Departamento de Ciências da Engenharia e da Arquitectura
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Percorrer Departamento de Ciências da Engenharia e da Arquitectura por Objetivos de Desenvolvimento Sustentável (ODS) "09:Indústria, Inovação e Infraestruturas"
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- The 15-minute city in Porto, Portugal: accessibility for the elderlyPublication . Guerreiro, Maria; Dinis, Maria Alzira Pimenta; Sucena, Sara; Pereira, Madalena Sofia Araujo; Silva, Isabel; Ferreira, Diogo; Silva Moreira, RuiThe concept of the 15-Minute City aims to enhance urban accessibility by ensuring that essential services are within a short walking distance. This study evaluates the accessibility of Porto, Portugal, particularly for the elderly, by assessing urban density, permeability, and walkability, with a specific focus on crossings and ramps. A five-step methodology was employed, including spatial analysis using QGIS and Place Syntax Tool, proximity assessments, and an in-situ survey of crossings and ramps in the CHP. The results indicate that while the city of Porto offers a dense and walkable urban environment, significant accessibility challenges remain due to inadequate ramp distribution. The data collection identified 80 crossings, of which only 60 were listed in OpenStreetMap, highlighting data inconsistencies. Additionally, 18 crossings lacked curb ramps, posing mobility barriers for elderly residents. These findings highlight the need of infrastructure improvements to support inclusive urban mobility. The study also proposes an automated method to enhance ramp data collection for broader applications. Addressing these gaps is crucial for achieving the equity and sustainability goals of the 15-Minute City model, ensuring that aging populations can navigate urban spaces safely and efficiently.
- Sustainable generative AI and quantum computing: review assessment on the environmental impact of generative AI and quantum technologiesPublication . Esho, Esther Oreofeoluwa; Akinyelu, Andronicus Ayobami; Dinis, Maria Alzira PimentaThe rapid advancement of Generative Artificial Intelligence (GenAI) and Quantum Computing (QC) presents transformative opportunities, yet their high computational requirements raise concerns about their environmental sustainability. This comprehensive review examines the ecological footprint of both technologies, focusing on key metrics like energy consumption, carbon emissions, and resource depletion. Findings from existing studies consistently indicate that the impact of GenAI is mostly driven by the immense energy demands of large-scale model training and inference. Moreover, findings from the review reveal that the footprint of QC largely stems from the energy-intensive cryogenic cooling and rare material requirements of its specialized hardware. This paper benchmarks current approaches to environmental assessment, highlighting the important role of Life Cycle Assessment (LCA) in providing a holistic view of the classification of environmental impacts across the entire supply chain, from manufacturing to disposal. This study proposes a range of domain-specific mitigation strategies, including algorithmic optimizations like pruning and distillation for AI, and cryogenic and material sourcing improvements for quantum systems. This study also proposes a framework for proactive, responsible innovation and identifies some gaps in the literature, such as the lack of standardized metrics and transparent reporting. There is a need to embed eco-conscious principles in the design of future technologies and highlight opportunities where these technologies can be used to handle broader climate challenges. The findings in this study can be used by policymakers, researchers, and industry stakeholders in aligning technological progress with global climate and sustainability goals.