Search Results (11,724)

(1) Background: Urban villages in Guangzhou are high-density communities with challenging outdoor thermal environments, which significantly impact residents’ thermal comfort. Addressing these issues is crucial for improving the quality of life and mitigating heat stress in such environments. (2) Methods: This study utilized a validated ENVI-met microclimate model to explore the synergistic cooling effects of roof greening and facade greening. Three greening types—total greening, facade greening, and roof greening—were analyzed for their impacts on air temperature, mean radiant temperature, and physiologically equivalent temperature (PET) at a pedestrian height of 1.5 m under varying green coverage scenarios. (3) Results: The findings showed that total greening exhibited the greatest cooling potential, especially under high coverage (≥50%), reducing PET by approximately 2.5 °C, from 53.5 °C to 51.0 °C, during midday, and shifting the heat stress level from “extreme heat stress” to “strong heat stress”. Facade greening reduced PET by about 1.5 °C, while roof greening had a limited effect, reducing PET by 1.0 °C. Furthermore, under coverage exceeding 75%, total greening achieved maximum reductions of 3.0 °C in mean radiant temperature and 1.2 °C in air temperature. (4) Conclusions: This study provides scientific evidence supporting total greening as the most effective strategy for mitigating heat stress and improving thermal comfort in high-density urban villages, offering practical insights for optimizing green infrastructure. Full article

The transition to electric vehicles (EVs) is hindered by the insufficient development of charging infrastructure (CI) networks, particularly in urban areas. The existing literature highlights significant advancements in highway CI modeling, yet urban-specific models remain underdeveloped, due to the complexity of diverse driver behaviors and evolving environmental factors. To address this gap, this study investigates the influence of urban sprawl on future urban CI demand. Using a vector field analysis methodology, we first define the urban environment to capture its heterogeneity. A conceptual framework is then developed to analyze how changes in urban environments affect critical factors influencing CI demand. The results demonstrate that urban sprawl significantly impacts key variables shaping CI demand, including population distribution, transportation patterns, and land use. To quantify these impacts, geospatial metrics are derived from highly cited literature and integrated into the analysis, offering a novel approach to incorporating sprawl effects into CI planning. This study concludes that urban sprawl has a profound influence on future CI demand and emphasizes the importance of monitoring geospatial metrics over time. The proposed methodology provides a theoretical framework that enables stakeholders to anticipate changes in CI demand, thereby facilitating more effective infrastructure planning to accommodate urban sprawl. Full article

Unmanned aerial vehicle (UAV) swarms have shown substantial potential to enhance operational efficiency and reduce strike costs, presenting extensive applications in modern urban warfare. However, achieving effective strike performance in complex urban environments remains challenging, particularly when considering three-dimensional obstacles and threat zones simultaneously, which can significantly degrade strike effectiveness. To address this challenge, this paper proposes a target strike strategy using the Electric Eel Foraging Optimization (EEFO) algorithm, a heuristic optimization method designed to ensure precise strikes in complex environments. The problem is formulated with specific constraints, modeling each UAV as an electric eel with random initial positions and velocities. This algorithm simulates the interaction, resting, hunting, and migrating behaviors of electric eels during their foraging process. During the interaction phase, UAVs engage in global exploration through communication and environmental sensing. The resting phase allows UAVs to temporarily hold their positions, preventing premature convergence to local optima. In the hunting phase, the swarm identifies and pursues optimal paths, while in the migration phase the UAVs transition to target areas, avoiding threats and obstacles while seeking safer routes. The algorithm enhances overall optimization capabilities by sharing information among surrounding individuals and promoting group cooperation, effectively planning flight paths and avoiding obstacles for precise strikes. The MATLAB(R2024b) simulation platform is used to compare the performance of five optimization algorithms—SO, SCA, WOA, MFO, and HHO—against the proposed Electric Eel Foraging Optimization (EEFO) algorithm for UAV swarm target strike missions. The experimental results demonstrate that in a sparse undefended environment, EEFO outperforms the other algorithms in terms of trajectory planning efficiency, stability, and minimal trajectory costs while also exhibiting faster convergence rates. In densely defended environments, EEFO not only achieves the optimal target strike trajectory but also shows superior performance in terms of convergence trends and trajectory cost reduction, along with the highest mission completion rate. These results highlight the effectiveness of EEFO in both sparse and complex defended scenarios, making it a promising approach for UAV swarm operations in dynamic urban environments. Full article

