Search Results (8,315)

This study introduces a comprehensive framework combining building information modeling (BIM), project management body of knowledge (PMBOK), and machine learning (ML) to optimize energy efficiency and reduce environmental impacts in Riyadh’s construction sector. The suggested methodology utilizes BIM for dynamic energy simulations and design visualization, PMBOK for integrating sustainability into project-management processes, and ML for predictive modeling and real-time energy optimization. Implementing an integrated model that incorporates building-management strategies and machine learning for both commercial and residential structures can offer stakeholders a thorough solution for forecasting energy performance and environmental impact. This is particularly essential in arid climates owing to specific conditions and environmental limitations. Using a simulation-based methodology, the framework was evaluated based on two representative case studies: (i) a commercial complex and (ii) a residential building. The neural network (NN), reinforcement learning (RL), and decision tree (DT) were implemented to assess performance in energy prediction and optimization. Results demonstrated notable seasonal energy savings, particularly in spring (15% reduction for commercial buildings) and fall (13% reduction for residential buildings), driven by optimized heating, ventilation, and air conditioning (HVAC) systems, insulation strategies, and window configurations. ML models successfully predicted energy consumption and greenhouse gas (GHG) emissions, enabling targeted mitigation strategies. GHG emissions were reduced by up to 25% in commercial and 20% in residential settings. Among the models, NN achieved the highest predictive accuracy (R² = 0.95), while RL proved effective in adaptive operational control. This study highlights the synergistic potential of BIM, PMBOK, and ML in advancing green project management and sustainable construction. Full article

This paper provides a comprehensive review of sessile benthic invertebrate biodiversity across three interconnected marine areas in Western Australia’s Gascoyne and southern Pilbara regions: Ningaloo Reef (a UNESCO World Heritage site), the nearby Muiron Islands to its north, and Exmouth Gulf to its east. The study aims to identify taxonomic and spatial knowledge gaps and establish a baseline biodiversity record for the broader region. We collated specimen-based records from seven Australian museums and supplemented them with data from the Atlas of Living Australia, iNaturalist, and a Web of Science literature review. In total, we report 827 verified species of sessile benthic invertebrates in shallow waters (less than 30 m depth) across the Gascoyne and southern Pilbara regions from 4578 records. Ningaloo Reef exhibits the highest diversity, hosting 587 species, including 239 scleractinian corals and 124 sponges. Exmouth Gulf is home to a diverse and unique assemblage of at least 295 species, including 165 species of putative turbid water specialists or regionally restricted species which are not found at Ningaloo Reef or the Muiron Islands. Notably, all three sea pen species identified in this review are recorded exclusively from Exmouth Gulf. The Gulf also hosts a distinctive community of filter-feeding invertebrates, including 125 sponges, 27 tunicates, and 18 anemones that are not found in neighboring regions. The Muiron Islands, although under sampled, host 22 species of sponges, 14 octocorals, and 5 tunicates that have not so far been found at Ningaloo Reef or Exmouth Gulf, highlighting the uniqueness of the islands’ marine invertebrate fauna. The southern sector of Ningaloo Reef is under sampled, and there are gaps in the state faunal collections for many groups, including anemones, corallimorphs, zoanthids, cerianthids, and hydrozoans. Further targeted taxonomic research on existing museum collections is crucial, as only 18% of specimen records have been verified, and 41% of the verified records are only identified to morphospecies. This limits our understanding of regional diversity and distribution patterns but provides ample opportunity for further taxonomic study. Expanding monitoring programs to include Exmouth Gulf and the Muiron Islands, along with unique habitats such as the King Reef artificial reef, and conducting additional biodiversity, demographic, and ecosystem health research is essential to assess the cumulative impacts of climate change and other environmental stressors on the unique and culturally significant marine ecosystems of this region. Full article

This study investigates the sustainable livelihoods of households in the coastal forest regions of Quang Tri Province, Vietnam, focusing on identifying the key factors that shape household resilience in the face of socio-economic and environmental challenges. Although the sustainable livelihoods approach is widely established in research, this study differentiates itself by applying a multivariate analysis to explore the relative impacts of various livelihood capitals—human, physical, financial, social, and environmental—specifically within the context of coastal forest ecosystems, a relatively under-researched area in Vietnam. The research identifies both factors affecting livelihood outcomes, emphasizing the role of community resources, seasonal fluctuations, and adaptation strategies. Additionally, the study highlights how environmental changes and natural resource constraints are more detrimental to livelihoods in these regions compared to other rural settings. Through these insights, this paper contributes to the growing body of literature by offering a nuanced understanding of how coastal forest communities can navigate the pressures of climate change, market volatility, and limited resources. The findings underscore the importance of enhancing adaptive capacity and crafting targeted policy interventions to support vulnerable households in the region. This study also highlights the limitations of existing research, emphasizing the need for future studies to integrate the complex interplay of environmental, social, and economic factors in coastal ecosystems. Full article

