Environmental Challenges Research Articles

Exploring Organisational Agility's Impact on Nurses' Green Work Behaviour: The Mediating Role of Climate Activism.

To examine the relationship between organisational agility and nurses' green work behaviour and to assess how climate activism mediates this relationship. Understanding this relationship is crucial for promoting sustainable practices in healthcare. A cross-sectional research design was employed. This approach was chosen to examine how organisational agility and climate activism simultaneously influence green work behaviour in the present context, providing a snapshot of their synergistic interactions. This study was conducted in 2024 at eight hospitals in Egypt, with a total of 781 nurses conveniently selected for participation. Data were collected using validated instruments: the Agility Survey, Employee Green Behaviour Scale and Environmental Action Scale. Correlation and path analyses were utilised to test the study hypotheses. Nurses reported moderate levels of organisational agility, climate activism and green work behaviour. Statistically significant positive correlations were found between organisational agility, climate activism and green work behaviour. Organisational agility and climate activism emerged as significant predictors of green work behaviour, with climate activism acting as a partial mediator between organisational agility and green work behaviour. This study contributes to the growing body of knowledge on fostering sustainable nursing practices as results indicate that agile organisations, which embrace flexibility and nurse-led climate initiatives, are better positioned to promote sustainable behaviour. Practical strategies include selecting nurses with high climate literacy, designing agile working strategies and promoting eco-conscious behaviours. Nurse leaders should develop policies that integrate climate initiatives into everyday practice to enhance green work behaviour. The healthcare sector faces increasing environmental challenges, making it crucial to foster green work behaviour. Our study addresses a gap in the literature by revealing that organisational agility and climate activism are essential drivers of green behaviour among nurses, offering actionable insights for greening healthcare practices. This study was reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE). No patient or public contribution.

Effect of road infrastructure on food sovereignty in Akwa Ibom State, Nigeria

The study was designed to assess the effect of road infrastructure on food Sovereignty in Akwa lbom State, Nigeria. The specific objectives of the study were to: ascertain the socioeconomic characteristics of the respondents; identify the food sovereignty in the study area and ascertain the effect of road infrastructure on food sovereignty in the study area. The survey research design was adopted for the study. The population of the study comprised all rural farming households in Akwa Ibom State. The study adopted multi-stage and simple random sampling techniques. Three blocks were selected from each of the three Agricultural Zones in the state. Three cells were randomly selected from each of the blocks sampled, which gave a total of twenty-seven (27) cells. A total of 450 respondents were selected using simple random sampling technique. Data were collected with the aid of a semi structured questionnaire. Data obtained were analyzed using percentages, means and standard deviation as well as ranking. The results of the socio-economic characteristics of the respondents showed that 58.90% of the respondents were males (265), while 41.10% of them were females (185). A good number of the respondents, 53.60%, were married (241), while 24.20%were single (109). Also, the results showed that 19.60% of the respondents had no formal education (88), while 30.70% attained secondary level of education (134), and about 33.70% of the respondents had tertiary level of education (152). The socio-economic characteristics of the respondents also indicated that 40.0% of the respondents had farm size ranging from 1-2 hectares, while 5.80% had farm size of 5 hectares and above. A good number of the respondents had access to credit (59.60%), while a small proportion (40.40%) had no credit facilities. The study revealed that 21.30% of the respondents had income ranging from N351,000 to N450,000, less than one US$ while a small proportion of the famers (8.90%) had income of about N251,000 to N350,000 only from farming activities. The main sources of food sovereignty of the people were crop farming and livestock production, though some were involved in trading and artisanal activities. The study noted that road projects have reduced accident (x ̅=2.75), increased farmers’ income (x ̅=3.20), increased trading and shopping activities (x ̅ =2.62), and reduced floods (x ̅ =2.64) among others. It was also concluded that road projects have positive effects of food sovereignty although some of the abandoned projects have caused some hardship and environmental challenges. The study recommended the completion of all abandoned road projects carried out in rural Akwa Ibom State in particular, and Nigeria in general. The study, however, concluded that in Akwa Ibom State, rural road projects have brought the much needed relief from accidents, wastage, spoilage, and food sovereignty to many hitherto isolated rural communities. Key words: Akwa Ibom State, Effect, Farmers, Food, Sovereignty, Road infrastructure

