Search Results (1,634)

Urban heat islands (UHIs) are a growing sustainability challenge impacting public health, energy use, and climate resilience, especially in hot, arid cities like San Antonio, Texas, where land surface temperatures reach up to 47.63 °C. This study advances a data-driven, interdisciplinary approach to UHI mitigation by integrating Machine Learning (ML) with physical and socio-demographic data for sustainable urban planning. Using high-resolution spatial data across five functional zones (residential, commercial, industrial, official, and downtown), we apply three ML models, Random Forest (RF), Support Vector Machine (SVM), and Gradient Boosting Machine (GBM), to predict land surface temperature (LST). The models incorporate both environmental variables, such as imperviousness, Normalized Difference Vegetation Index (NDVI), building area, and solar influx, and social determinants, such as population density, income, education, and age distribution. SVM achieved the highest R² (0.870), while RF yielded the lowest RMSE (0.488 °C), confirming robust predictive performance. Key predictors of elevated LST included imperviousness, building area, solar influx, and NDVI. Our results underscore the need for zone-specific strategies like more greenery, less impervious cover, and improved building design. These findings offer actionable insights for urban planners and policymakers seeking to develop equitable and sustainable UHI mitigation strategies aligned with climate adaptation and environmental justice goals. Full article

The complexity of assessment is a significant problem in designing renewable energy source (RES) products, especially when one wants to take into account their various aspects, e.g., technical, environmental, or social. Hence, the aim of the research is to develop a model supporting the decision-making process of RES product development based on meeting the criteria of quality, environmental impact, and social responsibility (QES). The model was developed in four main stages, implementing multi-criteria decision support methods such as DEMATEL (decision-making trial and evaluation laboratory) and TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution), as well as criteria for social responsibility and environmental impact from the ISO 26000 standard. The model was tested and illustrated using the example of photovoltaic panels (PVs): (i) five prototypes were developed, (ii) 30 PV criteria were identified from the qualitative, environmental, and social groups, (iii) the criteria were reduced to 13 key (strongly intercorrelated) criteria according to DEMATEL, (iv) the PV prototypes were assessed taking into account the importance and fulfilment of their key criteria according to TOPSIS, and (v) a PV ranking was created, where the fifth prototype turned out to be the most advantageous (QES = 0.79). The main advantage of the model is its simple form and transparency of application through a systematic analysis and evaluation of many different criteria, after which a ranking of design solutions is obtained. QES ensures precise decision-making in terms of sustainability of new or already available products on the market, also those belonging to RES. Therefore, QES will find application in various companies, especially those looking for low-cost decision-making support techniques at early stages of product development (design and conceptualization). Full article

Individual willingness to pay (WTP) for green energy plays a vital role in mitigating climate change. Based on social cognitive theory (SCT), which emphasizes the dynamic interaction among individual cognition, behavior and the environment, this study develops a theoretical model to identify factors influencing green energy WTP. The study is based on 585 valid questionnaire responses from urban areas in China and uses Structural Equation Modeling (SEM) to reveal the linear causal path. Meanwhile, fuzzy-set Qualitative Comparative Analysis (fsQCA) is utilized to identify the combined paths of multiple conditions leading to a high WTP, making up for the limitations of SEM in explaining complex mechanisms. The SEM analysis shows that social trust, social networks, and social norms have a significant positive impact on individual green energy WTP. And this influence is further transmitted through the mediating role of environmental self-efficacy and expectations of environmental outcomes. The FsQCA results identified three combined paths of social capital and environmental cognitive conditions, including the Network–Norm path, the Network–efficacy path and the Network–Outcome path, all of which can achieve a high level of green energy WTP. Among them, the social networks are a core condition in every path and a key element for enhancing the high green energy WTP. This study promotes the expansion of SCT, from emphasizing the linear role of individual cognition to focusing on the configuration interaction between social structure and psychological cognition, provides empirical evidence for formulating differentiated social intervention strategies and environmental education policies, and contributes to sustainable development and the green energy transition. Full article

Since the start of the energy crisis in 2020, the Dutch government has introduced various programmes aimed at alleviating energy poverty among low-income households. This research examines the effects of three specific interventions—energy coaching, home renovations, and white goods schemes—on a range of energy poverty-related aspects, including living comfort, physical and mental health, energy costs, financial concerns, social connection, neighbourhood involvement, and sustainable behaviour. While previous studies have mostly investigated these interventions in isolation, this research offers a comparative analysis to explore how their impacts differ and how they may complement one another. This research, comparing an intervention group and control, shows that energy coaches, renovations, and white goods schemes each have positive effects on various aspects of energy poverty. However, the nature and magnitude of these effects differ by type of support measure. Renovations are the most effective overall, significantly improving living comfort, physical health, and reducing energy costs. White goods schemes primarily reduce moisture and mould in dwellings and have a notable positive impact on mental health. Energy coaches contribute to improved living comfort, lower energy costs, and uniquely enhance community involvement. The complementary nature of these interventions highlights the potential added value of integrated or combined approaches to tackling energy poverty. Full article