Increasing urbanisation is occurring in Australia’s major cities and in almost every country in the world. This creates a challenge for the urban water sector, which not only needs to provide traditional water services (i.e., wastewater, domestic water) for a rapidly growing population, but also to service potential additional demands to contribute to enhanced amenity, and to do so in the context of climate change. This paper is focused on stormwater management controls for the develop of new greenfield urban sites in the three major east coast Australian cities—Melbourne, Sydney and Brisbane. While stormwater management in all three cities is focused on the protection of community values of the waterways, including environment (ecology), amenity and recreation, the scale or type of the waterways considered is considerably different—Melbourne has adopted a regional waterway strategy, while the Sydney and Brisbane approach is more localised. Pollution load reduction targets (TSS, TP, TN and litter) from new urban areas have been enforced in all three cities for many years, although there is concern that these targets primarily aimed at protecting the values of downstream bays (e.g., Port Phillip Bay, Sydney Harbour and Morton Bay) will not necessarily protect the values of the contributing waterways. However, targets to control stormwater volumes entering waterways are proving to be considerably more difficult to both develop and implement. These targets are typically expressed as volumes of stormwater to be harvested and/or infiltrated for every additional hectare of directly connected impervious (DCI) surface created as a result of urban development. The three cities have approached the setting of stormwater flow targets somewhat differently, as is apparent from the details provided in the paper. Additionally, we argue that there is a need for the development of new targets related to the reuse of stormwater and its integration with wastewater and domestic water management. Full article

The resilient city plays an increasingly important role in coping with the challenges raised by economic, social, and environmental risks. In this review, we examine approximately 27,094 papers published in the Web of Science Core Collection (WOSCC) and perform extensive bibliometric and scientometric analyses to identify the research themes, evolutionary history, and potential research trends in the state of the art in resilient city studies. Seven main resilient city research themes are identified, with significant differences persisting across regions. Specifically, the research on resilient cities in Europe, Asia, Africa, and North America reveals clear regional characteristics in macro development planning and strategies, technological methods, urban economic growth, urban water resource protection, and so on. The analysis also reveals the collaborative networks among different countries and regions in the study of resilient cities. The evolutionary history of resilient city research shows that it has gradually evolved from a single research field into a multidisciplinary field and further formed a unique discipline. Moreover, the urban ecological environment, urban economic development, urban sprawl, and urban mobility have become key research hot spots and trends in resilient city research. This study provides a systematic and data-driven analytical demonstration of resilient city research, which provides empirical support for policy formulation and practice. Full article

Healthy watershed environments are essential for socioeconomic sustainability. The long-term monitoring and assessment of watershed ecological environments provide a timely and accurate understanding of ecosystem dynamics, informing industry and policy adjustments. This study focused on the upper-middle Fen River Basin (UMFRB) in eastern China’s Loess Plateau and analyzed the long-term spatial and temporal characteristics of eco-quality from 2000 to 2023 by calculating a remote sensing ecological index (RSEI) via the Google Earth Engine (GEE) platform. In addition, this study also explored the trends and future consistency of the RSEI, as well as the impacts of natural and anthropogenic factors on RSEI spatial variations. The findings revealed that (1) the average RSEI value increased from 0.51 to 0.57 over the past 24 years, reflecting an overall improvement in eco-quality, although urban centers in the Taiyuan Basin exhibited localized degradation. (2) The Hurst index value was 0.468, indicating anti-consistency, with most regions showing trends of future decline or exhibiting stochastic fluctuations. (3) Elevation, temperature, precipitation, slope, and land use intensity are significantly correlated with ecological quality. Natural factors dominate in densely vegetated regions, whereas socioeconomic factors dominate in populated plains. These results provide valuable guidance for formulating targeted ecological restoration measures, protection policies, and engineering solutions. Full article