Inhibitory effect of Bacillus velezensis 1273 strain cell-free supernatant against developing and preformed biofilms of Staphylococcus aureus and MRSA

Microbial biofilms constitute a significant virulence factor and a substantial challenge in clinical environments due to their role in promoting antimicrobial resistance and their resilience to eradication efforts. Methicillin-resistant Staphylococcus aureus (MRSA) infections substantially increase healthcare costs, extend hospitalizations, and elevate morbidity and mortality rates. Therefore, developing innovative strategies to target and eliminate these bacteria and their biofilms effectively is imperative for robust epidemiological control. In this study, we evaluated the antibacterial and antibiofilm activities of cell-free supernatant (CFS) obtained from the Bacillus velezensis 1273 strain culture. Our data showed that CFS inhibited the growth of S. aureus ATCC 29213 and MRSA (clinical strain), with greater efficacy observed against S. aureus (1:16 dilution). Furthermore, CFS showed substantial potential in reducing biofilm formation in both strains (∼30 %) at subinhibitory concentrations. Additionally, the antibacterial activity against biofilm-formed cells showed that pure CFS treatment decreased the viability of S. aureus (60 %) and MRSA (45 %) sessile cells. We further demonstrated that CFS treatment induces the production of reactive oxygen species (ROS) and damages the membranes and cell walls of the pathogen cells. Genome analysis revealed the presence of genes encoding bacteriocins and secondary metabolites with antibacterial activity in the B. velezensis 1273 genome. These findings highlight the potential of probiotic bacterial metabolites as antibiofilm and anti-multidrug-resistant pathogens.

Sustainable watersheds management in Peru: Challenges and perspectives

Sustainable watershed management stands at the forefront of global efforts to tackle pressing environmental and socio-economic challenges. This study offers a pioneering assessment of the state of research on Peru's watersheds, integrating geographical, environmental, and socio-economic dimensions. By harnessing cutting-edge bibliometric tools, including Bibliometrix and VOSviewer, and adhering to PRISMA guidelines for a systematic review, this work maps the scientific landscape of watershed management in Peru. Utilizing comprehensive databases such as Scopus and Web of Science, the study identifies and analyses key thematic clusters, revealing an escalating focus on the urgent issues of climate change and urbanization, particularly within the critical Rimac River Basin. This basin, vital to the water supply of Lima, the world's second-largest desert city, faces severe threats from pollution and climate instability. Our findings not only chart the evolution of research in this domain but also spotlight emerging opportunities to modernize water management practices through the integration of climate change models, advanced data monitoring, and artificial intelligence. The study makes a compelling case for a collaborative approach, urging stronger alliances among local communities, research institutions, and international stakeholders to foster more resilient and sustainable watershed management strategies in Peru. This paper provides actionable insights, making it an indispensable resource for policymakers and practitioners aiming to secure Peru's water future.

Laccase: A Green Biocatalyst Offers Immense Potential for Food Industrial and Biotechnological Applications.

Laccase, a multipurpose biocatalyst, is widely distributed across all kingdoms of life and plays a key role in essential biological processes such as lignin synthesis, degradation, and pigment formation. These functions are critical for fungal growth, plant-pathogen interactions, and maintenance of soil health. Due to its broad substrate specificity, multifunctional nature, and environmentally friendly characteristics, laccase is widely employed as a catalyst in various green chemistry initiatives. With its ability to oxidize a diverse range of phenolic and nonphenolic compounds, laccase has also been found to be useful as a food additive and for assessing food quality parameters. Ongoing advancements in research and technology are continually expanding the recognition of laccase's potential to address global environmental, health, and energy challenges. This review aims to provide critical insights into the applications of laccases in the biotechnology and food industry.