Mountain glaciers are the most direct and sensitive indicators of climate change. In the context of global warming, monitoring changes in glacier elevation has become a crucial issue in modern cryosphere research. The Global Ecosystem Dynamics Investigation (GEDI) is a full-waveform laser altimeter with a multi-beam that provides unprecedented measurements of the Earth’s surface. Many studies have investigated its applications in assessing the vertical structure of various forests. However, few studies have assessed GEDI’s performance in detecting variations in glacier elevation in land ice in high-mountain Asia. To address this limitation, we selected the Southeastern Tibetan Plateau (SETP), one of the most sensitive areas to climate change, as a test area to assess the feasibility of using GEDI to monitor glacier elevation changes by comparing it with ICESat-2 ATL06 and the reference TanDEM-X DEM products. Moreover, this study further analyzes the influence of environmental factors (e.g., terrain slope and aspect, and altitude distribution) and glacier attributes (e.g., glacier area and debris cover) on changes in glacier elevation. The results show the following: (1) Compared to ICESat-2, in most cases, GEDI overestimated glacier thinning (i.e., elevation reduction) to some extent from 2019 to 2021, with an average overestimation value of about −0.29 m, while the annual average rate of elevation change was relatively close, at −0.70 ± 0.12 m/yr versus −0.62 ± 0.08 m/yr, respectively. (2) In terms of time, GEDI reflected glacier elevation changes at interannual and seasonal scales, and the trend of change was consistent with that found with ICESat-2. The results indicate that glacier accumulation mainly occurred in spring and winter, while the melting rate accelerated in summer and autumn. (3) GEDI effectively monitored and revealed the characteristics and patterns of glacier elevation changes with different terrain features, glacier area grades, etc.; however, as the slope increased, the accuracy of the reported changes in glacier elevation gradually decreased. Nonetheless, GEDI still provided reasonable estimates for changes in mountain glacier elevation. (4) The spatial distribution of GEDI footprints was uneven, directly affecting the accuracy of the monitoring results. Thus, to improve analyses of changes in glacier elevation, terrain factors should be comprehensively considered in further research. Overall, these promising results have the potential to be used as a basic dataset for further investigations of glacier mass and global climate change research. Full article

This entry is based on the premise that pressing issues of climate change, social injustice, and post-COVID practices appear to have superseded some essential values of architectural and design pedagogy, leading to improvements in content that may be offset by a loss of focus on the core curriculum. The entry reimagines architectural pedagogy by arguing for a transformative shift from traditional product-based education to a process-oriented, inquiry-driven approach that cultivates critical thinking and empirical making, predicated upon experiential learning. It aims to integrate rigorous critical inquiry into both studio-based and lecture-based settings, thus critiquing assumed limitations of conventional approaches that prioritise final outcomes over iterative design processes, dialogue, and active engagement. Employing a comprehensive qualitative approach that incorporates diverse case studies and critical reviews, the analysis is divided into two main threads: one that places emphasis on the studio environment and another that focuses on lecture-based courses. Within these threads, the analysis is structured around a series of key themes central to experiential learning, each of which concludes with a key message that synthesises the core insights derived from case studies. The two threads instigate the identification of aligned areas of emphasis which articulate the need for active engagements and reflection, for bridging theory and practice, and for adopting interdisciplinary and experiential approaches. Conclusions are drawn to establish guidance for a future direction of a strengthened and pedagogically enriched architectural education. Full article