Groundwater contamination with sub-lethal dissolved contaminants poses significant health risks globally, especially in rural India, where access to safe drinking water remains a critical challenge. This study explores the hydrogeochemical characterization and associated health risks of groundwater from shallow aquifers in the Marginal Ganga Alluvial Plain (MGAP) of northern India. The groundwater chemistry is dominated by Ca-Mg-CO₃ and Ca-Mg-Cl types, where there is dominance of silicate weathering and the ion-exchange processes are responsible for this solute composition in the groundwater. All the ionic species are within the permissible limits of the World Health Organization, except fluoride (F⁻) and nitrate (NO₃⁻). Geochemical analysis using bivariate relationships and saturation plots attributes the occurrence of F⁻ to geogenic sources, primarily the chemical weathering of granite-granodiorite, while NO₃⁻ contaminants are linked to anthropogenic inputs, such as nitrogen-rich fertilizers, in the absence of a large-scale urban environment. Multivariate statistical analyses, including hierarchical cluster analysis and factor analysis, confirm the predominance of geogenic controls, with NO₃⁻-enriched samples derived from anthropogenic factors. The spatial distribution and probability predictions of F⁻ and NO₃⁻ were generated using a non-parametric co-kriging technique approach, aiding in the delineation of contamination hotspots. The integration of the USEPA human health risk assessment methodology with the urbanization index has revealed critical findings, identifying approximately 23% of the study area as being at high risk. This comprehensive approach, which synergizes geospatial analysis and statistical methods, proves to be highly effective in delineating priority zones for health intervention. The results highlight the pressing need for targeted mitigation measures and the implementation of sustainable groundwater management practices at regional, national, and global levels. Full article

The growing complexity of urban environments and high-rise facilities presents new challenges for disaster preparedness and response, particularly when managing multiple hazards. Traditional systems that focus on single hazards are insufficient for complex facilities that are prone to cascading disasters. This study develops an open disaster information platform that integrates Building Information Modeling (BIM), Geographic Information Systems (GIS), and real-time monitoring tools to enhance situational awareness and multi-hazard response coordination. The platform combines data from the internet of things’ sensors, structural models, and environmental systems to provide responders and facility managers with real-time access to critical information. Simulation tests and real-world deployments have confirmed the platform’s ability to optimize evacuation routes, improve response times, and minimize risks during emergencies. Integration with GIS further supports risk mapping and post-disaster recovery efforts. This study proposes a scalable disaster management framework that promotes real-time data sharing and collaboration across stakeholders. Aligned with the trend toward smart, resilient cities, the platform provides practical solutions for improving disaster preparedness and response in high-rise and complex urban environments. Full article

The expected number of drone operations in the coming decades, together with the fact that most of them will take place in very-low-level airspace, will lead to a density of drone flights much greater than that of conventional manned aviation. In this context, the number of conflicts (i.e., 4D convergence of drone trajectories below the safe separation minima) will be much more frequent than in manned aviation and, therefore, conventional air traffic management methods or even the specific proposed mechanisms for drone traffic management are unlikely to be able to solve them safely. This paper considers a set of simulated drone trajectories in a high-density urban environment to analyze the applicability of machine learning regression and classification techniques to detect conflicts among such trajectory times in advance of their occurrence in order to provide new methods to manage the expected drone traffic density safely and efficiently. This would not be possible with current drone traffic management solutions. The obtained results suggest that the Random Forest, Artificial Neural Networks and Logistic Regression algorithms could detect nearly all near-collisions up to 10 s before they occur, and the first two algorithms could also detect a significant number of near-collisions more than 60 s earlier. Full article