Impact Assessment of Forest Degradation on Peoples Livelihood: The Case of Harena Buluq Woreda Bale Eco Region, Southeast Ethiopia

In developing countries like Ethiopia, forest degradation, characterized by the decline in forest cover and diminished capacity to provide essential goods and services, presents significant environmental, social, and economic challenges. The purpose of this study is to assess the effects of forest degradation on the way of life for the people living in the southeast Ethiopian woreda of Harena Buluq. Examining how forest degradation affects local livelihoods with a particular emphasis on livelihood strategies and the degree of reliance on forest resources is the main goal. In order to obtain qualitative insights, data was gathered by means of a combination of secondary sources and key informant interviews, which were complemented by on-site observations of the consequences of forest degradation. After gathering, the data was examined and shown. The findings underscore the multifaceted impact of forest degradation on the socio-economic fabric of communities in Harena Buluq, highlighting the urgent need for targeted interventions to mitigate its adverse effects and promote sustainable livelihood practices.

Green horizons: Exploring the potential of vertical green walls

The term “Green walls” also known as vertical gardens or living walls has emerged as a promising solution to combat the environmental challenges posed by rapid urbanization. This review explores the concept ornamental, plant choice suitable and benefits associated with green walls in urban settings. Utilising vegetation to cover vertical surfaces, green walls offer several benefits to the environment, society and economy. They contribute to improved air quality, noise reduction, energy conservation and biodiversity enhancement. Vertical greenery allows for the utilization of unused wall surfaces, creating green areas without occupying valuable ground space, which is often scarce in urban environments. Additionally, green walls offer aesthetic appeal, promote urban agriculture and create opportunities for community engagement. However, their implementation requires careful consideration of factors such as structural integrity, irrigation and maintenance. Despite these challenges, green walls offer a sustainable and innovative approach to enhancing the quality of urban life while mitigating the negative impacts of urban development on the environment. The current emphasis highlights the significance of green walls as an effective tool in sustainable urban planning, underscoring the need for further research and their integration into urban planning practices.

Revolutionizing Textile Manufacturing: Sustainable and Profitable Production by Integrating Industry 4.0, Activity-Based Costing, and the Theory of Constraints

The textile industry, a cornerstone of daily life and a highly globalized sector, faces significant environmental challenges due to its high water and energy consumption and extensive chemical usage. This study proposes a comprehensive green production planning and control model integrating Industry 4.0 concepts, activity-based costing (ABC), and the theory of constraints (TOC). The model utilizes mathematical programming to optimize product mix, maximize profitability, and minimize environmental impact. It leverages real-time sensing technologies and ERP systems to facilitate waste recovery, reduce carbon emissions, and achieve energy savings. Various carbon emission cost models, including continuous and discontinuous tax functions, are explored to balance corporate profitability with environmental sustainability. The findings demonstrate the model’s potential in optimizing resource utilization, reducing the environmental footprint, and enhancing profitability.

Recent and recurrent autopolyploidization fueled diversification of snow carp on the Tibetan Plateau

