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Environmental risks, in particular climate change and environmental pollution, are among the key challenges faced by modern governments nowadays. Environmental risks are associated with specific costs and expenditures necessary to mitigate their negative effects. In this context, the financial system plays a significant role, particularly the public financial system, which allocates and redistributes public resources and has an impact on market participants by imposing environmental taxes. This study assessed the interdependence between environmental degradation and public expenditure, financial sector development, environmental taxes, and related socioeconomic policies. The aim was to diagnose and define the relationship between environmental degradation and sustainable fiscal instruments used in the financial system. The original research approach adopted in the study is the inclusion of variables representing a sustainable approach to assessment of the financial system. Two groups of European Union countries were analyzed for the period 2008–2017, namely, converging economies from Central and Eastern Europe and the largest developed economies of Western Europe. The authors found a strong relationship between greenhouse gas emissions and fiscal instruments, especially expenditure on research and development, and the development of the financial sector. In the case of environmental taxes, their impact differed depending on the country, being predominantly beneficial in countries with higher greenhouse gas emissions but unfavorable in countries with lower emissions levels.

The Single Europe Sky Air Traffic Management Research (SESAR) program develops and implements innovative technological and operational solutions to modernize European air traffic management and to eliminate the negative environmental impacts of aviation activity. This article presents our developments within the SESAR Solution &ldquo, Safety Support Tools for Avoiding Runway Excursions&rdquo, This SESAR Solution aims to mitigate the risk of runway excursion, to optimize airport operation management by decreasing the number of runway inspections, to make chemical treatment effective with respect to the environment, and to increase resilience, efficiency and safety in adverse weather situations. The proposed approach is based on the enhancement of runway surface condition awareness by integrating data from various sources. Dangerous windy conditions based on Lidar measurements are also discussed as another relevant factor in relation to runway excursions. The paper aims to explore four different data mining methods to obtain runway conditions from the available input data sources, examines their performance and discusses their pros and cons in comparison with a rule-based algorithm approach. The output of the SESAR Solution is developed in compliance with the new Global Reporting Format of the International Civil Aviation Organization for runway condition description to be valid from 2020. This standard is expected to provide concerned stakeholders with more precise information to enhance flight safety and environmental protection.

The purpose of this paper is to develop a fuzzy model of the risk assessment for environmental start-up projects in the air transport sector at the stage of business expansion. The model developed for the following software will be a useful tool for the risk decision support system of investment funds in financing environmental start-up projects at the stage of market conquest. Developing a quantitative risk assessment for environmental start-up projects for the air transport sector will increase the resilience of making risk decisions about their financing by the investors. In this paper, a set of 21 criteria for assessing the risk of launching environmental start-up projects in the air transport sector were formulated for the first time by presenting inputs in the form of a linguistic risk assessment and the number of credible expert considerations. The fuzzy risk assessment model, based on expert knowledge, uses linguistic variables, reveals the uncertainty of the input data, and displays a risk assessment with linguistic interpretation. The result of the paper is a fuzzy model that is embedded in a generalized algorithm and tested in an example risk assessment of environmental start-up projects in the air transport sector.

The article presents an assessment of the long-term variability of storm activity in the aspect of potential threats to aircraft. The analysis of data from the period 1970−2018 was conducted for selected airports in Poland: Gdańsk Lech Wałęsa Airport, IATA code: GDN, ICAO code: EPGD (54°22′39″N 18°27′59″E, altitude above sea level 149 m above sea level); Solidarity Szczecin- Goleniow Airport, IATA code: SZZ, ICAO code: EPSC (53°35′05″ N 14°54′08″ E, altitude above sea level 47 m above sea level); Poznań-Ławica Henryk Wieniawski Airport, IATA code: POZ, ICAO code: EPPO (52°25′16″ N 16°49′35″ E, altitude above sea level 94 m above sea level); Warsaw Chopin Airport, IATA code: WAW, ICAO code: EPWA (52°09′57″ N 20°58′02″ E, altitude above sea level 110 m above sea level); Copernicus Airport Wrocław, IATA code: WRO, ICAO code: EPWR (51°06′10″ N 16°53′10″ E, altitude above sea level 123 m above sea level); John Paul II International Airport Kraków-Balice, IATA code: KRK, ICAO code: EPKK (50°04′40″ N 19°47′06″ E, altitude above sea level 241 m above sea level). The purpose of this paper is to assess the long-term variability of storm activity in the aspect of potential threats to air operations in Poland with the examples of six selected airports. In order to achieve the goal, an analysis of the frequency of storm phenomena in Poland was carried out both in annual and long- term terms. The analysis will allow the assessment of the geographical diversity of the distribution of storm phenomena and their variability in the years 1970−2018. The next stage of the work will be to determine the climatic conditions that exert the greatest impact on the formation of storms. The important factors include atmospheric circulation, which, over the Polish territory, is shaped by the influence of air masses from the Atlantic Ocean, the Baltic Sea and in addition, from the vast continental area. All these air masses clash over the area of Poland causing large variability in the frequency of occurrence of hazardous atmospheric phenomena. For this reason, the Polish climate is defined as a moderate warm climate with transitory features. The important factors affecting regional diversity are local conditions, such as terrain, nature of the land, and distance from water reservoirs. The thermal, humidity and aerodynamic properties of the substrate, which are components of radiation processes, determine the exchange of energy at the interface between the atmosphere and the earth, and largely determine the intensity of selected hazardous atmospheric phenomena. Each occurrence of a storm is a potentially dangerous meteorological event that threatens the environment and human activities, including all types of transport. The studied phenomenon of storms is particularly dangerous for air transport. Literature shows that storm phenomena in Poland are characterized by a large regional diversity, both during the year and over many years. The greatest threat of storm phenomena occurs in the warm period of the year—spring and summer.