Polycyclic aromatic hydrocarbons (PAH) are key components of particulate matter (PM) in terms of the toxicological risk of polluted air. Although commonly monitored in ambient air, PAHs are also present in indoor air, making the measurement of indoor PAH content essential for understanding the health risks associated with indoor environments. This study presents findings from measurements conducted across 37 households where children resided, using 7-day sampling campaigns to collect PM₁. The health risk assessment methods are detailed herein, along with a source apportionment analysis to explore the associations with potential sources and differences from ambient air concentrations. Additionally, the incremental lifetime cancer risk (ILCR) was calculated to assess long-term health risks associated with exposure to indoor PAHs. The results showed consistently higher PAH concentrations in outdoor environments (from 0.079 ng m⁻³ for dibenzo(a,h)anthracene to 1.638 ng m⁻³ for benzo(b)fluoranthene) compared to indoor environments (from 0.029 ng m⁻³ for dibenzo(a,h)anthracene to 0.772 ng m⁻³ for indeno(1,2,3-cd)pyrene), suggesting significant transfer of PAHs from outdoor to indoor air. The source apportionment analysis indicated that traffic emissions, fossil fuel combustion, and residential heating were the predominant sources of PAHs in both environments, with the concentration of indoor PAHs largely influenced by gasoline and liquid fossil fuel combustion. The diagnostic ratios supported these findings, with coal and biomass as additional sources impacting outdoor PAH levels. The ILCR analysis revealed that the exposure levels for both children (indoors at 1.78 × 10⁻⁵, outdoors at 1.92 × 10⁻⁶) and adults (indoors at 1.15 × 10⁻⁵, outdoors at 1.24 × 10⁻⁶) remained below the U.S. EPA’s risk threshold, suggesting limited carcinogenic risk under typical household conditions in this study. These findings emphasize the complexity of PAH distribution between indoor and outdoor environments, illustrating how urban outdoor pollution sources contribute to indoor air quality and highlighting the relevance of effective air quality management strategies. Full article

With the advancement of electric vehicles, their low energy recovery efficiency has become the main obstacle to development. This study focuses on the problem of braking energy loss in electric vehicles during urban road driving and proposes an improved fuzzy control strategy to optimize the energy management of electric vehicles. The exploration first introduces fuzzy control logic to adjust and optimize the energy recovery system of electric vehicles and then introduces a sparrow search algorithm to optimize the adjustment parameters. Finally, using MATLAB R2022a simulation software environment, a comparative analysis is conducted on two driving cycles: urban dynamometer driving schedule and New York City conditions. Simulation results show that the improved fuzzy control strategy can recover 906.41 kJ of energy under urban driving cycle conditions, and the energy recovery rate reaches 49.00%, while the ADVISOR strategy is 507.47 kJ and 27.13%, respectively. The energy recovery rate of the research method is 21.87% higher than that of the comparison method. Improved energy recovery rate of 80.68%. In the driving cycle with New York City, the improved strategy recovered 294.45 kJ of energy, and the energy recovery rate was 48.54%. Compared with the ADVISOR strategy, the energy recovery rate increased by 100.20%, and the energy recovery rate increased by about 110.77%. The research results indicate that the improved fuzzy control strategy is significantly superior to the ADVISOR control strategy, effectively improving energy recovery efficiency and battery charge state maintenance ability under an urban dynamometer driving schedule, achieving more efficient energy management. Full article

With the acceleration of urbanization, many traditional buildings have been dismantled and built indiscriminately, resulting in a uniform urban landscape. The problem of urban microclimate has been aggravated, and the renovation of historic districts, especially including the renewal of microclimate, has become an important component of sustainable urban renewal. The old commercial street in Huili Ancient City is used as an example in this paper. Through literature research, we note that previous studies have mainly examined the renewal of historic districts from the perspective of the old city environment, while most of the traditional neighborhood renewal designs have neglected the wind and heat environments. Combining the limitations of previous studies and field research, we summarized the current problems of the neighborhood and developed specific renovation strategies for the identified problems in terms of historical and cultural heritage, the relationship between the old and the new, and the layout of green building technologies. In addition, the green building strategy was used to optimize the microclimate environment of the neighborhood, and the wind and heat environment simulation was conducted to evaluate the modeling of the renovated neighborhood. The results show that the outdoor wind environment is better in winter than in summer, and the natural ventilation environment of the neighborhood could be optimized by optimizing the building layout to form an alleyway wind. The indoor wind–heat environment simulation was carried out with the Green Pottery Experience Hall as an example, and the indoor and outdoor air circulation and ventilation were good, and the comfort of the human thermal environment was high. This paper explores the updating strategy of the historic district in the transition zone between old and new and the wind–heat environment simulation and evaluation of green building renovation, which provides a new perspective for the related renovation research and the optimization strategy of the microclimate environment in the district. Full article