Abstract Whole-genome duplication (WGD), or polyploidization, is a major contributor to biodiversity. However, the establishment and survival of WGDs are often considered to be stochastic, since elucidating the processes of WGD establishment remains challenging. In the current study, we explored the processes leading to polyploidy establishment in snow carp (Cyprinidae: Schizothoracinae), a predominant component of the ichthyofauna of the Tibetan Plateau and its surrounding areas. Using large-scale genomic data from isoform sequencing, we analyzed ohnolog genealogies and divergence in hundreds to thousands of gene families across major snow carp lineages. Our findings demonstrated that independent autopolyploidization subsequent to speciation was prevalent, while autopolyploidization followed by speciation also occurred in the diversification of snow carp. This was further supported by matrilineal divergence and drainage evolution evidence. Contrary to the long-standing hypothesis that ancient polyploidization preceded the diversification of snow carp, we determined that polyploidy in extant snow carp was established by recurrent autopolyploidization events during the Pleistocene. These findings indicate that the diversification of extant snow carp resembles a coordinated duet: first, the uplift of the Tibetan Plateau orchestrated the biogeography and diversification of their diploid progenitors; then, the extensive Pliocene-Pleistocene climate changes acted as relay runners, further fueling diversification through recurrent autopolyploidization. Overall, this study not only reveals a hitherto unrecognized recent WGD lineage in vertebrates but also advances current understanding of WGD processes, emphasizing that WGD establishment is a non-stochastic event, emerging from numerous adaptations to environmental challenges and recurring throughout evolutionary history rather than merely in plants.

Using Spatial Literacy for Disaster Management in Coastal Communities of Small Island Developing States (SIDS): A Case Study from Lavongai, Papua New Guinea

This study investigates the use of participatory geographic information systems (PGIS) for hazard assessment in small island developing states (SIDS), with a focus on spatial literacy and community-based disaster management. By partnering with the Lavongai community on Papua New Guinea, this research aimed to empower community members through skill development in geodata processing. The program leveraged local knowledge and the global positioning system to create participatory maps, enhancing both community capacity and researcher data quality. Workshops and focus group discussions (FGDs) were conducted to assess the community’s understanding of spatial concepts related to disaster risks. The core objective was a preliminary assessment of the community’s social and economic vulnerability to coastal disasters, using household data and GIS analysis. The results showed varied vulnerability levels within the community, highlighting the need for targeted disaster mitigation training and nature-based solutions. High-resolution satellite imagery and a simple bathtub model simulated sea level rise, identifying land-uses at risk. The program concluded with a community presentation of thematic maps, fostering collaboration and transparency. Future projects will address environmental challenges identified by local leaders and prioritize skill development, social data collection, and water resource mapping.

Exploring the potential of contemporary deep learning methods in purifying polluted information

Abstract Accurately predicting chaotic dynamical systems is a crucial task in various fields, and recent advancements have leveraged deep learning for this purpose. However, in the era of big data, the inevitable challenge of data contamination caused by invalid information from other interfering systems becomes increasingly prominent and complicates accurate predictions. Although contemporary deep learning methods have shown their potential, very few studies have focused on developing algorithms specifically designed to address the problem posed by such data contamination. Thus, exploring the ability of contemporary deep learning methods to purify polluted information fills an important gap in the current body of research. This study explores the performance and stability of several modern deep learning techniques for predicting chaotic systems using datasets polluted by invalid information. Our findings reveal that while most of the state-of-the-art deep learning methods exhibit reduced and unstable predictive performance owing to such contamination, the dynamical system deep learning (DSDL) method stands out, remaining unaffected by any interference. This breakthrough illustrates DSDL's unique ability to purify invalid data and uncover the inherent rules of chaotic systems. As we move forward, DSDL paves the way for a more reliable and interpretable model, ensuring that we can confidently predict chaotic systems with precision even in the most challenging environments.

Research Progress on Environmental Corrosion Resistance of Thermal Barrier Coatings: A Review

With the development of marine science and technology, marine construction is entering a new period of modern ocean development and utilization. The scale of marine development is expanding constantly. The lifespan of aircraft engines faces new challenges in marine environments. This paper reviews recent progress in the development of high-temperature coatings for aero-engines designed to resist marine atmospheric corrosion, with a focus on corrosion mechanisms, detection technologies, current research on marine atmospheric corrosion, standards for evaluating coating resistance, and novel advancements in coating materials.

