Search Results (1,554)

Urban school environments often face significant thermal discomfort due to extensive paved surfaces, limited vegetation, and outdated building designs. This study examines how green spaces can mitigate temperature extremes and improve thermal comfort at two secondary schools in Coimbra, Portugal: Escola Secundária José Falcão (ESJF) and Escola Secundária D. Dinis (ESDD). Using a mixed-methods approach that combined school community surveys with on-site microclimatic measurements, we integrated user feedback on comfort with data on temperature and humidity variations across different indoor and outdoor spaces. Results revealed that tree-shaded areas consistently maintained lower air temperatures and higher relative humidity than unshaded zones, which experienced intense heat accumulation—up to a 5 °C difference. At ESJF, the older infrastructure and large asphalt surfaces led to severe heat retention, with east-facing classrooms recording the highest indoor temperatures. ESDD’s pavilion-style layout and existing green spaces provided comparatively better thermal conditions, although insufficient vegetation maintenance and limited shade reduced their effectiveness. The findings demonstrate a clear correspondence between the school community’s perceptions of thermal comfort and the measured microclimatic data. Vegetation—particularly deciduous trees—plays a critical role in cooling the school microclimate through shading and evapotranspiration. Strategic interventions such as expanding tree cover in high-exposure areas, installing green roofs and walls, and carefully selecting species can significantly reduce temperature extremes and improve outdoor usability. In addition, fostering environmental education and participatory co-design programs can encourage sustainable behaviors within the school community, underlining the importance of inclusive, nature-based solutions for climate adaptation. This research highlights that integrating green infrastructure in school design and management is a cost-effective strategy for thermal regulation. Green spaces, when co-designed with community involvement, not only enhance climate resilience and student well-being but also contribute to broader sustainable urban development goals. Full article

This paper offers content priorities, justifications, and pedagogical approaches for the integration of climate change education into the training of teachers, and thus into public schooling. To meet urgent imperatives presented by the polycrisis of the Anthropocene, climate change education must be inclusive, comprehensive, flexible, and regionally responsive. Climate change education can be achieved by adapting regional programs for teacher education to meet those requirements. An example is the Climate Education in Teacher Education (CETE) project in northern British Columbia, Canada. Using the Education Design-Based Research methodology, the project addresses critical questions for curricular and pedagogical development of teachers to address the following three questions: (a) what content and outcomes to prioritize, (b) why these elements matter, and (c) how to implement them effectively. Over two years, CETE engaged pre-service and in-service teachers through workshops, reflective practices, and consultations with Indigenous communities. Our tentative answers emphasize the importance of adapting curriculum and pedagogy to foster community resilience, address climate anxiety, and promote an ethical renewal toward sustainability. The iterative development of objectives as “High-Level Conjectures” provides flexibility and reflexivity in the design process in the face of rapid contextual change. CETE developed practical pedagogical tools and workshop strategies that align educational priorities with local and global needs. This study offers a replicable framework to empower educators and communities in diverse locations to navigate the complexities of the climate crisis in their quest for a more secure and sustainable future. Full article

The integration of artificial intelligence (AI) into bioclimatic building design is reshaping the architecture, engineering, and construction (AEC) industry by addressing critical challenges in sustainability and efficiency. By aligning structures with local climates, bioclimatic design addresses global challenges such as energy consumption, urbanization, and climate change. Complementing these principles, AI technologies—including machine learning, digital twins, and generative algorithms—are revolutionizing the sector by optimizing processes across the entire building lifecycle, from design and construction to operation and maintenance. Amid the diverse array of AI-driven innovations, this research highlights digital twin (DT) technologies as a key to AI-driven transformation, enabling real-time monitoring, simulation, and optimization for sustainable design. Applications like façade optimization, energy flow analysis, and predictive maintenance showcase their role in adaptive architecture, while frameworks like Construction 4.0 and 5.0 promote human-centric, data-driven sustainability. By bridging AI with bioclimatic design, the findings contribute to a vision of a built environment that seamlessly aligns environmental sustainability with technological advancement and societal well-being, setting new standards for adaptive and resilient architecture. Despite the immense potential, AI and DTs face challenges like high computational demands, regulatory barriers, interoperability and skill gaps. Overcoming these challenges will be crucial for maximizing the impact on sustainable building, requiring ongoing research to ensure scalability, ethics, and accessibility. Full article