The purpose of this paper is to develop an applied fuzzy model of information technology to obtain quantitative estimates of environmental start-up projects in air transport. The developed model will become a useful tool for venture funds, business angels, or crowdfunding platforms for the development of innovative air transport businesses. Obtaining a quantitative estimate of the environmental start-up projects will increase the sustainability of the decision making on the security of financing of such projects by investors. This article develops a fuzzy evaluation model of project start-ups in air transport as an application of our neuro-fuzzy model in a specific air transport environment. The applied model provides output ranking of start-up project teams in air transport based on a four-layer neuro-fuzzy network. The presented model declares the possibilities of the application to solve these economic problems and offers the space for subsequent research focused on its usability in several areas of start-up development, in sectors and processes differentiated. The benefits are also visible for several types of policies, with an emphasis on decision-making processes in regulatory mechanisms to support the state funding in Slovakia, the EU etc.

Low-level wind shear, i.e., sudden changes in wind speed and/or wind direction up to altitudes of 1600 ft (500 m) above-ground is a hazardous meteorological phenomenon in aviation. It may radically change the aerodynamic circumstances of the flight, particularly during landing and take-off and consequently, it may threaten human lives and the health of passengers, people at the airport and its surrounding areas. The Bratislava Airport, the site of this case study, is one of the few airports worldwide and the first in Central Europe that is equipped with a Doppler lidar system, a perspective remote sensing tool for detecting low-level wind shear. The main objective of this paper was to assess the weather events collected over a period of one year with the occurrences of low-level wind shear situations, such as vertical discontinuities in the wind field, frontal passages and gust fronts to increase the level of flight safety and protect human lives and health. The lidar data were processed by a computer algorithm with the main focus on potential wind shear alerts and microburst alerts, guided by the recommendations of the International Civil Aviation Organisation. In parallel, the selected weather events were analyzed by the nearby located meteorological radar to utilize the strengths of both approaches. Additionally, an evaluation of the lidar capability to scan dynamics of aerosol content above the airport is presented.

The main objective of the presented study was to examine the associations between the use of renewable energy sources in selected sectors (transport, electricity, heating, and cooling) and the prevalence of selected groups of diseases in the European Union, with an emphasis on the application of statistical methods considering the structure of data. The analyses included data on 27 countries of the European Union from 2010 to 2019 published in the Eurostat database and the Global Burden of Disease Study. Panel regression models (pooling model, fixed (within) effects model, random effects model) were primarily used in analytical procedures, in which a panel variable was represented by countries. In most cases, positive and significant associations between the use of renewable energy sources and the prevalence of diseases were confirmed. The results of panel regression models could be generally interpreted as meaning that renewable energy sources are associated with the prevalence of diseases such as cardiovascular diseases, diabetes and kidney diseases, digestive diseases, musculoskeletal disorders, neoplasms, sense organ diseases, and skin and subcutaneous diseases at a significance level (α) of 0.05 and lower. These findings could be explained by the awareness of the health problem and the response in the form of preference for renewable energy sources. Regarding statistical methods used for country data or for data with a specific structure, it is recommended to use the methods that take this structure into account. The absence of these methods could lead to misleading conclusions. © 2021 by the authors. Licensee MDPI, Basel, Switzerland., Slovak Research and Development AgencySlovak Research and Development Agency [APVV-17-0166]; Internal Grant Agency of FaME Tomas Bata University in Zlin [RO/2020/05], Agentúra na Podporu Výskumu a Vývoja, APVV: APVV-17-0166; Univerzita Tomáše Bati ve Zlíně: RO/2020/05