Advancing Global Climate and Biodiversity Goals Through Regenerative Tourism

Tourism has a particular responsibility to contribute to climate and biodiversity goals because of its intense use of long-range transport and its strong dependence on natural capital as an asset. Tourism is a major contributor to the global economy, but also to greenhouse gas emissions. The severe impacts of the SARS-CoV-2 pandemic on the tourism sector triggered a search for enhanced resilience, replacing the past paradigm of “boosterism”, and the dominant paradigm of “sustainable tourism”. Sustainable tourism is no longer sufficient, and a shift towards a new paradigm of regenerative tourism is needed to address the environmental and societal challenges faced by the tourism industry. Here, the evidence pointing at the rise of regenerative tourism as a new paradigm is reviewed, the differential goals of regenerative, relative to sustainable tourism, are defined and actions along five domains of action are identified that can help tourism destinations embrace the transition toward the regenerative tourism paradigm. Regenerative tourism seeks to enhance the natural, cultural and social capital of destinations while creating net positive benefits for people and the planet. It emphasizes collaboration with local communities and an ambitious and holistic approach to sustainability, going beyond reducing negative impacts to creating positive ones. Regenerative tourism aligns the industry, the Paris Agreement, and the Convention on Biological Diversity, while advancing the delivery of the Sustainable Development Goals. The transition to regenerative tourism requires investments in technology and innovation, transparent collaboration, and a holistic focus on well-being for both people and the planet.

Blind Recognition of Frame Synchronization Based on Deep Learning.

In this paper, a deep-learning-based frame synchronization blind recognition algorithm is proposed to improve the detection performance in non-cooperative communication systems. Current methods face challenges in accurately detecting frames under high bit error rates (BER). Our approach begins with flat-top interpolation of binary data and converting it into a series of grayscale images, enabling the application of image processing techniques. By incorporating a scaling factor, we generate RGB images. Based on the matching radius, frame length, and frame synchronization code, RGB images with distinct stripe features are classified as positive samples for each category, while the remaining images are classified as negative samples. Finally, the neural network is trained on these sets to classify test data effectively. Simulation results demonstrate that the proposed algorithm achieves a 100% probability in frame recognition when BER is below 0.2. Even with a BER of 0.25, the recognition probability remains above 90%, which exhibits a performance improvement of over 60% compared with traditional algorithms. This work addresses the shortcomings of existing methods under high error conditions, and the idea of converting sequences into RGB images also provides a reliable solution for frame synchronization in challenging communication environments.

Evaluation of Urbanization Influences on Beach Sediment Contamination with Heavy Metals Along the Littoral Zone of Alexandria City, Egypt

The western coastal area of Alexandria City, Egypt, faces significant environmental challenges due to heavy metal (HM) contamination in beach sediments, driven by intensive urbanization, tourism, commercial harbors, and industrial activities. Therefore, this study focuses on geochemically assessing HM levels in sediment samples from 28 sites and employed various descriptive and multivariate statistical approaches, pollution indices, and sediment quality guidelines (SQGs) to identify pollution hotspots, define contamination grades, and assess the quality of beach sediments. The average concentrations of Cd, Co, Cr, Cu, Pb, and Zn were 25.7, 30, 2.2, 7.5, 2.9, and 8.0 times, respectively, compared to the geochemical background (carbonate sedimentary rocks). et al.-Hanuvil Beach, relatively elevated contents of these metals were recorded. In addition, samples showed Zn levels higher than the corresponding probable effect concentration (PEC) and effect range medium (ERM) values, suggesting adverse impacts on biota. The principal component (PC) analysis revealed the anthropogenic origin of Cd, Co, and Pb in PC1, the mixed origin of Cr, Cu, Mn, and Zn in PC2, and the natural source of Fe in PC3. According to the applied single pollution indices, HM contamination grades were ranked in ascending order of Mn < Fe < Cr < Cd < Cu < Pb < Zn < Co. In conclusion, the HMs (Cu, Zn, Cd, Co, Pb, and Cr) in the study area are anthropogenic, attributed mainly to untreated discharge of municipal and industrial wastewater and solid wastes, atmospheric deposition of air pollutants, and tourism activities.

