In a climate change scenario where extreme precipitation events occur more frequently and intensely, risk assessment plays a critical role in ensuring the safety and operational efficiency of facilities. This case study uses a combination of the multi-criteria analysis approach and hydrological studies that use machine learning algorithms to simulate new rainfall events in order to estimate the risk of flooding on railroads. Risk variables, including terrain, drainage capability, accumulated flow, and land use and land cover, will be weighed using the multicriteria approach. A methodical evaluation of the most vulnerable locations on the railroad network will be possible thanks to the analysis of these parameters based on the geographic information system (GIS) approach. In the meantime, historical precipitation, flow, and hydrological balance data will be used to calibrate and validate hydrological models. The database required for the machine learning model can be created with these hydrological data. The research regions are situated in the densely rail-networked state of Minas Gerais. The geographical and climatic diversity of Minas Gerais makes it the perfect place to test and validate the suggested approaches. The models evaluated included linear regression, random forest, decision tree, and support vector machines. Among the evaluated models, Linear Regression emerged as the best-performing model with an R² value of 0.999998, a mean squared error (MSE) of 0.018672, and a low tendency to overfitting (0.000011).

The increasing global demand for a more sustainable economy is propelling the exploration of alternatives to conventional practices. The adoption of a hydrogen production and distribution system is gaining global consensus, driven by its lower environmental impact compared to fossil fuels. This study delves into the feasibility of renewable hydrogen, sourced from avenues like solar and wind power, particularly in the realm of sustainable urban transportation. The urgency for innovative technologies, underscored by emissions targets and sustainable development goals, positions hydrogen as a promising solution with superior calorific value and reduced emissions. Nonetheless, formidable challenges, including limited infrastructure and the requirement for substantial investment, pose significant hurdles to its widespread adoption. The pertinence of this study is further emphasized by the necessity to continually update the literature, ensuring alignment with the dynamic developments in this field.

This study examines the integration of epistemological principles into road infrastructure risk management, emphasizing the need for adaptive strategies in the face of inherent climate uncertainties, particularly flash floods. A systematic review of peer-reviewed articles, industry reports, and case studies from the past two decades was conducted, focusing on the application of epistemological approaches within the infrastructure sector. The research employs a mixed methods approach. Quantitatively, the risk of pavement failure is measured by analyzing the relationship between pavement serviceability rates and Intensity–Duration–Frequency (IDF) data in areas frequently affected by flash floods. For example, rainfall intensities during flood events on the BR-324 highway in Brazil were significantly higher than monthly averages, with maximum values reaching 235.73 mm for a 5 min duration over a 50-year return period. These intensities showed an increase of approximately 15% over 5 to 10 years and 8% over 50 to 75 years. Qualitatively, traditional risk management methods are combined with epistemological concepts. This integrated approach fosters reflective practice, encourages the use of both quantitative and qualitative data, promotes a dynamic management environment, and supports sustainable development goals by aligning risk management with environmental and social sustainability. This study finds that incorporating epistemological insights can lead to more fluid and continuously improving risk management practices in construction, design, and maintenance. It concludes with a call for future research to explore the integration of emerging technologies such as artificial intelligence to further refine these approaches and more effectively manage complexity and uncertainty.

RESUMO O Brasil se destaca como um dos maiores produtores de minérios do mundo. No entanto, essa atividade tão importante economicamente também acarreta danos significativos ao meio ambiente. O problema da disposição dos rejeitos de mineração em barragens ganhou grande repercussão após os desastres em Mariana, em 2015, e Brumadinho, em 2019, que evidenciou a necessidade de encontrar um novo uso para esses materiais. A pesquisa teve como principal objetivo avaliar a adição de rejeitos de minério de ferro em materiais utilizados nas camadas de pavimentos rodoviários, na produção de solo-cimento. Os resultados dos ensaios mecânicos mostraram que é tecnicamente viável adicionar rejeito de minério de ferro nas misturas de solo-cimento, sendo que, para camada de base, foi encontrado o teor mínimo de 6% de cimento, e de 5% e 4% para a camada de sub-base. Isso indica que o rejeito pode ser uma excelente alternativa para reduzir o consumo de cimento. Além disso, essa incorporação poderia reduzir o consumo de recursos naturais, oferecer um destino alternativo para os rejeitos de mineração e até mesmo diminuir os custos das obras de pavimentação. Com essa pesquisa, busca-se uma solução inteligente e sustentável para os impactos causados pelos rejeitos de mineração no Brasil.

Climate change poses substantial challenges to the transportation sector due to its high vulnerability to adverse weather conditions and extreme events, which directly impact infrastructure longevity and operational safety. This study examines the critical need to integrate climate considerations into the planning and execution of transportation infrastructure projects through comprehensive and methodologically rigorous Climate Risk Analysis (CRA). Various CRA methodologies are analyzed, highlighting their advantages and limitations, as well as the importance of an integrated approach that encompasses resilience, sustainability, and climate justice. The study also discusses the economic impacts of adaptation strategies and explores the challenges and opportunities developing countries face. The research concludes that a holistic and adaptive approach is essential to addressing the complex challenges posed by climate change to the transportation sector, promoting risk mitigation and sustainable and inclusive adaptation.