Urban heat exposure has become an increasingly critical environmental issue under the dual pressures of global climate warming and rapid urbanization, posing significant threats to public health and urban sustainability. However, conventional linear regression models often fail to capture the complex, nonlinear interactions among multiple environmental factors, and studies confined to single LCZ types lack a comprehensive understanding of urban thermal mechanisms. This study takes the central urban area of Zhengzhou as a case and proposes an integrated “Local Climate Zone (LCZ) framework + random forest-based multi-factor contribution analysis” approach. By incorporating multi-temporal Landsat imagery, this method effectively identifies nonlinear drivers of heat exposure across different urban morphological units. Compared to traditional approaches, the proposed model retains spatial heterogeneity while uncovering intricate regulatory pathways among contributing factors, demonstrating superior adaptability and explanatory power. Results indicate that (1) high-density built-up zones (LCZ1 and E) constitute the core of heat exposure, with land surface temperatures (LSTs) 6–12 °C higher than those of natural surfaces and LCZ3 reaching a peak LST of 49.15 °C during extreme heat events; (2) NDVI plays a dominant cooling role, contributing 50.5% to LST mitigation in LCZ3, with the expansion of low-NDVI areas significantly enhancing cooling potential (up to 185.39 °C·km²); (3) LCZ5 exhibits an anomalous spatial pattern with low-temperature patches embedded within high-temperature surroundings, reflecting the nonlinear impacts of urban form and anthropogenic heat sources. The findings demonstrate that the LCZ framework, combined with random forest modeling, effectively overcomes the limitations of traditional linear models, offering a robust analytical tool for decoding urban heat exposure mechanisms and informing targeted climate adaptation strategies. Full article

Corporate carbon emissions reporting is central to climate accountability, yet significant gaps remain in transparency, completeness, and methodological rigor. This study introduces the Carbon Integrity Index (CIX), a structured framework for assessing disclosure quality through ten indicators covering Scopes 1, 2, and 3. Unlike existing standards focused on reporting requirements, the CIX evaluates how well emissions are reported, addressing methodological transparency, scope coverage, and treatment of uncertainty. Applied to 2022 sustainability reports from companies listed in Spain’s IBEX 35 index, the framework reveals an average score of 5.7/10, with 69% of firms achieving passing results. While Scope 2 reporting was generally robust (mean: 0.82), Scope 3 disclosures—often representing the majority of emissions—and uncertainty assessments were systematically weak (mean: 0.08). Findings provide empirical support for legitimacy and institutional theory, showing how formal compliance can mask performative compliance that limits meaningful accountability. Sectoral differences suggest that institutional pressures and operational complexity shape divergent transparency pathways, raising concerns that universal standards may entrench reporting disparities. The CIX offers regulators, investors, and companies a practical tool for distinguishing symbolic from substantive disclosure, enabling more informed decision-making and strengthening the role of reporting in driving the transition to net-zero business models. Full article

This paper is aimed at landscape managers and designers. It looks at 123 real-world coastal landscape projects and organizes them into clear design categories, i.e., wetland restoration, hybrid infrastructure, or urban green spaces. We looked at how these projects were framed (whether they focused on climate adaptation, flood protection, or other goals) and how they tracked performance. We are hoping to bring some clarity to a very scattered field, helping us to see patterns in what is actually being carried out in terms of landscape interventions and increasing sea levels. We are hoping to provide a practical reference for making better, more climate-responsive design decisions. Coastal cities face escalating climate-driven threats from increasing sea levels and storm surges to urban heat islands. These threats are driving increased interest in nature-based solutions (NbSs) as green adaptive alternatives to traditional gray infrastructure. Despite an abundance of individual case studies, there have been few systematic syntheses aimed at landscape designers and managers linking design typologies, project framing, and performance outcomes. This study addresses this gap through a meta-synthesis of 123 implemented coastal landscape interventions aimed directly at landscape-oriented research and professions. Flood risk reduction was the dominant framing strategy (30.9%), followed by climate resilience (24.4%). Critical evidence gaps emerged—only 1.6% employed integrated monitoring approaches, 30.1% provided ambiguous performance documentation, and mean monitoring quality scored 0.89 out of 5.0. While 95.9% of the projects acknowledged SLR as a driver, only 4.1% explicitly integrated climate projections into design parameters. Community monitoring approaches demonstrated significantly higher ecosystem service integration, particularly cultural services (36.4% vs. 6.9%, $p<0.001$), and enhanced monitoring quality (mean score 1.64 vs. 0.76, $p<0.001$). Implementation barriers spanned technical constraints, institutional fragmentation, and data limitations, each affecting 20.3% of projects. Geographic analysis revealed evidence generation inequities, with systematic underrepresentation of high-risk regions (Africa: 4.1%; Latin America: 2.4%) versus concentration in well-resourced areas (North America: 27.6%; Europe: 17.1%). Full article