Sustainability in the non-alcoholic beverage industry requires effective metrics to assess environmental, social, and economic performance. However, the lack of standardised indicators for small and medium-sized enterprises (SMEs) hinders the implementation of sustainable strategies. This study aims to select a set of sustainability indicators for small and medium-sized non-alcoholic beverage industries in Brazil. Seventy-four indicators were identified based on the Global Reporting Initiative (GRI) guidelines, which were subsequently evaluated and refined by industry experts for prioritisation. Statistical analysis led to the selection of 31 final indicators, distributed across environmental (10), social (12), and economic (9) dimensions. In the environmental dimension, priority indicators include water management, energy efficiency, carbon emissions, and waste recycling. The social dimension highlights working conditions, occupational safety, gender equity, and impacts on local communities. In the economic dimension, key indicators relate to supply chain efficiency, technological innovation, financial transparency, and anti-corruption practices. The results provide a robust framework to guide managers in adopting sustainable practices and support policymakers in improving the environmental, social, and economic performance of small and medium-sized non-alcoholic beverage industries. Full article

The transition to clean energy is not inherently positive or negative, and its impacts depend on the social context, power relations, and mechanisms to include marginalized voices. India, with its ambitious climate targets and commitment to the UN SDG Agenda, is a key country for ensuring an inclusive and sustainable transition. This paper aims to understand whether India’s commitment to the SDG Agenda’s overarching principle of ‘leaving no one behind’ is reflected in the design of its domestic solar policies. It analyzes how energy justice concerns are addressed in state-level solar policies. To that end, a pragmatic framework was developed to identify key justice dimensions and indicators, linked to the SDG targets, that are essential for an inclusive transition. This research conducted a qualitative interpretive content analysis of 29 solar energy policies, using the three identified framework dimensions—income growth, enhancing inclusion, and equal opportunities. We found that the themes around energy access, employment, and skill development are reflected in policies, while those around the inclusion of the poor, women, and community remain limited. The findings indicate that the policies have focused on low-impact justice concerns, lacking structural transformation. To address these gaps, the study proposes targeted subsidies, community ownership, and gender-inclusive mechanisms. The framework offers a pragmatic tool for the evaluation of clean energy policies in the Global South, and the empirical results provide insights for the synergistic implementation of the climate and sustainable development agenda. Full article

Mycelium-bonded composites (MBCs), or myco-composites, represent a novel engineered material that combines natural lignocellulosic substrates with a fungal matrix. As a sustainable alternative to plastics, MBCs are gaining increasing interest; however, their large-scale industrial adoption remains limited, partly due to low social acceptance resulting from their unattractive appearance. Laser engraving provides a promising method for fabricating intricate patterns and functional surfaces on MBCs, minimizing tool wear, material loss, and environmental impact, while enhancing esthetic and engineering properties. This study investigates the influence of CO₂ laser parameters on the material removal rate during the engraving of myco-composites, focusing on the effects of variable laser power, beam defocus, and head feed rate on engraving outcomes. The results demonstrate that laser power and beam focus significantly impact material removal in mycelium-bonded composites. Specifically, increasing the laser power results in greater material removal, which is more pronounced when the beam is focused due to higher energy density. In contrast, a beam defocused by 1 mm produces less intense material removal. These findings highlight the critical role of beam focus—surpassing the influence of power alone—in determining engraving quality, particularly on irregular or uneven surfaces. Moreover, reducing the laser head feed rate at a constant power level increases the material removal rate linearly; however, it also results in excessive charring and localized overheating, revealing the low thermal tolerance of myco-composites. These insights are essential for optimizing laser processing techniques to fully realize the potential of mycelium-bonded composites as sustainable engineering materials, simultaneously maintaining their appearance and functional properties. Full article

The Retabit platform is a data-driven tool designed to bridge the gap between building rehabilitation and urban regeneration by integrating energy, economic, and social dimensions into a single framework. Leveraging multiple public data sources, the platform provides actionable insights to local and national authorities, public housing agencies, urban planners, energy service providers, and research institutions, helping to align renovation initiatives with broader urban transformation goals and climate action objectives. The platform consists of two main components: Analyse, for examining building conditions through multidimensional indicators, and Plan, for designing and simulating renovation projects. Retabit contributes to more transparent and informed decision-making, encourages collaboration across sectors, and addresses long-term sustainability by incorporating participatory planning and impact evaluation. Its scalable structure makes it applicable across diverse geographic areas, policy contexts, and domains linked to sustainable urban development. Full article