Forests are critical ecosystems that play a fundamental role in supporting biodiversity and maintaining climate stability. However, forest monitoring and exploration present huge challenges due to the vast scale and complex terrain. This paper proposes a novel bionic robot, PteroBot, designed to support a new paradigm for forest exploration inspired by the locomotion of Pteromyini. PteroBot is capable of regulating its gliding posture via a flexible membrane, enabling low-energy and low-disturbance mobility within forest environments. An adaptive gliding control system tailored to the robot’s structure is developed and its effectiveness is validated through aerodynamic analysis, simulation, and experimental testing. Results show that under a cascaded closed-loop attitude controller, PteroBot achieves an average glide ratio of 2.02 and demonstrates controllable turning via attitude modulation. Additionally, comparative tests with UAVs demonstrate that PteroBot offers significant advantages in energy efficiency and acoustic disturbance. Experimental outcomes confirm that PteroBot offers a biologically inspired and ecologically compatible solution for forest exploration, with strong potential in applications such as environmental monitoring, habitat assessment, and covert reconnaissance. Full article

Land degradation in Iraq’s Mesopotamian plain threatens food security and rural livelihoods, yet the relative roles of climatic water deficits versus anthropogenic pressures remain poorly attributed in space. We test the hypothesis that multi-timescale climatic water deficits (SPEI-03/-06/-12) exert a stronger effect on vegetation degradation risk than anthropogenic pressures, conditional on hydrological connectivity and irrigation. Using Babil and Al-Qadisiyah (2000–2023) as a case, we implement a four-part pipeline: (i) Fractional Vegetation Cover with Mann–Kendall/Sen’s slope to quantify greening/browning trends; (ii) LandTrendr to extract disturbance timing and magnitude; (iii) annual LULC maps from a Random Forest classifier to resolve transitions; and (iv) an XGBoost classifier to map degradation risk and attribute climate vs. anthropogenic influence via drop-group permutation (ΔAUC), grouped SHAP shares, and leave-group-out ablation, all under spatial block cross-validation. Driver attribution shows mid-term and short-term drought (SPEI-06, SPEI-03) as the strongest predictors, and conditional permutation yields a larger average AUC loss for the climate block than for the anthropogenic block, while grouped SHAP shares are comparable between the two, and ablation suggests a neutral to weak anthropogenic edge. The XGBoost model attains AUC = 0.884 (test) and maps 9.7% of the area as high risk (>0.70), concentrated away from perennial water bodies. Over 2000–2023, LULC change indicates CA +515 km², HO +129 km², UL +70 km², BL −697 km², WB −16.7 km². Trend analysis shows recovery across 51.5% of the landscape (+29.6% dec⁻¹ median) and severe decline over 2.5% (−22.0% dec⁻¹). The integrated design couples trend mapping with driver attribution, clarifying how compounded climatic stress and intensive land use shape contemporary desertification risk and providing spatial priorities for restoration and adaptive water management. Full article