Despite the increased research on violence toward teachers and public policies aimed at protecting teachers from violence, knowledge of the factors contributing to teachers’ sense of safety at school remains limited. Drawing from socioecological theory, we examined the contributions of both teachers’, parents’, students’, and schools’ characteristics to teachers’ sense of feeling unsafe in school. Specifically, we examined teachers’ individual and work characteristics (sex, age, years of experience, and working in the regular classroom or not), their perceptions of school violence, and their relationships with students and their peers. At the school level, we examined the school size, poverty level, and school-level reports of parents’, students’, and teachers’ perception of the school climate and school violence. The sample consisted of 9625 teachers (73% female), 126,301 students, and 56,196 parents from 2116 schools with a low socioeconomic status in Chile. Descriptive statistics showed that most teachers do not feel afraid (72.9%) nor thought that their job was dangerous (74.6%). A hierarchical multivariate regression analysis and multilevel analyses showed that teachers with higher perceptions of feeling unsafe were females or reported being “other sex”, had fewer years of experience, worked mainly in the classroom, perceived a higher level of school violence, and had worse perceptions of peer relationships and teacher–student relationships. These teachers were mostly in schools with higher poverty levels, larger enrollment, and higher student-reported and parent-reported school violence compared to the rest of the sample of low-SES Chilean schools. We discuss the implications of these findings for preventive school interventions and programs regarding school violence and teacher turnover. Full article

This research evaluates the financial sustainability of a basic income (BI) model funded through carbon taxation in Türkiye. Unlike classical BI models that provide unconditional transfers to everyone, this study proposes an income support scheme targeted only at those below the poverty line. The model seeks to balance limited resources with the goal of social equity. In this scenario, sectoral carbon taxation evolves progressively. The tax starts with the energy sector, which has the highest emissions, and subsequently shifts to industry and other sectors. Emissions will be reduced by 1% each year, while a carbon tax that starts at USD 12 per ton will be dynamically converted to TL based on the increasing exchange rate year by year. The simulation looks at 2023–2050 and computes annual revenue and expenditure forecasts for the period. The findings indicate that the revenues from carbon taxation are not only sufficient to cover the prioritized expenditure in the targeted basic income (TBI) scheme but also will lead to fiscal surplus in the long run. The research proposes for the first time a framework which integrates social protection and the environmental taxation of carbon, synergizing policies aimed at alleviating income disparity and climate change within Türkiye’s context. Full article

Carbon dioxide is naturally present in the Earth’s atmosphere and plays a role in regulating and balancing the planet’s temperature. However, due to various human activities, the amount of carbon dioxide is increasing beyond safe limits, disrupting the Earth’s natural temperature regulation system. Today, CO₂ is the most prevalent greenhouse gas; as its concentration rises, significant climate change occurs. Therefore, there is a need to utilize anthropogenically released carbon dioxide in valuable fuels, such as formic acid (HCOOH). Single-atom catalysts are widely used, where a single metal atom is anchored on a surface to catalyze chemical reactions. In this study, we investigated the potential of Cu@Phosphorene as a single-atom catalyst (SAC) for CO₂ reduction using quantum chemical calculations. All computations for Cu@Phosphorene were performed using density functional theory (DFT). Mechanistic studies were conducted for both bimolecular and termolecular pathways. The bimolecular mechanism involves one CO₂ and one H₂ molecule adsorbing on the surface, while the termolecular mechanism involves two CO₂ molecules adsorbing first, followed by H₂. Results indicate that the termolecular mechanism is preferred for formic acid formation due to its lower activation energy. Further analysis included charge transfer assessment via NBO, and interactions between the substrate, phosphorene, and the Cu atom were confirmed using quantum theory of atoms in molecules (QTAIM) and non-covalent interactions (NCI) analysis. Ab initio molecular dynamics (AIMD) calculations examined the temperature stability of the catalytic complex. Overall, Cu@Phosphorene appears to be an effective catalyst for converting CO₂ to formic acid and remains stable at higher temperatures, supporting efforts to mitigate climate change. Full article

South Korea and North Korea share the same environment on the Korean peninsula, but they differ in socio-economic conditions, which leads to differences in crop productivity and status of food security. This study aimed at assessing food security in South Korea and North Korea by analyzing food demand and supply from 1991 to 2020. Food security was assessed by determining whether the food supply met the demand in two countries. South Korea achieved food security due to decreasing consumption, diverse nutrition, and stable rice productivity despite a reduction in cultivated paddy areas. In contrast, North Korea has faced food insecurity for 30 years, caused by a growing population, a lack of dietary diversity, and low crop productivity. To overcome food shortage, the North Korean government needs to focus on improving agricultural productivity through comprehensive reforms of agricultural infrastructures, rather than simply expanding low-productive cultivated areas. Although this study was conducted with limited data for North Korea, it sought to collect and utilize open and publicly accessible data. In the long term, both South Korea and North Korea should prepare for the impacts of climate change, considering agriculture-related sectors such as water and energy. Full article