The growing frequency and severity of extreme events, both natural and human-induced, have heightened concerns about the resilience of power systems. Enhancing the resilience of power systems alleviates the adverse impacts of power outages caused by unforeseen events, delivering substantial social and economic benefits. Energy storage systems play a crucial role in enhancing the resilience of power systems. Researchers have proposed various single and hybrid energy storage systems to enhance power system resilience. However, a comprehensive review of the latest trends in utilizing energy storage systems to address the challenges related to improving power system resilience is required. This critical review, therefore, discusses various aspects of energy storage systems, such as type, capacity, and efficacy, as well as modeling and control in the context of power system resilience enhancement. Finally, this review suggests future research directions leading to optimal use of energy storage systems for enhancing resilience of power systems. Full article

The building sector remains one of the largest contributors to global energy consumption and CO₂ emissions, yet selecting optimal retrofit strategies is often hindered by inconsistent evaluation practices and limited integration of environmental and social impacts. This review addresses that gap by systematically analyzing how various assessment methods are applied to building retrofits, particularly from a financial and environmental perspective. A structured literature review was conducted across four major scientific databases using predefined keywords, filters, and inclusion/exclusion criteria, resulting in a final sample of 50 studies (green colored citations of this paper). The review focuses on the application of Life Cycle Cost Analysis (LCCA), Cost–Benefit Analysis (CBA), and Life Cycle Assessment (LCA), as well as additional indicators that quantify energy and sustainability performance. Results show that LCCA is the most frequently used method, applied in over 60% of the studies, often in combination with LCA (particularly for long time horizons). CBA appears in fewer than 25% of cases. More than 50% of studies are based in Europe, and over 60% of case studies involve residential buildings. EnergyPlus and DesignBuilder were the most common simulation tools, used in 28% and 16% of the cases, respectively. Risk and uncertainty were typically addressed through Monte Carlo simulations (22%) and sensitivity analysis. Comfort and social impact indicators were underrepresented, with thermal comfort included in only 12% of studies and no formal use of tools like Social-LCA or SROI. The findings highlight the growing sophistication of retrofit assessments post-2020, but also reveal gaps such as geographic imbalance (absence of African case studies), inconsistent treatment of discount rates, and limited integration of social indicators. The study concludes that future research should develop standardized, multidimensional evaluation frameworks that incorporate social equity, stakeholder values, and long-term resilience alongside cost and carbon metrics. Full article

With an economic model characterized by high energy consumption and low efficiency, China is facing serious energy shortages and environmental problems. However, education, as the cornerstone of social progress, has been overlooked in its role in improving energy efficiency. This study aims to enhance our understanding of the impact of educational competitiveness on urban green total factor energy efficiency (GTFEE), helping policymakers to achieve sustainable urban development. This study utilizes panel data from 20 major Chinese cities spanning from 2012 to 2022 and applies a two-way fixed effects model to investigate the relationship and pathways of educational competitiveness (Ec) on GTFEE. Our results show that the Ec index can enhance the major urban GTFEE. Among them, educational resource competitiveness, input competitiveness, efficiency competitiveness, and sustainable competitiveness can all enhance urban GTFEE, but the coefficient of the educational scale is not significant. In addition, Ec can effectively improve GTFEE by promoting green technological innovation, alleviating human resource mismatch, and driving industrial structure upgrading. Furthermore, the impact of Ec on GTFEE shows significant regional heterogeneity, with its effect weakening from the eastern coastal areas to the western inland regions. Full article

Power-to-X (ptx) technologies are considered a promising solution for enabling the storage and sectoral integration of renewable energy, playing a vital role in the sustainable transition of industrialized energy systems. This study investigates the public acceptance of ptx technologies in Germany using a quantitative, environmental–psychological framework. Key influencing factors such as social and personal norms, environmental awareness, and openness to innovation are analyzed. A particular focus is placed on generational differences, comparing the perceptions of youth (16–25 years) and adults (>25 years) through a representative online survey. The results reveal a general lack of knowledge about ptx technologies yet a positive assessment of their decarbonization potential. Ecological impact—particularly the ability to reduce CO₂ emissions—emerges as the strongest predictor of acceptance. This is closely tied to conditions such as the use of renewable electricity and sustainable sourcing of carbon and water. Notably, acceptance among youth is also influenced by environmental awareness, prior knowledge, and perceived behavioral control. The results show that, in general, there is still a need for improved science communication to address the existing uncertainties in the population. At the same time, age-specific approaches are required, as perceptions and acceptance factors differ significantly between younger and older age groups. Full article