As climate action becomes increasingly urgent, nations and institutions worldwide seek advanced technologies for practical mitigation efforts. This study examines how agentic artificial intelligence systems capable of decision-making and learning from experience drive innovation dynamics in climate change mitigation, with a particular focus on ethical considerations during the net-zero transition. The current urgency of climate action demands advanced technologies, yet organisations struggle to effectively deploy agentic AI for climate mitigation due to unclear implementation pathways and ethical consideration. This study examines the relationships among agentic AI capabilities, innovation dynamics, and net-zero transition performance, using survey data from 340 organisations across the manufacturing, energy, and technology sectors, and analysed using structural equation modelling. Based on dynamic capabilities theory, this research proposes a novel theoretical model that examines how agentic AI drives innovation dynamics in climate change mitigation within governance frameworks that encompass transparency, accountability, and environmental justice. Results reveal significant mediation effects of innovation dynamics, dynamic capabilities, and ethical considerations, while environmental context negatively moderates innovation and ethical pathways. Findings suggest that overly restrictive ethical considerations can lead to implementation delays that undermine the urgency of climate action. This study proposes three solutions: (1) adaptive ethical protocols adjusting governance intensity based on climate risk severity, (2) pre-approved ethical templates reducing approval delays by 60%, and (3) stakeholder co-design processes building consensus during development. The research advances dynamic capabilities theory for AI contexts by demonstrating how AI-enabled sensing, seizing, and reconfiguring capabilities create differentiated pathways to climate performance. This study provides empirical validation of the responsible innovation framework, identifies asymmetric environmental contingencies, and offers evidence-based guidance for organisations implementing agentic AI for climate action. Full article

China’s dual carbon goals necessitate green transformation across industries, with STAR Market enterprises serving as crucial drivers of technological innovation. Existing studies predominantly focus on traditional sectors, overlooking dynamic policy interactions and structural heterogeneity in these technology-intensive firms. This study examines how coordinated environmental tax reforms, green finance initiatives, and equity network synergies collectively shape enterprise green transition, using multi-period difference-in-differences and triple-difference models across 2019 Q3–2023 Q4. By integrating financial records, patent filings, and carbon emission data from 487 STAR Market firms, the analysis identifies environmental cost pressures as the dominant policy driver, complemented by delayed financing incentives and accelerated resource integration through corporate networks. Regional institutional environments further modulate these effects, with areas implementing stricter tax reforms exhibiting stronger outcomes. The findings advocate for adaptive policy designs that align fiscal instruments with regional innovation capacities, optimize financial tools for technology commercialization cycles, and leverage inter-firm networks to amplify sustainability efforts. These insights contribute to refining China’s climate governance framework for emerging technology sectors. Full article

The building sector plays a key role in the transition toward climate neutrality, with national regulations across the EU requiring the construction of nearly zero-energy buildings (nZEBs). However, while energy performance has been extensively studied, less attention has been given to the problem of ensuring user comfort—both indoors and in the surrounding outdoor areas—under nZEB design constraints. This gap raises two key research objectives: (1) to evaluate whether a well-designed nZEB with extensive glazing maintains acceptable indoor thermal comfort and (2) to assess whether residents experience greater outdoor thermal comfort and satisfaction in small, sun-exposed private gardens or in larger, shaded communal green spaces. To address these objectives, a newly built residential estate near Kraków (Poland) was analyzed. The investigation included simulation-based assessments during the design phase and in situ measurements during building operation, complemented by a user survey on spatial preferences. Indoor comfort was evaluated for rooms with large glazed façades, as well as rooms with standard-sized windows, while outdoor comfort was assessed in both private gardens and a shared green courtyard. Results show that shading the southwest-oriented glazed façade with an overhanging terrace provided slightly lower temperatures in ground-floor rooms compared to rooms with standard unshaded windows. Outdoors, users experienced lower thermal comfort in small, unshaded gardens than in the larger, vegetated communal area (pocket park), which demonstrated greater capacity for temperature moderation and thermal stress reduction. Survey responses further indicate that potential future residents prefer the inclusion of a shared green–blue infrastructure area, even at the expense of building some housing units in semi-detached form, instead of maximizing the number of detached units with unshaded individual gardens. These findings emphasize the importance of addressing both indoor and outdoor comfort in residential nZEB design, showing that technological efficiency must be complemented by user-centered design strategies. This integrated approach can improve the well-being of residents while supporting climate change adaptation in the built environment. Full article