The construction of prefabricated concrete houses in Ecuador poses significant challenges in terms of environmental and social sustainability, amid growing housing demand and the urgent need to mitigate adverse impacts associated with the construction processes and materials. In particular, the lack of a comprehensive assessment of these impacts limits the development of effective strategies to improve the sustainability of the sector. In addition, in rural areas, the design of flexible and adapted solutions is required, as evidenced by recent studies in the Andean area. This study conducts a comprehensive assessment of the impacts and sustainability indicators for prefabricated concrete houses, employing international certification systems such as LEED, BREEAM, and VERDE, to validate various relevant environmental and social indicators. The methodology used is the Hierarchical Analytical Process (AHP), which facilitates the prioritization of impacts through paired comparisons, establishing priorities for decision-making. Hydrological, soil, faunal, floral, and socioeconomic aspects are evaluated in a regional context. The results reveal that the most critical environmental impacts in Ecuador are climate change (28.77%), water depletion (13.73%) and loss of human health (19.17%), generation of non-hazardous waste 8.40%, changes in biodiversity 5%, extraction of mineral resources 12.07%, financial risks 5.33%, loss of aquatic life 4.67%, and loss of fertility 3%, as derived from hierarchical and standardization matrices. Despite being grounded in a literature review and being constrained due to the scarcity of previous projects in the country, this research provides a useful framework for the environmental evaluation and planning of prefabricated housing. To conclude, this study enhances existing methodologies of environmental assessment techniques and practices in the construction of precast concrete and promotes the development of sustainable and socially responsible housing in Ecuador. Full article

Global climate change has intensified the frequency, intensity, and spatial heterogeneity of drought events, posing severe threats to the stability of terrestrial ecosystems. Plant drought resilience, which encompasses a plant’s capacity for drought resistance, post-stress recovery, and long-term adaptation and transformation to sustain ecosystem functionality, has emerged as a central focus in botanical and ecological research. This review synthesizes the conceptual evolution of plant drought resilience, from early emphasis on resistance and recovery to the current multi-dimensional framework integrating adaptation and transformation, and synthesizes advances in understanding multi-scale drought resilience in terrestrial plants—spanning molecular, physiological, individual, community, and ecosystem levels. Key mechanisms include molecular/physiological adaptations (osmotic adjustment, antioxidant defense, hydraulic regulation, carbon–water reallocation via gene networks and aquaporins), morpho-anatomical traits (root architectural plasticity, leaf structural modifications, and hydraulic vulnerability segmentation), community/ecosystem drivers (biodiversity effects, microbial symbioses, and soil–plant–feedback dynamics). We critically evaluate quantitative metrics and expose critical gaps, including neglect of stress legacy effects, oversimplified spatiotemporal heterogeneity, and limited integration of concurrent stressors. Future research should prioritize multi-scale and multi-dimensional integrated analysis, long-term multi-scenario simulations with field validation, and harnessing plant–microbe interactions to enhance drought resilience, providing a theoretical basis for ecosystem sustainability and agricultural production under climate change. Full article

Abnormally warm winters in recent years have accelerated flowering in fruit trees, increasing their vulnerability to late frost damage. To address this challenge, this study aimed to evaluate and compare the performance of three phenology models—the development rate (DVR), modified DVR (mDVR), and Chill Days (CD) models—for predicting full bloom dates of ‘Niitaka’ pear, using image-derived phenological observations. The goal was to identify the most reliable and regionally transferable model for nationwide application in South Korea. A key strength of this study lies in the integration of real-time orchard imagery with automated weather station (AWS) data, enabling standardized and objective phenological monitoring across multiple regions. Using five years of temperature data from seven orchard sites, chill and heat unit accumulations were calculated and compared with observed full bloom dates obtained from orchard imagery and field records. Correlation analysis revealed a strong negative relationship between cumulative heat units and bloom timing, with correlation coefficients ranging from –0.88 (DVR) to –0.94 (mDVR). Among the models, the mDVR model demonstrated the highest stability in chill unit estimation (CV = 6.3%), the lowest root-mean-square error (RMSE = 2.9 days), and the highest model efficiency (EF = 0.74), indicating superior predictive performance across diverse climatic conditions. In contrast, the DVR model showed limited generalizability beyond its original calibration zone. These findings suggest that the mDVR model, when supported by image-based phenological data, provides a robust and scalable tool for forecasting full bloom dates of temperate fruit trees and enhancing grower preparedness against late frost risks under changing climate conditions. Full article