The promotion of sustainability and resilience within urban environments is widely recognized as an essential approach to educating urban communities through innovative strategies and tools. This paper presents a process for integrating stakeholders into urban growth simulation, thereby enhancing sustainable decision-making. Currently, most urban growth models fail to incorporate the perspectives of diverse stakeholders, leading to reduced equitable participation in the decision-making process. To achieve long-term sustainability, it is imperative to include the input and viewpoints of stakeholders. This study follows a four-step approach: identifying relevant stakeholders, developing the framework, evaluating its effectiveness, and documenting lessons learned. The framework involves key steps, including initial participatory modeling, analysis of development pressures and suitability with stakeholders, and technical urban growth modeling. A unique combination of modeling tools and an innovative approach was employed, incorporating the default FUTURES (GRASS-GIS) model alongside the CA-Markov Chain, Agent-Based Modeling (ABM) (NetLogo), the Cellular-Automata-based Python model, and MOLUSCE-QGIS. This integrated approach facilitates the inclusion of stakeholder-based knowledge into conventional urban growth modeling, providing novel local lessons in science, technology, and innovation initiatives. Validation was conducted through both technical and stakeholder mechanisms, confirming the effectiveness of the proposed framework. Full article

As Urban Air Mobility (UAM) moves toward implementation, managing high-density, high-volume flights in urban airspaces becomes increasingly critical. In such environments, the design of vertiport airspace structures plays a key role in determining how many UAVs can operate safely and efficiently within a specific airspace. Existing studies have not fully explored the complex interdependencies between airspace structure parameters and fleet operation capacity, particularly regarding how various structural components and their configurations affect UAV fleet performance. This paper addresses these gaps by proposing a multi-layered funnel-shaped airspace structure for vertiports, along with an adjustable parameter model to assess factors affecting landing capacity. The proposed design includes the assembly layer, upper layer, lower layer, and approach point, forming the basis for fleet operations, divided into three phases: arrival, approach, and landing. By modeling fleet operations with various constraints and time-based algorithms, simulations have been conducted to analyze the impact of changing airspace structure parametric dimensions on UAV fleet operation capacity. The results reveal that fleet capacity is closely influenced by two limitations: the distance traveled in each phase and the availability of holding points at each layer. These findings provide valuable insights and contribute to future airspace design efforts for UAM vertiports. Full article

In order to improve the network performance of multi-unmanned ground vehicle (UGV) systems in urban environments, this article proposes a novel online autonomous motion-control method for the relay UAV. The problem is solved by jointly considering unknown RF channel parameters, unknown multi-agent mobility, the impact of the environments on channel characteristics, and the unavailable angle-of-arrival (AoA) information of the received signal, making the solution of the problem more practical and comprehensive. The method mainly consists of two parts: wireless channel parameter estimation and optimal relay position search. Considering that in practical applications, the radio frequency (RF) channel parameters in complex urban environments are difficult to obtain in advance and are constantly changing, an estimation algorithm based on Gaussian process learning is proposed for online evaluation of the wireless channel parameters near the current position of the UAV; for the optimal relay position search problem, in order to improve the real-time performance of the method, a line search algorithm and a general gradient-based algorithm are proposed, which are used for point-to-point communication and multi-node communication scenarios, respectively, reducing the two-dimensional search to a one-dimensional search, and the stability proof and convergence conditions of the algorithm are given. Comparative experiments and simulation results under different scenarios show that the proposed motion-control method can drive the UAV to reach or track the optimal relay position and improve the network performance, while demonstrating that it is beneficial to consider the impact of the environments on the channel characteristics. Full article