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This study assesses the relationship between economic performance and environmental sustainability by taking into account the role of energy consumption, urbanization, and trade openness in Brazil by using data spanning from 1965 to 2019. The study is distinct from previously documented studies in literature in terms of scope for Brazil, where few entries have been recorded. The major objectives are to address the questions: (a) Is there a long-run connection between the variables under consideration? (b) Can CO2 emissions, trade openness, and energy consumption predict economic performance of Brazil? (c) What is the connection between economic growth and the independent variables at different frequencies and time-period? Furthermore, the study utilized dynamic ordinary least square (DOLS), fully modified ordinary least square (FMOLS), Maki Cointegration, and autoregressive distributed lag (ARDL) to capture the long-run association between the variables of interest. Also, we used the Wavelet coherence and Gradual-shift causality tests to capture the causal linkage between economic growth and the regressors. The advantage of the wavelet coherence test is that it can capture causal linkage between series at different frequencies and periods. The outcome of both Maki cointegration and ARDL bounds testing to cointegration affirms the presence of long-run interaction among the parameters of interest. Furthermore, the outcomes of the DOLS and FMOLS revealed that energy consumption, CO2 emissions, and urbanization exert positive impacts on economic growth in Brazil while there is no significant connection between trade openness and economic growth. Moreover, Gradual shift causality test outcomes disclosed that urbanization, trade openness, CO2 emissions and energy usage can predict the economic performance of Brazil. The outcomes of the wavelet coherence test give credence to the FMOLS, DOLS, and Gradual shift causality tests.

The paper analyses the sustainable development of tourism in selected cities located in Turkey and in Poland. The starting point for the conducted research was the adoption of indicators used to assess the sustainable development of tourism in the cities of Amasya (Turkey) and Zakopane (Poland). Ultimately, the authors used slightly modified indicators developed by the Voluntary Initiative for Sustainability in Tourism (VISIT). The studies demonstrated that in Amasya the development of tourism is quite stable and revealed quite a lot of deficiencies in Zakopane. Sustainable development was assessed as poor in terms of environmental obligations, in particular waste water management solutions and municipal waste management as well as in terms of water consumption. The research revealed that some of the indicators were not recorded in central statistical offices, which hindered the assessment considerably. This refers mainly to indicators related to social and cultural considerations. In general, the results are rather surprising, as the analysis revealed significant differences in the development of technological infrastructure and land use intensity. Unfortunately, in these aspects, Zakopane seems to have lost the competition.

The scope of the paper is to overview the different approaches for evaluation of urban infrastructure sustainability. In this context, urban infrastructure covers transportation, energy, water, sewage and information networks as well as waste management and blue-green infrastructure, in terms of both the supply and demand side. A common effort of partners in the European project “C8—Best Practice in Sustainable Urban Infrastructure”, developed under the Cooperation in Science and Technology program (COST), in brief COST C8, was focused on defining the methods, indicators and criteria for evaluation of sustainability, and resulted in a guidebook for decision-makers in local authorities. Here, the COST C8 matrix for simple sustainability assessment of urban infrastructure is applied to The Path (POT) case—a circular memorial and recreational park around the city of Ljubljana, Slovenia. The applicability and acceptance of the matrix in 43 other cases of sustainable urban infrastructure, collected in the COST C8 project, is presented and discussed.

Mountainous basins are frequently called “natural water towers” because they supply essential water to downstream regions for irrigation, industrial–municipal use, and hydropower generation. The possible implications of climate change on water supplies have gained prominence in recent years, particularly in snow-dominated mountainous basins. The Euphrates River, a snow-fed transboundary river that originates from the Eastern part of Türkiye with several large dam reservoirs downstream, was chosen within this scope. The study reveals the impact of climate change on two snow-dominated headwaters, namely Karasu and Murat, which have a basin area of 41,109 km2. The impact of climate change is assessed across runoff regimes and snow dynamics for future periods (2024–2099). Global Climate Model (GCM) data sets (CNRM-CM5, IPSL-CM5A, EC-EARTH, MPI-ESM-LR, NorESM1-M, HadGEM2-ES) were downscaled by Regional Circulation Models (RCMs), provided from CMIP5 EURO-CORDEX domain for climate projections under RCP4.5 and RCP8.5 scenarios. Future projections of runoff and snow variables are predicted by two conceptual hydrological models, HBV and HEC-HMS. The results indicate a dramatic shrink in snow cover extents (>65%) and snow duration (25%), a decrease in snow water equivalent (>50%), and a timely shift (up to a month) in peak runoff through early spring in the runoff hydrograph for the last future period (2075–2099). The overall assessment shows that operations of downstream water systems should be reconsidered for future changes.