CO2 capture enhancement by metal oxides impregnated coal fly ash: a breakthrough adsorption study.

Coal fired power plants are significant contributors to CO2 emissions and produce solid waste in the form of coal fly ash, posing severe environmental challenges. This study explores the application of dry-impregnated coal fly ash for CO2 capture from gas stream. The modification of coal fly ash was achieved using alkaline earth metal oxides, specifically CaO and MgO, to alter its physical and chemical properties. Characterization techniques like X-ray fluorescence (XRF), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and BET (Brunauer-Emmett-Teller) analysis were employed for physio-chemical changes in the adsorbent. Breakthrough experiments were conducted using a laboratory-scale fixed packed-bed reactor to assess the influence of temperature and gas flow rate on CO2 adsorption. Among the synthesized sorbents, calcium oxide-impregnated ash showed the highest CO2 uptake capacity, achieving 9.41mg/g at 30°C and a flow rate of 20 L/hr under atmospheric pressure. Isotherm modeling indicated a heterogeneous adsorbent surface, with the data best fitting the Sips isotherm model. Furthermore, the adsorption data conformed well to the Yoon-Nelson and Thomas kinetic models, affirming their relevance in characterizing the adsorption process under varying conditions. This research emphasizes the potential of coal fly ash-an abundant, cost-free material-as an effective CO2 adsorbent, contributing to both CO2 mitigation and landfill waste reduction.

Characterization, fractionation and untapped potential of phosphate-amended sewage sludge biochar in soil-plant systems

Sewage sludge, a byproduct of wastewater treatment, poses serious environmental and health risks due to its content of organic contaminants, heavy metals, and pathogenic microorganisms. With the growing global production of municipal wastewater, finding effective methods for managing and disposing of sewage sludge has become increasingly urgent. Traditional methods such as land disposal, dumping, and incineration have limitations and environmental drawbacks. However, recent advancements have shown promise in the valorization of sewage sludge, particularly through pyrolysis, which converts it into biochar for use in soil amendment and pollutant mitigation. This study aims to characterize and fractionate phosphate-amended sewage sludge biochar produced at 300 °C, 400 °C, and 500 °C, and to evaluate its potential use in soil-plant systems. It examines nutrient bioavailability in soil after the addition of this biochar and its effects on plant growth. The pyrolysis process resulted in biochar with high alkalinity (7.2–11.1), ash content ranging from 56.9% to 87.3%, and significant phosphorus retention, with phosphorus concentrations increasing with pyrolysis temperature (5.35%–9.38%). Phosphorus fractionation showed a shift toward more stable fractions particularly at 500 °C. Soil incubation experiments indicated increased phosphorus availability with HCl-extractable P showing a high extraction efficiency of up to 94.95%. In plant growth experiments, the amended biochar significantly enhanced growth, with corn showing an increase of up to 28.8% and wheat showing an increase of up to 86% compared to the control in the first four weeks after emergence. These findings indicate that phosphate-amended sewage sludge biochar enhances nutrient availability and supports plant growth, providing a sustainable solution for sewage sludge management, contributing to soil improvement and carbon sequestration, thereby addressing global environmental challenges.

