improvement. In an attempt to define Aviation 4.0, this chapter discusses the stages of aviation development from basic VFR flight rules at Aviation 1.0 up to Aviation 4.0 where cyber-physical systems are designed to assist humans’ unkind or hazardous work, to take decisions and to complete tasks autonomously. It illustrates the current and future cases of application of Aviation 4.0 to increase the aviation safety, while outlines how they might increase aviation safety levels.

In the last 40 years, the aeronautical industry has managed to move from a specialized sector to a worldwide leading industry. Companies, governments and associations all over the world acknowledge the importance of the aviation industry in supporting global development and the economy. However, aviation will be facing new challenges related to sustainability and performance in a technological environment in evolution. To succeed, the aeronautical industry must keep innovation as one of its main assets. It must master a wide range of technologies and then collaborate to integrate them into an aircraft design and development program. A collaborative approach to innovation is key to achieve these goals. The main purpose of this paper is to analyze the structure of technological innovation networks in the aviation industry and to characterize the map of the “Aviation Technology Space”. Two different approaches and methods are used. In one approach, we performed a bibliometric network analysis of aviation research scientific publications using a keyword co-occurrence analysis method to map the aerospace collaboration structures. Complementarily, we performed a patent analysis to evaluate the innovation capacity of the aviation industry in the cutting-edge technologies previously identified. From the results of this analysis, the paper provides recommendations for future innovation and research policies to allow the sector to fulfill the demanding goals by the year 2050.

Airports around the world are more and more environmentally concerned, increasing their efforts in reducing aviation impacts by applying environmental management, certification systems, or other types of ecological rating systems to their infrastructures and operation. Especially relevant are the airports’ efforts to manage and reduce their CO₂ emissions through Airport Carbon Accreditation, the efforts made by Eurocontrol to encourage collaborative environmental management, or the increasing numbers of airports worldwide that get their terminals certified according to several world-recognized Green Building Rating Standards (GBRS). However, although these standards are state-of-the-art sustainability valuation programs, none of them fully cover all the environmental impacts of aeronautical activity at an airport. This paper presents the results of an exploratory research where the use of a GBRS into a more holistic certification scheme for airports is discussed and areas of challenge are highlighted. The paper seeks to shed some light on the value of holistic approaches from the perspective of maximizing environmental management efficiency and effectiveness, the integration of actions of individual airport partners to potentially encourage greater coordination of efforts, the challenges of dealing with both construction and operational impacts within one scheme, and the accountability difficulties.

The European Universities initiative, launched by the European Commission in 2018, has its origin in the concept of Civic Universities (CivUs) and consists of transnational higher education alliances throughout the European Union that share long-term strategies. They are expected to become universities of the future, to promote European ideals and character, and to revolutionize the competitiveness and excellence of European higher education. European universities add 41 alliances, involving 31 different countries. This article presents an early quantitative evaluation of this initiative. This paper addresses the coverage of the 41 alliances and selects five of the most advanced for a deeper evaluation of their best practices and their contribution to the realization of CivUs. This paper also outlines the criteria for evaluating the extent to which good practices implemented by these alliances are aligned and can contribute to the attributes of CivUs, based upon state-of-the-art educational standards. A quantitative framework, based on application of the analytical hierarchy process (AHP), is also provided to rank the good practices developed by these alliances against the previous evaluation criteria. Furthermore, by applying a sensitivity analysis, this paper also addresses the robustness of this approach.

Today, aircraft demand is exceeding the capacity of the Air Traffic Control (ATC) system. As a result, airspace is becoming a very complex environment to control. The complexity of airspace is thus closely related to the workload of controllers and is a topic of great interest. The major concern is that variables that are related to complexity are currently recognised, but there is still a debate about how to define complexity. This paper attempts to define which variables determine airspace complexity. To do so, a novel methodology based on the use of machine learning models is used. In this way, it tries to overcome one of the main disadvantages of the current complexity models: the subjectivity of the models based on expert opinion. This study has determined that the main indicator that defines complexity is the number of aircraft in the sector, together with the occupancy of the traffic flows and the vertical distribution of aircraft. This research can help numerous studies on both air traffic complexity assessment and Air Traffic Controller (ATCO) workload studies. This model can also help to study the behaviour of air traffic and to verify that there is symmetry in structure and the origin of the complexity in the different ATC sectors. This would have a great benefit on ATM, as it would allow progress to be made in solving the existing capacity problem.

Aviation emissions from 2016 to 2050 could consume between 12% and 27% of the remaining carbon budget to keep global temperature rise below 1.5 °C above preindustrial levels. Consequently, aviation is being challenged to immediately start to reduce its in-sector emissions, then sharply reduce its CO₂ emissions and fully decarbonize toward the second half of this century. Among the analyses carried out within the Horizon 2020 project PARE—Perspectives for Aeronautical Research in Europe, this paper tackles the potential role of climate change levy schemes in achieving the ambitious objective of aviation decarbonization by the year 2050.