The environmental impact of first-generation biodiesel production, particularly deforestation and soil degradation caused by palm and soybean cultivation, has raised concerns about sustainability. In contrast, second-generation biodiesel utilizes waste as feedstock, offering a more sustainable alternative. Used cooking oil (UCO), a significant waste stream, represents a viable feedstock for biodiesel production, reducing pollution and mitigating economic, environmental, and social challenges. While Europe has demonstrated successful UCO waste management strategies, many regions lack efficient systems, leading to improper disposal that causes water eutrophication, soil degradation, and increased wastewater treatment costs. This study develops a comprehensive strategy for UCO management to optimize its energy potential in biodiesel production, using Barranquilla, Colombia, as a case study. Transesterification, identified as the most efficient conversion method, achieves conversion rates of up to 90%. A pilot project in the Barranquilla area estimates that 963,070.95 kg of UCO is generated annually, with the potential to produce 902,108.56 kg of biodiesel. These findings contribute to the advancement of circular economy principles, offering an adaptable framework for sustainable biofuel production in other regions. Full article

This study contributes to the broader sustainability discourse by evaluating public knowledge, awareness, and practices regarding air pollution among residents of Hanoi, Vietnam, focusing on its causes, health impacts, and mitigation strategies. A cross-sectional survey was conducted with 521 individuals in suburbs around Hanoi. A multistage sampling technique, combining cluster and simple random sampling, was used for participant recruitment. Three central and three suburban districts of Hanoi were randomly selected as clusters. One individual from each household was invited to participate and answer a structured survey, which assessed perceptions of air pollution, its human-induced causes, recognised health impacts, and individual and community-level mitigation behaviours. Nearly all participants (98.3%) were aware of air pollution, with 65.3% attributing it to human activities and 61.2% recognising specific air pollutants as primary contributors. The majority (93.9%) acknowledged health impacts, citing respiratory infections (55.1%) and sinus issues (51.2%) as prevalent concerns. Vulnerable groups, such as children under 5 (82.3%) and adults over 65 years old (77.4%), were identified as disproportionately affected. Social media (68.9%) and television (58.3%) were the dominant sources of information. Despite a recognition of air pollution’s importance (98.5%), there was limited engagement in systemic sustainability actions, such as supporting renewable energy initiatives. Most participants (84.3%) reported personal mitigation efforts, including energy-saving practices (35.5%) and walking instead of driving a car or bike (35.3%). While awareness of air pollution and its health impacts is high among Hanoi residents, proactive engagement in systemic solutions remains limited. Policymakers should prioritise community-based programs, public–private partnerships, sustainability education, and culturally tailored policy interventions to bridge gaps between awareness and action. Tailored interventions addressing demographic and cultural factors are essential to fostering socio-environmental sustainability in rapidly urbanising contexts. Full article

Prefabricated buildings, known for their energy efficiency, environmental benefits, and industrial advantages, play a crucial role in urban renewal. Previous studies on the carbon emissions of prefabricated buildings mainly concentrate on the assessment and auditing of carbon emissions at the materialization and construction phase. Few of them have analyzed the carbon emissions at the operational phase or the influence mechanisms of prefabricated buildings on carbon emissions in urban renewal. Thus, this paper explored the factors and mechanisms that influence carbon emissions in prefabricated buildings in China’s urban renewal. Firstly, the factors that influence the carbon emissions of prefabricated buildings in China’s urban renewal were identified through meta-analysis. Secondly, the theoretical model was developed to illustrate the influence paths of prefabricated buildings on the carbon emissions of urban renewal. Finally, the structural equation model (SEM) was used to test the hypotheses in the theoretical model using data collected from questionnaires. The results show that the carbon emission reduction potential of prefabricated buildings is influenced by four aspects, namely, socioeconomic factors, policy regulations, building operation, and materialization. Policy regulations have the greatest impact on the carbon emissions of prefabricated buildings. They not only directly affect the carbon emissions of urban renewal but also influence carbon emissions indirectly through the social economy aspect. The direct impact of social economy on the carbon emissions of prefabricated buildings is insignificant, while it can indirectly affect the carbon emission reduction in prefabricated buildings by influencing building operations and the materialization stage. The findings could help provide strategies for prefabrication and enhance the reduction potential of urban renewal. Full article