EarthCODE – ESA’s Earth Science Collaborative Open Development Environment

Abstract. Earth Observations (EO) have become crucial for advancing climate and Earth System research, enabling significant scientific discoveries. Advanced EO missions, such as ESA’s Earth Explorers and the EU's Copernicus Programme, provide vast data volumes and continuous and global observations with cutting-edge technology, a vital resource for understanding processes and interactions within Earth's sub-systems, offering critical evidence of climate change impacts on society and ecosystems. Open access to such data products has been instrumental in facilitating global scientific collaboration and innovation. Reproducibility in Earth Science is essential for validating discoveries, enabling the scientific community to trust and build upon each other’s work. Open data, coupled with open-source software, is key to achieving this reproducibility, ensuring transparency, and facilitating peer review. Addressing scientific challenges requires collaborative efforts supported by fit-for-purpose technology to enable new insights and ensuring they are FAIR (findable, accessible, interoperable, and reusable), trustable and up to date, supporting long-term climate studies and action-driven science. Several initiatives within ESA’s Earth Observation Programme are fostering FAIR and Open Science. EarthCODE is one such initiative, focusing on implementing ESA’s vision of EO Open Science and Innovation by adopting FAIR and Open principles in Earth Science activities funded by ESA’s FutureEO Programme. EarthCODE leverages existing European platform solutions for effective cloud-based analyses of EO data and higher-level geospatial products. It aims to ensure the persistence of end-to-end scientific workflows and provide means for managing open research data, including data, code, and documentation. EarthCODE aims to make Earth Science research more reproducible, transparent, and collaborative, driving progress in understanding and addressing global environmental challenges.

Urban Heat Island Differentiation and Influencing Factors: A Local Climate Zone Perspective

With the acceleration of urbanization, the urban heat island (UHI) effect has become a major environmental challenge, severely affecting the quality of life of residents and the ecological environment. Quantitative analysis of the factors influencing urban heat island intensity (UHII) is crucial for precise urban planning. Although extensive research has investigated the causes of UHI effects and their spatial variability, most studies focus on macro-scale analyses, overlooking the spatial heterogeneity of thermal characteristics within local climate zones (LCZs) under rapid urbanization. To address this gap, this study took the central urban area of Chengdu, constructing a LCZ map using multisource remote sensing data. Moran’s Index was employed to analyze the spatial clustering effects of UHI across different LCZs. By constructing Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) models, the study further explored the influencing factors within these climate zones. The results showed that: (1) Chengdu’s built and natural environments had comparable proportions, with the scattered building zone comprising the highest proportion at 22.12% in the built environment, and the low vegetation zone accounting for 21.8% in the natural environment. The UHII values in this study ranged from 10.2 °C to −1.58 °C, based on specific measurement conditions. Since UHII varied with meteorological conditions, time, seasons, and the selection of rural reference points, these values represented dynamic results during the study period and were not constant. (2) Chengdu’s urban spatial morphology and UHII exhibited significant spatial heterogeneity, with a global Moran’s I index of 0.734, indicating a high degree of spatial correlation. The highest local Moran’s I value was found in the proportion of impervious surfaces (0.776), while the lowest is in the floor area ratio (0.176). (3) The GWR model demonstrated greater explanatory power compared to the OLS model, with a fit of 0.827. The impact of spatial morphological factors on UHII varied significantly across different environments, with the most substantial difference observed in the sky view factor, which has a standard deviation of 13.639. The findings provide precise recommendations for ecological spatial planning, aiming to mitigate the UHI effect and enhance the quality of life for urban residents.

Comparison of Urban Environment Factors for Solar-Powered Vehicles

Abstract. Urban areas face significant environmental challenges, including high CO2 emissions largely attributed to the transportation sector. Introducing solar-powered vehicles (SPVs) presents a promising solution to reduce urban carbon footprints. However, in dense urban settings, the effectiveness of SPVs is often compromised by shading from buildings, which significantly diminishes solar power generation. This study explores the impact of shading on urban roads, aiming to identify roads with substantial shadow variations that affect solar energy harvesting. Using Geographic Information Systems (GIS) and hillshade analysis, the study examines how nearby buildings and road orientation influence shadow variability. The findings reveal considerable variability in shadow throughout the year, with significant fluctuations during transitional months like February, August, October, and November. These results highlight the importance of considering shadow patterns in urban planning and vehicle routing to optimise the use of solar energy in urban settings.