The COVID-19 pandemic has led to major disruptions in workflows across all industries. All sectors are trying to sustain operations during this extremely difficult time and the healthcare sector is the most important of them. It is unthinkable to stop the operations of the health system because it serves human life. Health institutions must supply the products such as masks, gloves, and ventilators subject to service on time for certain activities to continue indefinitely under all conditions. By adopting modern logistics activities and technologies, healthcare organizations can provide sustainable diagnosis and treatments to patients by automating their various operations. With the COVID-19 pandemic, how to select an appropriate sustainable supplier has become an important task in the era of Logistics 4.0. From this viewpoint, a sustainable supplier selection framework is implemented for a health institution under the effect of the pandemic. To determine the direct effects of the pandemic in the health sector, fuzzy Multi-Criteria Decision-Making (MCDM) methods are utilized in the application. After a thorough review of the literature and interviews with experts, the criteria are organized in a comprehensive hierarchical structure. The fuzzy Best-Worst Method (F-BWM) technique is employed to find the weights for the determined criteria. Consequently, the fuzzy Additive Ratio Assessment Method (F-ARAS) method was applied to rank the alternative suppliers. In addition, with a comprehensive sensitivity analysis, alternative situations are examined against possible breaks in the supply chain. Thus, from the perspective of Logistics 4.0 and sustainability, this study contributes to the literature with an analysis of the health system’s survival in difficult and fragile periods, such as COVID-19. Investigating the importance of SSS can be a road map for the policymakers and the decision-makers is beneficial since the impact of COVID-19 on SSS is studied from the perspective of Logistics 4.0.

The transportation of oil and gas through pipelines is an integral aspect of the global energy infrastructure. It is crucial to ensure the safety and integrity of these pipelines, and one way to do so is by utilizing an inspection tool called a smart pig. This paper reviews various smart pigs used in steel oil and gas pipelines and classifies them according to pipeline structure, anomaly-detection capability, working principles, and application areas. The advantages and limitations of each sensor technology that can be used with the smart pig for in-line inspection (ILI) are discussed. In this context, ultrasonic testing (UT), electromagnetic acoustic transducer (EMAT), eddy current (EC), magnetic flux leakage (MFL), and mechanical contact (MC) sensors are investigated. This paper also provides a comprehensive analysis of the development chronology of these sensors in the literature. Additionally, combinations of relevant sensor technologies are compared for their accuracy in sizing anomaly depth, length, and width. In addition to their importance in maintaining the safety and reliability of pipelines, the use of ILI can also have environmental benefits. This study aims to further our understanding of the relationship between ILI and the environment.

Biological invasions have posed a major threat to global and regional biodiversity. The Mediterranean Sea, one of the major biodiversity hotspots in the world, has long suffered multiple and frequent invasion events. This paper represents the screening results of the potential invasiveness of 23 introduced marine fish species, which are classified as neonative and alien. To predict the invasiveness potential of species under current and predicted climate conditions, the Aquatic Species Invasiveness Screening Kit (AS-ISK) is applied. Thresholds have been constituted to classify low, medium and high-risk species by receiver operative characteristic curve analysis (ROC). The calibrated basic and climate-change threshold assessment scores used to classify species from low, to medium to high risk were computed between 27.5 and 33.0 respectively. Based on these thresholds, under current climatic conditions, 15 species were high risk, while the remaining species were medium risk, and the Chaetodipterus faber and the Holocentrus adscensionis switched from the medium-risk to the high-risk group under future climatic conditions. The highest score belonged to Fistularia petimba, followed by Siganus fuscescens, Abudefduf spp., Acanthurus monroviae and Lutjanus argentimaculatus. This study focused on the species that have not been assessed for their invasiveness potential, and the results can provide important insights into their sustainable management in the future.