Mountain regions are increasingly affected by the interplay of climate change, infrastructure stress, and evolving socio-ecological systems, intensifying pressure on both water and energy systems. This systematic review investigates how recent scientific literature addresses the management and integration of water and energy systems in mountainous contexts. Following PRISMA guidelines, 88 peer-reviewed studies from 2022 to 2025 were selected through structured database queries and thematic screening. Two key imbalances emerge. First, a geographical imbalance is evident: while the majority of studies come from Asia, Europe shows a strong record of applied efforts, the Americas are moderately represented, and research from Africa remains scarce. Second, a thematic imbalance: water management research is conceptually and methodologically mature, while energy-focused studies remain limited in number and scope. Efforts toward integrated water–energy management are emerging but are mostly confined to pilot projects or modelling exercises, often lacking systemic framing and institutional support. From these findings, three priority directions are identified: advancing adaptive co-design approaches that link water supply, energy storage, ecological flows, and human demand; harmonizing methods, metrics and cross-regional benchmarks to enhance comparability and transferability; strengthening social and institutional pathways to foster resilient, adaptive water–energy systems in mountain environments. Full article

The increasing frequency and severity of natural disasters—such as floods, storms, droughts, and earthquakes—have created a growing demand for temporary housing. These facilities must be rapidly deployed to provide safe, functional living environments for displaced individuals. This study proposes a design methodology for temporary housing exteriors using the text-to-image capabilities of generative artificial intelligence (GenAI) to address urgent post-disaster housing needs. The approach aims to improve both the efficiency and practicality of early-stage design processes. The study reviews global trends in temporary housing and the architectural applications of GenAI, identifying five key environmental factors that influence design: type of disaster, location and climate, duration of residence, materials and structure, and housing design. Based on these factors, hypothetical disaster scenarios were developed using ChatGPT, and corresponding exterior designs were generated using Stable Diffusion. The results show that diverse, scenario-specific design alternatives can be effectively produced using GenAI, demonstrating its potential as a valuable tool in architectural planning for disaster response. Expert evaluation of the generated designs confirmed their ability to adhere to text prompts but revealed a significant gap in terms of architectural plausibility and practical feasibility, highlighting the essential role of expert oversight. This study offers a foundation for expanding GenAI applications in emergency housing systems and supports the development of faster, more adaptable design solutions for communities affected by natural disasters. Full article

The interconnection between health and environment is increasingly recognised, as is the role of healthcare professionals in raising awareness among patients and healthcare policymakers. To explore the relevance of enhancing patients’ awareness of the links between health and environment in ambulatory care, we conducted a qualitative study on General Practitioner (GP) practices in Switzerland. Using a co-benefit approach, we designed materials on meat consumption and active mobility, which were displayed in the waiting rooms. We conducted observations in five practices and interviewed five patients and five GPs to examine patients’ understanding of the messages and assess the acceptability of discussing them during medical encounters. Patients and GPs were receptive to the co-benefit approach. However, barriers were identified in promoting co-benefits during clinical encounters, including time constraints and lack of knowledge. Patients showed reactance to the messages and questioned the reliability of messages related to climate change. GPs were reluctant to compromise relationships with patients and were ambivalent, viewing environmental discussions as political. Positive message display and community promotion were identified as facilitators. This study highlights the need to develop clear educational materials to support GPs, to adapt messages to patients’ backgrounds, and to address the dichotomy between GPs’ political and scientific perspectives. Full article

This paper presents a novel model for the year-round simulation of evapotranspiration (ET) and substrate temperature on two fundamentally different extensive green roof types: a conventional drainage-based “Economy Roof” and a retention-optimized “Retention Roof” featuring capillary water redistribution. The main scope is to bridge the gap in urban climate adaptation by providing a modeling tool that captures both hydrological and thermal functions of green roofs throughout all seasons, notably including periods with dormancy and low vegetation activity. A key novelty is the explicit and empirically validated integration of core physical processes—water storage layer coupling, explicit rainfall interception, and vegetation cover dynamics—with the latter strongly controlled by plant area index (PAI). The PAI, here quantified as the plant surface area per unit ground area using digital image analysis, directly determines interception capacity and vegetative transpiration rates within the model. This process-based representation enables a more realistic simulation of seasonal fluctuations and physiological plant responses, a feature often neglected in previous green roof models. The model, which can be fully executed without high computational power, was validated against comprehensive field measurements from a temperate climate, showing high predictive accuracy (R² = 0.87 and percentage bias = −1% for ET on the Retention Roof; R² = 0.91 and percentage bias = −8% for substrate temperature on the Economy Roof). Notably, the layer-specific coupling of vegetation, substrate, and water storage advances ecological realism compared to prior approaches. The results illustrate the model’s practical applicability for urban planners and researchers, offering a user-friendly and transparent tool for integrated assessments of green infrastructure within the context of climate-resilient city design. Full article

Civil engineering today faces the challenge of responding to climate change, rapid urbanization, and the need to reduce environmental impacts. These factors drive the search for more sustainable approaches and the adoption of digital technologies. This article addresses three principal dimensions: advanced low-impact materials, resilient structural designs, and digital tools applied throughout the infrastructure life cycle. To this end, a systematic search was conducted considering studies published between 2020 and 2025, including both experimental and review works. The results show that materials such as geopolymers, biopolymers, natural fibers, and nanocomposites can significantly reduce the carbon footprint; however, they still face regulatory, cost, and adoption barriers. Likewise, modular, adaptable, and performance-based design proposals enhance infrastructure resilience against extreme climate events. Finally, digital tools such as Building Information Modeling, digital twins, artificial intelligence, the Internet of Things, and 3D printing provide improvements in planning, construction, and maintenance, though with limitations related to interoperability, investment, and training. In conclusion, the integration of materials, design, and digitalization presents a promising pathway toward safer, more resilient, and sustainable infrastructure, aligning with the Sustainable Development Goals and the concept of smart cities. Full article

This study develops an integrated drought assessment framework based on trivariate copula modeling to simultaneously evaluate three key drought characteristics: duration, severity, and peak intensity. Meteorological data from stations across 23 meteorological stations in Northeastern Thailand, covering the period of 2007–2025, were analyzed. The Standardized Precipitation–Evapotranspiration Index (SPEI) was employed to characterize multidimensional drought conditions. The trivariate copula approach provides a flexible and robust statistical framework, enabling the separation of marginal distributions from dependence structures, capturing nonlinear and tail dependencies more effectively than traditional methods. Results demonstrate that this modeling framework significantly improves the accuracy of drought risk estimation and enables the calculation of joint return periods for extreme drought events. These findings offer valuable insights with respect to designing adaptive water resource management strategies, enhancing agricultural resilience, and strengthening early warning systems under future climate variability. Full article

Climate change is increasingly affecting the aquaculture sector, particularly in estuarine systems that support high-value production. In the Galician Rías Baixas, where shellfish farming is a cornerstone of the coastal economy, rising sea temperatures, sea-level rise, and changing precipitation patterns pose significant risks to mussel aquaculture. This study presents a spatially explicit Aquaculture Suitability Similarity Index (ASI) designed to identify alternative cultivation areas that replicate the environmental and logistical characteristics of historically successful mussel farms. The ASI integrates a set of environmental variables (water temperature, salinity, biogeochemical quality, current velocity, and wave height) and technical constraints (depth and distance to port), with factor weights derived via expert elicitation using the Delphi method. Results show that most waters are highly similar to current farming areas, suggesting strong potential for spatial expansion or relocation. In contrast, areas near the mouths of the rías and the adjacent continental shelf show lower suitability due to greater oceanic exposure and associated logistical challenges. The ASI provides a robust, transferable tool to inform aquaculture spatial planning and climate adaptation strategies. Its methodological framework can be adapted to other regions and species, supporting evidence-based decision-making for sustainable aquaculture development. Full article